From 258e3b7443285fc2a2b86073a7d4064cc926ad44 Mon Sep 17 00:00:00 2001 From: jefferis Date: Fri, 26 Jan 2024 23:41:12 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20natverse?= =?UTF-8?q?/fafbseg@0fde1deb0672ba870d4d860a3b2da7017d4404ba=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- articles/FAFB-FlyWire.html | 8 +- pkgdown.yml | 2 +- reference/flytable-queries.html | 28 +- reference/flytable_login.html | 10 +- reference/flywire_cave_client.html | 2 +- reference/flywire_ids.html | 11271 +++++++++++++-------------- reference/flywire_partners.html | 22 +- reference/flywire_timestamp.html | 2 +- search.json | 2 +- 9 files changed, 5684 insertions(+), 5663 deletions(-) diff --git a/articles/FAFB-FlyWire.html b/articles/FAFB-FlyWire.html index dc479d1a..4ded120f 100644 --- a/articles/FAFB-FlyWire.html +++ b/articles/FAFB-FlyWire.html @@ -163,8 +163,8 @@

Basic point mappingjet.colors<-colorRampPalette(c('navy','cyan','yellow','red')) nclear3d(); spheres3d(xyzmatrix(sxyz.in), col=jet.colors(10)[cut(delta, breaks = 10)], rad=2000) - - + +

Round trip error @@ -208,10 +208,10 @@

Mapping anythingnclear3d() plot3d(AV4b1.fw, col='red', lwd=3)

-
+
 wire3d(av4.fwm[[1]], col='grey', alpha=.2)

 

-
+
diff --git a/pkgdown.yml b/pkgdown.yml index c1d44173..a0ce05c9 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -8,7 +8,7 @@ articles: installing-cloudvolume-meshparty: installing-cloudvolume-meshparty.html mesh-to-mesh: mesh-to-mesh.html fafbseg-catmaid-legacy-info: fafbseg-catmaid-legacy-info.html -last_built: 2024-01-18T03:13Z +last_built: 2024-01-26T23:03Z urls: reference: https://natverse.org/fafbseg/reference article: https://natverse.org/fafbseg/articles diff --git a/reference/flytable-queries.html b/reference/flytable-queries.html index 048e4699..39addb86 100644 --- a/reference/flytable-queries.html +++ b/reference/flytable-queries.html @@ -192,7 +192,7 @@

Examples#> 1 H8BckTnXRL2PaVuLDcRPMA 2022-05-12 16:58:07 2021-12-17 13:36:17 apple #> 2 SrBW3vFLRxafKRYHoPrGQQ 2022-05-12 16:58:08 2021-12-17 13:36:17 banana #> 3 F1h-TZKpTcWiHujZ2xnF8Q 2022-05-12 16:58:08 2021-12-17 13:36:17 clementine -#> 4 KZrMyoJKTeS_o9Pgynu7YQ 2024-01-18 00:42:52 2022-05-11 00:34:27 kiwi +#> 4 KZrMyoJKTeS_o9Pgynu7YQ 2024-01-26 22:25:57 2022-05-11 00:34:27 kiwi #> 5 cI4fqlOUQK2A1jZKZvFpdg 2022-05-12 16:58:09 2022-05-11 00:39:59 kiwi #> 6 AOUcHHZ0RTC-auONZURx4g 2022-05-12 16:58:10 2022-05-11 00:40:57 kiwi #> 7 dxs7n1NpRM-hWoGJxPZpKA 2022-05-12 16:58:10 2022-05-11 00:41:17 kiwi @@ -663,11 +663,17 @@

Examples#> 472 N8lByhadRym68iMWyMKo1Q 2024-01-18 00:19:09 2024-01-18 00:19:09 kiwi #> 473 c8RQlG0-TDiGeY2SQk0i0w 2024-01-18 00:25:17 2024-01-18 00:25:17 kiwi #> 474 JSQglb37SzquHiXR2viZsg 2024-01-18 00:42:53 2024-01-18 00:42:53 kiwi +#> 475 DurLLmkrTWKPhIeRj1Whdg 2024-01-25 23:15:13 2024-01-25 23:15:13 kiwi +#> 476 QgYVjyKfQliBP7-KYHkIjA 2024-01-26 09:22:02 2024-01-26 09:22:02 kiwi +#> 477 CfCJdGFzSZ2iDpgX9thCCg 2024-01-26 09:33:24 2024-01-26 09:33:24 kiwi +#> 478 Eqf5rqZeQT2che-bBoICug 2024-01-26 21:56:28 2024-01-26 21:56:28 kiwi +#> 479 V45C6dt-TQyd01F03xeWbw 2024-01-26 22:00:24 2024-01-26 22:00:24 kiwi +#> 480 FHVFcBL3TSOm1E_9q2oPtA 2024-01-26 22:25:58 2024-01-26 22:25:58 kiwi #> nid person last_modified date_nominute #> 1 1 Alice 2022-05-12 16:58:07 2022-01-06 #> 2 2 Bob 2022-05-12 16:58:08 2022-01-03 #> 3 3 Clara 2022-05-12 16:58:08 2021-08-05 -#> 4 6 Frederick the Great 2024-01-18 00:42:52 <NA> +#> 4 6 Frederick the Great 2024-01-26 22:25:57 <NA> #> 5 6 Frederick the Great 2022-05-12 16:58:09 <NA> #> 6 6 Frederick the Great 2022-05-12 16:58:10 <NA> #> 7 6 Frederick the Great 2022-05-12 16:58:10 <NA> @@ -1138,6 +1144,12 @@

Examples#> 472 6 Frederick the Great 2024-01-18 00:19:09 <NA> #> 473 6 Frederick the Great 2024-01-18 00:25:17 <NA> #> 474 6 Frederick the Great 2024-01-18 00:42:53 <NA> +#> 475 6 Frederick the Great 2024-01-25 23:15:13 <NA> +#> 476 6 Frederick the Great 2024-01-26 09:22:02 <NA> +#> 477 6 Frederick the Great 2024-01-26 09:33:24 <NA> +#> 478 6 Frederick the Great 2024-01-26 21:56:28 <NA> +#> 479 6 Frederick the Great 2024-01-26 22:00:24 <NA> +#> 480 6 Frederick the Great 2024-01-26 22:25:58 <NA> #> date_wminute user camid #> 1 2022-01-12 09:30:00 8adf4f5dd661449fa6cc1f5a0b1815c0@auth.local 100001 #> 2 2022-01-03 07:56:00 c7efb8019da54923a9b04d4a74f0fde8@auth.local 100002 @@ -1613,6 +1625,12 @@

Examples#> 472 <NA> NaN 100657 #> 473 <NA> NaN 100658 #> 474 <NA> NaN 100659 +#> 475 <NA> NaN 100660 +#> 476 <NA> NaN 100661 +#> 477 <NA> NaN 100662 +#> 478 <NA> NaN 100663 +#> 479 <NA> NaN 100664 +#> 480 <NA> NaN 100665 # } # \donttest{ flytable_query("SELECT person, fruit_name FROM testfruit WHERE person!='Bob'") @@ -2090,6 +2108,12 @@

Examples#> 471 Frederick the Great kiwi #> 472 Frederick the Great kiwi #> 473 Frederick the Great kiwi +#> 474 Frederick the Great kiwi +#> 475 Frederick the Great kiwi +#> 476 Frederick the Great kiwi +#> 477 Frederick the Great kiwi +#> 478 Frederick the Great kiwi +#> 479 Frederick the Great kiwi # } if (FALSE) { flytable_query(paste("SELECT root_id, supervoxel_id FROM info limit 5")) diff --git a/reference/flytable_login.html b/reference/flytable_login.html index ded37170..f0e13ed8 100644 --- a/reference/flytable_login.html +++ b/reference/flytable_login.html @@ -343,9 +343,8 @@

Examples#> 88 test 5 testfruit #> 89 fanc_maleVNC_matching 123 Table3_nblast95_20 #> 90 fanc_maleVNC_matching 123 Table3_nblast95_30 -#> 91 manc_maleCNS 123 Table1_nblast95_60_backup -#> 92 manc_maleCNS 123 Table1_nblast95_60_backup2 -#> 93 manc_maleCNS 123 Table1_nblast95_60 +#> 91 manc_maleCNS 123 Table1_nblast95_60 +#> 92 DB Comparison 1 Table1 #> _id #> 1 96g5 #> 2 DHtk @@ -437,9 +436,8 @@

Examples#> 88 0000 #> 89 7ve8 #> 90 EAqv -#> 91 24bm -#> 92 qea1 -#> 93 kg2f +#> 91 kg2f +#> 92 0000 # } # \donttest{ flytable_columns("info") diff --git a/reference/flywire_cave_client.html b/reference/flywire_cave_client.html index 6b4a80be..29115f4c 100644 --- a/reference/flywire_cave_client.html +++ b/reference/flywire_cave_client.html @@ -181,7 +181,7 @@

Examples#> [1] "fly_v31" #> #> $last_updated -#> [1] "2024-01-18T01:00:00.187468" +#> [1] "2024-01-26T23:00:00.312383" #> #> $annotation_table #> [1] "nuclei_v1" diff --git a/reference/flywire_ids.html b/reference/flywire_ids.html index 5ef98b2e..f89ef1e5 100644 --- a/reference/flywire_ids.html +++ b/reference/flywire_ids.html @@ -192,5642 +192,5641 @@

Examplesflywire_ids("super:sensory", integer64=TRUE) #> integer64 #> [1] 720575940622360358 720575940615856345 720575940614548253 -#> [4] 720575940605699104 720575940619893072 720575940613684370 -#> [7] 720575940627135306 720575940637321847 720575940628673474 -#> [10] 720575940610460514 720575940616239873 720575940633280107 -#> [13] 720575940638509952 720575940617969961 720575940630644281 -#> [16] 720575940606871497 720575940622242253 720575940626522910 -#> [19] 720575940633816986 720575940625653029 720575940630047019 -#> [22] 720575940632644639 720575940638836285 720575940636052927 -#> [25] 720575940628677114 720575940638513752 720575940617041728 -#> [28] 720575940616999069 720575940628953210 720575940608376132 -#> [31] 720575940645728132 720575940628599296 720575940623087859 -#> [34] 720575940617534676 720575940613118610 720575940612096370 -#> [37] 720575940617433142 720575940618512624 720575940613191591 -#> [40] 720575940611720362 720575940623793741 720575940631630893 -#> [43] 720575940613664874 720575940610185221 720575940621659563 -#> [46] 720575940613794114 720575940627214891 720575940642599328 -#> [49] 720575940618293883 720575940633367377 720575940626811023 -#> [52] 720575940623274935 720575940619024774 720575940619219627 -#> [55] 720575940616039197 720575940609924306 720575940622745834 -#> [58] 720575940627944464 720575940622082518 720575940629007230 -#> [61] 720575940617986345 720575940646372228 720575940635969399 -#> [64] 720575940614844994 720575940646785924 720575940621831804 -#> [67] 720575940631875298 720575940625293514 720575940620847086 -#> [70] 720575940632913461 720575940617986089 720575940609792206 -#> [73] 720575940623476661 720575940633059381 720575940630271862 -#> [76] 720575940617665950 720575940617987113 720575940605264305 -#> [79] 720575940614921501 720575940621654298 720575940638389437 -#> [82] 720575940619385583 720575940627000582 720575940627606375 -#> [85] 720575940614570793 720575940635767524 720575940624853600 -#> [88] 720575940623503945 720575940625148174 720575940619419757 -#> [91] 720575940613637782 720575940628264721 720575940618912427 -#> [94] 720575940603820716 720575940622972820 720575940629693302 -#> [97] 720575940631925096 720575940627677258 720575940614634786 -#> [100] 720575940627431080 720575940620634537 720575940635916942 -#> [103] 720575940629906060 720575940622700749 720575940620602236 -#> [106] 720575940620644446 720575940628961644 720575940613914774 -#> [109] 720575940651079158 720575940621100117 720575940611377893 -#> [112] 720575940624673936 720575940626580361 720575940627264262 -#> [115] 720575940616783361 720575940613942301 720575940613941533 -#> [118] 720575940633670904 720575940628519482 720575940626674707 -#> [121] 720575940627707753 720575940613942045 720575940604931249 -#> [124] 720575940613942557 720575940624716746 720575940615119400 -#> [127] 720575940620981274 720575940626553993 720575940628945516 -#> [130] 720575940626107800 720575940630763390 720575940622211845 -#> [133] 720575940627271230 720575940623638967 720575940626614405 -#> [136] 720575940626726730 720575940607960843 720575940624555838 -#> [139] 720575940622084681 720575940614919709 720575940622112726 -#> [142] 720575940613449202 720575940647994164 720575940615696490 -#> [145] 720575940608053852 720575940616653030 720575940626581525 -#> [148] 720575940622375389 720575940628061968 720575940622625097 -#> [151] 720575940631842119 720575940629275898 720575940625657928 -#> [154] 720575940632625837 720575940619169985 720575940630282297 -#> [157] 720575940629918762 720575940619725844 720575940614711638 -#> [160] 720575940629728732 720575940618728395 720575940626256992 -#> [163] 720575940614676447 720575940619075073 720575940653829537 -#> [166] 720575940620714921 720575940606915849 720575940632063396 -#> [169] 720575940622581651 720575940616439697 720575940637494837 -#> [172] 720575940658539905 720575940631450451 720575940628597291 -#> [175] 720575940621740493 720575940611353457 720575940605742002 -#> [178] 720575940629270487 720575940618960555 720575940629154810 -#> [181] 720575940632014284 720575940623265258 720575940626356306 -#> [184] 720575940634781620 720575940649429625 720575940622604749 -#> [187] 720575940618574983 720575940620028788 720575940647978804 -#> [190] 720575940617695572 720575940623065013 720575940632224031 -#> [193] 720575940629965788 720575940623209703 720575940619210375 -#> [196] 720575940620673776 720575940628660224 720575940623090412 -#> [199] 720575940630284306 720575940636767856 720575940626737685 -#> [202] 720575940613875222 720575940614610630 720575940652581878 -#> [205] 720575940628800277 720575940630037291 720575940628601344 -#> [208] 720575940618531544 720575940621309534 720575940633259360 -#> [211] 720575940611990738 720575940631217782 720575940628564350 -#> [214] 720575940635146926 720575940644512791 720575940635419237 -#> [217] 720575940611056846 720575940637013726 720575940620421153 -#> [220] 720575940618577081 720575940626779644 720575940635757936 -#> [223] 720575940646514740 720575940628290895 720575940629710444 -#> [226] 720575940612003282 720575940628431671 720575940637887872 -#> [229] 720575940626976522 720575940628429056 720575940610686162 -#> [232] 720575940622651389 720575940614155882 720575940643842340 -#> [235] 720575940642692059 720575940624030734 720575940643977070 -#> [238] 720575940607927817 720575940653295009 720575940628624956 -#> [241] 720575940642284704 720575940628976887 720575940624030478 -#> [244] 720575940619844534 720575940614236575 720575940632193055 -#> [247] 720575940643707246 720575940614926790 720575940617141789 -#> [250] 720575940616311513 720575940617511169 720575940633471839 -#> [253] 720575940628277147 720575940631240296 720575940624045155 -#> [256] 720575940645824035 720575940614212514 720575940623942119 -#> [259] 720575940646136599 720575940614102930 720575940614898037 -#> [262] 720575940611762329 720575940631960290 720575940620224677 -#> [265] 720575940634776218 720575940620675711 720575940624508341 -#> [268] 720575940625154283 720575940633509407 720575940620023024 -#> [271] 720575940615723350 720575940631510865 720575940606210220 -#> [274] 720575940626179334 720575940625733868 720575940629539269 -#> [277] 720575940610864533 720575940636093541 720575940629728988 -#> [280] 720575940627253865 720575940639427416 720575940622262593 -#> [283] 720575940628632702 720575940625337546 720575940626893834 -#> [286] 720575940630569815 720575940631345964 720575940605328230 -#> [289] 720575940625657530 720575940612674257 720575940645789988 -#> [292] 720575940623129587 720575940625821758 720575940628599595 -#> [295] 720575940630958673 720575940620574305 720575940627402852 -#> [298] 720575940625342648 720575940617067305 720575940629232492 -#> [301] 720575940628246121 720575940630511055 720575940637472053 -#> [304] 720575940619280110 720575940624689336 720575940641979277 -#> [307] 720575940624037052 720575940612455917 720575940630496975 -#> [310] 720575940620109550 720575940633353568 720575940623270945 -#> [313] 720575940641592973 720575940632624813 720575940647088004 -#> [316] 720575940623610919 720575940615221800 720575940645808931 -#> [319] 720575940614548765 720575940618903345 720575940619451233 -#> [322] 720575940619418304 720575940616546333 720575940639030094 -#> [325] 720575940643183140 720575940617989417 720575940617577797 -#> [328] 720575940639415248 720575940628285450 720575940628690423 -#> [331] 720575940627370027 720575940616256059 720575940621398366 -#> [334] 720575940620055905 720575940645751844 720575940622987007 -#> [337] 720575940650751873 720575940607459849 720575940618539422 -#> [340] 720575940622891923 720575940622972167 720575940619559956 -#> [343] 720575940609577518 720575940633817405 720575940653542817 -#> [346] 720575940626865289 720575940638339773 720575940606869513 -#> [349] 720575940634078303 720575940608227541 720575940639004032 -#> [352] 720575940638773693 720575940639080526 720575940642968776 -#> [355] 720575940640282869 720575940649394553 720575940608253891 -#> [358] 720575940639022414 720575940616254016 720575940632284717 -#> [361] 720575940627996315 720575940614053149 720575940620997409 -#> [364] 720575940630662737 720575940614037533 720575940626769304 -#> [367] 720575940624146019 720575940622276791 720575940613885506 -#> [370] 720575940630664273 720575940604352689 720575940612160153 -#> [373] 720575940620133568 720575940620202111 720575940627675535 -#> [376] 720575940616322397 720575940626529448 720575940613466577 -#> [379] 720575940637400183 720575940621100117 720575940619357264 -#> [382] 720575940610519747 720575940627316303 720575940614105342 -#> [385] 720575940615659381 720575940626202237 720575940621209513 -#> [388] 720575940611844886 720575940630738171 720575940629350782 -#> [391] 720575940617645652 720575940631084684 720575940638872629 -#> [394] 720575940627817260 720575940620253311 720575940636670644 -#> [397] 720575940621668428 720575940630696901 720575940634733537 -#> [400] 720575940629343799 720575940648191609 720575940617454114 -#> [403] 720575940620705012 720575940618806101 720575940612149014 -#> [406] 720575940609586645 720575940623267559 720575940620024560 -#> [409] 720575940624853276 720575940627805096 720575940617626781 -#> [412] 720575940612140781 720575940631003723 720575940624061116 -#> [415] 720575940646094388 720575940611208818 720575940611905138 -#> [418] 720575940637728063 720575940615831947 720575940619429803 -#> [421] 720575940615809366 720575940627239848 720575940625868184 -#> [424] 720575940621897496 720575940614053405 720575940627787343 -#> [427] 720575940629338750 720575940631474316 720575940626856721 -#> [430] 720575940631413585 720575940606974219 720575940620822049 -#> [433] 720575940619430571 720575940621766680 720575940612700450 -#> [436] 720575940624849040 720575940621137833 720575940639213033 -#> [439] 720575940627144010 720575940629724411 720575940606001074 -#> [442] 720575940638165875 720575940604675430 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720575940629548649 720575940622753776 720575940614190563 +#> [16636] 720575940619502400 720575940646408302 720575940636507384 +#> [16639] 720575940606387046 720575940640152509 720575940624875015 +#> [16642] 720575940630383866 720575940618101563 720575940634602465 +#> [16645] 720575940621850971 720575940624327818 720575940632882024 +#> [16648] 720575940627249214 720575940623351116 720575940624413222 +#> [16651] 720575940621018709 720575940624058061 720575940645106632 +#> [16654] 720575940633519308 720575940624882439 720575940630981111 +#> [16657] 720575940634530530 720575940621168775 720575940621681067 +#> [16660] 720575940622415286 720575940629894416 720575940628312595 +#> [16663] 720575940629765675 720575940630703607 720575940635618400 +#> [16666] 720575940640176693 720575940629605419 720575940615513490 +#> [16669] 720575940627588953 720575940605939628 720575940631883717 +#> [16672] 720575940616516162 720575940623919373 720575940640233149 +#> [16675] 720575940625998823 720575940623912205 720575940616471967 +#> [16678] 720575940632868163 720575940610260437 720575940622261168 +#> [16681] 720575940625025533 720575940631140919 720575940643199885 +#> [16684] 720575940625440073 720575940618958337 720575940620740432 +#> [16687] 720575940608122498 720575940645933079 720575940616514370 +#> [16690] 720575940642439899 720575940622172854 720575940624196095 +#> [16693] 720575940621685595 720575940634577633 720575940625473772 +#> [16696] 720575940646459502 720575940632393258 720575940627900056 +#> [16699] 720575940618897492 720575940628592917 720575940625009917 +#> [16702] 720575940635005347 720575940619556416 720575940618851585 +#> [16705] 720575940620410161 720575940636922735 720575940624931509 +#> [16708] 720575940616580930 720575940626927664 720575940621720747 +#> [16711] 720575940635514775 720575940621235732 720575940612286670 +#> [16714] 720575940631912389 720575940605998508 720575940632853816 +#> [16717] 720575940616408223 720575940624088319 720575940623062817 +#> [16720] 720575940645877271 720575940636658100 720575940631278807 +#> [16723] 720575940635753312 720575940613087962 720575940623072801 +#> [16726] 720575940624089855 720575940622635135 720575940623051297 +#> [16729] 720575940630865602 720575940618050363 720575940613061781 +#> [16732] 720575940619195677 720575940622872816 720575940637538958 +#> [16735] 720575940640690339 720575940632930188 720575940618353369 +#> [16738] 720575940616193386 720575940624032013 720575940647842356 +#> [16741] 720575940621742189 720575940625686759 720575940622139056 +#> [16744] 720575940626014759 720575940624368934 720575940623559804 +#> [16747] 720575940613397221 720575940629252170 720575940640206781 +#> [16750] 720575940612334178 720575940633017415 720575940632242450 +#> [16753] 720575940650042233 720575940621286053 720575940616835014 +#> [16756] 720575940639018468 720575940624153599 720575940624370628 +#> [16759] 720575940625026557 720575940625327368 720575940630097307 +#> [16762] 720575940628134410 720575940632243218 720575940625855420 +#> [16765] 720575940628240906 720575940635771287 720575940628337541 +#> [16768] 720575940620789720 720575940628620565 720575940621297032 +#> [16771] 720575940632714823 720575940651015289 720575940614392547 +#> [16774] 720575940625302280 720575940627455234 720575940637002351 +#> [16777] 720575940610358723 720575940606830950 720575940620936784 +#> [16780] 720575940633988179 720575940640315701 720575940627496537 +#> [16783] 720575940627135674 720575940615659682 720575940619473221 +#> [16786] 720575940624978357 720575940637181815 720575940626892581 +#> [16789] 720575940641300096 720575940623611094 720575940621142036 +#> [16792] 720575940634840345 720575940644545952 720575940618989725 +#> [16795] 720575940633918803 720575940639368937 720575940637804206 +#> [16798] 720575940616946886 720575940631913047 720575940614717736 +#> [16801] 720575940630630782 720575940625954744 720575940626854842 +#> [16804] 720575940620222034 720575940628520767 720575940618193881 +#> [16807] 720575940627050954 720575940633161799 720575940633588900 +#> [16810] 720575940620810443 720575940613601765 720575940618412125 +#> [16813] 720575940621667462 720575940609928459 720575940624028003 +#> [16816] 720575940633341521 720575940621016912 720575940637640293 +#> [16819] 720575940621017680 720575940612990101 720575940617341883 +#> [16822] 720575940627225274 720575940621668742 720575940632467498 +#> [16825] 720575940626408525 720575940628409989 720575940614736365 +#> [16828] 720575940637641573 720575940611082564 720575940633343825 +#> [16831] 720575940631998149 720575940631388887 720575940633561887 +#> [16834] 720575940621696448 720575940631484119 720575940624172824 +#> [16837] 720575940613619353 720575940613619865 720575940630688762 +#> [16840] 720575940628266066 720575940627223482 720575940624602406 +#> [16843] 720575940627789401 720575940620030518 720575940626038460 +#> [16846] 720575940613621145 720575940631176960 720575940639155433 +#> [16849] 720575940615153071 720575940625714446 720575940625114877 +#> [16852] 720575940625115133 720575940623458124 720575940632520040 +#> [16855] 720575940608368050 720575940640218702 720575940618591920 +#> [16858] 720575940628232467 720575940640885336 720575940618396628 +#> [16861] 720575940614704424 720575940618323641 720575940613166042 +#> [16864] 720575940629425994 720575940622011969 720575940631815161 +#> [16867] 720575940642656219 720575940632001733 720575940628816917 +#> [16870] 720575940633049912 720575940616030358 720575940622464383 +#> [16873] 720575940627258810 720575940615244851 720575940615571966 +#> [16876] 720575940628429445 720575940627807065 720575940630824130 +#> [16879] 720575940631717996 720575940617947275 720575940622484852 +#> [16882] 720575940622616670 720575940630981623 720575940616252010 +#> [16885] 720575940624455050 720575940634427603 720575940628737679 +#> [16888] 720575940629158140 720575940639185242 720575940631205888 +#> [16891] 720575940628100489 720575940625093813 720575940621324564 +#> [16894] 720575940620069430 720575940631186176 720575940609726731 +#> [16897] 720575940615115059 720575940631281463 720575940639062106 +#> [16900] 720575940615592354 720575940632649795 720575940640655779 +#> [16903] 720575940615303475 720575940623589708 720575940631771735 +#> [16906] 720575940623201404 # note that side is defined by soma position (not arbour side) flywire_ids("class:MBON_R", integer64=TRUE) diff --git a/reference/flywire_partners.html b/reference/flywire_partners.html index cfc4ac9c..fe1de922 100644 --- a/reference/flywire_partners.html +++ b/reference/flywire_partners.html @@ -283,12 +283,12 @@

Examples#> 5 1236914 33.748131 0 81631042385459399 81631042385454876 #> 6 1236915 6.670522 0 81631042385462087 81631042385470852 #> post_id pre_id -#> 1 720575940631693610 720575940621039145 +#> 1 720575940623607372 720575940621039145 #> 2 720575940632985261 720575940621039145 #> 3 720575940589754844 720575940621039145 -#> 4 720575940631693610 720575940621039145 -#> 5 720575940631693610 720575940621039145 -#> 6 720575940631693610 720575940621039145 +#> 4 720575940623607372 720575940621039145 +#> 5 720575940623607372 720575940621039145 +#> 6 720575940623607372 720575940621039145 class(pp$post_id) #> [1] "integer64" # } @@ -303,8 +303,8 @@

Examples#> # A tibble: 1,215 × 3 #> post_id weight n #> <chr> <int> <int> -#> 1 720575940631693610 891 1 -#> 2 720575940618522433 172 1 +#> 1 720575940623607372 891 1 +#> 2 720575940630149419 172 1 #> 3 720575940622838154 62 1 #> 4 720575940631200327 62 1 #> 5 720575940631914700 34 1 @@ -323,7 +323,7 @@

Examples#> # A tibble: 620 × 3 #> pre_id weight n #> <chr> <int> <int> -#> 1 720575940631693610 891 1 +#> 1 720575940623607372 891 1 #> 2 720575940613380914 90 1 #> 3 720575940631842360 88 1 #> 4 720575940621000831 77 1 @@ -343,8 +343,8 @@

Examples#> # A tibble: 1,215 × 3 #> post_id weight n #> <chr> <int> <int> -#> 1 720575940631693610 891 1 -#> 2 720575940618522433 172 1 +#> 1 720575940623607372 891 1 +#> 2 720575940630149419 172 1 #> 3 720575940622838154 62 1 #> 4 720575940631200327 62 1 #> 5 720575940631914700 34 1 @@ -359,14 +359,14 @@

Examplesflywire_partner_summary(flywire_xyz2id(cbind(155682, 58180, 3215), rawcoords = TRUE)) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist -#> Fetching supervoxel ids for id: 720575940631693610 +#> Fetching supervoxel ids for id: 720575940623607372 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids #> # A tibble: 1,214 × 3 #> post_id weight n #> <chr> <int> <int> -#> 1 720575940618522433 172 1 +#> 1 720575940630149419 172 1 #> 2 720575940622838154 62 1 #> 3 720575940631200327 62 1 #> 4 720575940631914700 34 1 diff --git a/reference/flywire_timestamp.html b/reference/flywire_timestamp.html index 076f4163..7b852f43 100644 --- a/reference/flywire_timestamp.html +++ b/reference/flywire_timestamp.html @@ -141,7 +141,7 @@

Examples # nb this will return the current time *in UTC* regardless of your timezone flywire_timestamp(timestamp="now") -#> [1] "2024-01-18 03:40:39 UTC" +#> [1] "2024-01-26 23:36:51 UTC" # } if (FALSE) { # same but gives a warning diff --git a/search.json b/search.json index 9683392e..c78cf617 100644 --- a/search.json +++ b/search.json @@ -1 +1 @@ -[{"path":"https://natverse.org/fafbseg/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://natverse.org/fafbseg/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. 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Definitions","title":"GNU General Public License","text":"“License” refers version 3 GNU General Public License. “Copyright” also means copyright-like laws apply kinds works, semiconductor masks. “Program” refers copyrightable work licensed License. licensee addressed “”. “Licensees” “recipients” may individuals organizations. “modify” work means copy adapt part work fashion requiring copyright permission, making exact copy. resulting work called “modified version” earlier work work “based ” earlier work. “covered work” means either unmodified Program work based Program. “propagate” work means anything , without permission, make directly secondarily liable infringement applicable copyright law, except executing computer modifying private copy. Propagation includes copying, distribution (without modification), making available public, countries activities well. “convey” work means kind propagation enables parties make receive copies. 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Source Code","title":"GNU General Public License","text":"“source code” work means preferred form work making modifications . “Object code” means non-source form work. “Standard Interface” means interface either official standard defined recognized standards body, , case interfaces specified particular programming language, one widely used among developers working language. “System Libraries” executable work include anything, work whole, () included normal form packaging Major Component, part Major Component, (b) serves enable use work Major Component, implement Standard Interface implementation available public source code form. “Major Component”, context, means major essential component (kernel, window system, ) specific operating system () executable work runs, compiler used produce work, object code interpreter used run . “Corresponding Source” work object code form means source code needed generate, install, (executable work) run object code modify work, including scripts control activities. 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Protecting Users’ Legal Rights From Anti-Circumvention Law","title":"GNU General Public License","text":"covered work shall deemed part effective technological measure applicable law fulfilling obligations article 11 WIPO copyright treaty adopted 20 December 1996, similar laws prohibiting restricting circumvention measures. convey covered work, waive legal power forbid circumvention technological measures extent circumvention effected exercising rights License respect covered work, disclaim intention limit operation modification work means enforcing, work’s users, third parties’ legal rights forbid circumvention technological measures.","code":""},{"path":"https://natverse.org/fafbseg/LICENSE.html","id":"id_4-conveying-verbatim-copies","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"4. Conveying Verbatim Copies","title":"GNU General Public License","text":"may convey verbatim copies Program’s source code receive , medium, provided conspicuously appropriately publish copy appropriate copyright notice; keep intact notices stating License non-permissive terms added accord section 7 apply code; keep intact notices absence warranty; give recipients copy License along Program. may charge price price copy convey, may offer support warranty protection fee.","code":""},{"path":"https://natverse.org/fafbseg/LICENSE.html","id":"id_5-conveying-modified-source-versions","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"5. 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Use with the GNU Affero General Public License","title":"GNU General Public License","text":"Notwithstanding provision License, permission link combine covered work work licensed version 3 GNU Affero General Public License single combined work, convey resulting work. terms License continue apply part covered work, special requirements GNU Affero General Public License, section 13, concerning interaction network apply combination .","code":""},{"path":"https://natverse.org/fafbseg/LICENSE.html","id":"id_14-revised-versions-of-this-license","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"14. Revised Versions of this License","title":"GNU General Public License","text":"Free Software Foundation may publish revised /new versions GNU General Public License time time. new versions similar spirit present version, may differ detail address new problems concerns. version given distinguishing version number. Program specifies certain numbered version GNU General Public License “later version” applies , option following terms conditions either numbered version later version published Free Software Foundation. Program specify version number GNU General Public License, may choose version ever published Free Software Foundation. Program specifies proxy can decide future versions GNU General Public License can used, proxy’s public statement acceptance version permanently authorizes choose version Program. Later license versions may give additional different permissions. However, additional obligations imposed author copyright holder result choosing follow later version.","code":""},{"path":"https://natverse.org/fafbseg/LICENSE.html","id":"id_15-disclaimer-of-warranty","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"15. Disclaimer of Warranty","title":"GNU General Public License","text":"WARRANTY PROGRAM, EXTENT PERMITTED APPLICABLE LAW. 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Interpretation of Sections 15 and 16","title":"GNU General Public License","text":"disclaimer warranty limitation liability provided given local legal effect according terms, reviewing courts shall apply local law closely approximates absolute waiver civil liability connection Program, unless warranty assumption liability accompanies copy Program return fee. END TERMS CONDITIONS","code":""},{"path":"https://natverse.org/fafbseg/LICENSE.html","id":"how-to-apply-these-terms-to-your-new-programs","dir":"","previous_headings":"","what":"How to Apply These Terms to Your New Programs","title":"GNU General Public License","text":"develop new program, want greatest possible use public, best way achieve make free software everyone can redistribute change terms. , attach following notices program. safest attach start source file effectively state exclusion warranty; file least “copyright” line pointer full notice found. Also add information contact electronic paper mail. program terminal interaction, make output short notice like starts interactive mode: hypothetical commands show w show c show appropriate parts General Public License. course, program’s commands might different; GUI interface, use “box”. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU GPL, see . GNU General Public License permit incorporating program proprietary programs. program subroutine library, may consider useful permit linking proprietary applications library. want , use GNU Lesser General Public License instead License. first, please read .","code":" Copyright (C) 2018 Gregory Jefferis This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . fafbseg Copyright (C) 2018 Gregory Jefferis This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://natverse.org/fafbseg/SUPPORT.html","id":null,"dir":"","previous_headings":"","what":"Getting help with fafbseg","title":"Getting help with fafbseg","text":"Thanks using fafbseg. ’re sorry ’re trouble, don’t worry, ’re help! get help quickly possible, please read following:","code":""},{"path":"https://natverse.org/fafbseg/SUPPORT.html","id":"search","dir":"","previous_headings":"","what":"Search","title":"Getting help with fafbseg","text":"first thing see anyone problem : Search nat-user google group. Search GitHub issues fafbseg package. Search GitHub issues across whole natverse case problem related package. can add terms search search box top left page. solves problem, great!","code":""},{"path":"https://natverse.org/fafbseg/SUPPORT.html","id":"known-problems","dir":"","previous_headings":"","what":"Known Problems","title":"Getting help with fafbseg","text":"need help known problem: found relevant thread nat-user google group: please reply . found GitHub issue: please reply details just like (click emoji button add thumbs ) let us know ’re trouble . ’ll need GitHub login . ’re sure: ask new question nat-user google group linking found.","code":""},{"path":"https://natverse.org/fafbseg/SUPPORT.html","id":"new-problems","dir":"","previous_headings":"","what":"New Problems","title":"Getting help with fafbseg","text":"looks like new problem : just question: please ask nat-user google group. need report new bug: please file issue. ’re sure: please just ask nat-user google group! problem bug feature request, can easily return report - may able point existing report workaround.","code":""},{"path":"https://natverse.org/fafbseg/SUPPORT.html","id":"good-questions-and-bug-reports","dir":"","previous_headings":"","what":"Good Questions and Bug Reports","title":"Getting help with fafbseg","text":"specific Include code triggered problem possible, make minimal reproducible example (reprex) much easier us help can run reprex machine without data. might want use sample data nat package help, refer publicly available data online. can use reprex package help prepare reprex. Read Get help! section tidyverse site information. Thanks help!","code":""},{"path":"https://natverse.org/fafbseg/articles/FAFB-FlyWire.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"FAFB-FlyWire","text":"articles gives quick overview mapping points FAFB14 (used “walled garden” Virtual Fly Brain FlyWire.","code":"library(fafbseg) #> Run dr_fafbseg() for a status report on your installation"},{"path":"https://natverse.org/fafbseg/articles/FAFB-FlyWire.html","id":"basic-point-mapping","dir":"Articles","previous_headings":"Introduction","what":"Basic point mapping","title":"FAFB-FlyWire","text":"known points Compare displacements (nm) forward inverse mapping sample neuron. First map points stats quick histogram","code":"# identified location in FAFB14 p.fafb.nm <- cbind(477042, 284535, 90680) p.fafb.raw <- p.fafb.nm/c(4,4,40) # corresponding location in FlyWire p.flywire.raw <- cbind(118865, 71338, 2267) p.flywire.nm <- p.flywire.raw * c(4,4,40) # check displacement flywire2fafb(p.flywire.nm)-p.fafb.nm #> X Y Z #> [1,] 3 -1 0 # check what happens when you apply the inverse fafb2flywire(p.fafb.nm)-p.flywire.nm #> X Y Z #> [1,] -3 2 0 data(\"AV4b1\", package='catmaid') before=xyzmatrix(AV4b1) after=fafb2flywire(before) d=sqrt(rowSums((before-after)^2)) summary(d) #> Min. 1st Qu. Median Mean 3rd Qu. Max. #> 2.0 287.9 416.0 446.9 559.1 2113.7 hist(d, br=20, main='Displacement /µm') sample_points_in_surf <- function(x, n){ x=as.mesh3d(x) bb=boundingbox(x) mm=mapply(runif, min=bb[1,], max=bb[2,], n = n) colnames(mm)=c(\"X\",\"Y\",\"Z\") data.frame(mm, inside=pointsinside(mm,x)) } set.seed(42) sxyz=sample_points_in_surf(FAFB14.surf,25000) sxyz.in=subset(sxyz, inside) sxyz.fw=fafb2flywire(xyzmatrix(sxyz.in)) deltas=sxyz.fw-sxyz.in delta=rowSums(deltas[,c(\"X\",\"Y\")]) jet.colors<-colorRampPalette(c('navy','cyan','yellow','red')) nclear3d(); spheres3d(xyzmatrix(sxyz.in), col=jet.colors(10)[cut(delta, breaks = 10)], rad=2000)"},{"path":"https://natverse.org/fafbseg/articles/FAFB-FlyWire.html","id":"round-trip-error","dir":"Articles","previous_headings":"Introduction","what":"Round trip error","title":"FAFB-FlyWire","text":"Let’s send points back ","code":"sxyz.fafb2=flywire2fafb(sxyz.fw) deltas=sxyz.fafb2-xyzmatrix(sxyz.in) delta=rowSums(deltas[,c(\"X\",\"Y\")]) hist(delta, main = \"Round Trip Error\", xlab='delta /nm')"},{"path":"https://natverse.org/fafbseg/articles/FAFB-FlyWire.html","id":"mapping-anything","dir":"Articles","previous_headings":"","what":"Mapping anything","title":"FAFB-FlyWire","text":"map complex objects, use xform_brain() Note relevant links: Load flywire mesh plot CATMAID skeleton","code":"AV4b1.fw=xform_brain(AV4b1, sample='FAFB14', reference = 'FlyWire') # find the main branch point of a neuron, a good place to point to mainbranch <- function(x, ...) { if(is.neuronlist(x)) return(nlapply(x, mainbranch, ...)) sx=nat::simplify_neuron(x, ...) xyzmatrix(sx)[sx$BranchPoints,] } choose_segmentation(\"flywire\") open_fafb_ngl(mainbranch(AV4b1.fw), coords.only = TRUE) #> [1] \"88371.25,40478.75,3668\" av4.fwm=read_cloudvolume_meshes('720575940618054533') nclear3d() plot3d(AV4b1.fw, col='red', lwd=3) wire3d(av4.fwm[[1]], col='grey', alpha=.2)"},{"path":"https://natverse.org/fafbseg/articles/accessing-graphene-server.html","id":"tldr","dir":"Articles","previous_headings":"","what":"tl;dr","title":"Accessing the chunked graph server","text":"set programmatic access FlyWire, use flywire_set_token() follows: follow -screen prompts.","code":"library(fafbseg) flywire_set_token()"},{"path":"https://natverse.org/fafbseg/articles/accessing-graphene-server.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Accessing the chunked graph server","text":"main goal connectomics trace (segment) branching morphology neurons 3D volume (typically based electron microscopy) identify connections (synapses) together define connectome. Neuron segmentation can either skeleton-based (centre line defining part neuronal arbour traced ) voxel-based, filled 3D structure defined labelling every voxel integer id, representing membership particular object; typically displayed 3D mesh surface. Although skeleton-based segmentation efficient manual segmentation humans, voxel-wise segmentation natural machine learning algorithms. Furthermore, generates richer representation neuron (capturing structural features) , crucially, also resolves ambiguities object identity. example two users manually trace neuron skeleton, place nodes different positions trivial computationally determine part object join tracing independent pieces together. contrast voxel-wise segmentation every xyz location image explicitly defined part specified object. voxel-wise segmentation, neuron can considered collection voxels grouped together connected components. Machine learning based algorithms try identify connected components (e.g. using flood filling networks). However machines perfect many segments wrongly connected. Hence need step humans proofread segments alters connections. connected components can readily represented vertices connections edges. human observer essentially modifies edges graph structure. Note graph representation object segmentation distinct binary tree represents neuronal morphology connection graph neurons within neural network. graph based representation segmentation also advantages synchronous editing, can major technical issue many users generate proof-read segmentation time. CATMAID web application (skeleton based tracing) approaches allowing multiple users edit neurons using shared database. implementation reduces conflicts simple expedient allowing users see ’s work real time. However explicit merge step needed conflicting annotations created (usually editing happened different database) can computationally complex. Seung Lab developed data structure system called chunked graph lets users modify segmentations (3D voxel-wise) real-time allows access earlier versions segmentation. brief overview system published medium. practice initial -segmentation generated, consisting many “supervoxels”. supervoxels, small collections perhaps tens thousands individual voxels, effectively immutable almost certain belong object. supervoxels leaves graph database representation segmented objects. use supervoxels reduces size graph database compared situation individual voxel represented. long human proof-reading based base segmentation, strategies merge proof-reading even happens asynchronously. However merging proof-reading based different base segmentations defined different underlying supervoxels still complex; similar challenge exists necessary map proof-reading based one base segmentation newer (presumably improved) base segmentation.","code":""},{"path":"https://natverse.org/fafbseg/articles/accessing-graphene-server.html","id":"goal","dir":"Articles","previous_headings":"","what":"Goal","title":"Accessing the chunked graph server","text":"One goals fafbseg package provide access different 3D segmentations FAFB dataset. Currently available segmentations include FlyWire (based 3D CNNs : U-Net) GoogleBrain (based recursive CNNs : flood-filling networks). Furthermore enable location transfer comparison CATMAID (skeleton based) manual reconstruction. order achieve one needs access 3D segmentations stored graph database Graphene/PyChunkedGraph. also provide Python tool called CloudVolume provides programmatic access graph database.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/articles/accessing-graphene-server.html","id":"simple-instructions","dir":"Articles","previous_headings":"ChunkedGraph token","what":"Simple Instructions","title":"Accessing the chunked graph server","text":"gain access Graphene/Chunkedgraph server using token granted authenticate via Google account. simplest way offer open browser, generate new token save standard location. Note invalidate previous token!","code":"library(fafbseg) flywire_set_token()"},{"path":"https://natverse.org/fafbseg/articles/accessing-graphene-server.html","id":"details","dir":"Articles","previous_headings":"ChunkedGraph token","what":"Details","title":"Accessing the chunked graph server","text":"manual steps flywire_set_token() tries automate follows Visit https://globalv1.flywire-daf.com/auth/api/v1/refresh_token, Copy token present , let’s say \"xxyyzz\" create file named cave-secret.json location ~/.cloudvolume/secrets/cave-secret.json. example, Terminal: Paste following contents Save file Now access chunked graph server","code":"mkdir -p .cloudvolume/secrets/ touch ~/.cloudvolume/secrets/cave-secret.json open ~/.cloudvolume/secrets/cave-secret.json -e { \"token\": \"xxyyzz\" }"},{"path":"https://natverse.org/fafbseg/articles/capturing-ngl-meshes.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Capturing neuroglancer meshes from a browser scene","text":"Originally fafbseg support reading objects directly neuroglancer scene URL. approach capture interactive web session. Things moved ability read meshes directly brainmaps API via read_brainmaps_meshes() using CloudVolume interface via read_cloudvolume_meshes(). However information retained reference might helpful direct mesh retrieval yet available.","code":""},{"path":"https://natverse.org/fafbseg/articles/capturing-ngl-meshes.html","id":"method","dir":"Articles","previous_headings":"","what":"Method","title":"Capturing neuroglancer meshes from a browser scene","text":"make sure one neuron displayed want parse object identifier relationships. Chrome can generate appropriate set curl download commands : Opening Chrome Developer console (View … Developer … JavaScript Console), (re)loading page interest selecting network tab selecting downloaded object right clicking choosing (Copy … Copy cURL). can either save contents clipboard text file (e.g.  all_curl.sh) just keep clipboard. can go R proceed follows","code":"library(fafbseg) # omit the first argument if you want to use the clipboard fetch_all_curl(\"all_curl.sh\", outdir=\"alldata\", regex=\"brainmaps.googleapis.com\", fixed=TRUE) meshdata=read_ng_dump(\"alldata\") library(elmr) # or whatever your CATMAID neuron skid is y=read.neuron.catmaid(23432) compare_ng_neuron(meshdata, y)"},{"path":"https://natverse.org/fafbseg/articles/fafbseg-catmaid-legacy-info.html","id":"neuroglancer-urls","dir":"Articles","previous_headings":"","what":"Neuroglancer URLs","title":"fafbseg-catmaid-legacy-info","text":"can use package generate URLs pointing defined location neuroglancer dataset. includes arbitrary locations FAFB dataset specified interactively using CATMAID URLs. example, find location referenced tweet: Zoom @dddavi whole fly brain EM dataset using public @catmaid server hosted @virtualflybrain. whole brain view synaptic detail. Click explore location within mushroom body parallel fibre system ! https://t.co/JxsBGe3RbJ @flyconnectome pic.twitter.com/NfDiXgJOPX can use approach https://flywire.ai URLs additional option transforming coordinates get closer correct location FlyWire assembly FAFB data (typically hundred nm ). See flywire2fafb() details.","code":"library(fafbseg) # First, optionally set a package option with an example neuroglancer URL for your dataset. # This URL will define the image layers that are visible. You need to use an # URL for which you have access. The package ships with a default using segmentation # fafb_v14:fafb_v14_16nm_v00c_split3xfill2 which is probably what you need. options(fafbseg.sampleurl=\"https://\") # Now open location specified by CATMAID URL u='https://fafb.catmaid.virtualflybrain.org/?pid=2&zp=131280&yp=170014.98879622458&xp=426584.81386896875&tool=navigator&sid0=2&s0=-1' open_fafb_ngl(u) # or display raw coordinates that you can paste into active Neuroglancer session open_fafb_ngl(u, coords.only = TRUE) # opens a new browser tab with_segmentation('flywire31', open_fafb_ngl(u, sample = 'FAFB14', reference = \"FlyWire\")) # writes coordinates to clipboard so that you can paste them into an existings # flywire neuroglancer browser tab with_segmentation('flywire31', clipr::write_clip( open_fafb_ngl(u, coords.only = TRUE, sample = 'FAFB14', reference = \"FlyWire\")))"},{"path":"https://natverse.org/fafbseg/articles/fafbseg-catmaid-legacy-info.html","id":"catmaid-urls","dir":"Articles","previous_headings":"","what":"CATMAID URLs","title":"fafbseg-catmaid-legacy-info","text":"can also go opposite direction convert neuroglancer location CATMAID URL. neuroglancer location can come either URL JSON scene specification obtained clicking {} icon.","code":"# round trip using the CATMAID URL we used earlier ngu = open_fafb_ngl(u, open = FALSE) # now open using elmr package - installed like so if necessary: # natmanager::install(pkgs=\"natverse/elmr\") elmr::open_fafb(ngl_decode_scene(ngu))"},{"path":"https://natverse.org/fafbseg/articles/fafbseg-catmaid-legacy-info.html","id":"shiny-application","dir":"Articles","previous_headings":"","what":"Shiny application","title":"fafbseg-catmaid-legacy-info","text":"package now includes simple Shiny application translates two URL schemes. can use online version app https://jefferislab.shinyapps.io/CATMAID-Neuroglancer-Converter/ download GitHub run locally latest version app: Currently application convert FlyWire<->FAFB coordinates, relatively simple addition using flywire2fafb().","code":"if (!require(\"shiny\")) install.packages(\"shiny\") shiny::runGitHub(\"natverse/fafbseg\", subdir = \"inst/app/\")"},{"path":"https://natverse.org/fafbseg/articles/fafbseg-catmaid-legacy-info.html","id":"analysis-of-neuroglancer-meshes","dir":"Articles","previous_headings":"","what":"Analysis of neuroglancer meshes","title":"fafbseg-catmaid-legacy-info","text":"Currently package provides functionality read neuroglancer meshes R compare meshes traced neuron objects e.g. CATMAID. need authenticate appropriate API. Alternatively see article Capturing neuroglancer meshes browser scene. can read meshes FlyWire segmentation FAFB (roughly) can read meshes Google brain segmentation FAFB (roughly)","code":"choose_segmentation(release = 'flywire31') open_fafb_ngl(c(109459, 41305, 5424)*c(4,4,40)) va6pn=read_cloudvolume_meshes(\"720575940633169983\") # compare with VFB CATMAID library(elmr) va6pn.skel=read.neurons.catmaid(\"name:VA6.*PN\") # let's take a look at those plot3d(va6pn, col='grey', lwd=0.5, type='wire') # only plot first neuron on RHS plot3d(va6pn.skel[1], lwd=3, col='red') # can also transform the FAFB14 skeleton from VFB to FlyWire coordinates va6pn.skel.fw <- xform_brain(va6pn.skel[1], reference = 'FlyWire', sample='FAFB14') nclear3d() plot3d(va6pn, col='grey', lwd=0.5, type='wire') # only plot first neuron on RHS plot3d(va6pn.skel.fw, lwd=3, col='red') choose_segmentation(release = '20190805') open_fafb_ngl(c(109459, 41305, 5424)*c(4,4,40)) va6pn=read_brainmaps_meshes(\"710435991\")"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"tldr","dir":"Articles","previous_headings":"","what":"tl;dr","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Experts disagree best method install Python associated packages. users whose principal use Python R, found following reticulate package’s default setting dedicated miniconda installation simple efficient way install Python environment R. provides access cloud-volume package powers many functions required talk flywire environment. Extension packages mesh skeletonisation also install cleanly method. Now Python installed check everything went well Caveats avoid complications, recommend starting clean R session installation. told restart R session update Python disk already running Python interpreter attached R session. taken steps tweak version Python use (e.g. via RETICULATE_PYTHON environment variable) python virtual environment R use. want use different Python can : recommend set RETICULATE_PYTHON point explicitly preferred Python. details see simple_python() help consult extended instructions .","code":"# If you don't already have the R -> python bridge package if(!requireNamespace('reticulate')) install.packages(\"reticulate\") # just the basics for python simple_python(\"basic\") # if you want to skeletonise meshes simple_python(\"full\") fafbseg::dr_fafbseg() # dr_fafbseg may tell you to get a flywire authorisation token (one time step) flywire_set_token() simple_python(\"full\", miniconda = FALSE)"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"need cloudvolume meshparty python order get flywire meshes. help article written much experience using python. experienced users, see cloud-volume install basic command info . new python, especially pip, conda, blog post can helpful understanding ’s . Bottom line conda can install python non-python software specific environment, trying keep environment functional taking different dependencies packages consideration, pip installs python packages wherever want, whatever tell install. general packages can pip install (PyPi), can also conda environment without problem cases. Since bunch non-python dependencies cloud-volume meshparty , conda looks better want.","code":""},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"install-conda","dir":"Articles","previous_headings":"","what":"Install conda","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Download miniconda install , includes conda, python, basic packages, including pip: Make sure know install (e.g. usually : /opt/miniconda3), update recent version Terminal: $ conda update conda Hit ‘y’ proceed prompted. default python /opt/miniconda3/bin/python, can check $ python","code":""},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"work-with-a-new-environment","dir":"Articles","previous_headings":"","what":"Work with a new environment","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Use conda create activate environment can install everything need: (deactivate active environment, use $ conda deactivate flywire_env) point environment can use conda install simply anything ’s available , pip also install packages environment, unless PATH variable bash.profile file tells otherwise. Check pip default: $ pip give something miniconda folder, like /opt/miniconda3/envs/flywire_env/bin/pip. However, might system python’s pip. can comment PATH variable python .bash.profile running: $ touch ~/.bash_profile; open ~/.bash_profile adding # lines PATH=\"/Library/Frameworks/Python.framework/Versions/3.7/bin:${PATH}\" export PATH. pip return right thing, thing applies python. Alternatively can always specify terminal pip want use, suboptimal (e.g. /opt/miniconda3/envs/flywire_env/bin/pip install cloud-volume).","code":"$ conda create --name flywire_env python=3.7 $ conda activate flywire_env $ conda install nomkl"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"install-cloudvolume","dir":"Articles","previous_headings":"","what":"Install cloudvolume","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Now can install cloud-volume $ pip install cloud-volume need compiler (XCode Mac) install everything. don’t XCode, either need update OSX recent version download AppStore, can get version compatible current system : https://developer.apple.com/support/xcode/ tried installing Windows, try get right compiler help Google. thread FlyWire Slack might find useful things. use cloud-volume, need get token authorisation : https://globalv1.flywire-daf.com/auth/api/v1/refresh_token, add .json file create location: ~/.cloudvolume/secrets/cave-secret.json, see help .","code":""},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"install-meshparty","dir":"Articles","previous_headings":"","what":"Install meshparty","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Install meshparty: $ pip install meshparty errored failure install dependency: pykdtree clang: error: unsupported option '-fopenmp'. issue C++ compiler version (probably), good thing ’re using conda now can : $ conda install -c conda-forge pykdtree pip installing meshparty worked fine previous command. Now meshparty cloud-volume environment, meshparty optional dependencies skeletonisation, need install: order use meshparty_skeletonisation also install PyChunkedGraph, dependency called igneous, Seung lab. Install igneous GitHub, pip install PyChunkedGraph:","code":"$ conda install -c conda-forge pyembree $ pip install caveclient $ git clone git@github.com:seung-lab/igneous.git $ cd igneous $ pip install -r requirements.txt $ python setup.py develop $ pip install PyChunkedGraph"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"working-with-r-and-python","dir":"Articles","previous_headings":"","what":"Working with R and python","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"want use packages R reticulate natverse fafbseg functions objects need package reticulate R (install.packages(\"reticulate\")) tell use python version conda environment. Run R console:usethis::edit_r_environ() add line RETICULATE_PYTHON=\"/opt/miniconda3/envs/flywire_env/bin/python\" path python conda environment. sure leave blank line end file. Restart R session, load reticulate fafbseg (necessary install/update remotes::install_github(\"jefferis/fafbseg\"). Check python version reticulate::py_config(), show path gave RETICULATE_PYTHON variable. possible RStudio session crash reticulate::py_config(). may multiple copies OpenMP runtime linked program. dangerous, since can degrade performance cause incorrect results. fix, try:","code":"$ conda uninstall numpy scikit-learn $ conda install nomkl numpy scikit-learn $ conda remove mkl mkl-service"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"the-natverse-and-flywire-meshes","dir":"Articles","previous_headings":"Working with R and python","what":"The natverse and flywire meshes","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Let’s set R look write flywire data. need access production node flywire environment (.e. passed test). Use usethis::edit_r_profile, R profile add: GJ: Don’t . Just use choose_segmentation(\"flywire\") able read meshes, skeletonise , plot FAFB:","code":"# Production flywire options(fafbseg.cloudvolume.url='graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31') # Load packages library(natverse) library(fafbseg) choose_segmentation(\"flywire\") dir.create(\"flywire_skeletons\") # Points in FAFBv14 (nm) to flywire coordinates (also nm) points = matrix(c(723086,200499,90960),ncol=3) flywire.fafb = xform_brain(points, sample='FAFB14', ref=\"FlyWire\") # Get mesh id = flywire_xyz2id(flywire.fafb) neuron_mesh = read_cloudvolume_meshes(id) # Skeletonise mesh meshparty_skeletonize(id, savedir = \"flywire_skeletons\") neuron_skel <- read.neuron.swc(sprintf(\"flywire_skeletons/%s.swc\",id)) nopen3d() plot3d(FAFB, alpha = 0.1) plot3d(neuron_skel*1000, WithNodes = F, col = \"red\", lwd = 2) wire3d(neuron_mesh[[1]], col = \"cyan\", alpha = 0.2)"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"skeletor","dir":"Articles","previous_headings":"Working with R and python","what":"Skeletor","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"may also want install skeletor, package Philipp Schlegel helps thin skeletonise meshes . can produce accurate results get using TEASAR meshparty, depend either. install, : test skeletor works flywire neurons python using: installed skeletor specified python environment described , R able :","code":"$ source activate flywire_env $ conda install nomkl $ pip3 install git+git://github.com/schlegelp/skeletor@master $ pip3 install fastremap $ pip3 install ncollpyde python from cloudvolume import CloudVolume import trimesh as tm import skeletor as sk id=720575940614134045 id=720575940634367221 vol = CloudVolume('graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31', use_https=True) m = vol.mesh.get(id, deduplicate_chunk_boundaries=False)[id] m = tm.Trimesh(m.vertices, m.faces) simp = sk.pre.simplify(m, ratio=.1) cntr = sk.pre.contract(simp, SL=10, WH0=2, iter_lim=4, epsilon=0.05, precision=1e-6, progress=False, operator='umbrella') swc = sk.skeletonize.by_vertex_clusters(cntr, sampling_dist=500, progress=False) swc = sk.post.clean_up(s = swc, mesh = simp, theta = 0.01) sk.post.radii(s = swc, mesh = simp, method='knn', n=5, aggregate='mean') print(swc) # Faster, wavefront skeletonisation m = sk.pre.fix_mesh(m, remove_disconnected=10) swc2 = sk.skeletonize.by_wavefront(m, waves=2s) print(swc2) # Skeletonise choose_segmentation(\"flywire\") nx=xform_brain(elmr::dense_core_neurons, ref=\"FlyWire\", sample=\"FAFB14\") xyz =xyzmatrix(nx) ids = unique(flywire_xyz2id(xyz[sample(1:nrow(xyz),100),])) neurons = skeletor(ids) # Plot in 3D nopen3d() plot3d(neurons) # note, in flywire space, slightly different to FAFBv14 space plot3d(nx, col=\"black\", lwd =2) # note, in flywire space"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"issues","dir":"Articles","previous_headings":"Working with R and python","what":"Issues","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"run issues, can try wiping re-initiating conda environment. can try without igneous PyChunkedGraph. may also need specify installing cloudvolume version 1.20.1. GJ: Don’t important bug fixes since cloudvolume v 1.20.1 format URLs changed example: need install specific version cloudvolume (occasionally latest version breaks things), try e.g.:","code":"$ conda remove -n flywire_env --all $ conda create --name flywire_env python=3.7 $ conda activate flywire_env $ conda install nomkl $ conda install -c conda-forge pykdtree $ pip install --upgrade --prefer-binary meshparty cloud-volume $ pip3 install git+git://github.com/schlegelp/skeletor@master $ pip3 install fastremap $ pip3 install ncollpyde pip install --upgrade --prefer-binary cloud-volume~=3.8.0"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"note","dir":"Articles","previous_headings":"","what":"Note","title":"Mesh to mesh distances","text":"R Markdown Notebook. execute code within notebook, results appear beneath code. Try executing chunk clicking Run button within chunk placing cursor inside pressing Cmd+Shift+Enter.","code":""},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"find-the-distance-between-meshes","dir":"Articles","previous_headings":"","what":"Find the distance between meshes","title":"Mesh to mesh distances","text":"two ways can immediately think addressing Find distance every vertex mesh 1 nearest neighbour mesh 2 Find (signed) distance every vertex mesh 1 surface mesh 2 Obviously ideal situation find mesh mesh distances two objects (even Euclidean distance transform voxel representation objects.) neither accessible. Option 1 probably still perfectly good option purposes since meshes quite densely sampled (.e. vertices close together).","code":""},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"setup-and-mesh-volume","dir":"Articles","previous_headings":"","what":"Setup and Mesh volume","title":"Mesh to mesh distances","text":"Let’s use example mentioned FlyWire slack. asked find volume mesh. first attempt fails need clean mesh:","code":"library(fafbseg) ## Loading required package: nat ## Loading required package: rgl ## Registered S3 method overwritten by 'nat': ## method from ## as.mesh3d.ashape3d rgl ## Some nat functions depend on a CMTK installation. See ?cmtk and README.md for details. ## ## Attaching package: 'nat' ## The following object is masked from 'package:rgl': ## ## wire3d ## The following objects are masked from 'package:base': ## ## intersect, setdiff, union ## Run dr_fafbseg() for a status report on your installation choose_segmentation(\"flywire31\") va6pn=read_cloudvolume_meshes(\"720575940633169983\") ## downloading meshes ## parsing downloaded meshes Rvcg::vcgVolume(va6pn[[1]]) va6pn.clean=Rvcg::vcgClean(va6pn[[1]], sel=0:6, iterate = T) ## removed 68 duplicate faces and 0 duplicate vertices ## removed 0 unreferenced vertices ## removed 34 Non-manifold faces ## removed 0 degenerate faces ## removed 16 Non-manifold vertices ## split 3 non-manifold vertices ## merged 0 close vertices ## removed 0 duplicate faces and 0 duplicate vertices ## removed 3 unreferenced vertices ## removed 0 Non-manifold faces ## removed 0 degenerate faces ## removed 3 Non-manifold vertices ## split 0 non-manifold vertices ## merged 0 close vertices ## removed 0 duplicate faces and 0 duplicate vertices ## removed 0 unreferenced vertices ## removed 0 Non-manifold faces ## removed 0 degenerate faces ## removed 0 Non-manifold vertices ## split 0 non-manifold vertices ## merged 0 close vertices vol=Rvcg::vcgVolume(va6pn.clean) ## Warning in Rvcg::vcgVolume(va6pn.clean): Mesh is not watertight! USE RESULT ## WITH CARE! ## Warning in Rvcg::vcgVolume(va6pn.clean): Mesh is not coherently oriented! USE ## RESULT WITH CARE! vol ## [1] 2.506317e+12 # cubic microns vol/1e9 ## [1] 2506.317"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"compare-with-neurons-skeleton-available-from-vfb-catmaid","dir":"Articles","previous_headings":"Setup and Mesh volume","what":"Compare with neuron’s skeleton available from VFB catmaid","title":"Mesh to mesh distances","text":"","code":"library(elmr) ## Loading required package: catmaid ## Loading required package: httr ## Loading required package: nat.flybrains ## Loading required package: nat.templatebrains ## Loading required package: nat.nblast fafbconn=vfbcatmaid(\"fafb\") va6pn.skel=read.neurons.catmaid(\"name:VA6.*PN\", conn=fafbconn) summary(va6pn.skel) ## root nodes segments branchpoints endpoints cable.length nTrees connectors ## 16 11222 16840 2402 1172 1231 4003108 1 2158 ## 3133 5762 19832 2974 1461 1514 4800908 1 1026 ## nsoma ## 16 1 ## 3133 1 cable.length=summary(va6pn.skel)[1,\"cable.length\"] vol/cable.length # in nm ## [1] 626092.8 vol/cable.length/1e6 # in µm ## [1] 0.6260928 A=vol/cable.length/1e6 # mean area µm2 sqrt(A/(2*pi)) # implied radius µm, seems reasonable ## [1] 0.3156672"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"option-1-vertex-to-vertex-distance","dir":"Articles","previous_headings":"","what":"Option 1: Vertex to vertex distance","title":"Mesh to mesh distances","text":"let’s try find vertex vertex distance pair neurons. happen know lateral horn local interneuron target VA6 PN. Now can use k-d tree find nearest neighbour distances efficiently. Note also use xyzmatrix function extract vertex locations - works objects natverse knows . gives us: set vertex indices closest match VA6 PN every vertex LHLN distances matching vertices can take look distribution distances like : can see actually quite lot close distances. assume excess distances <1000 nm little dip distribution related pair neurons actually synaptically connected.","code":"pv4b4=read_cloudvolume_meshes('720575940619630430') ## downloading meshes ## parsing downloaded meshes # better to make the tree from the larger object # and query using points from the smaller object nvertices(pv4b4) ## 720575940619630430 ## 101419 nvertices(va6pn) ## 720575940633169983 ## 877023 kd=nabor::knn(query = xyzmatrix(pv4b4), data=xyzmatrix(va6pn), k=1) str(kd) ## List of 2 ## $ nn.idx : int [1:101419, 1] 4041 4041 4041 4041 4041 4041 4041 4041 4041 4041 ... ## $ nn.dists: num [1:101419, 1] 30734 30613 30251 30724 30213 ... hist(kd$nn.dists, br=100) hist(kd$nn.dists, br=500, xlim=c(0,2000))"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"locations-of-closest-approach","dir":"Articles","previous_headings":"Option 1: Vertex to vertex distance","what":"Locations of closest approach","title":"Mesh to mesh distances","text":"OK. meshes actually approach . Well look locations closest distances <100 nm. many ? Still lot! location close approach neurons, multiple vertices close together. Separating distinct contact locations complex problem simply calculating vertex distances. first thing throw cases vertex target neuron match. Looks like reduce third.","code":"sum(kd$nn.dists<100) ## [1] 1508 length(unique(kd$nn.idx[kd$nn.dists<100])) ## [1] 1017"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"visualising-contacts","dir":"Articles","previous_headings":"Option 1: Vertex to vertex distance","what":"Visualising contacts","title":"Mesh to mesh distances","text":"Let’s just take quick detour see close approaches look like: Show close nodes query mesh LHLN + PN Just query mesh LHLN close contact areas red","code":"rgl::setupKnitr() nopen3d() plot3d(pv4b4, type='wire') plot3d(va6pn, col='red', type='wire') spheres3d(xyzmatrix(pv4b4)[kd$nn.dists<100,], col='green', r=500) nclear3d() plot3d(pv4b4, col=ifelse(kd$nn.dists<100, 'red', 'black')) plot3d(va6pn, col='grey') nclear3d() plot3d(pv4b4, col=ifelse(kd$nn.dists<100, 'red', 'black'), type='wire')"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"identifying-discrete-contact-zones","dir":"Articles","previous_headings":"Option 1: Vertex to vertex distance","what":"Identifying discrete contact zones","title":"Mesh to mesh distances","text":"range ways done, essentially number local minima distance field find. might also case one “patch” one neuron actually matches several patches neuron. However ’ll just try pick simpler approach example. Let’s take points threshold distance query neuron find geodesic distance (.e. distance along mesh surface) . need bit prep work , make graph representation mesh. Convert LHLN mesh representation Now can find geodesic distance selected nodes. Let’s try clustering distance matrix Close contacts different colours","code":"#' Make an igraph representation of the edge network of a mesh object #' #' @param x A \\code{mesh3d} object or an object for which an \\code{as.mesh3d} #' method is defined. As a convenience the first mesh object is extracted when #' \\code{x} is a \\code{shapelist3d} object. #' @param ... additional arguments passed to \\code{as.mesh3d} #' #' @return a \\code{igraph} object whose vertices correspond to the vertices of the #' original mesh object and whose edges have weights matching the edge lengths #' in the mesh. #' @export mesh2graph <- function(x, ...) { if(inherits(x, 'shapelist3d')) x=x[[1]] if(inherits(x, 'neuronlist')) x=x[[1]] if(!inherits(x, 'mesh3d')) x=as.mesh3d(x, ...) if(nrow(x$it)!=3) stop(\"I only work for triangulat meshes right now\") # make the edge list v1=x$it[1,] v2=x$it[2,] v3=x$it[3,] el=rbind(cbind(v1,v2), cbind(v1,v3), cbind(v2,v3)) g=igraph::graph_from_edgelist(el, directed = FALSE) # calculate lengths of each edge xyz=xyzmatrix(x) edgelengths = function(v1, v2) { deltas=xyz[v1,,drop=F]-xyz[v2,,drop=F] sqrt(rowSums(deltas^2)) } weights=c(edgelengths(v1,v2), edgelengths(v1,v3), edgelengths(v2,v3)) igraph::E(g)$weight=weights g } g=mesh2graph(pv4b4) dmat=igraph::distances(g, v=which(kd$nn.dists<100), to = which(kd$nn.dists<100)) dd=hclust(as.dist(dmat)) plot(dd, labels = F) # cut using a height relating to a separation of 3000nm groups=cutree(dd, h=3000) # sample randomises colours so that neighbouring clusters have different colours set.seed(42) groupcols=sample(rainbow(max(groups)))[groups] nclear3d() spheres3d(xyzmatrix(pv4b4)[kd$nn.dists<100,], col=groupcols, rad=200) wire3d(pv4b4[[1]], col=ifelse(kd$nn.dists<100, 'red', 'black'), type='wire')"},{"path":"https://natverse.org/fafbseg/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Gregory Jefferis. Author, maintainer. Sridhar Jagannathan. Contributor. Alexander Bates. Contributor.","code":""},{"path":"https://natverse.org/fafbseg/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Jefferis G (2024). fafbseg: Support Functions Analysis FAFB EM Segmentation. R package version 0.13.0.9000, https://github.com/natverse/fafbseg.","code":"@Manual{, title = {fafbseg: Support Functions for Analysis of FAFB EM Segmentation}, author = {Gregory Jefferis}, year = {2024}, note = {R package version 0.13.0.9000}, url = {https://github.com/natverse/fafbseg}, }"},{"path":"https://natverse.org/fafbseg/index.html","id":"fafbseg","dir":"","previous_headings":"","what":"Support Functions for Analysis of FAFB EM Segmentation","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"goal fafbseg provide support analysis segmented EM data, focussed full adult female brain (FAFB) dataset. Although support range data sources services, point principal target FlyWire automated segmentation. Legacy support also exists Google brain automatic segmentation FAFB data. fafbseg integrated NeuroAnatomy Toolbox suite (aka natverse) including elmr catmaid. fafbseg also one building block coconatfly provides unified simplified interface range Drosophila connectome datasets. actually recommend coconatfly good place start users since provides convenient access specific FlyWire data releases well powerful cross-connectome analyses requiring minimal configuration. See https://natverse.org/coconatfly/articles/getting-started.html details.","code":""},{"path":"https://natverse.org/fafbseg/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"Assuming want use production (progress) version FlyWire dataset access lower level functionality, fafbseg way go. need install package configure environment including recording authorisation token likely downloading canned data releases.","code":""},{"path":"https://natverse.org/fafbseg/index.html","id":"package-installation","dir":"","previous_headings":"Installation","what":"Package installation","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"recommend installing fafbseg GitHub using natmanager package:","code":"# install natmanager if required if (!requireNamespace(\"natmanager\")) install.packages(\"natmanager\") natmanager::install(pkgs=\"fafbseg\")"},{"path":"https://natverse.org/fafbseg/index.html","id":"flywire-setup","dir":"","previous_headings":"Installation","what":"FlyWire setup","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"Basic steps setting access FlyWire data: note time writing (Dec 2023) download_flywire_release_data() targets materialisation 783 FlyWire dataset, fetching annotations connectivity information.","code":"library(fafbseg) # record your authorisation token flywire_set_token() # install python tools required for some functionality simple_python() # fetch canned connectivity *and* cell type data download_flywire_release_data()"},{"path":"https://natverse.org/fafbseg/index.html","id":"use","dir":"","previous_headings":"","what":"Use","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"Detailed examples follow additional vignettes, first motivation, connectivity query using precomputed data.","code":"library(fafbseg) dl4df=flytable_meta('DL4.*') dl4df dl4out <- flywire_partner_summary2(dl4df, partners = 'out', threshold = 3) dl4out"},{"path":"https://natverse.org/fafbseg/index.html","id":"acknowledgements","dir":"","previous_headings":"","what":"Acknowledgements","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"fafbseg package enables access number published many pre-publication resources. hope accelerate science strongly request ensure acknowledge authors package original data sources ensure can justify free sharing code data. use proofread annotated FlyWire dataset, please co-cite: Dorkenwald et al 2023 Schlegel et al. 2023 acknowledge specific FAFB resources: FAFB dataset, Zheng et al Cell 2018 FFN1 autosegmentation, Li et al bioRxiv 2019 FlyWire autosegmentation, Dorkenwald et al Nat Meth 2022 https://flywire.ai using cleft_score metric please also cite Heinrich et al 2018 neurotransmitter prediction, Eckstein et al. 2023 bioRxiv FlyWire coordinate transforms synapse predictions make use infrastructure contributed Davi Bock, Gregory Jefferis, Philipp Schlegel Eric Perlman, supported NIH BRAIN Initiative (grant 1RF1MH120679-01); additional work including assembling ground truth data also supported Wellcome trust (203261/Z/16/Z). fabseg package , please include reference github page methods section well citation Bates et al eLife 2020 along statement: Development natverse including fafbseg package supported NIH BRAIN Initiative (grant 1RF1MH120679-01), NSF/MRC Neuronex2 (NSF 2014862/MC_EX_MR/T046279/1) core funding Medical Research Council (MC_U105188491). Thank !","code":""},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"add_celltype_info add information existing dataframe. flytable_meta fetch data.frame metadata flytable given set identifiers.","code":""},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"","code":"add_celltype_info( x, idcol = NULL, version = NULL, suffix = NULL, table = c(\"both\", \"info\", \"optic\"), ... ) flytable_meta( ids = NULL, version = NULL, table = c(\"both\", \"info\", \"optic\"), unique = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"x data.frame containing root ids neuronlist () idcol Optional character vector specifying column containing ids neurons cell type information provided. version Optional numeric CAVE version (see flywire_cave_query). special signalling value TRUE uses current default data dump returned flywire_connectome_data_version. suffix character suffix new columns (default value NULL implies suffix). table cell type information tables use (info brain, optic optic lobes ). ... additional arguments passed flytable_cell_types ids Flywire identifiers/query form understood flywire_ids unique Whether ensure rows contain unique identifiers. Default FALSE. TRUE duplicate rows returned warning.","code":""},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"data.frame extra columns","code":""},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"root ids must column called one \"pre_id\", \"post_id\", \"root_id\", \"post_pt_root_id\", \"pre_pt_root_id\". exactly one columns present must specify preferred column idcol argument.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"","code":"# \\donttest{ kcin=flywire_partner_summary(\"720575940626474889\", partners = 'in', cleft.threshold = 50) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist #> Fetching supervoxel ids for id: 720575940626474889 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids kcin #> # A tibble: 103 × 3 #> pre_id weight n #> #> 1 720575940630547909 29 1 #> 2 720575940613583001 28 1 #> 3 720575940632698797 26 1 #> 4 720575940631269175 25 1 #> 5 720575940607687260 19 1 #> 6 720575940642086389 14 1 #> 7 720575940622673703 8 1 #> 8 720575940620709681 6 1 #> 9 720575940621178206 6 1 #> 10 720575940619665023 5 1 #> # ℹ 93 more rows kcin2=add_celltype_info(kcin) kcin2 #> # A tibble: 103 × 13 #> pre_id weight n supervoxel_id side flow super_class cell_class #> #> 1 72057594063054… 29 1 807870292352… right intr… central ALPN #> 2 72057594061358… 28 1 813486739212… right intr… central MBIN #> 3 72057594063269… 26 1 803649542764… right intr… central ALPN #> 4 72057594063126… 25 1 802240106295… right intr… central ALPN #> 5 72057594060768… 19 1 802240792818… right intr… central ALPN #> 6 72057594064208… 14 1 804353917399… right intr… central ALPN #> 7 72057594062267… 8 1 816302178184… right intr… central Kenyon_Ce… #> 8 72057594062070… 6 1 813494986893… right intr… central NA #> 9 72057594062117… 6 1 812080052867… right intr… central Kenyon_Ce… #> 10 72057594061966… 5 1 814192490249… right intr… central Kenyon_Ce… #> # ℹ 93 more rows #> # ℹ 5 more variables: cell_type , top_nt , ito_lee_hemilineage , #> # hemibrain_type , fbbt_id library(dplyr) #> #> Attaching package: ‘dplyr’ #> The following objects are masked from ‘package:nat’: #> #> intersect, setdiff, union #> The following objects are masked from ‘package:stats’: #> #> filter, lag #> The following objects are masked from ‘package:base’: #> #> intersect, setdiff, setequal, union kcin2 %>% group_by(cell_type) %>% summarise(wt = sum(weight),n=n()) %>% arrange(desc(wt)) #> # A tibble: 20 × 3 #> cell_type wt n #> #> 1 KCab 144 78 #> 2 VA1d_adPN 29 1 #> 3 APL 28 1 #> 4 DM2_lPN 26 2 #> 5 VM6_adPN 26 1 #> 6 VM2_adPN 19 1 #> 7 VA4_lPN 14 1 #> 8 LHPV12a1 9 2 #> 9 PAM11 4 2 #> 10 DPM 3 1 #> 11 PAM10 3 2 #> 12 PPL202 3 1 #> 13 PAM04 2 2 #> 14 PPL105 2 2 #> 15 KCapbp-m 1 1 #> 16 MBON02 1 1 #> 17 MBON06 1 1 #> 18 MBON07 1 1 #> 19 PPL106 1 1 #> 20 NA 1 1 kcin2 %>% count(cell_class, wt = weight) #> # A tibble: 6 × 2 #> cell_class n #> #> 1 ALPN 114 #> 2 DAN 15 #> 3 Kenyon_Cell 145 #> 4 MBIN 31 #> 5 MBON 3 #> 6 NA 10 # } if (FALSE) { # read neuronlist containing \"dotprops\" for some olfactory projection neurons da2=read_l2dps('DA2') # add cell type details to that da2=add_celltype_info(da2) } # \\donttest{ flytable_meta(\"class:MBON\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940624185095 79448854932107696 left intrinsic central MBON #> 2 720575940623472716 80011942324010318 right intrinsic central MBON #> 3 720575940638526278 80715286101144676 right intrinsic central MBON #> 4 720575940629585602 81137979670302132 right intrinsic central MBON #> 5 720575940637934308 81349085835581377 right intrinsic central MBON #> 6 720575940632118343 78744342923662254 left intrinsic central MBON #> 7 720575940609959637 78603948898007978 left intrinsic central MBON #> 8 720575940638163428 78111986298788517 left intrinsic central MBON #> 9 720575940630496374 81349223341739625 right intrinsic central MBON #> 10 720575940642142861 78393323903110735 left intrinsic central MBON #> 11 720575940611344078 80223254782485510 right intrinsic central MBON #> 12 720575940634822751 81277549061520124 right intrinsic central MBON #> 13 720575940617552340 79588561627810154 right intrinsic central MBON #> 14 720575940624280328 81489685951698728 right intrinsic central MBON #> 15 720575940617567206 78180912067538056 left intrinsic central MBON #> 16 720575940643700640 80152611093049624 right intrinsic central MBON #> 17 720575940615221811 81137979670297348 right intrinsic central MBON #> 18 720575940614026193 80154466519131949 right intrinsic central MBON #> 19 720575940633209647 78463486488950059 left intrinsic central MBON #> 20 720575940623001480 80154535238527400 right intrinsic central MBON #> 21 720575940613070485 81066305390179956 right intrinsic central MBON #> 22 720575940614595218 78040449457502610 left intrinsic central MBON #> 23 720575940636992368 80785654845309410 right intrinsic central MBON #> 24 720575940621828443 79166830266640003 left intrinsic central MBON #> 25 720575940637902938 78181599128215629 left intrinsic central MBON #> 26 720575940638774606 78040449457461921 left intrinsic central MBON #> 27 720575940639697827 80224766543977933 right intrinsic central MBON #> 28 720575940626833021 78251349531485275 left intrinsic central MBON #> 29 720575940618008859 77901086224032815 left intrinsic central MBON #> 30 720575940635841143 78110818201436707 left intrinsic central MBON #> 31 720575940618249797 80082723452177136 right intrinsic central MBON #> 32 720575940629856515 77408917331762608 left intrinsic central MBON #> 33 720575940623905719 80224972702135904 right intrinsic central MBON #> 34 720575940629529722 78533992672102680 left intrinsic central MBON #> 35 720575940624659943 80011255129536552 left intrinsic central MBON #> 36 720575940624590316 79167173863853528 right intrinsic central MBON #> 37 720575940645304430 79380479052758063 left intrinsic central MBON #> 38 720575940612196850 81136880426746412 right intrinsic central MBON #> 39 720575940630767959 78251486970442209 left intrinsic central MBON #> 40 720575940640963747 76985537105536911 left intrinsic central MBON #> 41 720575940628757547 78040449457463315 left intrinsic central MBON #> 42 720575940627144069 79166692827138268 right intrinsic central MBON #> 43 720575940610647416 81137979602919932 right intrinsic central MBON #> 44 720575940622093436 81136880426744139 right intrinsic central MBON #> 45 720575940624696810 78110818201651448 left intrinsic central MBON #> 46 720575940629422086 77760348668670642 left intrinsic central MBON #> 47 720575940647328900 81137979670303492 right intrinsic central MBON #> 48 720575940650386553 78110818201681795 left intrinsic central MBON #> 49 720575940639556467 81067610926141558 right intrinsic central MBON #> 50 720575940636120986 81700242831237167 right intrinsic central MBON #> 51 720575940617749538 80786135881765925 right intrinsic central MBON #> 52 720575940617760257 81277549061455173 right intrinsic central MBON #> 53 720575940619810389 79518055445188833 right intrinsic central MBON #> 54 720575940634482783 81136605414678093 right intrinsic central MBON #> 55 720575940644615716 78182286188838645 left intrinsic central MBON #> 56 720575940626109315 81066305390093306 right intrinsic central MBON #> 57 720575940623377802 78110818201621392 left intrinsic central MBON #> 58 720575940626744921 81277549061481189 right intrinsic central MBON #> 59 720575940623464316 81136880426764424 right intrinsic central MBON #> 60 720575940622979277 79027192356412856 left intrinsic central MBON #> 61 720575940614892182 81277617781167541 right intrinsic central MBON #> 62 720575940620715224 78111917579300796 left intrinsic central MBON #> 63 720575940613090673 78324741798855874 left intrinsic central MBON #> 64 720575940621777391 81137979736901319 right intrinsic central MBON #> 65 720575940606953858 81136880426735755 right intrinsic central MBON #> 66 720575940630075703 79309972869657633 left intrinsic central MBON #> 67 720575940652390134 78603949099622269 left intrinsic central MBON #> 68 720575940632535756 79380204241413766 left intrinsic central MBON #> 69 720575940643696288 79309904216692475 left intrinsic central MBON #> 70 720575940620162718 78323023677138555 left intrinsic central MBON #> 71 720575940635063135 80082242348953693 right intrinsic central MBON #> 72 720575940616463477 77830305364995511 left intrinsic central MBON #> 73 720575940629981440 78885355625276424 left intrinsic central MBON #> 74 720575940623182847 78463211409646517 left intrinsic central MBON #> 75 720575940626315010 79943222847625326 right intrinsic central MBON #> 76 720575940632943277 80925980016963911 right intrinsic central MBON #> 77 720575940624539284 78040449457553649 left intrinsic central MBON #> 78 720575940626180878 80011530007496199 left intrinsic central MBON #> 79 720575940628783363 80434292093847745 right intrinsic central MBON #> 80 720575940643309197 79870998677653042 left intrinsic central MBON #> 81 720575940614392999 79237542540872430 left intrinsic central MBON #> 82 720575940617302365 78604086538417636 left intrinsic central MBON #> 83 720575940635651680 81277549061591572 right intrinsic central MBON #> 84 720575940624694503 79941230049538531 left intrinsic central MBON #> 85 720575940628734376 79869899232522382 right intrinsic central MBON #> 86 720575940610964946 81630904409213619 right intrinsic central MBON #> 87 720575940607155890 80433124332533007 right intrinsic central MBON #> 88 720575940623381956 80644779918075196 right intrinsic central MBON #> 89 720575940628487813 81560466945525625 right intrinsic central MBON #> 90 720575940638028607 81419592152467685 right intrinsic central MBON #> 91 720575940621164720 80222636373797362 left intrinsic central MBON #> 92 720575940623841463 78251349531447591 left intrinsic central MBON #> 93 720575940631177803 78814711734490195 left intrinsic central MBON #> 94 720575940622306625 79166761480079751 right intrinsic central MBON #> 95 720575940616398303 79729161744437991 left intrinsic central MBON #> 96 720575940623750325 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON02 glutamate putative_primary MBON02 FBbt_00111012 #> 2 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 3 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 4 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 5 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 6 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 7 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 8 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 9 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 10 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 11 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 12 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 13 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 14 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 15 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 16 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 17 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 18 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 19 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 20 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 21 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 22 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 23 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 24 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 25 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 26 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 27 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 28 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 29 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 30 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 31 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 32 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 33 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 34 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 35 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 36 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 37 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 38 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 39 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 40 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 41 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 42 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 43 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 44 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 45 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 46 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 47 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 48 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 49 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 50 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 51 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 52 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 53 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 54 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 55 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 56 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 57 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 58 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 59 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 60 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 61 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 62 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 63 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 64 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 65 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 66 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 67 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 68 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 69 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 70 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 71 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 72 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 73 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 74 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 75 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 76 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 77 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 78 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 79 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 80 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 81 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 82 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 83 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 84 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 85 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 86 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 87 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 88 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 89 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 90 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 91 MBON05 acetylcholine putative_primary MBON05 FBbt_00111004 #> 92 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 93 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 94 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 95 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 96 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 flytable_meta(\"type:MBON2%\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940611344078 80223254782485510 right intrinsic central MBON #> 2 720575940617567206 78180912067538056 left intrinsic central MBON #> 3 720575940643700640 80152611093049624 right intrinsic central MBON #> 4 720575940614595218 78040449457502610 left intrinsic central MBON #> 5 720575940618249797 80082723452177136 right intrinsic central MBON #> 6 720575940624659943 80011255129536552 left intrinsic central MBON #> 7 720575940627144069 79166692827138268 right intrinsic central MBON #> 8 720575940619810389 79518055445188833 right intrinsic central MBON #> 9 720575940623464316 81136880426764424 right intrinsic central MBON #> 10 720575940622979277 79027192356412856 left intrinsic central MBON #> 11 720575940614892182 81277617781167541 right intrinsic central MBON #> 12 720575940620715224 78111917579300796 left intrinsic central MBON #> 13 720575940613090673 78324741798855874 left intrinsic central MBON #> 14 720575940621777391 81137979736901319 right intrinsic central MBON #> 15 720575940606953858 81136880426735755 right intrinsic central MBON #> 16 720575940635063135 80082242348953693 right intrinsic central MBON #> 17 720575940616463477 77830305364995511 left intrinsic central MBON #> 18 720575940629981440 78885355625276424 left intrinsic central MBON #> 19 720575940614392999 79237542540872430 left intrinsic central MBON #> 20 720575940607155890 80433124332533007 right intrinsic central MBON #> 21 720575940631177803 78814711734490195 left intrinsic central MBON #> 22 720575940622306625 79166761480079751 right intrinsic central MBON #> 23 720575940616398303 79729161744437991 left intrinsic central MBON #> 24 720575940623750325 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 2 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 3 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 4 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 5 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 6 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 7 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 8 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 9 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 10 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 11 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 12 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 13 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 14 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 15 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 16 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 17 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 18 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 19 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 20 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 21 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 22 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 23 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 24 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 # the / introduces a regex query (small performance penalty, more flexible) flytable_meta(\"/type:MBON2[0-5]\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940611344078 80223254782485510 right intrinsic central MBON #> 2 720575940617567206 78180912067538056 left intrinsic central MBON #> 3 720575940624659943 80011255129536552 left intrinsic central MBON #> 4 720575940627144069 79166692827138268 right intrinsic central MBON #> 5 720575940619810389 79518055445188833 right intrinsic central MBON #> 6 720575940623464316 81136880426764424 right intrinsic central MBON #> 7 720575940620715224 78111917579300796 left intrinsic central MBON #> 8 720575940613090673 78324741798855874 left intrinsic central MBON #> 9 720575940621777391 81137979736901319 right intrinsic central MBON #> 10 720575940606953858 81136880426735755 right intrinsic central MBON #> 11 720575940635063135 80082242348953693 right intrinsic central MBON #> 12 720575940616463477 77830305364995511 left intrinsic central MBON #> 13 720575940631177803 78814711734490195 left intrinsic central MBON #> 14 720575940622306625 79166761480079751 right intrinsic central MBON #> 15 720575940616398303 79729161744437991 left intrinsic central MBON #> 16 720575940623750325 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 2 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 3 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 4 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 5 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 6 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 7 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 8 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 9 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 10 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 11 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 12 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 13 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 14 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 15 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 16 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 # }"},{"path":"https://natverse.org/fafbseg/reference/as.mesh3d.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a raw neuroglancer mesh into a mesh3d object — as.mesh3d.ng_raw","title":"Convert a raw neuroglancer mesh into a mesh3d object — as.mesh3d.ng_raw","text":"Convert raw neuroglancer mesh mesh3d object","code":""},{"path":"https://natverse.org/fafbseg/reference/as.mesh3d.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a raw neuroglancer mesh into a mesh3d object — as.mesh3d.ng_raw","text":"","code":"# S3 method for ng_raw as.mesh3d(x, ...) # S3 method for ng_raw_list as.mesh3d(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/as.mesh3d.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a raw neuroglancer mesh into a mesh3d object — as.mesh3d.ng_raw","text":"x ng_raw ng_raw_list object ... additional arguments passed tmesh3d","code":""},{"path":"https://natverse.org/fafbseg/reference/braincircuits_login.html","id":null,"dir":"Reference","previous_headings":"","what":"Create and log into a braincircuits account — braincircuits_register","title":"Create and log into a braincircuits account — braincircuits_register","text":"braincircuits website built Stephan Gerhard provides services FAFB flywire data. example, information predictions dense core vesicles (DCVs). functions assist registering logging braincircuits account order query API. must first log website . run braincircuits_login, call braincircuits_register. moment, function needed flywire_dcvs called hood . Therefore, beyond testing can connect braincircuits.io little reason call function directly.","code":""},{"path":"https://natverse.org/fafbseg/reference/braincircuits_login.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create and log into a braincircuits account — braincircuits_register","text":"","code":"braincircuits_register( open = TRUE, email = NULL, password = NULL, url = \"https://api.braincircuits.io\" ) braincircuits_login( email = NULL, password = NULL, url = \"https://api.braincircuits.io\" ) braincircuits_token( email = NULL, password = NULL, url = \"https://api.braincircuits.io\" )"},{"path":"https://natverse.org/fafbseg/reference/braincircuits_login.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create and log into a braincircuits account — braincircuits_register","text":"open logical, whether open browser window login page braincircuits.io. email email registered/want register braincircuits.io. password password want set (using braincircuits_register) set (using braincircuits_login) account. url URL braincircuits API. Typically need change .","code":""},{"path":"https://natverse.org/fafbseg/reference/braincircuits_login.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create and log into a braincircuits account — braincircuits_register","text":"bearer access token query braincircuits API.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/braincircuits_login.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create and log into a braincircuits account — braincircuits_register","text":"","code":"if (FALSE) { # Run this function: braincircuits_login() # If you run it for the first time, a window will open # to the braincircuits log in page. Log in with an email. # then when prompted in the R command line, re-give your email address and # give a new password. You can save these in your .Renviron file to prevent having # to do this in future. }"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a token to enable access to brainmaps API — brainmaps_auth","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"Generate token enable access brainmaps API","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"","code":"brainmaps_auth( client_id = Sys.getenv(\"BRAINMAPS_CLIENT_ID\"), client_secret = Sys.getenv(\"BRAINMAPS_CLIENT_SECRET\"), scope = \"https://www.googleapis.com/auth/brainmaps\" )"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"client_id, client_secret Client id secret copied https://console.developers.google.com. See details. scope scope brainmaps API - need change .","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"token can used e.g. GET.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"need activate brainmaps API, generate project https://console.developers.google.com request OAuth credentials, create client id client secret. application name console must fafbseg. put keys .Renviron file. BRAINMAPS_CLIENT_ID=\"xxxx\" BRAINMAPS_CLIENT_SECRET=\"xxxx\"","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"","code":"if (FALSE) { google_token=brainmaps_auth() # get a list of available volumes req <- GET(\"https://brainmaps.googleapis.com/v1beta2/volumes\", config(token = google_token)) }"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_fetch.html","id":null,"dir":"Reference","previous_headings":"","what":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","title":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","text":"brainmaps_fetch calls brainmaps API optional request cache retries. brainmaps_clear_cache clears cache used brainmaps_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_fetch.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","text":"","code":"brainmaps_fetch( url, body = NULL, parse.json = TRUE, cache = FALSE, retry = 0L, include_headers = FALSE, simplifyVector = TRUE, ... ) brainmaps_clear_cache()"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_fetch.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","text":"url Full URL brainmaps API endpoint body R list parameters converted jsonlite::toJSON passed POST. can also pass JSON character vector control JSON encoding. parse.json Whether parse JSON response R object (default TRUE) cache Whether cache responses (default FALSE) retry number times retry operation (default 0, FALSE=>0 TRUE=>3). See documentation times argument httr::RETRY details. include_headers Whether include basic headers http request attributes parsed JSON object (default TRUE) parse.json=TRUE. simplifyVector Whether use jsonlite::simplifyVector ... additional arguments passed httr::{RETRY} function. may include config list named parameters etc.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_fetch.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","text":"R list parse","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_fetch.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","text":"","code":"if (FALSE) { brainmaps_fetch(\"https://brainmaps.googleapis.com/v1/volumes\") # retry up to 4 times on failure brainmaps_fetch(\"https://brainmaps.googleapis.com/v1/volumes\", retry=4) # cache results brainmaps_fetch(\"https://brainmaps.googleapis.com/v1/volumes\", cache=TRUE) # use arbitrary curl/httr options (see httr_options()) httr::with_config(httr::verbose(), { brainmaps_fetch(\"https://brainmaps.googleapis.com/v1/volumes\") }) } # \\donttest{ brainmaps_clear_cache() #> [1] TRUE # }"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_listfragments.html","id":null,"dir":"Reference","previous_headings":"","what":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","title":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","text":"Low level call brainmaps API list mesh fragment ids segment ids","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_listfragments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","text":"","code":"brainmaps_listfragments( x, volume = getOption(\"fafbseg.brainmaps.volume\"), meshName = getOption(\"fafbseg.brainmaps.meshName\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_listfragments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","text":"x Single segment identifier volume String identifier volume containing segments meshName String identifier meshes ... Additional arguments passed brainmaps_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_listfragments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","text":"Character vector fragment ids","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/brainmaps_listfragments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","text":"","code":"if (FALSE) { brainmaps_listfragments(7186840767) }"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":null,"dir":"Reference","previous_headings":"","what":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"Low level function fetch skeleton brainmaps API","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"","code":"brainmaps_skeleton(x, skeletonuri = getOption(\"fafbseg.skeletonuri\"), ...)"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"x single segment id skeletonuri brainmaps URI describing skeleton source. Defaults value options(\"fafbseg.skeletonuri\"). ... Additional arguments passed brainmaps_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"list containing following fields nvertices number vertices (n) nedges number edges (m) vertices n x 3 matrix vertex locations","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"API seems return skeletons physical (.e. already calibrated) coordinates.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"","code":"if (FALSE) { brainmaps_skeleton(9208128833) brainmaps_skeleton(9208128833, skeletonuri=paste0(\"brainmaps://772153499790:fafb_v14:\", \"fafb_v14_16nm_v00c_split3xfill2_flatreseg2_skeletons32\", \"/teasar512_nnconn165_mc10000_prune10_thresh1000_sparse250\")) }"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_volume.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract brainmaps volume identifier — brainmaps_volume","title":"Extract brainmaps volume identifier — brainmaps_volume","text":"Extract brainmaps volume identifier","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_volume.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract brainmaps volume identifier — brainmaps_volume","text":"","code":"brainmaps_volume(x)"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_volume.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract brainmaps volume identifier — brainmaps_volume","text":"x character vector containing brainmaps URI, parsed brainmaps_uri object character vector already containing volume specifier.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_volume.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract brainmaps volume identifier — brainmaps_volume","text":"character vector containing volume specifier.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_volume.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract brainmaps volume identifier — brainmaps_volume","text":"","code":"brainmaps_volume(\"772153499790:fafb_v14:fafb_v14_16nm_v00c_split3xfill2\") #> [1] \"772153499790:fafb_v14:fafb_v14_16nm_v00c_split3xfill2\" brainmaps_volume(\"brainmaps://772153499790:fafb_v14:fafb_v14_16nm_v00c_split3xfill2\") #> [1] \"772153499790:fafb_v14:fafb_v14_16nm_v00c_split3xfill2\""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"Convert 3D x,y,z locations brainmaps volumes segmentation ids","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"","code":"brainmaps_xyz2id( xyz, volume = getOption(\"fafbseg.skeletonuri\"), rawcoords = FALSE, rawvoxdims = c(8, 8, 40), chunksize = getOption(\"fafbseg.brainmaps_xyz2id.chunksize\", 200), ... )"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"xyz N x 3 matrix points object containing vertex data compatible xyzmatrix. physical space (.e. nm) unless voxdims=NULL. volume character vector identifier string volume containing segmentation data - default uses value fafbseg.skeletonuri option. input can parsed brainmaps_volume acceptable. rawcoords Whether coordinates voxel indices (rawcoords=TRUE) physical units (nm, default). rawvoxdims implied voxel dimensions volume. rawcoords=TRUE used convert raw coordinates physical units. default value matches normal voxel size neuroglancer. rawvoxdims=NULL attempt made scale coordinates whatsoever. See details. chunksize send queries batches chunksize points. default chosen since brainmaps API can time points take long map (likely spread across brain). also maximum number points per call (10,000 recommended upper limit one point). ... Additional arguments passed brainmaps_fetch. can include setting retry argument >0. See Details Examples.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"numeric vector Google segment ids","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"underlying brainmaps API expects raw coordinates .e. voxel indices. slightly complicated fact different segmentation, skeleton etc volumes may different associated voxel dimensions. brainmaps_xyz2id automatically looks voxel dimension. However may want pass raw coordinates neuroglancer. generally associated resolution image data e.g. skeletons may larger (coarser) voxel size. convenience situation can set rawcoords=TRUE. problems requests failing sporadically, may helpful know Google keep underlying data live may spin-time. arbitrary timeout Google end (currently ~ 5s) batching nearby points helps Using chunksize argument retry argument passed brainmaps_fetch can overcome issues. See examples.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"","code":"if (FALSE) { # Physical location in nm brainmaps_xyz2id(c(433368, 168208, 128480)) # Same location as displayed in neuroglancer brainmaps_xyz2id(c(54171, 21026, 3212), rawcoords=TRUE) # Raw coodinates for the brainmaps volume in question - don't touch brainmaps_xyz2id(c(433368, 168208, 128480)/c(32,32,40), rawvoxdims=NULL) library(elmr) # get a manually traced neuron (just keep first and only entry in neuronlist) dl4=read.neurons.catmaid('glomerulus DL4 right')[[1]] # map every node location to segmentation ids dl4.segs=brainmaps_xyz2id(dl4) # remove unmapped locations which get id 0 dl4.segs=setdiff(dl4.segs, 0) # read in corresponding skeletons dl4.skels=read_segments2(dl4.segs) # read in corresponding skeletons after including agglomeration merge groups dl4.allskels=read_segments2(find_merged_segments(dl4.segs)) ## retries / cache / chunksize issues # set small chunk size dl4.segs=brainmaps_xyz2id(dl4, chunksize=500) # use retries in case of failure dl4.segs=brainmaps_xyz2id(dl4, chunksize=500, retry=3) # cache successful requests (if you might need to repeat) dl4.segs=brainmaps_xyz2id(dl4, chunksize=500, retry=3, cache=TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/catmaid2ngl.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert CATMAID things (eg neurons) into Neuroglancer equivalents — catmaid2ngl","title":"Convert CATMAID things (eg neurons) into Neuroglancer equivalents — catmaid2ngl","text":"catmaid2ngl.neuron uses brainmaps_xyz2id read_segments2 find skeletons corresponding (catmaid) neuron catmaid2ngl.neuronlist applies catmaid2ngl.neuron neuronlist catmaid2ngl.character uses open_fafb_ngl open CATMAID location matching Neuroglancer URL. Converts CATMAID skid specification (see catmaid_skids) one neuron autosegmentation based neuron using catmaid2ngl.neuron.","code":""},{"path":"https://natverse.org/fafbseg/reference/catmaid2ngl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert CATMAID things (eg neurons) into Neuroglancer equivalents — catmaid2ngl","text":"","code":"catmaid2ngl(x, ...) # S3 method for neuron catmaid2ngl( x, chunksize = getOption(\"fafbseg.brainmaps_xyz2id.chunksize\", 4000), ... ) # S3 method for neuronlist catmaid2ngl(x, OmitFailures = TRUE, ...) # S3 method for character catmaid2ngl(x, open = FALSE, ...) # S3 method for default catmaid2ngl(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/catmaid2ngl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert CATMAID things (eg neurons) into Neuroglancer equivalents — catmaid2ngl","text":"x object convert (see Descriptions method) ... Additional arguments passed methods chunksize send queries batches chunksize points. default chosen since brainmaps API can time points take long map (likely spread across brain). also maximum number points per call (10,000 recommended upper limit one point). OmitFailures Whether omit neurons FUN gives error. default value (NA) result nlapply stopping error message moment error. values, see details. open Whether open URL browser - defaults TRUE interactive use.","code":""},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":null,"dir":"Reference","previous_headings":"","what":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"with_segmentation allows specific segmentation temporarily selected.","code":""},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"","code":"choose_segmentation( release = c(\"flywire31\", \"public-flywire31\", \"20200412\", \"20190805\", \"20190521\", \"sandbox-flywire31\"), set = TRUE, moreoptions = list() ) with_segmentation(release, expr)"},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"release character vector specifying released segmentation via known short name sample neuroglancer URL. set Whether set selected options selected release. moreoptions options might wish set (optional, expert use , principally intended use fancr package). expr expression execute temporary options set","code":""},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"set=TRUE list containing previous values relevant global options (style options. set=FALSE named list containing option values. result evaluating expr","code":""},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"released segmentation implies number global options. package comes multiple different default scene urls specified via choose_segmentation with_segmentation. easiest way choose particular segmentation. can also pass sample URL release argument. Nov 2020, \"flywire31\" default segmentation package loads. specifies production (.e. progress) version flywire dataset. need register flywire team generate flywire token linked email used registration access . Alternatively can also use \"public-flywire31\" data release accompanying Dorkenwald et al 2023 Schlegel et al 2023 publications; still need token (see flywire_set_token), registration required ( limitations use data new projects besides citing two preprints). can also specify different sample URL via sampleurl argument functions; remembered rest R session. regularly use particular kind scene URL, can set options(fafbseg.sampleurl) Rprofile file. need use built-custom segmentation URLs, recommend specifying custom URL Rprofile file using with_segmentation run code uses one built- segmentations.","code":""},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"","code":"# \\donttest{ choose_segmentation('20190805', set=FALSE) #> $fafbseg.sampleurl #> [1] \"https://neuroglancer-demo.appspot.com/#!%7B%22layers%22:%5B%7B%22source%22:%22precomputed://gs://neuroglancer-fafb-data/fafb_v14/fafb_v14_clahe_sharded%22%2C%22type%22:%22image%22%2C%22name%22:%22fafb_v14_clahe%22%7D%2C%7B%22source%22:%22brainmaps://772153499790:fafb_v14:fafb-ffn1-20190805%22%2C%22type%22:%22segmentation%22%2C%22skeletonRendering%22:%7B%22mode2d%22:%22lines_and_points%22%2C%22mode3d%22:%22lines%22%7D%2C%22name%22:%22fafb-ffn1-20190805%22%7D%2C%7B%22source%22:%22brainmaps://772153499790:fafb_v14:fafb-ffn1-20190805-skeletons32nm%22%2C%22type%22:%22segmentation%22%2C%22segments%22:%5B%220%22%5D%2C%22skeletonRendering%22:%7B%22mode2d%22:%22lines_and_points%22%2C%22mode3d%22:%22lines%22%7D%2C%22name%22:%22fafb-ffn1-20190805-skeletons32nm%22%7D%5D%2C%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22:%5B122437.5625%2C36391.234375%2C2057.085205078125%5D%7D%7D%2C%22zoomFactor%22:8%7D%2C%22perspectiveOrientation%22:%5B-0.6771116256713867%2C0.6536111831665039%2C-0.1610027700662613%2C0.2973051071166992%5D%2C%22perspectiveZoom%22:5184.860830857428%2C%22showSlices%22:false%2C%22layout%22:%224panel%22%7D\" #> #> $fafbseg.skeletonuri #> [1] \"brainmaps://772153499790:fafb_v14:fafb-ffn1-20190805-skeletons32nm\" #> #> $fafbseg.brainmaps.volume #> [1] \"772153499790:fafb_v14:fafb-ffn1-20190805\" #> #> $fafbseg.brainmaps.meshName #> [1] \"mcws_quad1e6\" #> #> $fafbseg.catmaid #> [1] \"https://garden.catmaid.org/tracing/fafb/v14-seg-li-190805.0/\" #> #> $fafbseg.cloudvolume.url #> [1] \"brainmaps://772153499790:fafb_v14:fafb-ffn1-20190805\" #> # } if (FALSE) { # temporarily change default segmentation to run a command # but restore original default when finished # Choose the FlyWire segmentation with_segmentation('flywire31', {open_fafb_ngl(c(460792, 221812, 61480))}) # similarly for one Google (Li and Jain) segmentation with_segmentation('20190805', {open_fafb_ngl(c(460792, 221812, 61480))}) } if (FALSE) { n <- with_segmentation(\"20190521\", read.neuron.brainmaps(22427007374)) # open location in flywire with_segmentation(\"flywire\", open_fafb_ngl(c(433440, 168344, 131200))) }"},{"path":"https://natverse.org/fafbseg/reference/compare_ng_neuron.html","id":null,"dir":"Reference","previous_headings":"","what":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","title":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","text":"Compare neuroglancer mesh object regular neuron","code":""},{"path":"https://natverse.org/fafbseg/reference/compare_ng_neuron.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","text":"","code":"compare_ng_neuron( x, n, breaks = 3, colpal = c(\"cyan\", \"red\"), plot = TRUE, plotn = plot, pointsize = 0.1, sample_dots = 1, ... )"},{"path":"https://natverse.org/fafbseg/reference/compare_ng_neuron.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","text":"x neuroglancer mesh, rgl::mesh3d object object defined xyzmatrix function. n nat::neuron object breaks either numeric vector two unique cut points single number (greater equal 2) giving number intervals x cut. colpal function defining colour palette vector colour names. plot Whether plot anything (set FALSE just want get distance information) plotn Whether plot neuron n pointsize Size plotted points mesh - passed points3d. Default pointsize=0.1 makes points smaller usual. sample_dots Fraction points (0-1) mesh plot - default value 1 implies points. Values sample_dots < 1 select random subsample points. ... Additional arguments passed plot3d.neuron","code":""},{"path":"https://natverse.org/fafbseg/reference/compare_ng_neuron.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","text":"Invisibly, data.frame distances object x nearest neighbour n well breaks used colouring points plotting.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/compare_ng_neuron.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","text":"","code":"if (FALSE) { x=read_ng_raw('meshdata/') library(elmr) y=read.neuron.catmaid(23432) compare_ng_neuron(x,y) }"},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"Download FlyWire connectivity annotations public release","code":""},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"","code":"download_flywire_release_data( which = c(\"core\", \"all\"), version = c(783L, 630L) )"},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"data download. core gets used files (~300 MB). gets additional useful ones (~900 MB). version materialisation version use. See details.","code":""},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"return value - just used side effect downloading files.","code":""},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"Note must accept abide flywire principles order use flywire data. Version 630 released June 2023 bioRxiv manuscripts remains default time significant improvements cell typing associated version 783 released Dec 2023 resubmissions core flywire manuscripts.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"","code":"if (FALSE) { # 300 MB download_flywire_release_data() # 900 MB includes download_flywire_release_data('all') }"},{"path":"https://natverse.org/fafbseg/reference/dr_fafbseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Print information about fafbseg setup including tokens and python modules — dr_fafbseg","title":"Print information about fafbseg setup including tokens and python modules — dr_fafbseg","text":"Print information fafbseg setup including FlyWire/ChunkedGraph authentication tokens, Python modules nat.h5reg / java setup required transforming points EM light level template brains.","code":""},{"path":"https://natverse.org/fafbseg/reference/dr_fafbseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print information about fafbseg setup including tokens and python modules — dr_fafbseg","text":"","code":"dr_fafbseg(pypkgs = NULL)"},{"path":"https://natverse.org/fafbseg/reference/dr_fafbseg.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print information about fafbseg setup including tokens and python modules — dr_fafbseg","text":"pypkgs Additional python packages check beyond standard ones fafbseg knows cloudvolume. set FALSE, turns Python package report altogether.","code":""},{"path":"https://natverse.org/fafbseg/reference/dr_fafbseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print information about fafbseg setup including tokens and python modules — dr_fafbseg","text":"","code":"if (FALSE) { dr_fafbseg(pymodules=FALSE) }"},{"path":"https://natverse.org/fafbseg/reference/fafb14_to_flywire_ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","title":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","text":"Provide function CATMAID query (skeleton IDs annotation term, provide catmaid::catmaid_skids) nat::neuronlist object FAFB14 space, return ranked list flywire IDs map onto given neuron(s).","code":""},{"path":"https://natverse.org/fafbseg/reference/fafb14_to_flywire_ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","text":"","code":"fafb14_to_flywire_ids( search, only.root = FALSE, only.biggest = FALSE, pid = 1L, conn = NULL, fetch.annotations = FALSE, OmitFailures = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/fafb14_to_flywire_ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","text":"search one skids CATMAID query expression. Else, neuronlist neurons FAFB14 space. .root return one root_id location root node given CATMAID neuron(s).. .biggest return one root_id per CATMAID skid .e. biggest overlapping fragment. pid Project id (default 1) conn catmaid_connection objection returned catmaid_login. NULL (default) new connection object generated using values catmaid.* package options described help catmaid_login. fetch.annotations Whether fetch annotations skeleton (default FALSE) OmitFailures logical, whether omit neurons read CATMAID. ... Additional arguments passed nat::nlapply.","code":""},{"path":"https://natverse.org/fafbseg/reference/fafb14_to_flywire_ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","text":"data.frame ranked flywire IDs, number points CATMAID neuron maps ID.","code":""},{"path":"https://natverse.org/fafbseg/reference/fafb14_to_flywire_ids.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","text":"","code":"if (FALSE) { # a specific skid df=fafb14_to_flywire_ids(16) head(df) # Get neurons from a specific CATMAID environment ## See catmaid package help for details on how to 'login' # This is the Drosophila anatomy ontology identifier for DL1 # adult antennal lobe projection neuron DL1 adPN # see \\url{https://virtualflybrain.org} for details. hits=fafb14_to_flywire_ids(search=\"FBbt:00067353\", conn=catmaid::vfbcatmaid()) head(hits) }"},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert between filenames and neuroglancer ids — fafbseg-ids","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"swc2segmentid converts swc filename segment id segmentid2zip converts segment id zip file contains zip2segmentstem converts zip file initial part segment id .e. segment stem (see details).","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"","code":"swc2segmentid(x, include.fragment = FALSE) segmentid2zip(x) zip2segmentstem(x)"},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"x Input file id include.fragment Whether include sub identifier skeleton fragment (see details).","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"swc2segmentid numeric vector matrix depending value include.fragment","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"Segment ids unique integers. 8E8 current skeletonisation seems ids can still > 2^31 (usually .Machine$integer.max). Therefore stored R numeric values bit64::integer64 values. segmentation keen skeletonised however usually results multiple skeleton fragments written separate SWC files: \"named ..swc\" segment id mapped onto zip file dividing divisor discarding remainder. Peter Li's data release 2018-10-02 switched 1E5 1E6.","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"","code":"swc2segmentid(\"10001654273.1.swc\") #> [1] 10001654273 swc2segmentid(sprintf(\"10001654273.%d.swc\", 0:2), include.fragment=TRUE) #> segment fragment #> [1,] 10001654273 0 #> [2,] 10001654273 1 #> [3,] 10001654273 2 if (FALSE) { # NB the default segmentation for fafbseg (flywire) no longer implies a local # collection of skeletons, wrap calls in with_segmentation with_segmentation(\"20190805\", segmentid2zip(10001654273)) with_segmentation(\"20190805\", segmentid2zip(swc2segmentid(\"10001654273.1.swc\"))) }"},{"path":"https://natverse.org/fafbseg/reference/fafbseg-package.html","id":null,"dir":"Reference","previous_headings":"","what":"fafbseg: Support Functions for Analysis of FAFB EM Segmentation — fafbseg-package","title":"fafbseg: Support Functions for Analysis of FAFB EM Segmentation — fafbseg-package","text":"Functions read raw data formats produced Google electron microscopy segmentation tools displayed 'neuroglancer' allow basic 3D visualisation analysis.","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-package.html","id":"package-options","dir":"Reference","previous_headings":"","what":"Package Options","title":"fafbseg: Support Functions for Analysis of FAFB EM Segmentation — fafbseg-package","text":"fafbseg.sampleurl optionally set sample Neuroglancer URL modified point arbitrary locations open_fafb_ngl. fafbseg.cave.datastack_name optionally set datastack_name used CAVE system. Expert use . Normally choose_segmentation looks . See flywire_cave_query details. fafbseg.condaenv python environment use miniconda. Defaults \"r-reticulate\", environment set reticulate::install_miniconda. can set something different like keep separate miniconda virtual environment just fafbseg (expert use ). fafbseg.sqlitepath optional set location SQLite tables used flywire_partners friends. fafbseg.cachedir location disk caches functions including flywire_leaves unset package load, set appropriate user folder using rappdirs::user_data_dir. fafbseg.flcachesize maximum cache size bytes. Defaults 1.5 * 1024^3 unset. See flywire_leaves details. fafbseg.flywire_roots.chunksize default processing 100,000 rootids time. Set smaller queries time / give \"Request Entity Large\" errors. Larger settings unlikely much speed impact. See flywire_rootid details. fafbseg.skelziproot set location folder containing zipped versions skeletonised segmentations. used read_segments, read_topn etc. fafbseg.skeletonuri brainmaps URI specifying remote source used read.neurons.brainmaps brainmaps_skeleton read neuronal skeletons. fafbseg.brainmaps_xyz2id.chunksize default querying 4000 vertices time. Set smaller queries time larger speed things . See brainmaps_xyz2id details.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/fafbseg-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"fafbseg: Support Functions for Analysis of FAFB EM Segmentation — fafbseg-package","text":"Maintainer: Gregory Jefferis jefferis@gmail.com (ORCID) contributors: Sridhar Jagannathan j.sridharrajan@gmail.com (ORCID) [contributor] Alexander Bates alexander.shakeel.bates@gmail.com (ORCID) [contributor]","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-package.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"fafbseg: Support Functions for Analysis of FAFB EM Segmentation — fafbseg-package","text":"","code":"options()[grep(\"^fafbseg\\\\.\", names(options()))] #> $fafbseg.cachedir #> [1] \"/home/runner/.local/share/R/fafbseg\" #> #> $fafbseg.cave.datastack_name #> [1] \"flywire_fafb_production\" #> #> $fafbseg.cloudvolume.url #> [1] \"graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31\" #> #> $fafbseg.condaenv #> [1] \"r-reticulate\" #> #> $fafbseg.sampleurl #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22:%5B%7B%22source%22:%22precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked%22%2C%22type%22:%22image%22%2C%22blend%22:%22default%22%2C%22shaderControls%22:%7B%7D%2C%22name%22:%22Production-image%22%7D%2C%7B%22source%22:%22graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31%22%2C%22type%22:%22segmentation_with_graph%22%2C%22segments%22:%5B%220%22%5D%2C%22skeletonRendering%22:%7B%22mode2d%22:%22lines_and_points%22%2C%22mode3d%22:%22lines%22%7D%2C%22graphOperationMarker%22:%5B%7B%22annotations%22:%5B%5D%2C%22tags%22:%5B%5D%7D%2C%7B%22annotations%22:%5B%5D%2C%22tags%22:%5B%5D%7D%5D%2C%22pathFinder%22:%7B%22color%22:%22#ffff00%22%2C%22pathObject%22:%7B%22annotationPath%22:%7B%22annotations%22:%5B%5D%2C%22tags%22:%5B%5D%7D%2C%22hasPath%22:false%7D%7D%2C%22name%22:%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22:%5B108360%2C42086%2C3279%5D%7D%7D%2C%22zoomFactor%22:8%7D%2C%22perspectiveZoom%22:2230.6094286986126%2C%22jsonStateServer%22:%22https://globalv1.flywire-daf.com/nglstate/post%22%2C%22selectedLayer%22:%7B%22layer%22:%22Production-segmentation_with_graph%22%2C%22visible%22:true%7D%2C%22layout%22:%22xy-3d%22%7D\" #> #> $fafbseg.sqlitepath #> [1] \"~/projects/JanFunke/\" #>"},{"path":"https://natverse.org/fafbseg/reference/fct2nginfo.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","title":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","text":"Convert flytable cell type information neuroglancer info file","code":""},{"path":"https://natverse.org/fafbseg/reference/fct2nginfo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","text":"","code":"fct2nginfo(f, ids = NULL, version = NULL, sep = \"_\", gluestr = NULL, ...)"},{"path":"https://natverse.org/fafbseg/reference/fct2nginfo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","text":"f Path json file. write_nginfo create enclosing directory necessary. ids FlyWire root ids form understood flywire_ids version Optional numeric CAVE version (see flywire_cave_query). special signalling value TRUE uses current default data dump returned flywire_connectome_data_version. sep separator used paste multiple columns annotations together. gluestr Optional string passed glue::glue interpreted context annotation data.frame produced flytable_meta. allows arbitrary formatting ... Additional arguments passed flytable_meta eventually flytable_cell_types.","code":""},{"path":"https://natverse.org/fafbseg/reference/fct2nginfo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","text":"path f invisibly","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/fct2nginfo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","text":"","code":"if (FALSE) { # all neurons in info table fct2nginfo(f='path/to/flytablev526/info', version=526) fct2nginfo(f='path/to/hemilineagev526/info', version=526, gluestr=\"{ito_lee_hemilineage}_{toupper(substr(side,1,1))}\") fct2nginfo(\"MBON%\", 'path/to/mboninfo/info') }"},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"Fetch data specified set curl shell commands (e.g. Chrome)","code":""},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"","code":"fetch_all_curl( x = clipr::read_clip(), outdir = NULL, regex = \"^curl\", filename = \"chunk%05d.raw\", ... )"},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"x Path file character vector statements (default reads statements clipboard) outdir Optional output directory (created necessary) regex Optional regular expression curl statements must match filename sprintf style format statement used name downloaded files. ... Additional arguments grep","code":""},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"named character vector containing matched URLs named downloaded files disk (invisibly)","code":""},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"can generate appropriate set commands opening Chrome Developer console (View ... Developer ... JavaScript Console), (re)loading page interest, selecting network tab, selecting downloaded object, right clicking choosing (Copy ... Copy cURL). make sure one neuron displayed want parse object identifier relationships.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"","code":"if (FALSE) { fetch_all_curl(\"all_curl.sh\", outdir=\"alldata\", regex=\"brainmaps.googleapis.com\", fixed=TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":null,"dir":"Reference","previous_headings":"","what":"Find all merged segment ids for a given starting google segment id — find_merged_segments","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"Find merged segment ids given starting google segment id","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"","code":"find_merged_segments( x, return.groups = FALSE, return.segmentids.for.groups = TRUE )"},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"x segment id input can interpreted ngl_segments return.groups Whether return merge groups well segment ids return.segmentids..groups Whether return canonical segment id group rather 1-index merge group (see details).","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"vector segment ids (ascending order) return.groups=TRUE data.frame columns segment integer segment id, numeric (double) column group arbitrary group id starting 1 canonical segment id (see details), integer numeric (double), respectively","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"segment ids ffn16reseg-ms1000_md0.02_c0.6_iou0.7 always match one raw segment id fafb_v14_16nm_v00c_split3xfill2 may map large agglomerated merge group. provide two ways define identifier merge groups. One uses canonical segment id: first (.e. lowest) segment id merge group appears brainmaps API identifies merge group. case even known merges given segment. R field numeric (double) column since R native support 64 bit integers. second approach group identifiers uses integer 1 number known merge groups. known merges segment, NA value returned. Note function depends segment_merge_groups.dt object fafbsegdata package.","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"","code":"# \\donttest{ if(requireNamespace('fafbsegdata', quietly = TRUE)) { find_merged_segments(7186840767) # these all belong to one merge group by definition find_merged_segments(7186840767, return.groups=TRUE) } #> segment group #> 1 10218295532 7186840767 #> 2 10233257420 7186840767 #> 3 7186840767 7186840767 #> 4 7186844852 7186840767 #> 5 7188488573 7186840767 #> 6 7188488876 7186840767 #> 7 7506547847 7186840767 #> 8 7511521487 7186840767 #> 9 7513174533 7186840767 #> 10 7523125878 7186840767 #> 11 7524769973 7186840767 #> 12 7528082928 7186840767 #> 13 7528082999 7186840767 #> 14 7528083090 7186840767 #> 15 7528087811 7186840767 #> 16 7844472994 7186840767 #> 17 7844473351 7186840767 #> 18 7866011642 7186840767 #> 19 7866015978 7186840767 #> 20 7869320680 7186840767 #> 21 8184049304 7186840767 #> 22 8184049546 7186840767 #> 23 8187380528 7186840767 #> 24 8193975632 7186840767 #> 25 8198954037 7186840767 #> 26 8515392737 7186840767 #> 27 8525318026 7186840767 #> 28 8525318518 7186840767 #> 29 8525318619 7186840767 #> 30 8525318881 7186840767 #> 31 8526948746 7186840767 #> 32 8535280040 7186840767 #> 33 8541870917 7186840767 #> 34 8543523319 7186840767 #> 35 8861569429 7186840767 #> 36 8866569630 7186840767 #> 37 8866569764 7186840767 #> 38 8869882415 7186840767 #> 39 8873165227 7186840767 #> 40 8873192134 7186840767 #> 41 8874821377 7186840767 #> 42 8876521709 7186840767 #> 43 8876543998 7186840767 #> 44 8878156810 7186840767 #> 45 8881456848 7186840767 #> 46 8883135153 7186840767 #> 47 9217782462 7186840767 #> 48 9219408058 7186840767 #> 49 9219408083 7186840767 #> 50 9221047258 7186840767 #> 51 9537450356 7186840767 #> 52 9539102248 7186840767 #> 53 9540758370 7186840767 #> 54 9540758400 7186840767 #> 55 9540758403 7186840767 #> 56 9554037005 7186840767 #> 57 9554041768 7186840767 #> 58 9555689874 7186840767 #> 59 9560632655 7186840767 #> 60 9562293635 7186840767 #> 61 9563945725 7186840767 #> 62 9875383416 7186840767 #> 63 9880358224 7186840767 #> 64 9885314546 7186840767 # }"},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments_slow.html","id":null,"dir":"Reference","previous_headings":"","what":"Find all merged segment ids for a given starting google segment id — find_merged_segments_slow","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments_slow","text":"naive implementation depends mergeinfo object created read_mergeinfo. retained verify correctness. slow require pre-processing table merge information.","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments_slow.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments_slow","text":"","code":"find_merged_segments_slow(x, mergeinfo)"},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments_slow.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments_slow","text":"x segment id input can interpreted ngl_segments mergeinfo merge information data.frame created read_mergeinfo","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments_slow.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments_slow","text":"vector segment ids","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":null,"dir":"Reference","previous_headings":"","what":"Flytable database queries — flytable-queries","title":"Flytable database queries — flytable-queries","text":"flytable_query performs SQL query flytable database. can omit base argument unless tables name different bases.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Flytable database queries — flytable-queries","text":"","code":"flytable_list_rows( table, base = NULL, view_name = NULL, order_by = NULL, desc = FALSE, start = 0L, limit = Inf, python = FALSE, chunksize = NULL ) flytable_query( sql, limit = 100000L, base = NULL, python = FALSE, convert = TRUE )"},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Flytable database queries — flytable-queries","text":"table name table inside database base Character vector naming seatable base (recommended) Base object returned flytable_base (expert use). view_name optional view may limit rows/columns displayed. order_by Optional name columns order results desc Whether use descending order (default FALSE => ascending order) start Optional starting row limit optional limit, applies specify limit directly sql query. default seatable limits SQL queries 100 rows. increase limit 100000 rows default. python Whether return Python pandas DataFrame. default FALSE returns R data.frame chunksize Optional maximum number rows request one web request. advanced use default value NULL fetch many possible. sql SQL query string. See examples seatable docs. convert Expert use : Whether allow Python seatable module process raw output database. principally debugging purposes. NB imposes requirement seatable_api >=2.4.0.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Flytable database queries — flytable-queries","text":"R data.frame Pandas DataFrame depending value python argument. data.frame results. 0 rows rows matched query.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Flytable database queries — flytable-queries","text":"Flytable uses programmatic access seatable API.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Flytable database queries — flytable-queries","text":"","code":"# \\donttest{ flytable_list_rows(table = \"testfruit\") #> _id _mtime _ctime fruit_name #> 1 H8BckTnXRL2PaVuLDcRPMA 2022-05-12 16:58:07 2021-12-17 13:36:17 apple #> 2 SrBW3vFLRxafKRYHoPrGQQ 2022-05-12 16:58:08 2021-12-17 13:36:17 banana #> 3 F1h-TZKpTcWiHujZ2xnF8Q 2022-05-12 16:58:08 2021-12-17 13:36:17 clementine #> 4 KZrMyoJKTeS_o9Pgynu7YQ 2024-01-18 00:42:52 2022-05-11 00:34:27 kiwi #> 5 cI4fqlOUQK2A1jZKZvFpdg 2022-05-12 16:58:09 2022-05-11 00:39:59 kiwi #> 6 AOUcHHZ0RTC-auONZURx4g 2022-05-12 16:58:10 2022-05-11 00:40:57 kiwi #> 7 dxs7n1NpRM-hWoGJxPZpKA 2022-05-12 16:58:10 2022-05-11 00:41:17 kiwi #> 8 J-JrluKcRzmYjgKCtMEAKw 2022-05-12 16:58:11 2022-05-11 00:41:25 kiwi #> 9 aMmi4iegRNCdpY39-iAfdg 2022-05-12 16:58:11 2022-05-11 01:00:47 kiwi #> 10 EH-l0qAyQyyJO8UpNYSj8w 2022-05-12 16:58:12 2022-05-11 01:07:10 kiwi #> 11 E6uAS8ehQyid0sSj1bD-HA 2022-05-12 16:58:12 2022-05-11 20:52:00 kiwi #> 12 P83tySHzT-iFfbwvlhJU7A 2022-05-12 16:58:13 2022-05-11 21:18:45 kiwi #> 13 GBCn8fkaTnidSg8Nh7CLkQ 2022-05-12 16:58:13 2022-05-11 21:25:28 kiwi #> 14 DHSK4OmSRYiNHFn6yHWEjQ 2022-05-12 16:58:13 2022-05-11 21:29:40 kiwi #> 15 CVL59Pt2Ta6BWXXmEmLFSw 2022-05-12 16:58:14 2022-05-11 21:34:07 kiwi #> 16 DHq2ty1nQn-LolwKbR5D9A 2022-05-12 16:58:14 2022-05-11 21:34:22 kiwi #> 17 Y4aoKGjIQU6WskMCll9LtA 2022-05-12 16:58:15 2022-05-12 16:56:52 kiwi #> 18 L94KQt88S6-cPBQSSk8IDg 2022-05-12 16:58:15 2022-05-12 16:58:15 kiwi #> 19 JgCx-eJfQI22f1ynv_G4aA 2022-05-12 18:16:18 2022-05-12 18:16:18 kiwi #> 20 HWP0B4R2TVinR51ZEiCh1Q 2022-05-12 18:33:47 2022-05-12 18:33:47 kiwi #> 21 frinTnwQS_yT-p-6bUdUjg 2022-05-12 18:49:36 2022-05-12 18:49:36 kiwi #> 22 Q79Qb0tMSi-NT__KJOXdnw 2022-05-12 19:03:47 2022-05-12 19:03:47 kiwi #> 23 e63mt6sxSCSHK-AqkyE7rQ 2022-05-12 20:22:02 2022-05-12 20:22:02 kiwi #> 24 e3AH4HFxTHiIILhWAgVfnQ 2022-05-12 20:41:57 2022-05-12 20:41:57 kiwi #> 25 LIbNUlKpQhq3pHuqs_GG2A 2022-05-13 13:10:55 2022-05-13 13:10:55 kiwi #> 26 Jox91CBQQIq8zv58pjE-gA 2022-05-13 13:11:49 2022-05-13 13:11:49 kiwi #> 27 Mm7xFfvlQ6Ohb3FFA7-y3g 2022-05-13 13:12:24 2022-05-13 13:12:24 kiwi #> 28 SY5dA23CSfCqFnePxJP1Ng 2022-05-13 13:13:31 2022-05-13 13:13:31 kiwi #> 29 c-9ONdxnTsyIWgMx8_Qo5w 2022-05-13 14:15:29 2022-05-13 14:15:29 kiwi #> 30 NvptrkSgS36T-Q6TBbyioA 2022-05-13 14:20:30 2022-05-13 14:20:30 kiwi #> 31 PXX2Ay_XRwSOkVrJqBftsA 2022-05-13 14:21:21 2022-05-13 14:21:21 kiwi #> 32 ET9-W5hxRdOoeEr54TgfZw 2022-05-13 14:26:16 2022-05-13 14:26:16 kiwi #> 33 GBy5d_8jTYyV1RUEwpAwfQ 2022-05-13 14:32:10 2022-05-13 14:32:10 kiwi #> 34 UvG5kHD7ST6m4yj5-xk2QA 2022-05-22 07:43:19 2022-05-22 07:43:19 kiwi #> 35 SI2RldvDSsmadBqYrCqaqQ 2022-05-22 07:47:43 2022-05-22 07:47:43 kiwi #> 36 MNPFKn5zRRKMHq66LQNWiA 2022-05-22 07:51:06 2022-05-22 07:51:06 kiwi #> 37 OTsRNBFrS3mtawfKiREmrw 2022-05-29 06:31:28 2022-05-29 06:31:28 kiwi #> 38 Nv8oP_hUSvyHgws5DQ0ZGA 2022-05-29 10:30:15 2022-05-29 10:30:15 kiwi #> 39 OrEYIA_bQDCx6v-MkTuDYw 2022-05-29 10:34:54 2022-05-29 10:34:54 kiwi #> 40 BhzO_0xqQsi41eCEKsAjGQ 2022-05-29 10:38:00 2022-05-29 10:38:00 kiwi #> 41 BNeHPQNnSyuMvAEd3Kh6MQ 2022-05-29 20:33:27 2022-05-29 20:33:27 kiwi #> 42 aVoVAUuWTFOtoUhQvOd_bg 2022-05-29 20:40:41 2022-05-29 20:40:41 kiwi #> 43 BYauV5OwTa2tOk9JWW1N_A 2022-05-29 20:42:10 2022-05-29 20:42:10 kiwi #> 44 DR3lfQrkQmu_tUcwlzx6Aw 2022-05-29 20:45:57 2022-05-29 20:45:57 kiwi #> 45 JVksPUCFSFCD4pF__s5E2A 2022-06-06 14:40:12 2022-06-06 14:40:12 kiwi #> 46 T4IY3mh6Sniovww6Yg3OWQ 2022-06-06 14:44:59 2022-06-06 14:44:59 kiwi #> 47 TQqr1_nAQv27Qm3p1GXIMQ 2022-06-06 14:50:54 2022-06-06 14:50:54 kiwi #> 48 c87JLpHXS5CRtj1YtXpL0g 2022-07-01 20:06:17 2022-07-01 20:06:17 kiwi #> 49 AirzCY7yRS26fFBU_F6j5g 2022-07-01 20:33:14 2022-07-01 20:33:14 kiwi #> 50 fRamo6FETfqaProIZuRbaA 2022-07-01 20:41:09 2022-07-01 20:41:09 kiwi #> 51 Uy0XHWAhQjqJ2QtM-rDj3A 2022-07-01 20:42:29 2022-07-01 20:42:29 kiwi #> 52 EcabRY2tSZyxjT9dztNVhQ 2022-07-01 21:11:03 2022-07-01 21:11:03 kiwi #> 53 VdYIA9bAQaWnTafJOR7-IA 2022-07-01 21:16:00 2022-07-01 21:16:00 kiwi #> 54 YiTEtjEnT3OlWI8RJ0GbHA 2022-07-01 21:25:19 2022-07-01 21:25:19 kiwi #> 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2024-01-16 10:08:59 kiwi #> 467 GHfdynarRXqaL0voP_eZAQ 2024-01-17 15:53:35 2024-01-17 15:53:35 kiwi #> 468 OUbwDZywTaS-JMbEaXA-Tw 2024-01-17 16:25:50 2024-01-17 16:25:50 kiwi #> 469 EXHFx-sTT_GxPuFYVVNzUg 2024-01-17 22:58:48 2024-01-17 22:58:48 kiwi #> 470 CYCqSBn3S7aQNdBHZmd0cg 2024-01-17 23:09:06 2024-01-17 23:09:06 kiwi #> 471 G516rJm2Qq6LBfGPafzgXw 2024-01-17 23:13:55 2024-01-17 23:13:55 kiwi #> 472 N8lByhadRym68iMWyMKo1Q 2024-01-18 00:19:09 2024-01-18 00:19:09 kiwi #> 473 c8RQlG0-TDiGeY2SQk0i0w 2024-01-18 00:25:17 2024-01-18 00:25:17 kiwi #> 474 JSQglb37SzquHiXR2viZsg 2024-01-18 00:42:53 2024-01-18 00:42:53 kiwi #> nid person last_modified date_nominute #> 1 1 Alice 2022-05-12 16:58:07 2022-01-06 #> 2 2 Bob 2022-05-12 16:58:08 2022-01-03 #> 3 3 Clara 2022-05-12 16:58:08 2021-08-05 #> 4 6 Frederick the Great 2024-01-18 00:42:52 #> 5 6 Frederick the Great 2022-05-12 16:58:09 #> 6 6 Frederick the Great 2022-05-12 16:58:10 #> 7 6 Frederick the Great 2022-05-12 16:58:10 #> 8 6 Frederick the Great 2022-05-12 16:58:11 #> 9 6 Frederick the Great 2022-05-12 16:58:11 #> 10 6 Frederick the Great 2022-05-12 16:58:12 #> 11 6 Frederick the Great 2022-05-12 16:58:12 #> 12 6 Frederick the Great 2022-05-12 16:58:13 #> 13 6 Frederick the Great 2022-05-12 16:58:13 #> 14 6 Frederick the Great 2022-05-12 16:58:13 #> 15 6 Frederick the Great 2022-05-12 16:58:14 #> 16 6 Frederick the Great 2022-05-12 16:58:14 #> 17 6 Frederick the Great 2022-05-12 16:58:15 #> 18 6 Frederick the Great 2022-05-12 16:58:15 #> 19 6 Frederick the Great 2022-05-12 18:16:18 #> 20 6 Frederick the Great 2022-05-12 18:33:47 #> 21 6 Frederick the Great 2022-05-12 18:49:36 #> 22 6 Frederick the Great 2022-05-12 19:03:47 #> 23 6 Frederick the Great 2022-05-12 20:22:02 #> 24 6 Frederick the Great 2022-05-12 20:41:57 #> 25 6 Frederick the Great 2022-05-13 13:10:55 #> 26 6 Frederick the Great 2022-05-13 13:11:49 #> 27 6 Frederick the Great 2022-05-13 13:12:24 #> 28 6 Frederick the Great 2022-05-13 13:13:31 #> 29 6 Frederick the Great 2022-05-13 14:15:29 #> 30 6 Frederick the Great 2022-05-13 14:20:30 #> 31 6 Frederick the Great 2022-05-13 14:21:21 #> 32 6 Frederick the Great 2022-05-13 14:26:16 #> 33 6 Frederick the Great 2022-05-13 14:32:10 #> 34 6 Frederick the Great 2022-05-22 07:43:19 #> 35 6 Frederick the Great 2022-05-22 07:47:43 #> 36 6 Frederick the Great 2022-05-22 07:51:06 #> 37 6 Frederick the Great 2022-05-29 06:31:28 #> 38 6 Frederick the Great 2022-05-29 10:30:15 #> 39 6 Frederick the Great 2022-05-29 10:34:54 #> 40 6 Frederick the Great 2022-05-29 10:38:00 #> 41 6 Frederick the Great 2022-05-29 20:33:27 #> 42 6 Frederick the Great 2022-05-29 20:40:41 #> 43 6 Frederick the Great 2022-05-29 20:42:10 #> 44 6 Frederick the Great 2022-05-29 20:45:57 #> 45 6 Frederick the Great 2022-06-06 14:40:12 #> 46 6 Frederick the Great 2022-06-06 14:44:59 #> 47 6 Frederick the Great 2022-06-06 14:50:54 #> 48 6 Frederick the Great 2022-07-01 20:06:17 #> 49 6 Frederick the Great 2022-07-01 20:33:14 #> 50 6 Frederick the Great 2022-07-01 20:41:09 #> 51 6 Frederick the Great 2022-07-01 20:42:29 #> 52 6 Frederick the Great 2022-07-01 21:11:03 #> 53 6 Frederick the Great 2022-07-01 21:16:00 #> 54 6 Frederick the Great 2022-07-01 21:25:19 #> 55 6 Frederick the Great 2022-08-01 19:57:01 #> 56 6 Frederick the Great 2022-08-01 20:02:23 #> 57 6 Frederick the Great 2022-08-01 20:11:08 #> 58 6 Frederick the Great 2022-08-01 20:48:34 #> 59 6 Frederick the Great 2022-08-01 20:55:12 #> 60 6 Frederick the Great 2022-08-01 21:00:19 #> 61 6 Frederick the Great 2022-08-28 18:36:52 #> 62 6 Frederick the Great 2022-08-28 18:42:31 #> 63 6 Frederick the Great 2022-08-28 19:44:37 #> 64 6 Frederick the Great 2022-08-31 19:52:42 #> 65 6 Frederick the Great 2022-08-31 20:00:52 #> 66 6 Frederick the Great 2022-08-31 21:35:54 #> 67 6 Frederick the Great 2022-08-31 21:41:49 #> 68 6 Frederick the Great 2022-08-31 21:51:44 #> 69 6 Frederick the Great 2022-09-12 11:42:51 #> 70 6 Frederick the Great 2022-09-12 11:59:40 #> 71 6 Frederick the Great 2022-09-12 12:21:12 #> 72 6 Frederick the Great 2022-09-12 12:39:22 #> 73 6 Frederick the Great 2022-09-12 13:59:26 #> 74 6 Frederick the Great 2022-09-12 14:05:01 #> 75 6 Frederick the Great 2022-09-13 09:01:13 #> 76 6 Frederick the Great 2022-09-13 09:07:08 #> 77 6 Frederick the Great 2022-09-13 09:09:27 #> 78 6 Frederick the Great 2022-09-14 09:31:22 #> 79 6 Frederick the Great 2022-09-14 09:36:24 #> 80 6 Frederick the Great 2022-09-14 09:54:34 #> 81 6 Frederick the Great 2022-09-14 15:44:47 #> 82 6 Frederick the Great 2022-09-14 16:20:36 #> 83 6 Frederick the Great 2022-09-14 16:47:53 #> 84 6 Frederick the Great 2022-09-14 16:55:04 #> 85 6 Frederick the Great 2022-09-14 23:30:37 #> 86 6 Frederick the Great 2022-09-14 23:36:40 #> 87 6 Frederick the Great 2022-09-14 23:50:18 #> 88 6 Frederick the Great 2022-09-15 09:33:48 #> 89 6 Frederick the Great 2022-09-15 09:49:01 #> 90 6 Frederick the Great 2022-09-15 09:53:43 #> 91 6 Frederick the Great 2022-09-15 09:59:12 #> 92 6 Frederick the Great 2022-09-15 10:02:06 #> 93 6 Frederick the Great 2022-09-15 10:08:05 #> 94 6 Frederick the Great 2022-09-15 10:10:25 #> 95 6 Frederick the Great 2022-09-15 16:44:02 #> 96 6 Frederick the Great 2022-09-15 17:01:50 #> 97 6 Frederick the Great 2022-09-15 17:45:04 #> 98 6 Frederick the Great 2022-09-15 17:51:49 #> 99 6 Frederick the Great 2022-09-25 23:58:56 #> 100 6 Frederick the Great 2022-09-26 00:00:50 #> 101 6 Frederick the Great 2022-09-26 00:05:20 #> 102 6 Frederick the Great 2022-09-26 00:41:12 #> 103 6 Frederick the Great 2022-09-26 00:47:49 #> 104 6 Frederick the Great 2022-09-26 07:00:20 #> 105 6 Frederick the Great 2022-09-26 07:06:14 #> 106 6 Frederick the Great 2022-09-26 09:12:11 #> 107 6 Frederick the Great 2022-09-26 09:17:19 #> 108 6 Frederick the Great 2022-10-04 11:23:23 #> 109 6 Frederick the Great 2022-10-04 11:29:16 #> 110 6 Frederick the Great 2022-10-04 11:53:29 #> 111 6 Frederick the Great 2022-10-04 11:58:25 #> 112 6 Frederick the Great 2022-10-04 12:07:24 #> 113 6 Frederick the Great 2022-10-04 13:05:57 #> 114 6 Frederick the Great 2022-10-04 13:07:44 #> 115 6 Frederick the Great 2022-10-04 13:10:34 #> 116 6 Frederick the Great 2022-10-04 13:11:08 #> 117 6 Frederick the Great 2022-10-04 13:15:40 #> 118 6 Frederick the Great 2022-10-04 13:16:00 #> 119 6 Frederick the Great 2022-10-04 16:18:32 #> 120 6 Frederick the Great 2022-10-04 16:34:25 #> 121 6 Frederick the Great 2022-10-04 17:16:23 #> 122 6 Frederick the Great 2022-10-04 17:21:45 #> 123 6 Frederick the Great 2022-10-04 17:30:58 #> 124 6 Frederick the Great 2022-10-04 17:34:17 #> 125 6 Frederick the Great 2022-10-04 17:37:40 #> 126 6 Frederick the Great 2022-10-04 17:44:31 #> 127 6 Frederick the Great 2022-10-04 19:01:50 #> 128 6 Frederick the Great 2022-10-04 19:07:20 #> 129 6 Frederick the Great 2022-10-04 19:19:51 #> 130 6 Frederick the Great 2022-10-07 21:04:12 #> 131 6 Frederick the Great 2022-10-07 21:25:49 #> 132 6 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2022-11-18 19:49:24 #> 153 6 Frederick the Great 2022-11-18 20:06:08 #> 154 6 Frederick the Great 2022-11-18 20:08:24 #> 155 6 Frederick the Great 2022-11-18 20:33:51 #> 156 6 Frederick the Great 2022-11-19 17:46:18 #> 157 6 Frederick the Great 2022-11-19 17:57:46 #> 158 6 Frederick the Great 2022-11-22 20:29:27 #> 159 6 Frederick the Great 2022-11-22 20:37:23 #> 160 6 Frederick the Great 2022-11-22 20:37:30 #> 161 6 Frederick the Great 2022-11-22 20:44:33 #> 162 6 Frederick the Great 2022-11-23 16:51:24 #> 163 6 Frederick the Great 2022-11-23 17:13:32 #> 164 6 Frederick the Great 2022-11-26 21:46:30 #> 165 6 Frederick the Great 2022-11-26 21:51:09 #> 166 6 Frederick the Great 2022-11-27 15:38:01 #> 167 6 Frederick the Great 2022-11-27 15:38:52 #> 168 6 Frederick the Great 2022-11-27 15:45:02 #> 169 6 Frederick the Great 2022-11-27 17:40:54 #> 170 6 Frederick the Great 2022-11-27 17:47:19 #> 171 6 Frederick the Great 2022-11-28 07:49:23 #> 172 6 Frederick the Great 2022-11-28 07:55:10 #> 173 6 Frederick the Great 2022-11-28 07:59:30 #> 174 6 Frederick the Great 2022-11-28 08:25:33 #> 175 6 Frederick the Great 2022-11-28 08:31:14 #> 176 6 Frederick the Great 2022-11-28 09:30:12 #> 177 6 Frederick the Great 2022-11-28 09:36:28 #> 178 6 Frederick the Great 2022-11-28 09:39:28 #> 179 6 Frederick the Great 2022-11-28 11:01:59 #> 180 6 Frederick the Great 2022-11-28 11:08:09 #> 181 6 Frederick the Great 2022-11-28 11:11:31 #> 182 6 Frederick the Great 2022-11-29 18:58:51 #> 183 6 Frederick the Great 2022-11-29 19:06:13 #> 184 6 Frederick the Great 2022-11-29 19:13:02 #> 185 6 Frederick the Great 2022-12-11 00:17:18 #> 186 6 Frederick the Great 2022-12-11 00:21:03 #> 187 6 Frederick the Great 2022-12-11 00:23:42 #> 188 6 Frederick the Great 2023-01-13 11:59:47 #> 189 6 Frederick the Great 2023-01-13 12:33:40 #> 190 6 Frederick the Great 2023-01-13 12:39:37 #> 191 6 Frederick the Great 2023-01-22 22:50:26 #> 192 6 Frederick the Great 2023-01-22 22:57:27 #> 193 6 Frederick the Great 2023-01-22 23:00:59 #> 194 6 Frederick the Great 2023-01-23 10:47:44 #> 195 6 Frederick the Great 2023-01-23 10:51:45 #> 196 6 Frederick the Great 2023-01-23 10:54:02 #> 197 6 Frederick the Great 2023-01-23 11:04:46 #> 198 6 Frederick the Great 2023-01-23 11:06:44 #> 199 6 Frederick the Great 2023-01-23 11:11:03 #> 200 6 Frederick the Great 2023-01-23 11:12:12 #> 201 6 Frederick the Great 2023-01-23 11:18:42 #> 202 6 Frederick the Great 2023-01-23 11:21:54 #> 203 6 Frederick the Great 2023-01-23 11:33:49 #> 204 6 Frederick the Great 2023-01-23 14:34:46 #> 205 6 Frederick the Great 2023-01-23 14:40:14 #> 206 6 Frederick the Great 2023-01-23 14:52:29 #> 207 6 Frederick the Great 2023-01-23 23:23:30 #> 208 6 Frederick the Great 2023-01-23 23:31:56 #> 209 6 Frederick the Great 2023-01-24 01:52:16 #> 210 6 Frederick the Great 2023-01-24 01:59:44 #> 211 6 Frederick the Great 2023-01-24 02:08:23 #> 212 6 Frederick the Great 2023-01-24 08:03:55 #> 213 6 Frederick the Great 2023-01-24 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Frederick the Great 2023-01-30 15:05:56 #> 235 6 Frederick the Great 2023-01-30 15:09:27 #> 236 6 Frederick the Great 2023-01-30 19:58:34 #> 237 6 Frederick the Great 2023-01-30 20:06:57 #> 238 6 Frederick the Great 2023-01-30 20:14:00 #> 239 6 Frederick the Great 2023-01-30 22:03:04 #> 240 6 Frederick the Great 2023-01-30 22:15:06 #> 241 6 Frederick the Great 2023-02-13 08:34:44 #> 242 6 Frederick the Great 2023-02-13 08:37:48 #> 243 6 Frederick the Great 2023-02-13 10:53:05 #> 244 6 Frederick the Great 2023-02-13 11:14:57 #> 245 6 Frederick the Great 2023-02-13 11:54:27 #> 246 6 Frederick the Great 2023-04-02 12:52:46 #> 247 6 Frederick the Great 2023-04-02 12:58:52 #> 248 6 Frederick the Great 2023-04-02 13:04:37 #> 249 6 Frederick the Great 2023-04-02 21:14:25 #> 250 6 Frederick the Great 2023-04-02 21:21:24 #> 251 6 Frederick the Great 2023-06-13 18:37:23 #> 252 6 Frederick the Great 2023-06-13 18:46:47 #> 253 6 Frederick the Great 2023-06-14 06:09:12 #> 254 6 Frederick the Great 2023-06-14 10:27:24 #> 255 6 Frederick the Great 2023-06-14 11:05:47 #> 256 6 Frederick the Great 2023-06-14 12:00:24 #> 257 6 Frederick the Great 2023-06-14 12:44:12 #> 258 6 Frederick the Great 2023-06-14 12:56:28 #> 259 6 Frederick the Great 2023-06-14 13:54:05 #> 260 6 Frederick the Great 2023-06-15 20:12:49 #> 261 6 Frederick the Great 2023-06-15 20:17:28 #> 262 6 Frederick the Great 2023-06-15 20:25:20 #> 263 6 Frederick the Great 2023-06-16 09:39:16 #> 264 6 Frederick the Great 2023-06-26 06:10:47 #> 265 6 Frederick the Great 2023-06-26 06:33:34 #> 266 6 Frederick the Great 2023-06-26 07:22:55 #> 267 6 Frederick the Great 2023-06-26 07:26:51 #> 268 6 Frederick the Great 2023-06-26 07:31:48 #> 269 6 Frederick the Great 2023-06-26 07:34:59 #> 270 6 Frederick the Great 2023-06-26 08:55:32 #> 271 6 Frederick the Great 2023-06-26 09:01:34 #> 272 6 Frederick the Great 2023-06-26 09:10:31 #> 273 6 Frederick the Great 2023-06-26 10:07:19 #> 274 6 Frederick the Great 2023-06-26 10:26:06 #> 275 6 Frederick the Great 2023-06-26 10:34:52 #> 276 6 Frederick the Great 2023-06-26 10:37:19 #> 277 6 Frederick the Great 2023-06-27 10:17:07 #> 278 6 Frederick the Great 2023-06-27 10:23:22 #> 279 6 Frederick the Great 2023-06-27 10:32:51 #> 280 6 Frederick the Great 2023-06-27 12:31:48 #> 281 6 Frederick the Great 2023-06-27 12:38:28 #> 282 6 Frederick the Great 2023-06-27 20:57:41 #> 283 6 Frederick the Great 2023-06-28 08:51:08 #> 284 6 Frederick the Great 2023-06-28 09:08:31 #> 285 6 Frederick the Great 2023-06-28 09:15:01 #> 286 6 Frederick the Great 2023-06-28 09:25:48 #> 287 6 Frederick the Great 2023-07-04 20:56:37 #> 288 6 Frederick the Great 2023-07-10 12:26:30 #> 289 6 Frederick the Great 2023-07-10 12:27:20 #> 290 6 Frederick the Great 2023-07-10 12:36:06 #> 291 6 Frederick the Great 2023-07-10 12:37:54 #> 292 6 Frederick the Great 2023-07-10 12:58:10 #> 293 6 Frederick the Great 2023-07-10 13:05:41 #> 294 6 Frederick the Great 2023-07-10 13:06:43 #> 295 6 Frederick the Great 2023-07-10 18:02:11 #> 296 6 Frederick the Great 2023-07-10 18:08:22 #> 297 6 Frederick the Great 2023-07-10 18:18:04 #> 298 6 Frederick the Great 2023-07-12 12:36:05 #> 299 6 Frederick the Great 2023-07-12 12:39:26 #> 300 6 Frederick the Great 2023-07-12 12:41:55 #> 301 6 Frederick the Great 2023-07-12 12:42:13 #> 302 6 Frederick the Great 2023-07-12 12:42:53 #> 303 6 Frederick the Great 2023-07-12 12:46:35 #> 304 6 Frederick the Great 2023-07-12 18:18:16 #> 305 6 Frederick the Great 2023-07-12 18:25:46 #> 306 6 Frederick the Great 2023-07-12 18:31:02 #> 307 6 Frederick the Great 2023-07-12 22:29:25 #> 308 6 Frederick the Great 2023-07-12 22:36:56 #> 309 6 Frederick the Great 2023-07-13 10:32:56 #> 310 6 Frederick the Great 2023-07-13 10:39:37 #> 311 6 Frederick the Great 2023-07-13 10:45:42 #> 312 6 Frederick the Great 2023-07-13 13:45:26 #> 313 6 Frederick the Great 2023-07-13 13:53:45 #> 314 6 Frederick the Great 2023-07-13 14:01:53 #> 315 6 Frederick the Great 2023-07-21 17:25:24 #> 316 6 Frederick the Great 2023-07-21 17:37:09 #> 317 6 Frederick the Great 2023-07-23 19:32:35 #> 318 6 Frederick the Great 2023-07-23 19:33:26 #> 319 6 Frederick the Great 2023-07-23 19:41:04 #> 320 6 Frederick the Great 2023-07-25 14:26:49 #> 321 6 Frederick the Great 2023-07-25 14:34:39 #> 322 6 Frederick the Great 2023-07-25 14:41:55 #> 323 6 Frederick the Great 2023-07-27 20:38:15 #> 324 6 Frederick the Great 2023-07-27 20:45:23 #> 325 6 Frederick the Great 2023-07-27 20:53:01 #> 326 6 Frederick the Great 2023-08-02 06:13:53 #> 327 6 Frederick the Great 2023-08-02 06:21:37 #> 328 6 Frederick the Great 2023-08-02 06:25:45 #> 329 6 Frederick the Great 2023-08-19 04:44:30 #> 330 6 Frederick the Great 2023-08-23 02:19:20 #> 331 6 Frederick the Great 2023-08-23 02:33:07 #> 332 6 Frederick the Great 2023-08-23 11:49:50 #> 333 6 Frederick the Great 2023-08-23 11:58:10 #> 334 6 Frederick the Great 2023-08-23 11:58:29 #> 335 6 Frederick the Great 2023-08-25 03:33:51 #> 336 6 Frederick the Great 2023-08-25 04:07:05 #> 337 6 Frederick the Great 2023-08-25 07:14:59 #> 338 6 Frederick the Great 2023-08-26 00:46:31 #> 339 6 Frederick the Great 2023-08-26 00:52:49 #> 340 6 Frederick the Great 2023-08-26 01:05:23 #> 341 6 Frederick the Great 2023-08-26 01:22:54 #> 342 6 Frederick the Great 2023-08-26 01:29:17 #> 343 6 Frederick the Great 2023-08-26 01:38:58 #> 344 6 Frederick the Great 2023-08-26 11:37:47 #> 345 6 Frederick the Great 2023-08-26 12:09:11 #> 346 6 Frederick the Great 2023-08-26 15:08:50 #> 347 6 Frederick the Great 2023-08-26 15:15:17 #> 348 6 Frederick the Great 2023-08-26 15:21:32 #> 349 6 Frederick the Great 2023-08-26 16:19:18 #> 350 6 Frederick the Great 2023-08-26 16:25:57 #> 351 6 Frederick the Great 2023-08-26 16:26:47 #> 352 6 Frederick the Great 2023-08-28 09:39:38 #> 353 6 Frederick the Great 2023-08-28 09:53:53 #> 354 6 Frederick the Great 2023-08-28 09:58:49 #> 355 6 Frederick the Great 2023-08-28 10:00:20 #> 356 6 Frederick the Great 2023-08-28 10:18:13 #> 357 6 Frederick the Great 2023-08-28 10:18:41 #> 358 6 Frederick the Great 2023-08-28 12:08:57 #> 359 6 Frederick the Great 2023-08-28 12:30:24 #> 360 6 Frederick the Great 2023-08-28 15:09:51 #> 361 6 Frederick the Great 2023-08-28 15:16:52 #> 362 6 Frederick the Great 2023-08-28 15:27:17 #> 363 6 Frederick the Great 2023-08-28 15:45:48 #> 364 6 Frederick the Great 2023-08-28 15:52:12 #> 365 6 Frederick the Great 2023-08-28 15:55:46 #> 366 6 Frederick the Great 2023-08-28 17:38:53 #> 367 6 Frederick the Great 2023-08-28 17:46:14 #> 368 6 Frederick the Great 2023-08-28 18:08:06 #> 369 6 Frederick the Great 2023-08-28 18:20:26 #> 370 6 Frederick the Great 2023-08-28 18:24:10 #> 371 6 Frederick the Great 2023-08-28 18:25:03 #> 372 6 Frederick the Great 2023-08-28 18:29:33 #> 373 6 Frederick the Great 2023-08-28 18:45:46 #> 374 6 Frederick the Great 2023-08-28 19:33:41 #> 375 6 Frederick the Great 2023-08-28 21:53:16 #> 376 6 Frederick the Great 2023-08-28 22:12:50 #> 377 6 Frederick the Great 2023-08-28 22:22:43 #> 378 6 Frederick the Great 2023-08-28 22:48:21 #> 379 6 Frederick the Great 2023-08-28 23:04:52 #> 380 6 Frederick the Great 2023-08-29 00:20:25 #> 381 6 Frederick the Great 2023-08-29 00:37:40 #> 382 6 Frederick the Great 2023-08-29 00:40:34 #> 383 6 Frederick the Great 2023-08-31 08:33:33 #> 384 6 Frederick the Great 2023-08-31 08:43:27 #> 385 6 Frederick the Great 2023-08-31 08:49:49 #> 386 6 Frederick the Great 2023-09-04 19:48:39 #> 387 6 Frederick the Great 2023-09-04 19:54:44 #> 388 6 Frederick the Great 2023-09-04 20:10:15 #> 389 6 Frederick the Great 2023-09-04 21:30:05 #> 390 6 Frederick the Great 2023-09-04 21:37:46 #> 391 6 Frederick the Great 2023-09-04 21:47:49 #> 392 6 Frederick the Great 2023-09-05 00:10:15 #> 393 6 Frederick the Great 2023-09-05 00:14:07 #> 394 6 Frederick the Great 2023-09-05 00:35:09 #> 395 6 Frederick the Great 2023-09-08 13:29:11 #> 396 6 Frederick the Great 2023-09-08 13:45:11 #> 397 6 Frederick the Great 2023-09-08 13:45:40 #> 398 6 Frederick the Great 2023-09-09 10:55:29 #> 399 6 Frederick the Great 2023-09-09 11:14:17 #> 400 6 Frederick the Great 2023-09-09 11:20:13 #> 401 6 Frederick the Great 2023-09-09 12:58:11 #> 402 6 Frederick the Great 2023-09-09 13:14:28 #> 403 6 Frederick the Great 2023-09-09 13:25:26 #> 404 6 Frederick the Great 2023-09-22 11:35:42 #> 405 6 Frederick the Great 2023-09-22 11:58:52 #> 406 6 Frederick the Great 2023-09-22 12:05:58 #> 407 6 Frederick the Great 2023-09-22 14:38:44 #> 408 6 Frederick the Great 2023-09-22 14:54:22 #> 409 6 Frederick the Great 2023-10-04 15:38:45 #> 410 6 Frederick the Great 2023-10-04 15:44:55 #> 411 6 Frederick the Great 2023-10-04 16:00:19 #> 412 6 Frederick the Great 2023-10-08 15:32:39 #> 413 6 Frederick the Great 2023-10-08 15:43:09 #> 414 6 Frederick the Great 2023-10-08 15:49:14 #> 415 6 Frederick the Great 2023-10-12 23:34:35 #> 416 6 Frederick the Great 2023-10-12 23:44:48 #> 417 6 Frederick the Great 2023-10-13 00:10:51 #> 418 6 Frederick the Great 2023-10-16 07:03:26 #> 419 6 Frederick the Great 2023-10-16 07:08:28 #> 420 6 Frederick the Great 2023-10-19 21:22:40 #> 421 6 Frederick the Great 2023-10-19 21:34:50 #> 422 6 Frederick the Great 2023-10-19 22:02:52 #> 423 6 Frederick the Great 2023-10-21 11:25:24 #> 424 6 Frederick the Great 2023-10-21 11:28:23 #> 425 6 Frederick the Great 2023-10-31 15:18:50 #> 426 6 Frederick the Great 2023-10-31 15:24:52 #> 427 6 Frederick the Great 2023-10-31 17:17:50 #> 428 6 Frederick the Great 2023-10-31 17:26:10 #> 429 6 Frederick the Great 2023-10-31 17:40:01 #> 430 6 Frederick the Great 2023-11-14 12:08:55 #> 431 6 Frederick the Great 2023-11-14 12:20:34 #> 432 6 Frederick the Great 2023-11-14 12:45:11 #> 433 6 Frederick the Great 2023-12-04 23:43:33 #> 434 6 Frederick the Great 2023-12-04 23:50:28 #> 435 6 Frederick the Great 2023-12-05 00:08:44 #> 436 6 Frederick the Great 2023-12-05 05:38:51 #> 437 6 Frederick the Great 2023-12-05 08:50:02 #> 438 6 Frederick the Great 2023-12-05 08:50:42 #> 439 6 Frederick the Great 2023-12-05 09:18:33 #> 440 6 Frederick the Great 2023-12-05 14:28:43 #> 441 6 Frederick the Great 2023-12-05 14:43:20 #> 442 6 Frederick the Great 2023-12-05 14:44:45 #> 443 6 Frederick the Great 2023-12-27 09:08:20 #> 444 6 Frederick the Great 2023-12-27 15:32:22 #> 445 6 Frederick the Great 2023-12-27 15:50:03 #> 446 6 Frederick the Great 2023-12-27 16:04:07 #> 447 6 Frederick the Great 2023-12-27 16:05:20 #> 448 6 Frederick the Great 2023-12-27 16:47:40 #> 449 6 Frederick the Great 2023-12-27 17:14:31 #> 450 6 Frederick the Great 2023-12-27 18:49:23 #> 451 6 Frederick the Great 2023-12-27 18:59:53 #> 452 6 Frederick the Great 2023-12-27 19:05:27 #> 453 6 Frederick the Great 2023-12-27 20:09:49 #> 454 6 Frederick the Great 2023-12-27 20:35:02 #> 455 6 Frederick the Great 2023-12-27 23:29:51 #> 456 6 Frederick the Great 2023-12-27 23:43:07 #> 457 6 Frederick the Great 2023-12-27 23:48:17 #> 458 6 Frederick the Great 2023-12-28 00:29:37 #> 459 6 Frederick the Great 2023-12-28 00:42:07 #> 460 6 Frederick the Great 2023-12-28 00:43:28 #> 461 6 Frederick the Great 2023-12-28 12:20:04 #> 462 6 Frederick the Great 2023-12-28 12:24:08 #> 463 6 Frederick the Great 2023-12-28 12:45:17 #> 464 6 Frederick the Great 2024-01-15 17:54:42 #> 465 6 Frederick the Great 2024-01-15 18:10:30 #> 466 6 Frederick the Great 2024-01-16 10:08:59 #> 467 6 Frederick the Great 2024-01-17 15:53:35 #> 468 6 Frederick the Great 2024-01-17 16:25:50 #> 469 6 Frederick the Great 2024-01-17 22:58:48 #> 470 6 Frederick the Great 2024-01-17 23:09:06 #> 471 6 Frederick the Great 2024-01-17 23:13:55 #> 472 6 Frederick the Great 2024-01-18 00:19:09 #> 473 6 Frederick the Great 2024-01-18 00:25:17 #> 474 6 Frederick the Great 2024-01-18 00:42:53 #> date_wminute user camid #> 1 2022-01-12 09:30:00 8adf4f5dd661449fa6cc1f5a0b1815c0@auth.local 100001 #> 2 2022-01-03 07:56:00 c7efb8019da54923a9b04d4a74f0fde8@auth.local 100002 #> 3 2021-08-05 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100244 #> 60 NaN 100245 #> 61 NaN 100246 #> 62 NaN 100247 #> 63 NaN 100248 #> 64 NaN 100249 #> 65 NaN 100250 #> 66 NaN 100251 #> 67 NaN 100252 #> 68 NaN 100253 #> 69 NaN 100254 #> 70 NaN 100255 #> 71 NaN 100256 #> 72 NaN 100257 #> 73 NaN 100258 #> 74 NaN 100259 #> 75 NaN 100260 #> 76 NaN 100261 #> 77 NaN 100262 #> 78 NaN 100263 #> 79 NaN 100264 #> 80 NaN 100265 #> 81 NaN 100266 #> 82 NaN 100267 #> 83 NaN 100268 #> 84 NaN 100269 #> 85 NaN 100270 #> 86 NaN 100271 #> 87 NaN 100272 #> 88 NaN 100273 #> 89 NaN 100274 #> 90 NaN 100275 #> 91 NaN 100276 #> 92 NaN 100277 #> 93 NaN 100278 #> 94 NaN 100279 #> 95 NaN 100280 #> 96 NaN 100281 #> 97 NaN 100282 #> 98 NaN 100283 #> 99 NaN 100284 #> 100 NaN 100285 #> 101 NaN 100286 #> 102 NaN 100287 #> 103 NaN 100288 #> 104 NaN 100289 #> 105 NaN 100290 #> 106 NaN 100291 #> 107 NaN 100292 #> 108 NaN 100293 #> 109 NaN 100294 #> 110 NaN 100295 #> 111 NaN 100296 #> 112 NaN 100297 #> 113 NaN 100298 #> 114 NaN 100299 #> 115 NaN 100300 #> 116 NaN 100301 #> 117 NaN 100302 #> 118 NaN 100303 #> 119 NaN 100304 #> 120 NaN 100305 #> 121 NaN 100306 #> 122 NaN 100307 #> 123 NaN 100308 #> 124 NaN 100309 #> 125 NaN 100310 #> 126 NaN 100311 #> 127 NaN 100312 #> 128 NaN 100313 #> 129 NaN 100314 #> 130 NaN 100315 #> 131 NaN 100316 #> 132 NaN 100317 #> 133 NaN 100318 #> 134 NaN 100319 #> 135 NaN 100320 #> 136 NaN 100321 #> 137 NaN 100322 #> 138 NaN 100323 #> 139 NaN 100324 #> 140 NaN 100325 #> 141 NaN 100326 #> 142 NaN 100327 #> 143 NaN 100328 #> 144 NaN 100329 #> 145 NaN 100330 #> 146 NaN 100331 #> 147 NaN 100332 #> 148 NaN 100333 #> 149 NaN 100334 #> 150 NaN 100335 #> 151 NaN 100336 #> 152 NaN 100337 #> 153 NaN 100338 #> 154 NaN 100339 #> 155 NaN 100340 #> 156 NaN 100341 #> 157 NaN 100342 #> 158 NaN 100343 #> 159 NaN 100344 #> 160 NaN 100345 #> 161 NaN 100346 #> 162 NaN 100347 #> 163 NaN 100348 #> 164 NaN 100349 #> 165 NaN 100350 #> 166 NaN 100351 #> 167 NaN 100352 #> 168 NaN 100353 #> 169 NaN 100354 #> 170 NaN 100355 #> 171 NaN 100356 #> 172 NaN 100357 #> 173 NaN 100358 #> 174 NaN 100359 #> 175 NaN 100360 #> 176 NaN 100361 #> 177 NaN 100362 #> 178 NaN 100363 #> 179 NaN 100364 #> 180 NaN 100365 #> 181 NaN 100366 #> 182 NaN 100367 #> 183 NaN 100368 #> 184 NaN 100369 #> 185 NaN 100370 #> 186 NaN 100371 #> 187 NaN 100372 #> 188 NaN 100373 #> 189 NaN 100374 #> 190 NaN 100375 #> 191 NaN 100376 #> 192 NaN 100377 #> 193 NaN 100378 #> 194 NaN 100379 #> 195 NaN 100380 #> 196 NaN 100381 #> 197 NaN 100382 #> 198 NaN 100383 #> 199 NaN 100384 #> 200 NaN 100385 #> 201 NaN 100386 #> 202 NaN 100387 #> 203 NaN 100388 #> 204 NaN 100389 #> 205 NaN 100390 #> 206 NaN 100391 #> 207 NaN 100392 #> 208 NaN 100393 #> 209 NaN 100394 #> 210 NaN 100395 #> 211 NaN 100396 #> 212 NaN 100397 #> 213 NaN 100398 #> 214 NaN 100399 #> 215 NaN 100400 #> 216 NaN 100401 #> 217 NaN 100402 #> 218 NaN 100403 #> 219 NaN 100404 #> 220 NaN 100405 #> 221 NaN 100406 #> 222 NaN 100407 #> 223 NaN 100408 #> 224 NaN 100409 #> 225 NaN 100410 #> 226 NaN 100411 #> 227 NaN 100412 #> 228 NaN 100413 #> 229 NaN 100414 #> 230 NaN 100415 #> 231 NaN 100416 #> 232 NaN 100417 #> 233 NaN 100418 #> 234 NaN 100419 #> 235 NaN 100420 #> 236 NaN 100421 #> 237 NaN 100422 #> 238 NaN 100423 #> 239 NaN 100424 #> 240 NaN 100425 #> 241 NaN 100426 #> 242 NaN 100427 #> 243 NaN 100428 #> 244 NaN 100429 #> 245 NaN 100430 #> 246 NaN 100431 #> 247 NaN 100432 #> 248 NaN 100433 #> 249 NaN 100434 #> 250 NaN 100435 #> 251 NaN 100436 #> 252 NaN 100437 #> 253 NaN 100438 #> 254 NaN 100439 #> 255 NaN 100440 #> 256 NaN 100441 #> 257 NaN 100442 #> 258 NaN 100443 #> 259 NaN 100444 #> 260 NaN 100445 #> 261 NaN 100446 #> 262 NaN 100447 #> 263 NaN 100448 #> 264 NaN 100449 #> 265 NaN 100450 #> 266 NaN 100451 #> 267 NaN 100452 #> 268 NaN 100453 #> 269 NaN 100454 #> 270 NaN 100455 #> 271 NaN 100456 #> 272 NaN 100457 #> 273 NaN 100458 #> 274 NaN 100459 #> 275 NaN 100460 #> 276 NaN 100461 #> 277 NaN 100462 #> 278 NaN 100463 #> 279 NaN 100464 #> 280 NaN 100465 #> 281 NaN 100466 #> 282 NaN 100467 #> 283 NaN 100468 #> 284 NaN 100469 #> 285 NaN 100470 #> 286 NaN 100471 #> 287 NaN 100472 #> 288 NaN 100473 #> 289 NaN 100474 #> 290 NaN 100475 #> 291 NaN 100476 #> 292 NaN 100477 #> 293 NaN 100478 #> 294 NaN 100479 #> 295 NaN 100480 #> 296 NaN 100481 #> 297 NaN 100482 #> 298 NaN 100483 #> 299 NaN 100484 #> 300 NaN 100485 #> 301 NaN 100486 #> 302 NaN 100487 #> 303 NaN 100488 #> 304 NaN 100489 #> 305 NaN 100490 #> 306 NaN 100491 #> 307 NaN 100492 #> 308 NaN 100493 #> 309 NaN 100494 #> 310 NaN 100495 #> 311 NaN 100496 #> 312 NaN 100497 #> 313 NaN 100498 #> 314 NaN 100499 #> 315 NaN 100500 #> 316 NaN 100501 #> 317 NaN 100502 #> 318 NaN 100503 #> 319 NaN 100504 #> 320 NaN 100505 #> 321 NaN 100506 #> 322 NaN 100507 #> 323 NaN 100508 #> 324 NaN 100509 #> 325 NaN 100510 #> 326 NaN 100511 #> 327 NaN 100512 #> 328 NaN 100513 #> 329 NaN 100514 #> 330 NaN 100515 #> 331 NaN 100516 #> 332 NaN 100517 #> 333 NaN 100518 #> 334 NaN 100519 #> 335 NaN 100520 #> 336 NaN 100521 #> 337 NaN 100522 #> 338 NaN 100523 #> 339 NaN 100524 #> 340 NaN 100525 #> 341 NaN 100526 #> 342 NaN 100527 #> 343 NaN 100528 #> 344 NaN 100529 #> 345 NaN 100530 #> 346 NaN 100531 #> 347 NaN 100532 #> 348 NaN 100533 #> 349 NaN 100534 #> 350 NaN 100535 #> 351 NaN 100536 #> 352 NaN 100537 #> 353 NaN 100538 #> 354 NaN 100539 #> 355 NaN 100540 #> 356 NaN 100541 #> 357 NaN 100542 #> 358 NaN 100543 #> 359 NaN 100544 #> 360 NaN 100545 #> 361 NaN 100546 #> 362 NaN 100547 #> 363 NaN 100548 #> 364 NaN 100549 #> 365 NaN 100550 #> 366 NaN 100551 #> 367 NaN 100552 #> 368 NaN 100553 #> 369 NaN 100554 #> 370 NaN 100555 #> 371 NaN 100556 #> 372 NaN 100557 #> 373 NaN 100558 #> 374 NaN 100559 #> 375 NaN 100560 #> 376 NaN 100561 #> 377 NaN 100562 #> 378 NaN 100563 #> 379 NaN 100564 #> 380 NaN 100565 #> 381 NaN 100566 #> 382 NaN 100567 #> 383 NaN 100568 #> 384 NaN 100569 #> 385 NaN 100570 #> 386 NaN 100571 #> 387 NaN 100572 #> 388 NaN 100573 #> 389 NaN 100574 #> 390 NaN 100575 #> 391 NaN 100576 #> 392 NaN 100577 #> 393 NaN 100578 #> 394 NaN 100579 #> 395 NaN 100580 #> 396 NaN 100581 #> 397 NaN 100582 #> 398 NaN 100583 #> 399 NaN 100584 #> 400 NaN 100585 #> 401 NaN 100586 #> 402 NaN 100587 #> 403 NaN 100588 #> 404 NaN 100589 #> 405 NaN 100590 #> 406 NaN 100591 #> 407 NaN 100592 #> 408 NaN 100593 #> 409 NaN 100594 #> 410 NaN 100595 #> 411 NaN 100596 #> 412 NaN 100597 #> 413 NaN 100598 #> 414 NaN 100599 #> 415 NaN 100600 #> 416 NaN 100601 #> 417 NaN 100602 #> 418 NaN 100603 #> 419 NaN 100604 #> 420 NaN 100605 #> 421 NaN 100606 #> 422 NaN 100607 #> 423 NaN 100608 #> 424 NaN 100609 #> 425 NaN 100610 #> 426 NaN 100611 #> 427 NaN 100612 #> 428 NaN 100613 #> 429 NaN 100614 #> 430 NaN 100615 #> 431 NaN 100616 #> 432 NaN 100617 #> 433 NaN 100618 #> 434 NaN 100619 #> 435 NaN 100620 #> 436 NaN 100621 #> 437 NaN 100622 #> 438 NaN 100623 #> 439 NaN 100624 #> 440 NaN 100625 #> 441 NaN 100626 #> 442 NaN 100627 #> 443 NaN 100628 #> 444 NaN 100629 #> 445 NaN 100630 #> 446 NaN 100631 #> 447 NaN 100632 #> 448 NaN 100633 #> 449 NaN 100634 #> 450 NaN 100635 #> 451 NaN 100636 #> 452 NaN 100637 #> 453 NaN 100638 #> 454 NaN 100639 #> 455 NaN 100640 #> 456 NaN 100641 #> 457 NaN 100642 #> 458 NaN 100643 #> 459 NaN 100644 #> 460 NaN 100645 #> 461 NaN 100646 #> 462 NaN 100647 #> 463 NaN 100648 #> 464 NaN 100649 #> 465 NaN 100650 #> 466 NaN 100651 #> 467 NaN 100652 #> 468 NaN 100653 #> 469 NaN 100654 #> 470 NaN 100655 #> 471 NaN 100656 #> 472 NaN 100657 #> 473 NaN 100658 #> 474 NaN 100659 # } # \\donttest{ flytable_query(\"SELECT person, fruit_name FROM testfruit WHERE person!='Bob'\") #> person fruit_name #> 1 Alice apple #> 2 Clara clementine #> 3 Frederick the Great kiwi #> 4 Frederick the Great kiwi #> 5 Frederick the Great kiwi #> 6 Frederick the Great kiwi #> 7 Frederick the Great kiwi #> 8 Frederick the Great kiwi #> 9 Frederick the Great kiwi #> 10 Frederick the Great kiwi #> 11 Frederick the Great kiwi #> 12 Frederick the Great kiwi #> 13 Frederick the Great kiwi #> 14 Frederick the Great kiwi #> 15 Frederick the Great kiwi #> 16 Frederick the Great kiwi #> 17 Frederick the Great kiwi #> 18 Frederick the Great kiwi #> 19 Frederick the Great kiwi #> 20 Frederick the Great kiwi #> 21 Frederick the Great kiwi #> 22 Frederick the Great kiwi #> 23 Frederick the Great kiwi #> 24 Frederick the Great kiwi #> 25 Frederick the Great kiwi #> 26 Frederick the Great kiwi #> 27 Frederick the Great kiwi #> 28 Frederick the Great kiwi #> 29 Frederick the Great kiwi #> 30 Frederick the Great kiwi #> 31 Frederick the Great kiwi #> 32 Frederick the Great kiwi #> 33 Frederick the Great kiwi #> 34 Frederick the Great kiwi #> 35 Frederick the Great kiwi #> 36 Frederick the Great kiwi #> 37 Frederick the Great kiwi #> 38 Frederick the Great kiwi #> 39 Frederick the Great kiwi #> 40 Frederick the Great kiwi #> 41 Frederick the Great kiwi #> 42 Frederick the Great kiwi #> 43 Frederick the Great kiwi #> 44 Frederick the Great kiwi #> 45 Frederick the Great kiwi #> 46 Frederick the Great kiwi #> 47 Frederick the Great kiwi #> 48 Frederick the Great kiwi #> 49 Frederick the Great kiwi #> 50 Frederick the Great kiwi #> 51 Frederick the Great kiwi #> 52 Frederick the Great kiwi #> 53 Frederick the Great kiwi #> 54 Frederick the Great kiwi #> 55 Frederick the Great kiwi #> 56 Frederick the Great kiwi #> 57 Frederick the Great kiwi #> 58 Frederick the Great kiwi #> 59 Frederick the Great kiwi #> 60 Frederick the Great kiwi #> 61 Frederick the Great kiwi #> 62 Frederick the Great kiwi #> 63 Frederick the Great kiwi #> 64 Frederick the Great kiwi #> 65 Frederick the Great kiwi #> 66 Frederick the Great kiwi #> 67 Frederick the Great kiwi #> 68 Frederick the Great kiwi #> 69 Frederick the Great kiwi #> 70 Frederick the Great kiwi #> 71 Frederick the Great kiwi #> 72 Frederick the Great kiwi #> 73 Frederick the Great kiwi #> 74 Frederick the Great kiwi #> 75 Frederick the Great kiwi #> 76 Frederick the Great kiwi #> 77 Frederick the Great kiwi #> 78 Frederick the Great kiwi #> 79 Frederick the Great kiwi #> 80 Frederick the Great kiwi #> 81 Frederick the Great kiwi #> 82 Frederick the Great kiwi #> 83 Frederick the Great kiwi #> 84 Frederick the Great kiwi #> 85 Frederick the Great kiwi #> 86 Frederick the Great kiwi #> 87 Frederick the Great kiwi #> 88 Frederick the Great kiwi #> 89 Frederick the Great kiwi #> 90 Frederick the Great kiwi #> 91 Frederick the Great kiwi #> 92 Frederick the Great kiwi #> 93 Frederick the Great kiwi #> 94 Frederick the Great kiwi #> 95 Frederick the Great kiwi #> 96 Frederick the Great kiwi #> 97 Frederick the Great kiwi #> 98 Frederick the Great kiwi #> 99 Frederick the Great kiwi #> 100 Frederick the Great kiwi #> 101 Frederick the Great kiwi #> 102 Frederick the Great kiwi #> 103 Frederick the Great kiwi #> 104 Frederick the Great kiwi #> 105 Frederick the Great kiwi #> 106 Frederick the Great kiwi #> 107 Frederick the Great kiwi #> 108 Frederick the Great kiwi #> 109 Frederick the Great kiwi #> 110 Frederick the Great kiwi #> 111 Frederick the Great kiwi #> 112 Frederick the Great kiwi #> 113 Frederick the Great kiwi #> 114 Frederick the Great kiwi #> 115 Frederick the Great kiwi #> 116 Frederick the Great kiwi #> 117 Frederick the Great kiwi #> 118 Frederick the Great kiwi #> 119 Frederick the Great kiwi #> 120 Frederick the Great kiwi #> 121 Frederick the Great kiwi #> 122 Frederick the Great kiwi #> 123 Frederick the Great kiwi #> 124 Frederick the Great kiwi #> 125 Frederick the Great kiwi #> 126 Frederick the Great kiwi #> 127 Frederick the Great kiwi #> 128 Frederick the Great kiwi #> 129 Frederick the Great kiwi #> 130 Frederick the Great kiwi #> 131 Frederick the Great kiwi #> 132 Frederick the Great kiwi #> 133 Frederick the Great kiwi #> 134 Frederick the Great kiwi #> 135 Frederick the Great kiwi #> 136 Frederick the Great kiwi #> 137 Frederick the Great kiwi #> 138 Frederick the Great kiwi #> 139 Frederick the Great kiwi #> 140 Frederick the Great kiwi #> 141 Frederick the Great kiwi #> 142 Frederick the Great kiwi #> 143 Frederick the Great kiwi #> 144 Frederick the Great kiwi #> 145 Frederick the Great kiwi #> 146 Frederick the Great kiwi #> 147 Frederick the Great kiwi #> 148 Frederick the Great kiwi #> 149 Frederick the Great kiwi #> 150 Frederick the Great kiwi #> 151 Frederick the Great kiwi #> 152 Frederick the Great kiwi #> 153 Frederick the Great kiwi #> 154 Frederick the Great kiwi #> 155 Frederick the Great kiwi #> 156 Frederick the Great kiwi #> 157 Frederick the Great kiwi #> 158 Frederick the Great kiwi #> 159 Frederick the Great kiwi #> 160 Frederick the Great kiwi #> 161 Frederick the Great kiwi #> 162 Frederick the Great kiwi #> 163 Frederick the Great kiwi #> 164 Frederick the Great kiwi #> 165 Frederick the Great kiwi #> 166 Frederick the Great kiwi #> 167 Frederick the Great kiwi #> 168 Frederick the Great kiwi #> 169 Frederick the Great kiwi #> 170 Frederick the Great kiwi #> 171 Frederick the Great kiwi #> 172 Frederick the Great kiwi #> 173 Frederick the Great kiwi #> 174 Frederick the Great kiwi #> 175 Frederick the Great kiwi #> 176 Frederick the Great kiwi #> 177 Frederick the Great kiwi #> 178 Frederick the Great kiwi #> 179 Frederick the Great kiwi #> 180 Frederick the Great kiwi #> 181 Frederick the Great kiwi #> 182 Frederick the Great kiwi #> 183 Frederick the Great kiwi #> 184 Frederick the Great kiwi #> 185 Frederick the Great kiwi #> 186 Frederick the Great kiwi #> 187 Frederick the Great kiwi #> 188 Frederick the Great kiwi #> 189 Frederick the Great kiwi #> 190 Frederick the Great kiwi #> 191 Frederick the Great kiwi #> 192 Frederick the Great kiwi #> 193 Frederick the Great kiwi #> 194 Frederick the Great kiwi #> 195 Frederick the Great kiwi #> 196 Frederick the Great kiwi #> 197 Frederick the Great kiwi #> 198 Frederick the Great kiwi #> 199 Frederick the Great kiwi #> 200 Frederick the Great kiwi #> 201 Frederick the Great kiwi #> 202 Frederick the Great kiwi #> 203 Frederick the Great kiwi #> 204 Frederick the Great kiwi #> 205 Frederick the Great kiwi #> 206 Frederick the Great kiwi #> 207 Frederick the Great kiwi #> 208 Frederick the Great kiwi #> 209 Frederick the Great kiwi #> 210 Frederick the Great kiwi #> 211 Frederick the Great kiwi #> 212 Frederick the Great kiwi #> 213 Frederick the Great kiwi #> 214 Frederick the Great kiwi #> 215 Frederick the Great kiwi #> 216 Frederick the Great kiwi #> 217 Frederick the Great kiwi #> 218 Frederick the Great kiwi #> 219 Frederick the Great kiwi #> 220 Frederick the Great kiwi #> 221 Frederick the Great kiwi #> 222 Frederick the Great kiwi #> 223 Frederick the Great kiwi #> 224 Frederick the Great kiwi #> 225 Frederick the Great kiwi #> 226 Frederick the Great kiwi #> 227 Frederick the Great kiwi #> 228 Frederick the Great kiwi #> 229 Frederick the Great kiwi #> 230 Frederick the Great kiwi #> 231 Frederick the Great kiwi #> 232 Frederick the Great kiwi #> 233 Frederick the Great kiwi #> 234 Frederick the Great kiwi #> 235 Frederick the Great kiwi #> 236 Frederick the Great kiwi #> 237 Frederick the Great kiwi #> 238 Frederick the Great kiwi #> 239 Frederick the Great kiwi #> 240 Frederick the Great kiwi #> 241 Frederick the Great kiwi #> 242 Frederick the Great kiwi #> 243 Frederick the Great kiwi #> 244 Frederick the Great kiwi #> 245 Frederick the Great kiwi #> 246 Frederick the Great kiwi #> 247 Frederick the Great kiwi #> 248 Frederick the Great kiwi #> 249 Frederick the Great kiwi #> 250 Frederick the Great kiwi #> 251 Frederick the Great kiwi #> 252 Frederick the Great kiwi #> 253 Frederick the Great kiwi #> 254 Frederick the Great kiwi #> 255 Frederick the Great kiwi #> 256 Frederick the Great kiwi #> 257 Frederick the Great kiwi #> 258 Frederick the Great kiwi #> 259 Frederick the Great kiwi #> 260 Frederick the Great kiwi #> 261 Frederick the Great kiwi #> 262 Frederick the Great kiwi #> 263 Frederick the Great kiwi #> 264 Frederick the Great kiwi #> 265 Frederick the Great kiwi #> 266 Frederick the Great kiwi #> 267 Frederick the Great kiwi #> 268 Frederick the Great kiwi #> 269 Frederick the Great kiwi #> 270 Frederick the Great kiwi #> 271 Frederick the Great kiwi #> 272 Frederick the Great kiwi #> 273 Frederick the Great kiwi #> 274 Frederick the Great kiwi #> 275 Frederick the Great kiwi #> 276 Frederick the Great kiwi #> 277 Frederick the Great kiwi #> 278 Frederick the Great kiwi #> 279 Frederick the Great kiwi #> 280 Frederick the Great kiwi #> 281 Frederick the Great kiwi #> 282 Frederick the Great kiwi #> 283 Frederick the Great kiwi #> 284 Frederick the Great kiwi #> 285 Frederick the Great kiwi #> 286 Frederick the Great kiwi #> 287 Frederick the Great kiwi #> 288 Frederick the Great kiwi #> 289 Frederick the Great kiwi #> 290 Frederick the Great kiwi #> 291 Frederick the Great kiwi #> 292 Frederick the Great kiwi #> 293 Frederick the Great kiwi #> 294 Frederick the Great kiwi #> 295 Frederick the Great kiwi #> 296 Frederick the Great kiwi #> 297 Frederick the Great kiwi #> 298 Frederick the Great kiwi #> 299 Frederick the Great kiwi #> 300 Frederick the Great kiwi #> 301 Frederick the Great kiwi #> 302 Frederick the Great kiwi #> 303 Frederick the Great kiwi #> 304 Frederick the Great kiwi #> 305 Frederick the Great kiwi #> 306 Frederick the Great kiwi #> 307 Frederick the Great kiwi #> 308 Frederick the Great kiwi #> 309 Frederick the Great kiwi #> 310 Frederick the Great kiwi #> 311 Frederick the Great kiwi #> 312 Frederick the Great kiwi #> 313 Frederick the Great kiwi #> 314 Frederick the Great kiwi #> 315 Frederick the Great kiwi #> 316 Frederick the Great kiwi #> 317 Frederick the Great kiwi #> 318 Frederick the Great kiwi #> 319 Frederick the Great kiwi #> 320 Frederick the Great kiwi #> 321 Frederick the Great kiwi #> 322 Frederick the Great kiwi #> 323 Frederick the Great kiwi #> 324 Frederick the Great kiwi #> 325 Frederick the Great kiwi #> 326 Frederick the Great kiwi #> 327 Frederick the Great kiwi #> 328 Frederick the Great kiwi #> 329 Frederick the Great kiwi #> 330 Frederick the Great kiwi #> 331 Frederick the Great kiwi #> 332 Frederick the Great kiwi #> 333 Frederick the Great kiwi #> 334 Frederick the Great kiwi #> 335 Frederick the Great kiwi #> 336 Frederick the Great kiwi #> 337 Frederick the Great kiwi #> 338 Frederick the Great kiwi #> 339 Frederick the Great kiwi #> 340 Frederick the Great kiwi #> 341 Frederick the Great kiwi #> 342 Frederick the Great kiwi #> 343 Frederick the Great kiwi #> 344 Frederick the Great kiwi #> 345 Frederick the Great kiwi #> 346 Frederick the Great kiwi #> 347 Frederick the Great kiwi #> 348 Frederick the Great kiwi #> 349 Frederick the Great kiwi #> 350 Frederick the Great kiwi #> 351 Frederick the Great kiwi #> 352 Frederick the Great kiwi #> 353 Frederick the Great kiwi #> 354 Frederick the Great kiwi #> 355 Frederick the Great kiwi #> 356 Frederick the Great kiwi #> 357 Frederick the Great kiwi #> 358 Frederick the Great kiwi #> 359 Frederick the Great kiwi #> 360 Frederick the Great kiwi #> 361 Frederick the Great kiwi #> 362 Frederick the Great kiwi #> 363 Frederick the Great kiwi #> 364 Frederick the Great kiwi #> 365 Frederick the Great kiwi #> 366 Frederick the Great kiwi #> 367 Frederick the Great kiwi #> 368 Frederick the Great kiwi #> 369 Frederick the Great kiwi #> 370 Frederick the Great kiwi #> 371 Frederick the Great kiwi #> 372 Frederick the Great kiwi #> 373 Frederick the Great kiwi #> 374 Frederick the Great kiwi #> 375 Frederick the Great kiwi #> 376 Frederick the Great kiwi #> 377 Frederick the Great kiwi #> 378 Frederick the Great kiwi #> 379 Frederick the Great kiwi #> 380 Frederick the Great kiwi #> 381 Frederick the Great kiwi #> 382 Frederick the Great kiwi #> 383 Frederick the Great kiwi #> 384 Frederick the Great kiwi #> 385 Frederick the Great kiwi #> 386 Frederick the Great kiwi #> 387 Frederick the Great kiwi #> 388 Frederick the Great kiwi #> 389 Frederick the Great kiwi #> 390 Frederick the Great kiwi #> 391 Frederick the Great kiwi #> 392 Frederick the Great kiwi #> 393 Frederick the Great kiwi #> 394 Frederick the Great kiwi #> 395 Frederick the Great kiwi #> 396 Frederick the Great kiwi #> 397 Frederick the Great kiwi #> 398 Frederick the Great kiwi #> 399 Frederick the Great kiwi #> 400 Frederick the Great kiwi #> 401 Frederick the Great kiwi #> 402 Frederick the Great kiwi #> 403 Frederick the Great kiwi #> 404 Frederick the Great kiwi #> 405 Frederick the Great kiwi #> 406 Frederick the Great kiwi #> 407 Frederick the Great kiwi #> 408 Frederick the Great kiwi #> 409 Frederick the Great kiwi #> 410 Frederick the Great kiwi #> 411 Frederick the Great kiwi #> 412 Frederick the Great kiwi #> 413 Frederick the Great kiwi #> 414 Frederick the Great kiwi #> 415 Frederick the Great kiwi #> 416 Frederick the Great kiwi #> 417 Frederick the Great kiwi #> 418 Frederick the Great kiwi #> 419 Frederick the Great kiwi #> 420 Frederick the Great kiwi #> 421 Frederick the Great kiwi #> 422 Frederick the Great kiwi #> 423 Frederick the Great kiwi #> 424 Frederick the Great kiwi #> 425 Frederick the Great kiwi #> 426 Frederick the Great kiwi #> 427 Frederick the Great kiwi #> 428 Frederick the Great kiwi #> 429 Frederick the Great kiwi #> 430 Frederick the Great kiwi #> 431 Frederick the Great kiwi #> 432 Frederick the Great kiwi #> 433 Frederick the Great kiwi #> 434 Frederick the Great kiwi #> 435 Frederick the Great kiwi #> 436 Frederick the Great kiwi #> 437 Frederick the Great kiwi #> 438 Frederick the Great kiwi #> 439 Frederick the Great kiwi #> 440 Frederick the Great kiwi #> 441 Frederick the Great kiwi #> 442 Frederick the Great kiwi #> 443 Frederick the Great kiwi #> 444 Frederick the Great kiwi #> 445 Frederick the Great kiwi #> 446 Frederick the Great kiwi #> 447 Frederick the Great kiwi #> 448 Frederick the Great kiwi #> 449 Frederick the Great kiwi #> 450 Frederick the Great kiwi #> 451 Frederick the Great kiwi #> 452 Frederick the Great kiwi #> 453 Frederick the Great kiwi #> 454 Frederick the Great kiwi #> 455 Frederick the Great kiwi #> 456 Frederick the Great kiwi #> 457 Frederick the Great kiwi #> 458 Frederick the Great kiwi #> 459 Frederick the Great kiwi #> 460 Frederick the Great kiwi #> 461 Frederick the Great kiwi #> 462 Frederick the Great kiwi #> 463 Frederick the Great kiwi #> 464 Frederick the Great kiwi #> 465 Frederick the Great kiwi #> 466 Frederick the Great kiwi #> 467 Frederick the Great kiwi #> 468 Frederick the Great kiwi #> 469 Frederick the Great kiwi #> 470 Frederick the Great kiwi #> 471 Frederick the Great kiwi #> 472 Frederick the Great kiwi #> 473 Frederick the Great kiwi # } if (FALSE) { flytable_query(paste(\"SELECT root_id, supervoxel_id FROM info limit 5\")) }"},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"Fetch (memoised) flywire cell type information flytable","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"","code":"flytable_cell_types( pattern = NULL, version = NULL, timestamp = NULL, target = c(\"type\", \"cell_type\", \"hemibrain_type\", \"cell_class\", \"super_class\", \"ito_lee_hemilineage\", \"all\"), table = c(\"info\", \"optic\", \"both\"), transfer_hemibrain_type = c(\"extra\", \"none\", \"all\"), cache = TRUE, use_static = NA )"},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"pattern Optional character vector specifying pattern cell types must match SQL LIKE statement executed flytable_query. suffix _L _R can used restricted neurons annotated L R hemisphere. See examples. version optional CAVE materialisation version number. See flywire_cave_query details. Note also special signalling value TRUE implies latest locally available connectome dump. timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. target character vector specifying flytable columns pattern match. special value type means either cell_type hemibrain_type match. special value means match cell_type, hemibrain_type, cell_class. table cell type information tables use (info brain, optic optic lobes ). transfer_hemibrain_type Whether transfer hemibrain_type column cell_type (default TRUE, see details) cache Whether cache results 5m (default TRUE since flytable query little expensive) use_static Whether use static cell type information (Schlegel et al)","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"original data.frame left joined appropriate rows flytable.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"transfer_hemibrain_type=TRUE, hemibrain_type values transferred cell_type column cell_type empty. seems SQL LIKE searches (e.g. containing % symbol) work ito_lee_hemilineage column. can still search exact matches use full regular expression queries (operate downloading rows filtering machine). Static cell type information provided Schlegel et 2023. See flywire_annotations github repository. used default connection pre-release Cambridge flytable available specified options(fafbseg.use_static_celltypes=TRUE). Note presently one materialisation version (630) supported static data.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"","code":"# \\donttest{ flytable_cell_types(\"MBON%\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940624185095 79448854932107696 left intrinsic central MBON #> 2 720575940623472716 80011942324010318 right intrinsic central MBON #> 3 720575940638526278 80715286101144676 right intrinsic central MBON #> 4 720575940629585602 81137979670302132 right intrinsic central MBON #> 5 720575940637934308 81349085835581377 right intrinsic central MBON #> 6 720575940632118343 78744342923662254 left intrinsic central MBON #> 7 720575940609959637 78603948898007978 left intrinsic central MBON #> 8 720575940638163428 78111986298788517 left intrinsic central MBON #> 9 720575940630496374 81349223341739625 right intrinsic central MBON #> 10 720575940642142861 78393323903110735 left intrinsic central MBON #> 11 720575940611344078 80223254782485510 right intrinsic central MBON #> 12 720575940634822751 81277549061520124 right intrinsic central MBON #> 13 720575940617552340 79588561627810154 right intrinsic central MBON #> 14 720575940624280328 81489685951698728 right intrinsic central MBON #> 15 720575940617567206 78180912067538056 left intrinsic central MBON #> 16 720575940643700640 80152611093049624 right intrinsic central MBON #> 17 720575940615221811 81137979670297348 right intrinsic central MBON #> 18 720575940614026193 80154466519131949 right intrinsic central MBON #> 19 720575940633209647 78463486488950059 left intrinsic central MBON #> 20 720575940623001480 80154535238527400 right intrinsic central MBON #> 21 720575940613070485 81066305390179956 right intrinsic central MBON #> 22 720575940614595218 78040449457502610 left intrinsic central MBON #> 23 720575940636992368 80785654845309410 right intrinsic central MBON #> 24 720575940621828443 79166830266640003 left intrinsic central MBON #> 25 720575940637902938 78181599128215629 left intrinsic central MBON #> 26 720575940638774606 78040449457461921 left intrinsic central MBON #> 27 720575940639697827 80224766543977933 right intrinsic central MBON #> 28 720575940626833021 78251349531485275 left intrinsic central MBON #> 29 720575940618008859 77901086224032815 left intrinsic central MBON #> 30 720575940635841143 78110818201436707 left intrinsic central MBON #> 31 720575940618249797 80082723452177136 right intrinsic central MBON #> 32 720575940629856515 77408917331762608 left intrinsic central MBON #> 33 720575940623905719 80224972702135904 right intrinsic central MBON #> 34 720575940629529722 78533992672102680 left intrinsic central MBON #> 35 720575940624659943 80011255129536552 left intrinsic central MBON #> 36 720575940624590316 79167173863853528 right intrinsic central MBON #> 37 720575940645304430 79380479052758063 left intrinsic central MBON #> 38 720575940612196850 81136880426746412 right intrinsic central MBON #> 39 720575940630767959 78251486970442209 left intrinsic central MBON #> 40 720575940640963747 76985537105536911 left intrinsic central MBON #> 41 720575940628757547 78040449457463315 left intrinsic central MBON #> 42 720575940627144069 79166692827138268 right intrinsic central MBON #> 43 720575940610647416 81137979602919932 right intrinsic central MBON #> 44 720575940622093436 81136880426744139 right intrinsic central MBON #> 45 720575940624696810 78110818201651448 left intrinsic central MBON #> 46 720575940629422086 77760348668670642 left intrinsic central MBON #> 47 720575940647328900 81137979670303492 right intrinsic central MBON #> 48 720575940650386553 78110818201681795 left intrinsic central MBON #> 49 720575940639556467 81067610926141558 right intrinsic central MBON #> 50 720575940636120986 81700242831237167 right intrinsic central MBON #> 51 720575940617749538 80786135881765925 right intrinsic central MBON #> 52 720575940617760257 81277549061455173 right intrinsic central MBON #> 53 720575940619810389 79518055445188833 right intrinsic central MBON #> 54 720575940634482783 81136605414678093 right intrinsic central MBON #> 55 720575940644615716 78182286188838645 left intrinsic central MBON #> 56 720575940626109315 81066305390093306 right intrinsic central MBON #> 57 720575940623377802 78110818201621392 left intrinsic central MBON #> 58 720575940626744921 81277549061481189 right intrinsic central MBON #> 59 720575940623464316 81136880426764424 right intrinsic central MBON #> 60 720575940622979277 79027192356412856 left intrinsic central MBON #> 61 720575940614892182 81277617781167541 right intrinsic central MBON #> 62 720575940620715224 78111917579300796 left intrinsic central MBON #> 63 720575940613090673 78324741798855874 left intrinsic central MBON #> 64 720575940621777391 81137979736901319 right intrinsic central MBON #> 65 720575940606953858 81136880426735755 right intrinsic central MBON #> 66 720575940630075703 79309972869657633 left intrinsic central MBON #> 67 720575940652390134 78603949099622269 left intrinsic central MBON #> 68 720575940632535756 79380204241413766 left intrinsic central MBON #> 69 720575940643696288 79309904216692475 left intrinsic central MBON #> 70 720575940620162718 78323023677138555 left intrinsic central MBON #> 71 720575940635063135 80082242348953693 right intrinsic central MBON #> 72 720575940616463477 77830305364995511 left intrinsic central MBON #> 73 720575940629981440 78885355625276424 left intrinsic central MBON #> 74 720575940623182847 78463211409646517 left intrinsic central MBON #> 75 720575940626315010 79943222847625326 right intrinsic central MBON #> 76 720575940632943277 80925980016963911 right intrinsic central MBON #> 77 720575940624539284 78040449457553649 left intrinsic central MBON #> 78 720575940626180878 80011530007496199 left intrinsic central MBON #> 79 720575940628783363 80434292093847745 right intrinsic central MBON #> 80 720575940643309197 79870998677653042 left intrinsic central MBON #> 81 720575940614392999 79237542540872430 left intrinsic central MBON #> 82 720575940617302365 78604086538417636 left intrinsic central MBON #> 83 720575940635651680 81277549061591572 right intrinsic central MBON #> 84 720575940624694503 79941230049538531 left intrinsic central MBON #> 85 720575940628734376 79869899232522382 right intrinsic central MBON #> 86 720575940610964946 81630904409213619 right intrinsic central MBON #> 87 720575940607155890 80433124332533007 right intrinsic central MBON #> 88 720575940623381956 80644779918075196 right intrinsic central MBON #> 89 720575940628487813 81560466945525625 right intrinsic central MBON #> 90 720575940638028607 81419592152467685 right intrinsic central MBON #> 91 720575940621164720 80222636373797362 left intrinsic central MBON #> 92 720575940623841463 78251349531447591 left intrinsic central MBON #> 93 720575940631177803 78814711734490195 left intrinsic central MBON #> 94 720575940622306625 79166761480079751 right intrinsic central MBON #> 95 720575940616398303 79729161744437991 left intrinsic central MBON #> 96 720575940623750325 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON02 glutamate putative_primary MBON02 FBbt_00111012 #> 2 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 3 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 4 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 5 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 6 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 7 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 8 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 9 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 10 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 11 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 12 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 13 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 14 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 15 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 16 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 17 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 18 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 19 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 20 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 21 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 22 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 23 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 24 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 25 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 26 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 27 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 28 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 29 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 30 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 31 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 32 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 33 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 34 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 35 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 36 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 37 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 38 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 39 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 40 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 41 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 42 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 43 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 44 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 45 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 46 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 47 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 48 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 49 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 50 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 51 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 52 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 53 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 54 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 55 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 56 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 57 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 58 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 59 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 60 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 61 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 62 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 63 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 64 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 65 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 66 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 67 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 68 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 69 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 70 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 71 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 72 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 73 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 74 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 75 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 76 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 77 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 78 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 79 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 80 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 81 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 82 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 83 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 84 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 85 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 86 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 87 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 88 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 89 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 90 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 91 MBON05 acetylcholine putative_primary MBON05 FBbt_00111004 #> 92 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 93 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 94 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 95 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 96 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 flytable_cell_types(\"MBON%\", version=450) #> Updating 92 ids #> flywire_rootid_cached: Looking up 92 missing keys #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940620475757 79448854932107696 left intrinsic central MBON #> 2 720575940635988581 80011942324010318 right intrinsic central MBON #> 3 720575940616047221 80715286101144676 right intrinsic central MBON #> 4 720575940638780494 81137979670302132 right intrinsic central MBON #> 5 720575940610014510 81349085835581377 right intrinsic central MBON #> 6 720575940608009737 78744342923662254 left intrinsic central MBON #> 7 720575940620520769 78603948898007978 left intrinsic central MBON #> 8 720575940621245680 78111986298788517 left intrinsic central MBON #> 9 720575940631910308 81349223341739625 right intrinsic central MBON #> 10 720575940612772579 78393323903110735 left intrinsic central MBON #> 11 720575940616240011 80223254782485510 right intrinsic central MBON #> 12 720575940624260839 81277549061520124 right intrinsic central MBON #> 13 720575940625496010 79588561627810154 right intrinsic central MBON #> 14 720575940621704361 81489685951698728 right intrinsic central MBON #> 15 720575940616298635 78180912067538056 left intrinsic central MBON #> 16 720575940621187056 80152611093049624 right intrinsic central MBON #> 17 720575940614206866 81137979670297348 right intrinsic central MBON #> 18 720575940621208820 80154466519131949 right intrinsic central MBON #> 19 720575940615431692 78463486488950059 left intrinsic central MBON #> 20 720575940639603584 80154535238527400 right intrinsic central MBON #> 21 720575940634657899 81066305390179956 right intrinsic central MBON #> 22 720575940630796363 78040449457502610 left intrinsic central MBON #> 23 720575940621196784 80785654845309410 right intrinsic central MBON #> 24 720575940617807429 79166830266640003 left intrinsic central MBON #> 25 720575940623046035 78181599128215629 left intrinsic central MBON #> 26 720575940638774606 78040449457461921 left intrinsic central MBON #> 27 720575940643518408 80224766543977933 right intrinsic central MBON #> 28 720575940625168528 78251349531485275 left intrinsic central MBON #> 29 720575940615443468 77901086224032815 left intrinsic central MBON #> 30 720575940635841143 78110818201436707 left intrinsic central MBON #> 31 720575940613049325 80082723452177136 right intrinsic central MBON #> 32 720575940627152712 77408917331762608 left intrinsic central MBON #> 33 720575940623615561 80224972702135904 right intrinsic central MBON #> 34 720575940624260583 78533992672102680 left intrinsic central MBON #> 35 720575940623189431 80011255129536552 left intrinsic central MBON #> 36 720575940628356611 79167173863853528 right intrinsic central MBON #> 37 720575940629103486 79380479052758063 left intrinsic central MBON #> 38 720575940626510729 81136880426746412 right intrinsic central MBON #> 39 720575940631573165 78251486970442209 left intrinsic central MBON #> 40 720575940627235215 76985537105536911 left intrinsic central MBON #> 41 720575940625623165 78040449457463315 left intrinsic central MBON #> 42 720575940641532557 79166692827138268 right intrinsic central MBON #> 43 720575940604965809 81137979602919932 right intrinsic central MBON #> 44 720575940604592300 81136880426744139 right intrinsic central MBON #> 45 720575940613666001 78110818201651448 left intrinsic central MBON #> 46 720575940620015275 77760348668670642 left intrinsic central MBON #> 47 720575940619587975 81137979670303492 right intrinsic central MBON #> 48 720575940636538480 78110818201681795 left intrinsic central MBON #> 49 720575940629528064 81067610926141558 right intrinsic central MBON #> 50 720575940630182467 81700242831237167 right intrinsic central MBON #> 51 720575940611534193 80786135881765925 right intrinsic central MBON #> 52 720575940624149908 81277549061455173 right intrinsic central MBON #> 53 720575940635705719 79518055445188833 right intrinsic central MBON #> 54 720575940634482783 81136605414678093 right intrinsic central MBON #> 55 720575940628680039 78182286188838645 left intrinsic central MBON #> 56 720575940626109315 81066305390093306 right intrinsic central MBON #> 57 720575940644139812 78110818201621392 left intrinsic central MBON #> 58 720575940654302881 81277549061481189 right intrinsic central MBON #> 59 720575940626786949 81136880426764424 right intrinsic central MBON #> 60 720575940611536241 79027192356412856 left intrinsic central MBON #> 61 720575940623018730 81277617781167541 right intrinsic central MBON #> 62 720575940635488623 78111917579300796 left intrinsic central MBON #> 63 720575940616286603 78324741798855874 left intrinsic central MBON #> 64 720575940621503265 81137979736901319 right intrinsic central MBON #> 65 720575940631189304 81136880426735755 right intrinsic central MBON #> 66 720575940617330945 79309972869657633 left intrinsic central MBON #> 67 720575940628523419 78603949099622269 left intrinsic central MBON #> 68 720575940610543826 79380204241413766 left intrinsic central MBON #> 69 720575940616968633 79309904216692475 left intrinsic central MBON #> 70 720575940623762923 78323023677138555 left intrinsic central MBON #> 71 720575940626901637 80082242348953693 right intrinsic central MBON #> 72 720575940623211498 77830305364995511 left intrinsic central MBON #> 73 720575940625816420 78885355625276424 left intrinsic central MBON #> 74 720575940619919531 78463211409646517 left intrinsic central MBON #> 75 720575940614532970 79943222847625326 right intrinsic central MBON #> 76 720575940643356064 80925980016963911 right intrinsic central MBON #> 77 720575940649242233 78040449457553649 left intrinsic central MBON #> 78 720575940619620487 80011530007496199 left intrinsic central MBON #> 79 720575940624835661 80434292093847745 right intrinsic central MBON #> 80 720575940625538110 79870998677653042 left intrinsic central MBON #> 81 720575940626706825 79237542540872430 left intrinsic central MBON #> 82 720575940605195878 78604086538417636 left intrinsic central MBON #> 83 720575940631910052 81277549061591572 right intrinsic central MBON #> 84 720575940608426197 79941230049538531 left intrinsic central MBON #> 85 720575940625222288 79869899232522382 right intrinsic central MBON #> 86 720575940620070278 81630904409213619 right intrinsic central MBON #> 87 720575940633688220 80433124332533007 right intrinsic central MBON #> 88 720575940613357096 80644779918075196 right intrinsic central MBON #> 89 720575940608355029 81560466945525625 right intrinsic central MBON #> 90 720575940624105196 81419592152467685 right intrinsic central MBON #> 91 720575940613666769 80222636373797362 left intrinsic central MBON #> 92 720575940605182822 78251349531447591 left intrinsic central MBON #> 93 720575940635161268 78814711734490195 left intrinsic central MBON #> 94 720575940631601292 79166761480079751 right intrinsic central MBON #> 95 720575940609440324 79729161744437991 left intrinsic central MBON #> 96 720575940604158124 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON02 glutamate putative_primary MBON02 FBbt_00111012 #> 2 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 3 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 4 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 5 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 6 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 7 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 8 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 9 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 10 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 11 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 12 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 13 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 14 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 15 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 16 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 17 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 18 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 19 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 20 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 21 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 22 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 23 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 24 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 25 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 26 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 27 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 28 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 29 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 30 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 31 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 32 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 33 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 34 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 35 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 36 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 37 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 38 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 39 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 40 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 41 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 42 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 43 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 44 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 45 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 46 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 47 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 48 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 49 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 50 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 51 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 52 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 53 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 54 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 55 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 56 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 57 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 58 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 59 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 60 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 61 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 62 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 63 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 64 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 65 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 66 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 67 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 68 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 69 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 70 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 71 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 72 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 73 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 74 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 75 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 76 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 77 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 78 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 79 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 80 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 81 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 82 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 83 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 84 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 85 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 86 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 87 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 88 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 89 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 90 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 91 MBON05 acetylcholine putative_primary MBON05 FBbt_00111004 #> 92 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 93 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 94 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 95 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 96 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 # the latest connectome dump, see flywire_connectome_data_version() if (FALSE) { flytable_cell_types(\"MBON%\", version=TRUE) } # two characters flytable_cell_types(\"MBON__\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940624185095 79448854932107696 left intrinsic central MBON #> 2 720575940623472716 80011942324010318 right intrinsic central MBON #> 3 720575940638526278 80715286101144676 right intrinsic central MBON #> 4 720575940629585602 81137979670302132 right intrinsic central MBON #> 5 720575940637934308 81349085835581377 right intrinsic central MBON #> 6 720575940632118343 78744342923662254 left intrinsic central MBON #> 7 720575940609959637 78603948898007978 left intrinsic central MBON #> 8 720575940638163428 78111986298788517 left intrinsic central MBON #> 9 720575940630496374 81349223341739625 right intrinsic central MBON #> 10 720575940642142861 78393323903110735 left intrinsic central MBON #> 11 720575940611344078 80223254782485510 right intrinsic central MBON #> 12 720575940617552340 79588561627810154 right intrinsic central MBON #> 13 720575940624280328 81489685951698728 right intrinsic central MBON #> 14 720575940617567206 78180912067538056 left intrinsic central MBON #> 15 720575940643700640 80152611093049624 right intrinsic central MBON #> 16 720575940615221811 81137979670297348 right intrinsic central MBON #> 17 720575940614026193 80154466519131949 right intrinsic central MBON #> 18 720575940633209647 78463486488950059 left intrinsic central MBON #> 19 720575940623001480 80154535238527400 right intrinsic central MBON #> 20 720575940614595218 78040449457502610 left intrinsic central MBON #> 21 720575940636992368 80785654845309410 right intrinsic central MBON #> 22 720575940621828443 79166830266640003 left intrinsic central MBON #> 23 720575940637902938 78181599128215629 left intrinsic central MBON #> 24 720575940638774606 78040449457461921 left intrinsic central MBON #> 25 720575940639697827 80224766543977933 right intrinsic central MBON #> 26 720575940626833021 78251349531485275 left intrinsic central MBON #> 27 720575940618008859 77901086224032815 left intrinsic central MBON #> 28 720575940635841143 78110818201436707 left intrinsic central MBON #> 29 720575940618249797 80082723452177136 right intrinsic central MBON #> 30 720575940629856515 77408917331762608 left intrinsic central MBON #> 31 720575940623905719 80224972702135904 right intrinsic central MBON #> 32 720575940629529722 78533992672102680 left intrinsic central MBON #> 33 720575940624590316 79167173863853528 right intrinsic central MBON #> 34 720575940645304430 79380479052758063 left intrinsic central MBON #> 35 720575940630767959 78251486970442209 left intrinsic central MBON #> 36 720575940610647416 81137979602919932 right intrinsic central MBON #> 37 720575940622093436 81136880426744139 right intrinsic central MBON #> 38 720575940629422086 77760348668670642 left intrinsic central MBON #> 39 720575940647328900 81137979670303492 right intrinsic central MBON #> 40 720575940639556467 81067610926141558 right intrinsic central MBON #> 41 720575940636120986 81700242831237167 right intrinsic central MBON #> 42 720575940617749538 80786135881765925 right intrinsic central MBON #> 43 720575940617760257 81277549061455173 right intrinsic central MBON #> 44 720575940634482783 81136605414678093 right intrinsic central MBON #> 45 720575940644615716 78182286188838645 left intrinsic central MBON #> 46 720575940626109315 81066305390093306 right intrinsic central MBON #> 47 720575940623377802 78110818201621392 left intrinsic central MBON #> 48 720575940626744921 81277549061481189 right intrinsic central MBON #> 49 720575940623464316 81136880426764424 right intrinsic central MBON #> 50 720575940622979277 79027192356412856 left intrinsic central MBON #> 51 720575940614892182 81277617781167541 right intrinsic central MBON #> 52 720575940620715224 78111917579300796 left intrinsic central MBON #> 53 720575940613090673 78324741798855874 left intrinsic central MBON #> 54 720575940621777391 81137979736901319 right intrinsic central MBON #> 55 720575940606953858 81136880426735755 right intrinsic central MBON #> 56 720575940630075703 79309972869657633 left intrinsic central MBON #> 57 720575940652390134 78603949099622269 left intrinsic central MBON #> 58 720575940632535756 79380204241413766 left intrinsic central MBON #> 59 720575940643696288 79309904216692475 left intrinsic central MBON #> 60 720575940620162718 78323023677138555 left intrinsic central MBON #> 61 720575940635063135 80082242348953693 right intrinsic central MBON #> 62 720575940616463477 77830305364995511 left intrinsic central MBON #> 63 720575940629981440 78885355625276424 left intrinsic central MBON #> 64 720575940623182847 78463211409646517 left intrinsic central MBON #> 65 720575940626315010 79943222847625326 right intrinsic central MBON #> 66 720575940632943277 80925980016963911 right intrinsic central MBON #> 67 720575940624539284 78040449457553649 left intrinsic central MBON #> 68 720575940626180878 80011530007496199 left intrinsic central MBON #> 69 720575940628783363 80434292093847745 right intrinsic central MBON #> 70 720575940643309197 79870998677653042 left intrinsic central MBON #> 71 720575940614392999 79237542540872430 left intrinsic central MBON #> 72 720575940617302365 78604086538417636 left intrinsic central MBON #> 73 720575940635651680 81277549061591572 right intrinsic central MBON #> 74 720575940624694503 79941230049538531 left intrinsic central MBON #> 75 720575940628734376 79869899232522382 right intrinsic central MBON #> 76 720575940610964946 81630904409213619 right intrinsic central MBON #> 77 720575940607155890 80433124332533007 right intrinsic central MBON #> 78 720575940623381956 80644779918075196 right intrinsic central MBON #> 79 720575940628487813 81560466945525625 right intrinsic central MBON #> 80 720575940638028607 81419592152467685 right intrinsic central MBON #> 81 720575940621164720 80222636373797362 left intrinsic central MBON #> 82 720575940623841463 78251349531447591 left intrinsic central MBON #> 83 720575940631177803 78814711734490195 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON02 glutamate putative_primary MBON02 FBbt_00111012 #> 2 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 3 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 4 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 5 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 6 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 7 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 8 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 9 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 10 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 11 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 12 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 13 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 14 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 15 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 16 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 17 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 18 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 19 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 20 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 21 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 22 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 23 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 24 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 25 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 26 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 27 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 28 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 29 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 30 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 31 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 32 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 33 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 34 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 35 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 36 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 37 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 38 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 39 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 40 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 41 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 42 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 43 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 44 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 45 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 46 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 47 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 48 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 49 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 50 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 51 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 52 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 53 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 54 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 55 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 56 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 57 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 58 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 59 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 60 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 61 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 62 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 63 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 64 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 65 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 66 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 67 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 68 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 69 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 70 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 71 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 72 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 73 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 74 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 75 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 76 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 77 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 78 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 79 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 80 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 81 MBON05 acetylcholine putative_primary MBON05 FBbt_00111004 #> 82 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 83 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 # at least one character flytable_cell_types(\"MBON_%\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940624185095 79448854932107696 left intrinsic central MBON #> 2 720575940623472716 80011942324010318 right intrinsic central MBON #> 3 720575940638526278 80715286101144676 right intrinsic central MBON #> 4 720575940629585602 81137979670302132 right intrinsic central MBON #> 5 720575940637934308 81349085835581377 right intrinsic central MBON #> 6 720575940632118343 78744342923662254 left intrinsic central MBON #> 7 720575940609959637 78603948898007978 left intrinsic central MBON #> 8 720575940638163428 78111986298788517 left intrinsic central MBON #> 9 720575940630496374 81349223341739625 right intrinsic central MBON #> 10 720575940642142861 78393323903110735 left intrinsic central MBON #> 11 720575940611344078 80223254782485510 right intrinsic central MBON #> 12 720575940634822751 81277549061520124 right intrinsic central MBON #> 13 720575940617552340 79588561627810154 right intrinsic central MBON #> 14 720575940624280328 81489685951698728 right intrinsic central MBON #> 15 720575940617567206 78180912067538056 left intrinsic central MBON #> 16 720575940643700640 80152611093049624 right intrinsic central MBON #> 17 720575940615221811 81137979670297348 right intrinsic central MBON #> 18 720575940614026193 80154466519131949 right intrinsic central MBON #> 19 720575940633209647 78463486488950059 left intrinsic central MBON #> 20 720575940623001480 80154535238527400 right intrinsic central MBON #> 21 720575940613070485 81066305390179956 right intrinsic central MBON #> 22 720575940614595218 78040449457502610 left intrinsic central MBON #> 23 720575940636992368 80785654845309410 right intrinsic central MBON #> 24 720575940621828443 79166830266640003 left intrinsic central MBON #> 25 720575940637902938 78181599128215629 left intrinsic central MBON #> 26 720575940638774606 78040449457461921 left intrinsic central MBON #> 27 720575940639697827 80224766543977933 right intrinsic central MBON #> 28 720575940626833021 78251349531485275 left intrinsic central MBON #> 29 720575940618008859 77901086224032815 left intrinsic central MBON #> 30 720575940635841143 78110818201436707 left intrinsic central MBON #> 31 720575940618249797 80082723452177136 right intrinsic central MBON #> 32 720575940629856515 77408917331762608 left intrinsic central MBON #> 33 720575940623905719 80224972702135904 right intrinsic central MBON #> 34 720575940629529722 78533992672102680 left intrinsic central MBON #> 35 720575940624659943 80011255129536552 left intrinsic central MBON #> 36 720575940624590316 79167173863853528 right intrinsic central MBON #> 37 720575940645304430 79380479052758063 left intrinsic central MBON #> 38 720575940612196850 81136880426746412 right intrinsic central MBON #> 39 720575940630767959 78251486970442209 left intrinsic central MBON #> 40 720575940640963747 76985537105536911 left intrinsic central MBON #> 41 720575940628757547 78040449457463315 left intrinsic central MBON #> 42 720575940627144069 79166692827138268 right intrinsic central MBON #> 43 720575940610647416 81137979602919932 right intrinsic central MBON #> 44 720575940622093436 81136880426744139 right intrinsic central MBON #> 45 720575940624696810 78110818201651448 left intrinsic central MBON #> 46 720575940629422086 77760348668670642 left intrinsic central MBON #> 47 720575940647328900 81137979670303492 right intrinsic central MBON #> 48 720575940650386553 78110818201681795 left intrinsic central MBON #> 49 720575940639556467 81067610926141558 right intrinsic central MBON #> 50 720575940636120986 81700242831237167 right intrinsic central MBON #> 51 720575940617749538 80786135881765925 right intrinsic central MBON #> 52 720575940617760257 81277549061455173 right intrinsic central MBON #> 53 720575940619810389 79518055445188833 right intrinsic central MBON #> 54 720575940634482783 81136605414678093 right intrinsic central MBON #> 55 720575940644615716 78182286188838645 left intrinsic central MBON #> 56 720575940626109315 81066305390093306 right intrinsic central MBON #> 57 720575940623377802 78110818201621392 left intrinsic central MBON #> 58 720575940626744921 81277549061481189 right intrinsic central MBON #> 59 720575940623464316 81136880426764424 right intrinsic central MBON #> 60 720575940622979277 79027192356412856 left intrinsic central MBON #> 61 720575940614892182 81277617781167541 right intrinsic central MBON #> 62 720575940620715224 78111917579300796 left intrinsic central MBON #> 63 720575940613090673 78324741798855874 left intrinsic central MBON #> 64 720575940621777391 81137979736901319 right intrinsic central MBON #> 65 720575940606953858 81136880426735755 right intrinsic central MBON #> 66 720575940630075703 79309972869657633 left intrinsic central MBON #> 67 720575940652390134 78603949099622269 left intrinsic central MBON #> 68 720575940632535756 79380204241413766 left intrinsic central MBON #> 69 720575940643696288 79309904216692475 left intrinsic central MBON #> 70 720575940620162718 78323023677138555 left intrinsic central MBON #> 71 720575940635063135 80082242348953693 right intrinsic central MBON #> 72 720575940616463477 77830305364995511 left intrinsic central MBON #> 73 720575940629981440 78885355625276424 left intrinsic central MBON #> 74 720575940623182847 78463211409646517 left intrinsic central MBON #> 75 720575940626315010 79943222847625326 right intrinsic central MBON #> 76 720575940632943277 80925980016963911 right intrinsic central MBON #> 77 720575940624539284 78040449457553649 left intrinsic central MBON #> 78 720575940626180878 80011530007496199 left intrinsic central MBON #> 79 720575940628783363 80434292093847745 right intrinsic central MBON #> 80 720575940643309197 79870998677653042 left intrinsic central MBON #> 81 720575940614392999 79237542540872430 left intrinsic central MBON #> 82 720575940617302365 78604086538417636 left intrinsic central MBON #> 83 720575940635651680 81277549061591572 right intrinsic central MBON #> 84 720575940624694503 79941230049538531 left intrinsic central MBON #> 85 720575940628734376 79869899232522382 right intrinsic central MBON #> 86 720575940610964946 81630904409213619 right intrinsic central MBON #> 87 720575940607155890 80433124332533007 right intrinsic central MBON #> 88 720575940623381956 80644779918075196 right intrinsic central MBON #> 89 720575940628487813 81560466945525625 right intrinsic central MBON #> 90 720575940638028607 81419592152467685 right intrinsic central MBON #> 91 720575940621164720 80222636373797362 left intrinsic central MBON #> 92 720575940623841463 78251349531447591 left intrinsic central MBON #> 93 720575940631177803 78814711734490195 left intrinsic central MBON #> 94 720575940622306625 79166761480079751 right intrinsic central MBON #> 95 720575940616398303 79729161744437991 left intrinsic central MBON #> 96 720575940623750325 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON02 glutamate putative_primary MBON02 FBbt_00111012 #> 2 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 3 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 4 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 5 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 6 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 7 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 8 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 9 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 10 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 11 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 12 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 13 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 14 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 15 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 16 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 17 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 18 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 19 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 20 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 21 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 22 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 23 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 24 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 25 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 26 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 27 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 28 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 29 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 30 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 31 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 32 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 33 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 34 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 35 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 36 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 37 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 38 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 39 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 40 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 41 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 42 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 43 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 44 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 45 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 46 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 47 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 48 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 49 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 50 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 51 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 52 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 53 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 54 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 55 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 56 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 57 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 58 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 59 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 60 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 61 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 62 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 63 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 64 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 65 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 66 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 67 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 68 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 69 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 70 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 71 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 72 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 73 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 74 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 75 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 76 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 77 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 78 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 79 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 80 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 81 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 82 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 83 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 84 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 85 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 86 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 87 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 88 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 89 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 90 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 91 MBON05 acetylcholine putative_primary MBON05 FBbt_00111004 #> 92 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 93 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 94 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 95 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 96 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 # range flytable_cell_types(\"MBON2[0-5]\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940611344078 80223254782485510 right intrinsic central MBON #> 2 720575940617567206 78180912067538056 left intrinsic central MBON #> 3 720575940623464316 81136880426764424 right intrinsic central MBON #> 4 720575940620715224 78111917579300796 left intrinsic central MBON #> 5 720575940613090673 78324741798855874 left intrinsic central MBON #> 6 720575940621777391 81137979736901319 right intrinsic central MBON #> 7 720575940606953858 81136880426735755 right intrinsic central MBON #> 8 720575940635063135 80082242348953693 right intrinsic central MBON #> 9 720575940616463477 77830305364995511 left intrinsic central MBON #> 10 720575940631177803 78814711734490195 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 2 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 3 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 4 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 5 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 6 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 7 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 8 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 9 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 10 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 # include side specification flytable_cell_types(\"DA2_lPN_R\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940639337461 80646154374848875 right intrinsic central ALPN #> 2 720575940628259407 81349910469210197 right intrinsic central ALPN #> 3 720575940624106442 80575785630612215 right intrinsic central ALPN #> 4 720575940622762995 80575785630553529 right intrinsic central ALPN #> 5 720575940622311704 80646154374760379 right intrinsic central ALPN #> 6 720575940610052266 80646154374867885 right intrinsic central ALPN #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 #> 2 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 #> 3 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 #> 4 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 #> 5 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 #> 6 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 # only the RHS MBON20 flytable_cell_types(\"MBON20_R\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940611344078 80223254782485510 right intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON20 gaba putative_primary MBON20 FBbt_00111013 # all RHS cells with class MBON flytable_cell_types(\"MBON_R\", target=\"cell_class\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940623472716 80011942324010318 right intrinsic central MBON #> 2 720575940638526278 80715286101144676 right intrinsic central MBON #> 3 720575940629585602 81137979670302132 right intrinsic central MBON #> 4 720575940637934308 81349085835581377 right intrinsic central MBON #> 5 720575940630496374 81349223341739625 right intrinsic central MBON #> 6 720575940611344078 80223254782485510 right intrinsic central MBON #> 7 720575940634822751 81277549061520124 right intrinsic central MBON #> 8 720575940617552340 79588561627810154 right intrinsic central MBON #> 9 720575940624280328 81489685951698728 right intrinsic central MBON #> 10 720575940643700640 80152611093049624 right intrinsic central MBON #> 11 720575940615221811 81137979670297348 right intrinsic central MBON #> 12 720575940614026193 80154466519131949 right intrinsic central MBON #> 13 720575940623001480 80154535238527400 right intrinsic central MBON #> 14 720575940613070485 81066305390179956 right intrinsic central MBON #> 15 720575940636992368 80785654845309410 right intrinsic central MBON #> 16 720575940639697827 80224766543977933 right intrinsic central MBON #> 17 720575940618249797 80082723452177136 right intrinsic central MBON #> 18 720575940623905719 80224972702135904 right intrinsic central MBON #> 19 720575940624590316 79167173863853528 right intrinsic central MBON #> 20 720575940612196850 81136880426746412 right intrinsic central MBON #> 21 720575940627144069 79166692827138268 right intrinsic central MBON #> 22 720575940610647416 81137979602919932 right intrinsic central MBON #> 23 720575940622093436 81136880426744139 right intrinsic central MBON #> 24 720575940647328900 81137979670303492 right intrinsic central MBON #> 25 720575940639556467 81067610926141558 right intrinsic central MBON #> 26 720575940636120986 81700242831237167 right intrinsic central MBON #> 27 720575940617749538 80786135881765925 right intrinsic central MBON #> 28 720575940617760257 81277549061455173 right intrinsic central MBON #> 29 720575940619810389 79518055445188833 right intrinsic central MBON #> 30 720575940634482783 81136605414678093 right intrinsic central MBON #> 31 720575940626109315 81066305390093306 right intrinsic central MBON #> 32 720575940626744921 81277549061481189 right intrinsic central MBON #> 33 720575940623464316 81136880426764424 right intrinsic central MBON #> 34 720575940614892182 81277617781167541 right intrinsic central MBON #> 35 720575940621777391 81137979736901319 right intrinsic central MBON #> 36 720575940606953858 81136880426735755 right intrinsic central MBON #> 37 720575940635063135 80082242348953693 right intrinsic central MBON #> 38 720575940626315010 79943222847625326 right intrinsic central MBON #> 39 720575940632943277 80925980016963911 right intrinsic central MBON #> 40 720575940628783363 80434292093847745 right intrinsic central MBON #> 41 720575940635651680 81277549061591572 right intrinsic central MBON #> 42 720575940628734376 79869899232522382 right intrinsic central MBON #> 43 720575940610964946 81630904409213619 right intrinsic central MBON #> 44 720575940607155890 80433124332533007 right intrinsic central MBON #> 45 720575940623381956 80644779918075196 right intrinsic central MBON #> 46 720575940628487813 81560466945525625 right intrinsic central MBON #> 47 720575940638028607 81419592152467685 right intrinsic central MBON #> 48 720575940622306625 79166761480079751 right intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 2 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 3 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 4 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 5 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 6 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 7 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 8 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 9 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 10 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 11 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 12 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 13 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 14 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 15 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 16 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 17 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 18 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 19 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 20 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 21 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 22 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 23 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 24 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 25 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 26 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 27 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 28 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 29 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 30 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 31 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 32 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 33 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 34 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 35 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 36 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 37 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 38 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 39 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 40 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 41 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 42 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 43 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 44 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 45 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 46 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 47 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 48 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 # anything with type *OR* class information cells=flytable_cell_types(target = 'all') # anything that mentions PN anywhere pncands=flytable_cell_types('%PN%', target = 'all') # }"},{"path":"https://natverse.org/fafbseg/reference/flytable_list_selected.html","id":null,"dir":"Reference","previous_headings":"","what":"List selected rows from flytable — flytable_list_selected","title":"List selected rows from flytable — flytable_list_selected","text":"List selected rows flytable","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_list_selected.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List selected rows from flytable — flytable_list_selected","text":"","code":"flytable_list_selected( ids = NULL, table = \"info\", fields = \"*\", idfield = \"root_id\", ... )"},{"path":"https://natverse.org/fafbseg/reference/flytable_list_selected.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List selected rows from flytable — flytable_list_selected","text":"ids One identifiers table name flytable table fields database columns return idfield field use key lookup ... Additional arguments passed flytable_query","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_list_selected.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List selected rows from flytable — flytable_list_selected","text":"dataframe containing selected rows / columns","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":null,"dir":"Reference","previous_headings":"","what":"Low level functions to access the flytable metadata service — flytable_login","title":"Low level functions to access the flytable metadata service — flytable_login","text":"flytable_login uses flytable user name email log service. flytable_set_token obtain store permanent seatable user-level API token. flytable_base returns base object (equivalent mysql database) allows access one tables, logging service necessary. returned base object give full access Python Base API allowing range row/column manipulations. flytable_alltables lists tables across flytables bases. flytable_columns returns name type regular columns base well default R type. Private columns _id included.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Low level functions to access the flytable metadata service — flytable_login","text":"","code":"flytable_login( url = \"https://flytable.mrc-lmb.cam.ac.uk/\", token = Sys.getenv(\"FLYTABLE_TOKEN\", unset = NA_character_) ) flytable_set_token(user, pwd, url = \"https://flytable.mrc-lmb.cam.ac.uk/\") flytable_base( table = NULL, base_name = NULL, workspace_id = NULL, url = \"https://flytable.mrc-lmb.cam.ac.uk/\", cached = TRUE ) flytable_alltables(ac = NULL, cached = TRUE) flytable_columns(table, base = NULL, cached = TRUE)"},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Low level functions to access the flytable metadata service — flytable_login","text":"url Optional URL server token normally retrieved FLYTABLE_TOKEN environment variable. user, pwd flytable user password used flytable_set_token obtain token table Character vector specifying table foe want base object. base_name Character vector specifying base workspace_id numeric id specifying workspace. Advanced use since can normally figure base_name. cached Whether use cached version response available. Set FALSE know tables added renamed session. ac Optional account object returned flytables_login base Optional character vector naming seatable base (recommended) Base object returned flytable_base (expert use). default value NULL rely table long unique across flytable server.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Low level functions to access the flytable metadata service — flytable_login","text":"flytable_login, Python Account object seatable api wrapped reticulate. flytable_base, Python Base object seatable api wrapped reticulate. data.frame containing base_name, workspace_id, table name table _id. flytable_columns data.frame containing columns name, type rtype","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Low level functions to access the flytable metadata service — flytable_login","text":"Besides initial setup (next paragraph), need use lower level functions directly. Instead recommend higher level functions flytable_query. order start using flytable, must get API token. seem convenient way seatable web interface can get one calling flytable_set_token flytable user password. step. Thereafter FLYTABLE_TOKEN environment variable set .Renviron file. flytable_base use flytable API token log service.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Low level functions to access the flytable metadata service — flytable_login","text":"","code":"if (FALSE) { flytable_login() } if (FALSE) { flytable_set_token(user='xxx@gmail.com', pwd='yyy') } if (FALSE) { hemilineages=flytable_base(base_name='hemilineages') # equivalent, but simpler since you only have to remember the table name hemilineages=flytable_base('fafb_hemilineages_survey') } # \\donttest{ flytable_alltables() #> base_name workspace_id name #> 1 maleCNS 111 cns_info #> 2 Orphan proofreading 44 v1 #> 3 Orphan proofreading 44 Table3 #> 4 Remainder proofreading 44 v1 #> 5 Remainder proofreading 44 add_proofreading_783 #> 6 Review 44 v1 #> 7 Review Catalog 44 v1 #> 8 Review Catalog 44 review_459 #> 9 LAL_orphan_linking 29 LAL_bodies #> 10 NO_orphan_linking 29 NO_bodies #> 11 Alan_Mathews_project 5 DL4R_downstream #> 12 Alan_Mathews_project 5 DL4L_downstream #> 13 Alan_Mathews_project 5 DL4_HB_downstream #> 14 Alan_Mathews_project 5 dl4_matches_fafb_r_hb #> 15 Alan_Mathews_project 5 dl4_matches_fafb #> 16 Alan_Mathews_project 5 dl4_matches_fafb_l_hb #> 17 Alan_Mathews_project 5 VL2R_downstream #> 18 Alan_Mathews_project 5 VL2L_downstream #> 19 Alan_Mathews_project 5 VL2_HB_downstream #> 20 Alan_Mathews_project 5 vl2_matches_fafb_r_hb #> 21 Alan_Mathews_project 5 vl2_matches_fafb #> 22 Alan_Mathews_project 5 Vilpn1_downstream #> 23 Alan_Mathews_project 5 Vilpn2_downstream #> 24 Alan_Mathews_project 5 vilpn1_HB_downstream #> 25 Alan_Mathews_project 5 vilpn2_HB_downstream #> 26 Alan_Mathews_project 5 vilpn1_ds_r #> 27 Alan_Mathews_project 5 vilpn1_ds_l #> 28 Alan_Mathews_project 5 vilpn2_ds_r #> 29 Alan_Mathews_project 5 vilpn2_ds_l #> 30 Alan_Mathews_project 5 vilpn1_matches_fafb #> 31 Alan_Mathews_project 5 vilpn1r_matches_fafbr_hb #> 32 Alan_Mathews_project 5 vilpn2r_matches_fafbr_hb #> 33 Alan_Mathews_project 5 vilpn2_matches_fafb #> 34 Alan_Mathews_project 5 vl2_matches_fafb_r_hb(copy) #> 35 Alan_Mathews_project 5 vilpn2r_matches_fafbr_hb(copy) #> 36 Alan_Mathews_project 5 vl2_matches_fafb(copy) #> 37 Alan_Mathews_project 5 vilpn1_fafb_matches(copy) #> 38 Alan_Mathews_project 5 cable_length #> 39 Alan_Mathews_project 5 prepostcable_dl4 #> 40 Alan_Mathews_project 5 prepostcable_vl2 #> 41 Alan_Mathews_project 5 prepostcable_vilpn2 #> 42 Alan_Mathews_project 5 PN_stats #> 43 Alan_Mathews_project 5 NBLAST_scores #> 44 Alan_Mathews_project 5 vilpn_matches_fafb(copy) #> 45 Alan_Mathews_project 5 vilpn_matches_1r_2l #> 46 Alan_Mathews_project 5 vilpn_matches_2r_1l #> 47 Alan_Mathews_project 5 vilpn_total #> 48 Alan_Mathews_project 5 dl4_norm #> 49 Alan_Mathews_project 5 vilpnlr_combo #> 50 Alan_Mathews_project 5 norm #> 51 Alan_Mathews_project 5 2022-04-20T19_03_21+00_00_0wpp #> 52 Alan_Mathews_project 5 misc #> 53 AL_library 5 AL_bodies #> 54 cam_proofreading 5 batches #> 55 cam_proofreading 5 FlyWire_neuron_list - for_flywire #> 56 CATMAID_proofreading 5 catmaid #> 57 CATMAID_proofreading 5 all_done #> 58 DO_NOT_USE_main 5 DO_NOT_USE_info #> 59 DO_NOT_USE_main 5 DO_NOT_USE_hemilineages #> 60 flywire_matching 5 flywire_right #> 61 flywire_matching 5 hemibrain2flywire #> 62 flywire_matching 5 hemibrain2flywire_rematch #> 63 flywire_matching 5 hemibrain2flywire_mirrored #> 64 flywire_matching 5 flywire_ALr_ALl #> 65 flywire_matching 5 new_singles #> 66 flywire_matching 5 new_singles_lr #> 67 flywire_matching 5 all_singletons #> 68 hemibrain 5 hb_info #> 69 hemibrain 5 hb_hemilineages #> 70 hemibrain_matching 5 type_matches #> 71 hemibrain_matching 5 MWP_LH_RHS_cell_typing #> 72 hemibrain_matching 5 MWP_LH_LHS_cell_typing_v_hb #> 73 hemibrain_matching 5 MWP_LH_LHS_cell_typing_v_rhs_flywire #> 74 hemibrain_matching 5 LH_LHS_hb_vs_RHS_conflict_table #> 75 hemibrain_matching 5 MWP_mega_df #> 76 hemibrain_matching 5 MWP_LH_stereotypy #> 77 hemibrain_matching 5 MWP_PM_YY_cell_typing #> 78 hemibrain_matching 5 post_GM #> 79 LH_library 5 LH_bodies #> 80 LH_library 5 _old_LH_bodies #> 81 main 5 info #> 82 main 5 hemilineages #> 83 main(lineage_backup) 5 lineage_project #> 84 MB_library 5 MB_bodies #> 85 MB_library 5 MB_bodies_RHS #> 86 meta 5 cb_numbers #> 87 optic_lobes 5 optic #> 88 test 5 testfruit #> 89 fanc_maleVNC_matching 123 Table3_nblast95_20 #> 90 fanc_maleVNC_matching 123 Table3_nblast95_30 #> 91 manc_maleCNS 123 Table1_nblast95_60_backup #> 92 manc_maleCNS 123 Table1_nblast95_60_backup2 #> 93 manc_maleCNS 123 Table1_nblast95_60 #> _id #> 1 96g5 #> 2 DHtk #> 3 0t5T #> 4 vlgx #> 5 9l9v #> 6 9JIF #> 7 Y9RH #> 8 SFd8 #> 9 wtpy #> 10 htKk #> 11 M4SW #> 12 P3aV #> 13 ip3N #> 14 jvT0 #> 15 0qC0 #> 16 8ZOA #> 17 Ikw9 #> 18 FCty #> 19 F9Sk #> 20 yP9j #> 21 dV47 #> 22 kcqG #> 23 4IO4 #> 24 qND2 #> 25 SvpB #> 26 ZCMx #> 27 IqEa #> 28 sikt #> 29 cxOO #> 30 UB2m #> 31 TuH0 #> 32 dZ2X #> 33 UYUu #> 34 K7hg #> 35 rrwF #> 36 1iG8 #> 37 935S #> 38 1Itd #> 39 Z738 #> 40 TKM9 #> 41 6D4l #> 42 p4KB #> 43 yJVR #> 44 7sqj #> 45 78cE #> 46 OE2j #> 47 iVH6 #> 48 14wl #> 49 dznE #> 50 A451 #> 51 J4ma #> 52 s6Oi #> 53 wNCm #> 54 0000 #> 55 FbAY #> 56 TYn5 #> 57 5mdz #> 58 BXTy #> 59 QGfh #> 60 Nscg #> 61 yN5a #> 62 LaYJ #> 63 2ThW #> 64 dwun #> 65 yHJb #> 66 wd66 #> 67 CXnQ #> 68 X2ZG #> 69 Sz01 #> 70 cpHc #> 71 NG0m #> 72 0Cl7 #> 73 Z5ea #> 74 8DAX #> 75 9yII #> 76 rRZE #> 77 q477 #> 78 pfDm #> 79 2PZZ #> 80 dvGc #> 81 f0ac #> 82 Z4SX #> 83 Nu8Q #> 84 K5lc #> 85 VR7q #> 86 0000 #> 87 Nato #> 88 0000 #> 89 7ve8 #> 90 EAqv #> 91 24bm #> 92 qea1 #> 93 kg2f # } # \\donttest{ flytable_columns(\"info\") #> name type rtype #> 1 supervoxel_id text character #> 2 root_id text character #> 3 pos_x number numeric #> 4 pos_y number numeric #> 5 pos_z number numeric #> 6 soma_x number numeric #> 7 soma_y number numeric #> 8 soma_z number numeric #> 9 nucleus_id number numeric #> 10 side single-select character #> 11 top_nt text character #> 12 top_nt_conf number numeric #> 13 ito_lee_hemilineage single-select character #> 14 hartenstein_hemilineage text character #> 15 flow text character #> 16 super_class text character #> 17 cell_class text character #> 18 cell_sub_class text character #> 19 cell_type text character #> 20 cell_type_source text character #> 21 fbbt_id text character #> 22 vfb_id text character #> 23 cb_type text character #> 24 hemibrain_match text character #> 25 hemibrain_type text character #> 26 hemibrain_type_source text character #> 27 malecns_match text character #> 28 malecns_match_source text character #> 29 reviewed_by text character #> 30 status single-select character #> 31 notes long-text character #> 32 lrcid text character #> 33 root_duplicated checkbox logical #> 34 proofread checkbox logical #> 35 root_last_modified date POSIXct #> 36 last_user last-modifier character #> 37 LM_match text character #> 38 LM_match_source text character #> 39 root_630 text character #> 40 root_783 text character #> 41 nerve single-select character #> 42 release_630 checkbox logical #> 43 release_783 checkbox logical #> 44 morphology_group text character #> 45 known_nt text character #> 46 known_nt_source text character #> data #> 1 NULL #> 2 NULL #> 3 number, dot, no #> 4 number, dot, no #> 5 number, dot, no #> 6 number, dot, no #> 7 number, dot, no #> 8 number, dot, no #> 9 number, 0, TRUE, FALSE, dot, no #> 10 center, #59CB74, #FFFFFF, 707150, #4EB867, left, #F4667C, #FFFFFF, 21928, #DC556A, right, #46A1FD, #FFFFFF, 666421, #3C8FE4, na, #4ECCCB, #FFFFFF, 488103 #> 11 FALSE, undefined #> 12 number, 2, FALSE, FALSE, dot, no #> 13 ADL25, #aaa, #000000, 819986, ADL26, #aaa, #000000, 919193, ADL27, #aaa, #000000, 109498, ADL28, #aaa, #000000, 957054, ADM09, #aaa, #000000, 130521, ADM11, #aaa, #000000, 531452, ADM12, #aaa, #000000, 168743, ALad1, #aaa, #000000, 598204, ALl1_dorsal, #aaa, #000000, 403005, ALl1_ventral, #aaa, #000000, 436910, ALlv1, #aaa, #000000, 511159, ALv1, #aaa, #000000, 840849, ALv2, #aaa, #000000, 974452, AOTUv1_medial, #aaa, #000000, 790264, AOTUv1_ventral, #aaa, #000000, 442853, AOTUv2, #aaa, #000000, 670976, AOTUv3_dorsal, #aaa, #000000, 313454, AOTUv3_ventral, #aaa, #000000, 69614, AOTUv4_dorsal, #aaa, #000000, 308944, AOTUv4_ventral, #aaa, #000000, 321043, AVL22, #aaa, #000000, 722933, AVL23, #aaa, #000000, 121546, AVL25, #aaa, #000000, 35613, AVL27, #aaa, #000000, 8745, AVM16, #aaa, #000000, 862786, AVM17, #aaa, #000000, 330386, AVM19, #aaa, #000000, 168929, AVM20, #aaa, #000000, 716823, AVM21, #aaa, #000000, 144063, CLp1, #aaa, #000000, 361572, CLp2, #aaa, #000000, 426046, CREa1_dorsal, #aaa, #000000, 431266, CREa1_ventral, #aaa, #000000, 138394, CREa2_medial, #aaa, #000000, 504873, CREa2_ventral, #aaa, #000000, 575424, DL1_dorsal, #aaa, #000000, 727120, DL1_ventral, #aaa, #000000, 690284, DL2_dorsal, #aaa, #000000, 140884, DL2_ventral, #aaa, #000000, 310772, DM1, #aaa, #000000, 681894, DM2, #aaa, #000000, 88295, DM2_dorsal, #aaa, #000000, 626036, DM3, #aaa, #000000, 39866, DM3_CX, #aaa, #000000, 586041, DM3_canonical, #aaa, #000000, 772662, DM3_lateral, #aaa, #000000, 643580, DM3_medial, #aaa, #000000, 784672, DM4_dorsal, #aaa, #000000, 617128, DM4_medial, #aaa, #000000, 679773, DM4_ventral, #aaa, #000000, 122933, DM5_dorsal, #aaa, #000000, 175466, DM5_ventral, #aaa, #000000, 963751, DM6, #aaa, #000000, 244601, DM6_dorsal, #aaa, #000000, 589874, DM6_inferior, #aaa, #000000, 442502, DM6_lateral, #aaa, #000000, 701347, DM6_medial, #aaa, #000000, 55166, DM6_ventral, #aaa, #000000, 250188, EBa1, #aaa, #000000, 656315, FLAa1, #aaa, #000000, 651426, FLAa2, #aaa, #000000, 156680, FLAa3, #aaa, #000000, 516710, LALv1, #aaa, #000000, 604466, LB0, #aaa, #000000, 345842, LB0_anterior, #aaa, #000000, 519161, LB12, #aaa, #000000, 112831, LB19, #aaa, #000000, 124622, LB23, #aaa, #000000, 150685, LB3, #aaa, #000000, 672428, LB5, #aaa, #000000, 358879, LB6, #aaa, #000000, 625446, LB7, #aaa, #000000, 643150, LB7_posterior, #aaa, #000000, 809156, LHa1, #aaa, #000000, 910788, LHa2, #aaa, #000000, 667511, LHa3, #aaa, #000000, 739277, LHd1, #aaa, #000000, 561176, LHd2, #aaa, #000000, 331974, LHl1, #aaa, #000000, 600796, LHl2_lateral, #aaa, #000000, 766960, LHl2_medial, #aaa, #000000, 886621, LHl3, #aaa, #000000, 990565, LHl4_anterior, #aaa, #000000, 430384, LHl4_posterior, #aaa, #000000, 831357, LHp1, #aaa, #000000, 202734, LHp2_lateral, #aaa, #000000, 483076, LHp2_medial, #aaa, #000000, 530919, MBp1, #aaa, #000000, 580860, MBp2, #aaa, #000000, 882629, MBp3, #aaa, #000000, 400019, MBp4, #aaa, #000000, 911444, MD0, #aaa, #000000, 778325, MD3, #aaa, #000000, 166730, MD_SA1, #aaa, #000000, 924667, MX12, #aaa, #000000, 266167, MX12_medial, #aaa, #000000, 201080, MX3, #aaa, #000000, 459574, MX7, #aaa, #000000, 315447, PBp1, #aaa, #000000, 923827, PDL25, #aaa, #000000, 741158, PDL26, #aaa, #000000, 137685, PDM26, #aaa, #000000, 546113, PDM32, #aaa, #000000, 998928, PDM33, #aaa, #000000, 513930, PDM34, #aaa, #000000, 585002, PSa1, #aaa, #000000, 119090, PSp1, #aaa, #000000, 509400, PSp2, #aaa, #000000, 245308, PSp3_dorsal, #aaa, #000000, 525301, PSp3_ventral, #aaa, #000000, 305464, PVL02, #aaa, #000000, 378736, PVL15, #aaa, #000000, 109937, PVL17, #aaa, #000000, 173088, PVM13, #aaa, #000000, 256717, PVM14, #aaa, #000000, 252725, PVM15, #aaa, #000000, 303423, SIPa1_dorsal, #aaa, #000000, 25514, SIPa1_ventral, #aaa, #000000, 950343, SIPp1, #aaa, #000000, 454037, SLPa&l1_anterior, #aaa, #000000, 692055, SLPa&l1_lateral, #aaa, #000000, 80274, SLPad1_anterior, #aaa, #000000, 797608, SLPad1_posterior, #aaa, #000000, 253192, SLPal1, #aaa, #000000, 137934, SLPal2_dorsal, #aaa, #000000, 604081, SLPal2_ventral, #aaa, #000000, 519197, SLPal3, #aaa, #000000, 919481, SLPal4, #aaa, #000000, 82841, SLPal5, #aaa, #000000, 623379, SLPav1_lateral, #aaa, #000000, 99481, SLPav1_medial, #aaa, #000000, 473276, SLPav2, #aaa, #000000, 324498, SLPav3, #aaa, #000000, 257038, SLPp&v1_posterior, #aaa, #000000, 51543, SLPp&v1_ventral, #aaa, #000000, 344955, SLPpl1, #aaa, #000000, 912263, SLPpl2, #aaa, #000000, 411606, SLPpl3, #aaa, #000000, 610066, SLPpm1, #aaa, #000000, 728496, SLPpm2, #aaa, #000000, 664395, SLPpm3, #aaa, #000000, 880997, SMPad1, #aaa, #000000, 719040, SMPad2, #aaa, #000000, 517718, SMPad3, #aaa, #000000, 20480, SMPp&v1_posterior, #aaa, #000000, 566750, SMPp&v1_ventral, #aaa, #000000, 218799, SMPpd1, #aaa, #000000, 480777, SMPpd2, #aaa, #000000, 735960, SMPpv1, #aaa, #000000, 116347, SMPpv2, #aaa, #000000, 782447, TRdl, #aaa, #000000, 67085, TRdm, #aaa, #000000, 126795, VESa1, #aaa, #000000, 694066, VESa2, #aaa, #000000, 214095, VLPa1_lateral, #aaa, #000000, 231042, VLPa1_medial, #aaa, #000000, 984989, VLPa2, #aaa, #000000, 256224, VLPd&p1_dorsal, #aaa, #000000, 718802, VLPd&p1_posterior, #aaa, #000000, 946964, VLPd1, #aaa, #000000, 659295, VLPl&d1_dorsal, #aaa, #000000, 314355, VLPl&d1_lateral, #aaa, #000000, 295490, VLPl&p1_lateral, #aaa, #000000, 757777, VLPl&p1_posterior, #aaa, #000000, 716311, VLPl&p2_lateral, #aaa, #000000, 277026, VLPl&p2_posterior, #aaa, #000000, 623102, VLPl1, #aaa, #000000, 501397, VLPl2_dorsal, #aaa, #000000, 53914, VLPl2_ventral, #aaa, #000000, 633998, VLPl4_dorsal, #aaa, #000000, 917914, VLPl4_ventral, #aaa, #000000, 217170, VLPp&l1_lateral, #aaa, #000000, 941299, VLPp&l1_posterior, #aaa, #000000, 7595, VLPp1, #aaa, #000000, 614935, VLPp2, #aaa, #000000, 816034, VPNd1, #aaa, #000000, 334196, VPNl&d1_dorsal, #aaa, #000000, 265620, VPNl&d1_lateral, #aaa, #000000, 971297, VPNp&v1_posterior, #aaa, #000000, 147127, VPNp&v1_ventral, #aaa, #000000, 677039, VPNp1_lateral, #aaa, #000000, 356514, VPNp1_medial, #aaa, #000000, 726617, WEDa1_dorsal, #aaa, #000000, 289847, WEDa1_ventral, #aaa, #000000, 578652, WEDa2, #aaa, #000000, 995569, WEDd1, #aaa, #000000, 521068, WEDd2, #aaa, #000000, 663295, new_clone_1, #aaa, #000000, 220838, new_clone_2, #aaa, #000000, 460867, new_clone_3, #aaa, #000000, 626699, new_clone_4, #aaa, #000000, 524170, 613654, SLPp&v1, #FBD44A, #FFFFFF, 500246, sensory, #46A1FD, #FFFFFF, 350369, DM1_CX1, #D7E8FF, #202428, 189612, DM1_SEZ, #DEF7C4, #202428, 481669, DM1_CX2, #DC82D2, #FFFFFF, 222402, DM1_CRE, #F4667C, #FFFFFF, needs_assigment, #F4667C, #FFFFFF, 491678, #DC556A, optic, #59CB74, #FFFFFF, 865758, 471218, DM2_ALT, #9F8CF1, #FFFFFF, 17271, DM2_CX_p, #EAA775, #FFFFFF, 324985, DM2_CX_v, #59CB74, #FFFFFF, 854446, DM3_CX_p, #DEF7C4, #202428, 306346, DM2_CX_d, #9860E5, #FFFFFF, DM1_CX_d, 536481, #46A1FD, #FFFFFF, 298311, DM1_CX_p, #D7E8FF, #202428, DM4_CX_d2, 81887, #FBD44A, #FFFFFF, DM4_CX_d3, 572727, #C2C2C2, #FFFFFF, DM3_CX_d1, 361124, #ADDF84, #FFFFFF, DM2_CX_d2, 891883, #DC82D2, #FFFFFF, DM2_CX_d1, 340460, #89D2EA, #FFFFFF, DM1_CX_d2, 594996, #F4667C, #FFFFFF, DM4_CX_d1, 967181, #9F8CF1, #FFFFFF, DM3_CX_d2, 116972, #EAA775, #FFFFFF, 402580, DM1_CX_v, #FFDDE5, #202428, 643080, DM3_CX_v, #FBD44A, #FFFFFF, 375589, DM4_CX_p, #FFDDE5, #202428, 205371, DM4_CX_v, #D7E8FF, #202428, DM£_cx_p, #9860E5, #FFFFFF, 818690, DM1_loSM, #46A1FD, #FFFFFF, 492623, 916866, LHp2, #D8FAFF, #202428, primary, #59CB74, #FFFFFF, 604797, putative_primary, #ADDF84, #FFFFFF, 23976, 445149, SLPal2, #89D2EA, #FFFFFF, 39423, LHl2, #F4667C, #FFFFFF, 793080, new_clone_5, #DDFFE6, #202428, 405583, LALv1_dorsal, #46A1FD, #FFFFFF, 370038, LALv1_ventral, #D7E8FF, #202428, 397095, LHl2_ventral, #DDFFE6, #202428, 710714, LHl2_dorsal, #B7CEF9, #202428, LB0_posterior, #C2C2C2, #FFFFFF, 32408, 534862, WEDa1, #46A1FD, #FFFFFF, seb, #DC82D2, #FFFFFF, 527295, 924833, new_clone_6, #DAD7FF, #202428, DM1_OL, #9860E5, #FFFFFF, 442700, 925417, CREa2_dorsal, #D7E8FF, #202428, 757382, VLPp&l1_intermediate, #EAA775, #FFFFFF, 12847, LB3__prim, #ADDF84, #FFFFFF, 720575940621734861, 497920, #9F8CF1, #FFFFFF, 468033, PSp3, #FFD4FF, #202428, 729648, TRdl_a, #FFD9C8, #202428, 663876, TRdl_b, #DDFFE6, #202428, 562672, MX0, #D7E8FF, #202428, VLPd1__prim, 463728, #F4667C, #FFFFFF, 458317, MX12__prim, #4ECCCB, #FFFFFF, 464745, LB7__prim, #FFFCB5, #202428, 673114, VLPp&l1__prim, #E9E9E9, #202428, 460071, MX7__prim, #FFDDE5, #202428, left, 767570, #46A1FD, #FFFFFF, AN_sensory, #9860E5, #FFFFFF, 770811, 192973, LN_sensory, #DAD7FF, #202428, 119081, aPN_sensory, #DAD7FF, #202428, 447259, ON_sensory, #B7CEF9, #202428, 739390, PN_sensory, #9F8CF1, #FFFFFF, 549916, SMPad2_prim, #D8FAFF, #202428, 975326, SMPp&v1_prim, #89D2EA, #FFFFFF, vlpl2-v, #DC82D2, #FFFFFF, 716489, vlpl7p1, #EAA775, #FFFFFF, 278892, 331845, SLPa&l1_prim, #EAA775, #FFFFFF, 909782, SLPal1_prim, #89D2EA, #FFFFFF, 329809, SLPad1_posterior_or_VLPd&p1_posterior, #FFD4FF, #202428, ptua, #C2C2C2, #FFFFFF, 85765, 431580, VLPa1_prim, #FBD44A, #FFFFFF, 36279, DM3__prim, #4ECCCB, #FFFFFF, 896397, DM4__prim, #FBD44A, #FFFFFF, 836945, DM6__prim, #FFD9C8, #202428, VLPa2__prim, #ADDF84, #FFFFFF, 521774, VLPa1__prim, #F4667C, #FFFFFF, 158068, SMPad2__prim, #46A1FD, #FFFFFF, 174816, SMPp&v1__prim, #9860E5, #FFFFFF, 167661, SLPa&l1__prim, #59CB74, #FFFFFF, 17217, SLPal1__prim, #EAA775, #FFFFFF, 43986, 172733, no_lineage, #FFD9C8, #202428, aotuv1_vn, #89D2EA, #FFFFFF, 489600, 27684, SLpav2, #9F8CF1, #FFFFFF, 598276, LHp3, #9860E5, #FFFFFF, 320500, CREl1, #FFD9C8, #202428, 768209, LALa1, #59CB74, #FFFFFF, 172236, SMPpm1, #FFDDE5, #202428, 743924, CLp1_or_SLPpm2, #59CB74, #FFFFFF, 340194, VLPl&d1_medial, #89D2EA, #FFFFFF, 395985, VLPl&d1_posterior, #ADDF84, #FFFFFF, 597064, VLPl2_posterior, #DC82D2, #FFFFFF, 375022, VLPl2_medial, #D7E8FF, #202428, 832640, SLPa&l1_medial, #DEF7C4, #202428, 685235, SLPa&l1_posterior, #DC82D2, #FFFFFF, 400165, LHl4_dorsal, #FFFCB5, #202428, 726853, VLPl4_anterior, #FFD4FF, #202428, 162052, VLPl&p2_anterior, #ADDF84, #FFFFFF, 610026, VLPl&p1_anterior, #FFD4FF, #202428, 397383, DM5_central, #FBD44A, #FFFFFF, 429742, DM6_dorso_lateral, #E9E9E9, #202428, 912751, DM6_central1, #F4667C, #FFFFFF, 610414, DM6_dorso_medial, #B7CEF9, #202428, 195122, VLPd&p1_anterior, #4ECCCB, #FFFFFF, 61607, SLPp&v1_anterior, #ADDF84, #FFFFFF, 489027, VLPp&l1_anterior, #FFD9C8, #202428, 999517, DM1_antero_dorsal, #DDFFE6, #202428, 741992, DM1_antero_ventral, #E9E9E9, #202428, 229517, DM1_dorsal, #B7CEF9, #202428, 941917, DM2_central, #DEF7C4, #202428, 898011, DM3_dorso_lateral, #FFD4FF, #202428, 397372, DM3_dorso_medial, #E9E9E9, #202428, 44197, DM3_posterior, #FFD9C8, #202428, 603980, VLPl1_or_VLPl5, #FFD4FF, #202428, 985402, DM6_posterior, #D7E8FF, #202428, 53388, LALa1_posterior, #EAA775, #FFFFFF, 38120, LALa1_anterior, #D7E8FF, #202428, SLPal3_or_SLPal4_dorsal, 965919, #C2C2C2, #FFFFFF, vlpl4_am, #F4667C, #FFFFFF, 685539, 807102, VPNl&d1_medial, #F4667C, #FFFFFF, 279229, DM6_IbSpsP, #9F8CF1, #FFFFFF, 212829, DM6_central2, #FFEAB6, #202428, SMPpv2_ventral, 791739, #4ECCCB, #FFFFFF, 472132, ALad1__prim, #EAA775, #FFFFFF, 337782, SMPpv2_dorsal, #FFDDE5, #202428, MD0__prim, 864257, #FBD44A, #FFFFFF, MX0__prim, 79006, #46A1FD, #FFFFFF, DILP__prim, 69103, #ADDF84, #FFFFFF, VLPl2_lateral, 764400, #DC82D2, #FFFFFF, DM1_posterior, 912445, #89D2EA, #FFFFFF, SLPal3_and_SLPal4_dorsal, 457802, #59CB74, #FFFFFF, VPNl&d1_medial_Lee, 711486, #F4667C, #FFFFFF, VPNd3, 285703, #9860E5, #FFFFFF, VPNd2, #C2C2C2, #FFFFFF, 861927, VPNv2, #4ECCCB, #FFFFFF, 808867, VPNp2, #9F8CF1, #FFFFFF, 165924, DM2_or_DM3_posterior, 60684, #EAA775, #FFFFFF, VPNv1, #FBD44A, #FFFFFF, 780536, VPNp3, #46A1FD, #FFFFFF, 248547, SLPpm4, 121448, #ADDF84, #FFFFFF, troll-b, #DC82D2, #FFFFFF, 744328, outa, #89D2EA, #FFFFFF, 89924, MTe49, 927894, #59CB74, #FFFFFF #> 14 NULL #> 15 FALSE, FALSE, , custom_format #> 16 FALSE, FALSE, , custom_format #> 17 NULL #> 18 FALSE, FALSE, , custom_format #> 19 NULL #> 20 FALSE, #> 21 FALSE, undefined #> 22 FALSE, FALSE, , custom_format #> 23 FALSE, FALSE, , custom_format #> 24 NULL #> 25 FALSE, #> 26 FALSE, #> 27 NULL #> 28 FALSE, #> 29 FALSE, undefined #> 30 adequate, #ADDF84, #FFFFFF, 615586, #9CCF72, complete, #59CB74, #FFFFFF, 399046, #4EB867, incomplete, #EAA775, #FFFFFF, 896972, #D59361, merge_error, #F4667C, #FFFFFF, 96230, #DC556A, needs_extending, #46A1FD, #FFFFFF, 654216, #3C8FE4, tiny, #E9E9E9, #202428, 11704, #DADADA, unassessed, #DAD7FF, #202428, 555449, #C3BEEF, unknown, #C2C2C2, #FFFFFF, 815844, #ADADAD, wrong_hemilineage, #FBD44A, #FFFFFF, 275663, #E5C142, wrong_side, #FFFCB5, #202428, 288083, #E8E79D, bad_nucleus, #DC82D2, #FFFFFF, #D166C5, 997771, duplicate, #4ECCCB, #FFFFFF, 230512, not_a_neuron, #9860E5, #FFFFFF, 953023, 367098, proofread, #FFD4FF, #202428, to_review, #59CB74, #FFFFFF, #4EB867, 478080, hard, #F4667C, #FFFFFF, 275338, tadpole, #FFDDE5, #202428, 295683, #EDC4C1, large_fragment, #89D2EA, #FFFFFF, 597301, 162109, NA, #DAD7FF, #202428, 463206, outlier_bio, #EAA775, #FFFFFF, 82369, outlier_seg, #B7CEF9, #202428, 78729, adequat, #FFD9C8, #202428, 527429, fragment, #9860E5, #FFFFFF, NEEDS4, #46A1FD, #FFFFFF, 835587 #> 31 FALSE #> 32 FALSE, undefined #> 33 NULL #> 34 NULL #> 35 YYYY-MM-DD HH:mm #> 36 NULL #> 37 FALSE, FALSE, , custom_format #> 38 FALSE, FALSE, , custom_format #> 39 FALSE, FALSE, , custom_format #> 40 FALSE, FALSE, , custom_format #> 41 NCC, #4ECCCB, #FFFFFF, #45BAB9, 197106, CV, #C2C2C2, #FFFFFF, #ADADAD, 467618, AN, #89D2EA, #FFFFFF, #7BC0D6, 329258, MxLbN, #F4667C, #FFFFFF, #DC556A, 771256, PhN, #FBD44A, #FFFFFF, #E5C142, 472174, aPhN, #DC82D2, #FFFFFF, #D166C5, 902576, 843153, ON, #FFD9C8, #202428, 129288, OCN, #FFFCB5, #202428 #> 42 FALSE, FALSE #> 43 FALSE, FALSE #> 44 FALSE, FALSE, , custom_format #> 45 FALSE, FALSE, , custom_format #> 46 FALSE, FALSE, , custom_format # }"},{"path":"https://natverse.org/fafbseg/reference/flytable_set_celltype.html","id":null,"dir":"Reference","previous_headings":"","what":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","title":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","text":"Set flytable cell type columns set root ids","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_set_celltype.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","text":"","code":"flytable_set_celltype( ids, cell_type = NULL, hemibrain_type = NULL, user = \"GJ\", supervoxel_id = NULL, DryRun = TRUE, table = c(\"info\", \"optic\"), copy_hemibrain_type = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flytable_set_celltype.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","text":"ids form understood flywire_ids. data.frame supervoxel_id column also present used ensure root ids efficiently mapped latest version. cell_type Character vector cell types - can either length 1 length ids. hemibrain_type also used set cell_type missing copy_hemibrain_type=TRUE user user initials (can vector length ids) supervoxel_id Supervoxel ids corresponding root ids argument. DryRun Default value (T) return dataframe used update table name flytable table update (currently support info (central brain) optic tables. copy_hemibrain_type recommendation now ** set cell_type hemibrain_type one provided, default FALSE. ... Additional columns update flytable","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_set_celltype.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","text":"default DryRun=TRUE can see happen apply changes. careful! Undoing changes hard, sometimes impossible exactly. doubt talk Greg, Philipp et al making programmatic updates. Since flytable always keeps root ids date (least every 30m), ids argument must mapped onto latest ids (using flywire_updateids) data can uploaded flytable. much efficient provide supervoxel id neuron.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable_set_celltype.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","text":"","code":"if (FALSE) { flytable_set_celltype('https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/4668606109450240', hemibrain_type = 'vLN25', fbbt_id='FBbt_20003784', DryRun = T) }"},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":null,"dir":"Reference","previous_headings":"","what":"Update or append rows in a flytable database — flytable_update_rows","title":"Update or append rows in a flytable database — flytable_update_rows","text":"flytable_update_rows updates existing rows table, returning TRUE success. flytable_append_rows appends data existing table, returning TRUE success. flytable_nrow returns number rows one flytable tables using SQL COUNT query.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update or append rows in a flytable database — flytable_update_rows","text":"","code":"flytable_update_rows( df, table, base = NULL, append_allowed = TRUE, chunksize = 1000L, ... ) flytable_append_rows(df, table, base = NULL, chunksize = 1000L, ...) flytable_nrow(table, base = NULL)"},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update or append rows in a flytable database — flytable_update_rows","text":"df data.frame containing data upload including _id column can identify row remote table. table Character vector naming table base Character vector naming seatable base (recommended) Base object returned flytable_base (expert use). append_allowed Whether rows without row identifiers can appended. chunksize split large requests smaller ones max many rows. ... Additional arguments passed pbsapply might include cl=2 specify number parallel jobs run.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update or append rows in a flytable database — flytable_update_rows","text":"Logical indicating success, invisibly (failures normally cause premature termination errors written console).","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Update or append rows in a flytable database — flytable_update_rows","text":"seatable automatically maintains unique id row _id column. returned flytable_query friends. modify data want update , need keep column containing row _id. need provide _id column appending new rows. Indeed get warning . chunksize argument required seems maximum 1000 rows per update action.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Update or append rows in a flytable database — flytable_update_rows","text":"","code":"if (FALSE) { fruit=flytable_list_rows('testfruit') flytable_update_rows(table='testfruit', fruit[1:2, c(1,4:6)]) } if (FALSE) { flytable_append_rows(table=\"testfruit\", data.frame(fruitname='lemon', person='David', nid=4)) }"},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":null,"dir":"Reference","previous_headings":"","what":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"flywire2fafb maps points FlyWire->FAFB fafb2flywire maps points FAFB->FlyWire","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"","code":"flywire2fafb( xyz, method = c(\"mapmany\", \"map1\"), chunksize = 40000, swap = FALSE, ... ) fafb2flywire( xyz, method = c(\"mapmany\", \"map1\"), chunksize = 40000, swap = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"xyz Nx3 matrix points method Whether map many points (default) just one chunksize number points send server mapping many points . swap TRUE applies deformation field opposite direction e.g. give coarse mapping points FAFB->FlyWire. wrong may useful. ... Additional arguments passed httr::GET/POST operation","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"Nx3 matrix points","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"Note can also access FlyWire<->FAFB bridging registrations via xform_brain series functions. allow transform kinds 3D data objects, whereas flywire2fafb function restricted plain 3D coordinates. See examples. Mapping single points unlikely useful, may wish adjust chunksize argument send points risk possible server timeouts. default value quite conservative. swap=TRUE displacements applied opposite direction intended. can used provide coarse inverse mapping feed FAFB points. wrong useful inverse mapping available can get closer right place FlyWire just assuming FAFB14 FlyWire space. works deformations mostly fairly smooth scale FAFB-FlyWire displacements. Operationally find residual displacements typically order 100 nm using procedure. Since 2020-08-08 real inverse available, now historical interest.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"","code":"# identified location in FAFB14 p.fafb.nm <- cbind(477042, 284535, 90680) p.fafb.raw <- p.fafb.nm/c(4,4,40) # corresponding location in FlyWire p.flywire.raw <- cbind(118865, 71338, 2267) p.flywire.nm <- p.flywire.raw * c(4,4,40) # check displacement flywire2fafb(p.flywire.nm)-p.fafb.nm #> X Y Z #> [1,] 3 -1 0 # check what happens when you apply the inverse fafb2flywire(p.fafb.nm)-p.flywire.nm #> X Y Z #> [1,] -3 2 0 data(\"AV4b1\", package='catmaid') set.seed(42) before=xyzmatrix(AV4b1)[sample(nvertices(AV4b1), size=2000), ] after=fafb2flywire(before) d=sqrt(rowSums((before-after)^2)) hist(d, br=20, main=\"FAFB14 - FlyWire Displacements\", xlab=\"d /nm\") if (FALSE) { AV4b1.flywire <- xform_brain(AV4b1, reference=\"FlyWire\", sample=\"FAFB14\") plot3d(neuronlist(AV4b1.flywire, AV4b1)) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"Get adjacency matrix predicted synaptic connectivity within set specific flywire bodies. can specify single pool ids separate input (upstream) output (downstream) ids. contrast flywire_partner_summary returns connections amongst defined set ids rather possible partners.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"","code":"flywire_adjacency_matrix( rootids = NULL, inputids = NULL, outputids = NULL, sparse = FALSE, remove_autapses = TRUE, cleft.threshold = 0, Verbose = interactive(), method = c(\"auto\", \"spine\", \"sqlite\") )"},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"rootids flywire root ids bodies fetch connectivity information. inputids, outputids identifiers input output bodies (use alternative rootids) sparse Whether return sparse matrix (default FALSE) remove_autapses whether remove autapses (self-connections); erroneous. cleft.threshold threshold cleft score calculated Buhmann et al 2019 (default 0, used 30-100 increase specificity) Verbose Logical indication whether print status messages query (default T interactive, F otherwise). method Whether use local SQLite database remote spine service synapse data. default auto uses local database available (45GB faster).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"matrix named rows inputs columns outputs. matrix square rootids specified may otherwise rectangular. Defaults regular (dense) matrix unless sparse=TRUE.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"limitations","dir":"Reference","previous_headings":"","what":"Limitations","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"function currently much efficient local SQLite tables available; absence queries remote spine server possible currently transfer data necessary. Future work allow spine queries consider pre postsynaptic supervoxel ids part query. also careful many neurons attempt query. function designed handle queries involving hundreds neurons spine method especially sensitive overloading. intention, might better using flywire_partners flywire_partner_summary fetch data chunks manually filtering ensemble interest.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"normalisation","dir":"Reference","previous_headings":"","what":"Normalisation","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"always important give careful thought data normalisation analysing connectivity matrices. general feel normalising total input onto target cell makes sense, since approximates effectiveness input making target cell fire. However include inputs onto target cells even normalisation difficulties may better use raw counts.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"","code":"# \\donttest{ u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5392055178100736\" sm=flywire_adjacency_matrix(u) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist # scaled to give proportion of inputs onto each target cell heatmap(sm, scale='col') # scale='none' => raw counts # nb note use of assignment and keep.dendro so we can use dendrogram later h=heatmap(sm, scale='none', keep.dendro = TRUE) # same but with the cleft threshold applied smc=flywire_adjacency_matrix(u, cleft.threshold = 30) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist # note the reuse of the earlier dendrogram to return col order for comparison heatmap(smc, scale='none', Colv=h$Colv) # just a single upstream neuron sm2=flywire_adjacency_matrix(inputids=\"720575940625862385\", outputids=u) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix2.html","id":null,"dir":"Reference","previous_headings":"","what":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","title":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","text":"Fast adjacency matrices based flywire connectome dumps","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","text":"","code":"flywire_adjacency_matrix2( rootids = NULL, inputids = NULL, outputids = NULL, sparse = TRUE, threshold = 0, version = NULL, Verbose = interactive() )"},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","text":"rootids flywire root ids bodies fetch connectivity information. inputids, outputids identifiers input output bodies (use alternative rootids) sparse Whether return sparse matrix (default FALSE) threshold flywire_partner_summary return partners greater number connections query neuron(s) (default 0 returns connections) version Optional CAVE version. default value NULL uses latest data dump available unless options(fafbseg.flywire_connectome_data_version) set (can conveniently using flywire_connectome_data_version()). Verbose Logical indication whether print status messages query (default T interactive, F otherwise).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","text":"sparse matrix (Matrix::dgCMatrix) regular matrix.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","text":"","code":"if (FALSE) { dm2pnkc=flywire_adjacency_matrix2(inputids=\"DM2_lPN_R\", outputids=\"class:Kenyon_Cell_R\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":null,"dir":"Reference","previous_headings":"","what":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"Low level access Flywire CAVE annotation system","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"","code":"flywire_cave_client( datastack_name = getOption(\"fafbseg.cave.datastack_name\", \"flywire_fafb_production\") )"},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"datastack_name defaults \"flywire_fafb_production\". See https://global.daf-apis.com/info/ options.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"caveclient.frameworkclient.CAVEclientFull Python module wrapped reticulate.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"depends installation Python caveclient library. See flywire_cave_query details.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"","code":"# \\donttest{ fac <- flywire_cave_client() fac$annotation$get_tables() #> [1] \"proofreading_status_public_v1\" #> [2] \"fly_synapses_neuropil_v2\" #> [3] \"synaptic_clefts\" #> [4] \"hierarchical_neuron_annotations\" #> [5] \"neuron_information_v2\" #> [6] \"fly_synapses_neuropil_v5\" #> [7] \"neuron_information_vtest\" #> [8] \"synapses_nt_v1\" #> [9] \"fly_synapses_neuropil\" #> [10] \"proofreading_review_public_vtest\" #> [11] \"braincircuits_annotation_test\" #> [12] \"valid_synapses_nt_vtest\" #> [13] \"neuron_information_v1\" #> [14] \"nuclei_v1\" #> [15] \"valid_synapses_nt_v2\" #> [16] \"valid_synapses_nt_v1\" #> [17] \"fly_synapses_neuropil_v4\" #> [18] \"hemilineages\" #> [19] \"braincircuits_annotation_test2\" #> [20] \"hemibrain_matched_types\" #> [21] \"neuron_representative_coordinates_v1\" #> [22] \"hierarchical_cell_types_v1\" #> [23] \"cambridge_celltypes\" #> [24] \"fly_synapses_neuropil_v3\" #> [25] \"proofreading_review_public_v1\" #> [26] \"cambridge_celltypes_v2\" #> [27] \"proofread_neurons\" fac$annotation$get_table_metadata('nuclei_v1') #> $id #> [1] 8 #> #> $schema_type #> [1] \"nucleus_detection\" #> #> $table_name #> [1] \"nuclei_v1__fly_v31\" #> #> $valid #> [1] TRUE #> #> $created #> [1] \"2021-08-13T18:01:55.211016\" #> #> $deleted #> NULL #> #> $user_id #> [1] \"2\" #> #> $description #> [1] \"\\nFlyWire nucleus description\\nNucleus version: 20210322\\n\\nNuclei in this table consist of center points (in nm), volume (in μm3), and bounding boxes (in nm).\\n\\nThe nucleus segmentation was generated by Shang Mu (smu@princeton.edu, Seung Lab at Princeton University) using a 2D convolutional neural network (CNN) and heuristic interpolations. The training data was assembled from annotations by Selden Koolman, Merlin Moore, Sarah Morejohn, Ben Silverman, Kyle Willie, Ryan Willie, Szi-chieh Yu and Shang Mu.\\n\\nAs this data was generated using a 2D, rather than 3D, neural network, defects are present in the detected nuclei, particularly where there are large defects in section alignment or a number of consecutive missing sections.\\n\\nFalse positive fragments, nucleus fragments and partial nuclei are the most common type of defects. A simple, rudimentary method for cleaning up is to disregard small fragments by thresholding by segment size or by the z-dimension of the bounding boxes. A size threshold of 2000 voxels (0.08 μm3) was already applied in producing this segmentation.\\n\\nA minimal number of nucleus merger instances have been observed, caused by section alignment defects or close nuclei appositions in certain non-neuronal cell clusters.\\n\\nWhen using the nucleus annotations, please acknowledge Shang Mu and let him know about your use case.\\n\\nWe encourage making (and using) improvements to this data based on the information provided (for example, utilizing bounding box dimensions and/or the segmentation to find and merge incorrectly split partial nuclei), and such improvements should be discussed with Shang. Data derived solely from this work should be similarly made available on this platform at the time of use in any publication.\\n\" #> #> $notice_text #> NULL #> #> $reference_table #> NULL #> #> $flat_segmentation_source #> [1] \"precomputed://gs://neuroglancer/drosophila_v0/nucleus/v5_z_intp_intp/seg\" #> #> $write_permission #> [1] \"PRIVATE\" #> #> $read_permission #> [1] \"PUBLIC\" #> #> $last_modified #> [1] \"2022-10-25T19:49:21.621037\" #> #> $segmentation_source #> [1] \"\" #> #> $pcg_table_name #> [1] \"fly_v31\" #> #> $last_updated #> [1] \"2024-01-18T01:00:00.187468\" #> #> $annotation_table #> [1] \"nuclei_v1\" #> #> $voxel_resolution #> [1] 1 1 1 #> # annotation tables that have been materialised in order to map XYZ # points onto current root ids (and immutable supervoxel ids) # typically the same as fac$annotation$get_tables() fac$materialize$get_tables() #> [1] \"proofreading_status_public_v1\" #> [2] \"fly_synapses_neuropil_v2\" #> [3] \"synaptic_clefts\" #> [4] \"hierarchical_neuron_annotations\" #> [5] \"neuron_information_v2\" #> [6] \"fly_synapses_neuropil_v5\" #> [7] \"neuron_information_vtest\" #> [8] \"synapses_nt_v1\" #> [9] \"fly_synapses_neuropil\" #> [10] \"proofreading_review_public_vtest\" #> [11] \"braincircuits_annotation_test\" #> [12] \"valid_synapses_nt_vtest\" #> [13] \"nuclei_v1\" #> [14] \"valid_synapses_nt_v2\" #> [15] \"valid_synapses_nt_v1\" #> [16] \"fly_synapses_neuropil_v4\" #> [17] \"hemilineages\" #> [18] \"neuron_representative_coordinates_v1\" #> [19] \"cambridge_celltypes\" #> [20] \"fly_synapses_neuropil_v3\" #> [21] \"proofreading_review_public_v1\" #> [22] \"cambridge_celltypes_v2\" #> [23] \"proofread_neurons\" info=fac$info$get_datastack_info() # the default synapse table for the dataset info$synapse_table #> [1] \"synapses_nt_v1\" # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":null,"dir":"Reference","previous_headings":"","what":"Query the FlyWire CAVE annotation system — flywire_cave_query","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"Query FlyWire CAVE annotation system","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"","code":"flywire_cave_query( table, datastack_name = getOption(\"fafbseg.cave.datastack_name\", \"flywire_fafb_production\"), version = NULL, timestamp = NULL, live = is.null(version) && is.null(timestamp), filter_in_dict = NULL, filter_out_dict = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"table name table (view, see views section) query datastack_name defaults \"flywire_fafb_production\". See https://global.daf-apis.com/info/ options. version optional CAVE materialisation version number. See details examples. timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. live Whether use live query mode, updates root ids current value. filter_in_dict, filter_out_dict Optional arguments consisting key value lists restrict returned rows (keeping matches filtering matches). Commonly used selected rows specific neurons. See examples CAVE documentation details. ... Additional arguments query method. See examples details.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"tibble. Note xyzmatrix can used single columns containing XYZ locations.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"CAVE (Connectome Annotation Versioning Engine) provides shared infrastructure number connectomics projects involving Sebastian Seung's group Princeton collaborators Allen Institute. backend system running servers Python client end users. can find https://caveclient.readthedocs.io/ well looking Python notebooks github repo https://github.com/seung-lab/CAVEclient. annotation system shares authentication infrastructure rest FlyWire API (see flywire_set_token).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"cave-materialisation-versions-and-timestamps","dir":"Reference","previous_headings":"","what":"CAVE Materialisation Versions and Timestamps","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"CAVE concept table snapshots identified integer materialization version number. cases may wish query table defined version number can avoid root_ids changing analysis. calls also faster since root id updates required. Note however materialisation versions expire point corresponding version database expunged. However still possible find timestamp expired materialisation version. flywire_cave_query automatically using flywire_timestamp. circumstances queries slower (quite possibly slower live query) since root ids must recalculated match timestamp. CAVE's ability handle different timepoints key analysis continually evolving segmentation frankly little difficult users work . find things simplest either use long-term support (LTS) version, expire 630 version June 2023 public release. use latest CAVE version","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"cave-views","dir":"Reference","previous_headings":"","what":"CAVE Views","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"addition regular database tables, CAVE provides support views. based SQL query typically aggregates combines multiple tables. example aggregation might define total number output synapses selected neurons. present several restrictions views. example, can fetch views using unexpired materialisation version ( specify timepoint using timestamp) . Furthermore filter_in, filter_out queries using columns created SQL statement may possible.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"","code":"# \\donttest{ # note use of limit to restrict the number of rows (must be integer) n10=flywire_cave_query(table = 'nuclei_v1', limit=10L) head(as.data.frame(n10)) #> id created superceded_id valid volume pt_supervoxel_id #> 1 2338 2021-06-23 19:56:18 NA t 0.2616115 0 #> 2 3078 2021-06-23 19:55:39 NA t 4.1247949 0 #> 3 3292 2021-06-23 19:56:19 NA t 0.2737357 0 #> 4 3502 2021-06-23 19:55:39 NA t 6.7878502 0 #> 5 4404 2021-06-23 19:55:51 NA t 0.8473395 0 #> 6 4446 2021-06-23 19:55:50 NA t 58.8006195 0 #> pt_root_id pt_position bb_start_position bb_end_position #> 1 0 95520, 254368, 218600 94528, 253184, 218520 96384, 255776, 218680 #> 2 0 97472, 252352, 218040 96128, 248992, 217640 98944, 254720, 218600 #> 3 0 97280, 250784, 219320 96544, 249408, 219240 98080, 251744, 219520 #> 4 0 98304, 253376, 216480 96928, 250752, 215240 99936, 256000, 217240 #> 5 0 81280, 295968, 186680 80640, 294496, 186320 82048, 297600, 187440 #> 6 0 84128, 291584, 193400 81504, 288000, 190240 87104, 295904, 196280 # } if (FALSE) { nuclei_v1=flywire_cave_query(table = 'nuclei_v1') points3d(xyzmatrix(nuclei_v1$pt_position)) library(elmr) # calculate signed distance to FAFB surface # NB this surface is not a perfect fit in the optic lobes nuclei_v1$d=pointsinside(xyzmatrix(nuclei_v1$pt_position), FAFB.surf, rval = 'dist') points3d(xyzmatrix(nuclei_v1$pt_position), col=matlab::jet.colors(20)[cut(nuclei_v1$d,20)]) plot3d(FAFB) } # Example of a query on a table if (FALSE) { # the Princeton (mostly) and Cambridge groups have tagged some bodies as # not a neuron - these are often glia. nans=flywire_cave_query('neuron_information_v2', filter_in_dict = list(tag='not a neuron')) nrow(nans) table(nans$user_id) } if (FALSE) { psp_351=flywire_cave_query(table = 'proofreading_status_public_v1', version=351) # get the last listed materialisation version fcc=flywire_cave_client() lastv=tail(fcc$materialize$get_versions(), n=1) # pull that psp_last=flywire_cave_query(table = 'proofreading_status_public_v1', version=lastv) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":null,"dir":"Reference","previous_headings":"","what":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"Summarise edits one FlyWire segment ids","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"","code":"flywire_change_log( x, filtered = TRUE, tz = \"UTC\", root_ids = TRUE, OmitFailures = TRUE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"x One flywire segment ids (character vector recommended format accepted flywire_ids work). filtered Whether filter edits unlikely relate current state neuron (default TRUE, see details). tz Time zone edit timestamps. Defaults \"UTC\" .e. Universal Time, Coordinated. Set \"\" current timezone. See .POSIXct details. root_ids Whether look root ids /change. Default TRUE. June 2021 root_ids always returned, noop. OmitFailures Whether omit neurons API timeout error. default value (TRUE) skip errors, NA) result hard stop error. See nlapply details. ... Additional arguments passed flywire_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"data frame values itemize addition filtered=FALSE, in_neuron is_relevant","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"filtered=TRUE following removed edits outside given root id - meaning edits history cell affected part arbour since cut . edits since undone inverse operation (often temporary splits made reviewing neuron.)","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"","code":"# \\donttest{ flywire_change_log(\"720575940619010932\") #> operation_id timestamp user_id #> 0 194549 2020-09-03 19:33:23 397 #> 1 194550 2020-09-03 19:37:26 397 #> 2 194551 2020-09-03 19:38:12 397 #> 3 194552 2020-09-03 19:40:33 397 #> 4 194582 2020-09-03 20:05:41 397 #> 5 194584 2020-09-03 20:06:51 397 #> before_root_ids after_root_ids is_merge #> 0 720575940615250973 720575940625952497 FALSE #> 1 720575940622305363 720575940625952497 720575940603341158 TRUE #> 2 720575940603341158 720575940620629528 FALSE #> 3 720575940620629528 720575940637849454 720575940625315922 TRUE #> 4 720575940625315922 720575940635457646 720575940610162858 TRUE #> 5 720575940610162858 720575940619010932 FALSE #> user_name user_affiliation #> 0 Marlon Blanquart Greg Jefferis Lab #> 1 Marlon Blanquart Greg Jefferis Lab #> 2 Marlon Blanquart Greg Jefferis Lab #> 3 Marlon Blanquart Greg Jefferis Lab #> 4 Marlon Blanquart Greg Jefferis Lab #> 5 Marlon Blanquart Greg Jefferis Lab flywire_change_log(\"720575940619010932\", filtered = FALSE) #> operation_id timestamp user_id #> 0 194549 2020-09-03 19:33:23 397 #> 1 194550 2020-09-03 19:37:26 397 #> 2 194551 2020-09-03 19:38:12 397 #> 3 194552 2020-09-03 19:40:33 397 #> 4 194582 2020-09-03 20:05:41 397 #> 5 194584 2020-09-03 20:06:51 397 #> before_root_ids after_root_ids is_merge in_neuron #> 0 720575940615250973 720575940625952497 FALSE TRUE #> 1 720575940622305363 720575940625952497 720575940603341158 TRUE TRUE #> 2 720575940603341158 720575940620629528 FALSE TRUE #> 3 720575940620629528 720575940637849454 720575940625315922 TRUE TRUE #> 4 720575940625315922 720575940635457646 720575940610162858 TRUE TRUE #> 5 720575940610162858 720575940619010932 FALSE TRUE #> is_relevant user_name user_affiliation #> 0 TRUE Marlon Blanquart Greg Jefferis Lab #> 1 TRUE Marlon Blanquart Greg Jefferis Lab #> 2 TRUE Marlon Blanquart Greg Jefferis Lab #> 3 TRUE Marlon Blanquart Greg Jefferis Lab #> 4 TRUE Marlon Blanquart Greg Jefferis Lab #> 5 TRUE Marlon Blanquart Greg Jefferis Lab # with a flywire URL u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5409525645443072\" flywire_change_log(u) #> id operation_id timestamp user_id #> 1 720575940621039145 1710 2019-08-03 23:17:28 4 #> 2 720575940621039145 1715 2019-08-03 23:21:22 4 #> 3 720575940621039145 1716 2019-08-03 23:22:16 4 #> 4 720575940621039145 1735 2019-08-03 23:31:40 4 #> 5 720575940621039145 1736 2019-08-03 23:31:57 4 #> 6 720575940621039145 1737 2019-08-03 23:32:08 4 #> 7 720575940621039145 1738 2019-08-03 23:32:20 4 #> 8 720575940621039145 1739 2019-08-03 23:32:30 4 #> 9 720575940621039145 1742 2019-08-03 23:33:22 4 #> 10 720575940621039145 1744 2019-08-03 23:33:56 4 #> 11 720575940621039145 1748 2019-08-03 23:34:34 4 #> 12 720575940621039145 1750 2019-08-03 23:34:48 4 #> 13 720575940621039145 1752 2019-08-03 23:35:15 4 #> 14 720575940621039145 1753 2019-08-03 23:35:31 4 #> 15 720575940621039145 1755 2019-08-03 23:35:50 4 #> 16 720575940621039145 1757 2019-08-03 23:36:12 4 #> 17 720575940621039145 1759 2019-08-03 23:36:26 4 #> 18 720575940621039145 1761 2019-08-03 23:36:45 4 #> 19 720575940621039145 1763 2019-08-03 23:37:06 4 #> 20 720575940621039145 1766 2019-08-03 23:37:33 4 #> 21 720575940621039145 1768 2019-08-03 23:37:55 4 #> 22 720575940621039145 1770 2019-08-03 23:38:14 4 #> 23 720575940621039145 1771 2019-08-03 23:38:27 4 #> 24 720575940621039145 1776 2019-08-03 23:39:39 4 #> 25 720575940621039145 1778 2019-08-03 23:42:10 4 #> 26 720575940621039145 1781 2019-08-03 23:47:50 4 #> 27 720575940621039145 1782 2019-08-03 23:49:56 4 #> 28 720575940621039145 1784 2019-08-03 23:55:56 4 #> 29 720575940621039145 1785 2019-08-03 23:56:10 4 #> 30 720575940621039145 1786 2019-08-03 23:56:36 4 #> 31 720575940621039145 1787 2019-08-03 23:56:48 4 #> 32 720575940621039145 1788 2019-08-03 23:57:10 4 #> 33 720575940621039145 1896 2019-08-04 02:42:31 4 #> 34 720575940621039145 2231 2019-08-08 16:45:15 4 #> 35 720575940621039145 2300 2019-08-08 19:39:12 4 #> 36 720575940621039145 2346 2019-08-09 21:51:43 4 #> 37 720575940621039145 2377 2019-08-12 18:19:12 4 #> 38 720575940621039145 2423 2019-08-14 17:16:15 4 #> 39 720575940621039145 2742 2019-08-16 17:14:54 4 #> 40 720575940621039145 8042 2019-09-05 23:10:59 4 #> 41 720575940621039145 8046 2019-09-05 23:22:12 4 #> 42 720575940621039145 8047 2019-09-05 23:26:27 4 #> 43 720575940621039145 8049 2019-09-05 23:29:06 4 #> 44 720575940621039145 8052 2019-09-05 23:32:15 4 #> 45 720575940621039145 8085 2019-09-06 00:28:46 4 #> 46 720575940621039145 8086 2019-09-06 00:30:04 4 #> 47 720575940621039145 8091 2019-09-06 00:34:02 4 #> 48 720575940621039145 11049 2019-09-16 11:57:40 13 #> 49 720575940621039145 11194 2019-09-16 19:22:17 13 #> 50 720575940621039145 20627 2019-10-18 18:04:25 16 #> 51 720575940621039145 40816 2020-01-07 18:48:38 13 #> 52 720575940621039145 40819 2020-01-07 18:50:06 13 #> 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Seung Lab #> 96 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 97 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 98 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 99 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 100 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 101 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 102 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 103 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 104 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 105 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 106 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 107 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 108 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 109 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 110 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 111 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 112 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 113 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 114 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 115 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 116 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 117 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 118 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 119 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 120 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 121 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 122 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 123 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 124 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 125 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 126 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 127 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 128 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 129 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 130 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 131 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 132 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 133 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 134 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 135 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 136 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 137 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 138 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 139 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 140 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 141 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 142 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 143 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 144 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 145 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 146 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 147 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 148 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 149 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 150 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 151 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 152 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 153 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 154 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 155 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 156 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 157 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 158 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 159 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 160 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 161 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 162 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 163 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 164 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 165 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 166 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 167 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 168 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 169 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 170 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 171 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 172 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 173 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 174 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 175 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 176 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 177 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 178 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 179 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 180 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 181 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 182 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 183 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 184 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 185 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 186 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 187 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 188 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 189 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 190 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 191 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 192 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 193 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 194 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 195 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 196 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 197 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 198 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 199 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 200 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 201 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 202 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 203 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 204 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 205 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 206 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 207 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 208 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 209 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 210 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 211 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 212 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 213 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 214 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 215 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 216 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 217 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 218 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 219 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 220 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 221 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 222 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 223 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 224 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 225 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 226 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 227 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 228 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 229 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 230 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 231 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 232 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 233 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 234 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 235 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 236 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 237 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 238 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 239 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 240 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 241 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 242 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 243 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 244 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 245 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 246 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 247 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 248 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 249 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 250 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 251 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 252 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 253 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 254 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 255 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 256 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 257 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 258 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 259 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 260 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 261 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 262 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 263 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 264 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 265 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 266 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 267 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 268 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 269 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 270 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 271 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 272 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 273 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 274 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 275 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 276 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 277 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 278 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 279 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 280 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 281 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 282 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 283 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 284 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 285 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 286 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 287 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 288 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab # } if (FALSE) { # use flexible root id specification flywire_change_log(\"DA2_lPN_R\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_cloudvolume.html","id":null,"dir":"Reference","previous_headings":"","what":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","title":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","text":"Low level access FlyWire data via Python cloudvolume module","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cloudvolume.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","text":"","code":"flywire_cloudvolume( cloudvolume.url = NULL, cached = TRUE, min_version = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_cloudvolume.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","text":"cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. cached TRUE (default) reuses cached CloudVolume object current Python session. See details. min_version minimum version cloudvolume Python module e.g. \"3.12\". default NULL implies version acceptable. ... Additional arguments passed CloudVolume constructor","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cloudvolume.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","text":"equivalent (Python): cloudvolume import CloudVolume vol = CloudVolume('graphene://https://prodv1.flywire-daf.com/segmentation/table/fly_v31', use_https=True) cache tries intelligent 1. generating new object every input parameter combination (course need Python) 2. avoiding stale references checking Python currently running returned CloudVolume object non-null. also regenerates object every hour. Note reticulate package allows R/Python interaction binds one Python session. Furthermore Python restarted without also restarting R.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_cloudvolume.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","text":"","code":"if (FALSE) { cv=flywire_cloudvolume() # detailed info about the image volume cv$info # bounding box (Python format in raw voxels) cv$bounds # in nm boundingbox(cv) # get help for a function reticulate::py_help(cv$get_roots) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Access precomputed flywire connectivity data — flywire_connectome_data","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"flywire_connectome_data returns dplyr compatible connection connectivity dumps disk. flywire_connectome_data_version sets integer version number preferred flywire connectome data dump returns currently version.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"","code":"flywire_connectome_data( type = c(\"syn\", \"pre\", \"post\"), version = NULL, cached = TRUE, ... ) flywire_connectome_data_version(set = NULL, default = NA)"},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"type Character vector specifying kind data version Optional CAVE version. default value NULL uses latest data dump available unless options(fafbseg.flywire_connectome_data_version) set (can conveniently using flywire_connectome_data_version()). cached version NULL whether use cached value (lasting 1 hour) latest available version. ... Additional arguments passed arrow::open_dataset. set set= passed argument specified data version used going forwards session default. achieved setting fafbseg.flywire_connectome_data_version option. set=NA specified option cleared. set=FALSE, latest version disk returned regardless value options(\"fafbseg.flywire_connectome_data_version\")). See examples. default version return information available. Defaults NA indicate version information available.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"arrow object can use dplyr verbs like filter order find neurons/connectivity data interest. integer version number list previous value options(fafbseg.flywire_connectome_data_version) set=.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"depends precomputed data dumps prepared periodically Sven Dorkenwald. can download public release version using function download_flywire_release_data. can download versions Sven's Google drive folder. See FlyWire Slack message details URL. Two pieces information used determine version queried. First value options(fafbseg.flywire_connectome_data_version), second latest available version connectivity dumps provided flywire_connectome_data().","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"","code":"# \\donttest{ # latest available version/ syn=try(flywire_connectome_data('syn'), silent=TRUE) syn450=try(flywire_connectome_data('syn', version=450), silent=TRUE) if(!inherits(syn450, 'try-error')) { syn450 syn450$metadata dl4ds <- syn450 %>% filter(pre_pt_root_id==flywire_ids(\"DL4_adPN_L\", version=450, integer64 = TRUE)) %>% collect() } # } if (FALSE) { # report active connectome dump version (defaults to most recent available) flywire_connectome_data_version() # use the June 2023 public release version as the default flywire_connectome_data_version(set=630) # confirm this is the default flywire_connectome_data_version() # check the latest version on disk flywire_connectome_data_version(set=FALSE) # stop defaulting to specific version (therefore using the latest on disk) flywire_connectome_data_version(set=NA) flywire_connectome_data_version() }"},{"path":"https://natverse.org/fafbseg/reference/flywire_dcvs.html","id":null,"dir":"Reference","previous_headings":"","what":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","title":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","text":"Preliminary dense core vesicle (DCV) detection results Lee group, Stephan Gerhard Minsu Kim.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_dcvs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","text":"","code":"flywire_dcvs( rootid, dataset = c(\"dcv.3.0\", \"dcv.2.0\", \"dcv.1.0\"), project = \"fruitfly_fafb_flywire\", islatest = TRUE, simplify = TRUE, return = c(\"parsed\", \"text\", \"response\"), token = NULL, simplifyVector = TRUE, include_headers = FALSE, OmitFailures = TRUE, cl = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_dcvs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","text":"rootid flywire rootid/rootids dataset DCV data set Stephan Gerhard access. 1.0 just antennal lobes FAFB. 2.0 first run whole brain. project project pull data. moment, one option DCV data. islatest logical, whether fetch latest root_id given IDs date. simplify logical, FALSE rootid separate set two data frames (one DCV positions, one neuron's synapses). Else, list two combined data frames returned. return One \"parsed\", \"text\" (raw JSON), \"response\" token Optional chunkedgraph token (otherwise default one current segmentation used). simplifyVector Whether use jsonlite::simplifyVector include_headers Whether include basic headers http request attributes parsed JSON object (default TRUE) parse.json=TRUE. OmitFailures logical, TRUE requests result 500 error dropped warning displayed error. cl cluster object created parallel::makeCluster, integer indicate number child-processes (integer values ignored Windows) parallel evaluations. ... additional arguments passed httr::{RETRY} function. may include config list named parameters etc.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_dcvs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","text":"list, first entry contains DCV locations second synapses given rootid, nearest DCV precalculated synapse..","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_dcvs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","text":"","code":"if (FALSE) { # Just AL test data set data = flywire_dcvs(\"720575940629166904\", dataset = \"dcv.1.0\") dcv = data$dcv synapse = data$syns # Whole brain data set dcv = flywire_dcvs(c(\"720575940631973089\",\"720575940629166904\"), dataset = \"dcv.2.0\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":null,"dir":"Reference","previous_headings":"","what":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"GET/POST flywire (graphene) servers appropriate authorisation token","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"","code":"flywire_fetch( url, body = NULL, config = NULL, token = NULL, return = c(\"parsed\", \"text\", \"response\"), cache = FALSE, retry = 0L, include_headers = FALSE, simplifyVector = TRUE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"url Full URL brainmaps API endpoint body R list parameters converted jsonlite::toJSON passed POST. can also pass JSON character vector control JSON encoding. config (optional) curl options, see httr::config details. token Optional chunkedgraph token (otherwise default one current segmentation used). return One \"parsed\", \"text\" (raw JSON), \"response\" cache Whether cache responses (default FALSE) retry number times retry operation (default 0, FALSE=>0 TRUE=>3). See documentation times argument httr::RETRY details. include_headers Whether include basic headers http request attributes parsed JSON object (default TRUE) parse.json=TRUE. simplifyVector Whether use jsonlite::simplifyVector ... additional arguments passed httr::{RETRY} function. may include config list named parameters etc.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"Either R object based parsing returned JSON, character vector containing raw JSON httr::response object, depending value return.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":"authorisation","dir":"Reference","previous_headings":"","what":"authorisation","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"authorisation based chunked graph token normally stored ~/.cloudvolume/secrets/cave-secret.json. See https://github.com/seung-lab/cloud-volume#cave-secretjson format. need generate token advised FlyWire team. Search ask help #help_software FlyWire slack find information. details see article accessing-graphene-server.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"","code":"# \\donttest{ # convert a flywire state URL into a parsed neuroglancer scene information # but see also flywire_expandurl json=flywire_fetch(\"https://globalv1.flywire-daf.com/nglstate/5747205470158848\", return=\"text\") ngl_segments(ngl_decode_scene(json), as_character = TRUE) #> [1] \"720575940619527173\" \"720575940628130268\" \"720575940630484179\" # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","title":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","text":"allows flexible specification flywire root ids compared ngl_segments including queries cell types recorded flytable.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","text":"","code":"flywire_ids( x, integer64 = FALSE, check_latest = FALSE, must_work = FALSE, na_ok = FALSE, unique = FALSE, version = NULL, table = c(\"both\", \"info\", \"optic\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","text":"x character bit64::integer64 vector dataframe specifying ids directly string specifying query, URL comma/space delimited list ids (see examples). integer64 Whether return ids 64 bit integers - compact character vector, can fragile (default FALSE). check_latest Whether check ids date. must_work Whether ids must valid na_ok whether NA ids acceptable must_work=TRUE unique Whether return unique ids version Integer materialisation version table x query whether search brain, optic lobe info tables. ... Additional arguments passed flytable_cell_types ngl_segments.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","text":"character (integer64)) vector segment ids","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_ids.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","text":"","code":"flywire_ids(data.frame(root_id=1)) #> [1] \"1\" flywire_ids(data.frame(root_id=1), integer64=TRUE) #> integer64 #> [1] 1 # Bad values will return 0 flywire_ids(data.frame(root_id=-1)) #> [1] \"0\" if (FALSE) { # will error flywire_ids(data.frame(root_id=-1), must_work = TRUE) } # DL1 olfactory PNs flywire_ids(\"DL1_adPN\") #> [1] \"720575940625157557\" \"720575940627042064\" \"720575940616079035\" #> [4] \"720575940632167085\" # DL1 olfactory PNs but only on the RHS flywire_ids(\"DL1_adPN_R\") #> [1] \"720575940627042064\" \"720575940632167085\" # specifying materialisation version flywire_ids(\"DL1_adPN_R\", version=630) #> Updating 1 ids #> flywire_rootid_cached: Looking up 1 missing keys #> [1] \"720575940627042064\" \"720575940632167085\" # using SQL wild cards flywire_ids(\"DA[12]_%PN_L\") #> [1] \"720575940614309535\" \"720575940611849187\" \"720575940622364184\" #> [4] \"720575940615086632\" \"720575940619385765\" \"720575940626937617\" #> [7] \"720575940638719104\" \"720575940626034819\" \"720575940621185050\" #> [10] \"720575940646122804\" \"720575940613345442\" \"720575940637208718\" #> [13] \"720575940603231916\" \"720575940605102694\" # all sensory neurons flywire_ids(\"super:sensory\", integer64=TRUE) #> integer64 #> [1] 720575940622360358 720575940615856345 720575940614548253 #> [4] 720575940605699104 720575940619893072 720575940613684370 #> [7] 720575940627135306 720575940637321847 720575940628673474 #> [10] 720575940610460514 720575940616239873 720575940633280107 #> [13] 720575940638509952 720575940617969961 720575940630644281 #> [16] 720575940606871497 720575940622242253 720575940626522910 #> [19] 720575940633816986 720575940625653029 720575940630047019 #> [22] 720575940632644639 720575940638836285 720575940636052927 #> [25] 720575940628677114 720575940638513752 720575940617041728 #> [28] 720575940616999069 720575940628953210 720575940608376132 #> [31] 720575940645728132 720575940628599296 720575940623087859 #> [34] 720575940617534676 720575940613118610 720575940612096370 #> [37] 720575940617433142 720575940618512624 720575940613191591 #> [40] 720575940611720362 720575940623793741 720575940631630893 #> [43] 720575940613664874 720575940610185221 720575940621659563 #> [46] 720575940613794114 720575940627214891 720575940642599328 #> [49] 720575940618293883 720575940633367377 720575940626811023 #> [52] 720575940623274935 720575940619024774 720575940619219627 #> [55] 720575940616039197 720575940609924306 720575940622745834 #> [58] 720575940627944464 720575940622082518 720575940629007230 #> [61] 720575940617986345 720575940646372228 720575940635969399 #> [64] 720575940614844994 720575940646785924 720575940621831804 #> [67] 720575940631875298 720575940625293514 720575940620847086 #> [70] 720575940632913461 720575940617986089 720575940609792206 #> [73] 720575940623476661 720575940633059381 720575940630271862 #> [76] 720575940617665950 720575940617987113 720575940605264305 #> [79] 720575940614921501 720575940621654298 720575940638389437 #> [82] 720575940619385583 720575940627000582 720575940627606375 #> [85] 720575940614570793 720575940635767524 720575940624853600 #> [88] 720575940623503945 720575940625148174 720575940619419757 #> [91] 720575940613637782 720575940628264721 720575940618912427 #> [94] 720575940603820716 720575940622972820 720575940629693302 #> [97] 720575940631925096 720575940627677258 720575940614634786 #> [100] 720575940627431080 720575940620634537 720575940635916942 #> [103] 720575940629906060 720575940622700749 720575940620602236 #> [106] 720575940620644446 720575940628961644 720575940613914774 #> [109] 720575940651079158 720575940621100117 720575940611377893 #> [112] 720575940624673936 720575940626580361 720575940627264262 #> [115] 720575940616783361 720575940613942301 720575940613941533 #> [118] 720575940633670904 720575940628519482 720575940626674707 #> [121] 720575940627707753 720575940613942045 720575940604931249 #> [124] 720575940613942557 720575940624716746 720575940615119400 #> [127] 720575940620981274 720575940626553993 720575940628945516 #> [130] 720575940626107800 720575940630763390 720575940622211845 #> [133] 720575940627271230 720575940623638967 720575940626614405 #> [136] 720575940626726730 720575940607960843 720575940624555838 #> [139] 720575940622084681 720575940614919709 720575940622112726 #> [142] 720575940613449202 720575940647994164 720575940615696490 #> [145] 720575940608053852 720575940616653030 720575940626581525 #> [148] 720575940622375389 720575940628061968 720575940622625097 #> [151] 720575940631842119 720575940629275898 720575940625657928 #> [154] 720575940632625837 720575940619169985 720575940630282297 #> [157] 720575940629918762 720575940619725844 720575940614711638 #> [160] 720575940629728732 720575940618728395 720575940626256992 #> [163] 720575940614676447 720575940619075073 720575940653829537 #> [166] 720575940620714921 720575940606915849 720575940632063396 #> [169] 720575940622581651 720575940616439697 720575940637494837 #> [172] 720575940658539905 720575940631450451 720575940628597291 #> [175] 720575940621740493 720575940611353457 720575940605742002 #> [178] 720575940629270487 720575940618960555 720575940629154810 #> [181] 720575940632014284 720575940623265258 720575940626356306 #> [184] 720575940634781620 720575940649429625 720575940622604749 #> [187] 720575940618574983 720575940620028788 720575940647978804 #> [190] 720575940617695572 720575940623065013 720575940632224031 #> [193] 720575940629965788 720575940623209703 720575940619210375 #> [196] 720575940620673776 720575940628660224 720575940623090412 #> [199] 720575940630284306 720575940636767856 720575940626737685 #> [202] 720575940613875222 720575940614610630 720575940652581878 #> [205] 720575940628800277 720575940630037291 720575940628601344 #> [208] 720575940618531544 720575940621309534 720575940633259360 #> [211] 720575940611990738 720575940631217782 720575940628564350 #> [214] 720575940635146926 720575940644512791 720575940635419237 #> [217] 720575940611056846 720575940637013726 720575940620421153 #> [220] 720575940618577081 720575940626779644 720575940635757936 #> [223] 720575940646514740 720575940628290895 720575940629710444 #> [226] 720575940612003282 720575940628431671 720575940637887872 #> [229] 720575940626976522 720575940628429056 720575940610686162 #> [232] 720575940622651389 720575940614155882 720575940643842340 #> [235] 720575940642692059 720575940624030734 720575940643977070 #> [238] 720575940607927817 720575940653295009 720575940628624956 #> [241] 720575940642284704 720575940628976887 720575940624030478 #> [244] 720575940619844534 720575940614236575 720575940632193055 #> [247] 720575940643707246 720575940614926790 720575940617141789 #> [250] 720575940616311513 720575940617511169 720575940633471839 #> [253] 720575940628277147 720575940631240296 720575940624045155 #> [256] 720575940645824035 720575940614212514 720575940623942119 #> [259] 720575940646136599 720575940614102930 720575940614898037 #> [262] 720575940611762329 720575940631960290 720575940620224677 #> [265] 720575940634776218 720575940620675711 720575940624508341 #> [268] 720575940625154283 720575940633509407 720575940620023024 #> [271] 720575940615723350 720575940631510865 720575940606210220 #> [274] 720575940626179334 720575940625733868 720575940629539269 #> [277] 720575940610864533 720575940636093541 720575940629728988 #> [280] 720575940627253865 720575940639427416 720575940622262593 #> [283] 720575940628632702 720575940625337546 720575940626893834 #> [286] 720575940630569815 720575940631345964 720575940605328230 #> [289] 720575940625657530 720575940612674257 720575940645789988 #> [292] 720575940623129587 720575940625821758 720575940628599595 #> [295] 720575940630958673 720575940620574305 720575940627402852 #> [298] 720575940625342648 720575940617067305 720575940629232492 #> [301] 720575940628246121 720575940630511055 720575940637472053 #> [304] 720575940619280110 720575940624689336 720575940641979277 #> [307] 720575940624037052 720575940612455917 720575940630496975 #> [310] 720575940620109550 720575940633353568 720575940623270945 #> [313] 720575940641592973 720575940632624813 720575940647088004 #> [316] 720575940623610919 720575940615221800 720575940645808931 #> [319] 720575940614548765 720575940618903345 720575940619451233 #> [322] 720575940619418304 720575940616546333 720575940639030094 #> [325] 720575940643183140 720575940617989417 720575940617577797 #> [328] 720575940639415248 720575940628285450 720575940628690423 #> [331] 720575940627370027 720575940616256059 720575940621398366 #> [334] 720575940620055905 720575940645751844 720575940622987007 #> [337] 720575940650751873 720575940607459849 720575940618539422 #> [340] 720575940622891923 720575940622972167 720575940619559956 #> [343] 720575940609577518 720575940633817405 720575940653542817 #> [346] 720575940626865289 720575940638339773 720575940606869513 #> [349] 720575940634078303 720575940608227541 720575940639004032 #> [352] 720575940638773693 720575940639080526 720575940642968776 #> [355] 720575940640282869 720575940649394553 720575940608253891 #> [358] 720575940639022414 720575940616254016 720575940632284717 #> [361] 720575940627996315 720575940614053149 720575940620997409 #> [364] 720575940630662737 720575940614037533 720575940626769304 #> [367] 720575940624146019 720575940622276791 720575940613885506 #> [370] 720575940630664273 720575940604352689 720575940612160153 #> [373] 720575940620133568 720575940620202111 720575940627675535 #> [376] 720575940616322397 720575940626529448 720575940613466577 #> [379] 720575940637400183 720575940621100117 720575940619357264 #> [382] 720575940610519747 720575940627316303 720575940614105342 #> [385] 720575940615659381 720575940626202237 720575940621209513 #> [388] 720575940611844886 720575940630738171 720575940629350782 #> [391] 720575940617645652 720575940631084684 720575940638872629 #> [394] 720575940627817260 720575940620253311 720575940636670644 #> [397] 720575940621668428 720575940630696901 720575940634733537 #> [400] 720575940629343799 720575940648191609 720575940617454114 #> [403] 720575940620705012 720575940618806101 720575940612149014 #> [406] 720575940609586645 720575940623267559 720575940620024560 #> [409] 720575940624853276 720575940627805096 720575940617626781 #> [412] 720575940612140781 720575940631003723 720575940624061116 #> [415] 720575940646094388 720575940611208818 720575940611905138 #> [418] 720575940637728063 720575940615831947 720575940619429803 #> [421] 720575940615809366 720575940627239848 720575940625868184 #> [424] 720575940621897496 720575940614053405 720575940627787343 #> [427] 720575940629338750 720575940631474316 720575940626856721 #> [430] 720575940631413585 720575940606974219 720575940620822049 #> [433] 720575940619430571 720575940621766680 720575940612700450 #> [436] 720575940624849040 720575940621137833 720575940639213033 #> [439] 720575940627144010 720575940629724411 720575940606001074 #> [442] 720575940638165875 720575940604675430 720575940611111907 #> [445] 720575940609633378 720575940624964362 720575940635562096 #> [448] 720575940628769662 720575940631931183 720575940626822916 #> [451] 720575940631313455 720575940649154425 720575940659770497 #> [454] 720575940611662706 720575940625999235 720575940616482363 #> [457] 720575940619519727 720575940630696645 720575940628703993 #> [460] 720575940623607527 720575940622204612 720575940614120190 #> [463] 720575940626240522 720575940625334424 720575940613798195 #> [466] 720575940644667246 720575940633422490 720575940654500257 #> [469] 720575940638229080 720575940638026842 720575940626984274 #> [472] 720575940633024924 720575940620319329 720575940607239947 #> [475] 720575940620671512 720575940616566745 720575940628335183 #> [478] 720575940637639396 720575940625818426 720575940626980358 #> [481] 720575940629099770 720575940625754643 720575940639449507 #> [484] 720575940639116496 720575940634407263 720575940621479295 #> [487] 720575940638402357 720575940633509949 720575940619150040 #> [490] 720575940630991308 720575940631247431 720575940631885485 #> [493] 720575940631930060 720575940637002574 720575940627154063 #> [496] 720575940630442745 720575940627737073 720575940626631441 #> [499] 720575940616903209 720575940624223888 720575940623943914 #> [502] 720575940640837027 720575940634818296 720575940630807619 #> [505] 720575940623151339 720575940611369938 720575940629842681 #> [508] 720575940629854953 720575940650894457 720575940636256398 #> [511] 720575940628478251 720575940635126452 720575940625162515 #> [514] 720575940626630699 720575940614184671 720575940621611614 #> [517] 720575940608273163 720575940608508228 720575940634057976 #> [520] 720575940615257395 720575940645686564 720575940614934178 #> [523] 720575940620802230 720575940644902179 720575940622547661 #> [526] 720575940614327442 720575940626867081 720575940628499322 #> [529] 720575940620686324 720575940631234643 720575940633915327 #> [532] 720575940613699807 720575940623276471 720575940631998511 #> [535] 720575940631964371 720575940630101497 720575940631718764 #> [538] 720575940627528964 720575940610124868 720575940616093746 #> [541] 720575940620421255 720575940611966194 720575940632239661 #> [544] 720575940615825211 720575940626585481 720575940620193472 #> [547] 720575940638116723 720575940619563429 720575940616475732 #> [550] 720575940614742214 720575940623981576 720575940639093411 #> [553] 720575940622477508 720575940638069875 720575940617542996 #> [556] 720575940638818357 720575940639451043 720575940627586091 #> [559] 720575940613736941 720575940617825563 720575940617739333 #> [562] 720575940631737261 720575940621307230 720575940624335548 #> [565] 720575940615994907 720575940616923945 720575940629588854 #> [568] 720575940633175196 720575940625127354 720575940637087039 #> [571] 720575940607510027 720575940630642447 720575940617308673 #> [574] 720575940623235848 720575940633731435 720575940613051699 #> [577] 720575940626907923 720575940626680453 720575940618343734 #> [580] 720575940619761072 720575940627163560 720575940633642391 #> [583] 720575940629518892 720575940617479169 720575940623729907 #> [586] 720575940634374867 720575940630947176 720575940619702337 #> [589] 720575940639068112 720575940625502595 720575940635561584 #> [592] 720575940638475573 720575940604700006 720575940620574817 #> [595] 720575940611916274 720575940619791019 720575940639442595 #> [598] 720575940627043048 720575940633250607 720575940626851471 #> [601] 720575940606460873 720575940639186264 720575940604876977 #> [604] 720575940625795453 720575940621590720 720575940639053885 #> [607] 720575940638511267 720575940645722660 720575940628749111 #> [610] 720575940643980910 720575940635081464 720575940617598621 #> [613] 720575940623771580 720575940628377107 720575940627948111 #> [616] 720575940635745855 720575940633389281 720575940616857757 #> [619] 720575940626565907 720575940616915753 720575940632637139 #> [622] 720575940618821067 720575940629390970 720575940631727308 #> [625] 720575940621147783 720575940624859834 720575940610059726 #> [628] 720575940620023261 720575940608313611 720575940629452670 #> [631] 720575940629424195 720575940623205705 720575940630514191 #> [634] 720575940629557292 720575940627311108 720575940620382704 #> [637] 720575940612704802 720575940628888375 720575940628702658 #> [640] 720575940619093524 720575940645431075 720575940616923433 #> [643] 720575940659447937 720575940618640542 720575940616913705 #> [646] 720575940607626453 720575940619403028 720575940617089876 #> [649] 720575940626812072 720575940618701703 720575940611085518 #> [652] 720575940614430102 720575940614378463 720575940614427567 #> [655] 720575940638914648 720575940611475370 720575940610694866 #> [658] 720575940623317261 720575940616601345 720575940622540713 #> [661] 720575940627948367 720575940625889625 720575940630971434 #> [664] 720575940613671330 720575940617650407 720575940624671490 #> [667] 720575940605343921 720575940625273116 720575940638678179 #> [670] 720575940614325138 720575940629677509 720575940625132983 #> [673] 720575940606690848 720575940639076669 720575940639025998 #> [676] 720575940628407375 720575940630107131 720575940633802045 #> [679] 720575940613302451 720575940620621665 720575940627454888 #> [682] 720575940614110375 720575940610189358 720575940631191353 #> [685] 720575940654499745 720575940615757362 720575940633811005 #> [688] 720575940621625349 720575940633813309 720575940623482355 #> [691] 720575940619812487 720575940625305884 720575940618784891 #> [694] 720575940633671319 720575940627171089 720575940626213642 #> [697] 720575940619565648 720575940617109597 720575940632351513 #> [700] 720575940635838565 720575940639088885 720575940621424397 #> [703] 720575940629153274 720575940620036417 720575940607221771 #> [706] 720575940617674141 720575940631911761 720575940661296001 #> [709] 720575940622196518 720575940632854156 720575940631450764 #> [712] 720575940626868361 720575940621192436 720575940616944251 #> [715] 720575940630033962 720575940616140171 720575940624062612 #> [718] 720575940626299678 720575940619681600 720575940619891041 #> [721] 720575940617208098 720575940608324994 720575940619566507 #> [724] 720575940625720890 720575940617720221 720575940609884258 #> [727] 720575940630990756 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720575940633038127 #> [16582] 720575940622101174 720575940645583908 720575940625385451 #> [16585] 720575940616032362 720575940624397862 720575940621706587 #> [16588] 720575940635154076 720575940625096375 720575940619936822 #> [16591] 720575940639141466 720575940643215501 720575940630699970 #> [16594] 720575940622960922 720575940622112182 720575940614171875 #> [16597] 720575940610933572 720575940645000648 720575940633256775 #> [16600] 720575940626879536 720575940632877379 720575940624600211 #> [16603] 720575940624993021 720575940615824534 720575940644599712 #> [16606] 720575940614207715 720575940610945092 720575940622959386 #> [16609] 720575940640256590 720575940634766817 720575940628810472 #> [16612] 720575940624996605 720575940623875939 720575940618455270 #> [16615] 720575940625911736 720575940627950973 720575940626673712 #> [16618] 720575940627604825 720575940632710979 720575940614198243 #> [16621] 720575940618456038 720575940626672944 720575940641552080 #> [16624] 720575940627210596 720575940609953547 720575940624375081 #> [16627] 720575940625937934 720575940622970394 720575940628231443 #> [16630] 720575940622977306 720575940621886630 720575940619283269 #> [16633] 720575940637943408 720575940632829240 720575940621514667 #> [16636] 720575940614587885 720575940629548649 720575940622753776 #> [16639] 720575940614190563 720575940619502400 720575940646408302 #> [16642] 720575940636507384 720575940606387046 720575940640152509 #> [16645] 720575940624875015 720575940630383866 720575940618101563 #> [16648] 720575940634602465 720575940621850971 720575940624327818 #> [16651] 720575940632882024 720575940627249214 720575940623351116 #> [16654] 720575940624413222 720575940621018709 720575940624058061 #> [16657] 720575940645106632 720575940633519308 720575940624882439 #> [16660] 720575940630981111 720575940634530530 720575940621168775 #> [16663] 720575940621681067 720575940622415286 720575940629894416 #> [16666] 720575940628312595 720575940629765675 720575940630703607 #> [16669] 720575940635618400 720575940640176693 720575940629605419 #> [16672] 720575940615513490 720575940627588953 720575940605939628 #> [16675] 720575940631883717 720575940616516162 720575940623919373 #> [16678] 720575940640233149 720575940625998823 720575940623912205 #> [16681] 720575940616471967 720575940632868163 720575940610260437 #> [16684] 720575940622261168 720575940625025533 720575940631140919 #> [16687] 720575940643199885 720575940625440073 720575940618958337 #> [16690] 720575940620740432 720575940608122498 720575940645933079 #> [16693] 720575940616514370 720575940642439899 720575940622172854 #> [16696] 720575940624196095 720575940621685595 720575940634577633 #> [16699] 720575940625473772 720575940646459502 720575940632393258 #> [16702] 720575940627900056 720575940618897492 720575940628592917 #> [16705] 720575940625009917 720575940635005347 720575940619556416 #> [16708] 720575940618851585 720575940620410161 720575940636922735 #> [16711] 720575940624931509 720575940616580930 720575940626927664 #> [16714] 720575940621720747 720575940635514775 720575940621235732 #> [16717] 720575940612286670 720575940631912389 720575940605998508 #> [16720] 720575940632853816 720575940616408223 720575940624088319 #> [16723] 720575940623062817 720575940645877271 720575940636658100 #> [16726] 720575940631278807 720575940616875462 720575940613087962 #> [16729] 720575940623072801 720575940624089855 720575940622635135 #> [16732] 720575940623051297 720575940630865602 720575940618050363 #> [16735] 720575940613061781 720575940619195677 720575940622872816 #> [16738] 720575940637538958 720575940640690339 720575940632930188 #> [16741] 720575940618353369 720575940616193386 720575940624032013 #> [16744] 720575940647842356 720575940621742189 720575940625686759 #> [16747] 720575940622139056 720575940626014759 720575940624368934 #> [16750] 720575940623559804 720575940613397221 720575940629252170 #> [16753] 720575940640206781 720575940612334178 720575940633017415 #> [16756] 720575940632242450 720575940650042233 720575940621286053 #> [16759] 720575940616835014 720575940639018468 720575940624153599 #> [16762] 720575940624370628 720575940625026557 720575940625327368 #> [16765] 720575940630097307 720575940628134410 720575940632243218 #> [16768] 720575940625855420 720575940628240906 720575940635771287 #> [16771] 720575940628337541 720575940620789720 720575940628620565 #> [16774] 720575940621297032 720575940632714823 720575940651015289 #> [16777] 720575940614392547 720575940625302280 720575940627455234 #> [16780] 720575940637002351 720575940610358723 720575940606830950 #> [16783] 720575940620936784 720575940633988179 720575940640315701 #> [16786] 720575940627496537 720575940627135674 720575940615659682 #> [16789] 720575940619473221 720575940624978357 720575940637181815 #> [16792] 720575940626892581 720575940641300096 720575940623611094 #> [16795] 720575940621142036 720575940634840345 720575940644545952 #> [16798] 720575940618989725 720575940633918803 720575940622354241 #> [16801] 720575940637804206 720575940616946886 720575940631913047 #> [16804] 720575940614717736 720575940630630782 720575940625954744 #> [16807] 720575940626854842 720575940620222034 720575940628520767 #> [16810] 720575940618193881 720575940627050954 720575940633161799 #> [16813] 720575940633588900 720575940620810443 720575940613601765 #> [16816] 720575940618412125 720575940621667462 720575940609928459 #> [16819] 720575940624028003 720575940633341521 720575940621016912 #> [16822] 720575940637640293 720575940621017680 720575940612990101 #> [16825] 720575940617341883 720575940627225274 720575940621668742 #> [16828] 720575940632467498 720575940626408525 720575940628409989 #> [16831] 720575940614736365 720575940637641573 720575940611082564 #> [16834] 720575940633343825 720575940631998149 720575940631388887 #> [16837] 720575940633561887 720575940621696448 720575940631484119 #> [16840] 720575940624172824 720575940613619353 720575940613619865 #> [16843] 720575940630688762 720575940628266066 720575940627223482 #> [16846] 720575940624602406 720575940627789401 720575940620030518 #> [16849] 720575940626038460 720575940613621145 720575940631176960 #> [16852] 720575940639155433 720575940615153071 720575940625714446 #> [16855] 720575940625114877 720575940625115133 720575940623458124 #> [16858] 720575940632520040 720575940608368050 720575940640218702 #> [16861] 720575940618591920 720575940628232467 720575940640885336 #> [16864] 720575940618396628 720575940614704424 720575940618323641 #> [16867] 720575940613166042 720575940629425994 720575940622011969 #> [16870] 720575940631815161 720575940642656219 720575940632001733 #> [16873] 720575940628816917 720575940633049912 720575940616030358 #> [16876] 720575940622464383 720575940627258810 720575940615244851 #> [16879] 720575940615571966 720575940628429445 720575940627807065 #> [16882] 720575940630824130 720575940631717996 720575940617947275 #> [16885] 720575940622484852 720575940622616670 720575940630981623 #> [16888] 720575940616252010 720575940624455050 720575940634427603 #> [16891] 720575940628737679 720575940629158140 720575940639185242 #> [16894] 720575940631205888 720575940628100489 720575940625093813 #> [16897] 720575940621324564 720575940620069430 720575940631186176 #> [16900] 720575940609726731 720575940615115059 720575940631281463 #> [16903] 720575940639062106 720575940615592354 720575940632649795 #> [16906] 720575940640655779 720575940615303475 720575940623589708 #> [16909] 720575940631771735 720575940623201404 # note that side is defined by soma position (not arbour side) flywire_ids(\"class:MBON_R\", integer64=TRUE) #> integer64 #> [1] 720575940623472716 720575940638526278 720575940629585602 720575940637934308 #> [5] 720575940630496374 720575940611344078 720575940634822751 720575940617552340 #> [9] 720575940624280328 720575940643700640 720575940615221811 720575940614026193 #> [13] 720575940623001480 720575940613070485 720575940636992368 720575940639697827 #> [17] 720575940618249797 720575940623905719 720575940624590316 720575940612196850 #> [21] 720575940627144069 720575940610647416 720575940622093436 720575940647328900 #> [25] 720575940639556467 720575940636120986 720575940617749538 720575940617760257 #> [29] 720575940619810389 720575940634482783 720575940626109315 720575940626744921 #> [33] 720575940623464316 720575940614892182 720575940621777391 720575940606953858 #> [37] 720575940635063135 720575940626315010 720575940632943277 720575940628783363 #> [41] 720575940635651680 720575940628734376 720575940610964946 720575940607155890 #> [45] 720575940623381956 720575940628487813 720575940638028607 720575940622306625 # superclass can also have a side specified flywire_ids(\"super:motor_R\", integer64=TRUE) #> integer64 #> [1] 720575940660219265 720575940644726432 720575940624342569 720575940631715896 #> [5] 720575940635360924 720575940624967612 720575940626939737 720575940621169690 #> [9] 720575940620025620 720575940614734754 720575940645697828 720575940622235930 #> [13] 720575940621499412 720575940611008718 720575940621126384 720575940616570966 #> [17] 720575940623137818 720575940607193986 720575940629561347 720575940637662697 #> [21] 720575940617403622 720575940629810748 720575940620982966 720575940628096586 #> [25] 720575940615596850 720575940607880578 720575940631023099 720575940628781333 #> [29] 720575940629936348 720575940623415849 720575940661338497 720575940605287358 #> [33] 720575940645528430 720575940622989300 720575940631999080 720575940628743752 #> [37] 720575940632304711 720575940634385875 720575940612888178 720575940626094350 #> [41] 720575940623457535 720575940628826128 720575940628164612 720575940629778554 #> [45] 720575940630868793 720575940645527918 720575940634813536 720575940650119289 #> [49] 720575940630233404 720575940624327572 720575940626149671 720575940620182181 #> [53] 720575940622168052 720575940627214282 # you can also use a comma/space delimited list flywire_ids(\"1234, 123456\") #> [1] \"1234\" \"123456\" # ... which could come from the clipboard if (FALSE) { flywire_ids(clipr::read_clip()) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":null,"dir":"Reference","previous_headings":"","what":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"can think flywire_islatest returning whether root id valid given timestamp (default now). corresponding object edited, invalidating root id, (yet) exist ","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"","code":"flywire_islatest( x, cloudvolume.url = NULL, timestamp = NULL, version = NULL, cache = NA, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"x FlyWire rootids format understandable ngl_segments including integer64 cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. timestamp (optional) argument set endpoint - edits time ignored (see details). version optional CAVE materialisation version number. See details examples. cache Whether cache result - default value NA timestamp version argument supplied. ... Additional arguments flywire_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"logical vector length matching input. NA/0 input values return NA output.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"call quite fast (think thousands ids per second). current implementation also de-duplicates input automatically. can pass vector containing duplicates unique ids passed server. provide input integer64 data sent binary form flywire server. can significant time saving large queries (think 10000+). timestamp version provided, edits time point considered. Note since August 2022 flywire_islatest return FALSE case rootid created timestamp. Formerly returned TRUE (see seung-lab/PyChunkedGraph#412)","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"","code":"# \\donttest{ flywire_islatest(\"720575940621039145\") #> [1] FALSE flywire_islatest(c(\"720575940619073968\", \"720575940637707136\")) #> [1] FALSE FALSE # check the first id up to a given timestamp # when was it created (= last modified) flywire_last_modified('720575940619073968') #> [1] \"2020-12-02 11:43:01 UTC\" # TRUE flywire_islatest('720575940619073968', timestamp = '2020-12-03 UTC') #> [1] TRUE # FALSE since it didn't exist flywire_islatest(\"720575940619073968\", timestamp = \"2020-12-01 UTC\") #> [1] FALSE # } if (FALSE) { latest=flywire_latestid(\"720575940619073968\") flywire_islatest(latest) # compare checking roots downstream of two large bilateral neurons blids=c(\"720575940619073968\", \"720575940637707136\") blidsout=flywire_partners(blids) # 3.2 vs 4.7s in my test bench::mark(bin=flywire_islatest(blidsout$post_id), str=flywire_islatest(as.character(blidsout$post_id))) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_l2ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Return level 2 supervoxel ids for neurons — flywire_l2ids","title":"Return level 2 supervoxel ids for neurons — flywire_l2ids","text":"Level 2 supervoxel ids one step terminal supervoxel ids (level 1) finest resolution chunked graph. Like root ids, level 2 supervoxels can edited: results level 2 id destroyed two new ones created. Unlike root id merge split, l2 ids edit location change, others remain .","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_l2ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return level 2 supervoxel ids for neurons — flywire_l2ids","text":"","code":"flywire_l2ids(x, integer64 = TRUE, cache = TRUE)"},{"path":"https://natverse.org/fafbseg/reference/flywire_l2ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return level 2 supervoxel ids for neurons — flywire_l2ids","text":"x root ids including neuroglancer scene URLs integer64 Whether return ids integer64 type (compact little fragile) rather character (default FALSE). cache Whether cache results disk","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_l2ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return level 2 supervoxel ids for neurons — flywire_l2ids","text":"vector ids (usually 64 bit integers); named list vectors x length >1.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_l2ids.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return level 2 supervoxel ids for neurons — flywire_l2ids","text":"","code":"if (FALSE) { length(flywire_l2ids(\"720575940604351334\")) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":null,"dir":"Reference","previous_headings":"","what":"Check when a root id was last edited — flywire_last_modified","title":"Check when a root id was last edited — flywire_last_modified","text":"Check root id last edited","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check when a root id was last edited — flywire_last_modified","text":"","code":"flywire_last_modified(x, tz = \"UTC\", cloudvolume.url = NULL, ...)"},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check when a root id was last edited — flywire_last_modified","text":"x set flywire ids tz timezone display modification time; defaults UTC (~ proper name GMT). cloudvolume.url segmentation source URL cloudvolume. Normally can ignore rely default segmentation chosen choose_segmentation ... additional arguments passed low-level flywire_fetch function","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check when a root id was last edited — flywire_last_modified","text":"vector POSIXct timestamps, default standard UTC timezone.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check when a root id was last edited — flywire_last_modified","text":"raw information call seconds since epoch, 00:00 1 January 1970 UTC. Specifying tz argument changes display actual time event .e. Princeton typically display 5h behind Cambridge corresponding physical time.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check when a root id was last edited — flywire_last_modified","text":"","code":"# \\donttest{ flywire_last_modified(\"720575940639218165\") #> [1] \"2021-05-07 09:50:36 UTC\" # Your local time zone flywire_last_modified(\"720575940639218165\", tz=\"\") #> [1] \"2021-05-07 09:50:36 UTC\" # Cambridge (the original one) flywire_last_modified(\"720575940639218165\", tz=\"GB\") #> [1] \"2021-05-07 10:50:36 BST\" # Princeton flywire_last_modified(\"720575940639218165\", tz=\"US/Eastern\") #> [1] \"2021-05-07 05:50:36 EDT\" # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_latestid.html","id":null,"dir":"Reference","previous_headings":"","what":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","title":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","text":"Finds supervoxel ids input rootid maps current rootid simple majority vote.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_latestid.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","text":"","code":"flywire_latestid( rootid, sample = 100L, level = 2L, timestamp = NULL, version = NULL, cloudvolume.url = NULL, Verbose = FALSE, method = c(\"auto\", \"leaves\", \"cave\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_latestid.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","text":"rootid One ore FlyWire rootids defining segment (form interpretable ngl_segments) sample absolute fractional number supervoxel ids map rootids FALSE (see details). level resolution level chunked graph use calculating identity changes. integer 1 2. default (2, implying slightly larger supervoxels) considerably faster gives good results smallest fragments. See flywire_l2ids. timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. version optional CAVE materialisation version number. See details examples. cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. Verbose set TRUE prints information fraction method \"cave\" uses caveclient python module, generally faster, disadvantage disambiguate two options split. \"auto\" chooses cave available \"leaves\" otherwise. ... Additional arguments passed flywire_leaves","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_latestid.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","text":"character vector rootids. input 0 NA rootid exist chunked graph, output 0.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_latestid.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","text":"default sample input rootids used since step time consuming part. sample can defined fraction (0 [1] \"720575940611617617\" if (FALSE) { with_segmentation('sandbox', flywire_latestid('720575940625602908', Verbose = T)) # check every supervoxel (slow for bigger neurons, but this KC is smallish) flywire_latestid('720575940616243077', sample=FALSE) # update a neuroglancer URL with the most up to date segment ids # nb this is slow since it looks at all supervoxels - much more efficient to # store a single xyz location or supervoxel id u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5695907068641280\" ngl_segments(u) <- flywire_latestid(ngl_segments(u)) # open modified URL in your browser browseURL(u) } # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_leaves.html","id":null,"dir":"Reference","previous_headings":"","what":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","title":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","text":"workhorse function underlies ability define synaptic connections neurotransmitter predictions flywire neurons.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_leaves.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","text":"","code":"flywire_leaves( x, cloudvolume.url = NULL, integer64 = FALSE, mip = 0L, bbox = NULL, cache = TRUE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_leaves.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","text":"x One FlyWire segment ids cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. integer64 Whether return ids integer64 type (default, compact little fragile) rather character (FALSE). mip mip level segmentation (expert use ) bbox bounding box within find supervoxels (default = NULL whole brain. Expert use .) cache Whether cache results flywire_leaves calls. See details. ... Additional arguments passed pbsapply eventually flywire_fetch method=\"flywire\" cv$CloudVolume method=\"cloudvolume\"","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_leaves.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","text":"default repeated calls flywire_leaves cached disk. functionality provided cachem package now used memoise package. default cache expand 1.5GB start pruning least recently used basis (LRU). 1.5GB might store 10-20,000 results flywire_leaves calls depending size corresponding neurons. Since root id can map hundreds thousands supervoxel ids, space implications. order save space, results stored compressed 64 bit integers (~30x smaller character vectors). compression step add extra ~ 5 100x + faster cache hit. default compression based suggested brotli library available, gzip otherwise. functionality memory cache top disk cache, currently exposed disk read time appears small compared time uncompressing overheads. cache can controlled two package options: fafbseg.cachedir location disk. previously set, set appropriate user folder package load using rappdirs::user_data_dir. Note cache function located inside folder called flywire_leaves. fafbseg.flcachesize maximum cache size bytes. storage space exceeds results pruned using LRU algorithm. Defaults 1.5 * 1024^3 unset. Note default configuration means cache shared given user across R sessions. worth bearing mind possibility race conditions multiple applications writing/pruning cache. example fafbseg.flcachesize different values different sessions, session smallest value start pruning files disk session.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_leaves.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","text":"","code":"# \\donttest{ kcid=\"720575940623755722\" length(flywire_leaves(kcid)) #> [1] 8536 # } if (FALSE) { # developer function to check cache status fafbseg:::flywire_leaves_cache_info() }"},{"path":"https://natverse.org/fafbseg/reference/flywire_neurons_add_synapses.html","id":null,"dir":"Reference","previous_headings":"","what":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","title":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","text":"Attach appropriate input output synapses flywire neuron skeleton neuronlist.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_neurons_add_synapses.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","text":"","code":"flywire_neurons_add_synapses( x, connectors = NULL, cloudvolume.url = NULL, method = c(\"auto\", \"spine\", \"sqlite\"), remove_autapses = TRUE, cleft.threshold = 0, Verbose = TRUE, transmitters = FALSE, local = NULL, ... ) # S3 method for neuron flywire_neurons_add_synapses( x, connectors = NULL, cloudvolume.url = NULL, method = c(\"auto\", \"spine\", \"sqlite\"), remove_autapses = TRUE, cleft.threshold = 0, Verbose = TRUE, transmitters = FALSE, local = NULL, ... ) # S3 method for neuronlist flywire_neurons_add_synapses( x, connectors = NULL, cloudvolume.url = NULL, method = c(\"auto\", \"spine\", \"sqlite\"), remove_autapses = TRUE, cleft.threshold = 0, Verbose = TRUE, transmitters = FALSE, local = NULL, ... ) flywire_synapse_annotations( x, file = NULL, scale = 1/c(4, 4, 40), sample = NULL, best = TRUE, cleft.threshold = 30, remove_autapses = TRUE, local = NULL, cloudvolume.url = NULL )"},{"path":"https://natverse.org/fafbseg/reference/flywire_neurons_add_synapses.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","text":"x nat::neuronlist flywire neurons FlyWire FAFB14 brainspace. skeletons can created using skeletor, retrieved using hemibrainr::flywire_neurons. using flywire_synapse_annotations can data.frame synapses, e.g. flywire_ntpred need formatted FlyWire annotations. connectors data.frame FAFB synapses, XYZ coordinates, attach x. NULL (default) synapses fetched, flywire_partners. cloudvolume.url segmentation source URL cloudvolume. Normally can ignore rely default segmentation chosen choose_segmentation method Whether use local SQLite database remote spine service synapse data. default auto uses local database available (45GB faster). remove_autapses whether remove autapses (defaults TRUE). cleft.threshold select synaptic connections exceeding confidence threshold (default 0 uses synapses; values range 30-100 seem make sense). Verbose Whether print status messages transmitters TRUE also attempt retrieve neurotransmitter predictions Eckstein et al. 2020, flywire neuron question. local path SQLite synapse data. Evaluated fafbseg:::local_or_google. Work progress. Default download data place ~/projects/JanFunke. ... methods sent nat::nlapply. file using flywire_synapse_annotations, file path output .csv. NULL, data.frame formatted like annotations CSV FlyWire, returned. scale scale factor applied XYZ coordinates synapses. Default moves nanometre FlyWire space raw voxel FlyWire space, appropriate FlyWire annotations. sample integer, number synapses sampled x. best logical. TRUE sample integer, synapses highest cleft scores chosen, 1:sample.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_neurons_add_synapses.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","text":"nat::neuronlist object, neuron neuronlist data.frame synapses neuron$connectors.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_neurons_add_synapses.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","text":"","code":"# \\donttest{ if (FALSE) { choose_segmentation(\"flywire\") nx=xform_brain(elmr::dense_core_neurons, ref=\"FlyWire\", sample=\"FAFB14\") xyz = xyzmatrix(nx) ids = unique(flywire_xyz2id(xyz[sample(nrow(xyz),100),])) neurons = skeletor(ids, brain = elmr::FAFB14.surf) neurons.syns = flywire_neurons_add_synapses(neurons, transmitters = TRUE) neurons.syns[,] # Plot in 3D library(catmaid) nopen3d() plot3d(neurons.syns, WithConnectors = TRUE) # Axon-dendrite split library(hemibrainr) neurons.flow = flow_centrality(neurons.syns, polypre = TRUE, mode = \"centrifugal\") clear3d() plot3d_split(neurons.flow, WithConnectors = TRUE, transmitter = TRUE, radius = 1000, soma = 4000) # Save .csv of synapses as FlyWire annotations flywire_synapse_annotations(ids[1], file=\"annotations1.csv\", cleft.threshold=30) # And similar, from a neuronlist syns = hemibrainr::hemibrain_extract_synapses(neurons.flow, .parallel = TRUE, OmitFailures = TRUE) flywire_synapse_annotations(syns, file=\"annotations2.csv\", cleft.threshold=30) } # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_ntplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","title":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","text":"flywire_ntplot plots ggplot2 histogram predicted neurotransmitter vs prediction probability. flywire_ntplot3d makes 3D plot synapse location","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ntplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","text":"","code":"flywire_ntplot( x, nts = c(\"gaba\", \"acetylcholine\", \"glutamate\", \"octopamine\", \"serotonin\", \"dopamine\", \"neither\"), cleft.threshold = 0, local = NULL, cloudvolume.url = NULL ) flywire_ntplot3d( x, nts = c(\"gaba\", \"acetylcholine\", \"glutamate\", \"octopamine\", \"serotonin\", \"dopamine\"), plot = c(\"points\", \"spheres\"), cleft.threshold = 0, local = NULL, cloudvolume.url = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_ntplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","text":"x flywire rootid data.frame neurotransmitter predictions returned flywire_ntpred nts character vector neurotransmitters include plot (default 6) cleft.threshold threshold cleft score calculated Buhmann et al 2019 (default 0, used 30-100 increase specificity) local path SQLite synapse data. Evaluated fafbseg:::local_or_google. Work progress. Default download data place ~/projects/JanFunke. cloudvolume.url segmentation source URL cloudvolume. Normally can ignore rely default segmentation chosen choose_segmentation plot Whether plot points spheres (\"points\" size=5 works quite well) ... additional arguments passed spheres3d points3d","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ntplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","text":"flywire_ntplot returns ggplot2::ggplot object can customised modify plot (see examples).","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_ntplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","text":"","code":"# \\donttest{ # a cholinergic olfactory projection neuron ntp=flywire_ntpred(\"720575940615237849\") #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist flywire_ntplot(ntp) #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. flywire_ntplot(ntp, nts=c(\"gaba\", \"acetylcholine\", \"glutamate\")) #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. flywire_ntplot(ntp, nts=c(\"gaba\", \"acetylcholine\", \"glutamate\"), cleft.threshold=100) #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. # ids for several Kenyon cells kcsel=c(\"720575940623755722\", \"720575940609992371\", \"720575940625494549\", \"720575940619442047\", \"720575940620517656\", \"720575940609793429\", \"720575940617265029\", \"720575940631869024\", \"720575940637441955\", \"720575940638892789\") kcpreds=flywire_ntpred(kcsel) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist # collect the ggplot object p <- flywire_ntplot(kcpreds) # print it to see the aggregate plot (all neurons together) p #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. # ... or use ggplot facets to separate by query neuron p+ggplot2::facet_wrap(query~.) #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. # } if (FALSE) { flywire_ntplot3d(ntp, nts=c(\"gaba\", \"acetylcholine\", \"glutamate\"), plot='points', cleft.threshold=30, size=5) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_ntpred.html","id":null,"dir":"Reference","previous_headings":"","what":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","title":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","text":"print.ntprediction method provides quick summary neurotransmitter prediction output synapses.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ntpred.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","text":"","code":"flywire_ntpred( x, cleft.threshold = 0, remove_autapses = TRUE, local = NULL, cloudvolume.url = NULL ) # S3 method for ntprediction print(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/flywire_ntpred.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","text":"x single root id string data.frame output (downstream) partners returned flywire_partners. cleft.threshold threshold cleft score calculated Buhmann et al 2019 (default 0, used 30-100 increase specificity) remove_autapses flywire_partner_summary whether remove autapses (defaults TRUE) local path SQLite synapse data. Evaluated fafbseg:::local_or_google. Work progress. Default download data place ~/projects/JanFunke. cloudvolume.url segmentation source URL cloudvolume. Normally can ignore rely default segmentation chosen choose_segmentation ... additional arguments passed print","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ntpred.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","text":"data.frame neurotransmitter predictions","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_ntpred.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","text":"","code":"# \\donttest{ # an olfactory projection neuron flywire_ntpred(\"720575940615237849\") #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist #> neuron 720575940615237849 with 23081 output synapses: #> acetylcholine serotonin dopamine gaba glutamate #> 94.658 2.158 1.447 0.737 0.607 #> octopamine #> 0.394 # alternatively if (FALSE) { flywire_ntpred(flywire_xyz2id(cbind(116923, 61378, 1474), rawcoords = T)) } # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":null,"dir":"Reference","previous_headings":"","what":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"flywire_nuclei finds nuclei based known rootids nucleus_ids flywire_nearest_nuclei returns nearest nucleus query xyz location. rawcoords=T input output positions raw voxels. Note however distances still calculated nm. xyz may contain single points unless k>1, case one query point allowed.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"","code":"flywire_nuclei(rootids = NULL, nucleus_ids = NULL, rawcoords = FALSE, ...) flywire_nearest_nuclei(xyz, rawcoords = F, k = 1)"},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"rootids Character vector specifying one flywire rootids. convenience flywire_partner_summary argument passed flywire_ids allowing pass data.frames, flywire URLs cell type queries. nucleus_ids ids nucleus table return (optional, NB one rootids nucleus_ids can provided). rawcoords Whether return coordinates raw form rather nm (default FALSE) ... Additional arguments passed flywire_cave_query xyz One (k=1) query points. raw coordinates rawcoords=T k number nearest nuclei return query position. k>1 currently limited one query point.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"data.frame containing information nuclei including id nucleus id pt_position XYZ position centre nucleus. always nm rawcoords=FALSE even remote table stores raw (uncalibrated) voxel coordinates. comma separated string rawcoords=TRUE since convenient pasting applications. pt_supervoxel_id corresponding nucleus may missing segmentation disrupted location nucleus e.g. masking issues, missing sections etc. pt_root_id current root id (pt_position maps onto segmentation.) volume volume cubic microns nucleus flywire_nearest_nuclei rawcoords=T input output positions raw voxels. Note however distances still calculated nm.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"flywire_nearest_nuclei caches nucleus table updates ids selected values. saves time subsequent queries assuming returning less half total rows.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"","code":"# \\donttest{ # an example where there are two nucleus matches flywire_nuclei(flywire_xyz2id(c(120152, 22864, 3564), rawcoords = TRUE)) #> # A tibble: 3 × 10 #> id created superceded_id valid volume pt_supervoxel_id #> #> 1 4390074 2021-06-23 19:56:08 NA t 0.172 7e16 #> 2 3533175 2021-06-23 20:01:43 NA t 21.0 7e16 #> 3 3533210 2021-06-23 19:57:49 NA t 6.74 7e16 #> # ℹ 4 more variables: pt_root_id , pt_position >, #> # bb_start_position >, bb_end_position > # } # \\donttest{ nn=flywire_nearest_nuclei(c(480608, 91456, 142560), k=2) as.data.frame(nn) #> id created superceded_id valid volume pt_supervoxel_id #> 1 3533210 2021-06-23 19:57:49 NA t 6.735708 78884462138180472 #> 2 3533175 2021-06-23 20:01:43 NA t 20.972257 78884462138083227 #> pt_root_id pt_position bb_start_position #> 1 720575940624943800 480608, 91456, 142560 478432, 89952, 142120 #> 2 720575940624943800 480512, 90784, 140360 478176, 89184, 138720 #> bb_end_position dist #> 1 482784, 92736, 143440 0.000 #> 2 482944, 92608, 141480 2302.347 flywire_nearest_nuclei('163113, 59074, 5295', rawcoords = TRUE) #> # A tibble: 1 × 11 #> id created superceded_id valid volume pt_supervoxel_id #> #> 1 6865768 2021-06-23 20:01:53 NA t 21.7 8e16 #> # ℹ 5 more variables: pt_root_id , pt_position , #> # bb_start_position , bb_end_position , dist # } if (FALSE) { # from clipboard e.g. copied from flywire flywire_nearest_nuclei(clipr::read_clip(), rawcoords = TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":null,"dir":"Reference","previous_headings":"","what":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"Rapid flywire connectivity summaries using cached connectome data","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"","code":"flywire_partner_summary2( ids, partners = c(\"outputs\", \"inputs\"), add_cell_types = TRUE, by.roi = FALSE, summarise = FALSE, threshold = 0, version = NULL )"},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"ids Root ids query (passed flywire_ids) partners Whether fetch input output synapses . add_cell_types Whether add cell type information result .roi Whether break connectivity rows neuropil region containing synapses. summarise Whether collapse results multiple query neurons single entry partner neuron. threshold flywire_partner_summary return partners greater number connections query neuron(s) (default 0 returns connections) version Optional CAVE version. default value NULL uses latest data dump available unless options(fafbseg.flywire_connectome_data_version) set (can conveniently using flywire_connectome_data_version()).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"data.frame","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"Note threshold applied row left grouping operations. Therefore .roi=TRUE neuropil regions exceeding threshold returned. CAVE specifies versions (effectively timestamps) connectome data. Every often Sven makes dump connectivity synapse information proofread neurons. order use data","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"","code":"if (FALSE) { flywire_partner_summary2('DA2_lPN', partners='out') flywire_partner_summary2('DA2_lPN', partners='out', summarise=T) flywire_partner_summary2('DA2_lPN', partners='out', summarise=T, by.roi=T) flywire_partner_summary2('DA2_lPN', partners='out', summarise=T, by.roi=T, add_cell_types=F) %>% filter(!grepl(\"AL\", neuropil)) %>% group_by(post_pt_root_id) %>% summarise(weight = sum(weight), top_np = neuropil[1]) %>% arrange(desc(weight)) %>% # nb version = TRUE will use ensure that ids match the default CAVE version add_celltype_info(version=TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":null,"dir":"Reference","previous_headings":"","what":"Find the input/output partners for a flywire neuron — flywire_partners","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"flywire_partners low level function returning one row every synapse. flywire_partner_summary summarises connectivity one flywire neurons.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"","code":"flywire_partners( rootids, partners = c(\"outputs\", \"inputs\", \"both\"), details = FALSE, roots = TRUE, reference = c(\"either\", \"FAFB14\", \"FlyWire\"), cloudvolume.url = NULL, method = c(\"auto\", \"spine\", \"sqlite\"), Verbose = TRUE, local = NULL, ... ) flywire_partner_summary( rootids, partners = c(\"outputs\", \"inputs\"), threshold = 0, remove_autapses = TRUE, cleft.threshold = 0, summarise = FALSE, surf = NULL, version = NULL, timestamp = NULL, method = c(\"auto\", \"spine\", \"sqlite\", \"cave\"), Verbose = NA, local = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"rootids Character vector specifying one flywire rootids. convenience flywire_partner_summary argument passed flywire_ids allowing pass data.frames, flywire URLs cell type queries. partners Whether fetch input output synapses . details Whether include additional details X Y Z location (default FALSE) roots Whether fetch flywire rootids partner neurons (default TRUE) reference character vector templatebrain object specifying reference template brain 3D coordinate information. default value \"either\" use natural reference space data source (FAFB14 SQLite tables, FlyWire spine service). cloudvolume.url segmentation source URL cloudvolume. Normally can ignore rely default segmentation chosen choose_segmentation method Whether use local SQLite database remote spine service synapse data. default auto uses local database available (45GB faster). Verbose Whether print status messages local path SQLite synapse data. Evaluated fafbseg:::local_or_google. Work progress. Default download data place ~/projects/JanFunke. ... Additional arguments passed pbsapply threshold flywire_partner_summary return partners greater number connections query neuron(s) (default 0 returns connections) remove_autapses flywire_partner_summary whether remove autapses (defaults TRUE) cleft.threshold threshold cleft score calculated Buhmann et al 2019 (default 0, used 30-100 increase specificity) summarise Whether collapse results multiple query neurons single entry partner neuron. surf object defining 3D ROI inside presynaptic position must located. Can mesh3d object, object .mesh3d can handle including hxsurf boundingbox objects. See pointsinside details. version Integer materialisation version timestamp timestamp normalise R Python timestamp UTC. special value 'now' means current time UTC.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"data.frame regtemplate attribute specifying reference brain space xyz points. Columns vary slightly depending whether data fetched spine/ITANNA local sqlite database. obscure ones include: prepost partners = \"\" column present. given row (synapse), prepost=1 initial query neuron downstream (postsynaptic) partner upstream. score came straight Buhmann et al supposed indicate confidence score predicted synapse. cleft_score useful one later addition Stephan Gerhard asks whether pre post synapses positioned sensible distances side cleft defined separate neural network Larissa Heinrich Stephan Saalfeld’s group.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"FIXME behaviour partners well-defined. Note many duplicated connections raw output, false autapses (.e. neuron connected ) false positives. See Buhmann et al details ideas cleaning results. Also note ids returned class integer64 flywire_partners one row synapses/connection; flywire_partner_summary rows report number connections pairs neurons, type character. integer64 type compact less robust base R type instead provided bit64 package. R functions sapply strip class integer64 vectors, treating doubles completely different value. flywire_partners flywire_partner_summary default report active connectivity state neurons. present flywire_partner_summary allows time travel historic materialisations using version timestamp arguments (see flywire_timestamp details). support actually depends cave backend (automatically selected method='auto').","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"","code":"# \\donttest{ pp=flywire_partners(\"720575940621039145\") #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Fetching supervoxel ids for id: 720575940621039145 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids head(pp) #> offset scores cleft_scores pre_svid post_svid #> 1 152196 9.542592 117 81491472725509269 81491472725509199 #> 2 828599 93.800766 0 81561978908660664 81561978908653994 #> 3 828625 93.588776 1 81561978908669037 81561978908667521 #> 4 1236913 54.307476 1 81631042385463742 81631042385462154 #> 5 1236914 33.748131 0 81631042385459399 81631042385454876 #> 6 1236915 6.670522 0 81631042385462087 81631042385470852 #> post_id pre_id #> 1 720575940631693610 720575940621039145 #> 2 720575940632985261 720575940621039145 #> 3 720575940589754844 720575940621039145 #> 4 720575940631693610 720575940621039145 #> 5 720575940631693610 720575940621039145 #> 6 720575940631693610 720575940621039145 class(pp$post_id) #> [1] \"integer64\" # } # \\donttest{ # Note that post_id is of type character flywire_partner_summary(\"720575940621039145\", partners='out') #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Fetching supervoxel ids for id: 720575940621039145 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids #> # A tibble: 1,215 × 3 #> post_id weight n #> #> 1 720575940631693610 891 1 #> 2 720575940618522433 172 1 #> 3 720575940622838154 62 1 #> 4 720575940631200327 62 1 #> 5 720575940631914700 34 1 #> 6 720575940628412732 31 1 #> 7 720575940619553671 30 1 #> 8 720575940621000831 29 1 #> 9 720575940611428761 27 1 #> 10 720575940624743946 27 1 #> # ℹ 1,205 more rows flywire_partner_summary(\"720575940621039145\", partners='in') #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Fetching supervoxel ids for id: 720575940621039145 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids #> # A tibble: 620 × 3 #> pre_id weight n #> #> 1 720575940631693610 891 1 #> 2 720575940613380914 90 1 #> 3 720575940631842360 88 1 #> 4 720575940621000831 77 1 #> 5 720575940613056149 74 1 #> 6 720575940631200327 69 1 #> 7 720575940624377224 62 1 #> 8 720575940613603737 60 1 #> 9 720575940635047672 57 1 #> 10 720575940621717469 56 1 #> # ℹ 610 more rows flywire_partner_summary(\"720575940621039145\") #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Fetching supervoxel ids for id: 720575940621039145 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids #> # A tibble: 1,215 × 3 #> post_id weight n #> #> 1 720575940631693610 891 1 #> 2 720575940618522433 172 1 #> 3 720575940622838154 62 1 #> 4 720575940631200327 62 1 #> 5 720575940631914700 34 1 #> 6 720575940628412732 31 1 #> 7 720575940619553671 30 1 #> 8 720575940621000831 29 1 #> 9 720575940611428761 27 1 #> 10 720575940624743946 27 1 #> # ℹ 1,205 more rows # summary for neuron at a XYZ location (in this case in raw coordinates) flywire_partner_summary(flywire_xyz2id(cbind(155682, 58180, 3215), rawcoords = TRUE)) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Fetching supervoxel ids for id: 720575940631693610 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids #> # A tibble: 1,214 × 3 #> post_id weight n #> #> 1 720575940618522433 172 1 #> 2 720575940622838154 62 1 #> 3 720575940631200327 62 1 #> 4 720575940631914700 34 1 #> 5 720575940628412732 31 1 #> 6 720575940619553671 30 1 #> 7 720575940621000831 29 1 #> 8 720575940611428761 27 1 #> 9 720575940624743946 27 1 #> 10 720575940650971257 27 1 #> # ℹ 1,204 more rows if (FALSE) { # Use Ctrl+Shift+J to share a flywire scene and then do this to get partner # summary for that URL flywire_partner_summary(clipr::read_clip()) cct=flywire_cave_query('cambridge_celltypes', live = T) dl1.lh=flywire_partner_summary(cct$pt_root_id[grep(\"DL1\", cct$cell_type)], surf=subset(elmr::FAFB14NP.surf, \"LH_R\")) # use a rectangular bounding box around LH instead dl1.lhbb=flywire_partner_summary(cct$pt_root_id[grep(\"DL1\", cct$cell_type)], surf=boundingbox(subset(elmr::FAFB14NP.surf, \"LH_R\"))) } # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":null,"dir":"Reference","previous_headings":"","what":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"Find root_id FlyWire segment / supervoxel.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"","code":"flywire_rootid( x, method = c(\"auto\", \"cave\", \"cloudvolume\", \"flywire\"), integer64 = FALSE, timestamp = NULL, version = NULL, cache = FALSE, stop_layer = NULL, cloudvolume.url = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"x One FlyWire segment ids method Whether use flywire API (slow python required) cave/cloudvolume (faster many input ids, requires python). \"auto\" (default) choose \"cave\" \"cloudvolume\" (order) available flywire otherwise. integer64 Whether return ids integer64 type (compact little fragile) rather character (default FALSE). timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. version optional CAVE materialisation version number. See details examples. cache Whether cache supervoxel id -> rootid mappings. Default FALSE works version timestamp available. Note cache held memory therefore regenerated R session. stop_layer layer chunked graph stop . default NULL equivalent layer 1 full root id. Coarser layer 2 IDs can useful intermediate operations. cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. ... Additional arguments passed pbsapply eventually flywire_fetch method=\"flywire\" cv$CloudVolume method=\"cloudvolume\"","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"vector root ids character vectors.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"main purpose function convert supervoxel current root id whole segment. segment id updated due editing, calling original segment id still return segment id (although calling supervoxel return new segment id). wish find latest root id, can use flywire_latestid, fairly slow (think 1 second per neuron). However general best select XYZ location defining neuron interest, associated supervoxel id store , since can rapidly looked flywire_xyz2id flywire_rootid. three methods. \"flywire\" simpler much slower many supervoxels since id requires separate http request. \"cave\" method much faster can process hundreds ids per second. order avoid sending many requests one go (limit post message size), id lookups chunked maximum 50,000 lookups single call. can modified passing chunksize argument setting fafbseg.flywire_roots.chunksize option. Set smaller queries time / give \"Request Entity Large\" errors. Larger settings unlikely much speed impact. cloudvolume method default August 2022. uses server endpoint tests 2x slower cave (still much faster method='flywire')","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"","code":"# \\donttest{ flywire_rootid(c(\"81489548781649724\", \"80011805220634701\")) #> [1] \"720575940628309186\" \"720575940630034127\" # same but using the flywire sandbox segmentation with_segmentation('sandbox', { flywire_rootid(c(\"81489548781649724\", \"80011805220634701\")) }) #> [1] \"720575940626292279\" \"720575940618460245\" # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_scene.html","id":null,"dir":"Reference","previous_headings":"","what":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","title":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","text":"Return sample Neuroglancer scene URL FlyWire dataset","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_scene.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","text":"","code":"flywire_scene( ids = NULL, annotations = NULL, open = FALSE, shorten = FALSE, segmentation = \"flywire31\", ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_scene.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","text":"ids set root ids include scene. Also accepts data.frame containing column rootid, root_id, id form acceptable ngl_segments including neuroglancer scene URLs. annotations data.frame matrix position information annotation layers. See ngl_annotation_layers details. open Whether open scene default browser shorten currently implemented segmentation Defaults 'flywire31'. See choose_segmentation options. ... Passed ngl_annotation_layers","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_scene.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","text":"character vector containing single Neuroglancer URL (invisibly open=TRUE)","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_scene.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","text":"","code":"if (FALSE) { flywire_scene(open=T) # top 20 partners of a neuron flywire_scene(flywire_partner_summary(\"720575940621039145\", partners='out')$partner[1:20], open=T) # using the ability to query flytable for cell types flywire_scene('DA2_lPN', open=TRUE) flywire_scene('class:MBON_R', open=TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":null,"dir":"Reference","previous_headings":"","what":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"chunkedgraph_token returns current chunked graph token, optionally specified URL / domain name. Writes token standard location disk found cloudvolume python package well fafbseg package used authenticate https://flywire.ai.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"","code":"chunkedgraph_token(url = NULL, cached = TRUE) flywire_set_token(token = NULL, domain = NULL)"},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"url URL domain name defines scope token cached Whether use cached version token (default yes speed, set FALSE reload writing new token disk). token Optional character vector containing token. missing, new token requested (note invalidate previous token) domain Optional fully qualified domain name, prepended filename token stored.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"character vector containing token (typically 32-44 bytes) path file storing token (invisibly)","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"Since cloudvolume 3.10.0 April 2021, recommended token filenames look like 'cave-secret.json' 'cave-secret.json'","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"","code":"if (FALSE) { # Will open browser to get new token flywire_set_token() # Writes a known token to correct location flywire_set_token(\"2f88e16c4f21bfcb290b2a8288c05bd0\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_shortenurl.html","id":null,"dir":"Reference","previous_headings":"","what":"Shorten or expand neuroglancer URLs — flywire_shortenurl","title":"Shorten or expand neuroglancer URLs — flywire_shortenurl","text":"flywire_shortenurl makes short URLs long URLs ngscene objects may constructed R. flywire_expandurl expands shortened URLs full neuroglancer JSON scene specification. active segmentation (choose_segmentation) flywire segmentation used define initial part output URL, otherwise flywire31 segmentation used. flywire_expandurl also expand tinyurl.com URLs.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_shortenurl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Shorten or expand neuroglancer URLs — flywire_shortenurl","text":"","code":"flywire_shortenurl(x, include_base = TRUE, baseurl = NULL, cache = TRUE, ...) flywire_expandurl(x, json.only = FALSE, cache = TRUE, ...)"},{"path":"https://natverse.org/fafbseg/reference/flywire_shortenurl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Shorten or expand neuroglancer URLs — flywire_shortenurl","text":"x One neuroglancer URLs (flywire_expandurl) ngscene parsed scene description. include_base Whether return full URL open neuroglancer session (default) component defines scene (display JSON browser). baseurl Optional URL defining neuroglancer browser use shortened URLs. cache Whether cache calls flywire state server shortening expanding URLs. Default TRUE. NB cache active current session. ... Additional arguments passed pbsapply (multiple URLs process) ngl_encode_url (generating short URL ngscene list object) flywire_fetch using flywire_expandurl. json.return JSON fragment rather neuroglancer URL","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_shortenurl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Shorten or expand neuroglancer URLs — flywire_shortenurl","text":"character vector containing one URLs.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_shortenurl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Shorten or expand neuroglancer URLs — flywire_shortenurl","text":"","code":"if (FALSE) { sc=ngl_blank_scene() short=flywire_shortenurl(sc) long=flywire_expandurl(short) } # \\donttest{ flywire_expandurl(\"https://globalv1.flywire-daf.com/nglstate/5747205470158848\") #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22tab%22%3A%22graph%22%2C%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprodv1.flywire-daf.com%2Fsegmentation%2F1.0%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22selectedAlpha%22%3A0.62%2C%22colorSeed%22%3A1358768360%2C%22segments%22%3A%5B%22720575940619527173%22%2C%22720575940628130268%22%2C%22720575940630484179%22%5D%2C%22hiddenSegments%22%3A%5B%22720575940634222734%22%2C%22720575940636364870%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B115198%2C55453%2C1537%5D%7D%7D%2C%22zoomFactor%22%3A4.145162302892657%7D%2C%22perspectiveOrientation%22%3A%5B-0.22566604614257812%2C-0.034010399132966995%2C-0.07959923148155212%2C0.97035151720047%5D%2C%22perspectiveZoom%22%3A4888.123757966904%2C%22showSlices%22%3Afalse%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" flywire_expandurl(\"https://tinyurl.com/rmr58jpn\") #> [1] \"https://neuroglancer-demo.appspot.com/#!%7B%22dimensions%22:%7B%22x%22:%5B1.6e-8%2C%22m%22%5D%2C%22y%22:%5B1.6e-8%2C%22m%22%5D%2C%22z%22:%5B4e-8%2C%22m%22%5D%7D%2C%22position%22:%5B35783.34765625%2C10234.412109375%2C3672.360107421875%5D%2C%22crossSectionScale%22:1.2071435133745394%2C%22projectionOrientation%22:%5B0.3210762143135071%2C-0.019618114456534386%2C-0.03835516422986984%2C-0.9460729956626892%5D%2C%22projectionScale%22:17861.319479912258%2C%22layers%22:%5B%7B%22type%22:%22image%22%2C%22source%22:%22precomputed://gs://flywire_em/aligned/v1%22%2C%22tab%22:%22source%22%2C%22name%22:%22v1%22%7D%2C%7B%22type%22:%22segmentation%22%2C%22source%22:%22graphene://middleauth+https://prod.flywire-daf.com/segmentation/1.0/fly_v31%22%2C%22tab%22:%22segments%22%2C%22segments%22:%5B%22720575940626927366%22%2C%22720575940632115923%22%5D%2C%22segmentQuery%22:%22720575940626927366%20720575940632115923%22%2C%22colorSeed%22:3185436646%2C%22name%22:%22fly_v31%22%7D%2C%7B%22type%22:%22segmentation%22%2C%22source%22:%7B%22url%22:%22graphene://middleauth+https://prod.flywire-daf.com/segmentation/1.0/fly_v31%22%2C%22transform%22:%7B%22matrix%22:%5B%5B-0.9923%2C-0.0451%2C0.0652%2C65672.5875%5D%2C%5B-0.0765%2C0.9961%2C0.0048%2C2454.31625%5D%2C%5B0.167%2C0.0059%2C0.9915%2C-2227.49425%5D%5D%2C%22outputDimensions%22:%7B%22x%22:%5B1.6e-8%2C%22m%22%5D%2C%22y%22:%5B1.6e-8%2C%22m%22%5D%2C%22z%22:%5B4e-8%2C%22m%22%5D%7D%7D%2C%22subsources%22:%7B%22default%22:true%2C%22graph%22:true%2C%22bounds%22:true%2C%22mesh%22:true%7D%2C%22enableDefaultSubsources%22:false%7D%2C%22tab%22:%22source%22%2C%22segments%22:%5B%22720575940626927366%22%5D%2C%22segmentQuery%22:%22720575940626927366%20720575940632115923%22%2C%22colorSeed%22:626504786%2C%22name%22:%22fly_v31_mirror%22%2C%22archived%22:true%7D%2C%7B%22type%22:%22segmentation%22%2C%22source%22:%22precomputed://https://spine.itanna.io/files/eric/jfrc_mesh_test%22%2C%22tab%22:%22source%22%2C%22selectedAlpha%22:0.55%2C%22objectAlpha%22:0.09%2C%22segments%22:%5B%221%22%5D%2C%22colorSeed%22:2225652644%2C%22segmentColors%22:%7B%221%22:%22#cacdd8%22%7D%2C%22name%22:%22jfrc_mesh_test1%22%2C%22visible%22:false%7D%5D%2C%22showAxisLines%22:false%2C%22selectedLayer%22:%7B%22size%22:646%2C%22visible%22:true%2C%22layer%22:%22fly_v31_mirror%22%7D%2C%22layout%22:%7B%22type%22:%223d%22%2C%22orthographicProjection%22:true%7D%2C%22selection%22:%7B%22size%22:646%2C%22visible%22:false%7D%2C%22layerListPanel%22:%7B%22visible%22:true%7D%7D\" # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":null,"dir":"Reference","previous_headings":"","what":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"flywire_sirepo_file_memo() memoised version 5 minute timeout","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"","code":"flywire_sirepo_file( p, mustWork = NA, read = FALSE, version = c(783L, 630L), ... ) flywire_sirepo_file_memo( p, mustWork = NA, read = FALSE, version = c(783L, 630L), ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"p Relative path file within flywire_annotations repository mustWork Whether path must exists (default NA => TRUE reading file) read Whether read file. Either logical value function. TRUE p tsv csv file default read function used (see details). version integer CAVE materialisation version (see flywire_connectome_data_version) ... Additional arguments passed function determined read argument (typically data.table::fread).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"path (read=TRUE function) result reading file (data.table csv/tsv files).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"TRUE p tsv csv file data.table::fread function used order ensure 64 bit integers correctly parsed. default behaviour read ids character vectors can overridden (see examples).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"","code":"if (FALSE) { annpath=flywire_sirepo_file('supplemental_files/Supplemental_file1_annotations.tsv', read=FALSE) # read in annotation file anns=flywire_sirepo_file('supplemental_files/Supplemental_file1_annotations.tsv', read = TRUE) # read in annotation file with ids as 64 bit integers rather than strings anns=flywire_sirepo_file('supplemental_files/Supplemental_file1_annotations.tsv', read = TRUE, integer64=\"integer64\") # same but memoised to avoid checking github / re-reading file anns=flywire_sirepo_file_memo('supplemental_files/Supplemental_file1_annotations.tsv', read = TRUE, integer64=\"integer64\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":null,"dir":"Reference","previous_headings":"","what":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"Find standard UTC timestamp flywire materialisation version timestamp","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"","code":"flywire_timestamp( version = NULL, timestamp = NULL, convert = TRUE, datastack_name = getOption(\"fafbseg.cave.datastack_name\", \"flywire_fafb_production\") )"},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"version Integer materialisation version timestamp timestamp normalise R Python timestamp UTC. special value 'now' means current time UTC. convert Whether convert Python R timestamp (default: TRUE) datastack_name defaults \"flywire_fafb_production\". See https://global.daf-apis.com/info/ options.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"POSIXct object Python datetime object UTC timezone.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"Note CAVE timestamps UTC. timestamp argument character vector assumed UTC regardless timezone specification. Unless input character vector contains string \"UTC\" warning issued.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"","code":"# \\donttest{ ts=flywire_timestamp(349) ts #> [1] \"2022-04-18 08:10:00 UTC\" # As a unix timestamp (number of seconds since 00:00 on 1970-01-01) as.numeric(ts) #> [1] 1650269400 tsp=flywire_timestamp(349, convert=FALSE) # should be same as the numeric timestamp above tsp$timestamp() #> [1] 1650269400 flywire_timestamp(timestamp=\"2022-08-28 17:04:49 UTC\") #> [1] \"2022-08-28 17:04:49 UTC\" # nb this will return the current time *in UTC* regardless of your timezone flywire_timestamp(timestamp=\"now\") #> [1] \"2024-01-18 03:40:39 UTC\" # } if (FALSE) { # same but gives a warning flywire_timestamp(timestamp=\"2022-08-28 17:04:49\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_updateids.html","id":null,"dir":"Reference","previous_headings":"","what":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","title":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","text":"flywire_updateids updates root ids latest version (arbitrary integer materialisation version / timestamp specify). efficient possible, use supervoxel ids, XYZ positions failing slower flywire_latestid. November 2022 default behaviour use per-session supervoxel id root id cache order speed repeated lookups root id / supervoxel id pairs given timestamp/version. See flywire_rootid details.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_updateids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","text":"","code":"flywire_updateids( x, svids = NULL, xyz = NULL, rawcoords = FALSE, voxdims = c(4, 4, 40), cache = NA, version = NULL, timestamp = NULL, Verbose = TRUE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_updateids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","text":"x Current root ids svids optional supervoxel ids xyz optional xyz locations form understood xyzmatrix rawcoords whether input values raw voxel indices nm voxdims voxel dimensions nm used convert raw coordinates. cache Whether cache supervoxel id root id mappings. default value NA version timestamp argument specified. See flywire_rootid details. version optional CAVE materialisation version number. See details examples. timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. Verbose Whether print message console updates required. ... Additional arguments passed flywire_islatest flywire_latestid","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_updateids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","text":"vector form x updated ids.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_updateids.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","text":"","code":"kcs=data.frame( rootid=c(\"720575940602553568\", \"720575940602564320\", \"720575940602605536\"), xyz=c(\"(159284,42762,3594)\", \"(159035,41959,3594)\", \"(157715,44345,3594)\") ) # update root ids kcs$rootid=flywire_updateids(kcs$rootid, xyz=kcs$xyz)"},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":null,"dir":"Reference","previous_headings":"","what":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"flywire_voxdims returns image voxel dimensions normally used scale raw nm coordinates.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"","code":"flywire_voxdims(url = getOption(\"fafbseg.sampleurl\")) flywire_nm2raw(x, vd = flywire_voxdims()) flywire_raw2nm(x, vd = flywire_voxdims())"},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"url Optional neuroglancer URL containing voxel size. Defaults getOption(\"fafbseg.sampleurl\") set choose_segmentation. x 3D coordinates form compatible xyzmatrix vd voxel dimensions nm. Expert use . Normally found automatically.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"flywire_voxdims 3-vector flywire_raw2nm flywire_nm2raw Nx3 matrix coordinates","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"relies nat >= 1.10.4","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"","code":"flywire_voxdims() #> [1] 4 4 40 # ensure that we use default production flywire scene with_segmentation('flywire', flywire_voxdims()) #> [1] 4 4 40 flywire_raw2nm(c(159144, 22192, 3560)) #> X Y Z #> [1,] 636576 88768 142400 flywire_raw2nm('159144 22192 3560') #> X Y Z #> [1,] 636576 88768 142400 if (FALSE) { flywire_nm2raw(clipr::read_clip()) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":null,"dir":"Reference","previous_headings":"","what":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"Find FlyWire root supervoxel (leaf) ids XYZ locations","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"","code":"flywire_xyz2id( xyz, rawcoords = FALSE, voxdims = c(4, 4, 40), cloudvolume.url = NULL, root = TRUE, timestamp = NULL, version = NULL, stop_layer = NULL, integer64 = FALSE, fast_root = TRUE, method = c(\"auto\", \"cloudvolume\", \"spine\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"xyz One xyz locations Nx3 matrix form compatible xyzmatrix including neuron mesh3d surface objects. rawcoords whether input values raw voxel indices nm voxdims voxel dimensions nm used convert raw coordinates. cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. root Whether return root id whole segment rather supervoxel id. timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. version optional CAVE materialisation version number. See details examples. stop_layer layer chunked graph stop . default NULL equivalent layer 1 full root id. Coarser layer 2 IDs can useful intermediate operations. integer64 Whether return ids integer64 type (compact little fragile) rather character (default FALSE). fast_root Whether use fast two-step look-procedure finding roots. strongly recommended alternative approach retained validation purposes. method Whether use spine transform-service API cloudvolume lookup. \"auto\" presently synonym \"spine\". ... additional arguments passed pbapply looking multiple positions.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"character vector segment ids, NA lookup fails.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"root ids define whole neuron segmented object. supervoxel ids correspond small group voxels assumed must belong object. supervoxel ids change given segmentation, whereas root ids change every time neuron edited. stable way refer FlyWire neuron choose nice safe location arbour (recommend major branch point) store location supervoxel id. can rapidly map supervoxel id current root id using flywire_rootid. November 2020, default approach look supervoxel ids 3D point using spine transform-service API. order 100x faster mapping via cloudvolume (since must make single web request every point) Eric Perlman optimised layout underlying data rapid mapping. Note using slower cloudvolume method (may still required volumes fast lookup via spine available) finding supervoxel given XYZ location order 3x faster finding root id agglomeration super voxels given object. Perhaps less intuitively, want look many root ids, actually quicker flywire_xyz2id(,root=F) followed flywire_rootid since function can look many root ids single call ChunkedGraph server. happens setting fast_root=TRUE, default.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"","code":"# \\donttest{ if (FALSE) { # example based on defining some sample points from real neurons # sample dataset from FAFB catmaid n=elmr::dense_core_neurons[[1]] set.seed(42) ss=sample(nvertices(n), size=10) # first convert FAF14 points to FlyWire coordinate space nx=xform_brain(elmr::dense_core_neurons[[1]], ref=\"FlyWire\", sample=\"FAFB14\") pts=xyzmatrix(nx)[ss,] } # for simplicity just define those same sample points directly pts = matrix( c(428910.52, 110629.64, 174800, 410201.86, 110419.1, 180400, 337136, 129926.28, 189280, 349981.85, 136041.53, 199280, 398361.74, 110731.26, 182640, 382789.26, 118987.04, 189920, 358033.92, 171592.92, 143960, 360990.48, 140277.42, 201400, 376258.06, 125201.51, 194400, 331370.31, 128338.58, 181760), ncol = 3, byrow = TRUE, dimnames = list(NULL, c(\"X\", \"Y\", \"Z\")) ) #' # Fast and simple appoach to find ids in one (user-facing) step flywire_xyz2id(pts) #> [1] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [4] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [7] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [10] \"720575940634984800\" ## illustrate what's happening under the hood # find the ids for the selected xyz locations # NB fast_root=FALSE was the default behaviour until Nov 2020 flywire_xyz2id(pts, fast_root=FALSE, method=\"cloudvolume\") #> [1] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [4] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [7] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [10] \"720575940634984800\" # we can also find the supervoxels - much faster svids=flywire_xyz2id(pts, root=FALSE) # now look up the root ids - very fast with method=\"cloudvolume\", the default flywire_rootid(svids) #> [1] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [4] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [7] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [10] \"720575940634984800\" # }"},{"path":"https://natverse.org/fafbseg/reference/make_merge_graph.html","id":null,"dir":"Reference","previous_headings":"","what":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","title":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","text":"make_merge_graph generates graph representation agglomeration merges. merge_graph_components uses full merge graph find connected subgraph corresponding isolated merge groups.","code":""},{"path":"https://natverse.org/fafbseg/reference/make_merge_graph.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","text":"","code":"make_merge_graph(x, n = NA) merge_graph_components(g, n = NA)"},{"path":"https://natverse.org/fafbseg/reference/make_merge_graph.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","text":"x mergeinfo data.frame generated read_mergeinfo n testing purposes, number rows merge information process - default processes rows. g Either graph generated make_merge_graph mergeinfo data.frame generated read_mergeinfo.","code":""},{"path":"https://natverse.org/fafbseg/reference/make_merge_graph.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","text":"make_merge_graph returns igraph object, merge_graph_components returns list elements describing mapping segment ids merge groups.","code":""},{"path":"https://natverse.org/fafbseg/reference/make_merge_graph.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","text":"","code":"if (FALSE) { g=make_merge_graph(mergeinfo) gc=merge_graph_components(g) str(gc) }"},{"path":"https://natverse.org/fafbseg/reference/meshparty_skeletonize.html","id":null,"dir":"Reference","previous_headings":"","what":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","title":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","text":"Skeletonize neurons using meshparty python library","code":""},{"path":"https://natverse.org/fafbseg/reference/meshparty_skeletonize.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","text":"","code":"meshparty_skeletonize(segments, savedir = NULL, invalidation_d = 12000, ...)"},{"path":"https://natverse.org/fafbseg/reference/meshparty_skeletonize.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","text":"segments neuron ids form understood ngl_segments paths obj files already saved disk. savedir save SWC files (defaults temporary directory) invalidation_d Distance parameter (nm) controlling skeletonisation level detail. See meshparty docs. ... additional arguments passed save_cloudvolume_meshes","code":""},{"path":"https://natverse.org/fafbseg/reference/meshparty_skeletonize.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","text":"character vector containing path one SWC files. Note SWCs calibrated µm even though input data nm.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/meshparty_skeletonize.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","text":"","code":"if (FALSE) { meshparty_skeletonize(\"720575940614134045\") meshparty_skeletonize(\"720575940614134045.obj\") }"},{"path":"https://natverse.org/fafbseg/reference/ngl_add_colours.html","id":null,"dir":"Reference","previous_headings":"","what":"Add colours to the neuroglancer scene — ngl_add_colours","title":"Add colours to the neuroglancer scene — ngl_add_colours","text":"Add colours neuroglancer scene","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_add_colours.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add colours to the neuroglancer scene — ngl_add_colours","text":"","code":"ngl_add_colours(x, colours, layer = NULL)"},{"path":"https://natverse.org/fafbseg/reference/ngl_add_colours.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add colours to the neuroglancer scene — ngl_add_colours","text":"x neuroglancer scene form acceptable ngl_decode_scene (including URL) colours dataframe two columns, first id second colour, character vector colours named ids one colour added displayed neurons. See col2rgb additional details col can specified. layer Optional character vector specifying layer colour. lyaer=NULL (default) choose layer type segmentation_with_graph one exists.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_add_colours.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add colours to the neuroglancer scene — ngl_add_colours","text":"neuroglancer scene object (see ngl_decode_scene)","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_add_colours.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add colours to the neuroglancer scene — ngl_add_colours","text":"","code":"fw_url=with_segmentation('flywire31', getOption('fafbseg.sampleurl')) ngl_add_colours(fw_url, colours=c(\"720575940614404544\"=\"red\")) #> neuroglancer scene with 2 layers and 2 segments (of which 2 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 2 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31 if (FALSE) { # colour all neurons in the URL on the clipboard red. # Then convert back to URL and open in default browser browseURL(as.character(ngl_add_colours(clipr::read_clip(), col=\"red\"))) # Let's colour neurons from these 3 scenes in red, green and blue u1=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5695474417795072\" u2=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5198787572137984\" u3=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5673953041317888\" # sequentially build up a data.frame with the colour information # note that col will be recycled to the same length as the number of segments colourdf=data.frame(ids=ngl_segments(u1), col='red') colourdf=rbind(colourdf, data.frame(ids=ngl_segments(u2), col='green')) colourdf=rbind(colourdf, data.frame(ids=ngl_segments(u3), col='blue')) # apply that to the first URL sc=ngl_add_colours(u1, colourdf) browseURL(as.character(sc)) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":null,"dir":"Reference","previous_headings":"","what":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"Construct one neuroglancer annotation layers","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"","code":"ngl_annotation_layers(ann, rawcoords = NA, colpal = NULL)"},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"ann annotation dataframe (see details) object containing 3D vertices xyzmatrix can successfully extract points. rawcoords Whether points provided raw (voxel) coordinates calibrated (nm) positions. default NA try infer based coordinate values. colpal function character vector colour names used set colour layer.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"list additional class nglayers can added ngscene object produced ngl_decode_scene.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"ann arguments","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"","code":"if (FALSE) { psp=flywire_cave_query('proofreading_status_public_v1') fwusers=googlesheets4::read_sheet('1G0zqA5DTrfd-a2LuebV4kcqNfl4q1ehlzHBrwT6ZMoc') psp2=left_join(psp, fwusers, by=c(\"user_id\"=\"id\")) psp2$layer=psp2$institution al=ngl_annotation_layers(psp2[c(\"pt_position\", \"layer\")]) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_annotations.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","title":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","text":"Extract annotations neuroglancer scene dataframe","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","text":"","code":"ngl_annotations( x, layer = NULL, types = c(\"point\", \"line\"), points = c(\"collapse\", \"expand\", \"list\") )"},{"path":"https://natverse.org/fafbseg/reference/ngl_annotations.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","text":"x neuroglancer scene URL (passed ngl_decode_scene necessary) layer Optional index vector specifying layers within scene extract annotations. probably safest use character vector layer names (appears neuroglancer). missing annotation layers processed. types annotation types process (currently points lines default) points point coordinates.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotations.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","text":"data.frame columns defined contents annotation layer types/points arguments. Additional attributes stored","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","text":"","code":"# \\donttest{ u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5963849085747200\" adf=ngl_annotations(u) str(attr(adf, 'ann_attrs')) #> List of 1 #> $ lines:List of 9 #> ..$ tool : chr \"annotatePoint\" #> ..$ selectedAnnotation :List of 1 #> .. ..$ id: chr \"c8e65c47e6677d4dcb2bc2846c26ec4b277756c4\" #> ..$ type : chr \"annotation\" #> ..$ annotationTags :List of 3 #> .. ..$ :List of 2 #> .. .. ..$ id : int 1 #> .. .. ..$ label: chr \"good\" #> .. ..$ :List of 2 #> .. .. ..$ id : int 2 #> .. .. ..$ label: chr \"bad\" #> .. ..$ :List of 2 #> .. .. ..$ id : int 3 #> .. .. ..$ label: chr \"ok\" #> ..$ voxelSize : int [1:3] 4 4 40 #> ..$ linkedSegmentationLayer : chr \"Production-segmentation_with_graph\" #> ..$ bracketShortcutsShowSegmentation : logi FALSE #> ..$ annotationSelectionShowsSegmentation: logi FALSE #> ..$ name : chr \"lines\" # }"},{"path":"https://natverse.org/fafbseg/reference/ngl_blank_scene.html","id":null,"dir":"Reference","previous_headings":"","what":"Return a blank neuroglancer scene based on a specified segmentation — ngl_blank_scene","title":"Return a blank neuroglancer scene based on a specified segmentation — ngl_blank_scene","text":"defaults current segmentation defined choose_segmentation release=NULL","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_blank_scene.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return a blank neuroglancer scene based on a specified segmentation — ngl_blank_scene","text":"","code":"ngl_blank_scene(release = NULL, return.url = FALSE)"},{"path":"https://natverse.org/fafbseg/reference/ngl_blank_scene.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return a blank neuroglancer scene based on a specified segmentation — ngl_blank_scene","text":"release character vector specifying released segmentation via known short name sample neuroglancer URL. return.url Whether return URL rather ngscene object.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_blank_scene.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return a blank neuroglancer scene based on a specified segmentation — ngl_blank_scene","text":"","code":"# blank scene for current segmentation ngl_blank_scene() #> neuroglancer scene with 2 layers and 0 segments (of which 0 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 0 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31 # add a specific id ngl_blank_scene()+\"720575940623755722\" #> neuroglancer scene with 2 layers and 1 segments (of which 1 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 1 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31 # a different segmentation ngl_blank_scene(\"202004\") #> neuroglancer scene with 2 layers and 0 segments (of which 0 shown) #> name type visible nsegs nhidden #> 1 fafb_v14_clahe image TRUE 0 0 #> 2 fafb-ffn1-20200412 segmentation TRUE 0 0 #> source #> 1 precomputed://gs://neuroglancer-fafb-data/fafb_v14/fafb_v14_clahe #> 2 precomputed://gs://fafb-ffn1-20200412/segmentation u=ngl_blank_scene(\"202004\", return.url=TRUE) if (FALSE) { u=ngl_blank_scene(\"sandbox\") browseURL(u) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_decode_scene.html","id":null,"dir":"Reference","previous_headings":"","what":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","title":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","text":"ngl_decode_scene takes Neuroglancer scene web browser turns R list object can programmatically manipulated e.g. add/remove segments. Manipulate scenes ngl_segments, ngl_layers. See ngl_encode_url turn scene back URL open browser.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_decode_scene.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","text":"","code":"ngl_decode_scene( x, return.json = FALSE, simplifyVector = TRUE, simplifyDataFrame = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/ngl_decode_scene.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","text":"x Character vector containing single Neuroglancer URL json block return.json TRUE extracts JSON block URL parse R list simplifyVector coerce JSON arrays containing primitives atomic vector simplifyDataFrame coerce JSON arrays containing records (JSON objects) data frame ... additional arguments passed jsonlite::fromJSON","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_decode_scene.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","text":"R list additional class ngscene describing scene, , return.json=TRUE, character vector.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_decode_scene.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","text":"","code":"# \\donttest{ # get sample FlyWire URL fw_url=with_segmentation('flywire31', getOption('fafbseg.sampleurl')) # only a 0 (dummy) segment id present ngl_segments(fw_url) #> [1] \"0\" # fw_sc=ngl_decode_scene(fw_url) fw_sc #> neuroglancer scene with 2 layers and 1 segments (of which 1 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 1 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31 # add two segments fw_sc=fw_sc+c(\"720575940621039145\", \"720575940626877799\") ngl_segments(fw_sc) #> [1] \"0\" \"720575940621039145\" \"720575940626877799\" # remove that 0 segment fw_sc=fw_sc-0 ngl_segments(fw_sc) #> [1] \"720575940621039145\" \"720575940626877799\" # repeated segments are ignored i.e. no duplicates ngl_segments(fw_sc+\"720575940621039145\") #> [1] \"720575940621039145\" \"720575940626877799\" # convert back to a URL, nb this depends on choose_segmentation ngl_encode_url(fw_sc) #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprod.flywire-daf.com%2Fsegmentation%2Ftable%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22segments%22%3A%5B%22720575940621039145%22%2C%22720575940626877799%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B108360%2C42086%2C3279%5D%7D%7D%2C%22zoomFactor%22%3A8%7D%2C%22perspectiveZoom%22%3A2230.6094%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" if (FALSE) { # open in your default browser browseURL(ngl_encode_url(fw_sc)) } # } if (FALSE) { ngl_decode_scene(\"\") # decode scene from URL currently on clipboard scene=ngl_decode_scene(clipr::read_clip()) # open a Neuroglancer URL in CATMAID ngu=\"\" library(elmr) open_fafb(ngl_decode_scene(ngu)) # Or store the URL rather than opening it cmu=open_fafb(ngl_decode_scene(ngu), open=FALSE) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":null,"dir":"Reference","previous_headings":"","what":"Encode scene information into a neuroglancer URL — ngl_encode_url","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"ngl_encode_url converts R list containing neuroglancer scene URL can open browser. .character.ngscene another way convert neuroglancer scene object URL.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"","code":"ngl_encode_url(body, baseurl = NULL, auto_unbox = TRUE, ...) # S3 method for ngscene as.character(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"body text file character vector JSON data R list object class ngscene. baseurl URL specifying neuroglancer server (missing, uses URL body decoded recorded , failing , options(\"fafbseg.sampleurl\")). can use neuroglancer URL appropriately truncated encodes scene information. auto_unbox expert use . See toJSON details. ... Additional arguments toJSON x ngscene object converted URL","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"Character vector containing encoded URL","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"take pains ensure entries neuroglancer expects JSON arrays (including segments hiddenSegments) always mapped JSON array (even length 1). default baseurl depends current segmentation chosen choose_segmentation.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"","code":"# \\donttest{ # get sample FlyWire URL fw_url=with_segmentation('flywire31', getOption('fafbseg.sampleurl')) # only a 0 (dummy) segment id present ngl_segments(fw_url) #> [1] \"0\" # fw_sc=ngl_decode_scene(fw_url) # add a segment fw_sc$layers[[2]]$segments=union(fw_sc$layers[[2]]$segments, \"720575940626877799\") # convert back to a URL, nb this depends on choose_segmentation ngl_encode_url(fw_sc) #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprod.flywire-daf.com%2Fsegmentation%2Ftable%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22segments%22%3A%5B%220%22%2C%22720575940626877799%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B108360%2C42086%2C3279%5D%7D%7D%2C%22zoomFactor%22%3A8%7D%2C%22perspectiveZoom%22%3A2230.6094%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" # another way to do this, which long time R users may find more intuitive as.character(fw_sc) #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprod.flywire-daf.com%2Fsegmentation%2Ftable%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22segments%22%3A%5B%220%22%2C%22720575940626877799%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B108360%2C42086%2C3279%5D%7D%7D%2C%22zoomFactor%22%3A8%7D%2C%22perspectiveZoom%22%3A2230.6094%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" if (FALSE) { # open in your default browser browseURL(ngl_encode_url(fw_sc)) # ... or browseURL(as.character(fw_sc)) } # } if (FALSE) { # copy JSON scene information from {} symbol at top right of neuroglancer # now make a permanent URL for the scene ngl_encode_url(clipr::read_clip()) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_layers.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","title":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","text":"ngl_layers extract neuroglancer layers convenience options selecting layers characteristics visibility, type etc. ngl_layers<- sets layers element ngscene object, taking care name/class details. +.ngscene adds segments layers neuroglancer scene -.ngscene removes segments whole layers neuroglancer scene. complain segment present.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_layers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","text":"","code":"ngl_layers(x, subset = NULL) ngl_layers(x) <- value # S3 method for ngscene +(x, y) # S3 method for ngscene -(x, y)"},{"path":"https://natverse.org/fafbseg/reference/ngl_layers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","text":"x neuroglancer scene object (see ngscene) subset expression (evaluated style subset.dataframe) defined value list specifying one neuroglancer layers. usually come json fragment another parsed neuroglancer scene. See examples. y Segments layers add remove neuroglancer scene. Segments provided character vectors applying ngl_segments complex object. Layers remove layer name. Layers add form R list returned ng_layers JSON fragment copied neuroglancer.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_layers.html","id":"using-and-","dir":"Reference","previous_headings":"","what":"Using + and -","title":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","text":"shortcut methods allow add subtract segments layers neuroglancer scenes. designed convenience interactive use, may bit fragile unusual inputs.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_layers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","text":"","code":"# \\donttest{ u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5409525645443072\" sc=ngl_decode_scene(u) sc #> neuroglancer scene with 2 layers and 2 segments (of which 2 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 2 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 names(ngl_layers(sc)) #> [1] \"Production-image\" \"Production-segmentation_with_graph\" str(ngl_layers(sc)) #> List of 2 #> $ Production-image :List of 5 #> ..$ source : chr \"precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked\" #> ..$ type : chr \"image\" #> ..$ blend : chr \"default\" #> ..$ shaderControls: Named list() #> ..$ name : chr \"Production-image\" #> $ Production-segmentation_with_graph:List of 7 #> ..$ source : chr \"graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31\" #> ..$ type : chr \"segmentation_with_graph\" #> ..$ segments : chr [1:2] \"720575940621039145\" \"720575940626877799\" #> ..$ skeletonRendering :List of 2 #> .. ..$ mode2d: chr \"lines_and_points\" #> .. ..$ mode3d: chr \"lines\" #> ..$ graphOperationMarker:List of 2 #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> ..$ pathFinder :List of 2 #> .. ..$ color : chr \"#ffff00\" #> .. ..$ pathObject:List of 2 #> .. .. ..$ annotationPath:List of 2 #> .. .. .. ..$ annotations: list() #> .. .. .. ..$ tags : list() #> .. .. ..$ hasPath : logi FALSE #> ..$ name : chr \"Production-segmentation_with_graph\" #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" str(ngl_layers(sc, nsegs>0)) #> List of 1 #> $ Production-segmentation_with_graph:List of 7 #> ..$ source : chr \"graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31\" #> ..$ type : chr \"segmentation_with_graph\" #> ..$ segments : chr [1:2] \"720575940621039145\" \"720575940626877799\" #> ..$ skeletonRendering :List of 2 #> .. ..$ mode2d: chr \"lines_and_points\" #> .. ..$ mode3d: chr \"lines\" #> ..$ graphOperationMarker:List of 2 #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> ..$ pathFinder :List of 2 #> .. ..$ color : chr \"#ffff00\" #> .. ..$ pathObject:List of 2 #> .. .. ..$ annotationPath:List of 2 #> .. .. .. ..$ annotations: list() #> .. .. .. ..$ tags : list() #> .. .. ..$ hasPath : logi FALSE #> ..$ name : chr \"Production-segmentation_with_graph\" #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" str(ngl_layers(sc, visible==TRUE)) #> List of 2 #> $ Production-image :List of 5 #> ..$ source : chr \"precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked\" #> ..$ type : chr \"image\" #> ..$ blend : chr \"default\" #> ..$ shaderControls: Named list() #> ..$ name : chr \"Production-image\" #> $ Production-segmentation_with_graph:List of 7 #> ..$ source : chr \"graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31\" #> ..$ type : chr \"segmentation_with_graph\" #> ..$ segments : chr [1:2] \"720575940621039145\" \"720575940626877799\" #> ..$ skeletonRendering :List of 2 #> .. ..$ mode2d: chr \"lines_and_points\" #> .. ..$ mode3d: chr \"lines\" #> ..$ graphOperationMarker:List of 2 #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> ..$ pathFinder :List of 2 #> .. ..$ color : chr \"#ffff00\" #> .. ..$ pathObject:List of 2 #> .. .. ..$ annotationPath:List of 2 #> .. .. .. ..$ annotations: list() #> .. .. .. ..$ tags : list() #> .. .. ..$ hasPath : logi FALSE #> ..$ name : chr \"Production-segmentation_with_graph\" #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" str(ngl_layers(sc, !visible)) #> Named list() #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" # flywire segmentation str(ngl_layers(sc, type==\"segmentation_with_graph\")) #> List of 1 #> $ Production-segmentation_with_graph:List of 7 #> ..$ source : chr \"graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31\" #> ..$ type : chr \"segmentation_with_graph\" #> ..$ segments : chr [1:2] \"720575940621039145\" \"720575940626877799\" #> ..$ skeletonRendering :List of 2 #> .. ..$ mode2d: chr \"lines_and_points\" #> .. ..$ mode3d: chr \"lines\" #> ..$ graphOperationMarker:List of 2 #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> ..$ pathFinder :List of 2 #> .. ..$ color : chr \"#ffff00\" #> .. ..$ pathObject:List of 2 #> .. .. ..$ annotationPath:List of 2 #> .. .. .. ..$ annotations: list() #> .. .. .. ..$ tags : list() #> .. .. ..$ hasPath : logi FALSE #> ..$ name : chr \"Production-segmentation_with_graph\" #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" # image or segmentation str(ngl_layers(sc, type %in% c(\"image\", \"segmentation_with_graph\"))) #> List of 2 #> $ Production-image :List of 5 #> ..$ source : chr \"precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked\" #> ..$ type : chr \"image\" #> ..$ blend : chr \"default\" #> ..$ shaderControls: Named list() #> ..$ name : chr \"Production-image\" #> $ Production-segmentation_with_graph:List of 7 #> ..$ source : chr \"graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31\" #> ..$ type : chr \"segmentation_with_graph\" #> ..$ segments : chr [1:2] \"720575940621039145\" \"720575940626877799\" #> ..$ skeletonRendering :List of 2 #> .. ..$ mode2d: chr \"lines_and_points\" #> .. ..$ mode3d: chr \"lines\" #> ..$ graphOperationMarker:List of 2 #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> ..$ pathFinder :List of 2 #> .. ..$ color : chr \"#ffff00\" #> .. ..$ pathObject:List of 2 #> .. .. ..$ annotationPath:List of 2 #> .. .. .. ..$ annotations: list() #> .. .. .. ..$ tags : list() #> .. .. ..$ hasPath : logi FALSE #> ..$ name : chr \"Production-segmentation_with_graph\" #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" # } # get a sample flywire neuroglancer scene sc=ngl_decode_scene(system.file(\"flywire-annotations.json\" , package = 'fafbseg')) sc #> neuroglancer scene with 4 layers and 43 segments (of which 1 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 1 #> 3 annotation annotation TRUE 0 #> 4 jfrc_mesh_test segmentation FALSE 1 #> nhidden #> 1 0 #> 2 42 #> 3 0 #> 4 1 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 #> 3 #> 4 precomputed://https://spine.itanna.io/files/eric/jfrc_mesh_test # save a copy sc.orig <- sc # remove a layer ngl_layers(sc)=ngl_layers(sc)[-3] # or using convenient - notation sc.noann <- sc.orig - \"annotation\" # reverse layer order ngl_layers(sc)=ngl_layers(sc)[2:1] # keep visible only ngl_layers(sc) <- ngl_layers(sc, visible) # visible + multiple segments ngl_layers(sc) <- ngl_layers(sc, visible & nsegs>0) # flywire segmentation ngl_layers(sc) <- ngl_layers(sc, type==\"segmentation_with_graph\") # combine layers using + convenience method sc.noann + ngl_layers(sc.orig)['annotation'] #> neuroglancer scene with 4 layers and 43 segments (of which 1 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 1 #> 3 jfrc_mesh_test segmentation FALSE 1 #> 4 annotation annotation TRUE 0 #> nhidden #> 1 0 #> 2 42 #> 3 1 #> 4 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 #> 3 precomputed://https://spine.itanna.io/files/eric/jfrc_mesh_test #> 4 if (FALSE) { # combine layers from two scenes ngl_layers(sc) <- c(ngl_layers(sc), ngl_layers(sc2)) ngl_layers(sc) <- c(ngl_layers(sc)[-(3:4)], ngl_layers(sc2)[3:4]) ngl_layers(sc) <- c(ngl_layers(sc), ngl_layers(sc2)[-1]) ngl_layers(sc) <- c(ngl_layers(sc), ngl_layers(sc2)['annotation']) sc # another way to add a single scene ngl_layers(sc)[[4]] <- ngl_layers(sc2)[[4]] # add a new layer to a scene by parsing some JSON from the clipboard # note the double brackets are essential here ngl_layers(sc)[['jfrc_mesh']] <- jsonlite::fromJSON(clipr::read_clip()) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":null,"dir":"Reference","previous_headings":"","what":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"ngl_segments<- replaces neuroglancer segments neuroglancer scene parsed ngl_decode_scene.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"","code":"ngl_segments( x, as_character = TRUE, include_hidden = FALSE, must_work = TRUE, unique = FALSE, ... ) ngl_segments(x) <- value"},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"x Neuroglancer ids either vector ids (character vector integer64 recommended) scene specification raw JSON. format (character vector), path file disk, neuroglancer scene URL (embeds JSON scene specification single URL), R list generated parsing one . as_character Whether return segments character rather numeric vector (default character safety). include_hidden Whether include hiddenSegments (typically flywire scenes). must_work TRUE, default, error generated scene segments invalid ids present. Explicit NAs trigger error must_work=T, returned id 0 without error must_work=F. unique TRUE drops duplicated ids warning ... Additional arguments passed ngl_decode_scene value Segment ids form understandable ngl_segments. can include character/numeric/int64 ids, URL, parsed neuroglancer scene etc.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"Numeric (character) vector segment ids, taken first segmentation layer (warning) scene contains one.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"simple vector inputs, ngl_segments treat values \"NA\", \"NAN\", \"NULL\" (case insensitive) \"\" NA. ngl_segments<- chooses FlyWire style segmentation_with_graph layer exists otherwise first visible segmentation layer. Note hiddenSegment removed process.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"","code":"# -> character ngl_segments(c(10950626347, 10952282491, 13307888342)) #> [1] \"10950626347\" \"10952282491\" \"13307888342\" # turns these into numeric ngl_segments(c(\"10950626347\", \"10952282491\", \"13307888342\"), as_character=FALSE) #> [1] 10950626347 10952282491 13307888342 # \\donttest{ u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5409525645443072\" ngl_segments(u, as_character = TRUE) #> [1] \"720575940621039145\" \"720575940626877799\" sc=ngl_decode_scene(u) # set segments ngl_segments(sc) <- c(\"720575940621039145\") # or a shortcut to add ids sc=sc+c(\"720575940621039145\", \"720575940626877799\") sc #> neuroglancer scene with 2 layers and 2 segments (of which 2 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 2 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 if (FALSE) { # paste resultant URL to clipboard to use in neuroglancer clipr::write_clip(as.character(sc)) } # you can also modify the URL directly ngl_segments(u)=c(\"720575940621039145\", \"720575940626877799\") # } if (FALSE) { browseURL(u) ## Summary of different classes of input # from clipboard ngl_segments(clipr::read_clip()) # URL ngl_segments(\"\") # path to file on disk ngl_segments(\"/path/to/scene.json\") # R list ngl_segments(scenelist) }"},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":null,"dir":"Reference","previous_headings":"","what":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"Construct Neuroglancer URL based 3D location data","code":""},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"","code":"open_fafb_ngl( x, s = rgl::select3d(), zoomFactor = 8, coords.only = FALSE, open = interactive() && !coords.only, sample = NULL, reference = NULL, sampleurl = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"x numeric vector object compatible xyzmatrix CATMAID URL (see details) s Optional selection function type returned select3d zoomFactor Neuroglancer zoomFactor (bigger means zoomed ) coords.Return raw coordinate string pasting Neuroglancer position widget (top left screen) open Whether open URL browser - defaults TRUE interactive use. sample, reference Template space input object sample target (reference). See examples xform_brain details specified. sampleurl sample URL defines Neuroglancer dataset. ... Additional arguments passed fromJSON control JSON parsing.","code":""},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"character vector Neuroglancer URL coordinate string (invisibly open=TRUE)","code":""},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"Neuroglancer scenes seem specified single URL encodes json object defining layers display, position etc. function works taking sample URL defining scene editing point new 3D location / adjust zoom. package comes 4 different default scene urls specified via choose_segmentation with_segmentation. easiest way choose particular segmentation. can also specify different sample URL via sampleurl argument; remembered rest R session. regularly use particular kind scene URL, can set options(fafbseg.sampleurl) Rprofile file.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"","code":"u=paste0(\"https://fafb.catmaid.virtualflybrain.org/?pid=2&zp=131280&\", \"yp=170014.98879622458&xp=426584.81386896875&tool=navigator&sid0=2&s0=-1\") # translate URL but don't open browser open_fafb_ngl(u, open=FALSE) #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprod.flywire-daf.com%2Fsegmentation%2Ftable%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22segments%22%3A%5B%220%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B106646.2035%2C42503.7472%2C3282%5D%7D%7D%2C%22zoomFactor%22%3A8%7D%2C%22perspectiveZoom%22%3A2230.6094%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" # produce an x,y,z string to paste into Neuroglancer open_fafb_ngl(u, coords.only=TRUE) #> [1] \"106646.203467242,42503.7471990561,3282\" # translate URL converting from FAFB14 to FlyWire coordinates # (only a small shift) open_fafb_ngl(u, sample=\"FAFB14\", reference=\"FlyWire\", open=FALSE) #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprod.flywire-daf.com%2Fsegmentation%2Ftable%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22segments%22%3A%5B%220%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B106560.9535%2C42529.9972%2C3282%5D%7D%7D%2C%22zoomFactor%22%3A8%7D%2C%22perspectiveZoom%22%3A2230.6094%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" if (FALSE) { # copy CATMAID URL from clipboard and Neuroglancer coords to clipboard clipr::write_clip(open_fafb_ngl(clipr::read_clip(), coords.only=TRUE)) # Open a location in MB peduncle with current preferred segmentation open_fafb_ngl(c(433440, 168344, 131200)) # choose a particular segmentation (Google FAFB) with_segmentation(\"20190805\", open_fafb_ngl(c(433440, 168344, 131200), zoomFactor=2)) # or FlyWire with_segmentation(\"flywire\", open_fafb_ngl(c(433440, 168344, 131200))) # ... and translate FAFB14 to FlyWire coordinates with_segmentation(\"flywire\", open_fafb_ngl(c(433440, 168344, 131200), sample=\"FAFB14\", reference=\"FlyWire\", zoomFactor=2)) # open a CATMAID URL in Neuroglancer open_fafb_ngl(u) # Set an existing scene URL (pointing to any old location) to act as # the template for open_fafb_ngl # nb the package sets one for you on startup if you haven't set yourself options(fafbseg.sampleurl=\"https://\") # Edit your R profile if you want to set a different default usethis::edit_r_profile() }"},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":null,"dir":"Reference","previous_headings":"","what":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"Read skeleton(s) brainmaps API nat::neuron object","code":""},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"","code":"read.neuron.brainmaps(x, ...) read.neurons.brainmaps(x, OmitFailures = NA, df = NULL, ...)"},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"x vector segment ids Neuroglancer scene specification includes segments ids (see examples ngl_segments details). ... Additional arguments passed brainmaps_skeleton brainmaps_fetch. may include skeletonuri argument, brainmaps URI specifying remote source skeletons. See brainmaps_skeleton details. OmitFailures Whether omit neurons FUN gives error. default value (NA) result nlapply stopping error message moment error. values, see details. df Optional data frame containing information neuron","code":""},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"nat::neuron object","code":""},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"OmitFailures NA, FUN wrapped call try ensure failure single neuron abort nlapply call. OmitFailures=TRUE resultant neuronlist subsetted return values FUN evaluated successfully. OmitFailures=FALSE, \"try-error\" objects left place. either last 2 cases error messages printed call wrapped try(expr, silent=TRUE). optional dataframe (df) detailing neuron rownames match names neuron. also make sense key present column data frame. dataframe contains rows neurons, superfluous rows dropped warning. dataframe missing rows neurons error generated. SortOnUpdate=TRUE updating existing neuronlist result new neuronlist ordering identical reading neurons scratch.","code":""},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"","code":"if (FALSE) { n=read.neuron.brainmaps(22427007374) nm=read.neurons.brainmaps(find_merged_segments(7186840767)) # you would specify a particular skeleton source like so read.neurons.brainmaps(find_merged_segments(7186840767), skeletonuri=\"brainmaps:///\") }"},{"path":"https://natverse.org/fafbseg/reference/read_brainmaps_meshes.html","id":null,"dir":"Reference","previous_headings":"","what":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","title":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","text":"Read 3D meshes via brainmaps API","code":""},{"path":"https://natverse.org/fafbseg/reference/read_brainmaps_meshes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","text":"","code":"read_brainmaps_meshes( x, volume = getOption(\"fafbseg.brainmaps.volume\"), meshName = getOption(\"fafbseg.brainmaps.meshName\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/read_brainmaps_meshes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","text":"x Vector integer segment ids volume String identifier volume containing segments meshName String identifier meshes ... Additional arguments passed brainmaps_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/read_brainmaps_meshes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","text":"mesh3d object","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_brainmaps_meshes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","text":"","code":"if (FALSE) { segs=find_merged_segments(7186840767) samplemesh=read_brainmaps_meshes(segs) sampleskel=read_segments2(segs) dot3d(samplemesh, col='grey') plot3d(sampleskel, lwd=2) # or compare mesh and skeleton colouring points by distance from skeleton compare_ng_neuron(samplemesh, sampleskel, pointsize=1, sample_dots = 0.3) }"},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":null,"dir":"Reference","previous_headings":"","what":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"save_cloudvolume_meshes saves meshes disk. read_cloudvolume_meshes uses save_cloudvolume_meshes internally save meshes disk reads memory neuronlist.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"","code":"save_cloudvolume_meshes( segments, savedir = tempfile(), OmitFailures = TRUE, Force = FALSE, format = c(\"obj\", \"ply\"), ..., cloudvolume.url = getOption(\"fafbseg.cloudvolume.url\") ) read_cloudvolume_meshes( segments, savedir = NULL, ..., cloudvolume.url = getOption(\"fafbseg.cloudvolume.url\") )"},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"segments segment ids fetch (probably character vector) savedir Optional path directory obj format files stored. specified, temporary directory created removed end call. OmitFailures Whether omit neurons FUN gives error. default value (NA) result nlapply stopping error message moment error. values, see details. Force whether overwrite downloaded mesh name format whether save meshes Wavefront obj Stanford poly format. obj default ply simpler compact format. ... Additional arguments passed save_cloudvolume_meshes eventually Python CloudVolume constructor (see https://github.com/seung-lab/cloud-volume details. cloudvolume.url Optional url fetch meshes normally specified fafbseg.cloudvolume.url option.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"rgl::shapelist3d list containing one mesh3d objects named segment id.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"may use fetch meshes https://flywire.ai among sources. may need select preferred remote data source using choose_segmentation (see examples). hood, uses CloudVolume serverless Python client reading data Neuroglancer compatible formats. therefore need working python3 install CloudVolume. Please install Python CloudVolume module described : https://github.com/seung-lab/cloud-volume#setup. must ensure using python3 (implicitly explicitly) mesh fetching graphene servers depends . normally work: pip3 install cloud-volume. already installed CloudVolume found, recommend editing Renviron file set environment variable pointing correct Python. can usethis::edit_r_environ() setting e.g. RETICULATE_PYTHON=\"/usr/local/bin/python3\". normally need set kind authentication order fetch data. flywire, recommend function flywire_set_token. data sources details, see https://github.com/seung-lab/cloud-volume#chunkedgraph-secretjson get token save . can either save json snippet ~/.cloudvolume/secrets/cave-secret.json set environment variable (CHUNKEDGRAPH_SECRET=\"XXXX\". Finally also need set option pointing server. conveniently achieved using e.g. choose_segmentation('flywire31'), now default, sources without built-support, can also specify full source URL, might look something like options(fafbseg.cloudvolume.url='graphene://https://xxx.dynamicannotationframework.com/segmentation/xxx/xxx') can easily add startup Rprofile usethis::edit_r_profile().","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"","code":"if (FALSE) { kcmesh=save_cloudvolume_meshes(\"720575940623755722\", savedir=\".\") kc=read.neurons(kcmesh) } if (FALSE) { # The very first time you access FlyWire data you need to get/store a token flywire_set_token() # Each R session, you should choose the default segmentation you want choose_segmentation('flywire31') pmn1.flywire=read_cloudvolume_meshes(\"720575940623979522\") pmn1.fafb=read.neuron.catmaid(5321581) # Read and plot sample KCs from a FlyWire (short) URL u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/6230669436911616\" kcs=read_cloudvolume_meshes(u) kcs plot3d(kcs) nclear3d() plot3d(pmn1.fafb, col='red', lwd=2, WithNodes = F) wire3d(pmn1.flywire) # you can select specific locations like so library(elmr) # CATMAID URL open_fafb(pmn1.flywire[[1]], open=F) # CATMAID coords to paste into PIN location box cat(xyzmatrix(catmaid::catmaid_parse_url(open_fafb(pmn1.flywire[[1]], open=F))), sep=',') # Neuroglancer coords (raw pixels not nm) open_fafb_ngl(pmn1.flywire[[1]], open=F, coords.only = T) }"},{"path":"https://natverse.org/fafbseg/reference/read_l2skel.html","id":null,"dir":"Reference","previous_headings":"","what":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","title":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","text":"read_l2skel reads one neurons simplified L2 skeletons. read_l2dp reads one neurons simplified dotprops format. See details.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_l2skel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","text":"","code":"read_l2skel(id, OmitFailures = TRUE, datastack_name = NULL, ...) read_l2dp(id, OmitFailures = TRUE, datastack_name = NULL, ...)"},{"path":"https://natverse.org/fafbseg/reference/read_l2skel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","text":"id One flywire ids OmitFailures Whether drop neurons read results (rather erroring ). Default TRUE. datastack_name CAVE datastack_name. missing use default implied segmentation chosen choose_segmentation. ... Additional arguments passed fafbseg.flywire.l2_skeleton fafbseg.flywire.l2_dotpropsfunctions.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_l2skel.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","text":"read_l2dp generally recommended rather fetching skeleton calculating dotprops much faster also computes better direction vectors. However wish simplify skeleton (e.g. find cell body fibre) need take two step approach. also possible advantage can specify step size direction vectors generated along neuron. Note also read_l2dp may drop regions neuron (likely thin ones) define small mesh volume. functions depends Philipp Schlegel's fafbseg-py package. can install using simple_python. datastack_name argument optional correct datastack name corresponding cloud volume URL read options set choose_segmentation; generally preferred way end users select active dataset. Neverthless, datastack_name used look correct segmentation URL fafbseg-py correctly set using two pieces information.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_l2skel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","text":"","code":"if (FALSE) { # install full set of recommended packages including fafbseg-py simple_python(\"full\") kcsvids=c(\"78603674556915608\", \"78462662124123765\", \"77547662357982001\", \"78533168373869635\", \"78251418452635714\", \"78323024281482155\", \"78322062208411707\", \"78533649477402370\", \"77829412279715493\", \"77899643517979532\", \"78814230967028270\", \"78533993141739277\", \"78041274292494941\", \"78252449311896359\", \"77618924522629940\", \"77618237260576979\", \"78673768356594679\", \"78182148951479619\", \"78392293379997680\", \"77688812230426430\") kcids=flywire_rootid(kcsvids) kcs=read_l2skel(kcids) library(nat.nblast) kcdps=read_l2dp(kcids) # nb these are in microns boundingbox(kcdps) kcaba=nblast_allbyall(kcdps) kchc=nhclust(scoremat = kcaba) plot(kchc) # 3d plot using the skeletons rather than dotprops versions of the neurons # gamma neurons seprate from the rest plot3d(kchc, k=2, db=kcs) }"},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":null,"dir":"Reference","previous_headings":"","what":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"Read CSV files containing raw agglomeration (merge) information","code":""},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"","code":"read_mergeinfo(x, pattern = \"10\\\\.csv$\", voxdims = c(16, 16, 40), ...)"},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"x Input directory pattern Optional pattern identify CSV files voxdims Optional voxel dimensions convert raw pixel coordinates physical (nm) coordinates ... Additional arguments passed readr::read_csv","code":""},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"data.frame columns id1,id2 Segment ids merged x,y,z Location (nm) merge point","code":""},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"Peter Li provided 10 CSV files merge information Aug 2018 function tested. merge information processed identify groups segments merged together fafbsegdata package, can accessed using find_merged_segments function.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"","code":"if (FALSE) { csvdir=\"~/projects/fafbseg/fafb14_v00c_split3xfill2x_merges/ffnreseg16nm_ms1000_md0.02_c0.6_iou0.7/\" mergeinfo <- read_mergeinfo(csvdir) # Show 3D position of merge locations for a large merge group containing a # tangential cell (widefield visual interneuron) tang_segs <- find_merged_segments(22139217567) tang_mi <- subset(mergeinfo, id1%in% tang_segs | id2 %in%tang_segs) points3d(xyzmatrix(tang_mi)) # plot brain surface for context library(elmr) plot3d(FAFB) }"},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":null,"dir":"Reference","previous_headings":"","what":"Read neuroglancer data dump from disk / web — read_ng_dump","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"Read neuroglancer data dump disk / web","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"","code":"read_ng_dump(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"x Path directory, zip file, set data files ... Additional argument passed read_ng_raw","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"list class ng_raw_list additional metadata attributes.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"neuroglancer data dump consists mix JSON custom binary data files, together define mesh data (fragments) neurons together associated metadata. See fetch_all_curl prepare data dump.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"","code":"if (FALSE) { fetch_all_curl(\"all_curl.sh\", outdir=\"alldata\", regex=\"brainmaps.googleapis.com\", fixed=TRUE) meshdata=read_ng_dump(\"alldata\") m=as.mesh3d(meshdata) shade3d(m, col='red') # can also be a (remote) zip file meshdata=read_ng_dump(\"https://myfiles.com/myneuron.zip\") }"},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":null,"dir":"Reference","previous_headings":"","what":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"Read raw neuroglancer data - currently supports mesh format","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"","code":"read_ng_raw(x, read_data = TRUE, Verbose = FALSE)"},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"x Path one files directory (case files read). read_data Whether read data (default TRUE) just header Verbose Whether print status messages (default FALSE)","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"object class 'ng_raw_list' containing one chunks data class 'ng_raw'. x contains multiple files, chunks merged single list.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"See https://github.com/google/neuroglancer","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"","code":"if (FALSE) { res <- read_ng_raw(\"meshdata/chunk00789.raw\") resh <- read_ng_raw(\"meshdata/chunk00789.raw\", read_data=FALSE) resl <- read_ng_raw(dir(\"meshdata\", full.names = TRUE)) }"},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":null,"dir":"Reference","previous_headings":"","what":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"read_segments2 reworked version read_segments reads skeletons straight zip files memory.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"","code":"read_segments(x, voxdims = c(32, 32, 40), ...) read_segments2( x, voxdims = c(32, 32, 40), minfilesize = 80, datafrac = NULL, coordsonly = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"x vector segment ids Neuroglancer scene specification includes segments ids (see examples ngl_segments details). voxdims voxel dimensions nm skeletonised data ... additional arguments passed read.neurons minfilesize uncompressed size swc file must >= . cheap way insist >1 point. datafrac Fraction data read based uncompressed file size (see details) coordsonly read XYZ coordinates neurons.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"neuronlist containing one neuron fragment","code":""},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"recommend read_segments2 point. read_segments potential benefit caching SWC files disk rather extracting every time. However large slowdown many filesystems number extracted files enters thousands - something hit times. Furthermore read_segments2 makes easier select fragment files extracting . datafrac number range 0-1 specifies fraction data read. Skeleton fragments placed descending size order read number bytes exceeds datafrac * sum(file sizes). noticed time taken read neuron zip file seems depend largely number fragments read , rather amount data fragment! Reading 90 can take < 10","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"","code":"if (FALSE) { # read neuron using raw segment identifier n <- read_segments2(22427007374) # read a neuron from a scene specification copied from Neuroglancer window # after clicking on the {} icon at top right n <- read_segments2(clipr::read_clip()) summary(n) n2 <- read_segments2(22427007374, datafrac=0.9) summary(n2) }"},{"path":"https://natverse.org/fafbseg/reference/read_topn.html","id":null,"dir":"Reference","previous_headings":"","what":"Find and read the largest n segments from one or more skeleton zip files — read_topn","title":"Find and read the largest n segments from one or more skeleton zip files — read_topn","text":"read_topn calls find_topn find top fragments reads using read_segments2. find_topn finds files, returning tibble (data.frame) results.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_topn.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find and read the largest n segments from one or more skeleton zip files — read_topn","text":"","code":"read_topn(zipfiles, n = 1, ...) find_topn(zipfiles, n = 1, decreasing = TRUE)"},{"path":"https://natverse.org/fafbseg/reference/read_topn.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find and read the largest n segments from one or more skeleton zip files — read_topn","text":"zipfiles path, name, number zipfiles. full path searched location defined options('fafbseg.skelziproot') n Number segments read ... additional arguments passed read_segments2 decreasing Whether sort skeletons decreasing order .e. largest first (default=TRUE)","code":""},{"path":"https://natverse.org/fafbseg/reference/read_topn.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find and read the largest n segments from one or more skeleton zip files — read_topn","text":"Note read fragment skeletons segment","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_topn.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find and read the largest n segments from one or more skeleton zip files — read_topn","text":"","code":"if (FALSE) { top3=read_topn(\"224270.zip\", n=3) }"},{"path":"https://natverse.org/fafbseg/reference/simple_python.html","id":null,"dir":"Reference","previous_headings":"","what":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","title":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","text":"Installs Python via isolated miniconda environment well recommended packages fafbseg. absolutely want use miniconda (much simpler get started) please read Details section.","code":""},{"path":"https://natverse.org/fafbseg/reference/simple_python.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","text":"","code":"simple_python( pyinstall = c(\"basic\", \"full\", \"extra\", \"cleanenv\", \"blast\", \"none\"), pkgs = NULL, miniconda = TRUE )"},{"path":"https://natverse.org/fafbseg/reference/simple_python.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","text":"pyinstall Whether \"basic\" install (enough functionality) \"full\" install, includes tools accessing fast/simple skeletons \"dotprops\" NBLAST via fafbseg-py package; \"extra\" installs neuron packages enable high resolution skeletonisation really necessary users frankly pain install. \"cleanenv\" show clean Python environment removing packages. \"blast\" show completely remove dedicated miniconda installation. Choosing =\"none\" skips update/install Python recommended packages installing extras defined pkgs. pkgs Additional python packages install. miniconda Whether use reticulate package's default approach dedicated python R based miniconda (recommended, default) allow specification different system installed Python via RETICULATE_PYTHON environment variable.","code":""},{"path":"https://natverse.org/fafbseg/reference/simple_python.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","text":"recommended Python install procedure installs miniconda Python distribution. added system PATH default can used exclusively R. want use miniconda, least ) make Python virtual environment using virtualenv (conda managing conda install) b) specify Python want use RETICULATE_PYTHON environment variable. can set RETICULATE_PYTHON usethis::edit_r_environ(). decided stick miniconda recommended, customisation still possible. halfway house, can set options('fafbseg.condaenv') specify non-standard miniconda virtual environment alternative default \"r-reticulate\". Furthermore can set environment variable RETICULATE_MINICONDA_PYTHON_VERSION=3.10 use newer version Python reticulate package recommends. sounds complicated, strongly suggest sticking default miniconda=TRUE approach. Note installing miniconda Python first time updating miniconda install, likely asked restart R. restart Python interpreter linked R session. Therefore Python already running session, must restart R use new Python install.","code":""},{"path":"https://natverse.org/fafbseg/reference/simple_python.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","text":"","code":"if (FALSE) { # just the basics simple_python(\"basic\") # if you want to skeletonise meshes simple_python(\"full\") # To install a special package using the recommended approach simple_python(pkgs=\"PyChunkedGraph\") # the same but without touching Python itself or the recommended packages simple_python('none', pkgs='PyChunkedGraph') # install a specific version of cloud-volume package simple_python('none', pkgs='cloud-volume~=3.8.0') # if you really need to insist (e.g. because a newer version is already installed) reticulate::py_install('cloud-volume==8.15.0', pip = TRUE) # install the latest version of a package from github simple_python('none', pkgs=\"git+git://github.com/schlegelp/skeletor@master\") # install a specific earlier version of a package simple_python('none', pkgs=\"git+git://github.com/seung-lab/DracoPy@v0.0.15\") # install all recommended packages but use your existing Python # only do this if you know what you are doing ... simple_python(\"full\", miniconda=FALSE) }"},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":null,"dir":"Reference","previous_headings":"","what":"Skeletonise neuron meshes using skeletor — skeletor","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"can skeletonise complex neuron meshes using skeletor skeletor-1.0.0. Skeletor python library function wraps series skeletor functions order smoothly process neurons use natverse. Note, default settings optimise performance fast skeletonisation flywire meshes. casual users recommend using 'wave' method, fast simple terms parameters, .e. just uses waves step_size. value 1 often works well.","code":""},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"","code":"skeletor( segments = NULL, obj = NULL, mesh3d = FALSE, save.obj = NULL, cloudvolume.url = getOption(\"fafbseg.cloudvolume.url\"), operator = c(\"umbrella\", \"contangent\"), clean = FALSE, remove_disconnected = 10, theta = 0.01, radius = TRUE, ratio = 0.1, SL = 10, WH0 = 2, iter_lim = 4, epsilon = 0.05, precision = 1e-06, validate = TRUE, method.radii = c(\"knn\", \"ray\"), method = c(\"wavefront\", \"vertex_clusters\", \"edge_collapse\", \"teasar\", \"tangent_ball\"), heal = TRUE, heal.k = 10L, heal.threshold = Inf, reroot = TRUE, k.soma.search = 10, radius.soma.search = 2500, brain = NULL, n = 5, n_rays = 20, projection = c(\"sphere\", \"tangents\"), fallback = \"knn\", waves = 2, step_size = 1, sampling_dist = 500, cluster_pos = c(\"median\", \"center\"), shape_weight = 1, sample_weight = 0.1, inv_dist = 100, cpu = Inf, elapsed = Inf, ... ) reroot_hairball(x, k.soma.search = 10, radius.soma.search = 2500, brain = NULL) download_neuron_obj( segments, save.obj = getwd(), ratio = 1, cloudvolume.url = getOption(\"fafbseg.cloudvolume.url\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"segments segment ids fetch (probably character vector), e.g. flywire IDs hemibrain bodyids. Meshes read specified CloudVolume (cloudvolume.url). obj character. Path obj file folder files. files read meshes skeletonised. segments given, argument overridden. mesh3d logical. TRUE neuron's volume added neuron object resultant neuronlist] neuron$mesh3d. save.obj character. Path save .obj file neuron volumes. NULL, .obj files saved (default). cloudvolume.url Optional url fetch meshes normally specified fafbseg.cloudvolume.url option. operator Laplacian operator use mesh contraction. \"contangent\" takes topology geometry mesh account better descriptor curvature flow. \"umbrella\", 'uniform weighting' operator uses topological features, making robust mesh flaws. clean logical. TRUE , python, skeletor.post.clean_up used collapse twigs line sight move nodes outside mesh back inside. Note magic bullet work (well) original mesh degenerate (e.g. internal faces watertight) begin . need ncollpyde python3 module installed. can get pip3 install ncollpyde. get issues related module, best set FALSE. skeletor.pre.fix_mesh also used remove seemingly erroneous vertices remove common mesh problems. remove_disconnected, integer 'False'. number given clean==TRUE,\\ iterate mesh's connected components remove consisting less given number vertices. example, ``remove_fragments=5`` drop parts mesh consist five less connected vertices. theta numeric. Used clean=TRUE. twig generate dot product tangent vectors parents. line perfectly dot product equal 1. theta determines much value can differ 1 us still prune twig: higher theta = pruning. radius logical. Whether return radius information skeleton node. want make use radii, need ncollpyde python3 module installed. can get pip3 install ncollpyde. get issues related module, best set FALSE. ratio numeric, 0-1. Factor reduce mesh faces. example, ratio 0.5 reduce number faces 50 percent. SL numeric. Factor contraction matrix multiplied iteration. theory, lower values likely get optimal contraction cost needing iterations. WH0 numeric. Initial weight factor attraction constraints. ratio initial weights WL0 (1e-3 * sqrt()) WH0 controls smoothness degree contraction first iteration result, thus determines amount details retained subsequent final contracted meshes. iter_lim integer. Maximum rounds contractions. epsilon numeric. Target contraction rate measured sum face areas contracted versus original mesh. Algorithm stop mesh contracted threshold. Depending mesh (number faces, shape) reaching strong contraction can extremely costly comparatively little benefit subsequent skeletonisation. Note algorithm might stop short target iter_lim reached first sum face areas increasing one iteration next instead decreasing. precision numeric. Sets precision finding least-square solution. main determinant speed vs quality: lower values take (much) longer get closer optimally contracted mesh. Higher values faster iterative contractions might stop early. validate True, try fix potential issues mesh (e.g. infinite values, duplicate vertices, degenerate faces) collapsing. Degenerate meshes can lead effectively infinite runtime function! method.radii method determine node's radius. \"knn\" uses k-nearest-neighbours get radii: fast potential wrong. \"ray\" uses ray-casting get radii: slower sometimes less wrong. method Skeletonisation comes two flavours different Pros Cons. \"vertex_clusters\" groups collapses vertices based geodesic distance along mesh's surface. fast scales well can lead oversimplification. Good quick & dirty skeletonisations. \"edge_collapse\" implements skeleton extraction edge collapse described Au et al. 2008. rather slow scale well really good preserving topology. heal logical. Whether , neuron id fragmented, stitch multiple fragments single neuron using minimum spanning tree. heal.k integer. number nearest neighbours consider trying merge different clusters. heal.threshold numeric. threshold distance new vertices connected (default=Inf disables feature). parameter prevents merging vertices far away main neuron likely spurious. reroot logical. Whether re-root neuron estimated 'soma'. soma usually large ball neuron, skeletonise something hair ball. can try detect quickly reroot skeleton . finding nearest leaf nodes leaf node, seeing going divergent directions. k.soma.search integer. number leaf nodes find, around leaf node radius radius.soma.search, rerooting process. larger number, better slower. radius.soma.search numeric. distance within search fellow leaf nodes rerooting process. inaccurate values high low. size expected soma. brain mesh3d hxsurf object within soma occur. re-rooting process. (Insect somata tend lie outside brain proper) n method.radii = \"knn\". Radius mean n nearest-neighbours. n_rays integer. method.radii = \"knn\".method.radii = \"ray\". Number rays cast node. projection method.radii = \"ray\". Whether cast rays sphere around node circle orthogonally node's tangent vector. fallback method.radii = \"ray\". point outside right surface mesh ray casting return nonsense results. can either ignore cases (\"None\"), assign arbitrary number can fall back radii k-nearest-neighbours (\"knn\"). waves integer. method = \"wavefront\". Number waves run across mesh. wave initialised different vertex produces slightly different rings. final skeleton produced mean across waves. waves produce higher resolution skeletons also introduce noise. step_size integer, Values greater 1 effectively lead binning rings. example stepsize 2 means two adjacent vertex rings collapsed center. can help reduce noise skeleton (counteracts large number waves) sampling_dist numeric. method = \"vertex_clusters\". Maximal distance vertices clustered. parameter tuned based resolution mesh. cluster_pos numeric. method = \"vertex_clusters\". determine x/y/z coordinates collapsed vertex clusters (.e. skeleton's nodes). \"median\": Use vertex closest cluster's centrer mass. \"center\": Use center mass. makes smoother skeletons can lead nodes outside mesh. shape_weight numeric. method = \"edge_collapse\". Weight shape costs penalize collapsing edges drastically change shape object. sample_weight numeric.method = \"edge_collapse\". Weight sampling costs penalise collapses generate prohibitively long edges. inv_dist numeric.method = \"teasar\". Distance along mesh used invalidation vertices. controls detailed (noisy) skeleton . cpu double (length one). Set limit total cpu time seconds. elapsed double (length one). Set limit total elapsed cpu time seconds ... Additional arguments passed reticulate::py_run_string. x nat::neuron object.","code":""},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"nat::neuronlist containing neuron skeleton objects.","code":""},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"pipeline: 1. Reads specified meshes CloudVolume source. 2. Simplifies mesh (python: skeletor.pre.simplify) 3. Contract mesh (python: skeletor.pre.contract) 4. Skeletonises mesh (python: skeletor.skeletonize) 5. Optionally, cleans mesh (python: skeletor.post.clean_up) 6. Optionally, add radius information skeleton (python: skeletor.post.radii) 7. Optionally, heal skeleton breaks (nat::stitch_neurons_mst) 8. Optionally, attempts re-root neuron 'hairball', .e. approximate soma (reroot_hairball). therefore need working python3 install skeletor, uses CloudVolume. require meshparty. Please install Python skeletor module described : https://github.com/schlegelp/skeletor. must ensure using python3 (implicitly explicitly) mesh fetching graphene servers depends . normally work: pip3 install git+git://github.com/schlegelp/skeletor@master. already installed skeletor found, recommend editing Renviron file set environment variable pointing correct Python. can usethis::edit_r_environ() setting e.g. RETICULATE_PYTHON=\"/usr/local/bin/python3\". (Though best practice create conda environment natverse R sessions direct R using environ file.) need set kind authentication order fetch volume data skeletonisation. See https://github.com/seung-lab/cloud-volume#chunkedgraph-secretjson get token save . can either save json snippet ~/.cloudvolume/secrets/cave-secret.json set environment variable (CHUNKEDGRAPH_SECRET=\"XXXX\". Finally also need set option pointing server. server hosting mesh data interested . might look something like: options(fafbseg.cloudvolume.url='graphene://https://xxx.dynamicannotationframework.com/segmentation/xxx/xxx') can easily add startup Rprofile usethis::edit_r_profile(). example, flywire data set, currently: 'graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31'. Roughly decreasing order impact speed: Ratio: lower ratio = less vertices = faster epsilon: lower target contraction rate = less steps = faster SL: faster contraction = pot. less steps target contraction rate = faster precision: lower precision = faster least-square computation = faster sampling_dist: larger dist = faster collapse mesh skeleton = faster","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"","code":"if (FALSE) { choose_segmentation(\"flywire\") nx=xform_brain(elmr::dense_core_neurons, ref=\"FlyWire\", sample=\"FAFB14\") xyz = xyzmatrix(nx) ids = unique(flywire_xyz2id(xyz[sample(1:nrow(xyz),100),])) neurons = skeletor(ids, brain = elmr::FAFB14.surf) plot3d(neurons) # note, in flywire space plot3d(nx, col=\"black\", lwd =2) # note, in flywire space # Also plot their meshes neuron.meshes = read_cloudvolume_meshes(ids) # We can also just save the .obj files dir.create(\"obj\") download_neuron_obj(ids, save.obj = \"obj\") # remove unlink(\"obj\", recurvise = TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/skelsforsegment.html","id":null,"dir":"Reference","previous_headings":"","what":"Find all skeleton fragments for one segment — skelsforsegment","title":"Find all skeleton fragments for one segment — skelsforsegment","text":"Find skeleton fragments one segment","code":""},{"path":"https://natverse.org/fafbseg/reference/skelsforsegment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find all skeleton fragments for one segment — skelsforsegment","text":"","code":"skelsforsegment(x, returndetails = FALSE)"},{"path":"https://natverse.org/fafbseg/reference/skelsforsegment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find all skeleton fragments for one segment — skelsforsegment","text":"x segment id returndetails Whether return zip list details","code":""},{"path":"https://natverse.org/fafbseg/reference/skelsforsegment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find all skeleton fragments for one segment — skelsforsegment","text":"character vector fragment names attribute containing path zip file","code":""},{"path":"https://natverse.org/fafbseg/reference/tabify_coords.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","title":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","text":"tabify_coords can used convert comma separated value clipboard e.g. neuroglancer tab separated values needed Seatable coordinates stored 3 separate columns. also words multiple coordinates.","code":""},{"path":"https://natverse.org/fafbseg/reference/tabify_coords.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","text":"","code":"tabify_coords(xyz = NULL, FUN = NULL, write_clip = NULL)"},{"path":"https://natverse.org/fafbseg/reference/tabify_coords.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","text":"xyz 3D Coordinates form compatible xyzmatrix. missing read clipboard. FUN transformer function apply incoming coordinates. convenience FUN missing xyz function function applied coordinates clipboard. write_clip Whether write result clipboard. missing (default) write clipboard coordinates read clipboard xyz=NULL.","code":""},{"path":"https://natverse.org/fafbseg/reference/tabify_coords.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","text":"Character vector tab separated coordinates. xyz missing returned invisibly also written clipboard.","code":""},{"path":"https://natverse.org/fafbseg/reference/tabify_coords.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","text":"","code":"# \\donttest{ tabify_coords(1:3) #> [1] \"1\\t2\\t3\" # } if (FALSE) { # copy position from clipboard and write back as TSV tabify_coords() # same but convert from raw coordinates to nm tabify_coords(flywire_raw2nm) }"},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":null,"dir":"Reference","previous_headings":"","what":"Read and write neuroglancer annotation info json files — write_nginfo","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"Read write neuroglancer annotation info json files","code":""},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"","code":"write_nginfo(anndf, f, sep = \"_\")"},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"anndf data.frame first column contains ids neuron additional columns contain annotations joined single string. f Path json file. write_nginfo create enclosing directory necessary. sep separator used paste multiple columns annotations together.","code":""},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"read_nginfo list containing annotations. write_nginfo, path f invisibly.","code":""},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"Note nothing specific flywire two functions - used data source.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"","code":"# \\donttest{ tf=tempfile(pattern = \"info\") df=data.frame(id=c(10000,10002), type=c(\"DNp01\")) write_nginfo(df, tf) # }"},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":null,"dir":"Reference","previous_headings":"","what":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"Add transformation one layers neuroglancer scene","code":""},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"","code":"# S3 method for ngscene xform(x, reg, layers = NULL, ...)"},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"x neuroglancer scene produced ngl_decode_scene reg registration either reglist containing multiple registrations single registration form handled xform. layers character vector specifying layers scene transform. elements named, names specify new names transformed layer. ... Additional arguments passed fit_xform reg specifies non-rigid registration. See details.","code":""},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"new ngscene object","code":""},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"Neuroglancer implements homogeneous affine transforms layers. However can still quite useful non-rigid transform applied layer e.g. underlying neurons undergoing rapid editing practical generate static set transformed meshes.","code":""},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"","code":"# \\donttest{ # flywire scene u='https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/4559706743898112' scf=ngl_decode_scene(u) m=matrix(c(-0.9663, -0.0695, 0.17, 0, 0.0351, 1.043, -0.028, 0, 0.1082, -0.0093, 0.9924, 0, 1021757.1284, 31409.0911, -85626.0572, 1), ncol=4) # nb replaces existing layer of this name xform(scf, m, layers=c('Production-mirrored')) #> neuroglancer scene with 4 layers and 1 segments (of which 1 shown) #> name type visible nsegs nhidden #> 1 Maryland-image image TRUE 0 0 #> 2 Production segmentation_with_graph TRUE 1 0 #> 3 Production-mirrored segmentation_with_graph TRUE 1 0 #> 4 brain_mesh_v141.surf segmentation TRUE 1 0 #> source #> 1 precomputed://https://bossdb-open-data.s3.amazonaws.com/flywire/fafbv14 #> 2 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 #> 3 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 #> 4 precomputed://gs://flywire_neuropil_meshes/whole_neuropil/brain_mesh_v141.surf scu=ngl_decode_scene('https://tinyurl.com/kj9rwn26') # make a new layer mirroring an existing layer scu2=xform(scu, m, layers=c('fly_v31_m'='fly_v31')) scu2 #> neuroglancer scene with 4 layers and 2 segments (of which 2 shown) #> name type visible nsegs nhidden #> 1 v1 image TRUE 0 0 #> 2 fly_v31 segmentation TRUE 2 0 #> 3 jfrc_mesh_test1 segmentation FALSE 1 0 #> 4 fly_v31_m segmentation TRUE 2 0 #> source #> 1 precomputed://gs://flywire_em/aligned/v1 #> 2 graphene://middleauth+https://prod.flywire-daf.com/segmentation/1.0/fly_v31 #> 3 precomputed://https://spine.itanna.io/files/eric/jfrc_mesh_test #> 4 graphene://middleauth+https://prod.flywire-daf.com/segmentation/1.0/fly_v31 # } if (FALSE) { browseURL(as.character(scu2)) } if (FALSE) { # mirror a flywire scene based on points from a specific pair of neurons mbon18.dps=read_l2dp('MBON18') mirror_reg=fit_xform(samplepts = mbon18.dps, refpts = nat.jrcbrains::mirror_fafb(mbon18.dps), subsample = 500) flywire_scene('MBON18') %>% ngl_decode_scene %>% xform(mirror_reg, layers=c(\"mirror\"=\"Production-segmentation_with_graph\")) %>% as.character() %>% browseURL() }"},{"path":"https://natverse.org/fafbseg/reference/xyzmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract the XYZ coordinates from neuroglancer mesh objects — xyzmatrix.ng_raw","title":"Extract the XYZ coordinates from neuroglancer mesh objects — xyzmatrix.ng_raw","text":"Extract XYZ coordinates neuroglancer mesh objects","code":""},{"path":"https://natverse.org/fafbseg/reference/xyzmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract the XYZ coordinates from neuroglancer mesh objects — xyzmatrix.ng_raw","text":"","code":"# S3 method for ng_raw xyzmatrix(x, ...) # S3 method for ng_raw_list xyzmatrix(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/xyzmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract the XYZ coordinates from neuroglancer mesh objects — xyzmatrix.ng_raw","text":"x ng_raw ng_raw_list object ... additional arguments (currently ignored)","code":""},{"path":[]},{"path":[]},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-0130","dir":"Changelog","previous_headings":"","what":"fafbseg 0.13.0","title":"fafbseg 0.13.0","text":"Feature optic info table @jefferis https://github.com/natverse/fafbseg/pull/174 Fix fafbseg inner_join / tests @jefferis https://github.com/natverse/fafbseg/pull/176 Support released cell type / connectivity data @jefferis https://github.com/natverse/fafbseg/pull/177 Add support ito_lee_hemilineage searches (d17a6edfcef0aa2b709797d33117b21c4c59b203) Give add_celltype_info suffix argument (136ecab3ecc149f683a3f81cf1c6cc02ce4c99c8) updates tests FAFB LR swap (afe883e86a8f958437c178a38d0878d47cc7298d) Fix flywire_latestids 64 bit root ids (aa8e560216af0117aed55fb49b222deccd385ccc) Full Changelog: https://github.com/natverse/fafbseg/compare/v0.12.0…v0.13.0","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/news/index.html","id":"whats-changed-0-12-0","dir":"Changelog","previous_headings":"","what":"What’s Changed","title":"fafbseg 0.12.0","text":"Add support cached flywire connectome dumps (see flywire_connectome_data() flywire_partner_summary2() flywire_adjacency_matrix2()) @jefferis https://github.com/natverse/fafbseg/pull/170 flywire_ids() (fafbseg functions take ids inputs) now supports full regular expressions define id queries. example /type:MBON0[24] (fc9df01b69eb5c540bc0bb1ebec89aad4621c695). flywire_islatest() cache option using specific version/timestamp (4b284d7d86b7e1a6da980c521a282fa693f71456). means flywire_updateids() flywire_partner_summary2() can fast using fixed version. export read_l2dp() read_l2skel() Neuroglancer URL handling (remember baseurl, support tinyurl) @jefferis https://github.com/natverse/fafbseg/pull/167 Make flywire_raw2nm() use vox dims supplied @jefferis https://github.com/natverse/fafbseg/pull/169 Add xform.ngscene() @jefferis https://github.com/natverse/fafbseg/pull/168 Python improvements standardise R-specific miniconda @jefferis https://github.com/natverse/fafbseg/pull/171. includes new fafbseg.condaenv option want specify non-standard miniconda environment. Support flytable super_class @jefferis https://github.com/natverse/fafbseg/pull/172 Export annotations neuroglancer info files (see write_nginfo()) @jefferis https://github.com/natverse/fafbseg/pull/173 add flytable_meta simple interface get flytable cell type information set flywire_ids Full Changelog: https://github.com/natverse/fafbseg/compare/v0.11.1…v0.12.0","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-0111","dir":"Changelog","previous_headings":"","what":"fafbseg 0.11.1","title":"fafbseg 0.11.1","text":"Fix nasty bug adjacency matrix inputids!=outputids @jefferis https://github.com/natverse/fafbseg/pull/165. Also ~2x speedup many use cases. Full Changelog: https://github.com/natverse/fafbseg/compare/v0.11.0…v0.11.1","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-0110","dir":"Changelog","previous_headings":"","what":"fafbseg 0.11.0","title":"fafbseg 0.11.0","text":"Support flytable cell type queries timestamped id updates @jefferis https://github.com/natverse/fafbseg/pull/163 Fix flytable maximum cells error adjusting chunksize @jefferis https://github.com/natverse/fafbseg/pull/147 respect chunksize provided flytable_list_rows @jefferis https://github.com/natverse/fafbseg/pull/148 Add support L2 ids speed flywire_latestid @jefferis https://github.com/natverse/fafbseg/pull/151 Better reporting token locations @jefferis https://github.com/natverse/fafbseg/pull/154 Feature/ng annotations @jefferis https://github.com/natverse/fafbseg/pull/153 Fix doc typo @jefferis https://github.com/natverse/fafbseg/pull/156 Fixes flywire_cave_query timestamp handling @jefferis https://github.com/natverse/fafbseg/pull/159 Feature navis+fafbseg-py reading L2 skeletons @jefferis https://github.com/natverse/fafbseg/pull/160 Teach flywire_cave_query query filter dicts @jefferis https://github.com/natverse/fafbseg/pull/162 Full Changelog: https://github.com/natverse/fafbseg/compare/v0.10.0…v0.11.0","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-0100","dir":"Changelog","previous_headings":"","what":"fafbseg 0.10.0","title":"fafbseg 0.10.0","text":"key change react breaking change URL access spine services. Feature flytable_append_rows @jefferis https://github.com/natverse/fafbseg/pull/132 Update Buhmann ref date @emilkind https://github.com/natverse/fafbseg/pull/138 Feature/misc flywire updates @jefferis https://github.com/natverse/fafbseg/pull/139 Add flywire_nuclei pkgdown @jefferis https://github.com/natverse/fafbseg/pull/140 flytable enhancements / fixes @jefferis https://github.com/natverse/fafbseg/pull/141 Better handling NAs handling body ids @jefferis https://github.com/natverse/fafbseg/pull/142 Fix/spine rename @jefferis https://github.com/natverse/fafbseg/pull/146 spine.janelia.org -> services.itanna.io @perlman https://github.com/natverse/fafbseg/pull/144 changed top.nt top.p top_nt top_p @alexanderbates https://github.com/natverse/fafbseg/pull/143","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"new-contributors-0-10-0","dir":"Changelog","previous_headings":"","what":"New Contributors","title":"fafbseg 0.10.0","text":"@emilkind made first contribution https://github.com/natverse/fafbseg/pull/138 @perlman made first contribution https://github.com/natverse/fafbseg/pull/144 Full Changelog: https://github.com/natverse/fafbseg/compare/v0.9.4…v0.10.0","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-094","dir":"Changelog","previous_headings":"","what":"fafbseg 0.9.4","title":"fafbseg 0.9.4","text":"add support Seung/Allen python CAVE including flywire_cave_client() flywire_cave_query() (#122) add flywire_updateids() (#127) also robustness handling NAs flywire_rootid() first implementation flytable_* functions including flytable_query() flytable_list_rows() flytable_login() (#126) note SSL certificate problem flywire/fanc queries bug (#125) Add ids type info flywire_partners() https://github.com/natverse/fafbseg/issues?q=closed%3A2021-09-20..2021-10-29+","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-093-pre-release-version","dir":"Changelog","previous_headings":"","what":"fafbseg 0.9.3 (pre-release version)","title":"fafbseg 0.9.3 (pre-release version)","text":"pre-release without full release notes, principally support new dependant package, fancr. new flywire_scene() function simple specification flywire neuroglancer scenes. add number features allow programmatic manipulation neuroglancer scenes. includes ngl_segments<-() replace segments scene +.ngscene() -.ngscene() add remove segments scene .character.ngscene() convert scene object URL. See examples ngl_segments() ngl_decode_scene() details (#55, #58). update flywire_set_token() support new cave zetta tokens (FANC dataset) (#119) expose chunkedgraph_token() function (#119) updates token handling handle FANC/FlyWire (#121) Private function check_cloudvolume_reticulate now supports minimum version Handle 1 node neurons (#120) Basic support Python caveclient package. enables fetching range annotation data CAVE (Connectome Annotation Versioning Engine) API including position nuclei user annotations. One notable improvement rapid fetching synaptic partner information. implemented new method=\"cave\" option flywire_partner_summary() (#122). https://github.com/natverse/fafbseg/issues?q=closed%3A2020-12-27..2021-09-20+","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-09","dir":"Changelog","previous_headings":"","what":"fafbseg 0.9","title":"fafbseg 0.9","text":"version change 0.9 reflects small potentially breaking changes user visible behaviour. particular ngl_segments() now returns character default (protect FlyWire ids, expressed 8 byte floating point values). Add flywire_latestid() function map (past) root id current root id. Specifically identifies neuron inheriting largest number super voxels object specified input root id. Support Google ffn1 20200412 segmentation (#14, #46) Make ngl_segments() return ids character vector, rather numeric, default. Also exclude hidden ids default (#50, #51). Allow ngl_segments() (flywire_*) fns accept URLs surface meshes. Previously cause error (#52) Fix ngl_encode_url() tested flywire scenes can parsed R converted back valid URLs can opened flywire.ai (#53) Add print.ngscene method summarise neuroglancer scenes console (#54) flywire_cloudvolume() enables improved low-level support flywire+cloudvolume (exposing reusable cloudvolume object) (#48) full list closed issues GitHub. # fafbseg 0.8.2 Much faster flywire_xyz2id() supervoxel id mapping using spine service (#44) Add new flywire_leaves() function find supervoxels neuron (#43) Fixing typos adding doi TEASAR (#41 @mmc46) Fixing 2 things overlay mesh+skeleton example (#40 @mmc46) Fix flywire_xyz2id eg doc ‘natverse flywire meshes’ returns error (#39) Output dr_fafbseg() points wrong token helper function (#38 @mmc46) can see full list closed issues GitHub.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-081","dir":"Changelog","previous_headings":"","what":"fafbseg 0.8.1","title":"fafbseg 0.8.1","text":"New function skeletor() skeletonise meshes especially flywire neurons based Python package name (#35). Large speed flywire_rootid() (#37) Fix flywire_xyz2id() can actually find supervoxels (well root ids) (#37) function dr_fafbseg() give status update installation (#36) read_cloudvolume_meshes() can now accept flywire URLs (expanded necessary define segments download) can see full list closed issues GitHub.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-080","dir":"Changelog","previous_headings":"","what":"fafbseg 0.8.0","title":"fafbseg 0.8.0","text":"Support basic flywire API calls #31, #34 Better integrate flywire api features Fix/flywire coordinate errors Fix error fafb2flywire() xform_brain #30, #32, #33 Switch transform-service API spine Add support FANC3-FANC4 transforms #28 switch back wire3d #27 Add fafb2flywire() .e. inverse original FlyWire->FAFB transformation #26 Support reading flywire meshes without cloudvolume #25 Flywire API streamlining (@SridharJagannathan) #22 Teach read_cloudvolume_meshes() work flywire URLs #20 ngl_segments() needs able expand flywire URLs #16 can see full list closed issues GitHub.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-070","dir":"Changelog","previous_headings":"","what":"fafbseg 0.7.0","title":"fafbseg 0.7.0","text":"basic support reading meshes via CloudVolume e.g. fetch neurons flywire.ai. See read_cloudvolume_meshes() details including required Python setup. basic support skeletonising neurons meshed (e.g. flywire neurons) via meshparty_skeletonize() add flywire2fafb() support transforming neurons FlyWire->FAFB (loss accuracy reverse) (#11) includes fix NaN values return (#12,#13) much faster FlyWire->FAFB transformation, millions points per minute (#24) moved repo https://github.com/natverse/fafbseg (#19)","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-065","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.5","title":"fafbseg 0.6.5","text":"default chunksize brainmaps_xyz2id() reduce 200 reflect API changes. new functions choose_segmentation() with_segmentation() choose default auto-segmentation New Shiny app (see README https://jefferislab.shinyapps.io/CATMAID-Neuroglancer-Converter/) give brainmaps_fetch() generic cache option ability clear cache brainmaps_clear_cache() (#8) give brainmaps_fetch() retry option help sporadic timeouts (#9) give catmaid2ngl() chunksize option can used reduce timeout issues. simplify package .onLoad retire fafbseg.divisor option (now calculated automatically rather user option) simplify internal brainmaps_voxdims function using cache mechanism","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-064","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.4","title":"fafbseg 0.6.4","text":"fix bug revealed latest public version zip package fix missing import dplyr::n() find_topn()","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-063","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.3","title":"fafbseg 0.6.3","text":"Give find_topn() read_top() ability return segments increasing (rather decreasing) size order.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-062","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.2","title":"fafbseg 0.6.2","text":"fix ngl_encode_url() one segment scene (#5) fix handling neuroglancer URLs two segment sources (#4)","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-061","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.1","title":"fafbseg 0.6.1","text":"New catmaid2ngl() function methods, high level approach converting URLs, neurons etc representations based Neuroglancer / brainmaps data.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-060","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.0","title":"fafbseg 0.6.0","text":"default remote volume brainmaps_xyz() updated brainmaps://772153499790:fafb_v14:fafb_v14_16nm_v00c_split3xfill2_flatreseg2_skeletons32 volume also used read.neurons.brainmaps()","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-055","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.5","title":"fafbseg 0.5.5","text":"brainmaps_skeleton() read.neurons.brainmaps() now use brainmaps URI specify remote skeleton source. new package option fafbseg.skeletonuri specify default remote skeleton source give brainmaps_xyz2id() chunksize argument handle query points remote API accept single call.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-054","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.4","title":"fafbseg 0.5.4","text":"add read.neuron.brainmaps() read.neurons.brainmaps() read skeletons nat neuron objects web. depends lower level brainmaps_skeleton() function. teach find_merge_groups() return segment ids","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-053","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.3","title":"fafbseg 0.5.3","text":"compare_ng_neuron(): add pointsize sample_dots args doc / example tweaks","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-052","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.2","title":"fafbseg 0.5.2","text":"Support reading 3D meshes directly brainmaps API via read_brainmaps_meshes()","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-051","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.1","title":"fafbseg 0.5.1","text":"export brainmaps_xyz2id() (#2)","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-050","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.0","title":"fafbseg 0.5.0","text":"Add brainmaps_auth(), brainmaps_fetch() talk brainmaps API Add brainmaps_xyz2id() convert arbitrary XYZ locations corresponding segment id. Teach find_merged_segments() return merge groups","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-041","dir":"Changelog","previous_headings":"","what":"fafbseg 0.4.1","title":"fafbseg 0.4.1","text":"additional functions reading/processing merge (agglomeration) information including read_mergeinfo(), make_merge_graph(), merge_graph_components(). used generate fafbsegdata package useful right.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-040","dir":"Changelog","previous_headings":"","what":"fafbseg 0.4.0","title":"fafbseg 0.4.0","text":"Add find_merged_segments() find raw segments candidate merges agglomeration runs. functionality depends new fafbsegdata package, installed automatically suggested dependency. Switch default zip file divisor 1E6 (actually check contents zip file accommodate new default Peter Li’s 2018-10-02 skeleton release (fafb14_v00c_split3xfill2x_skeleton32nm512_nnconn75_thresh1000_sparse250)","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-035","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.5","title":"fafbseg 0.3.5","text":"fix bug read_segments() datafrac argument logic - reading largest fragment datafrac applies files > minfilesize add internal skelsforsegments() function progress use read_segments2() Turn zip_list memoisation 5 min cache timeout - can speed read_segments2 considerably multiple segments inside zip file.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-034","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.4","title":"fafbseg 0.3.4","text":"turn zip_list memoisation save memory (#1)","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-033","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.3","title":"fafbseg 0.3.3","text":"teach read_segments2() read top n percent skeletons file size additional option read coordinates fix handling zip files >65535 files (see https://github.com/r-lib/zip/issues/11) making use new ziplist64 package available","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-032","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.2","title":"fafbseg 0.3.2","text":"export ngl_decode_scene() function parse neuroglancer URLs JSON scene specifications (turn allowing opened CATMAID) fail better skeleton zip files missing fix bug reading multiple bit64 ids","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-031","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.1","title":"fafbseg 0.3.1","text":"export open_fafb_ngl() teach open_fafb_ngl produce coordinate string paste Neuroglancer add ngl_segments() extract segment ids diverse scene specifications URLs JSON fragments copied Neuroglancer web page","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-030","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.0","title":"fafbseg 0.3.0","text":"read_segments2() (memory zip extraction) recommended add find_topn() find biggest segments zip files teach read_topn() cope multiple zip files fix sample URL point correct segmentation (fafb_v14_16nm_v00c_split3xfill2) compatible skeletons received.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-020","dir":"Changelog","previous_headings":"","what":"fafbseg 0.2.0","title":"fafbseg 0.2.0","text":"add support reading neurons zipped skeleton files support mapping ids files vice versa simplify setup neuroglancer URLs improved docs","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-010","dir":"Changelog","previous_headings":"","what":"fafbseg 0.1.0","title":"fafbseg 0.1.0","text":"first version","code":""}] +[{"path":"https://natverse.org/fafbseg/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://natverse.org/fafbseg/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. 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Definitions","title":"GNU General Public License","text":"“License” refers version 3 GNU General Public License. “Copyright” also means copyright-like laws apply kinds works, semiconductor masks. “Program” refers copyrightable work licensed License. licensee addressed “”. “Licensees” “recipients” may individuals organizations. “modify” work means copy adapt part work fashion requiring copyright permission, making exact copy. resulting work called “modified version” earlier work work “based ” earlier work. “covered work” means either unmodified Program work based Program. “propagate” work means anything , without permission, make directly secondarily liable infringement applicable copyright law, except executing computer modifying private copy. Propagation includes copying, distribution (without modification), making available public, countries activities well. “convey” work means kind propagation enables parties make receive copies. 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Protecting Users’ Legal Rights From Anti-Circumvention Law","title":"GNU General Public License","text":"covered work shall deemed part effective technological measure applicable law fulfilling obligations article 11 WIPO copyright treaty adopted 20 December 1996, similar laws prohibiting restricting circumvention measures. convey covered work, waive legal power forbid circumvention technological measures extent circumvention effected exercising rights License respect covered work, disclaim intention limit operation modification work means enforcing, work’s users, third parties’ legal rights forbid circumvention technological measures.","code":""},{"path":"https://natverse.org/fafbseg/LICENSE.html","id":"id_4-conveying-verbatim-copies","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"4. 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Use with the GNU Affero General Public License","title":"GNU General Public License","text":"Notwithstanding provision License, permission link combine covered work work licensed version 3 GNU Affero General Public License single combined work, convey resulting work. terms License continue apply part covered work, special requirements GNU Affero General Public License, section 13, concerning interaction network apply combination .","code":""},{"path":"https://natverse.org/fafbseg/LICENSE.html","id":"id_14-revised-versions-of-this-license","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"14. Revised Versions of this License","title":"GNU General Public License","text":"Free Software Foundation may publish revised /new versions GNU General Public License time time. new versions similar spirit present version, may differ detail address new problems concerns. version given distinguishing version number. Program specifies certain numbered version GNU General Public License “later version” applies , option following terms conditions either numbered version later version published Free Software Foundation. Program specify version number GNU General Public License, may choose version ever published Free Software Foundation. Program specifies proxy can decide future versions GNU General Public License can used, proxy’s public statement acceptance version permanently authorizes choose version Program. Later license versions may give additional different permissions. However, additional obligations imposed author copyright holder result choosing follow later version.","code":""},{"path":"https://natverse.org/fafbseg/LICENSE.html","id":"id_15-disclaimer-of-warranty","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"15. Disclaimer of Warranty","title":"GNU General Public License","text":"WARRANTY PROGRAM, EXTENT PERMITTED APPLICABLE LAW. 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Interpretation of Sections 15 and 16","title":"GNU General Public License","text":"disclaimer warranty limitation liability provided given local legal effect according terms, reviewing courts shall apply local law closely approximates absolute waiver civil liability connection Program, unless warranty assumption liability accompanies copy Program return fee. END TERMS CONDITIONS","code":""},{"path":"https://natverse.org/fafbseg/LICENSE.html","id":"how-to-apply-these-terms-to-your-new-programs","dir":"","previous_headings":"","what":"How to Apply These Terms to Your New Programs","title":"GNU General Public License","text":"develop new program, want greatest possible use public, best way achieve make free software everyone can redistribute change terms. , attach following notices program. safest attach start source file effectively state exclusion warranty; file least “copyright” line pointer full notice found. Also add information contact electronic paper mail. program terminal interaction, make output short notice like starts interactive mode: hypothetical commands show w show c show appropriate parts General Public License. course, program’s commands might different; GUI interface, use “box”. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU GPL, see . GNU General Public License permit incorporating program proprietary programs. program subroutine library, may consider useful permit linking proprietary applications library. want , use GNU Lesser General Public License instead License. first, please read .","code":" Copyright (C) 2018 Gregory Jefferis This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . fafbseg Copyright (C) 2018 Gregory Jefferis This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://natverse.org/fafbseg/SUPPORT.html","id":null,"dir":"","previous_headings":"","what":"Getting help with fafbseg","title":"Getting help with fafbseg","text":"Thanks using fafbseg. ’re sorry ’re trouble, don’t worry, ’re help! get help quickly possible, please read following:","code":""},{"path":"https://natverse.org/fafbseg/SUPPORT.html","id":"search","dir":"","previous_headings":"","what":"Search","title":"Getting help with fafbseg","text":"first thing see anyone problem : Search nat-user google group. Search GitHub issues fafbseg package. Search GitHub issues across whole natverse case problem related package. can add terms search search box top left page. solves problem, great!","code":""},{"path":"https://natverse.org/fafbseg/SUPPORT.html","id":"known-problems","dir":"","previous_headings":"","what":"Known Problems","title":"Getting help with fafbseg","text":"need help known problem: found relevant thread nat-user google group: please reply . found GitHub issue: please reply details just like (click emoji button add thumbs ) let us know ’re trouble . ’ll need GitHub login . ’re sure: ask new question nat-user google group linking found.","code":""},{"path":"https://natverse.org/fafbseg/SUPPORT.html","id":"new-problems","dir":"","previous_headings":"","what":"New Problems","title":"Getting help with fafbseg","text":"looks like new problem : just question: please ask nat-user google group. need report new bug: please file issue. ’re sure: please just ask nat-user google group! problem bug feature request, can easily return report - may able point existing report workaround.","code":""},{"path":"https://natverse.org/fafbseg/SUPPORT.html","id":"good-questions-and-bug-reports","dir":"","previous_headings":"","what":"Good Questions and Bug Reports","title":"Getting help with fafbseg","text":"specific Include code triggered problem possible, make minimal reproducible example (reprex) much easier us help can run reprex machine without data. might want use sample data nat package help, refer publicly available data online. can use reprex package help prepare reprex. Read Get help! section tidyverse site information. Thanks help!","code":""},{"path":"https://natverse.org/fafbseg/articles/FAFB-FlyWire.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"FAFB-FlyWire","text":"articles gives quick overview mapping points FAFB14 (used “walled garden” Virtual Fly Brain FlyWire.","code":"library(fafbseg) #> Run dr_fafbseg() for a status report on your installation"},{"path":"https://natverse.org/fafbseg/articles/FAFB-FlyWire.html","id":"basic-point-mapping","dir":"Articles","previous_headings":"Introduction","what":"Basic point mapping","title":"FAFB-FlyWire","text":"known points Compare displacements (nm) forward inverse mapping sample neuron. First map points stats quick histogram","code":"# identified location in FAFB14 p.fafb.nm <- cbind(477042, 284535, 90680) p.fafb.raw <- p.fafb.nm/c(4,4,40) # corresponding location in FlyWire p.flywire.raw <- cbind(118865, 71338, 2267) p.flywire.nm <- p.flywire.raw * c(4,4,40) # check displacement flywire2fafb(p.flywire.nm)-p.fafb.nm #> X Y Z #> [1,] 3 -1 0 # check what happens when you apply the inverse fafb2flywire(p.fafb.nm)-p.flywire.nm #> X Y Z #> [1,] -3 2 0 data(\"AV4b1\", package='catmaid') before=xyzmatrix(AV4b1) after=fafb2flywire(before) d=sqrt(rowSums((before-after)^2)) summary(d) #> Min. 1st Qu. Median Mean 3rd Qu. Max. #> 2.0 287.9 416.0 446.9 559.1 2113.7 hist(d, br=20, main='Displacement /µm') sample_points_in_surf <- function(x, n){ x=as.mesh3d(x) bb=boundingbox(x) mm=mapply(runif, min=bb[1,], max=bb[2,], n = n) colnames(mm)=c(\"X\",\"Y\",\"Z\") data.frame(mm, inside=pointsinside(mm,x)) } set.seed(42) sxyz=sample_points_in_surf(FAFB14.surf,25000) sxyz.in=subset(sxyz, inside) sxyz.fw=fafb2flywire(xyzmatrix(sxyz.in)) deltas=sxyz.fw-sxyz.in delta=rowSums(deltas[,c(\"X\",\"Y\")]) jet.colors<-colorRampPalette(c('navy','cyan','yellow','red')) nclear3d(); spheres3d(xyzmatrix(sxyz.in), col=jet.colors(10)[cut(delta, breaks = 10)], rad=2000)"},{"path":"https://natverse.org/fafbseg/articles/FAFB-FlyWire.html","id":"round-trip-error","dir":"Articles","previous_headings":"Introduction","what":"Round trip error","title":"FAFB-FlyWire","text":"Let’s send points back ","code":"sxyz.fafb2=flywire2fafb(sxyz.fw) deltas=sxyz.fafb2-xyzmatrix(sxyz.in) delta=rowSums(deltas[,c(\"X\",\"Y\")]) hist(delta, main = \"Round Trip Error\", xlab='delta /nm')"},{"path":"https://natverse.org/fafbseg/articles/FAFB-FlyWire.html","id":"mapping-anything","dir":"Articles","previous_headings":"","what":"Mapping anything","title":"FAFB-FlyWire","text":"map complex objects, use xform_brain() Note relevant links: Load flywire mesh plot CATMAID skeleton","code":"AV4b1.fw=xform_brain(AV4b1, sample='FAFB14', reference = 'FlyWire') # find the main branch point of a neuron, a good place to point to mainbranch <- function(x, ...) { if(is.neuronlist(x)) return(nlapply(x, mainbranch, ...)) sx=nat::simplify_neuron(x, ...) xyzmatrix(sx)[sx$BranchPoints,] } choose_segmentation(\"flywire\") open_fafb_ngl(mainbranch(AV4b1.fw), coords.only = TRUE) #> [1] \"88371.25,40478.75,3668\" av4.fwm=read_cloudvolume_meshes('720575940618054533') nclear3d() plot3d(AV4b1.fw, col='red', lwd=3) wire3d(av4.fwm[[1]], col='grey', alpha=.2)"},{"path":"https://natverse.org/fafbseg/articles/accessing-graphene-server.html","id":"tldr","dir":"Articles","previous_headings":"","what":"tl;dr","title":"Accessing the chunked graph server","text":"set programmatic access FlyWire, use flywire_set_token() follows: follow -screen prompts.","code":"library(fafbseg) flywire_set_token()"},{"path":"https://natverse.org/fafbseg/articles/accessing-graphene-server.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Accessing the chunked graph server","text":"main goal connectomics trace (segment) branching morphology neurons 3D volume (typically based electron microscopy) identify connections (synapses) together define connectome. Neuron segmentation can either skeleton-based (centre line defining part neuronal arbour traced ) voxel-based, filled 3D structure defined labelling every voxel integer id, representing membership particular object; typically displayed 3D mesh surface. Although skeleton-based segmentation efficient manual segmentation humans, voxel-wise segmentation natural machine learning algorithms. Furthermore, generates richer representation neuron (capturing structural features) , crucially, also resolves ambiguities object identity. example two users manually trace neuron skeleton, place nodes different positions trivial computationally determine part object join tracing independent pieces together. contrast voxel-wise segmentation every xyz location image explicitly defined part specified object. voxel-wise segmentation, neuron can considered collection voxels grouped together connected components. Machine learning based algorithms try identify connected components (e.g. using flood filling networks). However machines perfect many segments wrongly connected. Hence need step humans proofread segments alters connections. connected components can readily represented vertices connections edges. human observer essentially modifies edges graph structure. Note graph representation object segmentation distinct binary tree represents neuronal morphology connection graph neurons within neural network. graph based representation segmentation also advantages synchronous editing, can major technical issue many users generate proof-read segmentation time. CATMAID web application (skeleton based tracing) approaches allowing multiple users edit neurons using shared database. implementation reduces conflicts simple expedient allowing users see ’s work real time. However explicit merge step needed conflicting annotations created (usually editing happened different database) can computationally complex. Seung Lab developed data structure system called chunked graph lets users modify segmentations (3D voxel-wise) real-time allows access earlier versions segmentation. brief overview system published medium. practice initial -segmentation generated, consisting many “supervoxels”. supervoxels, small collections perhaps tens thousands individual voxels, effectively immutable almost certain belong object. supervoxels leaves graph database representation segmented objects. use supervoxels reduces size graph database compared situation individual voxel represented. long human proof-reading based base segmentation, strategies merge proof-reading even happens asynchronously. However merging proof-reading based different base segmentations defined different underlying supervoxels still complex; similar challenge exists necessary map proof-reading based one base segmentation newer (presumably improved) base segmentation.","code":""},{"path":"https://natverse.org/fafbseg/articles/accessing-graphene-server.html","id":"goal","dir":"Articles","previous_headings":"","what":"Goal","title":"Accessing the chunked graph server","text":"One goals fafbseg package provide access different 3D segmentations FAFB dataset. Currently available segmentations include FlyWire (based 3D CNNs : U-Net) GoogleBrain (based recursive CNNs : flood-filling networks). Furthermore enable location transfer comparison CATMAID (skeleton based) manual reconstruction. order achieve one needs access 3D segmentations stored graph database Graphene/PyChunkedGraph. also provide Python tool called CloudVolume provides programmatic access graph database.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/articles/accessing-graphene-server.html","id":"simple-instructions","dir":"Articles","previous_headings":"ChunkedGraph token","what":"Simple Instructions","title":"Accessing the chunked graph server","text":"gain access Graphene/Chunkedgraph server using token granted authenticate via Google account. simplest way offer open browser, generate new token save standard location. Note invalidate previous token!","code":"library(fafbseg) flywire_set_token()"},{"path":"https://natverse.org/fafbseg/articles/accessing-graphene-server.html","id":"details","dir":"Articles","previous_headings":"ChunkedGraph token","what":"Details","title":"Accessing the chunked graph server","text":"manual steps flywire_set_token() tries automate follows Visit https://globalv1.flywire-daf.com/auth/api/v1/refresh_token, Copy token present , let’s say \"xxyyzz\" create file named cave-secret.json location ~/.cloudvolume/secrets/cave-secret.json. example, Terminal: Paste following contents Save file Now access chunked graph server","code":"mkdir -p .cloudvolume/secrets/ touch ~/.cloudvolume/secrets/cave-secret.json open ~/.cloudvolume/secrets/cave-secret.json -e { \"token\": \"xxyyzz\" }"},{"path":"https://natverse.org/fafbseg/articles/capturing-ngl-meshes.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Capturing neuroglancer meshes from a browser scene","text":"Originally fafbseg support reading objects directly neuroglancer scene URL. approach capture interactive web session. Things moved ability read meshes directly brainmaps API via read_brainmaps_meshes() using CloudVolume interface via read_cloudvolume_meshes(). However information retained reference might helpful direct mesh retrieval yet available.","code":""},{"path":"https://natverse.org/fafbseg/articles/capturing-ngl-meshes.html","id":"method","dir":"Articles","previous_headings":"","what":"Method","title":"Capturing neuroglancer meshes from a browser scene","text":"make sure one neuron displayed want parse object identifier relationships. Chrome can generate appropriate set curl download commands : Opening Chrome Developer console (View … Developer … JavaScript Console), (re)loading page interest selecting network tab selecting downloaded object right clicking choosing (Copy … Copy cURL). can either save contents clipboard text file (e.g.  all_curl.sh) just keep clipboard. can go R proceed follows","code":"library(fafbseg) # omit the first argument if you want to use the clipboard fetch_all_curl(\"all_curl.sh\", outdir=\"alldata\", regex=\"brainmaps.googleapis.com\", fixed=TRUE) meshdata=read_ng_dump(\"alldata\") library(elmr) # or whatever your CATMAID neuron skid is y=read.neuron.catmaid(23432) compare_ng_neuron(meshdata, y)"},{"path":"https://natverse.org/fafbseg/articles/fafbseg-catmaid-legacy-info.html","id":"neuroglancer-urls","dir":"Articles","previous_headings":"","what":"Neuroglancer URLs","title":"fafbseg-catmaid-legacy-info","text":"can use package generate URLs pointing defined location neuroglancer dataset. includes arbitrary locations FAFB dataset specified interactively using CATMAID URLs. example, find location referenced tweet: Zoom @dddavi whole fly brain EM dataset using public @catmaid server hosted @virtualflybrain. whole brain view synaptic detail. Click explore location within mushroom body parallel fibre system ! https://t.co/JxsBGe3RbJ @flyconnectome pic.twitter.com/NfDiXgJOPX can use approach https://flywire.ai URLs additional option transforming coordinates get closer correct location FlyWire assembly FAFB data (typically hundred nm ). See flywire2fafb() details.","code":"library(fafbseg) # First, optionally set a package option with an example neuroglancer URL for your dataset. # This URL will define the image layers that are visible. You need to use an # URL for which you have access. The package ships with a default using segmentation # fafb_v14:fafb_v14_16nm_v00c_split3xfill2 which is probably what you need. options(fafbseg.sampleurl=\"https://\") # Now open location specified by CATMAID URL u='https://fafb.catmaid.virtualflybrain.org/?pid=2&zp=131280&yp=170014.98879622458&xp=426584.81386896875&tool=navigator&sid0=2&s0=-1' open_fafb_ngl(u) # or display raw coordinates that you can paste into active Neuroglancer session open_fafb_ngl(u, coords.only = TRUE) # opens a new browser tab with_segmentation('flywire31', open_fafb_ngl(u, sample = 'FAFB14', reference = \"FlyWire\")) # writes coordinates to clipboard so that you can paste them into an existings # flywire neuroglancer browser tab with_segmentation('flywire31', clipr::write_clip( open_fafb_ngl(u, coords.only = TRUE, sample = 'FAFB14', reference = \"FlyWire\")))"},{"path":"https://natverse.org/fafbseg/articles/fafbseg-catmaid-legacy-info.html","id":"catmaid-urls","dir":"Articles","previous_headings":"","what":"CATMAID URLs","title":"fafbseg-catmaid-legacy-info","text":"can also go opposite direction convert neuroglancer location CATMAID URL. neuroglancer location can come either URL JSON scene specification obtained clicking {} icon.","code":"# round trip using the CATMAID URL we used earlier ngu = open_fafb_ngl(u, open = FALSE) # now open using elmr package - installed like so if necessary: # natmanager::install(pkgs=\"natverse/elmr\") elmr::open_fafb(ngl_decode_scene(ngu))"},{"path":"https://natverse.org/fafbseg/articles/fafbseg-catmaid-legacy-info.html","id":"shiny-application","dir":"Articles","previous_headings":"","what":"Shiny application","title":"fafbseg-catmaid-legacy-info","text":"package now includes simple Shiny application translates two URL schemes. can use online version app https://jefferislab.shinyapps.io/CATMAID-Neuroglancer-Converter/ download GitHub run locally latest version app: Currently application convert FlyWire<->FAFB coordinates, relatively simple addition using flywire2fafb().","code":"if (!require(\"shiny\")) install.packages(\"shiny\") shiny::runGitHub(\"natverse/fafbseg\", subdir = \"inst/app/\")"},{"path":"https://natverse.org/fafbseg/articles/fafbseg-catmaid-legacy-info.html","id":"analysis-of-neuroglancer-meshes","dir":"Articles","previous_headings":"","what":"Analysis of neuroglancer meshes","title":"fafbseg-catmaid-legacy-info","text":"Currently package provides functionality read neuroglancer meshes R compare meshes traced neuron objects e.g. CATMAID. need authenticate appropriate API. Alternatively see article Capturing neuroglancer meshes browser scene. can read meshes FlyWire segmentation FAFB (roughly) can read meshes Google brain segmentation FAFB (roughly)","code":"choose_segmentation(release = 'flywire31') open_fafb_ngl(c(109459, 41305, 5424)*c(4,4,40)) va6pn=read_cloudvolume_meshes(\"720575940633169983\") # compare with VFB CATMAID library(elmr) va6pn.skel=read.neurons.catmaid(\"name:VA6.*PN\") # let's take a look at those plot3d(va6pn, col='grey', lwd=0.5, type='wire') # only plot first neuron on RHS plot3d(va6pn.skel[1], lwd=3, col='red') # can also transform the FAFB14 skeleton from VFB to FlyWire coordinates va6pn.skel.fw <- xform_brain(va6pn.skel[1], reference = 'FlyWire', sample='FAFB14') nclear3d() plot3d(va6pn, col='grey', lwd=0.5, type='wire') # only plot first neuron on RHS plot3d(va6pn.skel.fw, lwd=3, col='red') choose_segmentation(release = '20190805') open_fafb_ngl(c(109459, 41305, 5424)*c(4,4,40)) va6pn=read_brainmaps_meshes(\"710435991\")"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"tldr","dir":"Articles","previous_headings":"","what":"tl;dr","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Experts disagree best method install Python associated packages. users whose principal use Python R, found following reticulate package’s default setting dedicated miniconda installation simple efficient way install Python environment R. provides access cloud-volume package powers many functions required talk flywire environment. Extension packages mesh skeletonisation also install cleanly method. Now Python installed check everything went well Caveats avoid complications, recommend starting clean R session installation. told restart R session update Python disk already running Python interpreter attached R session. taken steps tweak version Python use (e.g. via RETICULATE_PYTHON environment variable) python virtual environment R use. want use different Python can : recommend set RETICULATE_PYTHON point explicitly preferred Python. details see simple_python() help consult extended instructions .","code":"# If you don't already have the R -> python bridge package if(!requireNamespace('reticulate')) install.packages(\"reticulate\") # just the basics for python simple_python(\"basic\") # if you want to skeletonise meshes simple_python(\"full\") fafbseg::dr_fafbseg() # dr_fafbseg may tell you to get a flywire authorisation token (one time step) flywire_set_token() simple_python(\"full\", miniconda = FALSE)"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"need cloudvolume meshparty python order get flywire meshes. help article written much experience using python. experienced users, see cloud-volume install basic command info . new python, especially pip, conda, blog post can helpful understanding ’s . Bottom line conda can install python non-python software specific environment, trying keep environment functional taking different dependencies packages consideration, pip installs python packages wherever want, whatever tell install. general packages can pip install (PyPi), can also conda environment without problem cases. Since bunch non-python dependencies cloud-volume meshparty , conda looks better want.","code":""},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"install-conda","dir":"Articles","previous_headings":"","what":"Install conda","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Download miniconda install , includes conda, python, basic packages, including pip: Make sure know install (e.g. usually : /opt/miniconda3), update recent version Terminal: $ conda update conda Hit ‘y’ proceed prompted. default python /opt/miniconda3/bin/python, can check $ python","code":""},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"work-with-a-new-environment","dir":"Articles","previous_headings":"","what":"Work with a new environment","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Use conda create activate environment can install everything need: (deactivate active environment, use $ conda deactivate flywire_env) point environment can use conda install simply anything ’s available , pip also install packages environment, unless PATH variable bash.profile file tells otherwise. Check pip default: $ pip give something miniconda folder, like /opt/miniconda3/envs/flywire_env/bin/pip. However, might system python’s pip. can comment PATH variable python .bash.profile running: $ touch ~/.bash_profile; open ~/.bash_profile adding # lines PATH=\"/Library/Frameworks/Python.framework/Versions/3.7/bin:${PATH}\" export PATH. pip return right thing, thing applies python. Alternatively can always specify terminal pip want use, suboptimal (e.g. /opt/miniconda3/envs/flywire_env/bin/pip install cloud-volume).","code":"$ conda create --name flywire_env python=3.7 $ conda activate flywire_env $ conda install nomkl"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"install-cloudvolume","dir":"Articles","previous_headings":"","what":"Install cloudvolume","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Now can install cloud-volume $ pip install cloud-volume need compiler (XCode Mac) install everything. don’t XCode, either need update OSX recent version download AppStore, can get version compatible current system : https://developer.apple.com/support/xcode/ tried installing Windows, try get right compiler help Google. thread FlyWire Slack might find useful things. use cloud-volume, need get token authorisation : https://globalv1.flywire-daf.com/auth/api/v1/refresh_token, add .json file create location: ~/.cloudvolume/secrets/cave-secret.json, see help .","code":""},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"install-meshparty","dir":"Articles","previous_headings":"","what":"Install meshparty","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Install meshparty: $ pip install meshparty errored failure install dependency: pykdtree clang: error: unsupported option '-fopenmp'. issue C++ compiler version (probably), good thing ’re using conda now can : $ conda install -c conda-forge pykdtree pip installing meshparty worked fine previous command. Now meshparty cloud-volume environment, meshparty optional dependencies skeletonisation, need install: order use meshparty_skeletonisation also install PyChunkedGraph, dependency called igneous, Seung lab. Install igneous GitHub, pip install PyChunkedGraph:","code":"$ conda install -c conda-forge pyembree $ pip install caveclient $ git clone git@github.com:seung-lab/igneous.git $ cd igneous $ pip install -r requirements.txt $ python setup.py develop $ pip install PyChunkedGraph"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"working-with-r-and-python","dir":"Articles","previous_headings":"","what":"Working with R and python","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"want use packages R reticulate natverse fafbseg functions objects need package reticulate R (install.packages(\"reticulate\")) tell use python version conda environment. Run R console:usethis::edit_r_environ() add line RETICULATE_PYTHON=\"/opt/miniconda3/envs/flywire_env/bin/python\" path python conda environment. sure leave blank line end file. Restart R session, load reticulate fafbseg (necessary install/update remotes::install_github(\"jefferis/fafbseg\"). Check python version reticulate::py_config(), show path gave RETICULATE_PYTHON variable. possible RStudio session crash reticulate::py_config(). may multiple copies OpenMP runtime linked program. dangerous, since can degrade performance cause incorrect results. fix, try:","code":"$ conda uninstall numpy scikit-learn $ conda install nomkl numpy scikit-learn $ conda remove mkl mkl-service"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"the-natverse-and-flywire-meshes","dir":"Articles","previous_headings":"Working with R and python","what":"The natverse and flywire meshes","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"Let’s set R look write flywire data. need access production node flywire environment (.e. passed test). Use usethis::edit_r_profile, R profile add: GJ: Don’t . Just use choose_segmentation(\"flywire\") able read meshes, skeletonise , plot FAFB:","code":"# Production flywire options(fafbseg.cloudvolume.url='graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31') # Load packages library(natverse) library(fafbseg) choose_segmentation(\"flywire\") dir.create(\"flywire_skeletons\") # Points in FAFBv14 (nm) to flywire coordinates (also nm) points = matrix(c(723086,200499,90960),ncol=3) flywire.fafb = xform_brain(points, sample='FAFB14', ref=\"FlyWire\") # Get mesh id = flywire_xyz2id(flywire.fafb) neuron_mesh = read_cloudvolume_meshes(id) # Skeletonise mesh meshparty_skeletonize(id, savedir = \"flywire_skeletons\") neuron_skel <- read.neuron.swc(sprintf(\"flywire_skeletons/%s.swc\",id)) nopen3d() plot3d(FAFB, alpha = 0.1) plot3d(neuron_skel*1000, WithNodes = F, col = \"red\", lwd = 2) wire3d(neuron_mesh[[1]], col = \"cyan\", alpha = 0.2)"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"skeletor","dir":"Articles","previous_headings":"Working with R and python","what":"Skeletor","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"may also want install skeletor, package Philipp Schlegel helps thin skeletonise meshes . can produce accurate results get using TEASAR meshparty, depend either. install, : test skeletor works flywire neurons python using: installed skeletor specified python environment described , R able :","code":"$ source activate flywire_env $ conda install nomkl $ pip3 install git+git://github.com/schlegelp/skeletor@master $ pip3 install fastremap $ pip3 install ncollpyde python from cloudvolume import CloudVolume import trimesh as tm import skeletor as sk id=720575940614134045 id=720575940634367221 vol = CloudVolume('graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31', use_https=True) m = vol.mesh.get(id, deduplicate_chunk_boundaries=False)[id] m = tm.Trimesh(m.vertices, m.faces) simp = sk.pre.simplify(m, ratio=.1) cntr = sk.pre.contract(simp, SL=10, WH0=2, iter_lim=4, epsilon=0.05, precision=1e-6, progress=False, operator='umbrella') swc = sk.skeletonize.by_vertex_clusters(cntr, sampling_dist=500, progress=False) swc = sk.post.clean_up(s = swc, mesh = simp, theta = 0.01) sk.post.radii(s = swc, mesh = simp, method='knn', n=5, aggregate='mean') print(swc) # Faster, wavefront skeletonisation m = sk.pre.fix_mesh(m, remove_disconnected=10) swc2 = sk.skeletonize.by_wavefront(m, waves=2s) print(swc2) # Skeletonise choose_segmentation(\"flywire\") nx=xform_brain(elmr::dense_core_neurons, ref=\"FlyWire\", sample=\"FAFB14\") xyz =xyzmatrix(nx) ids = unique(flywire_xyz2id(xyz[sample(1:nrow(xyz),100),])) neurons = skeletor(ids) # Plot in 3D nopen3d() plot3d(neurons) # note, in flywire space, slightly different to FAFBv14 space plot3d(nx, col=\"black\", lwd =2) # note, in flywire space"},{"path":"https://natverse.org/fafbseg/articles/installing-cloudvolume-meshparty.html","id":"issues","dir":"Articles","previous_headings":"Working with R and python","what":"Issues","title":"Installing python modules: cloudvolume, meshparty and skeletor","text":"run issues, can try wiping re-initiating conda environment. can try without igneous PyChunkedGraph. may also need specify installing cloudvolume version 1.20.1. GJ: Don’t important bug fixes since cloudvolume v 1.20.1 format URLs changed example: need install specific version cloudvolume (occasionally latest version breaks things), try e.g.:","code":"$ conda remove -n flywire_env --all $ conda create --name flywire_env python=3.7 $ conda activate flywire_env $ conda install nomkl $ conda install -c conda-forge pykdtree $ pip install --upgrade --prefer-binary meshparty cloud-volume $ pip3 install git+git://github.com/schlegelp/skeletor@master $ pip3 install fastremap $ pip3 install ncollpyde pip install --upgrade --prefer-binary cloud-volume~=3.8.0"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"note","dir":"Articles","previous_headings":"","what":"Note","title":"Mesh to mesh distances","text":"R Markdown Notebook. execute code within notebook, results appear beneath code. Try executing chunk clicking Run button within chunk placing cursor inside pressing Cmd+Shift+Enter.","code":""},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"find-the-distance-between-meshes","dir":"Articles","previous_headings":"","what":"Find the distance between meshes","title":"Mesh to mesh distances","text":"two ways can immediately think addressing Find distance every vertex mesh 1 nearest neighbour mesh 2 Find (signed) distance every vertex mesh 1 surface mesh 2 Obviously ideal situation find mesh mesh distances two objects (even Euclidean distance transform voxel representation objects.) neither accessible. Option 1 probably still perfectly good option purposes since meshes quite densely sampled (.e. vertices close together).","code":""},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"setup-and-mesh-volume","dir":"Articles","previous_headings":"","what":"Setup and Mesh volume","title":"Mesh to mesh distances","text":"Let’s use example mentioned FlyWire slack. asked find volume mesh. first attempt fails need clean mesh:","code":"library(fafbseg) ## Loading required package: nat ## Loading required package: rgl ## Registered S3 method overwritten by 'nat': ## method from ## as.mesh3d.ashape3d rgl ## Some nat functions depend on a CMTK installation. See ?cmtk and README.md for details. ## ## Attaching package: 'nat' ## The following object is masked from 'package:rgl': ## ## wire3d ## The following objects are masked from 'package:base': ## ## intersect, setdiff, union ## Run dr_fafbseg() for a status report on your installation choose_segmentation(\"flywire31\") va6pn=read_cloudvolume_meshes(\"720575940633169983\") ## downloading meshes ## parsing downloaded meshes Rvcg::vcgVolume(va6pn[[1]]) va6pn.clean=Rvcg::vcgClean(va6pn[[1]], sel=0:6, iterate = T) ## removed 68 duplicate faces and 0 duplicate vertices ## removed 0 unreferenced vertices ## removed 34 Non-manifold faces ## removed 0 degenerate faces ## removed 16 Non-manifold vertices ## split 3 non-manifold vertices ## merged 0 close vertices ## removed 0 duplicate faces and 0 duplicate vertices ## removed 3 unreferenced vertices ## removed 0 Non-manifold faces ## removed 0 degenerate faces ## removed 3 Non-manifold vertices ## split 0 non-manifold vertices ## merged 0 close vertices ## removed 0 duplicate faces and 0 duplicate vertices ## removed 0 unreferenced vertices ## removed 0 Non-manifold faces ## removed 0 degenerate faces ## removed 0 Non-manifold vertices ## split 0 non-manifold vertices ## merged 0 close vertices vol=Rvcg::vcgVolume(va6pn.clean) ## Warning in Rvcg::vcgVolume(va6pn.clean): Mesh is not watertight! USE RESULT ## WITH CARE! ## Warning in Rvcg::vcgVolume(va6pn.clean): Mesh is not coherently oriented! USE ## RESULT WITH CARE! vol ## [1] 2.506317e+12 # cubic microns vol/1e9 ## [1] 2506.317"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"compare-with-neurons-skeleton-available-from-vfb-catmaid","dir":"Articles","previous_headings":"Setup and Mesh volume","what":"Compare with neuron’s skeleton available from VFB catmaid","title":"Mesh to mesh distances","text":"","code":"library(elmr) ## Loading required package: catmaid ## Loading required package: httr ## Loading required package: nat.flybrains ## Loading required package: nat.templatebrains ## Loading required package: nat.nblast fafbconn=vfbcatmaid(\"fafb\") va6pn.skel=read.neurons.catmaid(\"name:VA6.*PN\", conn=fafbconn) summary(va6pn.skel) ## root nodes segments branchpoints endpoints cable.length nTrees connectors ## 16 11222 16840 2402 1172 1231 4003108 1 2158 ## 3133 5762 19832 2974 1461 1514 4800908 1 1026 ## nsoma ## 16 1 ## 3133 1 cable.length=summary(va6pn.skel)[1,\"cable.length\"] vol/cable.length # in nm ## [1] 626092.8 vol/cable.length/1e6 # in µm ## [1] 0.6260928 A=vol/cable.length/1e6 # mean area µm2 sqrt(A/(2*pi)) # implied radius µm, seems reasonable ## [1] 0.3156672"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"option-1-vertex-to-vertex-distance","dir":"Articles","previous_headings":"","what":"Option 1: Vertex to vertex distance","title":"Mesh to mesh distances","text":"let’s try find vertex vertex distance pair neurons. happen know lateral horn local interneuron target VA6 PN. Now can use k-d tree find nearest neighbour distances efficiently. Note also use xyzmatrix function extract vertex locations - works objects natverse knows . gives us: set vertex indices closest match VA6 PN every vertex LHLN distances matching vertices can take look distribution distances like : can see actually quite lot close distances. assume excess distances <1000 nm little dip distribution related pair neurons actually synaptically connected.","code":"pv4b4=read_cloudvolume_meshes('720575940619630430') ## downloading meshes ## parsing downloaded meshes # better to make the tree from the larger object # and query using points from the smaller object nvertices(pv4b4) ## 720575940619630430 ## 101419 nvertices(va6pn) ## 720575940633169983 ## 877023 kd=nabor::knn(query = xyzmatrix(pv4b4), data=xyzmatrix(va6pn), k=1) str(kd) ## List of 2 ## $ nn.idx : int [1:101419, 1] 4041 4041 4041 4041 4041 4041 4041 4041 4041 4041 ... ## $ nn.dists: num [1:101419, 1] 30734 30613 30251 30724 30213 ... hist(kd$nn.dists, br=100) hist(kd$nn.dists, br=500, xlim=c(0,2000))"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"locations-of-closest-approach","dir":"Articles","previous_headings":"Option 1: Vertex to vertex distance","what":"Locations of closest approach","title":"Mesh to mesh distances","text":"OK. meshes actually approach . Well look locations closest distances <100 nm. many ? Still lot! location close approach neurons, multiple vertices close together. Separating distinct contact locations complex problem simply calculating vertex distances. first thing throw cases vertex target neuron match. Looks like reduce third.","code":"sum(kd$nn.dists<100) ## [1] 1508 length(unique(kd$nn.idx[kd$nn.dists<100])) ## [1] 1017"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"visualising-contacts","dir":"Articles","previous_headings":"Option 1: Vertex to vertex distance","what":"Visualising contacts","title":"Mesh to mesh distances","text":"Let’s just take quick detour see close approaches look like: Show close nodes query mesh LHLN + PN Just query mesh LHLN close contact areas red","code":"rgl::setupKnitr() nopen3d() plot3d(pv4b4, type='wire') plot3d(va6pn, col='red', type='wire') spheres3d(xyzmatrix(pv4b4)[kd$nn.dists<100,], col='green', r=500) nclear3d() plot3d(pv4b4, col=ifelse(kd$nn.dists<100, 'red', 'black')) plot3d(va6pn, col='grey') nclear3d() plot3d(pv4b4, col=ifelse(kd$nn.dists<100, 'red', 'black'), type='wire')"},{"path":"https://natverse.org/fafbseg/articles/mesh-to-mesh.html","id":"identifying-discrete-contact-zones","dir":"Articles","previous_headings":"Option 1: Vertex to vertex distance","what":"Identifying discrete contact zones","title":"Mesh to mesh distances","text":"range ways done, essentially number local minima distance field find. might also case one “patch” one neuron actually matches several patches neuron. However ’ll just try pick simpler approach example. Let’s take points threshold distance query neuron find geodesic distance (.e. distance along mesh surface) . need bit prep work , make graph representation mesh. Convert LHLN mesh representation Now can find geodesic distance selected nodes. Let’s try clustering distance matrix Close contacts different colours","code":"#' Make an igraph representation of the edge network of a mesh object #' #' @param x A \\code{mesh3d} object or an object for which an \\code{as.mesh3d} #' method is defined. As a convenience the first mesh object is extracted when #' \\code{x} is a \\code{shapelist3d} object. #' @param ... additional arguments passed to \\code{as.mesh3d} #' #' @return a \\code{igraph} object whose vertices correspond to the vertices of the #' original mesh object and whose edges have weights matching the edge lengths #' in the mesh. #' @export mesh2graph <- function(x, ...) { if(inherits(x, 'shapelist3d')) x=x[[1]] if(inherits(x, 'neuronlist')) x=x[[1]] if(!inherits(x, 'mesh3d')) x=as.mesh3d(x, ...) if(nrow(x$it)!=3) stop(\"I only work for triangulat meshes right now\") # make the edge list v1=x$it[1,] v2=x$it[2,] v3=x$it[3,] el=rbind(cbind(v1,v2), cbind(v1,v3), cbind(v2,v3)) g=igraph::graph_from_edgelist(el, directed = FALSE) # calculate lengths of each edge xyz=xyzmatrix(x) edgelengths = function(v1, v2) { deltas=xyz[v1,,drop=F]-xyz[v2,,drop=F] sqrt(rowSums(deltas^2)) } weights=c(edgelengths(v1,v2), edgelengths(v1,v3), edgelengths(v2,v3)) igraph::E(g)$weight=weights g } g=mesh2graph(pv4b4) dmat=igraph::distances(g, v=which(kd$nn.dists<100), to = which(kd$nn.dists<100)) dd=hclust(as.dist(dmat)) plot(dd, labels = F) # cut using a height relating to a separation of 3000nm groups=cutree(dd, h=3000) # sample randomises colours so that neighbouring clusters have different colours set.seed(42) groupcols=sample(rainbow(max(groups)))[groups] nclear3d() spheres3d(xyzmatrix(pv4b4)[kd$nn.dists<100,], col=groupcols, rad=200) wire3d(pv4b4[[1]], col=ifelse(kd$nn.dists<100, 'red', 'black'), type='wire')"},{"path":"https://natverse.org/fafbseg/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Gregory Jefferis. Author, maintainer. Sridhar Jagannathan. Contributor. Alexander Bates. Contributor.","code":""},{"path":"https://natverse.org/fafbseg/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Jefferis G (2024). fafbseg: Support Functions Analysis FAFB EM Segmentation. R package version 0.13.0.9000, https://github.com/natverse/fafbseg.","code":"@Manual{, title = {fafbseg: Support Functions for Analysis of FAFB EM Segmentation}, author = {Gregory Jefferis}, year = {2024}, note = {R package version 0.13.0.9000}, url = {https://github.com/natverse/fafbseg}, }"},{"path":"https://natverse.org/fafbseg/index.html","id":"fafbseg","dir":"","previous_headings":"","what":"Support Functions for Analysis of FAFB EM Segmentation","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"goal fafbseg provide support analysis segmented EM data, focussed full adult female brain (FAFB) dataset. Although support range data sources services, point principal target FlyWire automated segmentation. Legacy support also exists Google brain automatic segmentation FAFB data. fafbseg integrated NeuroAnatomy Toolbox suite (aka natverse) including elmr catmaid. fafbseg also one building block coconatfly provides unified simplified interface range Drosophila connectome datasets. actually recommend coconatfly good place start users since provides convenient access specific FlyWire data releases well powerful cross-connectome analyses requiring minimal configuration. See https://natverse.org/coconatfly/articles/getting-started.html details.","code":""},{"path":"https://natverse.org/fafbseg/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"Assuming want use production (progress) version FlyWire dataset access lower level functionality, fafbseg way go. need install package configure environment including recording authorisation token likely downloading canned data releases.","code":""},{"path":"https://natverse.org/fafbseg/index.html","id":"package-installation","dir":"","previous_headings":"Installation","what":"Package installation","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"recommend installing fafbseg GitHub using natmanager package:","code":"# install natmanager if required if (!requireNamespace(\"natmanager\")) install.packages(\"natmanager\") natmanager::install(pkgs=\"fafbseg\")"},{"path":"https://natverse.org/fafbseg/index.html","id":"flywire-setup","dir":"","previous_headings":"Installation","what":"FlyWire setup","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"Basic steps setting access FlyWire data: note time writing (Dec 2023) download_flywire_release_data() targets materialisation 783 FlyWire dataset, fetching annotations connectivity information.","code":"library(fafbseg) # record your authorisation token flywire_set_token() # install python tools required for some functionality simple_python() # fetch canned connectivity *and* cell type data download_flywire_release_data()"},{"path":"https://natverse.org/fafbseg/index.html","id":"use","dir":"","previous_headings":"","what":"Use","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"Detailed examples follow additional vignettes, first motivation, connectivity query using precomputed data.","code":"library(fafbseg) dl4df=flytable_meta('DL4.*') dl4df dl4out <- flywire_partner_summary2(dl4df, partners = 'out', threshold = 3) dl4out"},{"path":"https://natverse.org/fafbseg/index.html","id":"acknowledgements","dir":"","previous_headings":"","what":"Acknowledgements","title":"Support Functions for Analysis of FAFB EM Segmentation","text":"fafbseg package enables access number published many pre-publication resources. hope accelerate science strongly request ensure acknowledge authors package original data sources ensure can justify free sharing code data. use proofread annotated FlyWire dataset, please co-cite: Dorkenwald et al 2023 Schlegel et al. 2023 acknowledge specific FAFB resources: FAFB dataset, Zheng et al Cell 2018 FFN1 autosegmentation, Li et al bioRxiv 2019 FlyWire autosegmentation, Dorkenwald et al Nat Meth 2022 https://flywire.ai using cleft_score metric please also cite Heinrich et al 2018 neurotransmitter prediction, Eckstein et al. 2023 bioRxiv FlyWire coordinate transforms synapse predictions make use infrastructure contributed Davi Bock, Gregory Jefferis, Philipp Schlegel Eric Perlman, supported NIH BRAIN Initiative (grant 1RF1MH120679-01); additional work including assembling ground truth data also supported Wellcome trust (203261/Z/16/Z). fabseg package , please include reference github page methods section well citation Bates et al eLife 2020 along statement: Development natverse including fafbseg package supported NIH BRAIN Initiative (grant 1RF1MH120679-01), NSF/MRC Neuronex2 (NSF 2014862/MC_EX_MR/T046279/1) core funding Medical Research Council (MC_U105188491). Thank !","code":""},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"add_celltype_info add information existing dataframe. flytable_meta fetch data.frame metadata flytable given set identifiers.","code":""},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"","code":"add_celltype_info( x, idcol = NULL, version = NULL, suffix = NULL, table = c(\"both\", \"info\", \"optic\"), ... ) flytable_meta( ids = NULL, version = NULL, table = c(\"both\", \"info\", \"optic\"), unique = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"x data.frame containing root ids neuronlist () idcol Optional character vector specifying column containing ids neurons cell type information provided. version Optional numeric CAVE version (see flywire_cave_query). special signalling value TRUE uses current default data dump returned flywire_connectome_data_version. suffix character suffix new columns (default value NULL implies suffix). table cell type information tables use (info brain, optic optic lobes ). ... additional arguments passed flytable_cell_types ids Flywire identifiers/query form understood flywire_ids unique Whether ensure rows contain unique identifiers. Default FALSE. TRUE duplicate rows returned warning.","code":""},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"data.frame extra columns","code":""},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"root ids must column called one \"pre_id\", \"post_id\", \"root_id\", \"post_pt_root_id\", \"pre_pt_root_id\". exactly one columns present must specify preferred column idcol argument.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/add_celltype_info.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch flytable cell type information to a dataframe with flywire ids — add_celltype_info","text":"","code":"# \\donttest{ kcin=flywire_partner_summary(\"720575940626474889\", partners = 'in', cleft.threshold = 50) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist #> Fetching supervoxel ids for id: 720575940626474889 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids kcin #> # A tibble: 103 × 3 #> pre_id weight n #> #> 1 720575940630547909 29 1 #> 2 720575940613583001 28 1 #> 3 720575940632698797 26 1 #> 4 720575940631269175 25 1 #> 5 720575940607687260 19 1 #> 6 720575940642086389 14 1 #> 7 720575940622673703 8 1 #> 8 720575940620709681 6 1 #> 9 720575940621178206 6 1 #> 10 720575940619665023 5 1 #> # ℹ 93 more rows kcin2=add_celltype_info(kcin) kcin2 #> # A tibble: 103 × 13 #> pre_id weight n supervoxel_id side flow super_class cell_class #> #> 1 72057594063054… 29 1 807870292352… right intr… central ALPN #> 2 72057594061358… 28 1 813486739212… right intr… central MBIN #> 3 72057594063269… 26 1 803649542764… right intr… central ALPN #> 4 72057594063126… 25 1 802240106295… right intr… central ALPN #> 5 72057594060768… 19 1 802240792818… right intr… central ALPN #> 6 72057594064208… 14 1 804353917399… right intr… central ALPN #> 7 72057594062267… 8 1 816302178184… right intr… central Kenyon_Ce… #> 8 72057594062070… 6 1 813494986893… right intr… central NA #> 9 72057594062117… 6 1 812080052867… right intr… central Kenyon_Ce… #> 10 72057594061966… 5 1 814192490249… right intr… central Kenyon_Ce… #> # ℹ 93 more rows #> # ℹ 5 more variables: cell_type , top_nt , ito_lee_hemilineage , #> # hemibrain_type , fbbt_id library(dplyr) #> #> Attaching package: ‘dplyr’ #> The following objects are masked from ‘package:nat’: #> #> intersect, setdiff, union #> The following objects are masked from ‘package:stats’: #> #> filter, lag #> The following objects are masked from ‘package:base’: #> #> intersect, setdiff, setequal, union kcin2 %>% group_by(cell_type) %>% summarise(wt = sum(weight),n=n()) %>% arrange(desc(wt)) #> # A tibble: 20 × 3 #> cell_type wt n #> #> 1 KCab 144 78 #> 2 VA1d_adPN 29 1 #> 3 APL 28 1 #> 4 DM2_lPN 26 2 #> 5 VM6_adPN 26 1 #> 6 VM2_adPN 19 1 #> 7 VA4_lPN 14 1 #> 8 LHPV12a1 9 2 #> 9 PAM11 4 2 #> 10 DPM 3 1 #> 11 PAM10 3 2 #> 12 PPL202 3 1 #> 13 PAM04 2 2 #> 14 PPL105 2 2 #> 15 KCapbp-m 1 1 #> 16 MBON02 1 1 #> 17 MBON06 1 1 #> 18 MBON07 1 1 #> 19 PPL106 1 1 #> 20 NA 1 1 kcin2 %>% count(cell_class, wt = weight) #> # A tibble: 6 × 2 #> cell_class n #> #> 1 ALPN 114 #> 2 DAN 15 #> 3 Kenyon_Cell 145 #> 4 MBIN 31 #> 5 MBON 3 #> 6 NA 10 # } if (FALSE) { # read neuronlist containing \"dotprops\" for some olfactory projection neurons da2=read_l2dps('DA2') # add cell type details to that da2=add_celltype_info(da2) } # \\donttest{ flytable_meta(\"class:MBON\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940624185095 79448854932107696 left intrinsic central MBON #> 2 720575940623472716 80011942324010318 right intrinsic central MBON #> 3 720575940638526278 80715286101144676 right intrinsic central MBON #> 4 720575940629585602 81137979670302132 right intrinsic central MBON #> 5 720575940637934308 81349085835581377 right intrinsic central MBON #> 6 720575940632118343 78744342923662254 left intrinsic central MBON #> 7 720575940609959637 78603948898007978 left intrinsic central MBON #> 8 720575940638163428 78111986298788517 left intrinsic central MBON #> 9 720575940630496374 81349223341739625 right intrinsic central MBON #> 10 720575940642142861 78393323903110735 left intrinsic central MBON #> 11 720575940611344078 80223254782485510 right intrinsic central MBON #> 12 720575940634822751 81277549061520124 right intrinsic central MBON #> 13 720575940617552340 79588561627810154 right intrinsic central MBON #> 14 720575940624280328 81489685951698728 right intrinsic central MBON #> 15 720575940617567206 78180912067538056 left intrinsic central MBON #> 16 720575940643700640 80152611093049624 right intrinsic central MBON #> 17 720575940615221811 81137979670297348 right intrinsic central MBON #> 18 720575940614026193 80154466519131949 right intrinsic central MBON #> 19 720575940633209647 78463486488950059 left intrinsic central MBON #> 20 720575940623001480 80154535238527400 right intrinsic central MBON #> 21 720575940613070485 81066305390179956 right intrinsic central MBON #> 22 720575940614595218 78040449457502610 left intrinsic central MBON #> 23 720575940636992368 80785654845309410 right intrinsic central MBON #> 24 720575940621828443 79166830266640003 left intrinsic central MBON #> 25 720575940637902938 78181599128215629 left intrinsic central MBON #> 26 720575940638774606 78040449457461921 left intrinsic central MBON #> 27 720575940639697827 80224766543977933 right intrinsic central MBON #> 28 720575940626833021 78251349531485275 left intrinsic central MBON #> 29 720575940618008859 77901086224032815 left intrinsic central MBON #> 30 720575940635841143 78110818201436707 left intrinsic central MBON #> 31 720575940618249797 80082723452177136 right intrinsic central MBON #> 32 720575940629856515 77408917331762608 left intrinsic central MBON #> 33 720575940623905719 80224972702135904 right intrinsic central MBON #> 34 720575940629529722 78533992672102680 left intrinsic central MBON #> 35 720575940624659943 80011255129536552 left intrinsic central MBON #> 36 720575940624590316 79167173863853528 right intrinsic central MBON #> 37 720575940645304430 79380479052758063 left intrinsic central MBON #> 38 720575940612196850 81136880426746412 right intrinsic central MBON #> 39 720575940630767959 78251486970442209 left intrinsic central MBON #> 40 720575940640963747 76985537105536911 left intrinsic central MBON #> 41 720575940628757547 78040449457463315 left intrinsic central MBON #> 42 720575940627144069 79166692827138268 right intrinsic central MBON #> 43 720575940610647416 81137979602919932 right intrinsic central MBON #> 44 720575940622093436 81136880426744139 right intrinsic central MBON #> 45 720575940624696810 78110818201651448 left intrinsic central MBON #> 46 720575940629422086 77760348668670642 left intrinsic central MBON #> 47 720575940647328900 81137979670303492 right intrinsic central MBON #> 48 720575940650386553 78110818201681795 left intrinsic central MBON #> 49 720575940639556467 81067610926141558 right intrinsic central MBON #> 50 720575940636120986 81700242831237167 right intrinsic central MBON #> 51 720575940617749538 80786135881765925 right intrinsic central MBON #> 52 720575940617760257 81277549061455173 right intrinsic central MBON #> 53 720575940619810389 79518055445188833 right intrinsic central MBON #> 54 720575940634482783 81136605414678093 right intrinsic central MBON #> 55 720575940644615716 78182286188838645 left intrinsic central MBON #> 56 720575940626109315 81066305390093306 right intrinsic central MBON #> 57 720575940623377802 78110818201621392 left intrinsic central MBON #> 58 720575940626744921 81277549061481189 right intrinsic central MBON #> 59 720575940623464316 81136880426764424 right intrinsic central MBON #> 60 720575940622979277 79027192356412856 left intrinsic central MBON #> 61 720575940614892182 81277617781167541 right intrinsic central MBON #> 62 720575940620715224 78111917579300796 left intrinsic central MBON #> 63 720575940613090673 78324741798855874 left intrinsic central MBON #> 64 720575940621777391 81137979736901319 right intrinsic central MBON #> 65 720575940606953858 81136880426735755 right intrinsic central MBON #> 66 720575940630075703 79309972869657633 left intrinsic central MBON #> 67 720575940652390134 78603949099622269 left intrinsic central MBON #> 68 720575940632535756 79380204241413766 left intrinsic central MBON #> 69 720575940643696288 79309904216692475 left intrinsic central MBON #> 70 720575940620162718 78323023677138555 left intrinsic central MBON #> 71 720575940635063135 80082242348953693 right intrinsic central MBON #> 72 720575940616463477 77830305364995511 left intrinsic central MBON #> 73 720575940629981440 78885355625276424 left intrinsic central MBON #> 74 720575940623182847 78463211409646517 left intrinsic central MBON #> 75 720575940626315010 79943222847625326 right intrinsic central MBON #> 76 720575940632943277 80925980016963911 right intrinsic central MBON #> 77 720575940624539284 78040449457553649 left intrinsic central MBON #> 78 720575940626180878 80011530007496199 left intrinsic central MBON #> 79 720575940628783363 80434292093847745 right intrinsic central MBON #> 80 720575940643309197 79870998677653042 left intrinsic central MBON #> 81 720575940614392999 79237542540872430 left intrinsic central MBON #> 82 720575940617302365 78604086538417636 left intrinsic central MBON #> 83 720575940635651680 81277549061591572 right intrinsic central MBON #> 84 720575940624694503 79941230049538531 left intrinsic central MBON #> 85 720575940628734376 79869899232522382 right intrinsic central MBON #> 86 720575940610964946 81630904409213619 right intrinsic central MBON #> 87 720575940607155890 80433124332533007 right intrinsic central MBON #> 88 720575940623381956 80644779918075196 right intrinsic central MBON #> 89 720575940628487813 81560466945525625 right intrinsic central MBON #> 90 720575940638028607 81419592152467685 right intrinsic central MBON #> 91 720575940621164720 80222636373797362 left intrinsic central MBON #> 92 720575940623841463 78251349531447591 left intrinsic central MBON #> 93 720575940631177803 78814711734490195 left intrinsic central MBON #> 94 720575940622306625 79166761480079751 right intrinsic central MBON #> 95 720575940616398303 79729161744437991 left intrinsic central MBON #> 96 720575940623750325 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON02 glutamate putative_primary MBON02 FBbt_00111012 #> 2 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 3 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 4 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 5 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 6 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 7 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 8 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 9 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 10 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 11 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 12 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 13 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 14 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 15 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 16 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 17 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 18 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 19 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 20 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 21 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 22 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 23 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 24 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 25 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 26 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 27 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 28 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 29 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 30 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 31 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 32 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 33 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 34 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 35 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 36 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 37 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 38 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 39 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 40 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 41 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 42 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 43 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 44 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 45 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 46 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 47 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 48 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 49 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 50 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 51 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 52 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 53 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 54 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 55 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 56 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 57 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 58 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 59 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 60 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 61 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 62 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 63 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 64 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 65 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 66 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 67 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 68 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 69 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 70 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 71 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 72 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 73 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 74 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 75 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 76 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 77 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 78 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 79 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 80 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 81 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 82 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 83 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 84 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 85 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 86 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 87 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 88 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 89 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 90 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 91 MBON05 acetylcholine putative_primary MBON05 FBbt_00111004 #> 92 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 93 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 94 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 95 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 96 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 flytable_meta(\"type:MBON2%\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940611344078 80223254782485510 right intrinsic central MBON #> 2 720575940617567206 78180912067538056 left intrinsic central MBON #> 3 720575940643700640 80152611093049624 right intrinsic central MBON #> 4 720575940614595218 78040449457502610 left intrinsic central MBON #> 5 720575940618249797 80082723452177136 right intrinsic central MBON #> 6 720575940624659943 80011255129536552 left intrinsic central MBON #> 7 720575940627144069 79166692827138268 right intrinsic central MBON #> 8 720575940619810389 79518055445188833 right intrinsic central MBON #> 9 720575940623464316 81136880426764424 right intrinsic central MBON #> 10 720575940622979277 79027192356412856 left intrinsic central MBON #> 11 720575940614892182 81277617781167541 right intrinsic central MBON #> 12 720575940620715224 78111917579300796 left intrinsic central MBON #> 13 720575940613090673 78324741798855874 left intrinsic central MBON #> 14 720575940621777391 81137979736901319 right intrinsic central MBON #> 15 720575940606953858 81136880426735755 right intrinsic central MBON #> 16 720575940635063135 80082242348953693 right intrinsic central MBON #> 17 720575940616463477 77830305364995511 left intrinsic central MBON #> 18 720575940629981440 78885355625276424 left intrinsic central MBON #> 19 720575940614392999 79237542540872430 left intrinsic central MBON #> 20 720575940607155890 80433124332533007 right intrinsic central MBON #> 21 720575940631177803 78814711734490195 left intrinsic central MBON #> 22 720575940622306625 79166761480079751 right intrinsic central MBON #> 23 720575940616398303 79729161744437991 left intrinsic central MBON #> 24 720575940623750325 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 2 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 3 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 4 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 5 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 6 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 7 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 8 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 9 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 10 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 11 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 12 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 13 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 14 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 15 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 16 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 17 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 18 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 19 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 20 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 21 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 22 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 23 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 24 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 # the / introduces a regex query (small performance penalty, more flexible) flytable_meta(\"/type:MBON2[0-5]\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940611344078 80223254782485510 right intrinsic central MBON #> 2 720575940617567206 78180912067538056 left intrinsic central MBON #> 3 720575940624659943 80011255129536552 left intrinsic central MBON #> 4 720575940627144069 79166692827138268 right intrinsic central MBON #> 5 720575940619810389 79518055445188833 right intrinsic central MBON #> 6 720575940623464316 81136880426764424 right intrinsic central MBON #> 7 720575940620715224 78111917579300796 left intrinsic central MBON #> 8 720575940613090673 78324741798855874 left intrinsic central MBON #> 9 720575940621777391 81137979736901319 right intrinsic central MBON #> 10 720575940606953858 81136880426735755 right intrinsic central MBON #> 11 720575940635063135 80082242348953693 right intrinsic central MBON #> 12 720575940616463477 77830305364995511 left intrinsic central MBON #> 13 720575940631177803 78814711734490195 left intrinsic central MBON #> 14 720575940622306625 79166761480079751 right intrinsic central MBON #> 15 720575940616398303 79729161744437991 left intrinsic central MBON #> 16 720575940623750325 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 2 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 3 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 4 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 5 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 6 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 7 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 8 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 9 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 10 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 11 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 12 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 13 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 14 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 15 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 16 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 # }"},{"path":"https://natverse.org/fafbseg/reference/as.mesh3d.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a raw neuroglancer mesh into a mesh3d object — as.mesh3d.ng_raw","title":"Convert a raw neuroglancer mesh into a mesh3d object — as.mesh3d.ng_raw","text":"Convert raw neuroglancer mesh mesh3d object","code":""},{"path":"https://natverse.org/fafbseg/reference/as.mesh3d.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a raw neuroglancer mesh into a mesh3d object — as.mesh3d.ng_raw","text":"","code":"# S3 method for ng_raw as.mesh3d(x, ...) # S3 method for ng_raw_list as.mesh3d(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/as.mesh3d.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a raw neuroglancer mesh into a mesh3d object — as.mesh3d.ng_raw","text":"x ng_raw ng_raw_list object ... additional arguments passed tmesh3d","code":""},{"path":"https://natverse.org/fafbseg/reference/braincircuits_login.html","id":null,"dir":"Reference","previous_headings":"","what":"Create and log into a braincircuits account — braincircuits_register","title":"Create and log into a braincircuits account — braincircuits_register","text":"braincircuits website built Stephan Gerhard provides services FAFB flywire data. example, information predictions dense core vesicles (DCVs). functions assist registering logging braincircuits account order query API. must first log website . run braincircuits_login, call braincircuits_register. moment, function needed flywire_dcvs called hood . Therefore, beyond testing can connect braincircuits.io little reason call function directly.","code":""},{"path":"https://natverse.org/fafbseg/reference/braincircuits_login.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create and log into a braincircuits account — braincircuits_register","text":"","code":"braincircuits_register( open = TRUE, email = NULL, password = NULL, url = \"https://api.braincircuits.io\" ) braincircuits_login( email = NULL, password = NULL, url = \"https://api.braincircuits.io\" ) braincircuits_token( email = NULL, password = NULL, url = \"https://api.braincircuits.io\" )"},{"path":"https://natverse.org/fafbseg/reference/braincircuits_login.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create and log into a braincircuits account — braincircuits_register","text":"open logical, whether open browser window login page braincircuits.io. email email registered/want register braincircuits.io. password password want set (using braincircuits_register) set (using braincircuits_login) account. url URL braincircuits API. Typically need change .","code":""},{"path":"https://natverse.org/fafbseg/reference/braincircuits_login.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create and log into a braincircuits account — braincircuits_register","text":"bearer access token query braincircuits API.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/braincircuits_login.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create and log into a braincircuits account — braincircuits_register","text":"","code":"if (FALSE) { # Run this function: braincircuits_login() # If you run it for the first time, a window will open # to the braincircuits log in page. Log in with an email. # then when prompted in the R command line, re-give your email address and # give a new password. You can save these in your .Renviron file to prevent having # to do this in future. }"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a token to enable access to brainmaps API — brainmaps_auth","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"Generate token enable access brainmaps API","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"","code":"brainmaps_auth( client_id = Sys.getenv(\"BRAINMAPS_CLIENT_ID\"), client_secret = Sys.getenv(\"BRAINMAPS_CLIENT_SECRET\"), scope = \"https://www.googleapis.com/auth/brainmaps\" )"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"client_id, client_secret Client id secret copied https://console.developers.google.com. See details. scope scope brainmaps API - need change .","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"token can used e.g. GET.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"need activate brainmaps API, generate project https://console.developers.google.com request OAuth credentials, create client id client secret. application name console must fafbseg. put keys .Renviron file. BRAINMAPS_CLIENT_ID=\"xxxx\" BRAINMAPS_CLIENT_SECRET=\"xxxx\"","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/brainmaps_auth.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a token to enable access to brainmaps API — brainmaps_auth","text":"","code":"if (FALSE) { google_token=brainmaps_auth() # get a list of available volumes req <- GET(\"https://brainmaps.googleapis.com/v1beta2/volumes\", config(token = google_token)) }"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_fetch.html","id":null,"dir":"Reference","previous_headings":"","what":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","title":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","text":"brainmaps_fetch calls brainmaps API optional request cache retries. brainmaps_clear_cache clears cache used brainmaps_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_fetch.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","text":"","code":"brainmaps_fetch( url, body = NULL, parse.json = TRUE, cache = FALSE, retry = 0L, include_headers = FALSE, simplifyVector = TRUE, ... ) brainmaps_clear_cache()"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_fetch.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","text":"url Full URL brainmaps API endpoint body R list parameters converted jsonlite::toJSON passed POST. can also pass JSON character vector control JSON encoding. parse.json Whether parse JSON response R object (default TRUE) cache Whether cache responses (default FALSE) retry number times retry operation (default 0, FALSE=>0 TRUE=>3). See documentation times argument httr::RETRY details. include_headers Whether include basic headers http request attributes parsed JSON object (default TRUE) parse.json=TRUE. simplifyVector Whether use jsonlite::simplifyVector ... additional arguments passed httr::{RETRY} function. may include config list named parameters etc.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_fetch.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","text":"R list parse","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_fetch.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"GET/POST from brainmaps API with optional retry / cache — brainmaps_fetch","text":"","code":"if (FALSE) { brainmaps_fetch(\"https://brainmaps.googleapis.com/v1/volumes\") # retry up to 4 times on failure brainmaps_fetch(\"https://brainmaps.googleapis.com/v1/volumes\", retry=4) # cache results brainmaps_fetch(\"https://brainmaps.googleapis.com/v1/volumes\", cache=TRUE) # use arbitrary curl/httr options (see httr_options()) httr::with_config(httr::verbose(), { brainmaps_fetch(\"https://brainmaps.googleapis.com/v1/volumes\") }) } # \\donttest{ brainmaps_clear_cache() #> [1] TRUE # }"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_listfragments.html","id":null,"dir":"Reference","previous_headings":"","what":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","title":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","text":"Low level call brainmaps API list mesh fragment ids segment ids","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_listfragments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","text":"","code":"brainmaps_listfragments( x, volume = getOption(\"fafbseg.brainmaps.volume\"), meshName = getOption(\"fafbseg.brainmaps.meshName\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_listfragments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","text":"x Single segment identifier volume String identifier volume containing segments meshName String identifier meshes ... Additional arguments passed brainmaps_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_listfragments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","text":"Character vector fragment ids","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/brainmaps_listfragments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Low level call to brainmaps API to list mesh fragment ids for segment ids — brainmaps_listfragments","text":"","code":"if (FALSE) { brainmaps_listfragments(7186840767) }"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":null,"dir":"Reference","previous_headings":"","what":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"Low level function fetch skeleton brainmaps API","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"","code":"brainmaps_skeleton(x, skeletonuri = getOption(\"fafbseg.skeletonuri\"), ...)"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"x single segment id skeletonuri brainmaps URI describing skeleton source. Defaults value options(\"fafbseg.skeletonuri\"). ... Additional arguments passed brainmaps_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"list containing following fields nvertices number vertices (n) nedges number edges (m) vertices n x 3 matrix vertex locations","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"API seems return skeletons physical (.e. already calibrated) coordinates.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_skeleton.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Low level function to fetch skeleton from brainmaps API — brainmaps_skeleton","text":"","code":"if (FALSE) { brainmaps_skeleton(9208128833) brainmaps_skeleton(9208128833, skeletonuri=paste0(\"brainmaps://772153499790:fafb_v14:\", \"fafb_v14_16nm_v00c_split3xfill2_flatreseg2_skeletons32\", \"/teasar512_nnconn165_mc10000_prune10_thresh1000_sparse250\")) }"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_volume.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract brainmaps volume identifier — brainmaps_volume","title":"Extract brainmaps volume identifier — brainmaps_volume","text":"Extract brainmaps volume identifier","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_volume.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract brainmaps volume identifier — brainmaps_volume","text":"","code":"brainmaps_volume(x)"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_volume.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract brainmaps volume identifier — brainmaps_volume","text":"x character vector containing brainmaps URI, parsed brainmaps_uri object character vector already containing volume specifier.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_volume.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract brainmaps volume identifier — brainmaps_volume","text":"character vector containing volume specifier.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_volume.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract brainmaps volume identifier — brainmaps_volume","text":"","code":"brainmaps_volume(\"772153499790:fafb_v14:fafb_v14_16nm_v00c_split3xfill2\") #> [1] \"772153499790:fafb_v14:fafb_v14_16nm_v00c_split3xfill2\" brainmaps_volume(\"brainmaps://772153499790:fafb_v14:fafb_v14_16nm_v00c_split3xfill2\") #> [1] \"772153499790:fafb_v14:fafb_v14_16nm_v00c_split3xfill2\""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"Convert 3D x,y,z locations brainmaps volumes segmentation ids","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"","code":"brainmaps_xyz2id( xyz, volume = getOption(\"fafbseg.skeletonuri\"), rawcoords = FALSE, rawvoxdims = c(8, 8, 40), chunksize = getOption(\"fafbseg.brainmaps_xyz2id.chunksize\", 200), ... )"},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"xyz N x 3 matrix points object containing vertex data compatible xyzmatrix. physical space (.e. nm) unless voxdims=NULL. volume character vector identifier string volume containing segmentation data - default uses value fafbseg.skeletonuri option. input can parsed brainmaps_volume acceptable. rawcoords Whether coordinates voxel indices (rawcoords=TRUE) physical units (nm, default). rawvoxdims implied voxel dimensions volume. rawcoords=TRUE used convert raw coordinates physical units. default value matches normal voxel size neuroglancer. rawvoxdims=NULL attempt made scale coordinates whatsoever. See details. chunksize send queries batches chunksize points. default chosen since brainmaps API can time points take long map (likely spread across brain). also maximum number points per call (10,000 recommended upper limit one point). ... Additional arguments passed brainmaps_fetch. can include setting retry argument >0. See Details Examples.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"numeric vector Google segment ids","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"underlying brainmaps API expects raw coordinates .e. voxel indices. slightly complicated fact different segmentation, skeleton etc volumes may different associated voxel dimensions. brainmaps_xyz2id automatically looks voxel dimension. However may want pass raw coordinates neuroglancer. generally associated resolution image data e.g. skeletons may larger (coarser) voxel size. convenience situation can set rawcoords=TRUE. problems requests failing sporadically, may helpful know Google keep underlying data live may spin-time. arbitrary timeout Google end (currently ~ 5s) batching nearby points helps Using chunksize argument retry argument passed brainmaps_fetch can overcome issues. See examples.","code":""},{"path":"https://natverse.org/fafbseg/reference/brainmaps_xyz2id.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert 3D x,y,z locations in brainmaps volumes to segmentation ids — brainmaps_xyz2id","text":"","code":"if (FALSE) { # Physical location in nm brainmaps_xyz2id(c(433368, 168208, 128480)) # Same location as displayed in neuroglancer brainmaps_xyz2id(c(54171, 21026, 3212), rawcoords=TRUE) # Raw coodinates for the brainmaps volume in question - don't touch brainmaps_xyz2id(c(433368, 168208, 128480)/c(32,32,40), rawvoxdims=NULL) library(elmr) # get a manually traced neuron (just keep first and only entry in neuronlist) dl4=read.neurons.catmaid('glomerulus DL4 right')[[1]] # map every node location to segmentation ids dl4.segs=brainmaps_xyz2id(dl4) # remove unmapped locations which get id 0 dl4.segs=setdiff(dl4.segs, 0) # read in corresponding skeletons dl4.skels=read_segments2(dl4.segs) # read in corresponding skeletons after including agglomeration merge groups dl4.allskels=read_segments2(find_merged_segments(dl4.segs)) ## retries / cache / chunksize issues # set small chunk size dl4.segs=brainmaps_xyz2id(dl4, chunksize=500) # use retries in case of failure dl4.segs=brainmaps_xyz2id(dl4, chunksize=500, retry=3) # cache successful requests (if you might need to repeat) dl4.segs=brainmaps_xyz2id(dl4, chunksize=500, retry=3, cache=TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/catmaid2ngl.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert CATMAID things (eg neurons) into Neuroglancer equivalents — catmaid2ngl","title":"Convert CATMAID things (eg neurons) into Neuroglancer equivalents — catmaid2ngl","text":"catmaid2ngl.neuron uses brainmaps_xyz2id read_segments2 find skeletons corresponding (catmaid) neuron catmaid2ngl.neuronlist applies catmaid2ngl.neuron neuronlist catmaid2ngl.character uses open_fafb_ngl open CATMAID location matching Neuroglancer URL. Converts CATMAID skid specification (see catmaid_skids) one neuron autosegmentation based neuron using catmaid2ngl.neuron.","code":""},{"path":"https://natverse.org/fafbseg/reference/catmaid2ngl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert CATMAID things (eg neurons) into Neuroglancer equivalents — catmaid2ngl","text":"","code":"catmaid2ngl(x, ...) # S3 method for neuron catmaid2ngl( x, chunksize = getOption(\"fafbseg.brainmaps_xyz2id.chunksize\", 4000), ... ) # S3 method for neuronlist catmaid2ngl(x, OmitFailures = TRUE, ...) # S3 method for character catmaid2ngl(x, open = FALSE, ...) # S3 method for default catmaid2ngl(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/catmaid2ngl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert CATMAID things (eg neurons) into Neuroglancer equivalents — catmaid2ngl","text":"x object convert (see Descriptions method) ... Additional arguments passed methods chunksize send queries batches chunksize points. default chosen since brainmaps API can time points take long map (likely spread across brain). also maximum number points per call (10,000 recommended upper limit one point). OmitFailures Whether omit neurons FUN gives error. default value (NA) result nlapply stopping error message moment error. values, see details. open Whether open URL browser - defaults TRUE interactive use.","code":""},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":null,"dir":"Reference","previous_headings":"","what":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"with_segmentation allows specific segmentation temporarily selected.","code":""},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"","code":"choose_segmentation( release = c(\"flywire31\", \"public-flywire31\", \"20200412\", \"20190805\", \"20190521\", \"sandbox-flywire31\"), set = TRUE, moreoptions = list() ) with_segmentation(release, expr)"},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"release character vector specifying released segmentation via known short name sample neuroglancer URL. set Whether set selected options selected release. moreoptions options might wish set (optional, expert use , principally intended use fancr package). expr expression execute temporary options set","code":""},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"set=TRUE list containing previous values relevant global options (style options. set=FALSE named list containing option values. result evaluating expr","code":""},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"released segmentation implies number global options. package comes multiple different default scene urls specified via choose_segmentation with_segmentation. easiest way choose particular segmentation. can also pass sample URL release argument. Nov 2020, \"flywire31\" default segmentation package loads. specifies production (.e. progress) version flywire dataset. need register flywire team generate flywire token linked email used registration access . Alternatively can also use \"public-flywire31\" data release accompanying Dorkenwald et al 2023 Schlegel et al 2023 publications; still need token (see flywire_set_token), registration required ( limitations use data new projects besides citing two preprints). can also specify different sample URL via sampleurl argument functions; remembered rest R session. regularly use particular kind scene URL, can set options(fafbseg.sampleurl) Rprofile file. need use built-custom segmentation URLs, recommend specifying custom URL Rprofile file using with_segmentation run code uses one built- segmentations.","code":""},{"path":"https://natverse.org/fafbseg/reference/choose_segmentation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Choose or (temporarily) use a FAFB autosegmentation — choose_segmentation","text":"","code":"# \\donttest{ choose_segmentation('20190805', set=FALSE) #> $fafbseg.sampleurl #> [1] \"https://neuroglancer-demo.appspot.com/#!%7B%22layers%22:%5B%7B%22source%22:%22precomputed://gs://neuroglancer-fafb-data/fafb_v14/fafb_v14_clahe_sharded%22%2C%22type%22:%22image%22%2C%22name%22:%22fafb_v14_clahe%22%7D%2C%7B%22source%22:%22brainmaps://772153499790:fafb_v14:fafb-ffn1-20190805%22%2C%22type%22:%22segmentation%22%2C%22skeletonRendering%22:%7B%22mode2d%22:%22lines_and_points%22%2C%22mode3d%22:%22lines%22%7D%2C%22name%22:%22fafb-ffn1-20190805%22%7D%2C%7B%22source%22:%22brainmaps://772153499790:fafb_v14:fafb-ffn1-20190805-skeletons32nm%22%2C%22type%22:%22segmentation%22%2C%22segments%22:%5B%220%22%5D%2C%22skeletonRendering%22:%7B%22mode2d%22:%22lines_and_points%22%2C%22mode3d%22:%22lines%22%7D%2C%22name%22:%22fafb-ffn1-20190805-skeletons32nm%22%7D%5D%2C%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22:%5B122437.5625%2C36391.234375%2C2057.085205078125%5D%7D%7D%2C%22zoomFactor%22:8%7D%2C%22perspectiveOrientation%22:%5B-0.6771116256713867%2C0.6536111831665039%2C-0.1610027700662613%2C0.2973051071166992%5D%2C%22perspectiveZoom%22:5184.860830857428%2C%22showSlices%22:false%2C%22layout%22:%224panel%22%7D\" #> #> $fafbseg.skeletonuri #> [1] \"brainmaps://772153499790:fafb_v14:fafb-ffn1-20190805-skeletons32nm\" #> #> $fafbseg.brainmaps.volume #> [1] \"772153499790:fafb_v14:fafb-ffn1-20190805\" #> #> $fafbseg.brainmaps.meshName #> [1] \"mcws_quad1e6\" #> #> $fafbseg.catmaid #> [1] \"https://garden.catmaid.org/tracing/fafb/v14-seg-li-190805.0/\" #> #> $fafbseg.cloudvolume.url #> [1] \"brainmaps://772153499790:fafb_v14:fafb-ffn1-20190805\" #> # } if (FALSE) { # temporarily change default segmentation to run a command # but restore original default when finished # Choose the FlyWire segmentation with_segmentation('flywire31', {open_fafb_ngl(c(460792, 221812, 61480))}) # similarly for one Google (Li and Jain) segmentation with_segmentation('20190805', {open_fafb_ngl(c(460792, 221812, 61480))}) } if (FALSE) { n <- with_segmentation(\"20190521\", read.neuron.brainmaps(22427007374)) # open location in flywire with_segmentation(\"flywire\", open_fafb_ngl(c(433440, 168344, 131200))) }"},{"path":"https://natverse.org/fafbseg/reference/compare_ng_neuron.html","id":null,"dir":"Reference","previous_headings":"","what":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","title":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","text":"Compare neuroglancer mesh object regular neuron","code":""},{"path":"https://natverse.org/fafbseg/reference/compare_ng_neuron.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","text":"","code":"compare_ng_neuron( x, n, breaks = 3, colpal = c(\"cyan\", \"red\"), plot = TRUE, plotn = plot, pointsize = 0.1, sample_dots = 1, ... )"},{"path":"https://natverse.org/fafbseg/reference/compare_ng_neuron.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","text":"x neuroglancer mesh, rgl::mesh3d object object defined xyzmatrix function. n nat::neuron object breaks either numeric vector two unique cut points single number (greater equal 2) giving number intervals x cut. colpal function defining colour palette vector colour names. plot Whether plot anything (set FALSE just want get distance information) plotn Whether plot neuron n pointsize Size plotted points mesh - passed points3d. Default pointsize=0.1 makes points smaller usual. sample_dots Fraction points (0-1) mesh plot - default value 1 implies points. Values sample_dots < 1 select random subsample points. ... Additional arguments passed plot3d.neuron","code":""},{"path":"https://natverse.org/fafbseg/reference/compare_ng_neuron.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","text":"Invisibly, data.frame distances object x nearest neighbour n well breaks used colouring points plotting.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/compare_ng_neuron.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compare a neuroglancer mesh object with a regular neuron — compare_ng_neuron","text":"","code":"if (FALSE) { x=read_ng_raw('meshdata/') library(elmr) y=read.neuron.catmaid(23432) compare_ng_neuron(x,y) }"},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"Download FlyWire connectivity annotations public release","code":""},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"","code":"download_flywire_release_data( which = c(\"core\", \"all\"), version = c(783L, 630L) )"},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"data download. core gets used files (~300 MB). gets additional useful ones (~900 MB). version materialisation version use. See details.","code":""},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"return value - just used side effect downloading files.","code":""},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"Note must accept abide flywire principles order use flywire data. Version 630 released June 2023 bioRxiv manuscripts remains default time significant improvements cell typing associated version 783 released Dec 2023 resubmissions core flywire manuscripts.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/download_flywire_release_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download FlyWire connectivity and annotations from public release — download_flywire_release_data","text":"","code":"if (FALSE) { # 300 MB download_flywire_release_data() # 900 MB includes download_flywire_release_data('all') }"},{"path":"https://natverse.org/fafbseg/reference/dr_fafbseg.html","id":null,"dir":"Reference","previous_headings":"","what":"Print information about fafbseg setup including tokens and python modules — dr_fafbseg","title":"Print information about fafbseg setup including tokens and python modules — dr_fafbseg","text":"Print information fafbseg setup including FlyWire/ChunkedGraph authentication tokens, Python modules nat.h5reg / java setup required transforming points EM light level template brains.","code":""},{"path":"https://natverse.org/fafbseg/reference/dr_fafbseg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print information about fafbseg setup including tokens and python modules — dr_fafbseg","text":"","code":"dr_fafbseg(pypkgs = NULL)"},{"path":"https://natverse.org/fafbseg/reference/dr_fafbseg.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print information about fafbseg setup including tokens and python modules — dr_fafbseg","text":"pypkgs Additional python packages check beyond standard ones fafbseg knows cloudvolume. set FALSE, turns Python package report altogether.","code":""},{"path":"https://natverse.org/fafbseg/reference/dr_fafbseg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print information about fafbseg setup including tokens and python modules — dr_fafbseg","text":"","code":"if (FALSE) { dr_fafbseg(pymodules=FALSE) }"},{"path":"https://natverse.org/fafbseg/reference/fafb14_to_flywire_ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","title":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","text":"Provide function CATMAID query (skeleton IDs annotation term, provide catmaid::catmaid_skids) nat::neuronlist object FAFB14 space, return ranked list flywire IDs map onto given neuron(s).","code":""},{"path":"https://natverse.org/fafbseg/reference/fafb14_to_flywire_ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","text":"","code":"fafb14_to_flywire_ids( search, only.root = FALSE, only.biggest = FALSE, pid = 1L, conn = NULL, fetch.annotations = FALSE, OmitFailures = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/fafb14_to_flywire_ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","text":"search one skids CATMAID query expression. Else, neuronlist neurons FAFB14 space. .root return one root_id location root node given CATMAID neuron(s).. .biggest return one root_id per CATMAID skid .e. biggest overlapping fragment. pid Project id (default 1) conn catmaid_connection objection returned catmaid_login. NULL (default) new connection object generated using values catmaid.* package options described help catmaid_login. fetch.annotations Whether fetch annotations skeleton (default FALSE) OmitFailures logical, whether omit neurons read CATMAID. ... Additional arguments passed nat::nlapply.","code":""},{"path":"https://natverse.org/fafbseg/reference/fafb14_to_flywire_ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","text":"data.frame ranked flywire IDs, number points CATMAID neuron maps ID.","code":""},{"path":"https://natverse.org/fafbseg/reference/fafb14_to_flywire_ids.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get flywire IDs that map onto CATMAID neurons — fafb14_to_flywire_ids","text":"","code":"if (FALSE) { # a specific skid df=fafb14_to_flywire_ids(16) head(df) # Get neurons from a specific CATMAID environment ## See catmaid package help for details on how to 'login' # This is the Drosophila anatomy ontology identifier for DL1 # adult antennal lobe projection neuron DL1 adPN # see \\url{https://virtualflybrain.org} for details. hits=fafb14_to_flywire_ids(search=\"FBbt:00067353\", conn=catmaid::vfbcatmaid()) head(hits) }"},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert between filenames and neuroglancer ids — fafbseg-ids","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"swc2segmentid converts swc filename segment id segmentid2zip converts segment id zip file contains zip2segmentstem converts zip file initial part segment id .e. segment stem (see details).","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"","code":"swc2segmentid(x, include.fragment = FALSE) segmentid2zip(x) zip2segmentstem(x)"},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"x Input file id include.fragment Whether include sub identifier skeleton fragment (see details).","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"swc2segmentid numeric vector matrix depending value include.fragment","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"Segment ids unique integers. 8E8 current skeletonisation seems ids can still > 2^31 (usually .Machine$integer.max). Therefore stored R numeric values bit64::integer64 values. segmentation keen skeletonised however usually results multiple skeleton fragments written separate SWC files: \"named ..swc\" segment id mapped onto zip file dividing divisor discarding remainder. Peter Li's data release 2018-10-02 switched 1E5 1E6.","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-ids.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert between filenames and neuroglancer ids — fafbseg-ids","text":"","code":"swc2segmentid(\"10001654273.1.swc\") #> [1] 10001654273 swc2segmentid(sprintf(\"10001654273.%d.swc\", 0:2), include.fragment=TRUE) #> segment fragment #> [1,] 10001654273 0 #> [2,] 10001654273 1 #> [3,] 10001654273 2 if (FALSE) { # NB the default segmentation for fafbseg (flywire) no longer implies a local # collection of skeletons, wrap calls in with_segmentation with_segmentation(\"20190805\", segmentid2zip(10001654273)) with_segmentation(\"20190805\", segmentid2zip(swc2segmentid(\"10001654273.1.swc\"))) }"},{"path":"https://natverse.org/fafbseg/reference/fafbseg-package.html","id":null,"dir":"Reference","previous_headings":"","what":"fafbseg: Support Functions for Analysis of FAFB EM Segmentation — fafbseg-package","title":"fafbseg: Support Functions for Analysis of FAFB EM Segmentation — fafbseg-package","text":"Functions read raw data formats produced Google electron microscopy segmentation tools displayed 'neuroglancer' allow basic 3D visualisation analysis.","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-package.html","id":"package-options","dir":"Reference","previous_headings":"","what":"Package Options","title":"fafbseg: Support Functions for Analysis of FAFB EM Segmentation — fafbseg-package","text":"fafbseg.sampleurl optionally set sample Neuroglancer URL modified point arbitrary locations open_fafb_ngl. fafbseg.cave.datastack_name optionally set datastack_name used CAVE system. Expert use . Normally choose_segmentation looks . See flywire_cave_query details. fafbseg.condaenv python environment use miniconda. Defaults \"r-reticulate\", environment set reticulate::install_miniconda. can set something different like keep separate miniconda virtual environment just fafbseg (expert use ). fafbseg.sqlitepath optional set location SQLite tables used flywire_partners friends. fafbseg.cachedir location disk caches functions including flywire_leaves unset package load, set appropriate user folder using rappdirs::user_data_dir. fafbseg.flcachesize maximum cache size bytes. Defaults 1.5 * 1024^3 unset. See flywire_leaves details. fafbseg.flywire_roots.chunksize default processing 100,000 rootids time. Set smaller queries time / give \"Request Entity Large\" errors. Larger settings unlikely much speed impact. See flywire_rootid details. fafbseg.skelziproot set location folder containing zipped versions skeletonised segmentations. used read_segments, read_topn etc. fafbseg.skeletonuri brainmaps URI specifying remote source used read.neurons.brainmaps brainmaps_skeleton read neuronal skeletons. fafbseg.brainmaps_xyz2id.chunksize default querying 4000 vertices time. Set smaller queries time larger speed things . See brainmaps_xyz2id details.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/fafbseg-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"fafbseg: Support Functions for Analysis of FAFB EM Segmentation — fafbseg-package","text":"Maintainer: Gregory Jefferis jefferis@gmail.com (ORCID) contributors: Sridhar Jagannathan j.sridharrajan@gmail.com (ORCID) [contributor] Alexander Bates alexander.shakeel.bates@gmail.com (ORCID) [contributor]","code":""},{"path":"https://natverse.org/fafbseg/reference/fafbseg-package.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"fafbseg: Support Functions for Analysis of FAFB EM Segmentation — fafbseg-package","text":"","code":"options()[grep(\"^fafbseg\\\\.\", names(options()))] #> $fafbseg.cachedir #> [1] \"/home/runner/.local/share/R/fafbseg\" #> #> $fafbseg.cave.datastack_name #> [1] \"flywire_fafb_production\" #> #> $fafbseg.cloudvolume.url #> [1] \"graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31\" #> #> $fafbseg.condaenv #> [1] \"r-reticulate\" #> #> $fafbseg.sampleurl #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22:%5B%7B%22source%22:%22precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked%22%2C%22type%22:%22image%22%2C%22blend%22:%22default%22%2C%22shaderControls%22:%7B%7D%2C%22name%22:%22Production-image%22%7D%2C%7B%22source%22:%22graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31%22%2C%22type%22:%22segmentation_with_graph%22%2C%22segments%22:%5B%220%22%5D%2C%22skeletonRendering%22:%7B%22mode2d%22:%22lines_and_points%22%2C%22mode3d%22:%22lines%22%7D%2C%22graphOperationMarker%22:%5B%7B%22annotations%22:%5B%5D%2C%22tags%22:%5B%5D%7D%2C%7B%22annotations%22:%5B%5D%2C%22tags%22:%5B%5D%7D%5D%2C%22pathFinder%22:%7B%22color%22:%22#ffff00%22%2C%22pathObject%22:%7B%22annotationPath%22:%7B%22annotations%22:%5B%5D%2C%22tags%22:%5B%5D%7D%2C%22hasPath%22:false%7D%7D%2C%22name%22:%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22:%5B108360%2C42086%2C3279%5D%7D%7D%2C%22zoomFactor%22:8%7D%2C%22perspectiveZoom%22:2230.6094286986126%2C%22jsonStateServer%22:%22https://globalv1.flywire-daf.com/nglstate/post%22%2C%22selectedLayer%22:%7B%22layer%22:%22Production-segmentation_with_graph%22%2C%22visible%22:true%7D%2C%22layout%22:%22xy-3d%22%7D\" #> #> $fafbseg.sqlitepath #> [1] \"~/projects/JanFunke/\" #>"},{"path":"https://natverse.org/fafbseg/reference/fct2nginfo.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","title":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","text":"Convert flytable cell type information neuroglancer info file","code":""},{"path":"https://natverse.org/fafbseg/reference/fct2nginfo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","text":"","code":"fct2nginfo(f, ids = NULL, version = NULL, sep = \"_\", gluestr = NULL, ...)"},{"path":"https://natverse.org/fafbseg/reference/fct2nginfo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","text":"f Path json file. write_nginfo create enclosing directory necessary. ids FlyWire root ids form understood flywire_ids version Optional numeric CAVE version (see flywire_cave_query). special signalling value TRUE uses current default data dump returned flywire_connectome_data_version. sep separator used paste multiple columns annotations together. gluestr Optional string passed glue::glue interpreted context annotation data.frame produced flytable_meta. allows arbitrary formatting ... Additional arguments passed flytable_meta eventually flytable_cell_types.","code":""},{"path":"https://natverse.org/fafbseg/reference/fct2nginfo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","text":"path f invisibly","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/fct2nginfo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert flytable cell type information into a neuroglancer info file — fct2nginfo","text":"","code":"if (FALSE) { # all neurons in info table fct2nginfo(f='path/to/flytablev526/info', version=526) fct2nginfo(f='path/to/hemilineagev526/info', version=526, gluestr=\"{ito_lee_hemilineage}_{toupper(substr(side,1,1))}\") fct2nginfo(\"MBON%\", 'path/to/mboninfo/info') }"},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"Fetch data specified set curl shell commands (e.g. Chrome)","code":""},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"","code":"fetch_all_curl( x = clipr::read_clip(), outdir = NULL, regex = \"^curl\", filename = \"chunk%05d.raw\", ... )"},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"x Path file character vector statements (default reads statements clipboard) outdir Optional output directory (created necessary) regex Optional regular expression curl statements must match filename sprintf style format statement used name downloaded files. ... Additional arguments grep","code":""},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"named character vector containing matched URLs named downloaded files disk (invisibly)","code":""},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"can generate appropriate set commands opening Chrome Developer console (View ... Developer ... JavaScript Console), (re)loading page interest, selecting network tab, selecting downloaded object, right clicking choosing (Copy ... Copy cURL). make sure one neuron displayed want parse object identifier relationships.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/fetch_all_curl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch data specified by a set of curl shell commands (e.g. from Chrome) — fetch_all_curl","text":"","code":"if (FALSE) { fetch_all_curl(\"all_curl.sh\", outdir=\"alldata\", regex=\"brainmaps.googleapis.com\", fixed=TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":null,"dir":"Reference","previous_headings":"","what":"Find all merged segment ids for a given starting google segment id — find_merged_segments","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"Find merged segment ids given starting google segment id","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"","code":"find_merged_segments( x, return.groups = FALSE, return.segmentids.for.groups = TRUE )"},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"x segment id input can interpreted ngl_segments return.groups Whether return merge groups well segment ids return.segmentids..groups Whether return canonical segment id group rather 1-index merge group (see details).","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"vector segment ids (ascending order) return.groups=TRUE data.frame columns segment integer segment id, numeric (double) column group arbitrary group id starting 1 canonical segment id (see details), integer numeric (double), respectively","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"segment ids ffn16reseg-ms1000_md0.02_c0.6_iou0.7 always match one raw segment id fafb_v14_16nm_v00c_split3xfill2 may map large agglomerated merge group. provide two ways define identifier merge groups. One uses canonical segment id: first (.e. lowest) segment id merge group appears brainmaps API identifies merge group. case even known merges given segment. R field numeric (double) column since R native support 64 bit integers. second approach group identifiers uses integer 1 number known merge groups. known merges segment, NA value returned. Note function depends segment_merge_groups.dt object fafbsegdata package.","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments","text":"","code":"# \\donttest{ if(requireNamespace('fafbsegdata', quietly = TRUE)) { find_merged_segments(7186840767) # these all belong to one merge group by definition find_merged_segments(7186840767, return.groups=TRUE) } #> segment group #> 1 10218295532 7186840767 #> 2 10233257420 7186840767 #> 3 7186840767 7186840767 #> 4 7186844852 7186840767 #> 5 7188488573 7186840767 #> 6 7188488876 7186840767 #> 7 7506547847 7186840767 #> 8 7511521487 7186840767 #> 9 7513174533 7186840767 #> 10 7523125878 7186840767 #> 11 7524769973 7186840767 #> 12 7528082928 7186840767 #> 13 7528082999 7186840767 #> 14 7528083090 7186840767 #> 15 7528087811 7186840767 #> 16 7844472994 7186840767 #> 17 7844473351 7186840767 #> 18 7866011642 7186840767 #> 19 7866015978 7186840767 #> 20 7869320680 7186840767 #> 21 8184049304 7186840767 #> 22 8184049546 7186840767 #> 23 8187380528 7186840767 #> 24 8193975632 7186840767 #> 25 8198954037 7186840767 #> 26 8515392737 7186840767 #> 27 8525318026 7186840767 #> 28 8525318518 7186840767 #> 29 8525318619 7186840767 #> 30 8525318881 7186840767 #> 31 8526948746 7186840767 #> 32 8535280040 7186840767 #> 33 8541870917 7186840767 #> 34 8543523319 7186840767 #> 35 8861569429 7186840767 #> 36 8866569630 7186840767 #> 37 8866569764 7186840767 #> 38 8869882415 7186840767 #> 39 8873165227 7186840767 #> 40 8873192134 7186840767 #> 41 8874821377 7186840767 #> 42 8876521709 7186840767 #> 43 8876543998 7186840767 #> 44 8878156810 7186840767 #> 45 8881456848 7186840767 #> 46 8883135153 7186840767 #> 47 9217782462 7186840767 #> 48 9219408058 7186840767 #> 49 9219408083 7186840767 #> 50 9221047258 7186840767 #> 51 9537450356 7186840767 #> 52 9539102248 7186840767 #> 53 9540758370 7186840767 #> 54 9540758400 7186840767 #> 55 9540758403 7186840767 #> 56 9554037005 7186840767 #> 57 9554041768 7186840767 #> 58 9555689874 7186840767 #> 59 9560632655 7186840767 #> 60 9562293635 7186840767 #> 61 9563945725 7186840767 #> 62 9875383416 7186840767 #> 63 9880358224 7186840767 #> 64 9885314546 7186840767 # }"},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments_slow.html","id":null,"dir":"Reference","previous_headings":"","what":"Find all merged segment ids for a given starting google segment id — find_merged_segments_slow","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments_slow","text":"naive implementation depends mergeinfo object created read_mergeinfo. retained verify correctness. slow require pre-processing table merge information.","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments_slow.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments_slow","text":"","code":"find_merged_segments_slow(x, mergeinfo)"},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments_slow.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments_slow","text":"x segment id input can interpreted ngl_segments mergeinfo merge information data.frame created read_mergeinfo","code":""},{"path":"https://natverse.org/fafbseg/reference/find_merged_segments_slow.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find all merged segment ids for a given starting google segment id — find_merged_segments_slow","text":"vector segment ids","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":null,"dir":"Reference","previous_headings":"","what":"Flytable database queries — flytable-queries","title":"Flytable database queries — flytable-queries","text":"flytable_query performs SQL query flytable database. can omit base argument unless tables name different bases.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Flytable database queries — flytable-queries","text":"","code":"flytable_list_rows( table, base = NULL, view_name = NULL, order_by = NULL, desc = FALSE, start = 0L, limit = Inf, python = FALSE, chunksize = NULL ) flytable_query( sql, limit = 100000L, base = NULL, python = FALSE, convert = TRUE )"},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Flytable database queries — flytable-queries","text":"table name table inside database base Character vector naming seatable base (recommended) Base object returned flytable_base (expert use). view_name optional view may limit rows/columns displayed. order_by Optional name columns order results desc Whether use descending order (default FALSE => ascending order) start Optional starting row limit optional limit, applies specify limit directly sql query. default seatable limits SQL queries 100 rows. increase limit 100000 rows default. python Whether return Python pandas DataFrame. default FALSE returns R data.frame chunksize Optional maximum number rows request one web request. advanced use default value NULL fetch many possible. sql SQL query string. See examples seatable docs. convert Expert use : Whether allow Python seatable module process raw output database. principally debugging purposes. NB imposes requirement seatable_api >=2.4.0.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Flytable database queries — flytable-queries","text":"R data.frame Pandas DataFrame depending value python argument. data.frame results. 0 rows rows matched query.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Flytable database queries — flytable-queries","text":"Flytable uses programmatic access seatable API.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable-queries.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Flytable database queries — flytable-queries","text":"","code":"# \\donttest{ flytable_list_rows(table = \"testfruit\") #> _id _mtime _ctime fruit_name #> 1 H8BckTnXRL2PaVuLDcRPMA 2022-05-12 16:58:07 2021-12-17 13:36:17 apple #> 2 SrBW3vFLRxafKRYHoPrGQQ 2022-05-12 16:58:08 2021-12-17 13:36:17 banana #> 3 F1h-TZKpTcWiHujZ2xnF8Q 2022-05-12 16:58:08 2021-12-17 13:36:17 clementine #> 4 KZrMyoJKTeS_o9Pgynu7YQ 2024-01-26 22:25:57 2022-05-11 00:34:27 kiwi #> 5 cI4fqlOUQK2A1jZKZvFpdg 2022-05-12 16:58:09 2022-05-11 00:39:59 kiwi #> 6 AOUcHHZ0RTC-auONZURx4g 2022-05-12 16:58:10 2022-05-11 00:40:57 kiwi #> 7 dxs7n1NpRM-hWoGJxPZpKA 2022-05-12 16:58:10 2022-05-11 00:41:17 kiwi #> 8 J-JrluKcRzmYjgKCtMEAKw 2022-05-12 16:58:11 2022-05-11 00:41:25 kiwi #> 9 aMmi4iegRNCdpY39-iAfdg 2022-05-12 16:58:11 2022-05-11 01:00:47 kiwi #> 10 EH-l0qAyQyyJO8UpNYSj8w 2022-05-12 16:58:12 2022-05-11 01:07:10 kiwi #> 11 E6uAS8ehQyid0sSj1bD-HA 2022-05-12 16:58:12 2022-05-11 20:52:00 kiwi #> 12 P83tySHzT-iFfbwvlhJU7A 2022-05-12 16:58:13 2022-05-11 21:18:45 kiwi #> 13 GBCn8fkaTnidSg8Nh7CLkQ 2022-05-12 16:58:13 2022-05-11 21:25:28 kiwi #> 14 DHSK4OmSRYiNHFn6yHWEjQ 2022-05-12 16:58:13 2022-05-11 21:29:40 kiwi #> 15 CVL59Pt2Ta6BWXXmEmLFSw 2022-05-12 16:58:14 2022-05-11 21:34:07 kiwi #> 16 DHq2ty1nQn-LolwKbR5D9A 2022-05-12 16:58:14 2022-05-11 21:34:22 kiwi #> 17 Y4aoKGjIQU6WskMCll9LtA 2022-05-12 16:58:15 2022-05-12 16:56:52 kiwi #> 18 L94KQt88S6-cPBQSSk8IDg 2022-05-12 16:58:15 2022-05-12 16:58:15 kiwi #> 19 JgCx-eJfQI22f1ynv_G4aA 2022-05-12 18:16:18 2022-05-12 18:16:18 kiwi #> 20 HWP0B4R2TVinR51ZEiCh1Q 2022-05-12 18:33:47 2022-05-12 18:33:47 kiwi #> 21 frinTnwQS_yT-p-6bUdUjg 2022-05-12 18:49:36 2022-05-12 18:49:36 kiwi #> 22 Q79Qb0tMSi-NT__KJOXdnw 2022-05-12 19:03:47 2022-05-12 19:03:47 kiwi #> 23 e63mt6sxSCSHK-AqkyE7rQ 2022-05-12 20:22:02 2022-05-12 20:22:02 kiwi #> 24 e3AH4HFxTHiIILhWAgVfnQ 2022-05-12 20:41:57 2022-05-12 20:41:57 kiwi #> 25 LIbNUlKpQhq3pHuqs_GG2A 2022-05-13 13:10:55 2022-05-13 13:10:55 kiwi #> 26 Jox91CBQQIq8zv58pjE-gA 2022-05-13 13:11:49 2022-05-13 13:11:49 kiwi #> 27 Mm7xFfvlQ6Ohb3FFA7-y3g 2022-05-13 13:12:24 2022-05-13 13:12:24 kiwi #> 28 SY5dA23CSfCqFnePxJP1Ng 2022-05-13 13:13:31 2022-05-13 13:13:31 kiwi #> 29 c-9ONdxnTsyIWgMx8_Qo5w 2022-05-13 14:15:29 2022-05-13 14:15:29 kiwi #> 30 NvptrkSgS36T-Q6TBbyioA 2022-05-13 14:20:30 2022-05-13 14:20:30 kiwi #> 31 PXX2Ay_XRwSOkVrJqBftsA 2022-05-13 14:21:21 2022-05-13 14:21:21 kiwi #> 32 ET9-W5hxRdOoeEr54TgfZw 2022-05-13 14:26:16 2022-05-13 14:26:16 kiwi #> 33 GBy5d_8jTYyV1RUEwpAwfQ 2022-05-13 14:32:10 2022-05-13 14:32:10 kiwi #> 34 UvG5kHD7ST6m4yj5-xk2QA 2022-05-22 07:43:19 2022-05-22 07:43:19 kiwi #> 35 SI2RldvDSsmadBqYrCqaqQ 2022-05-22 07:47:43 2022-05-22 07:47:43 kiwi #> 36 MNPFKn5zRRKMHq66LQNWiA 2022-05-22 07:51:06 2022-05-22 07:51:06 kiwi #> 37 OTsRNBFrS3mtawfKiREmrw 2022-05-29 06:31:28 2022-05-29 06:31:28 kiwi #> 38 Nv8oP_hUSvyHgws5DQ0ZGA 2022-05-29 10:30:15 2022-05-29 10:30:15 kiwi #> 39 OrEYIA_bQDCx6v-MkTuDYw 2022-05-29 10:34:54 2022-05-29 10:34:54 kiwi #> 40 BhzO_0xqQsi41eCEKsAjGQ 2022-05-29 10:38:00 2022-05-29 10:38:00 kiwi #> 41 BNeHPQNnSyuMvAEd3Kh6MQ 2022-05-29 20:33:27 2022-05-29 20:33:27 kiwi #> 42 aVoVAUuWTFOtoUhQvOd_bg 2022-05-29 20:40:41 2022-05-29 20:40:41 kiwi #> 43 BYauV5OwTa2tOk9JWW1N_A 2022-05-29 20:42:10 2022-05-29 20:42:10 kiwi #> 44 DR3lfQrkQmu_tUcwlzx6Aw 2022-05-29 20:45:57 2022-05-29 20:45:57 kiwi #> 45 JVksPUCFSFCD4pF__s5E2A 2022-06-06 14:40:12 2022-06-06 14:40:12 kiwi #> 46 T4IY3mh6Sniovww6Yg3OWQ 2022-06-06 14:44:59 2022-06-06 14:44:59 kiwi #> 47 TQqr1_nAQv27Qm3p1GXIMQ 2022-06-06 14:50:54 2022-06-06 14:50:54 kiwi #> 48 c87JLpHXS5CRtj1YtXpL0g 2022-07-01 20:06:17 2022-07-01 20:06:17 kiwi #> 49 AirzCY7yRS26fFBU_F6j5g 2022-07-01 20:33:14 2022-07-01 20:33:14 kiwi #> 50 fRamo6FETfqaProIZuRbaA 2022-07-01 20:41:09 2022-07-01 20:41:09 kiwi #> 51 Uy0XHWAhQjqJ2QtM-rDj3A 2022-07-01 20:42:29 2022-07-01 20:42:29 kiwi #> 52 EcabRY2tSZyxjT9dztNVhQ 2022-07-01 21:11:03 2022-07-01 21:11:03 kiwi #> 53 VdYIA9bAQaWnTafJOR7-IA 2022-07-01 21:16:00 2022-07-01 21:16:00 kiwi #> 54 YiTEtjEnT3OlWI8RJ0GbHA 2022-07-01 21:25:19 2022-07-01 21:25:19 kiwi #> 55 Gw_qH6Z7RIeR1QHF-PnQfw 2022-08-01 19:57:01 2022-08-01 19:57:01 kiwi #> 56 Za09YgQyT0y4y7ACVChnFA 2022-08-01 20:02:23 2022-08-01 20:02:23 kiwi #> 57 OqE9c2o2RYO-jGSfI7hlPg 2022-08-01 20:11:08 2022-08-01 20:11:08 kiwi #> 58 V__EDBYxRDaqLNoCGJnQ8w 2022-08-01 20:48:34 2022-08-01 20:48:34 kiwi #> 59 VPVed66YRFu7BH6deAd_Hw 2022-08-01 20:55:12 2022-08-01 20:55:12 kiwi #> 60 QO0OBDKNSl2mbxJX5vEjKg 2022-08-01 21:00:19 2022-08-01 21:00:19 kiwi #> 61 J9juoAsSQXuzzBI3TtuL6w 2022-08-28 18:36:52 2022-08-28 18:36:52 kiwi #> 62 MjCZO6wETZ29wzZuAWoSlQ 2022-08-28 18:42:31 2022-08-28 18:42:31 kiwi #> 63 IxvyCT3UQXOwGo2CUgjOuA 2022-08-28 19:44:37 2022-08-28 19:44:37 kiwi #> 64 OqW1gtFTRtq6MO06Sm_lCw 2022-08-31 19:52:42 2022-08-31 19:52:42 kiwi #> 65 JCAX6dZ5TvSycDTdhgjCsw 2022-08-31 20:00:52 2022-08-31 20:00:52 kiwi #> 66 a6G0CwCFRIaBdsN0ZKqrJg 2022-08-31 21:35:54 2022-08-31 21:35:54 kiwi #> 67 JMfv_ifOSQ6QsHg_tfjpVw 2022-08-31 21:41:49 2022-08-31 21:41:49 kiwi #> 68 LZp9F2A8RhGlWRJpVO5daA 2022-08-31 21:51:44 2022-08-31 21:51:44 kiwi #> 69 GeE_rs_bQfCTKEVKgTb9jQ 2022-09-12 11:42:51 2022-09-12 11:42:51 kiwi #> 70 AxVvTwGmQAafJYRpOJqx8g 2022-09-12 11:59:40 2022-09-12 11:59:40 kiwi #> 71 B5pXXJ8wTCO4mzbbesSIVA 2022-09-12 12:21:12 2022-09-12 12:21:12 kiwi #> 72 d_AkJSgzSRuZEqPapTahLA 2022-09-12 12:39:22 2022-09-12 12:39:22 kiwi #> 73 Ampj7vLgTYiP-w0p1LrHOA 2022-09-12 13:59:26 2022-09-12 13:59:26 kiwi #> 74 W3VuY_tXRpKwV644qtqh1A 2022-09-12 14:05:01 2022-09-12 14:05:01 kiwi #> 75 XoUJBlWuTP-E_m_Mkwtnbg 2022-09-13 09:01:13 2022-09-13 09:01:13 kiwi #> 76 WBbegVpbSCa_paGdR718pw 2022-09-13 09:07:08 2022-09-13 09:07:08 kiwi #> 77 Xu_lF9gIRBGZ1VY0bnzSqg 2022-09-13 09:09:27 2022-09-13 09:09:27 kiwi #> 78 AaQTau4rQMC0vJMti63XqA 2022-09-14 09:31:22 2022-09-14 09:31:22 kiwi #> 79 NGvXEDVGTKusZMQFb7X7bA 2022-09-14 09:36:24 2022-09-14 09:36:24 kiwi #> 80 IdF2TmPgT3mKDmxzZ6SSXw 2022-09-14 09:54:34 2022-09-14 09:54:34 kiwi #> 81 LaeL3mmQRwSf8RJ-NrZefg 2022-09-14 15:44:47 2022-09-14 15:44:47 kiwi #> 82 DDqyRYCvRO2Y9Uhw2-1tDw 2022-09-14 16:20:36 2022-09-14 16:20:36 kiwi #> 83 fo1kT5F5QP2TDmk_cHhhpQ 2022-09-14 16:47:53 2022-09-14 16:47:53 kiwi #> 84 HNDDYQHuQxaYFBrSwtnjpw 2022-09-14 16:55:04 2022-09-14 16:55:04 kiwi #> 85 PDNQ5A3_QFCf-YJw2uDGgg 2022-09-14 23:30:37 2022-09-14 23:30:37 kiwi #> 86 GLhZRDKJSQGGkoP5vAuO5w 2022-09-14 23:36:40 2022-09-14 23:36:40 kiwi #> 87 JAuywPlLQvukKwuEBXfMyw 2022-09-14 23:50:18 2022-09-14 23:50:18 kiwi #> 88 B2jl0go9Qcu_MXqwau0WYA 2022-09-15 09:33:48 2022-09-15 09:33:48 kiwi #> 89 TbJG8c-RQWSpHyCISJMhWA 2022-09-15 09:49:01 2022-09-15 09:49:01 kiwi #> 90 Q6tRp3t-QPy8Zp-aweV9VQ 2022-09-15 09:53:43 2022-09-15 09:53:43 kiwi #> 91 f69-_rT_RVGnhGuhyB0uJw 2022-09-15 09:59:12 2022-09-15 09:59:12 kiwi #> 92 HI8Lmwc9T-ihQJ5k5h4IMw 2022-09-15 10:02:06 2022-09-15 10:02:06 kiwi #> 93 Z6r_FG3gTd-j3sdf6TZ3HA 2022-09-15 10:08:05 2022-09-15 10:08:05 kiwi #> 94 D-bM34KyTyGAziycJ0mmyw 2022-09-15 10:10:25 2022-09-15 10:10:25 kiwi #> 95 M7h1HwTJSsibmQMAHV9Xnw 2022-09-15 16:44:02 2022-09-15 16:44:02 kiwi #> 96 fcoSfaqXRU6thcCOqifaEQ 2022-09-15 17:01:50 2022-09-15 17:01:50 kiwi #> 97 RXEUvn5bTdSMdoj8yPqY5w 2022-09-15 17:45:04 2022-09-15 17:45:04 kiwi #> 98 DdSEevBzQPyMU6UxXWwaKg 2022-09-15 17:51:49 2022-09-15 17:51:49 kiwi #> 99 ICvTVApETTutpbIgsAlkKQ 2022-09-25 23:58:56 2022-09-25 23:58:56 kiwi #> 100 cN75fj1aS2q-ZnaUP5wcuw 2022-09-26 00:00:50 2022-09-26 00:00:50 kiwi #> 101 cPXr4UHrQPODd4Bk7e1t5w 2022-09-26 00:05:20 2022-09-26 00:05:20 kiwi #> 102 X2MoZEqxTvq5JPTjPMLcgQ 2022-09-26 00:41:12 2022-09-26 00:41:12 kiwi #> 103 W56u11ofRwqXz-yMdtZumw 2022-09-26 00:47:49 2022-09-26 00:47:49 kiwi #> 104 fFoZKPghSWqjialXJOB6Bw 2022-09-26 07:00:20 2022-09-26 07:00:20 kiwi #> 105 PI9Fw2I5TvmJinqKKcwepQ 2022-09-26 07:06:14 2022-09-26 07:06:14 kiwi #> 106 I8rPbrIZTLGqsrmIcDJjiA 2022-09-26 09:12:11 2022-09-26 09:12:11 kiwi #> 107 GR2KIDhgTF2KbxNOTOU4Uw 2022-09-26 09:17:19 2022-09-26 09:17:19 kiwi #> 108 GwfOL861RpOSFaEnN6SwOQ 2022-10-04 11:23:23 2022-10-04 11:23:23 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2023-12-27 20:09:49 2023-12-27 20:09:49 kiwi #> 454 PCDP2CEKT5qGDlPR0htmTw 2023-12-27 20:35:02 2023-12-27 20:35:02 kiwi #> 455 XLW3t5IHQF69qZunEv1cwQ 2023-12-27 23:29:51 2023-12-27 23:29:51 kiwi #> 456 G9K42HcmQbKDMDbktd2gig 2023-12-27 23:43:07 2023-12-27 23:43:07 kiwi #> 457 Vpzc7a4GRl2uOMi4m_L-2A 2023-12-27 23:48:17 2023-12-27 23:48:17 kiwi #> 458 XMWPl3tRTtajI0U_bXpn7g 2023-12-28 00:29:37 2023-12-28 00:29:37 kiwi #> 459 AQZmld2UT2uizrycCL32qA 2023-12-28 00:42:07 2023-12-28 00:42:07 kiwi #> 460 ZMMgbZaJQQqyBW8qBm9lsQ 2023-12-28 00:43:28 2023-12-28 00:43:28 kiwi #> 461 FVipCjdDTaKCojyKvBYWgw 2023-12-28 12:20:04 2023-12-28 12:20:04 kiwi #> 462 RqEXYZ2bQP2_0S8bYl0GfA 2023-12-28 12:24:08 2023-12-28 12:24:08 kiwi #> 463 BgJIbcspTJ6XQzuPJiXwvQ 2023-12-28 12:45:17 2023-12-28 12:45:17 kiwi #> 464 HIgNe40gTJqNsNJ8D3yJcg 2024-01-15 17:54:42 2024-01-15 17:54:42 kiwi #> 465 NCqN0FjsSuq26oKmU9EeWw 2024-01-15 18:10:30 2024-01-15 18:10:30 kiwi #> 466 FAPMoj-YRmOwV2NLjQyyzQ 2024-01-16 10:08:59 2024-01-16 10:08:59 kiwi #> 467 GHfdynarRXqaL0voP_eZAQ 2024-01-17 15:53:35 2024-01-17 15:53:35 kiwi #> 468 OUbwDZywTaS-JMbEaXA-Tw 2024-01-17 16:25:50 2024-01-17 16:25:50 kiwi #> 469 EXHFx-sTT_GxPuFYVVNzUg 2024-01-17 22:58:48 2024-01-17 22:58:48 kiwi #> 470 CYCqSBn3S7aQNdBHZmd0cg 2024-01-17 23:09:06 2024-01-17 23:09:06 kiwi #> 471 G516rJm2Qq6LBfGPafzgXw 2024-01-17 23:13:55 2024-01-17 23:13:55 kiwi #> 472 N8lByhadRym68iMWyMKo1Q 2024-01-18 00:19:09 2024-01-18 00:19:09 kiwi #> 473 c8RQlG0-TDiGeY2SQk0i0w 2024-01-18 00:25:17 2024-01-18 00:25:17 kiwi #> 474 JSQglb37SzquHiXR2viZsg 2024-01-18 00:42:53 2024-01-18 00:42:53 kiwi #> 475 DurLLmkrTWKPhIeRj1Whdg 2024-01-25 23:15:13 2024-01-25 23:15:13 kiwi #> 476 QgYVjyKfQliBP7-KYHkIjA 2024-01-26 09:22:02 2024-01-26 09:22:02 kiwi #> 477 CfCJdGFzSZ2iDpgX9thCCg 2024-01-26 09:33:24 2024-01-26 09:33:24 kiwi #> 478 Eqf5rqZeQT2che-bBoICug 2024-01-26 21:56:28 2024-01-26 21:56:28 kiwi #> 479 V45C6dt-TQyd01F03xeWbw 2024-01-26 22:00:24 2024-01-26 22:00:24 kiwi #> 480 FHVFcBL3TSOm1E_9q2oPtA 2024-01-26 22:25:58 2024-01-26 22:25:58 kiwi #> nid person last_modified date_nominute #> 1 1 Alice 2022-05-12 16:58:07 2022-01-06 #> 2 2 Bob 2022-05-12 16:58:08 2022-01-03 #> 3 3 Clara 2022-05-12 16:58:08 2021-08-05 #> 4 6 Frederick the Great 2024-01-26 22:25:57 #> 5 6 Frederick the Great 2022-05-12 16:58:09 #> 6 6 Frederick the Great 2022-05-12 16:58:10 #> 7 6 Frederick the Great 2022-05-12 16:58:10 #> 8 6 Frederick the Great 2022-05-12 16:58:11 #> 9 6 Frederick the Great 2022-05-12 16:58:11 #> 10 6 Frederick the Great 2022-05-12 16:58:12 #> 11 6 Frederick the Great 2022-05-12 16:58:12 #> 12 6 Frederick the Great 2022-05-12 16:58:13 #> 13 6 Frederick the Great 2022-05-12 16:58:13 #> 14 6 Frederick the Great 2022-05-12 16:58:13 #> 15 6 Frederick the Great 2022-05-12 16:58:14 #> 16 6 Frederick the Great 2022-05-12 16:58:14 #> 17 6 Frederick the Great 2022-05-12 16:58:15 #> 18 6 Frederick the Great 2022-05-12 16:58:15 #> 19 6 Frederick the Great 2022-05-12 18:16:18 #> 20 6 Frederick the Great 2022-05-12 18:33:47 #> 21 6 Frederick the Great 2022-05-12 18:49:36 #> 22 6 Frederick the Great 2022-05-12 19:03:47 #> 23 6 Frederick the Great 2022-05-12 20:22:02 #> 24 6 Frederick the Great 2022-05-12 20:41:57 #> 25 6 Frederick the Great 2022-05-13 13:10:55 #> 26 6 Frederick the Great 2022-05-13 13:11:49 #> 27 6 Frederick the Great 2022-05-13 13:12:24 #> 28 6 Frederick the Great 2022-05-13 13:13:31 #> 29 6 Frederick the Great 2022-05-13 14:15:29 #> 30 6 Frederick the Great 2022-05-13 14:20:30 #> 31 6 Frederick the Great 2022-05-13 14:21:21 #> 32 6 Frederick the Great 2022-05-13 14:26:16 #> 33 6 Frederick the Great 2022-05-13 14:32:10 #> 34 6 Frederick the Great 2022-05-22 07:43:19 #> 35 6 Frederick the Great 2022-05-22 07:47:43 #> 36 6 Frederick the Great 2022-05-22 07:51:06 #> 37 6 Frederick the Great 2022-05-29 06:31:28 #> 38 6 Frederick the Great 2022-05-29 10:30:15 #> 39 6 Frederick the Great 2022-05-29 10:34:54 #> 40 6 Frederick the Great 2022-05-29 10:38:00 #> 41 6 Frederick the Great 2022-05-29 20:33:27 #> 42 6 Frederick the Great 2022-05-29 20:40:41 #> 43 6 Frederick the Great 2022-05-29 20:42:10 #> 44 6 Frederick the Great 2022-05-29 20:45:57 #> 45 6 Frederick the Great 2022-06-06 14:40:12 #> 46 6 Frederick the Great 2022-06-06 14:44:59 #> 47 6 Frederick the Great 2022-06-06 14:50:54 #> 48 6 Frederick the Great 2022-07-01 20:06:17 #> 49 6 Frederick the Great 2022-07-01 20:33:14 #> 50 6 Frederick the Great 2022-07-01 20:41:09 #> 51 6 Frederick the Great 2022-07-01 20:42:29 #> 52 6 Frederick the Great 2022-07-01 21:11:03 #> 53 6 Frederick the Great 2022-07-01 21:16:00 #> 54 6 Frederick the Great 2022-07-01 21:25:19 #> 55 6 Frederick the Great 2022-08-01 19:57:01 #> 56 6 Frederick the Great 2022-08-01 20:02:23 #> 57 6 Frederick the Great 2022-08-01 20:11:08 #> 58 6 Frederick the Great 2022-08-01 20:48:34 #> 59 6 Frederick the Great 2022-08-01 20:55:12 #> 60 6 Frederick the Great 2022-08-01 21:00:19 #> 61 6 Frederick the Great 2022-08-28 18:36:52 #> 62 6 Frederick the Great 2022-08-28 18:42:31 #> 63 6 Frederick the Great 2022-08-28 19:44:37 #> 64 6 Frederick the Great 2022-08-31 19:52:42 #> 65 6 Frederick the Great 2022-08-31 20:00:52 #> 66 6 Frederick the Great 2022-08-31 21:35:54 #> 67 6 Frederick the Great 2022-08-31 21:41:49 #> 68 6 Frederick the Great 2022-08-31 21:51:44 #> 69 6 Frederick the Great 2022-09-12 11:42:51 #> 70 6 Frederick the Great 2022-09-12 11:59:40 #> 71 6 Frederick the Great 2022-09-12 12:21:12 #> 72 6 Frederick the Great 2022-09-12 12:39:22 #> 73 6 Frederick the Great 2022-09-12 13:59:26 #> 74 6 Frederick the Great 2022-09-12 14:05:01 #> 75 6 Frederick the Great 2022-09-13 09:01:13 #> 76 6 Frederick the Great 2022-09-13 09:07:08 #> 77 6 Frederick the Great 2022-09-13 09:09:27 #> 78 6 Frederick the Great 2022-09-14 09:31:22 #> 79 6 Frederick the Great 2022-09-14 09:36:24 #> 80 6 Frederick the Great 2022-09-14 09:54:34 #> 81 6 Frederick the Great 2022-09-14 15:44:47 #> 82 6 Frederick the Great 2022-09-14 16:20:36 #> 83 6 Frederick the Great 2022-09-14 16:47:53 #> 84 6 Frederick the Great 2022-09-14 16:55:04 #> 85 6 Frederick the Great 2022-09-14 23:30:37 #> 86 6 Frederick the Great 2022-09-14 23:36:40 #> 87 6 Frederick the Great 2022-09-14 23:50:18 #> 88 6 Frederick the Great 2022-09-15 09:33:48 #> 89 6 Frederick the Great 2022-09-15 09:49:01 #> 90 6 Frederick the Great 2022-09-15 09:53:43 #> 91 6 Frederick the Great 2022-09-15 09:59:12 #> 92 6 Frederick the Great 2022-09-15 10:02:06 #> 93 6 Frederick the Great 2022-09-15 10:08:05 #> 94 6 Frederick the Great 2022-09-15 10:10:25 #> 95 6 Frederick the Great 2022-09-15 16:44:02 #> 96 6 Frederick the Great 2022-09-15 17:01:50 #> 97 6 Frederick the Great 2022-09-15 17:45:04 #> 98 6 Frederick the Great 2022-09-15 17:51:49 #> 99 6 Frederick the Great 2022-09-25 23:58:56 #> 100 6 Frederick the Great 2022-09-26 00:00:50 #> 101 6 Frederick the Great 2022-09-26 00:05:20 #> 102 6 Frederick the Great 2022-09-26 00:41:12 #> 103 6 Frederick the Great 2022-09-26 00:47:49 #> 104 6 Frederick the Great 2022-09-26 07:00:20 #> 105 6 Frederick the Great 2022-09-26 07:06:14 #> 106 6 Frederick the Great 2022-09-26 09:12:11 #> 107 6 Frederick the Great 2022-09-26 09:17:19 #> 108 6 Frederick the Great 2022-10-04 11:23:23 #> 109 6 Frederick the Great 2022-10-04 11:29:16 #> 110 6 Frederick the Great 2022-10-04 11:53:29 #> 111 6 Frederick the Great 2022-10-04 11:58:25 #> 112 6 Frederick the Great 2022-10-04 12:07:24 #> 113 6 Frederick the Great 2022-10-04 13:05:57 #> 114 6 Frederick the Great 2022-10-04 13:07:44 #> 115 6 Frederick the Great 2022-10-04 13:10:34 #> 116 6 Frederick the Great 2022-10-04 13:11:08 #> 117 6 Frederick the Great 2022-10-04 13:15:40 #> 118 6 Frederick the Great 2022-10-04 13:16:00 #> 119 6 Frederick the Great 2022-10-04 16:18:32 #> 120 6 Frederick the Great 2022-10-04 16:34:25 #> 121 6 Frederick the Great 2022-10-04 17:16:23 #> 122 6 Frederick the Great 2022-10-04 17:21:45 #> 123 6 Frederick the Great 2022-10-04 17:30:58 #> 124 6 Frederick the Great 2022-10-04 17:34:17 #> 125 6 Frederick the Great 2022-10-04 17:37:40 #> 126 6 Frederick the Great 2022-10-04 17:44:31 #> 127 6 Frederick the Great 2022-10-04 19:01:50 #> 128 6 Frederick the Great 2022-10-04 19:07:20 #> 129 6 Frederick the Great 2022-10-04 19:19:51 #> 130 6 Frederick the Great 2022-10-07 21:04:12 #> 131 6 Frederick the Great 2022-10-07 21:25:49 #> 132 6 Frederick the Great 2022-10-07 21:44:04 #> 133 6 Frederick the Great 2022-10-07 21:47:26 #> 134 6 Frederick the Great 2022-10-07 21:51:11 #> 135 6 Frederick the Great 2022-10-07 21:52:22 #> 136 6 Frederick the Great 2022-10-07 22:00:07 #> 137 6 Frederick the Great 2022-10-07 22:04:11 #> 138 6 Frederick the Great 2022-10-07 22:26:16 #> 139 6 Frederick the Great 2022-10-07 22:31:08 #> 140 6 Frederick the Great 2022-10-07 22:50:36 #> 141 6 Frederick the Great 2022-10-08 10:21:05 #> 142 6 Frederick the Great 2022-10-08 10:27:36 #> 143 6 Frederick the Great 2022-10-08 10:44:47 #> 144 6 Frederick the Great 2022-10-08 11:38:57 #> 145 6 Frederick the Great 2022-10-08 13:48:05 #> 146 6 Frederick the Great 2022-10-08 13:53:08 #> 147 6 Frederick the Great 2022-10-08 14:05:51 #> 148 6 Frederick the Great 2022-11-17 10:38:39 #> 149 6 Frederick the Great 2022-11-17 10:55:14 #> 150 6 Frederick the Great 2022-11-17 10:58:49 #> 151 6 Frederick the Great 2022-11-17 11:18:46 #> 152 6 Frederick the Great 2022-11-18 19:49:24 #> 153 6 Frederick the Great 2022-11-18 20:06:08 #> 154 6 Frederick the Great 2022-11-18 20:08:24 #> 155 6 Frederick the Great 2022-11-18 20:33:51 #> 156 6 Frederick the Great 2022-11-19 17:46:18 #> 157 6 Frederick the Great 2022-11-19 17:57:46 #> 158 6 Frederick the Great 2022-11-22 20:29:27 #> 159 6 Frederick the Great 2022-11-22 20:37:23 #> 160 6 Frederick the Great 2022-11-22 20:37:30 #> 161 6 Frederick the Great 2022-11-22 20:44:33 #> 162 6 Frederick the Great 2022-11-23 16:51:24 #> 163 6 Frederick the Great 2022-11-23 17:13:32 #> 164 6 Frederick the Great 2022-11-26 21:46:30 #> 165 6 Frederick the Great 2022-11-26 21:51:09 #> 166 6 Frederick the Great 2022-11-27 15:38:01 #> 167 6 Frederick the Great 2022-11-27 15:38:52 #> 168 6 Frederick the Great 2022-11-27 15:45:02 #> 169 6 Frederick the Great 2022-11-27 17:40:54 #> 170 6 Frederick the Great 2022-11-27 17:47:19 #> 171 6 Frederick the Great 2022-11-28 07:49:23 #> 172 6 Frederick the Great 2022-11-28 07:55:10 #> 173 6 Frederick the Great 2022-11-28 07:59:30 #> 174 6 Frederick the Great 2022-11-28 08:25:33 #> 175 6 Frederick the Great 2022-11-28 08:31:14 #> 176 6 Frederick the Great 2022-11-28 09:30:12 #> 177 6 Frederick the Great 2022-11-28 09:36:28 #> 178 6 Frederick the Great 2022-11-28 09:39:28 #> 179 6 Frederick the Great 2022-11-28 11:01:59 #> 180 6 Frederick the Great 2022-11-28 11:08:09 #> 181 6 Frederick the Great 2022-11-28 11:11:31 #> 182 6 Frederick the Great 2022-11-29 18:58:51 #> 183 6 Frederick the Great 2022-11-29 19:06:13 #> 184 6 Frederick the Great 2022-11-29 19:13:02 #> 185 6 Frederick the Great 2022-12-11 00:17:18 #> 186 6 Frederick the Great 2022-12-11 00:21:03 #> 187 6 Frederick the Great 2022-12-11 00:23:42 #> 188 6 Frederick the Great 2023-01-13 11:59:47 #> 189 6 Frederick the Great 2023-01-13 12:33:40 #> 190 6 Frederick the Great 2023-01-13 12:39:37 #> 191 6 Frederick the Great 2023-01-22 22:50:26 #> 192 6 Frederick the Great 2023-01-22 22:57:27 #> 193 6 Frederick the Great 2023-01-22 23:00:59 #> 194 6 Frederick the Great 2023-01-23 10:47:44 #> 195 6 Frederick the Great 2023-01-23 10:51:45 #> 196 6 Frederick the Great 2023-01-23 10:54:02 #> 197 6 Frederick the Great 2023-01-23 11:04:46 #> 198 6 Frederick the Great 2023-01-23 11:06:44 #> 199 6 Frederick the Great 2023-01-23 11:11:03 #> 200 6 Frederick the Great 2023-01-23 11:12:12 #> 201 6 Frederick the Great 2023-01-23 11:18:42 #> 202 6 Frederick the Great 2023-01-23 11:21:54 #> 203 6 Frederick the Great 2023-01-23 11:33:49 #> 204 6 Frederick the Great 2023-01-23 14:34:46 #> 205 6 Frederick the Great 2023-01-23 14:40:14 #> 206 6 Frederick the Great 2023-01-23 14:52:29 #> 207 6 Frederick the Great 2023-01-23 23:23:30 #> 208 6 Frederick the Great 2023-01-23 23:31:56 #> 209 6 Frederick the Great 2023-01-24 01:52:16 #> 210 6 Frederick the Great 2023-01-24 01:59:44 #> 211 6 Frederick the Great 2023-01-24 02:08:23 #> 212 6 Frederick the Great 2023-01-24 08:03:55 #> 213 6 Frederick the Great 2023-01-24 08:12:23 #> 214 6 Frederick the Great 2023-01-24 08:14:44 #> 215 6 Frederick the Great 2023-01-24 13:42:13 #> 216 6 Frederick the Great 2023-01-24 14:12:22 #> 217 6 Frederick the Great 2023-01-24 14:20:46 #> 218 6 Frederick the Great 2023-01-24 14:28:38 #> 219 6 Frederick the Great 2023-01-24 14:29:10 #> 220 6 Frederick the Great 2023-01-25 16:38:30 #> 221 6 Frederick the Great 2023-01-25 16:48:28 #> 222 6 Frederick the Great 2023-01-25 16:49:06 #> 223 6 Frederick the Great 2023-01-26 01:32:52 #> 224 6 Frederick the Great 2023-01-26 01:40:53 #> 225 6 Frederick the Great 2023-01-26 02:51:19 #> 226 6 Frederick the Great 2023-01-26 02:58:59 #> 227 6 Frederick the Great 2023-01-26 08:09:19 #> 228 6 Frederick the Great 2023-01-27 07:11:32 #> 229 6 Frederick the Great 2023-01-27 07:23:55 #> 230 6 Frederick the Great 2023-01-27 08:48:00 #> 231 6 Frederick the Great 2023-01-27 08:56:08 #> 232 6 Frederick the Great 2023-01-30 14:59:10 #> 233 6 Frederick the Great 2023-01-30 15:02:45 #> 234 6 Frederick the Great 2023-01-30 15:05:56 #> 235 6 Frederick the Great 2023-01-30 15:09:27 #> 236 6 Frederick the Great 2023-01-30 19:58:34 #> 237 6 Frederick the Great 2023-01-30 20:06:57 #> 238 6 Frederick the Great 2023-01-30 20:14:00 #> 239 6 Frederick the Great 2023-01-30 22:03:04 #> 240 6 Frederick the Great 2023-01-30 22:15:06 #> 241 6 Frederick the Great 2023-02-13 08:34:44 #> 242 6 Frederick the Great 2023-02-13 08:37:48 #> 243 6 Frederick the Great 2023-02-13 10:53:05 #> 244 6 Frederick the Great 2023-02-13 11:14:57 #> 245 6 Frederick the Great 2023-02-13 11:54:27 #> 246 6 Frederick the Great 2023-04-02 12:52:46 #> 247 6 Frederick the Great 2023-04-02 12:58:52 #> 248 6 Frederick the Great 2023-04-02 13:04:37 #> 249 6 Frederick the Great 2023-04-02 21:14:25 #> 250 6 Frederick the Great 2023-04-02 21:21:24 #> 251 6 Frederick the Great 2023-06-13 18:37:23 #> 252 6 Frederick the Great 2023-06-13 18:46:47 #> 253 6 Frederick the Great 2023-06-14 06:09:12 #> 254 6 Frederick the Great 2023-06-14 10:27:24 #> 255 6 Frederick the Great 2023-06-14 11:05:47 #> 256 6 Frederick the Great 2023-06-14 12:00:24 #> 257 6 Frederick the Great 2023-06-14 12:44:12 #> 258 6 Frederick the Great 2023-06-14 12:56:28 #> 259 6 Frederick the Great 2023-06-14 13:54:05 #> 260 6 Frederick the Great 2023-06-15 20:12:49 #> 261 6 Frederick the Great 2023-06-15 20:17:28 #> 262 6 Frederick the Great 2023-06-15 20:25:20 #> 263 6 Frederick the Great 2023-06-16 09:39:16 #> 264 6 Frederick the Great 2023-06-26 06:10:47 #> 265 6 Frederick the Great 2023-06-26 06:33:34 #> 266 6 Frederick the Great 2023-06-26 07:22:55 #> 267 6 Frederick the Great 2023-06-26 07:26:51 #> 268 6 Frederick the Great 2023-06-26 07:31:48 #> 269 6 Frederick the Great 2023-06-26 07:34:59 #> 270 6 Frederick the Great 2023-06-26 08:55:32 #> 271 6 Frederick the Great 2023-06-26 09:01:34 #> 272 6 Frederick the Great 2023-06-26 09:10:31 #> 273 6 Frederick the Great 2023-06-26 10:07:19 #> 274 6 Frederick the Great 2023-06-26 10:26:06 #> 275 6 Frederick the Great 2023-06-26 10:34:52 #> 276 6 Frederick the Great 2023-06-26 10:37:19 #> 277 6 Frederick the Great 2023-06-27 10:17:07 #> 278 6 Frederick the Great 2023-06-27 10:23:22 #> 279 6 Frederick the Great 2023-06-27 10:32:51 #> 280 6 Frederick the Great 2023-06-27 12:31:48 #> 281 6 Frederick the Great 2023-06-27 12:38:28 #> 282 6 Frederick the Great 2023-06-27 20:57:41 #> 283 6 Frederick the Great 2023-06-28 08:51:08 #> 284 6 Frederick the Great 2023-06-28 09:08:31 #> 285 6 Frederick the Great 2023-06-28 09:15:01 #> 286 6 Frederick the Great 2023-06-28 09:25:48 #> 287 6 Frederick the Great 2023-07-04 20:56:37 #> 288 6 Frederick the Great 2023-07-10 12:26:30 #> 289 6 Frederick the Great 2023-07-10 12:27:20 #> 290 6 Frederick the Great 2023-07-10 12:36:06 #> 291 6 Frederick the Great 2023-07-10 12:37:54 #> 292 6 Frederick the Great 2023-07-10 12:58:10 #> 293 6 Frederick the Great 2023-07-10 13:05:41 #> 294 6 Frederick the Great 2023-07-10 13:06:43 #> 295 6 Frederick the Great 2023-07-10 18:02:11 #> 296 6 Frederick the Great 2023-07-10 18:08:22 #> 297 6 Frederick the Great 2023-07-10 18:18:04 #> 298 6 Frederick the Great 2023-07-12 12:36:05 #> 299 6 Frederick the Great 2023-07-12 12:39:26 #> 300 6 Frederick the Great 2023-07-12 12:41:55 #> 301 6 Frederick the Great 2023-07-12 12:42:13 #> 302 6 Frederick the Great 2023-07-12 12:42:53 #> 303 6 Frederick the Great 2023-07-12 12:46:35 #> 304 6 Frederick the Great 2023-07-12 18:18:16 #> 305 6 Frederick the Great 2023-07-12 18:25:46 #> 306 6 Frederick the Great 2023-07-12 18:31:02 #> 307 6 Frederick the Great 2023-07-12 22:29:25 #> 308 6 Frederick the Great 2023-07-12 22:36:56 #> 309 6 Frederick the Great 2023-07-13 10:32:56 #> 310 6 Frederick the Great 2023-07-13 10:39:37 #> 311 6 Frederick the Great 2023-07-13 10:45:42 #> 312 6 Frederick the Great 2023-07-13 13:45:26 #> 313 6 Frederick the Great 2023-07-13 13:53:45 #> 314 6 Frederick the Great 2023-07-13 14:01:53 #> 315 6 Frederick the Great 2023-07-21 17:25:24 #> 316 6 Frederick the Great 2023-07-21 17:37:09 #> 317 6 Frederick the Great 2023-07-23 19:32:35 #> 318 6 Frederick the Great 2023-07-23 19:33:26 #> 319 6 Frederick the Great 2023-07-23 19:41:04 #> 320 6 Frederick the Great 2023-07-25 14:26:49 #> 321 6 Frederick the Great 2023-07-25 14:34:39 #> 322 6 Frederick the Great 2023-07-25 14:41:55 #> 323 6 Frederick the Great 2023-07-27 20:38:15 #> 324 6 Frederick the Great 2023-07-27 20:45:23 #> 325 6 Frederick the Great 2023-07-27 20:53:01 #> 326 6 Frederick the Great 2023-08-02 06:13:53 #> 327 6 Frederick the Great 2023-08-02 06:21:37 #> 328 6 Frederick the Great 2023-08-02 06:25:45 #> 329 6 Frederick the Great 2023-08-19 04:44:30 #> 330 6 Frederick the Great 2023-08-23 02:19:20 #> 331 6 Frederick the Great 2023-08-23 02:33:07 #> 332 6 Frederick the Great 2023-08-23 11:49:50 #> 333 6 Frederick the Great 2023-08-23 11:58:10 #> 334 6 Frederick the Great 2023-08-23 11:58:29 #> 335 6 Frederick the Great 2023-08-25 03:33:51 #> 336 6 Frederick the Great 2023-08-25 04:07:05 #> 337 6 Frederick the Great 2023-08-25 07:14:59 #> 338 6 Frederick the Great 2023-08-26 00:46:31 #> 339 6 Frederick the Great 2023-08-26 00:52:49 #> 340 6 Frederick the Great 2023-08-26 01:05:23 #> 341 6 Frederick the Great 2023-08-26 01:22:54 #> 342 6 Frederick the Great 2023-08-26 01:29:17 #> 343 6 Frederick the Great 2023-08-26 01:38:58 #> 344 6 Frederick the Great 2023-08-26 11:37:47 #> 345 6 Frederick the Great 2023-08-26 12:09:11 #> 346 6 Frederick the Great 2023-08-26 15:08:50 #> 347 6 Frederick the Great 2023-08-26 15:15:17 #> 348 6 Frederick the Great 2023-08-26 15:21:32 #> 349 6 Frederick the Great 2023-08-26 16:19:18 #> 350 6 Frederick the Great 2023-08-26 16:25:57 #> 351 6 Frederick the Great 2023-08-26 16:26:47 #> 352 6 Frederick the Great 2023-08-28 09:39:38 #> 353 6 Frederick the Great 2023-08-28 09:53:53 #> 354 6 Frederick the Great 2023-08-28 09:58:49 #> 355 6 Frederick the Great 2023-08-28 10:00:20 #> 356 6 Frederick the Great 2023-08-28 10:18:13 #> 357 6 Frederick the Great 2023-08-28 10:18:41 #> 358 6 Frederick the Great 2023-08-28 12:08:57 #> 359 6 Frederick the Great 2023-08-28 12:30:24 #> 360 6 Frederick the Great 2023-08-28 15:09:51 #> 361 6 Frederick the Great 2023-08-28 15:16:52 #> 362 6 Frederick the Great 2023-08-28 15:27:17 #> 363 6 Frederick the Great 2023-08-28 15:45:48 #> 364 6 Frederick the Great 2023-08-28 15:52:12 #> 365 6 Frederick the Great 2023-08-28 15:55:46 #> 366 6 Frederick the Great 2023-08-28 17:38:53 #> 367 6 Frederick the Great 2023-08-28 17:46:14 #> 368 6 Frederick the Great 2023-08-28 18:08:06 #> 369 6 Frederick the Great 2023-08-28 18:20:26 #> 370 6 Frederick the Great 2023-08-28 18:24:10 #> 371 6 Frederick the Great 2023-08-28 18:25:03 #> 372 6 Frederick the Great 2023-08-28 18:29:33 #> 373 6 Frederick the Great 2023-08-28 18:45:46 #> 374 6 Frederick the Great 2023-08-28 19:33:41 #> 375 6 Frederick the Great 2023-08-28 21:53:16 #> 376 6 Frederick the Great 2023-08-28 22:12:50 #> 377 6 Frederick the Great 2023-08-28 22:22:43 #> 378 6 Frederick the Great 2023-08-28 22:48:21 #> 379 6 Frederick the Great 2023-08-28 23:04:52 #> 380 6 Frederick the Great 2023-08-29 00:20:25 #> 381 6 Frederick the Great 2023-08-29 00:37:40 #> 382 6 Frederick the Great 2023-08-29 00:40:34 #> 383 6 Frederick the Great 2023-08-31 08:33:33 #> 384 6 Frederick the Great 2023-08-31 08:43:27 #> 385 6 Frederick the Great 2023-08-31 08:49:49 #> 386 6 Frederick the Great 2023-09-04 19:48:39 #> 387 6 Frederick the Great 2023-09-04 19:54:44 #> 388 6 Frederick the Great 2023-09-04 20:10:15 #> 389 6 Frederick the Great 2023-09-04 21:30:05 #> 390 6 Frederick the Great 2023-09-04 21:37:46 #> 391 6 Frederick the Great 2023-09-04 21:47:49 #> 392 6 Frederick the Great 2023-09-05 00:10:15 #> 393 6 Frederick the Great 2023-09-05 00:14:07 #> 394 6 Frederick the Great 2023-09-05 00:35:09 #> 395 6 Frederick the Great 2023-09-08 13:29:11 #> 396 6 Frederick the Great 2023-09-08 13:45:11 #> 397 6 Frederick the Great 2023-09-08 13:45:40 #> 398 6 Frederick the Great 2023-09-09 10:55:29 #> 399 6 Frederick the Great 2023-09-09 11:14:17 #> 400 6 Frederick the Great 2023-09-09 11:20:13 #> 401 6 Frederick the Great 2023-09-09 12:58:11 #> 402 6 Frederick the Great 2023-09-09 13:14:28 #> 403 6 Frederick the Great 2023-09-09 13:25:26 #> 404 6 Frederick the Great 2023-09-22 11:35:42 #> 405 6 Frederick the Great 2023-09-22 11:58:52 #> 406 6 Frederick the Great 2023-09-22 12:05:58 #> 407 6 Frederick the Great 2023-09-22 14:38:44 #> 408 6 Frederick the Great 2023-09-22 14:54:22 #> 409 6 Frederick the Great 2023-10-04 15:38:45 #> 410 6 Frederick the Great 2023-10-04 15:44:55 #> 411 6 Frederick the Great 2023-10-04 16:00:19 #> 412 6 Frederick the Great 2023-10-08 15:32:39 #> 413 6 Frederick the Great 2023-10-08 15:43:09 #> 414 6 Frederick the Great 2023-10-08 15:49:14 #> 415 6 Frederick the Great 2023-10-12 23:34:35 #> 416 6 Frederick the Great 2023-10-12 23:44:48 #> 417 6 Frederick the Great 2023-10-13 00:10:51 #> 418 6 Frederick the Great 2023-10-16 07:03:26 #> 419 6 Frederick the Great 2023-10-16 07:08:28 #> 420 6 Frederick the Great 2023-10-19 21:22:40 #> 421 6 Frederick the Great 2023-10-19 21:34:50 #> 422 6 Frederick the Great 2023-10-19 22:02:52 #> 423 6 Frederick the Great 2023-10-21 11:25:24 #> 424 6 Frederick the Great 2023-10-21 11:28:23 #> 425 6 Frederick the Great 2023-10-31 15:18:50 #> 426 6 Frederick the Great 2023-10-31 15:24:52 #> 427 6 Frederick the Great 2023-10-31 17:17:50 #> 428 6 Frederick the Great 2023-10-31 17:26:10 #> 429 6 Frederick the Great 2023-10-31 17:40:01 #> 430 6 Frederick the Great 2023-11-14 12:08:55 #> 431 6 Frederick the Great 2023-11-14 12:20:34 #> 432 6 Frederick the Great 2023-11-14 12:45:11 #> 433 6 Frederick the Great 2023-12-04 23:43:33 #> 434 6 Frederick the Great 2023-12-04 23:50:28 #> 435 6 Frederick the Great 2023-12-05 00:08:44 #> 436 6 Frederick the Great 2023-12-05 05:38:51 #> 437 6 Frederick the Great 2023-12-05 08:50:02 #> 438 6 Frederick the Great 2023-12-05 08:50:42 #> 439 6 Frederick the Great 2023-12-05 09:18:33 #> 440 6 Frederick the Great 2023-12-05 14:28:43 #> 441 6 Frederick the Great 2023-12-05 14:43:20 #> 442 6 Frederick the Great 2023-12-05 14:44:45 #> 443 6 Frederick the Great 2023-12-27 09:08:20 #> 444 6 Frederick the Great 2023-12-27 15:32:22 #> 445 6 Frederick the Great 2023-12-27 15:50:03 #> 446 6 Frederick the Great 2023-12-27 16:04:07 #> 447 6 Frederick the Great 2023-12-27 16:05:20 #> 448 6 Frederick the Great 2023-12-27 16:47:40 #> 449 6 Frederick the Great 2023-12-27 17:14:31 #> 450 6 Frederick the Great 2023-12-27 18:49:23 #> 451 6 Frederick the Great 2023-12-27 18:59:53 #> 452 6 Frederick the Great 2023-12-27 19:05:27 #> 453 6 Frederick the Great 2023-12-27 20:09:49 #> 454 6 Frederick the Great 2023-12-27 20:35:02 #> 455 6 Frederick the Great 2023-12-27 23:29:51 #> 456 6 Frederick the Great 2023-12-27 23:43:07 #> 457 6 Frederick the Great 2023-12-27 23:48:17 #> 458 6 Frederick the Great 2023-12-28 00:29:37 #> 459 6 Frederick the Great 2023-12-28 00:42:07 #> 460 6 Frederick the Great 2023-12-28 00:43:28 #> 461 6 Frederick the Great 2023-12-28 12:20:04 #> 462 6 Frederick the Great 2023-12-28 12:24:08 #> 463 6 Frederick the Great 2023-12-28 12:45:17 #> 464 6 Frederick the Great 2024-01-15 17:54:42 #> 465 6 Frederick the Great 2024-01-15 18:10:30 #> 466 6 Frederick the Great 2024-01-16 10:08:59 #> 467 6 Frederick the Great 2024-01-17 15:53:35 #> 468 6 Frederick the Great 2024-01-17 16:25:50 #> 469 6 Frederick the Great 2024-01-17 22:58:48 #> 470 6 Frederick the Great 2024-01-17 23:09:06 #> 471 6 Frederick the Great 2024-01-17 23:13:55 #> 472 6 Frederick the Great 2024-01-18 00:19:09 #> 473 6 Frederick the Great 2024-01-18 00:25:17 #> 474 6 Frederick the Great 2024-01-18 00:42:53 #> 475 6 Frederick the Great 2024-01-25 23:15:13 #> 476 6 Frederick the Great 2024-01-26 09:22:02 #> 477 6 Frederick the Great 2024-01-26 09:33:24 #> 478 6 Frederick the Great 2024-01-26 21:56:28 #> 479 6 Frederick the Great 2024-01-26 22:00:24 #> 480 6 Frederick the Great 2024-01-26 22:25:58 #> date_wminute user camid #> 1 2022-01-12 09:30:00 8adf4f5dd661449fa6cc1f5a0b1815c0@auth.local 100001 #> 2 2022-01-03 07:56:00 c7efb8019da54923a9b04d4a74f0fde8@auth.local 100002 #> 3 2021-08-05 08:30:00 c7efb8019da54923a9b04d4a74f0fde8@auth.local 100003 #> 4 NaN 100189 #> 5 NaN 100190 #> 6 NaN 100191 #> 7 NaN 100192 #> 8 NaN 100193 #> 9 NaN 100194 #> 10 NaN 100195 #> 11 NaN 100196 #> 12 NaN 100197 #> 13 NaN 100198 #> 14 NaN 100199 #> 15 NaN 100200 #> 16 NaN 100201 #> 17 NaN 100202 #> 18 NaN 100203 #> 19 NaN 100204 #> 20 NaN 100205 #> 21 NaN 100206 #> 22 NaN 100207 #> 23 NaN 100208 #> 24 NaN 100209 #> 25 NaN 100210 #> 26 NaN 100211 #> 27 NaN 100212 #> 28 NaN 100213 #> 29 NaN 100214 #> 30 NaN 100215 #> 31 NaN 100216 #> 32 NaN 100217 #> 33 NaN 100218 #> 34 NaN 100219 #> 35 NaN 100220 #> 36 NaN 100221 #> 37 NaN 100222 #> 38 NaN 100223 #> 39 NaN 100224 #> 40 NaN 100225 #> 41 NaN 100226 #> 42 NaN 100227 #> 43 NaN 100228 #> 44 NaN 100229 #> 45 NaN 100230 #> 46 NaN 100231 #> 47 NaN 100232 #> 48 NaN 100233 #> 49 NaN 100234 #> 50 NaN 100235 #> 51 NaN 100236 #> 52 NaN 100237 #> 53 NaN 100238 #> 54 NaN 100239 #> 55 NaN 100240 #> 56 NaN 100241 #> 57 NaN 100242 #> 58 NaN 100243 #> 59 NaN 100244 #> 60 NaN 100245 #> 61 NaN 100246 #> 62 NaN 100247 #> 63 NaN 100248 #> 64 NaN 100249 #> 65 NaN 100250 #> 66 NaN 100251 #> 67 NaN 100252 #> 68 NaN 100253 #> 69 NaN 100254 #> 70 NaN 100255 #> 71 NaN 100256 #> 72 NaN 100257 #> 73 NaN 100258 #> 74 NaN 100259 #> 75 NaN 100260 #> 76 NaN 100261 #> 77 NaN 100262 #> 78 NaN 100263 #> 79 NaN 100264 #> 80 NaN 100265 #> 81 NaN 100266 #> 82 NaN 100267 #> 83 NaN 100268 #> 84 NaN 100269 #> 85 NaN 100270 #> 86 NaN 100271 #> 87 NaN 100272 #> 88 NaN 100273 #> 89 NaN 100274 #> 90 NaN 100275 #> 91 NaN 100276 #> 92 NaN 100277 #> 93 NaN 100278 #> 94 NaN 100279 #> 95 NaN 100280 #> 96 NaN 100281 #> 97 NaN 100282 #> 98 NaN 100283 #> 99 NaN 100284 #> 100 NaN 100285 #> 101 NaN 100286 #> 102 NaN 100287 #> 103 NaN 100288 #> 104 NaN 100289 #> 105 NaN 100290 #> 106 NaN 100291 #> 107 NaN 100292 #> 108 NaN 100293 #> 109 NaN 100294 #> 110 NaN 100295 #> 111 NaN 100296 #> 112 NaN 100297 #> 113 NaN 100298 #> 114 NaN 100299 #> 115 NaN 100300 #> 116 NaN 100301 #> 117 NaN 100302 #> 118 NaN 100303 #> 119 NaN 100304 #> 120 NaN 100305 #> 121 NaN 100306 #> 122 NaN 100307 #> 123 NaN 100308 #> 124 NaN 100309 #> 125 NaN 100310 #> 126 NaN 100311 #> 127 NaN 100312 #> 128 NaN 100313 #> 129 NaN 100314 #> 130 NaN 100315 #> 131 NaN 100316 #> 132 NaN 100317 #> 133 NaN 100318 #> 134 NaN 100319 #> 135 NaN 100320 #> 136 NaN 100321 #> 137 NaN 100322 #> 138 NaN 100323 #> 139 NaN 100324 #> 140 NaN 100325 #> 141 NaN 100326 #> 142 NaN 100327 #> 143 NaN 100328 #> 144 NaN 100329 #> 145 NaN 100330 #> 146 NaN 100331 #> 147 NaN 100332 #> 148 NaN 100333 #> 149 NaN 100334 #> 150 NaN 100335 #> 151 NaN 100336 #> 152 NaN 100337 #> 153 NaN 100338 #> 154 NaN 100339 #> 155 NaN 100340 #> 156 NaN 100341 #> 157 NaN 100342 #> 158 NaN 100343 #> 159 NaN 100344 #> 160 NaN 100345 #> 161 NaN 100346 #> 162 NaN 100347 #> 163 NaN 100348 #> 164 NaN 100349 #> 165 NaN 100350 #> 166 NaN 100351 #> 167 NaN 100352 #> 168 NaN 100353 #> 169 NaN 100354 #> 170 NaN 100355 #> 171 NaN 100356 #> 172 NaN 100357 #> 173 NaN 100358 #> 174 NaN 100359 #> 175 NaN 100360 #> 176 NaN 100361 #> 177 NaN 100362 #> 178 NaN 100363 #> 179 NaN 100364 #> 180 NaN 100365 #> 181 NaN 100366 #> 182 NaN 100367 #> 183 NaN 100368 #> 184 NaN 100369 #> 185 NaN 100370 #> 186 NaN 100371 #> 187 NaN 100372 #> 188 NaN 100373 #> 189 NaN 100374 #> 190 NaN 100375 #> 191 NaN 100376 #> 192 NaN 100377 #> 193 NaN 100378 #> 194 NaN 100379 #> 195 NaN 100380 #> 196 NaN 100381 #> 197 NaN 100382 #> 198 NaN 100383 #> 199 NaN 100384 #> 200 NaN 100385 #> 201 NaN 100386 #> 202 NaN 100387 #> 203 NaN 100388 #> 204 NaN 100389 #> 205 NaN 100390 #> 206 NaN 100391 #> 207 NaN 100392 #> 208 NaN 100393 #> 209 NaN 100394 #> 210 NaN 100395 #> 211 NaN 100396 #> 212 NaN 100397 #> 213 NaN 100398 #> 214 NaN 100399 #> 215 NaN 100400 #> 216 NaN 100401 #> 217 NaN 100402 #> 218 NaN 100403 #> 219 NaN 100404 #> 220 NaN 100405 #> 221 NaN 100406 #> 222 NaN 100407 #> 223 NaN 100408 #> 224 NaN 100409 #> 225 NaN 100410 #> 226 NaN 100411 #> 227 NaN 100412 #> 228 NaN 100413 #> 229 NaN 100414 #> 230 NaN 100415 #> 231 NaN 100416 #> 232 NaN 100417 #> 233 NaN 100418 #> 234 NaN 100419 #> 235 NaN 100420 #> 236 NaN 100421 #> 237 NaN 100422 #> 238 NaN 100423 #> 239 NaN 100424 #> 240 NaN 100425 #> 241 NaN 100426 #> 242 NaN 100427 #> 243 NaN 100428 #> 244 NaN 100429 #> 245 NaN 100430 #> 246 NaN 100431 #> 247 NaN 100432 #> 248 NaN 100433 #> 249 NaN 100434 #> 250 NaN 100435 #> 251 NaN 100436 #> 252 NaN 100437 #> 253 NaN 100438 #> 254 NaN 100439 #> 255 NaN 100440 #> 256 NaN 100441 #> 257 NaN 100442 #> 258 NaN 100443 #> 259 NaN 100444 #> 260 NaN 100445 #> 261 NaN 100446 #> 262 NaN 100447 #> 263 NaN 100448 #> 264 NaN 100449 #> 265 NaN 100450 #> 266 NaN 100451 #> 267 NaN 100452 #> 268 NaN 100453 #> 269 NaN 100454 #> 270 NaN 100455 #> 271 NaN 100456 #> 272 NaN 100457 #> 273 NaN 100458 #> 274 NaN 100459 #> 275 NaN 100460 #> 276 NaN 100461 #> 277 NaN 100462 #> 278 NaN 100463 #> 279 NaN 100464 #> 280 NaN 100465 #> 281 NaN 100466 #> 282 NaN 100467 #> 283 NaN 100468 #> 284 NaN 100469 #> 285 NaN 100470 #> 286 NaN 100471 #> 287 NaN 100472 #> 288 NaN 100473 #> 289 NaN 100474 #> 290 NaN 100475 #> 291 NaN 100476 #> 292 NaN 100477 #> 293 NaN 100478 #> 294 NaN 100479 #> 295 NaN 100480 #> 296 NaN 100481 #> 297 NaN 100482 #> 298 NaN 100483 #> 299 NaN 100484 #> 300 NaN 100485 #> 301 NaN 100486 #> 302 NaN 100487 #> 303 NaN 100488 #> 304 NaN 100489 #> 305 NaN 100490 #> 306 NaN 100491 #> 307 NaN 100492 #> 308 NaN 100493 #> 309 NaN 100494 #> 310 NaN 100495 #> 311 NaN 100496 #> 312 NaN 100497 #> 313 NaN 100498 #> 314 NaN 100499 #> 315 NaN 100500 #> 316 NaN 100501 #> 317 NaN 100502 #> 318 NaN 100503 #> 319 NaN 100504 #> 320 NaN 100505 #> 321 NaN 100506 #> 322 NaN 100507 #> 323 NaN 100508 #> 324 NaN 100509 #> 325 NaN 100510 #> 326 NaN 100511 #> 327 NaN 100512 #> 328 NaN 100513 #> 329 NaN 100514 #> 330 NaN 100515 #> 331 NaN 100516 #> 332 NaN 100517 #> 333 NaN 100518 #> 334 NaN 100519 #> 335 NaN 100520 #> 336 NaN 100521 #> 337 NaN 100522 #> 338 NaN 100523 #> 339 NaN 100524 #> 340 NaN 100525 #> 341 NaN 100526 #> 342 NaN 100527 #> 343 NaN 100528 #> 344 NaN 100529 #> 345 NaN 100530 #> 346 NaN 100531 #> 347 NaN 100532 #> 348 NaN 100533 #> 349 NaN 100534 #> 350 NaN 100535 #> 351 NaN 100536 #> 352 NaN 100537 #> 353 NaN 100538 #> 354 NaN 100539 #> 355 NaN 100540 #> 356 NaN 100541 #> 357 NaN 100542 #> 358 NaN 100543 #> 359 NaN 100544 #> 360 NaN 100545 #> 361 NaN 100546 #> 362 NaN 100547 #> 363 NaN 100548 #> 364 NaN 100549 #> 365 NaN 100550 #> 366 NaN 100551 #> 367 NaN 100552 #> 368 NaN 100553 #> 369 NaN 100554 #> 370 NaN 100555 #> 371 NaN 100556 #> 372 NaN 100557 #> 373 NaN 100558 #> 374 NaN 100559 #> 375 NaN 100560 #> 376 NaN 100561 #> 377 NaN 100562 #> 378 NaN 100563 #> 379 NaN 100564 #> 380 NaN 100565 #> 381 NaN 100566 #> 382 NaN 100567 #> 383 NaN 100568 #> 384 NaN 100569 #> 385 NaN 100570 #> 386 NaN 100571 #> 387 NaN 100572 #> 388 NaN 100573 #> 389 NaN 100574 #> 390 NaN 100575 #> 391 NaN 100576 #> 392 NaN 100577 #> 393 NaN 100578 #> 394 NaN 100579 #> 395 NaN 100580 #> 396 NaN 100581 #> 397 NaN 100582 #> 398 NaN 100583 #> 399 NaN 100584 #> 400 NaN 100585 #> 401 NaN 100586 #> 402 NaN 100587 #> 403 NaN 100588 #> 404 NaN 100589 #> 405 NaN 100590 #> 406 NaN 100591 #> 407 NaN 100592 #> 408 NaN 100593 #> 409 NaN 100594 #> 410 NaN 100595 #> 411 NaN 100596 #> 412 NaN 100597 #> 413 NaN 100598 #> 414 NaN 100599 #> 415 NaN 100600 #> 416 NaN 100601 #> 417 NaN 100602 #> 418 NaN 100603 #> 419 NaN 100604 #> 420 NaN 100605 #> 421 NaN 100606 #> 422 NaN 100607 #> 423 NaN 100608 #> 424 NaN 100609 #> 425 NaN 100610 #> 426 NaN 100611 #> 427 NaN 100612 #> 428 NaN 100613 #> 429 NaN 100614 #> 430 NaN 100615 #> 431 NaN 100616 #> 432 NaN 100617 #> 433 NaN 100618 #> 434 NaN 100619 #> 435 NaN 100620 #> 436 NaN 100621 #> 437 NaN 100622 #> 438 NaN 100623 #> 439 NaN 100624 #> 440 NaN 100625 #> 441 NaN 100626 #> 442 NaN 100627 #> 443 NaN 100628 #> 444 NaN 100629 #> 445 NaN 100630 #> 446 NaN 100631 #> 447 NaN 100632 #> 448 NaN 100633 #> 449 NaN 100634 #> 450 NaN 100635 #> 451 NaN 100636 #> 452 NaN 100637 #> 453 NaN 100638 #> 454 NaN 100639 #> 455 NaN 100640 #> 456 NaN 100641 #> 457 NaN 100642 #> 458 NaN 100643 #> 459 NaN 100644 #> 460 NaN 100645 #> 461 NaN 100646 #> 462 NaN 100647 #> 463 NaN 100648 #> 464 NaN 100649 #> 465 NaN 100650 #> 466 NaN 100651 #> 467 NaN 100652 #> 468 NaN 100653 #> 469 NaN 100654 #> 470 NaN 100655 #> 471 NaN 100656 #> 472 NaN 100657 #> 473 NaN 100658 #> 474 NaN 100659 #> 475 NaN 100660 #> 476 NaN 100661 #> 477 NaN 100662 #> 478 NaN 100663 #> 479 NaN 100664 #> 480 NaN 100665 # } # \\donttest{ flytable_query(\"SELECT person, fruit_name FROM testfruit WHERE person!='Bob'\") #> person fruit_name #> 1 Alice apple #> 2 Clara clementine #> 3 Frederick the Great kiwi #> 4 Frederick the Great kiwi #> 5 Frederick the Great kiwi #> 6 Frederick the Great kiwi #> 7 Frederick the Great kiwi #> 8 Frederick the Great kiwi #> 9 Frederick the Great kiwi #> 10 Frederick the Great kiwi #> 11 Frederick the Great kiwi #> 12 Frederick the Great kiwi #> 13 Frederick the Great kiwi #> 14 Frederick the Great kiwi #> 15 Frederick the Great kiwi #> 16 Frederick the Great kiwi #> 17 Frederick the Great kiwi #> 18 Frederick the Great kiwi #> 19 Frederick the Great kiwi #> 20 Frederick the Great kiwi #> 21 Frederick the Great kiwi #> 22 Frederick the Great kiwi #> 23 Frederick the Great kiwi #> 24 Frederick the Great kiwi #> 25 Frederick the Great kiwi #> 26 Frederick the Great kiwi #> 27 Frederick the Great kiwi #> 28 Frederick the Great kiwi #> 29 Frederick the Great kiwi #> 30 Frederick the Great kiwi #> 31 Frederick the Great kiwi #> 32 Frederick the Great kiwi #> 33 Frederick the Great kiwi #> 34 Frederick the Great kiwi #> 35 Frederick the Great kiwi #> 36 Frederick the Great kiwi #> 37 Frederick the Great kiwi #> 38 Frederick the Great kiwi #> 39 Frederick the Great kiwi #> 40 Frederick the Great kiwi #> 41 Frederick the Great kiwi #> 42 Frederick the Great kiwi #> 43 Frederick the Great kiwi #> 44 Frederick the Great kiwi #> 45 Frederick the Great kiwi #> 46 Frederick the Great kiwi #> 47 Frederick the Great kiwi #> 48 Frederick the Great kiwi #> 49 Frederick the Great kiwi #> 50 Frederick the Great kiwi #> 51 Frederick the Great kiwi #> 52 Frederick the Great kiwi #> 53 Frederick the Great kiwi #> 54 Frederick the Great kiwi #> 55 Frederick the Great kiwi #> 56 Frederick the Great kiwi #> 57 Frederick the Great kiwi #> 58 Frederick the Great kiwi #> 59 Frederick the Great kiwi #> 60 Frederick the Great kiwi #> 61 Frederick the Great kiwi #> 62 Frederick the Great kiwi #> 63 Frederick the Great kiwi #> 64 Frederick the Great kiwi #> 65 Frederick the Great kiwi #> 66 Frederick the Great kiwi #> 67 Frederick the Great kiwi #> 68 Frederick the Great kiwi #> 69 Frederick the Great kiwi #> 70 Frederick the Great kiwi #> 71 Frederick the Great kiwi #> 72 Frederick the Great kiwi #> 73 Frederick the Great kiwi #> 74 Frederick the Great kiwi #> 75 Frederick the Great kiwi #> 76 Frederick the Great kiwi #> 77 Frederick the Great kiwi #> 78 Frederick the Great kiwi #> 79 Frederick the Great kiwi #> 80 Frederick the Great kiwi #> 81 Frederick the Great kiwi #> 82 Frederick the Great kiwi #> 83 Frederick the Great kiwi #> 84 Frederick the Great kiwi #> 85 Frederick the Great kiwi #> 86 Frederick the Great kiwi #> 87 Frederick the Great kiwi #> 88 Frederick the Great kiwi #> 89 Frederick the Great kiwi #> 90 Frederick the Great kiwi #> 91 Frederick the Great kiwi #> 92 Frederick the Great kiwi #> 93 Frederick the Great kiwi #> 94 Frederick the Great kiwi #> 95 Frederick the Great kiwi #> 96 Frederick the Great kiwi #> 97 Frederick the Great kiwi #> 98 Frederick the Great kiwi #> 99 Frederick the Great kiwi #> 100 Frederick the Great kiwi #> 101 Frederick the Great kiwi #> 102 Frederick the Great kiwi #> 103 Frederick the Great kiwi #> 104 Frederick the Great kiwi #> 105 Frederick the Great kiwi #> 106 Frederick the Great kiwi #> 107 Frederick the Great kiwi #> 108 Frederick the Great kiwi #> 109 Frederick the Great kiwi #> 110 Frederick the Great kiwi #> 111 Frederick the Great kiwi #> 112 Frederick the Great kiwi #> 113 Frederick the Great kiwi #> 114 Frederick the Great kiwi #> 115 Frederick the Great kiwi #> 116 Frederick the Great kiwi #> 117 Frederick the Great kiwi #> 118 Frederick the Great kiwi #> 119 Frederick the Great kiwi #> 120 Frederick the Great kiwi #> 121 Frederick the Great kiwi #> 122 Frederick the Great kiwi #> 123 Frederick the Great kiwi #> 124 Frederick the Great kiwi #> 125 Frederick the Great kiwi #> 126 Frederick the Great kiwi #> 127 Frederick the Great kiwi #> 128 Frederick the Great kiwi #> 129 Frederick the Great kiwi #> 130 Frederick the Great kiwi #> 131 Frederick the Great kiwi #> 132 Frederick the Great kiwi #> 133 Frederick the Great kiwi #> 134 Frederick the Great kiwi #> 135 Frederick the Great kiwi #> 136 Frederick the Great kiwi #> 137 Frederick the Great kiwi #> 138 Frederick the Great kiwi #> 139 Frederick the Great kiwi #> 140 Frederick the Great kiwi #> 141 Frederick the Great kiwi #> 142 Frederick the Great kiwi #> 143 Frederick the Great kiwi #> 144 Frederick the Great kiwi #> 145 Frederick the Great kiwi #> 146 Frederick the Great kiwi #> 147 Frederick the Great kiwi #> 148 Frederick the Great kiwi #> 149 Frederick the Great kiwi #> 150 Frederick the Great kiwi #> 151 Frederick the Great kiwi #> 152 Frederick the Great kiwi #> 153 Frederick the Great kiwi #> 154 Frederick the Great kiwi #> 155 Frederick the Great kiwi #> 156 Frederick the Great kiwi #> 157 Frederick the Great kiwi #> 158 Frederick the Great kiwi #> 159 Frederick the Great kiwi #> 160 Frederick the Great kiwi #> 161 Frederick the Great kiwi #> 162 Frederick the Great kiwi #> 163 Frederick the Great kiwi #> 164 Frederick the Great kiwi #> 165 Frederick the Great kiwi #> 166 Frederick the Great kiwi #> 167 Frederick the Great kiwi #> 168 Frederick the Great kiwi #> 169 Frederick the Great kiwi #> 170 Frederick the Great kiwi #> 171 Frederick the Great kiwi #> 172 Frederick the Great kiwi #> 173 Frederick the Great kiwi #> 174 Frederick the Great kiwi #> 175 Frederick the Great kiwi #> 176 Frederick the Great kiwi #> 177 Frederick the Great kiwi #> 178 Frederick the Great kiwi #> 179 Frederick the Great kiwi #> 180 Frederick the Great kiwi #> 181 Frederick the Great kiwi #> 182 Frederick the Great kiwi #> 183 Frederick the Great kiwi #> 184 Frederick the Great kiwi #> 185 Frederick the Great kiwi #> 186 Frederick the Great kiwi #> 187 Frederick the Great kiwi #> 188 Frederick the Great kiwi #> 189 Frederick the Great kiwi #> 190 Frederick the Great kiwi #> 191 Frederick the Great kiwi #> 192 Frederick the Great kiwi #> 193 Frederick the Great kiwi #> 194 Frederick the Great kiwi #> 195 Frederick the Great kiwi #> 196 Frederick the Great kiwi #> 197 Frederick the Great kiwi #> 198 Frederick the Great kiwi #> 199 Frederick the Great kiwi #> 200 Frederick the Great kiwi #> 201 Frederick the Great kiwi #> 202 Frederick the Great kiwi #> 203 Frederick the Great kiwi #> 204 Frederick the Great kiwi #> 205 Frederick the Great kiwi #> 206 Frederick the Great kiwi #> 207 Frederick the Great kiwi #> 208 Frederick the Great kiwi #> 209 Frederick the Great kiwi #> 210 Frederick the Great kiwi #> 211 Frederick the Great kiwi #> 212 Frederick the Great kiwi #> 213 Frederick the Great kiwi #> 214 Frederick the Great kiwi #> 215 Frederick the Great kiwi #> 216 Frederick the Great kiwi #> 217 Frederick the Great kiwi #> 218 Frederick the Great kiwi #> 219 Frederick the Great kiwi #> 220 Frederick the Great kiwi #> 221 Frederick the Great kiwi #> 222 Frederick the Great kiwi #> 223 Frederick the Great kiwi #> 224 Frederick the Great kiwi #> 225 Frederick the Great kiwi #> 226 Frederick the Great kiwi #> 227 Frederick the Great kiwi #> 228 Frederick the Great kiwi #> 229 Frederick the Great kiwi #> 230 Frederick the Great kiwi #> 231 Frederick the Great kiwi #> 232 Frederick the Great kiwi #> 233 Frederick the Great kiwi #> 234 Frederick the Great kiwi #> 235 Frederick the Great kiwi #> 236 Frederick the Great kiwi #> 237 Frederick the Great kiwi #> 238 Frederick the Great kiwi #> 239 Frederick the Great kiwi #> 240 Frederick the Great kiwi #> 241 Frederick the Great kiwi #> 242 Frederick the Great kiwi #> 243 Frederick the Great kiwi #> 244 Frederick the Great kiwi #> 245 Frederick the Great kiwi #> 246 Frederick the Great kiwi #> 247 Frederick the Great kiwi #> 248 Frederick the Great kiwi #> 249 Frederick the Great kiwi #> 250 Frederick the Great kiwi #> 251 Frederick the Great kiwi #> 252 Frederick the Great kiwi #> 253 Frederick the Great kiwi #> 254 Frederick the Great kiwi #> 255 Frederick the Great kiwi #> 256 Frederick the Great kiwi #> 257 Frederick the Great kiwi #> 258 Frederick the Great kiwi #> 259 Frederick the Great kiwi #> 260 Frederick the Great kiwi #> 261 Frederick the Great kiwi #> 262 Frederick the Great kiwi #> 263 Frederick the Great kiwi #> 264 Frederick the Great kiwi #> 265 Frederick the Great kiwi #> 266 Frederick the Great kiwi #> 267 Frederick the Great kiwi #> 268 Frederick the Great kiwi #> 269 Frederick the Great kiwi #> 270 Frederick the Great kiwi #> 271 Frederick the Great kiwi #> 272 Frederick the Great kiwi #> 273 Frederick the Great kiwi #> 274 Frederick the Great kiwi #> 275 Frederick the Great kiwi #> 276 Frederick the Great kiwi #> 277 Frederick the Great kiwi #> 278 Frederick the Great kiwi #> 279 Frederick the Great kiwi #> 280 Frederick the Great kiwi #> 281 Frederick the Great kiwi #> 282 Frederick the Great kiwi #> 283 Frederick the Great kiwi #> 284 Frederick the Great kiwi #> 285 Frederick the Great kiwi #> 286 Frederick the Great kiwi #> 287 Frederick the Great kiwi #> 288 Frederick the Great kiwi #> 289 Frederick the Great kiwi #> 290 Frederick the Great kiwi #> 291 Frederick the Great kiwi #> 292 Frederick the Great kiwi #> 293 Frederick the Great kiwi #> 294 Frederick the Great kiwi #> 295 Frederick the Great kiwi #> 296 Frederick the Great kiwi #> 297 Frederick the Great kiwi #> 298 Frederick the Great kiwi #> 299 Frederick the Great kiwi #> 300 Frederick the Great kiwi #> 301 Frederick the Great kiwi #> 302 Frederick the Great kiwi #> 303 Frederick the Great kiwi #> 304 Frederick the Great kiwi #> 305 Frederick the Great kiwi #> 306 Frederick the Great kiwi #> 307 Frederick the Great kiwi #> 308 Frederick the Great kiwi #> 309 Frederick the Great kiwi #> 310 Frederick the Great kiwi #> 311 Frederick the Great kiwi #> 312 Frederick the Great kiwi #> 313 Frederick the Great kiwi #> 314 Frederick the Great kiwi #> 315 Frederick the Great kiwi #> 316 Frederick the Great kiwi #> 317 Frederick the Great kiwi #> 318 Frederick the Great kiwi #> 319 Frederick the Great kiwi #> 320 Frederick the Great kiwi #> 321 Frederick the Great kiwi #> 322 Frederick the Great kiwi #> 323 Frederick the Great kiwi #> 324 Frederick the Great kiwi #> 325 Frederick the Great kiwi #> 326 Frederick the Great kiwi #> 327 Frederick the Great kiwi #> 328 Frederick the Great kiwi #> 329 Frederick the Great kiwi #> 330 Frederick the Great kiwi #> 331 Frederick the Great kiwi #> 332 Frederick the Great kiwi #> 333 Frederick the Great kiwi #> 334 Frederick the Great kiwi #> 335 Frederick the Great kiwi #> 336 Frederick the Great kiwi #> 337 Frederick the Great kiwi #> 338 Frederick the Great kiwi #> 339 Frederick the Great kiwi #> 340 Frederick the Great kiwi #> 341 Frederick the Great kiwi #> 342 Frederick the Great kiwi #> 343 Frederick the Great kiwi #> 344 Frederick the Great kiwi #> 345 Frederick the Great kiwi #> 346 Frederick the Great kiwi #> 347 Frederick the Great kiwi #> 348 Frederick the Great kiwi #> 349 Frederick the Great kiwi #> 350 Frederick the Great kiwi #> 351 Frederick the Great kiwi #> 352 Frederick the Great kiwi #> 353 Frederick the Great kiwi #> 354 Frederick the Great kiwi #> 355 Frederick the Great kiwi #> 356 Frederick the Great kiwi #> 357 Frederick the Great kiwi #> 358 Frederick the Great kiwi #> 359 Frederick the Great kiwi #> 360 Frederick the Great kiwi #> 361 Frederick the Great kiwi #> 362 Frederick the Great kiwi #> 363 Frederick the Great kiwi #> 364 Frederick the Great kiwi #> 365 Frederick the Great kiwi #> 366 Frederick the Great kiwi #> 367 Frederick the Great kiwi #> 368 Frederick the Great kiwi #> 369 Frederick the Great kiwi #> 370 Frederick the Great kiwi #> 371 Frederick the Great kiwi #> 372 Frederick the Great kiwi #> 373 Frederick the Great kiwi #> 374 Frederick the Great kiwi #> 375 Frederick the Great kiwi #> 376 Frederick the Great kiwi #> 377 Frederick the Great kiwi #> 378 Frederick the Great kiwi #> 379 Frederick the Great kiwi #> 380 Frederick the Great kiwi #> 381 Frederick the Great kiwi #> 382 Frederick the Great kiwi #> 383 Frederick the Great kiwi #> 384 Frederick the Great kiwi #> 385 Frederick the Great kiwi #> 386 Frederick the Great kiwi #> 387 Frederick the Great kiwi #> 388 Frederick the Great kiwi #> 389 Frederick the Great kiwi #> 390 Frederick the Great kiwi #> 391 Frederick the Great kiwi #> 392 Frederick the Great kiwi #> 393 Frederick the Great kiwi #> 394 Frederick the Great kiwi #> 395 Frederick the Great kiwi #> 396 Frederick the Great kiwi #> 397 Frederick the Great kiwi #> 398 Frederick the Great kiwi #> 399 Frederick the Great kiwi #> 400 Frederick the Great kiwi #> 401 Frederick the Great kiwi #> 402 Frederick the Great kiwi #> 403 Frederick the Great kiwi #> 404 Frederick the Great kiwi #> 405 Frederick the Great kiwi #> 406 Frederick the Great kiwi #> 407 Frederick the Great kiwi #> 408 Frederick the Great kiwi #> 409 Frederick the Great kiwi #> 410 Frederick the Great kiwi #> 411 Frederick the Great kiwi #> 412 Frederick the Great kiwi #> 413 Frederick the Great kiwi #> 414 Frederick the Great kiwi #> 415 Frederick the Great kiwi #> 416 Frederick the Great kiwi #> 417 Frederick the Great kiwi #> 418 Frederick the Great kiwi #> 419 Frederick the Great kiwi #> 420 Frederick the Great kiwi #> 421 Frederick the Great kiwi #> 422 Frederick the Great kiwi #> 423 Frederick the Great kiwi #> 424 Frederick the Great kiwi #> 425 Frederick the Great kiwi #> 426 Frederick the Great kiwi #> 427 Frederick the Great kiwi #> 428 Frederick the Great kiwi #> 429 Frederick the Great kiwi #> 430 Frederick the Great kiwi #> 431 Frederick the Great kiwi #> 432 Frederick the Great kiwi #> 433 Frederick the Great kiwi #> 434 Frederick the Great kiwi #> 435 Frederick the Great kiwi #> 436 Frederick the Great kiwi #> 437 Frederick the Great kiwi #> 438 Frederick the Great kiwi #> 439 Frederick the Great kiwi #> 440 Frederick the Great kiwi #> 441 Frederick the Great kiwi #> 442 Frederick the Great kiwi #> 443 Frederick the Great kiwi #> 444 Frederick the Great kiwi #> 445 Frederick the Great kiwi #> 446 Frederick the Great kiwi #> 447 Frederick the Great kiwi #> 448 Frederick the Great kiwi #> 449 Frederick the Great kiwi #> 450 Frederick the Great kiwi #> 451 Frederick the Great kiwi #> 452 Frederick the Great kiwi #> 453 Frederick the Great kiwi #> 454 Frederick the Great kiwi #> 455 Frederick the Great kiwi #> 456 Frederick the Great kiwi #> 457 Frederick the Great kiwi #> 458 Frederick the Great kiwi #> 459 Frederick the Great kiwi #> 460 Frederick the Great kiwi #> 461 Frederick the Great kiwi #> 462 Frederick the Great kiwi #> 463 Frederick the Great kiwi #> 464 Frederick the Great kiwi #> 465 Frederick the Great kiwi #> 466 Frederick the Great kiwi #> 467 Frederick the Great kiwi #> 468 Frederick the Great kiwi #> 469 Frederick the Great kiwi #> 470 Frederick the Great kiwi #> 471 Frederick the Great kiwi #> 472 Frederick the Great kiwi #> 473 Frederick the Great kiwi #> 474 Frederick the Great kiwi #> 475 Frederick the Great kiwi #> 476 Frederick the Great kiwi #> 477 Frederick the Great kiwi #> 478 Frederick the Great kiwi #> 479 Frederick the Great kiwi # } if (FALSE) { flytable_query(paste(\"SELECT root_id, supervoxel_id FROM info limit 5\")) }"},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"Fetch (memoised) flywire cell type information flytable","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"","code":"flytable_cell_types( pattern = NULL, version = NULL, timestamp = NULL, target = c(\"type\", \"cell_type\", \"hemibrain_type\", \"cell_class\", \"super_class\", \"ito_lee_hemilineage\", \"all\"), table = c(\"info\", \"optic\", \"both\"), transfer_hemibrain_type = c(\"extra\", \"none\", \"all\"), cache = TRUE, use_static = NA )"},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"pattern Optional character vector specifying pattern cell types must match SQL LIKE statement executed flytable_query. suffix _L _R can used restricted neurons annotated L R hemisphere. See examples. version optional CAVE materialisation version number. See flywire_cave_query details. Note also special signalling value TRUE implies latest locally available connectome dump. timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. target character vector specifying flytable columns pattern match. special value type means either cell_type hemibrain_type match. special value means match cell_type, hemibrain_type, cell_class. table cell type information tables use (info brain, optic optic lobes ). transfer_hemibrain_type Whether transfer hemibrain_type column cell_type (default TRUE, see details) cache Whether cache results 5m (default TRUE since flytable query little expensive) use_static Whether use static cell type information (Schlegel et al)","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"original data.frame left joined appropriate rows flytable.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"transfer_hemibrain_type=TRUE, hemibrain_type values transferred cell_type column cell_type empty. seems SQL LIKE searches (e.g. containing % symbol) work ito_lee_hemilineage column. can still search exact matches use full regular expression queries (operate downloading rows filtering machine). Static cell type information provided Schlegel et 2023. See flywire_annotations github repository. used default connection pre-release Cambridge flytable available specified options(fafbseg.use_static_celltypes=TRUE). Note presently one materialisation version (630) supported static data.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable_cell_types.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch (memoised) flywire cell type information from flytable — flytable_cell_types","text":"","code":"# \\donttest{ flytable_cell_types(\"MBON%\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940624185095 79448854932107696 left intrinsic central MBON #> 2 720575940623472716 80011942324010318 right intrinsic central MBON #> 3 720575940638526278 80715286101144676 right intrinsic central MBON #> 4 720575940629585602 81137979670302132 right intrinsic central MBON #> 5 720575940637934308 81349085835581377 right intrinsic central MBON #> 6 720575940632118343 78744342923662254 left intrinsic central MBON #> 7 720575940609959637 78603948898007978 left intrinsic central MBON #> 8 720575940638163428 78111986298788517 left intrinsic central MBON #> 9 720575940630496374 81349223341739625 right intrinsic central MBON #> 10 720575940642142861 78393323903110735 left intrinsic central MBON #> 11 720575940611344078 80223254782485510 right intrinsic central MBON #> 12 720575940634822751 81277549061520124 right intrinsic central MBON #> 13 720575940617552340 79588561627810154 right intrinsic central MBON #> 14 720575940624280328 81489685951698728 right intrinsic central MBON #> 15 720575940617567206 78180912067538056 left intrinsic central MBON #> 16 720575940643700640 80152611093049624 right intrinsic central MBON #> 17 720575940615221811 81137979670297348 right intrinsic central MBON #> 18 720575940614026193 80154466519131949 right intrinsic central MBON #> 19 720575940633209647 78463486488950059 left intrinsic central MBON #> 20 720575940623001480 80154535238527400 right intrinsic central MBON #> 21 720575940613070485 81066305390179956 right intrinsic central MBON #> 22 720575940614595218 78040449457502610 left intrinsic central MBON #> 23 720575940636992368 80785654845309410 right intrinsic central MBON #> 24 720575940621828443 79166830266640003 left intrinsic central MBON #> 25 720575940637902938 78181599128215629 left intrinsic central MBON #> 26 720575940638774606 78040449457461921 left intrinsic central MBON #> 27 720575940639697827 80224766543977933 right intrinsic central MBON #> 28 720575940626833021 78251349531485275 left intrinsic central MBON #> 29 720575940618008859 77901086224032815 left intrinsic central MBON #> 30 720575940635841143 78110818201436707 left intrinsic central MBON #> 31 720575940618249797 80082723452177136 right intrinsic central MBON #> 32 720575940629856515 77408917331762608 left intrinsic central MBON #> 33 720575940623905719 80224972702135904 right intrinsic central MBON #> 34 720575940629529722 78533992672102680 left intrinsic central MBON #> 35 720575940624659943 80011255129536552 left intrinsic central MBON #> 36 720575940624590316 79167173863853528 right intrinsic central MBON #> 37 720575940645304430 79380479052758063 left intrinsic central MBON #> 38 720575940612196850 81136880426746412 right intrinsic central MBON #> 39 720575940630767959 78251486970442209 left intrinsic central MBON #> 40 720575940640963747 76985537105536911 left intrinsic central MBON #> 41 720575940628757547 78040449457463315 left intrinsic central MBON #> 42 720575940627144069 79166692827138268 right intrinsic central MBON #> 43 720575940610647416 81137979602919932 right intrinsic central MBON #> 44 720575940622093436 81136880426744139 right intrinsic central MBON #> 45 720575940624696810 78110818201651448 left intrinsic central MBON #> 46 720575940629422086 77760348668670642 left intrinsic central MBON #> 47 720575940647328900 81137979670303492 right intrinsic central MBON #> 48 720575940650386553 78110818201681795 left intrinsic central MBON #> 49 720575940639556467 81067610926141558 right intrinsic central MBON #> 50 720575940636120986 81700242831237167 right intrinsic central MBON #> 51 720575940617749538 80786135881765925 right intrinsic central MBON #> 52 720575940617760257 81277549061455173 right intrinsic central MBON #> 53 720575940619810389 79518055445188833 right intrinsic central MBON #> 54 720575940634482783 81136605414678093 right intrinsic central MBON #> 55 720575940644615716 78182286188838645 left intrinsic central MBON #> 56 720575940626109315 81066305390093306 right intrinsic central MBON #> 57 720575940623377802 78110818201621392 left intrinsic central MBON #> 58 720575940626744921 81277549061481189 right intrinsic central MBON #> 59 720575940623464316 81136880426764424 right intrinsic central MBON #> 60 720575940622979277 79027192356412856 left intrinsic central MBON #> 61 720575940614892182 81277617781167541 right intrinsic central MBON #> 62 720575940620715224 78111917579300796 left intrinsic central MBON #> 63 720575940613090673 78324741798855874 left intrinsic central MBON #> 64 720575940621777391 81137979736901319 right intrinsic central MBON #> 65 720575940606953858 81136880426735755 right intrinsic central MBON #> 66 720575940630075703 79309972869657633 left intrinsic central MBON #> 67 720575940652390134 78603949099622269 left intrinsic central MBON #> 68 720575940632535756 79380204241413766 left intrinsic central MBON #> 69 720575940643696288 79309904216692475 left intrinsic central MBON #> 70 720575940620162718 78323023677138555 left intrinsic central MBON #> 71 720575940635063135 80082242348953693 right intrinsic central MBON #> 72 720575940616463477 77830305364995511 left intrinsic central MBON #> 73 720575940629981440 78885355625276424 left intrinsic central MBON #> 74 720575940623182847 78463211409646517 left intrinsic central MBON #> 75 720575940626315010 79943222847625326 right intrinsic central MBON #> 76 720575940632943277 80925980016963911 right intrinsic central MBON #> 77 720575940624539284 78040449457553649 left intrinsic central MBON #> 78 720575940626180878 80011530007496199 left intrinsic central MBON #> 79 720575940628783363 80434292093847745 right intrinsic central MBON #> 80 720575940643309197 79870998677653042 left intrinsic central MBON #> 81 720575940614392999 79237542540872430 left intrinsic central MBON #> 82 720575940617302365 78604086538417636 left intrinsic central MBON #> 83 720575940635651680 81277549061591572 right intrinsic central MBON #> 84 720575940624694503 79941230049538531 left intrinsic central MBON #> 85 720575940628734376 79869899232522382 right intrinsic central MBON #> 86 720575940610964946 81630904409213619 right intrinsic central MBON #> 87 720575940607155890 80433124332533007 right intrinsic central MBON #> 88 720575940623381956 80644779918075196 right intrinsic central MBON #> 89 720575940628487813 81560466945525625 right intrinsic central MBON #> 90 720575940638028607 81419592152467685 right intrinsic central MBON #> 91 720575940621164720 80222636373797362 left intrinsic central MBON #> 92 720575940623841463 78251349531447591 left intrinsic central MBON #> 93 720575940631177803 78814711734490195 left intrinsic central MBON #> 94 720575940622306625 79166761480079751 right intrinsic central MBON #> 95 720575940616398303 79729161744437991 left intrinsic central MBON #> 96 720575940623750325 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON02 glutamate putative_primary MBON02 FBbt_00111012 #> 2 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 3 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 4 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 5 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 6 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 7 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 8 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 9 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 10 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 11 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 12 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 13 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 14 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 15 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 16 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 17 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 18 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 19 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 20 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 21 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 22 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 23 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 24 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 25 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 26 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 27 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 28 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 29 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 30 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 31 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 32 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 33 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 34 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 35 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 36 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 37 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 38 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 39 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 40 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 41 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 42 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 43 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 44 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 45 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 46 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 47 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 48 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 49 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 50 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 51 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 52 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 53 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 54 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 55 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 56 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 57 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 58 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 59 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 60 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 61 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 62 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 63 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 64 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 65 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 66 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 67 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 68 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 69 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 70 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 71 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 72 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 73 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 74 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 75 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 76 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 77 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 78 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 79 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 80 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 81 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 82 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 83 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 84 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 85 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 86 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 87 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 88 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 89 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 90 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 91 MBON05 acetylcholine putative_primary MBON05 FBbt_00111004 #> 92 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 93 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 94 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 95 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 96 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 flytable_cell_types(\"MBON%\", version=450) #> Updating 92 ids #> flywire_rootid_cached: Looking up 92 missing keys #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940620475757 79448854932107696 left intrinsic central MBON #> 2 720575940635988581 80011942324010318 right intrinsic central MBON #> 3 720575940616047221 80715286101144676 right intrinsic central MBON #> 4 720575940638780494 81137979670302132 right intrinsic central MBON #> 5 720575940610014510 81349085835581377 right intrinsic central MBON #> 6 720575940608009737 78744342923662254 left intrinsic central MBON #> 7 720575940620520769 78603948898007978 left intrinsic central MBON #> 8 720575940621245680 78111986298788517 left intrinsic central MBON #> 9 720575940631910308 81349223341739625 right intrinsic central MBON #> 10 720575940612772579 78393323903110735 left intrinsic central MBON #> 11 720575940616240011 80223254782485510 right intrinsic central MBON #> 12 720575940624260839 81277549061520124 right intrinsic central MBON #> 13 720575940625496010 79588561627810154 right intrinsic central MBON #> 14 720575940621704361 81489685951698728 right intrinsic central MBON #> 15 720575940616298635 78180912067538056 left intrinsic central MBON #> 16 720575940621187056 80152611093049624 right intrinsic central MBON #> 17 720575940614206866 81137979670297348 right intrinsic central MBON #> 18 720575940621208820 80154466519131949 right intrinsic central MBON #> 19 720575940615431692 78463486488950059 left intrinsic central MBON #> 20 720575940639603584 80154535238527400 right intrinsic central MBON #> 21 720575940634657899 81066305390179956 right intrinsic central MBON #> 22 720575940630796363 78040449457502610 left intrinsic central MBON #> 23 720575940621196784 80785654845309410 right intrinsic central MBON #> 24 720575940617807429 79166830266640003 left intrinsic central MBON #> 25 720575940623046035 78181599128215629 left intrinsic central MBON #> 26 720575940638774606 78040449457461921 left intrinsic central MBON #> 27 720575940643518408 80224766543977933 right intrinsic central MBON #> 28 720575940625168528 78251349531485275 left intrinsic central MBON #> 29 720575940615443468 77901086224032815 left intrinsic central MBON #> 30 720575940635841143 78110818201436707 left intrinsic central MBON #> 31 720575940613049325 80082723452177136 right intrinsic central MBON #> 32 720575940627152712 77408917331762608 left intrinsic central MBON #> 33 720575940623615561 80224972702135904 right intrinsic central MBON #> 34 720575940624260583 78533992672102680 left intrinsic central MBON #> 35 720575940623189431 80011255129536552 left intrinsic central MBON #> 36 720575940628356611 79167173863853528 right intrinsic central MBON #> 37 720575940629103486 79380479052758063 left intrinsic central MBON #> 38 720575940626510729 81136880426746412 right intrinsic central MBON #> 39 720575940631573165 78251486970442209 left intrinsic central MBON #> 40 720575940627235215 76985537105536911 left intrinsic central MBON #> 41 720575940625623165 78040449457463315 left intrinsic central MBON #> 42 720575940641532557 79166692827138268 right intrinsic central MBON #> 43 720575940604965809 81137979602919932 right intrinsic central MBON #> 44 720575940604592300 81136880426744139 right intrinsic central MBON #> 45 720575940613666001 78110818201651448 left intrinsic central MBON #> 46 720575940620015275 77760348668670642 left intrinsic central MBON #> 47 720575940619587975 81137979670303492 right intrinsic central MBON #> 48 720575940636538480 78110818201681795 left intrinsic central MBON #> 49 720575940629528064 81067610926141558 right intrinsic central MBON #> 50 720575940630182467 81700242831237167 right intrinsic central MBON #> 51 720575940611534193 80786135881765925 right intrinsic central MBON #> 52 720575940624149908 81277549061455173 right intrinsic central MBON #> 53 720575940635705719 79518055445188833 right intrinsic central MBON #> 54 720575940634482783 81136605414678093 right intrinsic central MBON #> 55 720575940628680039 78182286188838645 left intrinsic central MBON #> 56 720575940626109315 81066305390093306 right intrinsic central MBON #> 57 720575940644139812 78110818201621392 left intrinsic central MBON #> 58 720575940654302881 81277549061481189 right intrinsic central MBON #> 59 720575940626786949 81136880426764424 right intrinsic central MBON #> 60 720575940611536241 79027192356412856 left intrinsic central MBON #> 61 720575940623018730 81277617781167541 right intrinsic central MBON #> 62 720575940635488623 78111917579300796 left intrinsic central MBON #> 63 720575940616286603 78324741798855874 left intrinsic central MBON #> 64 720575940621503265 81137979736901319 right intrinsic central MBON #> 65 720575940631189304 81136880426735755 right intrinsic central MBON #> 66 720575940617330945 79309972869657633 left intrinsic central MBON #> 67 720575940628523419 78603949099622269 left intrinsic central MBON #> 68 720575940610543826 79380204241413766 left intrinsic central MBON #> 69 720575940616968633 79309904216692475 left intrinsic central MBON #> 70 720575940623762923 78323023677138555 left intrinsic central MBON #> 71 720575940626901637 80082242348953693 right intrinsic central MBON #> 72 720575940623211498 77830305364995511 left intrinsic central MBON #> 73 720575940625816420 78885355625276424 left intrinsic central MBON #> 74 720575940619919531 78463211409646517 left intrinsic central MBON #> 75 720575940614532970 79943222847625326 right intrinsic central MBON #> 76 720575940643356064 80925980016963911 right intrinsic central MBON #> 77 720575940649242233 78040449457553649 left intrinsic central MBON #> 78 720575940619620487 80011530007496199 left intrinsic central MBON #> 79 720575940624835661 80434292093847745 right intrinsic central MBON #> 80 720575940625538110 79870998677653042 left intrinsic central MBON #> 81 720575940626706825 79237542540872430 left intrinsic central MBON #> 82 720575940605195878 78604086538417636 left intrinsic central MBON #> 83 720575940631910052 81277549061591572 right intrinsic central MBON #> 84 720575940608426197 79941230049538531 left intrinsic central MBON #> 85 720575940625222288 79869899232522382 right intrinsic central MBON #> 86 720575940620070278 81630904409213619 right intrinsic central MBON #> 87 720575940633688220 80433124332533007 right intrinsic central MBON #> 88 720575940613357096 80644779918075196 right intrinsic central MBON #> 89 720575940608355029 81560466945525625 right intrinsic central MBON #> 90 720575940624105196 81419592152467685 right intrinsic central MBON #> 91 720575940613666769 80222636373797362 left intrinsic central MBON #> 92 720575940605182822 78251349531447591 left intrinsic central MBON #> 93 720575940635161268 78814711734490195 left intrinsic central MBON #> 94 720575940631601292 79166761480079751 right intrinsic central MBON #> 95 720575940609440324 79729161744437991 left intrinsic central MBON #> 96 720575940604158124 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON02 glutamate putative_primary MBON02 FBbt_00111012 #> 2 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 3 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 4 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 5 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 6 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 7 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 8 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 9 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 10 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 11 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 12 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 13 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 14 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 15 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 16 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 17 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 18 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 19 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 20 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 21 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 22 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 23 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 24 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 25 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 26 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 27 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 28 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 29 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 30 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 31 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 32 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 33 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 34 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 35 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 36 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 37 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 38 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 39 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 40 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 41 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 42 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 43 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 44 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 45 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 46 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 47 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 48 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 49 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 50 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 51 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 52 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 53 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 54 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 55 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 56 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 57 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 58 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 59 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 60 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 61 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 62 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 63 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 64 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 65 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 66 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 67 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 68 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 69 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 70 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 71 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 72 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 73 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 74 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 75 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 76 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 77 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 78 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 79 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 80 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 81 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 82 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 83 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 84 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 85 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 86 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 87 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 88 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 89 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 90 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 91 MBON05 acetylcholine putative_primary MBON05 FBbt_00111004 #> 92 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 93 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 94 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 95 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 96 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 # the latest connectome dump, see flywire_connectome_data_version() if (FALSE) { flytable_cell_types(\"MBON%\", version=TRUE) } # two characters flytable_cell_types(\"MBON__\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940624185095 79448854932107696 left intrinsic central MBON #> 2 720575940623472716 80011942324010318 right intrinsic central MBON #> 3 720575940638526278 80715286101144676 right intrinsic central MBON #> 4 720575940629585602 81137979670302132 right intrinsic central MBON #> 5 720575940637934308 81349085835581377 right intrinsic central MBON #> 6 720575940632118343 78744342923662254 left intrinsic central MBON #> 7 720575940609959637 78603948898007978 left intrinsic central MBON #> 8 720575940638163428 78111986298788517 left intrinsic central MBON #> 9 720575940630496374 81349223341739625 right intrinsic central MBON #> 10 720575940642142861 78393323903110735 left intrinsic central MBON #> 11 720575940611344078 80223254782485510 right intrinsic central MBON #> 12 720575940617552340 79588561627810154 right intrinsic central MBON #> 13 720575940624280328 81489685951698728 right intrinsic central MBON #> 14 720575940617567206 78180912067538056 left intrinsic central MBON #> 15 720575940643700640 80152611093049624 right intrinsic central MBON #> 16 720575940615221811 81137979670297348 right intrinsic central MBON #> 17 720575940614026193 80154466519131949 right intrinsic central MBON #> 18 720575940633209647 78463486488950059 left intrinsic central MBON #> 19 720575940623001480 80154535238527400 right intrinsic central MBON #> 20 720575940614595218 78040449457502610 left intrinsic central MBON #> 21 720575940636992368 80785654845309410 right intrinsic central MBON #> 22 720575940621828443 79166830266640003 left intrinsic central MBON #> 23 720575940637902938 78181599128215629 left intrinsic central MBON #> 24 720575940638774606 78040449457461921 left intrinsic central MBON #> 25 720575940639697827 80224766543977933 right intrinsic central MBON #> 26 720575940626833021 78251349531485275 left intrinsic central MBON #> 27 720575940618008859 77901086224032815 left intrinsic central MBON #> 28 720575940635841143 78110818201436707 left intrinsic central MBON #> 29 720575940618249797 80082723452177136 right intrinsic central MBON #> 30 720575940629856515 77408917331762608 left intrinsic central MBON #> 31 720575940623905719 80224972702135904 right intrinsic central MBON #> 32 720575940629529722 78533992672102680 left intrinsic central MBON #> 33 720575940624590316 79167173863853528 right intrinsic central MBON #> 34 720575940645304430 79380479052758063 left intrinsic central MBON #> 35 720575940630767959 78251486970442209 left intrinsic central MBON #> 36 720575940610647416 81137979602919932 right intrinsic central MBON #> 37 720575940622093436 81136880426744139 right intrinsic central MBON #> 38 720575940629422086 77760348668670642 left intrinsic central MBON #> 39 720575940647328900 81137979670303492 right intrinsic central MBON #> 40 720575940639556467 81067610926141558 right intrinsic central MBON #> 41 720575940636120986 81700242831237167 right intrinsic central MBON #> 42 720575940617749538 80786135881765925 right intrinsic central MBON #> 43 720575940617760257 81277549061455173 right intrinsic central MBON #> 44 720575940634482783 81136605414678093 right intrinsic central MBON #> 45 720575940644615716 78182286188838645 left intrinsic central MBON #> 46 720575940626109315 81066305390093306 right intrinsic central MBON #> 47 720575940623377802 78110818201621392 left intrinsic central MBON #> 48 720575940626744921 81277549061481189 right intrinsic central MBON #> 49 720575940623464316 81136880426764424 right intrinsic central MBON #> 50 720575940622979277 79027192356412856 left intrinsic central MBON #> 51 720575940614892182 81277617781167541 right intrinsic central MBON #> 52 720575940620715224 78111917579300796 left intrinsic central MBON #> 53 720575940613090673 78324741798855874 left intrinsic central MBON #> 54 720575940621777391 81137979736901319 right intrinsic central MBON #> 55 720575940606953858 81136880426735755 right intrinsic central MBON #> 56 720575940630075703 79309972869657633 left intrinsic central MBON #> 57 720575940652390134 78603949099622269 left intrinsic central MBON #> 58 720575940632535756 79380204241413766 left intrinsic central MBON #> 59 720575940643696288 79309904216692475 left intrinsic central MBON #> 60 720575940620162718 78323023677138555 left intrinsic central MBON #> 61 720575940635063135 80082242348953693 right intrinsic central MBON #> 62 720575940616463477 77830305364995511 left intrinsic central MBON #> 63 720575940629981440 78885355625276424 left intrinsic central MBON #> 64 720575940623182847 78463211409646517 left intrinsic central MBON #> 65 720575940626315010 79943222847625326 right intrinsic central MBON #> 66 720575940632943277 80925980016963911 right intrinsic central MBON #> 67 720575940624539284 78040449457553649 left intrinsic central MBON #> 68 720575940626180878 80011530007496199 left intrinsic central MBON #> 69 720575940628783363 80434292093847745 right intrinsic central MBON #> 70 720575940643309197 79870998677653042 left intrinsic central MBON #> 71 720575940614392999 79237542540872430 left intrinsic central MBON #> 72 720575940617302365 78604086538417636 left intrinsic central MBON #> 73 720575940635651680 81277549061591572 right intrinsic central MBON #> 74 720575940624694503 79941230049538531 left intrinsic central MBON #> 75 720575940628734376 79869899232522382 right intrinsic central MBON #> 76 720575940610964946 81630904409213619 right intrinsic central MBON #> 77 720575940607155890 80433124332533007 right intrinsic central MBON #> 78 720575940623381956 80644779918075196 right intrinsic central MBON #> 79 720575940628487813 81560466945525625 right intrinsic central MBON #> 80 720575940638028607 81419592152467685 right intrinsic central MBON #> 81 720575940621164720 80222636373797362 left intrinsic central MBON #> 82 720575940623841463 78251349531447591 left intrinsic central MBON #> 83 720575940631177803 78814711734490195 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON02 glutamate putative_primary MBON02 FBbt_00111012 #> 2 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 3 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 4 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 5 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 6 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 7 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 8 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 9 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 10 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 11 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 12 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 13 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 14 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 15 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 16 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 17 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 18 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 19 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 20 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 21 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 22 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 23 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 24 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 25 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 26 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 27 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 28 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 29 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 30 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 31 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 32 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 33 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 34 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 35 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 36 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 37 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 38 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 39 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 40 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 41 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 42 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 43 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 44 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 45 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 46 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 47 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 48 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 49 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 50 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 51 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 52 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 53 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 54 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 55 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 56 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 57 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 58 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 59 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 60 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 61 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 62 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 63 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 64 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 65 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 66 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 67 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 68 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 69 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 70 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 71 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 72 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 73 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 74 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 75 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 76 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 77 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 78 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 79 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 80 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 81 MBON05 acetylcholine putative_primary MBON05 FBbt_00111004 #> 82 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 83 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 # at least one character flytable_cell_types(\"MBON_%\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940624185095 79448854932107696 left intrinsic central MBON #> 2 720575940623472716 80011942324010318 right intrinsic central MBON #> 3 720575940638526278 80715286101144676 right intrinsic central MBON #> 4 720575940629585602 81137979670302132 right intrinsic central MBON #> 5 720575940637934308 81349085835581377 right intrinsic central MBON #> 6 720575940632118343 78744342923662254 left intrinsic central MBON #> 7 720575940609959637 78603948898007978 left intrinsic central MBON #> 8 720575940638163428 78111986298788517 left intrinsic central MBON #> 9 720575940630496374 81349223341739625 right intrinsic central MBON #> 10 720575940642142861 78393323903110735 left intrinsic central MBON #> 11 720575940611344078 80223254782485510 right intrinsic central MBON #> 12 720575940634822751 81277549061520124 right intrinsic central MBON #> 13 720575940617552340 79588561627810154 right intrinsic central MBON #> 14 720575940624280328 81489685951698728 right intrinsic central MBON #> 15 720575940617567206 78180912067538056 left intrinsic central MBON #> 16 720575940643700640 80152611093049624 right intrinsic central MBON #> 17 720575940615221811 81137979670297348 right intrinsic central MBON #> 18 720575940614026193 80154466519131949 right intrinsic central MBON #> 19 720575940633209647 78463486488950059 left intrinsic central MBON #> 20 720575940623001480 80154535238527400 right intrinsic central MBON #> 21 720575940613070485 81066305390179956 right intrinsic central MBON #> 22 720575940614595218 78040449457502610 left intrinsic central MBON #> 23 720575940636992368 80785654845309410 right intrinsic central MBON #> 24 720575940621828443 79166830266640003 left intrinsic central MBON #> 25 720575940637902938 78181599128215629 left intrinsic central MBON #> 26 720575940638774606 78040449457461921 left intrinsic central MBON #> 27 720575940639697827 80224766543977933 right intrinsic central MBON #> 28 720575940626833021 78251349531485275 left intrinsic central MBON #> 29 720575940618008859 77901086224032815 left intrinsic central MBON #> 30 720575940635841143 78110818201436707 left intrinsic central MBON #> 31 720575940618249797 80082723452177136 right intrinsic central MBON #> 32 720575940629856515 77408917331762608 left intrinsic central MBON #> 33 720575940623905719 80224972702135904 right intrinsic central MBON #> 34 720575940629529722 78533992672102680 left intrinsic central MBON #> 35 720575940624659943 80011255129536552 left intrinsic central MBON #> 36 720575940624590316 79167173863853528 right intrinsic central MBON #> 37 720575940645304430 79380479052758063 left intrinsic central MBON #> 38 720575940612196850 81136880426746412 right intrinsic central MBON #> 39 720575940630767959 78251486970442209 left intrinsic central MBON #> 40 720575940640963747 76985537105536911 left intrinsic central MBON #> 41 720575940628757547 78040449457463315 left intrinsic central MBON #> 42 720575940627144069 79166692827138268 right intrinsic central MBON #> 43 720575940610647416 81137979602919932 right intrinsic central MBON #> 44 720575940622093436 81136880426744139 right intrinsic central MBON #> 45 720575940624696810 78110818201651448 left intrinsic central MBON #> 46 720575940629422086 77760348668670642 left intrinsic central MBON #> 47 720575940647328900 81137979670303492 right intrinsic central MBON #> 48 720575940650386553 78110818201681795 left intrinsic central MBON #> 49 720575940639556467 81067610926141558 right intrinsic central MBON #> 50 720575940636120986 81700242831237167 right intrinsic central MBON #> 51 720575940617749538 80786135881765925 right intrinsic central MBON #> 52 720575940617760257 81277549061455173 right intrinsic central MBON #> 53 720575940619810389 79518055445188833 right intrinsic central MBON #> 54 720575940634482783 81136605414678093 right intrinsic central MBON #> 55 720575940644615716 78182286188838645 left intrinsic central MBON #> 56 720575940626109315 81066305390093306 right intrinsic central MBON #> 57 720575940623377802 78110818201621392 left intrinsic central MBON #> 58 720575940626744921 81277549061481189 right intrinsic central MBON #> 59 720575940623464316 81136880426764424 right intrinsic central MBON #> 60 720575940622979277 79027192356412856 left intrinsic central MBON #> 61 720575940614892182 81277617781167541 right intrinsic central MBON #> 62 720575940620715224 78111917579300796 left intrinsic central MBON #> 63 720575940613090673 78324741798855874 left intrinsic central MBON #> 64 720575940621777391 81137979736901319 right intrinsic central MBON #> 65 720575940606953858 81136880426735755 right intrinsic central MBON #> 66 720575940630075703 79309972869657633 left intrinsic central MBON #> 67 720575940652390134 78603949099622269 left intrinsic central MBON #> 68 720575940632535756 79380204241413766 left intrinsic central MBON #> 69 720575940643696288 79309904216692475 left intrinsic central MBON #> 70 720575940620162718 78323023677138555 left intrinsic central MBON #> 71 720575940635063135 80082242348953693 right intrinsic central MBON #> 72 720575940616463477 77830305364995511 left intrinsic central MBON #> 73 720575940629981440 78885355625276424 left intrinsic central MBON #> 74 720575940623182847 78463211409646517 left intrinsic central MBON #> 75 720575940626315010 79943222847625326 right intrinsic central MBON #> 76 720575940632943277 80925980016963911 right intrinsic central MBON #> 77 720575940624539284 78040449457553649 left intrinsic central MBON #> 78 720575940626180878 80011530007496199 left intrinsic central MBON #> 79 720575940628783363 80434292093847745 right intrinsic central MBON #> 80 720575940643309197 79870998677653042 left intrinsic central MBON #> 81 720575940614392999 79237542540872430 left intrinsic central MBON #> 82 720575940617302365 78604086538417636 left intrinsic central MBON #> 83 720575940635651680 81277549061591572 right intrinsic central MBON #> 84 720575940624694503 79941230049538531 left intrinsic central MBON #> 85 720575940628734376 79869899232522382 right intrinsic central MBON #> 86 720575940610964946 81630904409213619 right intrinsic central MBON #> 87 720575940607155890 80433124332533007 right intrinsic central MBON #> 88 720575940623381956 80644779918075196 right intrinsic central MBON #> 89 720575940628487813 81560466945525625 right intrinsic central MBON #> 90 720575940638028607 81419592152467685 right intrinsic central MBON #> 91 720575940621164720 80222636373797362 left intrinsic central MBON #> 92 720575940623841463 78251349531447591 left intrinsic central MBON #> 93 720575940631177803 78814711734490195 left intrinsic central MBON #> 94 720575940622306625 79166761480079751 right intrinsic central MBON #> 95 720575940616398303 79729161744437991 left intrinsic central MBON #> 96 720575940623750325 79729161744426207 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON02 glutamate putative_primary MBON02 FBbt_00111012 #> 2 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 3 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 4 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 5 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 6 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 7 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 8 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 9 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 10 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 11 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 12 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 13 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 14 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 15 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 16 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 17 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 18 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 19 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 20 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 21 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 22 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 23 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 24 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 25 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 26 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 27 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 28 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 29 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 30 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 31 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 32 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 33 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 34 MBON10 glutamate EBa1 MBON10 FBbt_00111008 #> 35 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 36 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 37 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 38 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 39 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 40 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 41 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 42 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 43 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 44 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 45 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 46 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 47 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 48 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 49 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 50 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 51 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 52 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 53 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 54 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 55 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 56 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 57 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 58 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 59 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 60 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 61 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 62 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 63 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 64 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 65 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 66 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 67 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 68 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 69 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 70 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 71 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 72 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 73 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 74 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 75 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 76 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 77 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 78 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 79 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 80 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 81 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 82 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 83 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 84 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 85 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 86 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 87 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 88 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 89 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 90 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 91 MBON05 acetylcholine putative_primary MBON05 FBbt_00111004 #> 92 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 93 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 94 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 95 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 96 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 # range flytable_cell_types(\"MBON2[0-5]\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940611344078 80223254782485510 right intrinsic central MBON #> 2 720575940617567206 78180912067538056 left intrinsic central MBON #> 3 720575940623464316 81136880426764424 right intrinsic central MBON #> 4 720575940620715224 78111917579300796 left intrinsic central MBON #> 5 720575940613090673 78324741798855874 left intrinsic central MBON #> 6 720575940621777391 81137979736901319 right intrinsic central MBON #> 7 720575940606953858 81136880426735755 right intrinsic central MBON #> 8 720575940635063135 80082242348953693 right intrinsic central MBON #> 9 720575940616463477 77830305364995511 left intrinsic central MBON #> 10 720575940631177803 78814711734490195 left intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 2 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 3 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 4 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 5 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 6 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 7 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 8 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 9 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 10 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 # include side specification flytable_cell_types(\"DA2_lPN_R\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940639337461 80646154374848875 right intrinsic central ALPN #> 2 720575940628259407 81349910469210197 right intrinsic central ALPN #> 3 720575940624106442 80575785630612215 right intrinsic central ALPN #> 4 720575940622762995 80575785630553529 right intrinsic central ALPN #> 5 720575940622311704 80646154374760379 right intrinsic central ALPN #> 6 720575940610052266 80646154374867885 right intrinsic central ALPN #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 #> 2 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 #> 3 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 #> 4 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 #> 5 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 #> 6 DA2_lPN acetylcholine ALl1_ventral DA2_lPN FBbt_00110882 # only the RHS MBON20 flytable_cell_types(\"MBON20_R\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940611344078 80223254782485510 right intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON20 gaba putative_primary MBON20 FBbt_00111013 # all RHS cells with class MBON flytable_cell_types(\"MBON_R\", target=\"cell_class\") #> root_id supervoxel_id side flow super_class cell_class #> 1 720575940623472716 80011942324010318 right intrinsic central MBON #> 2 720575940638526278 80715286101144676 right intrinsic central MBON #> 3 720575940629585602 81137979670302132 right intrinsic central MBON #> 4 720575940637934308 81349085835581377 right intrinsic central MBON #> 5 720575940630496374 81349223341739625 right intrinsic central MBON #> 6 720575940611344078 80223254782485510 right intrinsic central MBON #> 7 720575940634822751 81277549061520124 right intrinsic central MBON #> 8 720575940617552340 79588561627810154 right intrinsic central MBON #> 9 720575940624280328 81489685951698728 right intrinsic central MBON #> 10 720575940643700640 80152611093049624 right intrinsic central MBON #> 11 720575940615221811 81137979670297348 right intrinsic central MBON #> 12 720575940614026193 80154466519131949 right intrinsic central MBON #> 13 720575940623001480 80154535238527400 right intrinsic central MBON #> 14 720575940613070485 81066305390179956 right intrinsic central MBON #> 15 720575940636992368 80785654845309410 right intrinsic central MBON #> 16 720575940639697827 80224766543977933 right intrinsic central MBON #> 17 720575940618249797 80082723452177136 right intrinsic central MBON #> 18 720575940623905719 80224972702135904 right intrinsic central MBON #> 19 720575940624590316 79167173863853528 right intrinsic central MBON #> 20 720575940612196850 81136880426746412 right intrinsic central MBON #> 21 720575940627144069 79166692827138268 right intrinsic central MBON #> 22 720575940610647416 81137979602919932 right intrinsic central MBON #> 23 720575940622093436 81136880426744139 right intrinsic central MBON #> 24 720575940647328900 81137979670303492 right intrinsic central MBON #> 25 720575940639556467 81067610926141558 right intrinsic central MBON #> 26 720575940636120986 81700242831237167 right intrinsic central MBON #> 27 720575940617749538 80786135881765925 right intrinsic central MBON #> 28 720575940617760257 81277549061455173 right intrinsic central MBON #> 29 720575940619810389 79518055445188833 right intrinsic central MBON #> 30 720575940634482783 81136605414678093 right intrinsic central MBON #> 31 720575940626109315 81066305390093306 right intrinsic central MBON #> 32 720575940626744921 81277549061481189 right intrinsic central MBON #> 33 720575940623464316 81136880426764424 right intrinsic central MBON #> 34 720575940614892182 81277617781167541 right intrinsic central MBON #> 35 720575940621777391 81137979736901319 right intrinsic central MBON #> 36 720575940606953858 81136880426735755 right intrinsic central MBON #> 37 720575940635063135 80082242348953693 right intrinsic central MBON #> 38 720575940626315010 79943222847625326 right intrinsic central MBON #> 39 720575940632943277 80925980016963911 right intrinsic central MBON #> 40 720575940628783363 80434292093847745 right intrinsic central MBON #> 41 720575940635651680 81277549061591572 right intrinsic central MBON #> 42 720575940628734376 79869899232522382 right intrinsic central MBON #> 43 720575940610964946 81630904409213619 right intrinsic central MBON #> 44 720575940607155890 80433124332533007 right intrinsic central MBON #> 45 720575940623381956 80644779918075196 right intrinsic central MBON #> 46 720575940628487813 81560466945525625 right intrinsic central MBON #> 47 720575940638028607 81419592152467685 right intrinsic central MBON #> 48 720575940622306625 79166761480079751 right intrinsic central MBON #> cell_type top_nt ito_lee_hemilineage hemibrain_type fbbt_id #> 1 MBON01 glutamate putative_primary MBON01 FBbt_00100234 #> 2 MBON32 gaba putative_primary MBON32 FBbt_00049852 #> 3 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 4 MBON30 glutamate putative_primary MBON30 FBbt_00049850 #> 5 MBON05 glutamate putative_primary MBON05 FBbt_00111004 #> 6 MBON20 gaba putative_primary MBON20 FBbt_00111013 #> 7 MBON17-like acetylcholine DL1_dorsal MBON17-like #> 8 MBON02 gaba putative_primary MBON02 FBbt_00111012 #> 9 MBON33 acetylcholine putative_primary MBON33 FBbt_00049853 #> 10 MBON29 acetylcholine DL2_ventral MBON29 FBbt_00049849 #> 11 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 12 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 13 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 14 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 15 MBON31 gaba putative_primary MBON31 FBbt_00049851 #> 16 MBON14 acetylcholine FLAa2 MBON14 FBbt_00100238 #> 17 MBON27 acetylcholine putative_primary MBON27 FBbt_00049847 #> 18 MBON12 acetylcholine FLAa2 MBON12 FBbt_00111009 #> 19 MBON03 glutamate putative_primary MBON03 FBbt_00100232 #> 20 MBON15-like acetylcholine DL1_dorsal MBON15-like #> 21 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 22 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 23 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 24 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 25 MBON10 gaba EBa1 MBON10 FBbt_00111008 #> 26 MBON15 acetylcholine DL1_dorsal MBON15 FBbt_00111010 #> 27 MBON11 gaba putative_primary MBON11 FBbt_00100246 #> 28 MBON17 acetylcholine DL1_dorsal MBON17 FBbt_00111064 #> 29 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 #> 30 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 31 MBON19 acetylcholine DL1_dorsal MBON19 FBbt_00111011 #> 32 MBON16 acetylcholine DL1_dorsal MBON16 FBbt_00111063 #> 33 MBON24 acetylcholine putative_primary MBON24 FBbt_00049844 #> 34 MBON28 acetylcholine DL1_dorsal MBON28 FBbt_00049848 #> 35 MBON21 acetylcholine putative_primary MBON21 FBbt_00111046 #> 36 MBON23 acetylcholine DL1_dorsal MBON23 FBbt_00049113 #> 37 MBON22 acetylcholine putative_primary MBON22 FBbt_00100240 #> 38 MBON13 acetylcholine FLAa2 MBON13 FBbt_00100239 #> 39 MBON35 acetylcholine putative_primary MBON35 FBbt_00049855 #> 40 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 41 MBON18 acetylcholine DL1_dorsal MBON18 FBbt_00110101 #> 42 MBON04 glutamate putative_primary MBON04 FBbt_00111014 #> 43 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 44 MBON26 acetylcholine putative_primary MBON26 FBbt_00049846 #> 45 MBON07 glutamate putative_primary MBON07 FBbt_00111005 #> 46 MBON09 gaba putative_primary MBON09 FBbt_00111007 #> 47 MBON06 glutamate putative_primary MBON06 FBbt_00100242 #> 48 MBON25,MBON34 glutamate SMPad3 MBON25,MBON34 # anything with type *OR* class information cells=flytable_cell_types(target = 'all') # anything that mentions PN anywhere pncands=flytable_cell_types('%PN%', target = 'all') # }"},{"path":"https://natverse.org/fafbseg/reference/flytable_list_selected.html","id":null,"dir":"Reference","previous_headings":"","what":"List selected rows from flytable — flytable_list_selected","title":"List selected rows from flytable — flytable_list_selected","text":"List selected rows flytable","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_list_selected.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List selected rows from flytable — flytable_list_selected","text":"","code":"flytable_list_selected( ids = NULL, table = \"info\", fields = \"*\", idfield = \"root_id\", ... )"},{"path":"https://natverse.org/fafbseg/reference/flytable_list_selected.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List selected rows from flytable — flytable_list_selected","text":"ids One identifiers table name flytable table fields database columns return idfield field use key lookup ... Additional arguments passed flytable_query","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_list_selected.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List selected rows from flytable — flytable_list_selected","text":"dataframe containing selected rows / columns","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":null,"dir":"Reference","previous_headings":"","what":"Low level functions to access the flytable metadata service — flytable_login","title":"Low level functions to access the flytable metadata service — flytable_login","text":"flytable_login uses flytable user name email log service. flytable_set_token obtain store permanent seatable user-level API token. flytable_base returns base object (equivalent mysql database) allows access one tables, logging service necessary. returned base object give full access Python Base API allowing range row/column manipulations. flytable_alltables lists tables across flytables bases. flytable_columns returns name type regular columns base well default R type. Private columns _id included.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Low level functions to access the flytable metadata service — flytable_login","text":"","code":"flytable_login( url = \"https://flytable.mrc-lmb.cam.ac.uk/\", token = Sys.getenv(\"FLYTABLE_TOKEN\", unset = NA_character_) ) flytable_set_token(user, pwd, url = \"https://flytable.mrc-lmb.cam.ac.uk/\") flytable_base( table = NULL, base_name = NULL, workspace_id = NULL, url = \"https://flytable.mrc-lmb.cam.ac.uk/\", cached = TRUE ) flytable_alltables(ac = NULL, cached = TRUE) flytable_columns(table, base = NULL, cached = TRUE)"},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Low level functions to access the flytable metadata service — flytable_login","text":"url Optional URL server token normally retrieved FLYTABLE_TOKEN environment variable. user, pwd flytable user password used flytable_set_token obtain token table Character vector specifying table foe want base object. base_name Character vector specifying base workspace_id numeric id specifying workspace. Advanced use since can normally figure base_name. cached Whether use cached version response available. Set FALSE know tables added renamed session. ac Optional account object returned flytables_login base Optional character vector naming seatable base (recommended) Base object returned flytable_base (expert use). default value NULL rely table long unique across flytable server.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Low level functions to access the flytable metadata service — flytable_login","text":"flytable_login, Python Account object seatable api wrapped reticulate. flytable_base, Python Base object seatable api wrapped reticulate. data.frame containing base_name, workspace_id, table name table _id. flytable_columns data.frame containing columns name, type rtype","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Low level functions to access the flytable metadata service — flytable_login","text":"Besides initial setup (next paragraph), need use lower level functions directly. Instead recommend higher level functions flytable_query. order start using flytable, must get API token. seem convenient way seatable web interface can get one calling flytable_set_token flytable user password. step. Thereafter FLYTABLE_TOKEN environment variable set .Renviron file. flytable_base use flytable API token log service.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable_login.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Low level functions to access the flytable metadata service — flytable_login","text":"","code":"if (FALSE) { flytable_login() } if (FALSE) { flytable_set_token(user='xxx@gmail.com', pwd='yyy') } if (FALSE) { hemilineages=flytable_base(base_name='hemilineages') # equivalent, but simpler since you only have to remember the table name hemilineages=flytable_base('fafb_hemilineages_survey') } # \\donttest{ flytable_alltables() #> base_name workspace_id name #> 1 maleCNS 111 cns_info #> 2 Orphan proofreading 44 v1 #> 3 Orphan proofreading 44 Table3 #> 4 Remainder proofreading 44 v1 #> 5 Remainder proofreading 44 add_proofreading_783 #> 6 Review 44 v1 #> 7 Review Catalog 44 v1 #> 8 Review Catalog 44 review_459 #> 9 LAL_orphan_linking 29 LAL_bodies #> 10 NO_orphan_linking 29 NO_bodies #> 11 Alan_Mathews_project 5 DL4R_downstream #> 12 Alan_Mathews_project 5 DL4L_downstream #> 13 Alan_Mathews_project 5 DL4_HB_downstream #> 14 Alan_Mathews_project 5 dl4_matches_fafb_r_hb #> 15 Alan_Mathews_project 5 dl4_matches_fafb #> 16 Alan_Mathews_project 5 dl4_matches_fafb_l_hb #> 17 Alan_Mathews_project 5 VL2R_downstream #> 18 Alan_Mathews_project 5 VL2L_downstream #> 19 Alan_Mathews_project 5 VL2_HB_downstream #> 20 Alan_Mathews_project 5 vl2_matches_fafb_r_hb #> 21 Alan_Mathews_project 5 vl2_matches_fafb #> 22 Alan_Mathews_project 5 Vilpn1_downstream #> 23 Alan_Mathews_project 5 Vilpn2_downstream #> 24 Alan_Mathews_project 5 vilpn1_HB_downstream #> 25 Alan_Mathews_project 5 vilpn2_HB_downstream #> 26 Alan_Mathews_project 5 vilpn1_ds_r #> 27 Alan_Mathews_project 5 vilpn1_ds_l #> 28 Alan_Mathews_project 5 vilpn2_ds_r #> 29 Alan_Mathews_project 5 vilpn2_ds_l #> 30 Alan_Mathews_project 5 vilpn1_matches_fafb #> 31 Alan_Mathews_project 5 vilpn1r_matches_fafbr_hb #> 32 Alan_Mathews_project 5 vilpn2r_matches_fafbr_hb #> 33 Alan_Mathews_project 5 vilpn2_matches_fafb #> 34 Alan_Mathews_project 5 vl2_matches_fafb_r_hb(copy) #> 35 Alan_Mathews_project 5 vilpn2r_matches_fafbr_hb(copy) #> 36 Alan_Mathews_project 5 vl2_matches_fafb(copy) #> 37 Alan_Mathews_project 5 vilpn1_fafb_matches(copy) #> 38 Alan_Mathews_project 5 cable_length #> 39 Alan_Mathews_project 5 prepostcable_dl4 #> 40 Alan_Mathews_project 5 prepostcable_vl2 #> 41 Alan_Mathews_project 5 prepostcable_vilpn2 #> 42 Alan_Mathews_project 5 PN_stats #> 43 Alan_Mathews_project 5 NBLAST_scores #> 44 Alan_Mathews_project 5 vilpn_matches_fafb(copy) #> 45 Alan_Mathews_project 5 vilpn_matches_1r_2l #> 46 Alan_Mathews_project 5 vilpn_matches_2r_1l #> 47 Alan_Mathews_project 5 vilpn_total #> 48 Alan_Mathews_project 5 dl4_norm #> 49 Alan_Mathews_project 5 vilpnlr_combo #> 50 Alan_Mathews_project 5 norm #> 51 Alan_Mathews_project 5 2022-04-20T19_03_21+00_00_0wpp #> 52 Alan_Mathews_project 5 misc #> 53 AL_library 5 AL_bodies #> 54 cam_proofreading 5 batches #> 55 cam_proofreading 5 FlyWire_neuron_list - for_flywire #> 56 CATMAID_proofreading 5 catmaid #> 57 CATMAID_proofreading 5 all_done #> 58 DO_NOT_USE_main 5 DO_NOT_USE_info #> 59 DO_NOT_USE_main 5 DO_NOT_USE_hemilineages #> 60 flywire_matching 5 flywire_right #> 61 flywire_matching 5 hemibrain2flywire #> 62 flywire_matching 5 hemibrain2flywire_rematch #> 63 flywire_matching 5 hemibrain2flywire_mirrored #> 64 flywire_matching 5 flywire_ALr_ALl #> 65 flywire_matching 5 new_singles #> 66 flywire_matching 5 new_singles_lr #> 67 flywire_matching 5 all_singletons #> 68 hemibrain 5 hb_info #> 69 hemibrain 5 hb_hemilineages #> 70 hemibrain_matching 5 type_matches #> 71 hemibrain_matching 5 MWP_LH_RHS_cell_typing #> 72 hemibrain_matching 5 MWP_LH_LHS_cell_typing_v_hb #> 73 hemibrain_matching 5 MWP_LH_LHS_cell_typing_v_rhs_flywire #> 74 hemibrain_matching 5 LH_LHS_hb_vs_RHS_conflict_table #> 75 hemibrain_matching 5 MWP_mega_df #> 76 hemibrain_matching 5 MWP_LH_stereotypy #> 77 hemibrain_matching 5 MWP_PM_YY_cell_typing #> 78 hemibrain_matching 5 post_GM #> 79 LH_library 5 LH_bodies #> 80 LH_library 5 _old_LH_bodies #> 81 main 5 info #> 82 main 5 hemilineages #> 83 main(lineage_backup) 5 lineage_project #> 84 MB_library 5 MB_bodies #> 85 MB_library 5 MB_bodies_RHS #> 86 meta 5 cb_numbers #> 87 optic_lobes 5 optic #> 88 test 5 testfruit #> 89 fanc_maleVNC_matching 123 Table3_nblast95_20 #> 90 fanc_maleVNC_matching 123 Table3_nblast95_30 #> 91 manc_maleCNS 123 Table1_nblast95_60 #> 92 DB Comparison 1 Table1 #> _id #> 1 96g5 #> 2 DHtk #> 3 0t5T #> 4 vlgx #> 5 9l9v #> 6 9JIF #> 7 Y9RH #> 8 SFd8 #> 9 wtpy #> 10 htKk #> 11 M4SW #> 12 P3aV #> 13 ip3N #> 14 jvT0 #> 15 0qC0 #> 16 8ZOA #> 17 Ikw9 #> 18 FCty #> 19 F9Sk #> 20 yP9j #> 21 dV47 #> 22 kcqG #> 23 4IO4 #> 24 qND2 #> 25 SvpB #> 26 ZCMx #> 27 IqEa #> 28 sikt #> 29 cxOO #> 30 UB2m #> 31 TuH0 #> 32 dZ2X #> 33 UYUu #> 34 K7hg #> 35 rrwF #> 36 1iG8 #> 37 935S #> 38 1Itd #> 39 Z738 #> 40 TKM9 #> 41 6D4l #> 42 p4KB #> 43 yJVR #> 44 7sqj #> 45 78cE #> 46 OE2j #> 47 iVH6 #> 48 14wl #> 49 dznE #> 50 A451 #> 51 J4ma #> 52 s6Oi #> 53 wNCm #> 54 0000 #> 55 FbAY #> 56 TYn5 #> 57 5mdz #> 58 BXTy #> 59 QGfh #> 60 Nscg #> 61 yN5a #> 62 LaYJ #> 63 2ThW #> 64 dwun #> 65 yHJb #> 66 wd66 #> 67 CXnQ #> 68 X2ZG #> 69 Sz01 #> 70 cpHc #> 71 NG0m #> 72 0Cl7 #> 73 Z5ea #> 74 8DAX #> 75 9yII #> 76 rRZE #> 77 q477 #> 78 pfDm #> 79 2PZZ #> 80 dvGc #> 81 f0ac #> 82 Z4SX #> 83 Nu8Q #> 84 K5lc #> 85 VR7q #> 86 0000 #> 87 Nato #> 88 0000 #> 89 7ve8 #> 90 EAqv #> 91 kg2f #> 92 0000 # } # \\donttest{ flytable_columns(\"info\") #> name type rtype #> 1 supervoxel_id text character #> 2 root_id text character #> 3 pos_x number numeric #> 4 pos_y number numeric #> 5 pos_z number numeric #> 6 soma_x number numeric #> 7 soma_y number numeric #> 8 soma_z number numeric #> 9 nucleus_id number numeric #> 10 side single-select character #> 11 top_nt text character #> 12 top_nt_conf number numeric #> 13 ito_lee_hemilineage single-select character #> 14 hartenstein_hemilineage text character #> 15 flow text character #> 16 super_class text character #> 17 cell_class text character #> 18 cell_sub_class text character #> 19 cell_type text character #> 20 cell_type_source text character #> 21 fbbt_id text character #> 22 vfb_id text character #> 23 cb_type text character #> 24 hemibrain_match text character #> 25 hemibrain_type text character #> 26 hemibrain_type_source text character #> 27 malecns_match text character #> 28 malecns_match_source text character #> 29 reviewed_by text character #> 30 status single-select character #> 31 notes long-text character #> 32 lrcid text character #> 33 root_duplicated checkbox logical #> 34 proofread checkbox logical #> 35 root_last_modified date POSIXct #> 36 last_user last-modifier character #> 37 LM_match text character #> 38 LM_match_source text character #> 39 root_630 text character #> 40 root_783 text character #> 41 nerve single-select character #> 42 release_630 checkbox logical #> 43 release_783 checkbox logical #> 44 morphology_group text character #> 45 known_nt text character #> 46 known_nt_source text character #> data #> 1 NULL #> 2 NULL #> 3 number, dot, no #> 4 number, dot, no #> 5 number, dot, no #> 6 number, dot, no #> 7 number, dot, no #> 8 number, dot, no #> 9 number, 0, TRUE, FALSE, dot, no #> 10 center, #59CB74, #FFFFFF, 707150, #4EB867, left, #F4667C, #FFFFFF, 21928, #DC556A, right, #46A1FD, #FFFFFF, 666421, #3C8FE4, na, #4ECCCB, #FFFFFF, 488103 #> 11 FALSE, undefined #> 12 number, 2, FALSE, FALSE, dot, no #> 13 ADL25, #aaa, #000000, 819986, ADL26, #aaa, #000000, 919193, ADL27, #aaa, #000000, 109498, ADL28, #aaa, #000000, 957054, ADM09, #aaa, #000000, 130521, ADM11, #aaa, #000000, 531452, ADM12, #aaa, #000000, 168743, ALad1, #aaa, #000000, 598204, ALl1_dorsal, #aaa, #000000, 403005, ALl1_ventral, #aaa, #000000, 436910, ALlv1, #aaa, #000000, 511159, ALv1, #aaa, #000000, 840849, ALv2, #aaa, #000000, 974452, AOTUv1_medial, #aaa, #000000, 790264, AOTUv1_ventral, #aaa, #000000, 442853, AOTUv2, #aaa, #000000, 670976, AOTUv3_dorsal, #aaa, #000000, 313454, AOTUv3_ventral, #aaa, #000000, 69614, AOTUv4_dorsal, #aaa, #000000, 308944, AOTUv4_ventral, #aaa, #000000, 321043, AVL22, #aaa, #000000, 722933, AVL23, #aaa, #000000, 121546, AVL25, #aaa, #000000, 35613, AVL27, #aaa, #000000, 8745, AVM16, #aaa, #000000, 862786, AVM17, #aaa, #000000, 330386, AVM19, #aaa, #000000, 168929, AVM20, #aaa, #000000, 716823, AVM21, #aaa, #000000, 144063, CLp1, #aaa, #000000, 361572, CLp2, #aaa, #000000, 426046, CREa1_dorsal, #aaa, #000000, 431266, CREa1_ventral, #aaa, #000000, 138394, CREa2_medial, #aaa, #000000, 504873, CREa2_ventral, #aaa, #000000, 575424, DL1_dorsal, #aaa, #000000, 727120, DL1_ventral, #aaa, #000000, 690284, DL2_dorsal, #aaa, #000000, 140884, DL2_ventral, #aaa, #000000, 310772, DM1, #aaa, #000000, 681894, DM2, #aaa, #000000, 88295, DM2_dorsal, #aaa, #000000, 626036, DM3, #aaa, #000000, 39866, DM3_CX, #aaa, #000000, 586041, DM3_canonical, #aaa, #000000, 772662, DM3_lateral, #aaa, #000000, 643580, DM3_medial, #aaa, #000000, 784672, DM4_dorsal, #aaa, #000000, 617128, DM4_medial, #aaa, #000000, 679773, DM4_ventral, #aaa, #000000, 122933, DM5_dorsal, #aaa, #000000, 175466, DM5_ventral, #aaa, #000000, 963751, DM6, #aaa, #000000, 244601, DM6_dorsal, #aaa, #000000, 589874, DM6_inferior, #aaa, #000000, 442502, DM6_lateral, #aaa, #000000, 701347, DM6_medial, #aaa, #000000, 55166, DM6_ventral, #aaa, #000000, 250188, EBa1, #aaa, #000000, 656315, FLAa1, #aaa, #000000, 651426, FLAa2, #aaa, #000000, 156680, FLAa3, #aaa, #000000, 516710, LALv1, #aaa, #000000, 604466, LB0, #aaa, #000000, 345842, LB0_anterior, #aaa, #000000, 519161, LB12, #aaa, #000000, 112831, LB19, #aaa, #000000, 124622, LB23, #aaa, #000000, 150685, LB3, #aaa, #000000, 672428, LB5, #aaa, #000000, 358879, LB6, #aaa, #000000, 625446, LB7, #aaa, #000000, 643150, LB7_posterior, #aaa, #000000, 809156, LHa1, #aaa, #000000, 910788, LHa2, #aaa, #000000, 667511, LHa3, #aaa, #000000, 739277, LHd1, #aaa, #000000, 561176, LHd2, #aaa, #000000, 331974, LHl1, #aaa, #000000, 600796, LHl2_lateral, #aaa, #000000, 766960, LHl2_medial, #aaa, #000000, 886621, LHl3, #aaa, #000000, 990565, LHl4_anterior, #aaa, #000000, 430384, LHl4_posterior, #aaa, #000000, 831357, LHp1, #aaa, #000000, 202734, LHp2_lateral, #aaa, #000000, 483076, LHp2_medial, #aaa, #000000, 530919, MBp1, #aaa, #000000, 580860, MBp2, #aaa, #000000, 882629, MBp3, #aaa, #000000, 400019, MBp4, #aaa, #000000, 911444, MD0, #aaa, #000000, 778325, MD3, #aaa, #000000, 166730, MD_SA1, #aaa, #000000, 924667, MX12, #aaa, #000000, 266167, MX12_medial, #aaa, #000000, 201080, MX3, #aaa, #000000, 459574, MX7, #aaa, #000000, 315447, PBp1, #aaa, #000000, 923827, PDL25, #aaa, #000000, 741158, PDL26, #aaa, #000000, 137685, PDM26, #aaa, #000000, 546113, PDM32, #aaa, #000000, 998928, PDM33, #aaa, #000000, 513930, PDM34, #aaa, #000000, 585002, PSa1, #aaa, #000000, 119090, PSp1, #aaa, #000000, 509400, PSp2, #aaa, #000000, 245308, PSp3_dorsal, #aaa, #000000, 525301, PSp3_ventral, #aaa, #000000, 305464, PVL02, #aaa, #000000, 378736, PVL15, #aaa, #000000, 109937, PVL17, #aaa, #000000, 173088, PVM13, #aaa, #000000, 256717, PVM14, #aaa, #000000, 252725, PVM15, #aaa, #000000, 303423, SIPa1_dorsal, #aaa, #000000, 25514, SIPa1_ventral, #aaa, #000000, 950343, SIPp1, #aaa, #000000, 454037, SLPa&l1_anterior, #aaa, #000000, 692055, SLPa&l1_lateral, #aaa, #000000, 80274, SLPad1_anterior, #aaa, #000000, 797608, SLPad1_posterior, #aaa, #000000, 253192, SLPal1, #aaa, #000000, 137934, SLPal2_dorsal, #aaa, #000000, 604081, SLPal2_ventral, #aaa, #000000, 519197, SLPal3, #aaa, #000000, 919481, SLPal4, #aaa, #000000, 82841, SLPal5, #aaa, #000000, 623379, SLPav1_lateral, #aaa, #000000, 99481, SLPav1_medial, #aaa, #000000, 473276, SLPav2, #aaa, #000000, 324498, SLPav3, #aaa, #000000, 257038, SLPp&v1_posterior, #aaa, #000000, 51543, SLPp&v1_ventral, #aaa, #000000, 344955, SLPpl1, #aaa, #000000, 912263, SLPpl2, #aaa, #000000, 411606, SLPpl3, #aaa, #000000, 610066, SLPpm1, #aaa, #000000, 728496, SLPpm2, #aaa, #000000, 664395, SLPpm3, #aaa, #000000, 880997, SMPad1, #aaa, #000000, 719040, SMPad2, #aaa, #000000, 517718, SMPad3, #aaa, #000000, 20480, SMPp&v1_posterior, #aaa, #000000, 566750, SMPp&v1_ventral, #aaa, #000000, 218799, SMPpd1, #aaa, #000000, 480777, SMPpd2, #aaa, #000000, 735960, SMPpv1, #aaa, #000000, 116347, SMPpv2, #aaa, #000000, 782447, TRdl, #aaa, #000000, 67085, TRdm, #aaa, #000000, 126795, VESa1, #aaa, #000000, 694066, VESa2, #aaa, #000000, 214095, VLPa1_lateral, #aaa, #000000, 231042, VLPa1_medial, #aaa, #000000, 984989, VLPa2, #aaa, #000000, 256224, VLPd&p1_dorsal, #aaa, #000000, 718802, VLPd&p1_posterior, #aaa, #000000, 946964, VLPd1, #aaa, #000000, 659295, VLPl&d1_dorsal, #aaa, #000000, 314355, VLPl&d1_lateral, #aaa, #000000, 295490, VLPl&p1_lateral, #aaa, #000000, 757777, VLPl&p1_posterior, #aaa, #000000, 716311, VLPl&p2_lateral, #aaa, #000000, 277026, VLPl&p2_posterior, #aaa, #000000, 623102, VLPl1, #aaa, #000000, 501397, VLPl2_dorsal, #aaa, #000000, 53914, VLPl2_ventral, #aaa, #000000, 633998, VLPl4_dorsal, #aaa, #000000, 917914, VLPl4_ventral, #aaa, #000000, 217170, VLPp&l1_lateral, #aaa, #000000, 941299, VLPp&l1_posterior, #aaa, #000000, 7595, VLPp1, #aaa, #000000, 614935, VLPp2, #aaa, #000000, 816034, VPNd1, #aaa, #000000, 334196, VPNl&d1_dorsal, #aaa, #000000, 265620, VPNl&d1_lateral, #aaa, #000000, 971297, VPNp&v1_posterior, #aaa, #000000, 147127, VPNp&v1_ventral, #aaa, #000000, 677039, VPNp1_lateral, #aaa, #000000, 356514, VPNp1_medial, #aaa, #000000, 726617, WEDa1_dorsal, #aaa, #000000, 289847, WEDa1_ventral, #aaa, #000000, 578652, WEDa2, #aaa, #000000, 995569, WEDd1, #aaa, #000000, 521068, WEDd2, #aaa, #000000, 663295, new_clone_1, #aaa, #000000, 220838, new_clone_2, #aaa, #000000, 460867, new_clone_3, #aaa, #000000, 626699, new_clone_4, #aaa, #000000, 524170, 613654, SLPp&v1, #FBD44A, #FFFFFF, 500246, sensory, #46A1FD, #FFFFFF, 350369, DM1_CX1, #D7E8FF, #202428, 189612, DM1_SEZ, #DEF7C4, #202428, 481669, DM1_CX2, #DC82D2, #FFFFFF, 222402, DM1_CRE, #F4667C, #FFFFFF, needs_assigment, #F4667C, #FFFFFF, 491678, #DC556A, optic, #59CB74, #FFFFFF, 865758, 471218, DM2_ALT, #9F8CF1, #FFFFFF, 17271, DM2_CX_p, #EAA775, #FFFFFF, 324985, DM2_CX_v, #59CB74, #FFFFFF, 854446, DM3_CX_p, #DEF7C4, #202428, 306346, DM2_CX_d, #9860E5, #FFFFFF, DM1_CX_d, 536481, #46A1FD, #FFFFFF, 298311, DM1_CX_p, #D7E8FF, #202428, DM4_CX_d2, 81887, #FBD44A, #FFFFFF, DM4_CX_d3, 572727, #C2C2C2, #FFFFFF, DM3_CX_d1, 361124, #ADDF84, #FFFFFF, DM2_CX_d2, 891883, #DC82D2, #FFFFFF, DM2_CX_d1, 340460, #89D2EA, #FFFFFF, DM1_CX_d2, 594996, #F4667C, #FFFFFF, DM4_CX_d1, 967181, #9F8CF1, #FFFFFF, DM3_CX_d2, 116972, #EAA775, #FFFFFF, 402580, DM1_CX_v, #FFDDE5, #202428, 643080, DM3_CX_v, #FBD44A, #FFFFFF, 375589, DM4_CX_p, #FFDDE5, #202428, 205371, DM4_CX_v, #D7E8FF, #202428, DM£_cx_p, #9860E5, #FFFFFF, 818690, DM1_loSM, #46A1FD, #FFFFFF, 492623, 916866, LHp2, #D8FAFF, #202428, primary, #59CB74, #FFFFFF, 604797, putative_primary, #ADDF84, #FFFFFF, 23976, 445149, SLPal2, #89D2EA, #FFFFFF, 39423, LHl2, #F4667C, #FFFFFF, 793080, new_clone_5, #DDFFE6, #202428, 405583, LALv1_dorsal, #46A1FD, #FFFFFF, 370038, LALv1_ventral, #D7E8FF, #202428, 397095, LHl2_ventral, #DDFFE6, #202428, 710714, LHl2_dorsal, #B7CEF9, #202428, LB0_posterior, #C2C2C2, #FFFFFF, 32408, 534862, WEDa1, #46A1FD, #FFFFFF, seb, #DC82D2, #FFFFFF, 527295, 924833, new_clone_6, #DAD7FF, #202428, DM1_OL, #9860E5, #FFFFFF, 442700, 925417, CREa2_dorsal, #D7E8FF, #202428, 757382, VLPp&l1_intermediate, #EAA775, #FFFFFF, 12847, LB3__prim, #ADDF84, #FFFFFF, 720575940621734861, 497920, #9F8CF1, #FFFFFF, 468033, PSp3, #FFD4FF, #202428, 729648, TRdl_a, #FFD9C8, #202428, 663876, TRdl_b, #DDFFE6, #202428, 562672, MX0, #D7E8FF, #202428, VLPd1__prim, 463728, #F4667C, #FFFFFF, 458317, MX12__prim, #4ECCCB, #FFFFFF, 464745, LB7__prim, #FFFCB5, #202428, 673114, VLPp&l1__prim, #E9E9E9, #202428, 460071, MX7__prim, #FFDDE5, #202428, left, 767570, #46A1FD, #FFFFFF, AN_sensory, #9860E5, #FFFFFF, 770811, 192973, LN_sensory, #DAD7FF, #202428, 119081, aPN_sensory, #DAD7FF, #202428, 447259, ON_sensory, #B7CEF9, #202428, 739390, PN_sensory, #9F8CF1, #FFFFFF, 549916, SMPad2_prim, #D8FAFF, #202428, 975326, SMPp&v1_prim, #89D2EA, #FFFFFF, vlpl2-v, #DC82D2, #FFFFFF, 716489, vlpl7p1, #EAA775, #FFFFFF, 278892, 331845, SLPa&l1_prim, #EAA775, #FFFFFF, 909782, SLPal1_prim, #89D2EA, #FFFFFF, 329809, SLPad1_posterior_or_VLPd&p1_posterior, #FFD4FF, #202428, ptua, #C2C2C2, #FFFFFF, 85765, 431580, VLPa1_prim, #FBD44A, #FFFFFF, 36279, DM3__prim, #4ECCCB, #FFFFFF, 896397, DM4__prim, #FBD44A, #FFFFFF, 836945, DM6__prim, #FFD9C8, #202428, VLPa2__prim, #ADDF84, #FFFFFF, 521774, VLPa1__prim, #F4667C, #FFFFFF, 158068, SMPad2__prim, #46A1FD, #FFFFFF, 174816, SMPp&v1__prim, #9860E5, #FFFFFF, 167661, SLPa&l1__prim, #59CB74, #FFFFFF, 17217, SLPal1__prim, #EAA775, #FFFFFF, 43986, 172733, no_lineage, #FFD9C8, #202428, aotuv1_vn, #89D2EA, #FFFFFF, 489600, 27684, SLpav2, #9F8CF1, #FFFFFF, 598276, LHp3, #9860E5, #FFFFFF, 320500, CREl1, #FFD9C8, #202428, 768209, LALa1, #59CB74, #FFFFFF, 172236, SMPpm1, #FFDDE5, #202428, 743924, CLp1_or_SLPpm2, #59CB74, #FFFFFF, 340194, VLPl&d1_medial, #89D2EA, #FFFFFF, 395985, VLPl&d1_posterior, #ADDF84, #FFFFFF, 597064, VLPl2_posterior, #DC82D2, #FFFFFF, 375022, VLPl2_medial, #D7E8FF, #202428, 832640, SLPa&l1_medial, #DEF7C4, #202428, 685235, SLPa&l1_posterior, #DC82D2, #FFFFFF, 400165, LHl4_dorsal, #FFFCB5, #202428, 726853, VLPl4_anterior, #FFD4FF, #202428, 162052, VLPl&p2_anterior, #ADDF84, #FFFFFF, 610026, VLPl&p1_anterior, #FFD4FF, #202428, 397383, DM5_central, #FBD44A, #FFFFFF, 429742, DM6_dorso_lateral, #E9E9E9, #202428, 912751, DM6_central1, #F4667C, #FFFFFF, 610414, DM6_dorso_medial, #B7CEF9, #202428, 195122, VLPd&p1_anterior, #4ECCCB, #FFFFFF, 61607, SLPp&v1_anterior, #ADDF84, #FFFFFF, 489027, VLPp&l1_anterior, #FFD9C8, #202428, 999517, DM1_antero_dorsal, #DDFFE6, #202428, 741992, DM1_antero_ventral, #E9E9E9, #202428, 229517, DM1_dorsal, #B7CEF9, #202428, 941917, DM2_central, #DEF7C4, #202428, 898011, DM3_dorso_lateral, #FFD4FF, #202428, 397372, DM3_dorso_medial, #E9E9E9, #202428, 44197, DM3_posterior, #FFD9C8, #202428, 603980, VLPl1_or_VLPl5, #FFD4FF, #202428, 985402, DM6_posterior, #D7E8FF, #202428, 53388, LALa1_posterior, #EAA775, #FFFFFF, 38120, LALa1_anterior, #D7E8FF, #202428, SLPal3_or_SLPal4_dorsal, 965919, #C2C2C2, #FFFFFF, vlpl4_am, #F4667C, #FFFFFF, 685539, 807102, VPNl&d1_medial, #F4667C, #FFFFFF, 279229, DM6_IbSpsP, #9F8CF1, #FFFFFF, 212829, DM6_central2, #FFEAB6, #202428, SMPpv2_ventral, 791739, #4ECCCB, #FFFFFF, 472132, ALad1__prim, #EAA775, #FFFFFF, 337782, SMPpv2_dorsal, #FFDDE5, #202428, MD0__prim, 864257, #FBD44A, #FFFFFF, MX0__prim, 79006, #46A1FD, #FFFFFF, DILP__prim, 69103, #ADDF84, #FFFFFF, VLPl2_lateral, 764400, #DC82D2, #FFFFFF, DM1_posterior, 912445, #89D2EA, #FFFFFF, SLPal3_and_SLPal4_dorsal, 457802, #59CB74, #FFFFFF, VPNl&d1_medial_Lee, 711486, #F4667C, #FFFFFF, VPNd3, 285703, #9860E5, #FFFFFF, VPNd2, #C2C2C2, #FFFFFF, 861927, VPNv2, #4ECCCB, #FFFFFF, 808867, VPNp2, #9F8CF1, #FFFFFF, 165924, DM2_or_DM3_posterior, 60684, #EAA775, #FFFFFF, VPNv1, #FBD44A, #FFFFFF, 780536, VPNp3, #46A1FD, #FFFFFF, 248547, SLPpm4, 121448, #ADDF84, #FFFFFF, troll-b, #DC82D2, #FFFFFF, 744328, outa, #89D2EA, #FFFFFF, 89924, MTe49, 927894, #59CB74, #FFFFFF #> 14 NULL #> 15 FALSE, FALSE, , custom_format #> 16 FALSE, FALSE, , custom_format #> 17 NULL #> 18 FALSE, FALSE, , custom_format #> 19 NULL #> 20 FALSE, #> 21 FALSE, undefined #> 22 FALSE, FALSE, , custom_format #> 23 FALSE, FALSE, , custom_format #> 24 NULL #> 25 FALSE, #> 26 FALSE, #> 27 NULL #> 28 FALSE, #> 29 FALSE, undefined #> 30 adequate, #ADDF84, #FFFFFF, 615586, #9CCF72, complete, #59CB74, #FFFFFF, 399046, #4EB867, incomplete, #EAA775, #FFFFFF, 896972, #D59361, merge_error, #F4667C, #FFFFFF, 96230, #DC556A, needs_extending, #46A1FD, #FFFFFF, 654216, #3C8FE4, tiny, #E9E9E9, #202428, 11704, #DADADA, unassessed, #DAD7FF, #202428, 555449, #C3BEEF, unknown, #C2C2C2, #FFFFFF, 815844, #ADADAD, wrong_hemilineage, #FBD44A, #FFFFFF, 275663, #E5C142, wrong_side, #FFFCB5, #202428, 288083, #E8E79D, bad_nucleus, #DC82D2, #FFFFFF, #D166C5, 997771, duplicate, #4ECCCB, #FFFFFF, 230512, not_a_neuron, #9860E5, #FFFFFF, 953023, 367098, proofread, #FFD4FF, #202428, to_review, #59CB74, #FFFFFF, #4EB867, 478080, hard, #F4667C, #FFFFFF, 275338, tadpole, #FFDDE5, #202428, 295683, #EDC4C1, large_fragment, #89D2EA, #FFFFFF, 597301, 162109, NA, #DAD7FF, #202428, 463206, outlier_bio, #EAA775, #FFFFFF, 82369, outlier_seg, #B7CEF9, #202428, 78729, adequat, #FFD9C8, #202428, 527429, fragment, #9860E5, #FFFFFF, NEEDS4, #46A1FD, #FFFFFF, 835587 #> 31 FALSE #> 32 FALSE, undefined #> 33 NULL #> 34 NULL #> 35 YYYY-MM-DD HH:mm #> 36 NULL #> 37 FALSE, FALSE, , custom_format #> 38 FALSE, FALSE, , custom_format #> 39 FALSE, FALSE, , custom_format #> 40 FALSE, FALSE, , custom_format #> 41 NCC, #4ECCCB, #FFFFFF, #45BAB9, 197106, CV, #C2C2C2, #FFFFFF, #ADADAD, 467618, AN, #89D2EA, #FFFFFF, #7BC0D6, 329258, MxLbN, #F4667C, #FFFFFF, #DC556A, 771256, PhN, #FBD44A, #FFFFFF, #E5C142, 472174, aPhN, #DC82D2, #FFFFFF, #D166C5, 902576, 843153, ON, #FFD9C8, #202428, 129288, OCN, #FFFCB5, #202428 #> 42 FALSE, FALSE #> 43 FALSE, FALSE #> 44 FALSE, FALSE, , custom_format #> 45 FALSE, FALSE, , custom_format #> 46 FALSE, FALSE, , custom_format # }"},{"path":"https://natverse.org/fafbseg/reference/flytable_set_celltype.html","id":null,"dir":"Reference","previous_headings":"","what":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","title":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","text":"Set flytable cell type columns set root ids","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_set_celltype.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","text":"","code":"flytable_set_celltype( ids, cell_type = NULL, hemibrain_type = NULL, user = \"GJ\", supervoxel_id = NULL, DryRun = TRUE, table = c(\"info\", \"optic\"), copy_hemibrain_type = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flytable_set_celltype.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","text":"ids form understood flywire_ids. data.frame supervoxel_id column also present used ensure root ids efficiently mapped latest version. cell_type Character vector cell types - can either length 1 length ids. hemibrain_type also used set cell_type missing copy_hemibrain_type=TRUE user user initials (can vector length ids) supervoxel_id Supervoxel ids corresponding root ids argument. DryRun Default value (T) return dataframe used update table name flytable table update (currently support info (central brain) optic tables. copy_hemibrain_type recommendation now ** set cell_type hemibrain_type one provided, default FALSE. ... Additional columns update flytable","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_set_celltype.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","text":"default DryRun=TRUE can see happen apply changes. careful! Undoing changes hard, sometimes impossible exactly. doubt talk Greg, Philipp et al making programmatic updates. Since flytable always keeps root ids date (least every 30m), ids argument must mapped onto latest ids (using flywire_updateids) data can uploaded flytable. much efficient provide supervoxel id neuron.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable_set_celltype.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set the flytable cell type and other columns for a set of root ids — flytable_set_celltype","text":"","code":"if (FALSE) { flytable_set_celltype('https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/4668606109450240', hemibrain_type = 'vLN25', fbbt_id='FBbt_20003784', DryRun = T) }"},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":null,"dir":"Reference","previous_headings":"","what":"Update or append rows in a flytable database — flytable_update_rows","title":"Update or append rows in a flytable database — flytable_update_rows","text":"flytable_update_rows updates existing rows table, returning TRUE success. flytable_append_rows appends data existing table, returning TRUE success. flytable_nrow returns number rows one flytable tables using SQL COUNT query.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update or append rows in a flytable database — flytable_update_rows","text":"","code":"flytable_update_rows( df, table, base = NULL, append_allowed = TRUE, chunksize = 1000L, ... ) flytable_append_rows(df, table, base = NULL, chunksize = 1000L, ...) flytable_nrow(table, base = NULL)"},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update or append rows in a flytable database — flytable_update_rows","text":"df data.frame containing data upload including _id column can identify row remote table. table Character vector naming table base Character vector naming seatable base (recommended) Base object returned flytable_base (expert use). append_allowed Whether rows without row identifiers can appended. chunksize split large requests smaller ones max many rows. ... Additional arguments passed pbsapply might include cl=2 specify number parallel jobs run.","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update or append rows in a flytable database — flytable_update_rows","text":"Logical indicating success, invisibly (failures normally cause premature termination errors written console).","code":""},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Update or append rows in a flytable database — flytable_update_rows","text":"seatable automatically maintains unique id row _id column. returned flytable_query friends. modify data want update , need keep column containing row _id. need provide _id column appending new rows. Indeed get warning . chunksize argument required seems maximum 1000 rows per update action.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flytable_update_rows.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Update or append rows in a flytable database — flytable_update_rows","text":"","code":"if (FALSE) { fruit=flytable_list_rows('testfruit') flytable_update_rows(table='testfruit', fruit[1:2, c(1,4:6)]) } if (FALSE) { flytable_append_rows(table=\"testfruit\", data.frame(fruitname='lemon', person='David', nid=4)) }"},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":null,"dir":"Reference","previous_headings":"","what":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"flywire2fafb maps points FlyWire->FAFB fafb2flywire maps points FAFB->FlyWire","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"","code":"flywire2fafb( xyz, method = c(\"mapmany\", \"map1\"), chunksize = 40000, swap = FALSE, ... ) fafb2flywire( xyz, method = c(\"mapmany\", \"map1\"), chunksize = 40000, swap = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"xyz Nx3 matrix points method Whether map many points (default) just one chunksize number points send server mapping many points . swap TRUE applies deformation field opposite direction e.g. give coarse mapping points FAFB->FlyWire. wrong may useful. ... Additional arguments passed httr::GET/POST operation","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"Nx3 matrix points","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"Note can also access FlyWire<->FAFB bridging registrations via xform_brain series functions. allow transform kinds 3D data objects, whereas flywire2fafb function restricted plain 3D coordinates. See examples. Mapping single points unlikely useful, may wish adjust chunksize argument send points risk possible server timeouts. default value quite conservative. swap=TRUE displacements applied opposite direction intended. can used provide coarse inverse mapping feed FAFB points. wrong useful inverse mapping available can get closer right place FlyWire just assuming FAFB14 FlyWire space. works deformations mostly fairly smooth scale FAFB-FlyWire displacements. Operationally find residual displacements typically order 100 nm using procedure. Since 2020-08-08 real inverse available, now historical interest.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire2fafb.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map points between FlyWire v1 and FAFB14 space (xyz nm) — flywire2fafb","text":"","code":"# identified location in FAFB14 p.fafb.nm <- cbind(477042, 284535, 90680) p.fafb.raw <- p.fafb.nm/c(4,4,40) # corresponding location in FlyWire p.flywire.raw <- cbind(118865, 71338, 2267) p.flywire.nm <- p.flywire.raw * c(4,4,40) # check displacement flywire2fafb(p.flywire.nm)-p.fafb.nm #> X Y Z #> [1,] 3 -1 0 # check what happens when you apply the inverse fafb2flywire(p.fafb.nm)-p.flywire.nm #> X Y Z #> [1,] -3 2 0 data(\"AV4b1\", package='catmaid') set.seed(42) before=xyzmatrix(AV4b1)[sample(nvertices(AV4b1), size=2000), ] after=fafb2flywire(before) d=sqrt(rowSums((before-after)^2)) hist(d, br=20, main=\"FAFB14 - FlyWire Displacements\", xlab=\"d /nm\") if (FALSE) { AV4b1.flywire <- xform_brain(AV4b1, reference=\"FlyWire\", sample=\"FAFB14\") plot3d(neuronlist(AV4b1.flywire, AV4b1)) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"Get adjacency matrix predicted synaptic connectivity within set specific flywire bodies. can specify single pool ids separate input (upstream) output (downstream) ids. contrast flywire_partner_summary returns connections amongst defined set ids rather possible partners.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"","code":"flywire_adjacency_matrix( rootids = NULL, inputids = NULL, outputids = NULL, sparse = FALSE, remove_autapses = TRUE, cleft.threshold = 0, Verbose = interactive(), method = c(\"auto\", \"spine\", \"sqlite\") )"},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"rootids flywire root ids bodies fetch connectivity information. inputids, outputids identifiers input output bodies (use alternative rootids) sparse Whether return sparse matrix (default FALSE) remove_autapses whether remove autapses (self-connections); erroneous. cleft.threshold threshold cleft score calculated Buhmann et al 2019 (default 0, used 30-100 increase specificity) Verbose Logical indication whether print status messages query (default T interactive, F otherwise). method Whether use local SQLite database remote spine service synapse data. default auto uses local database available (45GB faster).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"matrix named rows inputs columns outputs. matrix square rootids specified may otherwise rectangular. Defaults regular (dense) matrix unless sparse=TRUE.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"limitations","dir":"Reference","previous_headings":"","what":"Limitations","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"function currently much efficient local SQLite tables available; absence queries remote spine server possible currently transfer data necessary. Future work allow spine queries consider pre postsynaptic supervoxel ids part query. also careful many neurons attempt query. function designed handle queries involving hundreds neurons spine method especially sensitive overloading. intention, might better using flywire_partners flywire_partner_summary fetch data chunks manually filtering ensemble interest.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"normalisation","dir":"Reference","previous_headings":"","what":"Normalisation","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"always important give careful thought data normalisation analysing connectivity matrices. general feel normalising total input onto target cell makes sense, since approximates effectiveness input making target cell fire. However include inputs onto target cells even normalisation difficulties may better use raw counts.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch the synaptic adjacency matrix for a set of flywire neurons — flywire_adjacency_matrix","text":"","code":"# \\donttest{ u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5392055178100736\" sm=flywire_adjacency_matrix(u) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist # scaled to give proportion of inputs onto each target cell heatmap(sm, scale='col') # scale='none' => raw counts # nb note use of assignment and keep.dendro so we can use dendrogram later h=heatmap(sm, scale='none', keep.dendro = TRUE) # same but with the cleft threshold applied smc=flywire_adjacency_matrix(u, cleft.threshold = 30) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist # note the reuse of the earlier dendrogram to return col order for comparison heatmap(smc, scale='none', Colv=h$Colv) # just a single upstream neuron sm2=flywire_adjacency_matrix(inputids=\"720575940625862385\", outputids=u) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix2.html","id":null,"dir":"Reference","previous_headings":"","what":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","title":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","text":"Fast adjacency matrices based flywire connectome dumps","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","text":"","code":"flywire_adjacency_matrix2( rootids = NULL, inputids = NULL, outputids = NULL, sparse = TRUE, threshold = 0, version = NULL, Verbose = interactive() )"},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","text":"rootids flywire root ids bodies fetch connectivity information. inputids, outputids identifiers input output bodies (use alternative rootids) sparse Whether return sparse matrix (default FALSE) threshold flywire_partner_summary return partners greater number connections query neuron(s) (default 0 returns connections) version Optional CAVE version. default value NULL uses latest data dump available unless options(fafbseg.flywire_connectome_data_version) set (can conveniently using flywire_connectome_data_version()). Verbose Logical indication whether print status messages query (default T interactive, F otherwise).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","text":"sparse matrix (Matrix::dgCMatrix) regular matrix.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_adjacency_matrix2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fast adjacency matrices based on flywire connectome dumps — flywire_adjacency_matrix2","text":"","code":"if (FALSE) { dm2pnkc=flywire_adjacency_matrix2(inputids=\"DM2_lPN_R\", outputids=\"class:Kenyon_Cell_R\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":null,"dir":"Reference","previous_headings":"","what":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"Low level access Flywire CAVE annotation system","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"","code":"flywire_cave_client( datastack_name = getOption(\"fafbseg.cave.datastack_name\", \"flywire_fafb_production\") )"},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"datastack_name defaults \"flywire_fafb_production\". See https://global.daf-apis.com/info/ options.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"caveclient.frameworkclient.CAVEclientFull Python module wrapped reticulate.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"depends installation Python caveclient library. See flywire_cave_query details.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_client.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Low level access to the Flywire CAVE annotation system — flywire_cave_client","text":"","code":"# \\donttest{ fac <- flywire_cave_client() fac$annotation$get_tables() #> [1] \"proofreading_status_public_v1\" #> [2] \"fly_synapses_neuropil_v2\" #> [3] \"synaptic_clefts\" #> [4] \"hierarchical_neuron_annotations\" #> [5] \"neuron_information_v2\" #> [6] \"fly_synapses_neuropil_v5\" #> [7] \"neuron_information_vtest\" #> [8] \"synapses_nt_v1\" #> [9] \"fly_synapses_neuropil\" #> [10] \"proofreading_review_public_vtest\" #> [11] \"braincircuits_annotation_test\" #> [12] \"valid_synapses_nt_vtest\" #> [13] \"neuron_information_v1\" #> [14] \"nuclei_v1\" #> [15] \"valid_synapses_nt_v2\" #> [16] \"valid_synapses_nt_v1\" #> [17] \"fly_synapses_neuropil_v4\" #> [18] \"hemilineages\" #> [19] \"braincircuits_annotation_test2\" #> [20] \"hemibrain_matched_types\" #> [21] \"neuron_representative_coordinates_v1\" #> [22] \"hierarchical_cell_types_v1\" #> [23] \"cambridge_celltypes\" #> [24] \"fly_synapses_neuropil_v3\" #> [25] \"proofreading_review_public_v1\" #> [26] \"cambridge_celltypes_v2\" #> [27] \"proofread_neurons\" fac$annotation$get_table_metadata('nuclei_v1') #> $id #> [1] 8 #> #> $schema_type #> [1] \"nucleus_detection\" #> #> $table_name #> [1] \"nuclei_v1__fly_v31\" #> #> $valid #> [1] TRUE #> #> $created #> [1] \"2021-08-13T18:01:55.211016\" #> #> $deleted #> NULL #> #> $user_id #> [1] \"2\" #> #> $description #> [1] \"\\nFlyWire nucleus description\\nNucleus version: 20210322\\n\\nNuclei in this table consist of center points (in nm), volume (in μm3), and bounding boxes (in nm).\\n\\nThe nucleus segmentation was generated by Shang Mu (smu@princeton.edu, Seung Lab at Princeton University) using a 2D convolutional neural network (CNN) and heuristic interpolations. The training data was assembled from annotations by Selden Koolman, Merlin Moore, Sarah Morejohn, Ben Silverman, Kyle Willie, Ryan Willie, Szi-chieh Yu and Shang Mu.\\n\\nAs this data was generated using a 2D, rather than 3D, neural network, defects are present in the detected nuclei, particularly where there are large defects in section alignment or a number of consecutive missing sections.\\n\\nFalse positive fragments, nucleus fragments and partial nuclei are the most common type of defects. A simple, rudimentary method for cleaning up is to disregard small fragments by thresholding by segment size or by the z-dimension of the bounding boxes. A size threshold of 2000 voxels (0.08 μm3) was already applied in producing this segmentation.\\n\\nA minimal number of nucleus merger instances have been observed, caused by section alignment defects or close nuclei appositions in certain non-neuronal cell clusters.\\n\\nWhen using the nucleus annotations, please acknowledge Shang Mu and let him know about your use case.\\n\\nWe encourage making (and using) improvements to this data based on the information provided (for example, utilizing bounding box dimensions and/or the segmentation to find and merge incorrectly split partial nuclei), and such improvements should be discussed with Shang. Data derived solely from this work should be similarly made available on this platform at the time of use in any publication.\\n\" #> #> $notice_text #> NULL #> #> $reference_table #> NULL #> #> $flat_segmentation_source #> [1] \"precomputed://gs://neuroglancer/drosophila_v0/nucleus/v5_z_intp_intp/seg\" #> #> $write_permission #> [1] \"PRIVATE\" #> #> $read_permission #> [1] \"PUBLIC\" #> #> $last_modified #> [1] \"2022-10-25T19:49:21.621037\" #> #> $segmentation_source #> [1] \"\" #> #> $pcg_table_name #> [1] \"fly_v31\" #> #> $last_updated #> [1] \"2024-01-26T23:00:00.312383\" #> #> $annotation_table #> [1] \"nuclei_v1\" #> #> $voxel_resolution #> [1] 1 1 1 #> # annotation tables that have been materialised in order to map XYZ # points onto current root ids (and immutable supervoxel ids) # typically the same as fac$annotation$get_tables() fac$materialize$get_tables() #> [1] \"proofreading_status_public_v1\" #> [2] \"fly_synapses_neuropil_v2\" #> [3] \"synaptic_clefts\" #> [4] \"hierarchical_neuron_annotations\" #> [5] \"neuron_information_v2\" #> [6] \"fly_synapses_neuropil_v5\" #> [7] \"neuron_information_vtest\" #> [8] \"synapses_nt_v1\" #> [9] \"fly_synapses_neuropil\" #> [10] \"proofreading_review_public_vtest\" #> [11] \"braincircuits_annotation_test\" #> [12] \"valid_synapses_nt_vtest\" #> [13] \"nuclei_v1\" #> [14] \"valid_synapses_nt_v2\" #> [15] \"valid_synapses_nt_v1\" #> [16] \"fly_synapses_neuropil_v4\" #> [17] \"hemilineages\" #> [18] \"neuron_representative_coordinates_v1\" #> [19] \"cambridge_celltypes\" #> [20] \"fly_synapses_neuropil_v3\" #> [21] \"proofreading_review_public_v1\" #> [22] \"cambridge_celltypes_v2\" #> [23] \"proofread_neurons\" info=fac$info$get_datastack_info() # the default synapse table for the dataset info$synapse_table #> [1] \"synapses_nt_v1\" # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":null,"dir":"Reference","previous_headings":"","what":"Query the FlyWire CAVE annotation system — flywire_cave_query","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"Query FlyWire CAVE annotation system","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"","code":"flywire_cave_query( table, datastack_name = getOption(\"fafbseg.cave.datastack_name\", \"flywire_fafb_production\"), version = NULL, timestamp = NULL, live = is.null(version) && is.null(timestamp), filter_in_dict = NULL, filter_out_dict = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"table name table (view, see views section) query datastack_name defaults \"flywire_fafb_production\". See https://global.daf-apis.com/info/ options. version optional CAVE materialisation version number. See details examples. timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. live Whether use live query mode, updates root ids current value. filter_in_dict, filter_out_dict Optional arguments consisting key value lists restrict returned rows (keeping matches filtering matches). Commonly used selected rows specific neurons. See examples CAVE documentation details. ... Additional arguments query method. See examples details.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"tibble. Note xyzmatrix can used single columns containing XYZ locations.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"CAVE (Connectome Annotation Versioning Engine) provides shared infrastructure number connectomics projects involving Sebastian Seung's group Princeton collaborators Allen Institute. backend system running servers Python client end users. can find https://caveclient.readthedocs.io/ well looking Python notebooks github repo https://github.com/seung-lab/CAVEclient. annotation system shares authentication infrastructure rest FlyWire API (see flywire_set_token).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"cave-materialisation-versions-and-timestamps","dir":"Reference","previous_headings":"","what":"CAVE Materialisation Versions and Timestamps","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"CAVE concept table snapshots identified integer materialization version number. cases may wish query table defined version number can avoid root_ids changing analysis. calls also faster since root id updates required. Note however materialisation versions expire point corresponding version database expunged. However still possible find timestamp expired materialisation version. flywire_cave_query automatically using flywire_timestamp. circumstances queries slower (quite possibly slower live query) since root ids must recalculated match timestamp. CAVE's ability handle different timepoints key analysis continually evolving segmentation frankly little difficult users work . find things simplest either use long-term support (LTS) version, expire 630 version June 2023 public release. use latest CAVE version","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"cave-views","dir":"Reference","previous_headings":"","what":"CAVE Views","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"addition regular database tables, CAVE provides support views. based SQL query typically aggregates combines multiple tables. example aggregation might define total number output synapses selected neurons. present several restrictions views. example, can fetch views using unexpired materialisation version ( specify timepoint using timestamp) . Furthermore filter_in, filter_out queries using columns created SQL statement may possible.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_cave_query.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Query the FlyWire CAVE annotation system — flywire_cave_query","text":"","code":"# \\donttest{ # note use of limit to restrict the number of rows (must be integer) n10=flywire_cave_query(table = 'nuclei_v1', limit=10L) head(as.data.frame(n10)) #> id created superceded_id valid volume pt_supervoxel_id #> 1 2338 2021-06-23 19:56:18 NA t 0.2616115 0 #> 2 3078 2021-06-23 19:55:39 NA t 4.1247949 0 #> 3 3292 2021-06-23 19:56:19 NA t 0.2737357 0 #> 4 3502 2021-06-23 19:55:39 NA t 6.7878502 0 #> 5 4404 2021-06-23 19:55:51 NA t 0.8473395 0 #> 6 4446 2021-06-23 19:55:50 NA t 58.8006195 0 #> pt_root_id pt_position bb_start_position bb_end_position #> 1 0 95520, 254368, 218600 94528, 253184, 218520 96384, 255776, 218680 #> 2 0 97472, 252352, 218040 96128, 248992, 217640 98944, 254720, 218600 #> 3 0 97280, 250784, 219320 96544, 249408, 219240 98080, 251744, 219520 #> 4 0 98304, 253376, 216480 96928, 250752, 215240 99936, 256000, 217240 #> 5 0 81280, 295968, 186680 80640, 294496, 186320 82048, 297600, 187440 #> 6 0 84128, 291584, 193400 81504, 288000, 190240 87104, 295904, 196280 # } if (FALSE) { nuclei_v1=flywire_cave_query(table = 'nuclei_v1') points3d(xyzmatrix(nuclei_v1$pt_position)) library(elmr) # calculate signed distance to FAFB surface # NB this surface is not a perfect fit in the optic lobes nuclei_v1$d=pointsinside(xyzmatrix(nuclei_v1$pt_position), FAFB.surf, rval = 'dist') points3d(xyzmatrix(nuclei_v1$pt_position), col=matlab::jet.colors(20)[cut(nuclei_v1$d,20)]) plot3d(FAFB) } # Example of a query on a table if (FALSE) { # the Princeton (mostly) and Cambridge groups have tagged some bodies as # not a neuron - these are often glia. nans=flywire_cave_query('neuron_information_v2', filter_in_dict = list(tag='not a neuron')) nrow(nans) table(nans$user_id) } if (FALSE) { psp_351=flywire_cave_query(table = 'proofreading_status_public_v1', version=351) # get the last listed materialisation version fcc=flywire_cave_client() lastv=tail(fcc$materialize$get_versions(), n=1) # pull that psp_last=flywire_cave_query(table = 'proofreading_status_public_v1', version=lastv) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":null,"dir":"Reference","previous_headings":"","what":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"Summarise edits one FlyWire segment ids","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"","code":"flywire_change_log( x, filtered = TRUE, tz = \"UTC\", root_ids = TRUE, OmitFailures = TRUE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"x One flywire segment ids (character vector recommended format accepted flywire_ids work). filtered Whether filter edits unlikely relate current state neuron (default TRUE, see details). tz Time zone edit timestamps. Defaults \"UTC\" .e. Universal Time, Coordinated. Set \"\" current timezone. See .POSIXct details. root_ids Whether look root ids /change. Default TRUE. June 2021 root_ids always returned, noop. OmitFailures Whether omit neurons API timeout error. default value (TRUE) skip errors, NA) result hard stop error. See nlapply details. ... Additional arguments passed flywire_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"data frame values itemize addition filtered=FALSE, in_neuron is_relevant","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"filtered=TRUE following removed edits outside given root id - meaning edits history cell affected part arbour since cut . edits since undone inverse operation (often temporary splits made reviewing neuron.)","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_change_log.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Summarise edits for one or more FlyWire segment ids — flywire_change_log","text":"","code":"# \\donttest{ flywire_change_log(\"720575940619010932\") #> operation_id timestamp user_id #> 0 194549 2020-09-03 19:33:23 397 #> 1 194550 2020-09-03 19:37:26 397 #> 2 194551 2020-09-03 19:38:12 397 #> 3 194552 2020-09-03 19:40:33 397 #> 4 194582 2020-09-03 20:05:41 397 #> 5 194584 2020-09-03 20:06:51 397 #> before_root_ids after_root_ids is_merge #> 0 720575940615250973 720575940625952497 FALSE #> 1 720575940622305363 720575940625952497 720575940603341158 TRUE #> 2 720575940603341158 720575940620629528 FALSE #> 3 720575940620629528 720575940637849454 720575940625315922 TRUE #> 4 720575940625315922 720575940635457646 720575940610162858 TRUE #> 5 720575940610162858 720575940619010932 FALSE #> user_name user_affiliation #> 0 Marlon Blanquart Greg Jefferis Lab #> 1 Marlon Blanquart Greg Jefferis Lab #> 2 Marlon Blanquart Greg Jefferis Lab #> 3 Marlon Blanquart Greg Jefferis Lab #> 4 Marlon Blanquart Greg Jefferis Lab #> 5 Marlon Blanquart Greg Jefferis Lab flywire_change_log(\"720575940619010932\", filtered = FALSE) #> operation_id timestamp user_id #> 0 194549 2020-09-03 19:33:23 397 #> 1 194550 2020-09-03 19:37:26 397 #> 2 194551 2020-09-03 19:38:12 397 #> 3 194552 2020-09-03 19:40:33 397 #> 4 194582 2020-09-03 20:05:41 397 #> 5 194584 2020-09-03 20:06:51 397 #> before_root_ids after_root_ids is_merge in_neuron #> 0 720575940615250973 720575940625952497 FALSE TRUE #> 1 720575940622305363 720575940625952497 720575940603341158 TRUE TRUE #> 2 720575940603341158 720575940620629528 FALSE TRUE #> 3 720575940620629528 720575940637849454 720575940625315922 TRUE TRUE #> 4 720575940625315922 720575940635457646 720575940610162858 TRUE TRUE #> 5 720575940610162858 720575940619010932 FALSE TRUE #> is_relevant user_name user_affiliation #> 0 TRUE Marlon Blanquart Greg Jefferis Lab #> 1 TRUE Marlon Blanquart Greg Jefferis Lab #> 2 TRUE Marlon Blanquart Greg Jefferis Lab #> 3 TRUE Marlon Blanquart Greg Jefferis Lab #> 4 TRUE Marlon Blanquart Greg Jefferis Lab #> 5 TRUE Marlon Blanquart Greg Jefferis Lab # with a flywire URL u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5409525645443072\" flywire_change_log(u) #> id operation_id timestamp user_id #> 1 720575940621039145 1710 2019-08-03 23:17:28 4 #> 2 720575940621039145 1715 2019-08-03 23:21:22 4 #> 3 720575940621039145 1716 2019-08-03 23:22:16 4 #> 4 720575940621039145 1735 2019-08-03 23:31:40 4 #> 5 720575940621039145 1736 2019-08-03 23:31:57 4 #> 6 720575940621039145 1737 2019-08-03 23:32:08 4 #> 7 720575940621039145 1738 2019-08-03 23:32:20 4 #> 8 720575940621039145 1739 2019-08-03 23:32:30 4 #> 9 720575940621039145 1742 2019-08-03 23:33:22 4 #> 10 720575940621039145 1744 2019-08-03 23:33:56 4 #> 11 720575940621039145 1748 2019-08-03 23:34:34 4 #> 12 720575940621039145 1750 2019-08-03 23:34:48 4 #> 13 720575940621039145 1752 2019-08-03 23:35:15 4 #> 14 720575940621039145 1753 2019-08-03 23:35:31 4 #> 15 720575940621039145 1755 2019-08-03 23:35:50 4 #> 16 720575940621039145 1757 2019-08-03 23:36:12 4 #> 17 720575940621039145 1759 2019-08-03 23:36:26 4 #> 18 720575940621039145 1761 2019-08-03 23:36:45 4 #> 19 720575940621039145 1763 2019-08-03 23:37:06 4 #> 20 720575940621039145 1766 2019-08-03 23:37:33 4 #> 21 720575940621039145 1768 2019-08-03 23:37:55 4 #> 22 720575940621039145 1770 2019-08-03 23:38:14 4 #> 23 720575940621039145 1771 2019-08-03 23:38:27 4 #> 24 720575940621039145 1776 2019-08-03 23:39:39 4 #> 25 720575940621039145 1778 2019-08-03 23:42:10 4 #> 26 720575940621039145 1781 2019-08-03 23:47:50 4 #> 27 720575940621039145 1782 2019-08-03 23:49:56 4 #> 28 720575940621039145 1784 2019-08-03 23:55:56 4 #> 29 720575940621039145 1785 2019-08-03 23:56:10 4 #> 30 720575940621039145 1786 2019-08-03 23:56:36 4 #> 31 720575940621039145 1787 2019-08-03 23:56:48 4 #> 32 720575940621039145 1788 2019-08-03 23:57:10 4 #> 33 720575940621039145 1896 2019-08-04 02:42:31 4 #> 34 720575940621039145 2231 2019-08-08 16:45:15 4 #> 35 720575940621039145 2300 2019-08-08 19:39:12 4 #> 36 720575940621039145 2346 2019-08-09 21:51:43 4 #> 37 720575940621039145 2377 2019-08-12 18:19:12 4 #> 38 720575940621039145 2423 2019-08-14 17:16:15 4 #> 39 720575940621039145 2742 2019-08-16 17:14:54 4 #> 40 720575940621039145 8042 2019-09-05 23:10:59 4 #> 41 720575940621039145 8046 2019-09-05 23:22:12 4 #> 42 720575940621039145 8047 2019-09-05 23:26:27 4 #> 43 720575940621039145 8049 2019-09-05 23:29:06 4 #> 44 720575940621039145 8052 2019-09-05 23:32:15 4 #> 45 720575940621039145 8085 2019-09-06 00:28:46 4 #> 46 720575940621039145 8086 2019-09-06 00:30:04 4 #> 47 720575940621039145 8091 2019-09-06 00:34:02 4 #> 48 720575940621039145 11049 2019-09-16 11:57:40 13 #> 49 720575940621039145 11194 2019-09-16 19:22:17 13 #> 50 720575940621039145 20627 2019-10-18 18:04:25 16 #> 51 720575940621039145 40816 2020-01-07 18:48:38 13 #> 52 720575940621039145 40819 2020-01-07 18:50:06 13 #> 53 720575940621039145 52005 2020-02-03 18:42:45 26 #> 54 720575940621039145 52065 2020-02-03 19:42:24 26 #> 55 720575940621039145 52135 2020-02-03 20:34:35 26 #> 56 720575940621039145 52141 2020-02-03 20:35:32 26 #> 57 720575940621039145 52142 2020-02-03 20:36:01 26 #> 58 720575940621039145 52146 2020-02-03 20:40:29 26 #> 59 720575940626877799 4729 2019-08-23 21:17:22 12 #> 60 720575940626877799 6163 2019-08-28 20:48:48 12 #> 61 720575940626877799 10877 2019-09-13 16:00:25 13 #> 62 720575940626877799 10903 2019-09-13 16:52:47 13 #> 63 720575940626877799 10904 2019-09-13 16:57:06 13 #> 64 720575940626877799 10906 2019-09-13 16:58:52 13 #> 65 720575940626877799 10907 2019-09-13 17:01:45 13 #> 66 720575940626877799 10909 2019-09-13 17:11:08 13 #> 67 720575940626877799 10912 2019-09-13 17:14:06 13 #> 68 720575940626877799 10937 2019-09-13 17:37:41 13 #> 69 720575940626877799 10939 2019-09-13 17:43:53 13 #> 70 720575940626877799 10940 2019-09-13 17:44:28 13 #> 71 720575940626877799 10947 2019-09-13 18:00:31 13 #> 72 720575940626877799 10949 2019-09-13 18:04:35 13 #> 73 720575940626877799 10952 2019-09-13 18:08:03 13 #> 74 720575940626877799 10956 2019-09-13 18:12:46 13 #> 75 720575940626877799 10967 2019-09-13 18:19:11 13 #> 76 720575940626877799 10969 2019-09-13 18:20:48 13 #> 77 720575940626877799 10971 2019-09-13 18:22:16 13 #> 78 720575940626877799 10972 2019-09-13 18:24:20 13 #> 79 720575940626877799 10981 2019-09-13 18:26:26 13 #> 80 720575940626877799 11363 2019-09-17 14:53:32 17 #> 81 720575940626877799 11414 2019-09-17 16:03:08 17 #> 82 720575940626877799 33530 2019-12-13 19:16:56 84 #> 83 720575940626877799 46345 2020-01-17 18:27:27 84 #> 84 720575940626877799 46350 2020-01-17 18:28:49 84 #> 85 720575940626877799 46351 2020-01-17 18:30:32 84 #> 86 720575940626877799 46352 2020-01-17 18:33:23 84 #> 87 720575940626877799 107453 2020-04-27 18:44:42 104 #> 88 720575940626877799 107454 2020-04-27 18:44:46 104 #> 89 720575940626877799 107455 2020-04-27 18:44:53 104 #> 90 720575940626877799 107456 2020-04-27 18:45:00 104 #> 91 720575940626877799 107460 2020-04-27 18:45:43 104 #> 92 720575940626877799 107461 2020-04-27 18:45:46 104 #> 93 720575940626877799 107466 2020-04-27 18:46:08 104 #> 94 720575940626877799 107467 2020-04-27 18:46:14 104 #> 95 720575940626877799 107468 2020-04-27 18:48:06 104 #> 96 720575940626877799 107480 2020-04-27 19:03:54 104 #> 97 720575940626877799 107482 2020-04-27 19:07:39 104 #> 98 720575940626877799 107487 2020-04-27 19:17:14 104 #> 99 720575940626877799 107494 2020-04-27 19:30:34 104 #> 100 720575940626877799 107495 2020-04-27 19:30:47 104 #> 101 720575940626877799 107557 2020-04-27 20:40:33 104 #> 102 720575940626877799 107589 2020-04-27 21:10:52 104 #> 103 720575940626877799 107590 2020-04-27 21:11:03 104 #> 104 720575940626877799 107592 2020-04-27 21:11:47 104 #> 105 720575940626877799 107603 2020-04-27 21:20:09 104 #> 106 720575940626877799 107604 2020-04-27 21:20:13 104 #> 107 720575940626877799 107635 2020-04-27 21:31:33 104 #> 108 720575940626877799 107650 2020-04-27 22:15:31 104 #> 109 720575940626877799 107651 2020-04-27 22:15:46 104 #> 110 720575940626877799 107652 2020-04-27 22:15:51 104 #> 111 720575940626877799 107653 2020-04-27 22:15:57 104 #> 112 720575940626877799 107656 2020-04-27 22:27:41 104 #> 113 720575940626877799 107657 2020-04-27 22:29:06 104 #> 114 720575940626877799 107660 2020-04-27 22:31:44 104 #> 115 720575940626877799 107661 2020-04-27 22:37:56 104 #> 116 720575940626877799 107667 2020-04-27 22:57:59 104 #> 117 720575940626877799 107668 2020-04-27 22:58:05 104 #> 118 720575940626877799 107699 2020-04-27 23:36:50 104 #> 119 720575940626877799 107710 2020-04-27 23:42:21 104 #> 120 720575940626877799 107726 2020-04-28 00:43:21 104 #> 121 720575940626877799 107729 2020-04-28 00:48:13 104 #> 122 720575940626877799 107735 2020-04-28 01:00:38 104 #> 123 720575940626877799 107737 2020-04-28 01:09:32 104 #> 124 720575940626877799 107738 2020-04-28 01:11:31 104 #> 125 720575940626877799 107739 2020-04-28 01:12:12 104 #> 126 720575940626877799 107742 2020-04-28 01:21:57 104 #> 127 720575940626877799 107766 2020-04-28 01:47:17 104 #> 128 720575940626877799 107767 2020-04-28 01:47:22 104 #> 129 720575940626877799 107783 2020-04-28 02:06:45 104 #> 130 720575940626877799 107797 2020-04-28 02:55:10 104 #> 131 720575940626877799 107798 2020-04-28 02:59:17 104 #> 132 720575940626877799 107799 2020-04-28 03:01:32 104 #> 133 720575940626877799 107800 2020-04-28 03:02:02 104 #> 134 720575940626877799 107801 2020-04-28 03:03:27 104 #> 135 720575940626877799 107803 2020-04-28 03:08:37 104 #> 136 720575940626877799 107806 2020-04-28 03:22:03 104 #> 137 720575940626877799 107807 2020-04-28 03:22:07 104 #> 138 720575940626877799 107808 2020-04-28 03:22:49 104 #> 139 720575940626877799 107809 2020-04-28 03:22:52 104 #> 140 720575940626877799 107810 2020-04-28 03:22:56 104 #> 141 720575940626877799 107948 2020-04-28 18:23:53 104 #> 142 720575940626877799 107949 2020-04-28 18:24:11 104 #> 143 720575940626877799 107950 2020-04-28 18:34:57 104 #> 144 720575940626877799 107966 2020-04-28 19:01:09 104 #> 145 720575940626877799 107981 2020-04-28 19:07:41 104 #> 146 720575940626877799 108009 2020-04-28 19:33:43 104 #> 147 720575940626877799 108010 2020-04-28 19:33:53 104 #> 148 720575940626877799 108012 2020-04-28 19:34:00 104 #> 149 720575940626877799 108013 2020-04-28 19:34:03 104 #> 150 720575940626877799 108014 2020-04-28 19:34:06 104 #> 151 720575940626877799 108034 2020-04-28 20:22:10 104 #> 152 720575940626877799 108036 2020-04-28 20:31:23 104 #> 153 720575940626877799 108037 2020-04-28 20:32:38 104 #> 154 720575940626877799 108042 2020-04-28 20:40:41 104 #> 155 720575940626877799 108046 2020-04-28 20:46:59 104 #> 156 720575940626877799 108054 2020-04-28 20:56:18 104 #> 157 720575940626877799 108056 2020-04-28 20:56:26 104 #> 158 720575940626877799 108057 2020-04-28 20:59:15 104 #> 159 720575940626877799 108058 2020-04-28 20:59:18 104 #> 160 720575940626877799 108059 2020-04-28 21:01:17 104 #> 161 720575940626877799 108060 2020-04-28 21:01:32 104 #> 162 720575940626877799 108070 2020-04-28 21:26:49 104 #> 163 720575940626877799 108071 2020-04-28 21:28:23 104 #> 164 720575940626877799 108072 2020-04-28 21:28:24 104 #> 165 720575940626877799 108073 2020-04-28 21:28:28 104 #> 166 720575940626877799 108094 2020-04-28 21:58:38 104 #> 167 720575940626877799 108095 2020-04-28 21:59:26 104 #> 168 720575940626877799 108101 2020-04-29 00:47:33 104 #> 169 720575940626877799 108102 2020-04-29 00:53:33 104 #> 170 720575940626877799 108107 2020-04-29 01:16:53 104 #> 171 720575940626877799 108109 2020-04-29 01:17:03 104 #> 172 720575940626877799 108122 2020-04-29 01:32:15 104 #> 173 720575940626877799 108128 2020-04-29 01:37:54 104 #> 174 720575940626877799 108129 2020-04-29 01:38:22 104 #> 175 720575940626877799 108130 2020-04-29 01:44:41 104 #> 176 720575940626877799 108132 2020-04-29 01:57:21 104 #> 177 720575940626877799 108133 2020-04-29 02:27:13 104 #> 178 720575940626877799 108134 2020-04-29 02:36:06 104 #> 179 720575940626877799 108135 2020-04-29 03:23:50 104 #> 180 720575940626877799 108136 2020-04-29 03:28:56 104 #> 181 720575940626877799 108137 2020-04-29 03:32:06 104 #> 182 720575940626877799 108138 2020-04-29 03:32:24 104 #> 183 720575940626877799 108139 2020-04-29 03:33:11 104 #> 184 720575940626877799 108140 2020-04-29 03:33:23 104 #> 185 720575940626877799 108259 2020-04-29 17:12:45 104 #> 186 720575940626877799 108260 2020-04-29 17:12:49 104 #> 187 720575940626877799 108263 2020-04-29 17:13:05 104 #> 188 720575940626877799 108264 2020-04-29 17:13:12 104 #> 189 720575940626877799 108266 2020-04-29 17:13:32 104 #> 190 720575940626877799 108270 2020-04-29 17:14:03 104 #> 191 720575940626877799 108273 2020-04-29 17:14:23 104 #> 192 720575940626877799 108274 2020-04-29 17:14:25 104 #> 193 720575940626877799 108275 2020-04-29 17:14:35 104 #> 194 720575940626877799 108276 2020-04-29 17:14:44 104 #> 195 720575940626877799 108277 2020-04-29 17:15:58 104 #> 196 720575940626877799 108278 2020-04-29 17:16:15 104 #> 197 720575940626877799 108279 2020-04-29 17:16:20 104 #> 198 720575940626877799 108280 2020-04-29 17:16:33 104 #> 199 720575940626877799 108281 2020-04-29 17:16:39 104 #> 200 720575940626877799 108282 2020-04-29 17:16:43 104 #> 201 720575940626877799 108283 2020-04-29 17:16:59 104 #> 202 720575940626877799 108284 2020-04-29 17:17:25 104 #> 203 720575940626877799 108285 2020-04-29 17:17:36 104 #> 204 720575940626877799 108286 2020-04-29 17:17:44 104 #> 205 720575940626877799 108287 2020-04-29 17:18:38 104 #> 206 720575940626877799 108288 2020-04-29 17:18:50 104 #> 207 720575940626877799 108289 2020-04-29 17:19:04 104 #> 208 720575940626877799 108290 2020-04-29 17:19:16 104 #> 209 720575940626877799 108291 2020-04-29 17:19:26 104 #> 210 720575940626877799 108292 2020-04-29 17:21:44 104 #> 211 720575940626877799 108293 2020-04-29 17:21:48 104 #> 212 720575940626877799 108294 2020-04-29 17:22:01 104 #> 213 720575940626877799 108295 2020-04-29 17:22:04 104 #> 214 720575940626877799 108296 2020-04-29 17:22:40 104 #> 215 720575940626877799 108298 2020-04-29 17:23:02 104 #> 216 720575940626877799 108299 2020-04-29 17:23:05 104 #> 217 720575940626877799 108301 2020-04-29 17:23:23 104 #> 218 720575940626877799 108302 2020-04-29 17:23:38 104 #> 219 720575940626877799 108303 2020-04-29 17:23:50 104 #> 220 720575940626877799 108304 2020-04-29 17:23:53 104 #> 221 720575940626877799 108305 2020-04-29 17:24:02 104 #> 222 720575940626877799 108307 2020-04-29 17:24:23 104 #> 223 720575940626877799 108308 2020-04-29 17:24:34 104 #> 224 720575940626877799 108310 2020-04-29 17:24:47 104 #> 225 720575940626877799 108312 2020-04-29 17:25:02 104 #> 226 720575940626877799 108313 2020-04-29 17:25:29 104 #> 227 720575940626877799 108314 2020-04-29 17:25:47 104 #> 228 720575940626877799 108315 2020-04-29 17:25:54 104 #> 229 720575940626877799 108316 2020-04-29 17:26:06 104 #> 230 720575940626877799 108317 2020-04-29 17:26:21 104 #> 231 720575940626877799 108318 2020-04-29 17:33:43 104 #> 232 720575940626877799 108319 2020-04-29 17:33:51 104 #> 233 720575940626877799 108320 2020-04-29 17:33:59 104 #> 234 720575940626877799 108321 2020-04-29 17:34:05 104 #> 235 720575940626877799 108322 2020-04-29 17:34:12 104 #> 236 720575940626877799 108323 2020-04-29 17:34:21 104 #> 237 720575940626877799 108324 2020-04-29 17:34:26 104 #> 238 720575940626877799 108325 2020-04-29 17:34:33 104 #> 239 720575940626877799 108326 2020-04-29 17:34:38 104 #> 240 720575940626877799 108327 2020-04-29 17:34:44 104 #> 241 720575940626877799 108328 2020-04-29 17:34:48 104 #> 242 720575940626877799 108329 2020-04-29 17:34:58 104 #> 243 720575940626877799 108331 2020-04-29 17:35:13 104 #> 244 720575940626877799 108332 2020-04-29 17:35:19 104 #> 245 720575940626877799 108333 2020-04-29 17:35:25 104 #> 246 720575940626877799 108334 2020-04-29 17:35:32 104 #> 247 720575940626877799 108335 2020-04-29 17:35:41 104 #> 248 720575940626877799 108336 2020-04-29 17:35:46 104 #> 249 720575940626877799 108337 2020-04-29 17:36:01 104 #> 250 720575940626877799 108338 2020-04-29 17:37:18 104 #> 251 720575940626877799 108479 2020-04-29 20:48:54 104 #> 252 720575940626877799 111739 2020-05-06 16:16:58 84 #> 253 720575940626877799 111740 2020-05-06 16:17:10 84 #> 254 720575940626877799 111766 2020-05-06 16:48:07 84 #> 255 720575940626877799 111819 2020-05-06 17:05:02 84 #> 256 720575940626877799 111824 2020-05-06 17:13:58 84 #> 257 720575940626877799 111836 2020-05-06 17:22:18 84 #> 258 720575940626877799 111837 2020-05-06 17:22:28 84 #> 259 720575940626877799 111842 2020-05-06 17:26:58 84 #> 260 720575940626877799 111845 2020-05-06 17:29:53 84 #> 261 720575940626877799 111849 2020-05-06 17:32:11 84 #> 262 720575940626877799 112050 2020-05-06 18:47:44 84 #> 263 720575940626877799 112095 2020-05-06 19:17:35 84 #> 264 720575940626877799 112118 2020-05-06 19:50:26 84 #> 265 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Sebastian Seung Lab #> 7 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 8 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 9 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 10 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 11 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 12 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 13 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 14 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 15 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 16 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 17 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 18 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 19 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 20 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 21 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 22 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 23 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 24 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 25 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 26 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 27 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 28 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 29 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 30 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 31 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 32 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 33 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 34 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 35 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 36 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 37 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 38 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 39 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 40 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 41 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 42 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 43 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 44 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 45 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 46 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 47 Claire McKellar Mala Murthy Lab, Sebastian Seung Lab #> 48 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 49 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 50 Sandeep Kumar Mala Murthy Lab #> 51 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 52 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 53 Sarah Morejohn Mala Murthy Lab, Sebastian Seung Lab #> 54 Sarah Morejohn Mala Murthy Lab, Sebastian Seung Lab #> 55 Sarah Morejohn Mala Murthy Lab, Sebastian Seung Lab #> 56 Sarah Morejohn Mala Murthy Lab, Sebastian Seung Lab #> 57 Sarah Morejohn Mala Murthy Lab, Sebastian Seung Lab #> 58 Sarah Morejohn Mala Murthy Lab, Sebastian Seung Lab #> 59 Christa Baker Mala Murthy Lab #> 60 Christa Baker Mala Murthy Lab #> 61 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 62 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 63 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 64 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 65 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 66 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 67 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 68 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 69 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 70 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 71 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 72 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 73 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 74 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 75 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 76 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 77 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 78 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 79 Jay Gager Mala Murthy Lab, Sebastian Seung Lab #> 80 Austin T Burke Mala Murthy Lab, Sebastian Seung Lab #> 81 Austin T Burke Mala Murthy Lab, Sebastian Seung Lab #> 82 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 83 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 84 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 85 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 86 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 87 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 88 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 89 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 90 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 91 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 92 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 93 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 94 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 95 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 96 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 97 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 98 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 99 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 100 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 101 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 102 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 103 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 104 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 105 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 106 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 107 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 108 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 109 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 110 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 111 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 112 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 113 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 114 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 115 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 116 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 117 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 118 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 119 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 120 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 121 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 122 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 123 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 124 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 125 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 126 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 127 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 128 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 129 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 130 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 131 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 132 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 133 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 134 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 135 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 136 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 137 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 138 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 139 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 140 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 141 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 142 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 143 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 144 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 145 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 146 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 147 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 148 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 149 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 150 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 151 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 152 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 153 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 154 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 155 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 156 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 157 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 158 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 159 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 160 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 161 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 162 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 163 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 164 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 165 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 166 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 167 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 168 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 169 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 170 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 171 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 172 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 173 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 174 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 175 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 176 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 177 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 178 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 179 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 180 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 181 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 182 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 183 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 184 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 185 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 186 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 187 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 188 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 189 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 190 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 191 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 192 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 193 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 194 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 195 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 196 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 197 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 198 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 199 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 200 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 201 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 202 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 203 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 204 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 205 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 206 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 207 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 208 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 209 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 210 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 211 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 212 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 213 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 214 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 215 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 216 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 217 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 218 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 219 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 220 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 221 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 222 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 223 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 224 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 225 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 226 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 227 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 228 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 229 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 230 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 231 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 232 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 233 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 234 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 235 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 236 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 237 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 238 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 239 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 240 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 241 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 242 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 243 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 244 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 245 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 246 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 247 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 248 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 249 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 250 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 251 Ryan Willie Mala Murthy Lab, Sebastian Seung Lab #> 252 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 253 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 254 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 255 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 256 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 257 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 258 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 259 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 260 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 261 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 262 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 263 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 264 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 265 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 266 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 267 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 268 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 269 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 270 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 271 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 272 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 273 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 274 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 275 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 276 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 277 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 278 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 279 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 280 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 281 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 282 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 283 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 284 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 285 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 286 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 287 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab #> 288 Merlin Moore Mala Murthy Lab, Sebastian Seung Lab # } if (FALSE) { # use flexible root id specification flywire_change_log(\"DA2_lPN_R\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_cloudvolume.html","id":null,"dir":"Reference","previous_headings":"","what":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","title":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","text":"Low level access FlyWire data via Python cloudvolume module","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cloudvolume.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","text":"","code":"flywire_cloudvolume( cloudvolume.url = NULL, cached = TRUE, min_version = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_cloudvolume.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","text":"cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. cached TRUE (default) reuses cached CloudVolume object current Python session. See details. min_version minimum version cloudvolume Python module e.g. \"3.12\". default NULL implies version acceptable. ... Additional arguments passed CloudVolume constructor","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_cloudvolume.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","text":"equivalent (Python): cloudvolume import CloudVolume vol = CloudVolume('graphene://https://prodv1.flywire-daf.com/segmentation/table/fly_v31', use_https=True) cache tries intelligent 1. generating new object every input parameter combination (course need Python) 2. avoiding stale references checking Python currently running returned CloudVolume object non-null. also regenerates object every hour. Note reticulate package allows R/Python interaction binds one Python session. Furthermore Python restarted without also restarting R.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_cloudvolume.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Low level access to FlyWire data via Python cloudvolume module — flywire_cloudvolume","text":"","code":"if (FALSE) { cv=flywire_cloudvolume() # detailed info about the image volume cv$info # bounding box (Python format in raw voxels) cv$bounds # in nm boundingbox(cv) # get help for a function reticulate::py_help(cv$get_roots) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Access precomputed flywire connectivity data — flywire_connectome_data","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"flywire_connectome_data returns dplyr compatible connection connectivity dumps disk. flywire_connectome_data_version sets integer version number preferred flywire connectome data dump returns currently version.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"","code":"flywire_connectome_data( type = c(\"syn\", \"pre\", \"post\"), version = NULL, cached = TRUE, ... ) flywire_connectome_data_version(set = NULL, default = NA)"},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"type Character vector specifying kind data version Optional CAVE version. default value NULL uses latest data dump available unless options(fafbseg.flywire_connectome_data_version) set (can conveniently using flywire_connectome_data_version()). cached version NULL whether use cached value (lasting 1 hour) latest available version. ... Additional arguments passed arrow::open_dataset. set set= passed argument specified data version used going forwards session default. achieved setting fafbseg.flywire_connectome_data_version option. set=NA specified option cleared. set=FALSE, latest version disk returned regardless value options(\"fafbseg.flywire_connectome_data_version\")). See examples. default version return information available. Defaults NA indicate version information available.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"arrow object can use dplyr verbs like filter order find neurons/connectivity data interest. integer version number list previous value options(fafbseg.flywire_connectome_data_version) set=.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"depends precomputed data dumps prepared periodically Sven Dorkenwald. can download public release version using function download_flywire_release_data. can download versions Sven's Google drive folder. See FlyWire Slack message details URL. Two pieces information used determine version queried. First value options(fafbseg.flywire_connectome_data_version), second latest available version connectivity dumps provided flywire_connectome_data().","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_connectome_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access precomputed flywire connectivity data — flywire_connectome_data","text":"","code":"# \\donttest{ # latest available version/ syn=try(flywire_connectome_data('syn'), silent=TRUE) syn450=try(flywire_connectome_data('syn', version=450), silent=TRUE) if(!inherits(syn450, 'try-error')) { syn450 syn450$metadata dl4ds <- syn450 %>% filter(pre_pt_root_id==flywire_ids(\"DL4_adPN_L\", version=450, integer64 = TRUE)) %>% collect() } # } if (FALSE) { # report active connectome dump version (defaults to most recent available) flywire_connectome_data_version() # use the June 2023 public release version as the default flywire_connectome_data_version(set=630) # confirm this is the default flywire_connectome_data_version() # check the latest version on disk flywire_connectome_data_version(set=FALSE) # stop defaulting to specific version (therefore using the latest on disk) flywire_connectome_data_version(set=NA) flywire_connectome_data_version() }"},{"path":"https://natverse.org/fafbseg/reference/flywire_dcvs.html","id":null,"dir":"Reference","previous_headings":"","what":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","title":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","text":"Preliminary dense core vesicle (DCV) detection results Lee group, Stephan Gerhard Minsu Kim.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_dcvs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","text":"","code":"flywire_dcvs( rootid, dataset = c(\"dcv.3.0\", \"dcv.2.0\", \"dcv.1.0\"), project = \"fruitfly_fafb_flywire\", islatest = TRUE, simplify = TRUE, return = c(\"parsed\", \"text\", \"response\"), token = NULL, simplifyVector = TRUE, include_headers = FALSE, OmitFailures = TRUE, cl = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_dcvs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","text":"rootid flywire rootid/rootids dataset DCV data set Stephan Gerhard access. 1.0 just antennal lobes FAFB. 2.0 first run whole brain. project project pull data. moment, one option DCV data. islatest logical, whether fetch latest root_id given IDs date. simplify logical, FALSE rootid separate set two data frames (one DCV positions, one neuron's synapses). Else, list two combined data frames returned. return One \"parsed\", \"text\" (raw JSON), \"response\" token Optional chunkedgraph token (otherwise default one current segmentation used). simplifyVector Whether use jsonlite::simplifyVector include_headers Whether include basic headers http request attributes parsed JSON object (default TRUE) parse.json=TRUE. OmitFailures logical, TRUE requests result 500 error dropped warning displayed error. cl cluster object created parallel::makeCluster, integer indicate number child-processes (integer values ignored Windows) parallel evaluations. ... additional arguments passed httr::{RETRY} function. may include config list named parameters etc.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_dcvs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","text":"list, first entry contains DCV locations second synapses given rootid, nearest DCV precalculated synapse..","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_dcvs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get predicted dense core vesicle locations in the flywire dataset — flywire_dcvs","text":"","code":"if (FALSE) { # Just AL test data set data = flywire_dcvs(\"720575940629166904\", dataset = \"dcv.1.0\") dcv = data$dcv synapse = data$syns # Whole brain data set dcv = flywire_dcvs(c(\"720575940631973089\",\"720575940629166904\"), dataset = \"dcv.2.0\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":null,"dir":"Reference","previous_headings":"","what":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"GET/POST flywire (graphene) servers appropriate authorisation token","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"","code":"flywire_fetch( url, body = NULL, config = NULL, token = NULL, return = c(\"parsed\", \"text\", \"response\"), cache = FALSE, retry = 0L, include_headers = FALSE, simplifyVector = TRUE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"url Full URL brainmaps API endpoint body R list parameters converted jsonlite::toJSON passed POST. can also pass JSON character vector control JSON encoding. config (optional) curl options, see httr::config details. token Optional chunkedgraph token (otherwise default one current segmentation used). return One \"parsed\", \"text\" (raw JSON), \"response\" cache Whether cache responses (default FALSE) retry number times retry operation (default 0, FALSE=>0 TRUE=>3). See documentation times argument httr::RETRY details. include_headers Whether include basic headers http request attributes parsed JSON object (default TRUE) parse.json=TRUE. simplifyVector Whether use jsonlite::simplifyVector ... additional arguments passed httr::{RETRY} function. may include config list named parameters etc.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"Either R object based parsing returned JSON, character vector containing raw JSON httr::response object, depending value return.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":"authorisation","dir":"Reference","previous_headings":"","what":"authorisation","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"authorisation based chunked graph token normally stored ~/.cloudvolume/secrets/cave-secret.json. See https://github.com/seung-lab/cloud-volume#cave-secretjson format. need generate token advised FlyWire team. Search ask help #help_software FlyWire slack find information. details see article accessing-graphene-server.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_fetch.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"GET/POST from flywire (graphene) servers with appropriate authorisation token — flywire_fetch","text":"","code":"# \\donttest{ # convert a flywire state URL into a parsed neuroglancer scene information # but see also flywire_expandurl json=flywire_fetch(\"https://globalv1.flywire-daf.com/nglstate/5747205470158848\", return=\"text\") ngl_segments(ngl_decode_scene(json), as_character = TRUE) #> [1] \"720575940619527173\" \"720575940628130268\" \"720575940630484179\" # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","title":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","text":"allows flexible specification flywire root ids compared ngl_segments including queries cell types recorded flytable.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","text":"","code":"flywire_ids( x, integer64 = FALSE, check_latest = FALSE, must_work = FALSE, na_ok = FALSE, unique = FALSE, version = NULL, table = c(\"both\", \"info\", \"optic\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","text":"x character bit64::integer64 vector dataframe specifying ids directly string specifying query, URL comma/space delimited list ids (see examples). integer64 Whether return ids 64 bit integers - compact character vector, can fragile (default FALSE). check_latest Whether check ids date. must_work Whether ids must valid na_ok whether NA ids acceptable must_work=TRUE unique Whether return unique ids version Integer materialisation version table x query whether search brain, optic lobe info tables. ... Additional arguments passed flytable_cell_types ngl_segments.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","text":"character (integer64)) vector segment ids","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_ids.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Flexible specification of flywire ids (including from flytable types) — flywire_ids","text":"","code":"flywire_ids(data.frame(root_id=1)) #> [1] \"1\" flywire_ids(data.frame(root_id=1), integer64=TRUE) #> integer64 #> [1] 1 # Bad values will return 0 flywire_ids(data.frame(root_id=-1)) #> [1] \"0\" if (FALSE) { # will error flywire_ids(data.frame(root_id=-1), must_work = TRUE) } # DL1 olfactory PNs flywire_ids(\"DL1_adPN\") #> [1] \"720575940625157557\" \"720575940627042064\" \"720575940616079035\" #> [4] \"720575940632167085\" # DL1 olfactory PNs but only on the RHS flywire_ids(\"DL1_adPN_R\") #> [1] \"720575940627042064\" \"720575940632167085\" # specifying materialisation version flywire_ids(\"DL1_adPN_R\", version=630) #> Updating 1 ids #> flywire_rootid_cached: Looking up 1 missing keys #> [1] \"720575940627042064\" \"720575940632167085\" # using SQL wild cards flywire_ids(\"DA[12]_%PN_L\") #> [1] \"720575940614309535\" \"720575940611849187\" \"720575940622364184\" #> [4] \"720575940615086632\" \"720575940619385765\" \"720575940626937617\" #> [7] \"720575940638719104\" \"720575940626034819\" \"720575940621185050\" #> [10] \"720575940646122804\" \"720575940613345442\" \"720575940637208718\" #> [13] \"720575940603231916\" \"720575940605102694\" # all sensory neurons flywire_ids(\"super:sensory\", integer64=TRUE) #> integer64 #> [1] 720575940622360358 720575940615856345 720575940614548253 #> [4] 720575940605699104 720575940613684370 720575940627135306 #> [7] 720575940637321847 720575940628673474 720575940610460514 #> [10] 720575940616239873 720575940633280107 720575940638509952 #> [13] 720575940617969961 720575940630644281 720575940606871497 #> [16] 720575940622242253 720575940626522910 720575940633816986 #> [19] 720575940625653029 720575940630047019 720575940632644639 #> [22] 720575940638836285 720575940636052927 720575940628677114 #> [25] 720575940638513752 720575940617041728 720575940616999069 #> [28] 720575940628953210 720575940608376132 720575940645728132 #> [31] 720575940628599296 720575940623087859 720575940617534676 #> [34] 720575940613118610 720575940612096370 720575940617433142 #> [37] 720575940618512624 720575940613191591 720575940611720362 #> [40] 720575940623793741 720575940631630893 720575940613664874 #> [43] 720575940610185221 720575940621659563 720575940613794114 #> [46] 720575940627214891 720575940642599328 720575940618293883 #> [49] 720575940633367377 720575940626811023 720575940623274935 #> [52] 720575940619024774 720575940619219627 720575940616039197 #> [55] 720575940609924306 720575940622745834 720575940627944464 #> [58] 720575940622082518 720575940629007230 720575940617986345 #> [61] 720575940646372228 720575940635969399 720575940614844994 #> [64] 720575940646785924 720575940621831804 720575940631875298 #> [67] 720575940625293514 720575940620847086 720575940632913461 #> [70] 720575940617986089 720575940609792206 720575940623476661 #> [73] 720575940633059381 720575940630271862 720575940617665950 #> [76] 720575940617987113 720575940605264305 720575940614921501 #> [79] 720575940621654298 720575940638389437 720575940619385583 #> [82] 720575940627000582 720575940627606375 720575940614570793 #> [85] 720575940635767524 720575940624853600 720575940623503945 #> [88] 720575940625148174 720575940619419757 720575940613637782 #> [91] 720575940628264721 720575940618912427 720575940603820716 #> [94] 720575940622972820 720575940629693302 720575940631925096 #> [97] 720575940627677258 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720575940618317115 720575940630237775 720575940621607046 #> [16276] 720575940628684292 720575940630856960 720575940628426257 #> [16279] 720575940624919625 720575940637618830 720575940624294084 #> [16282] 720575940624834741 720575940626620464 720575940618092249 #> [16285] 720575940622825221 720575940639008063 720575940642394331 #> [16288] 720575940626688144 720575940633613869 720575940630606530 #> [16291] 720575940636396536 720575940615663522 720575940618351060 #> [16294] 720575940634157523 720575940628847612 720575940644883656 #> [16297] 720575940623183996 720575940613405098 720575940619807542 #> [16300] 720575940616141535 720575940619086149 720575940621113620 #> [16303] 720575940624117896 720575940622210932 720575940646251886 #> [16306] 720575940606517280 720575940621611503 720575940616727106 #> [16309] 720575940634076973 720575940624699901 720575940619239709 #> [16312] 720575940625986087 720575940626074040 720575940622829812 #> [16315] 720575940616317599 720575940624248870 720575940640156494 #> [16318] 720575940635605183 720575940619746880 720575940613630742 #> [16321] 720575940627799677 720575940630989879 720575940624829877 #> [16324] 720575940630523518 720575940632113682 720575940610187971 #> [16327] 720575940640383677 720575940621884654 720575940609568011 #> [16330] 720575940630055783 720575940624977481 720575940624871677 #> [16333] 720575940644542755 720575940613271781 720575940630984247 #> [16336] 720575940622463158 720575940624309798 720575940621906029 #> [16339] 720575940619775355 720575940623019870 720575940641445840 #> [16342] 720575940634094931 720575940622289830 720575940653419766 #> [16345] 720575940640234574 720575940626014247 720575940622637695 #> [16348] 720575940621742246 720575940625333228 720575940633938643 #> [16351] 720575940632951633 720575940631123968 720575940612986354 #> [16354] 720575940628919239 720575940627760280 720575940620592587 #> [16357] 720575940626009895 720575940628087326 720575940611758034 #> [16360] 720575940609232476 720575940648554628 720575940629144060 #> [16363] 720575940627180290 720575940614838323 720575940618657281 #> [16366] 720575940618927700 720575940647822900 720575940618793373 #> [16369] 720575940638284912 720575940610326723 720575940648473476 #> [16372] 720575940627186750 720575940628518287 720575940615398609 #> [16375] 720575940624294794 720575940613485994 720575940613486250 #> [16378] 720575940614727720 720575940630461799 720575940622329665 #> [16381] 720575940628128275 720575940645895447 720575940621957286 #> [16384] 720575940624271338 720575940631212252 720575940634881561 #> [16387] 720575940617136827 720575940608144002 720575940614966323 #> [16390] 720575940624923133 720575940629738795 720575940635704160 #> [16393] 720575940610336707 720575940621438144 720575940632746296 #> [16396] 720575940635075740 720575940625859367 720575940623862040 #> [16399] 720575940638782953 720575940613064049 720575940613110641 #> [16402] 720575940622239664 720575940632657512 720575940636190571 #> [16405] 720575940626152269 720575940623568716 720575940621956161 #> [16408] 720575940648335748 720575940621955649 720575940621139365 #> [16411] 720575940634787097 720575940661201025 720575940645427236 #> [16414] 720575940621264576 720575940616429890 720575940636077978 #> [16417] 720575940617143602 720575940634043437 720575940613482994 #> [16420] 720575940624028515 720575940623865624 720575940633595475 #> [16423] 720575940631550457 720575940640674211 720575940624379844 #> [16426] 720575940630687098 720575940633811795 720575940626022183 #> [16429] 720575940627396098 720575940631735127 720575940620255867 #> [16432] 720575940617816150 720575940629267655 720575940633482956 #> [16435] 720575940607056561 720575940615201711 720575940632619306 #> [16438] 720575940623300940 720575940640225845 720575940631836921 #> [16441] 720575940613887858 720575940606723942 720575940628851176 #> [16444] 720575940653399542 720575940632396875 720575940621743451 #> [16447] 720575940624456388 720575940624456644 720575940621810926 #> [16450] 720575940617241275 720575940630682684 720575940647329827 #> [16453] 720575940612886677 720575940622193217 720575940622747380 #> [16456] 720575940633541165 720575940638650846 720575940628954884 #> [16459] 720575940634057645 720575940642493403 720575940628712776 #> [16462] 720575940615141160 720575940609999115 720575940625146119 #> [16465] 720575940611726200 720575940633230929 720575940629559145 #> [16468] 720575940628899349 720575940621143637 720575940630285723 #> [16471] 720575940617383867 720575940614783784 720575940618582818 #> [16474] 720575940620433713 720575940640478269 720575940626774160 #> [16477] 720575940628273797 720575940641131648 720575940631599611 #> [16480] 720575940624016664 720575940620643787 720575940632037573 #> [16483] 720575940613529002 720575940624401958 720575940630694594 #> [16486] 720575940625891768 720575940638532062 720575940628725647 #> [16489] 720575940631519852 720575940632362255 720575940623089758 #> [16492] 720575940624854967 720575940619221573 720575940636703736 #> [16495] 720575940633049671 720575940628757252 720575940606595686 #> [16498] 720575940632435754 720575940636193387 720575940615542674 #> [16501] 720575940624094975 720575940655956897 720575940625736892 #> [16504] 720575940655971489 720575940633079948 720575940619279429 #> [16507] 720575940613290226 720575940622701695 720575940620454705 #> [16510] 720575940635917675 720575940624557203 720575940617154060 #> [16513] 720575940613144689 720575940618990420 720575940636943215 #> [16516] 720575940614457581 720575940626026791 720575940635146396 #> [16519] 720575940607039529 720575940615973482 720575940635668064 #> [16522] 720575940627396964 720575940624282248 720575940623124905 #> [16525] 720575940627375204 720575940636943727 720575940635483031 #> [16528] 720575940618310493 720575940661154177 720575940613024917 #> [16531] 720575940613220850 720575940621840321 720575940621391457 #> [16534] 720575940620511793 720575940609782281 720575940631141676 #> [16537] 720575940647793716 720575940623283324 720575940618595106 #> [16540] 720575940633861293 720575940627399196 720575940606554912 #> [16543] 720575940618815389 720575940617150395 720575940628503610 #> [16546] 720575940616680258 720575940632699459 720575940614555629 #> [16549] 720575940623869197 720575940634593249 720575940640759869 #> [16552] 720575940630107035 720575940630237083 720575940635846847 #> [16555] 720575940630502138 720575940639024356 720575940636770808 #> [16558] 720575940622619632 720575940629881679 720575940617800331 #> [16561] 720575940619936566 720575940632646712 720575940619446597 #> [16564] 720575940616058518 720575940650992249 720575940630331291 #> [16567] 720575940653564662 720575940629400838 720575940613033109 #> [16570] 720575940646380654 720575940638076528 720575940622111926 #> [16573] 720575940628738728 720575940622112438 720575940613449369 #> [16576] 720575940642709467 720575940633038127 720575940622101174 #> [16579] 720575940645583908 720575940625385451 720575940616032362 #> [16582] 720575940624397862 720575940621706587 720575940635154076 #> [16585] 720575940625096375 720575940619936822 720575940639141466 #> [16588] 720575940643215501 720575940630699970 720575940622960922 #> [16591] 720575940622112182 720575940614171875 720575940610933572 #> [16594] 720575940645000648 720575940633256775 720575940626879536 #> [16597] 720575940632877379 720575940624600211 720575940624993021 #> [16600] 720575940615824534 720575940644599712 720575940614207715 #> [16603] 720575940610945092 720575940622959386 720575940640256590 #> [16606] 720575940634766817 720575940628810472 720575940624996605 #> [16609] 720575940623875939 720575940618455270 720575940625911736 #> [16612] 720575940627950973 720575940626673712 720575940627604825 #> [16615] 720575940632710979 720575940614198243 720575940618456038 #> [16618] 720575940626672944 720575940641552080 720575940627210596 #> [16621] 720575940609953547 720575940624375081 720575940625937934 #> [16624] 720575940622970394 720575940628231443 720575940622977306 #> [16627] 720575940621886630 720575940619283269 720575940637943408 #> [16630] 720575940632829240 720575940621514667 720575940614587885 #> [16633] 720575940629548649 720575940622753776 720575940614190563 #> [16636] 720575940619502400 720575940646408302 720575940636507384 #> [16639] 720575940606387046 720575940640152509 720575940624875015 #> [16642] 720575940630383866 720575940618101563 720575940634602465 #> [16645] 720575940621850971 720575940624327818 720575940632882024 #> [16648] 720575940627249214 720575940623351116 720575940624413222 #> [16651] 720575940621018709 720575940624058061 720575940645106632 #> [16654] 720575940633519308 720575940624882439 720575940630981111 #> [16657] 720575940634530530 720575940621168775 720575940621681067 #> [16660] 720575940622415286 720575940629894416 720575940628312595 #> [16663] 720575940629765675 720575940630703607 720575940635618400 #> [16666] 720575940640176693 720575940629605419 720575940615513490 #> [16669] 720575940627588953 720575940605939628 720575940631883717 #> [16672] 720575940616516162 720575940623919373 720575940640233149 #> [16675] 720575940625998823 720575940623912205 720575940616471967 #> [16678] 720575940632868163 720575940610260437 720575940622261168 #> [16681] 720575940625025533 720575940631140919 720575940643199885 #> [16684] 720575940625440073 720575940618958337 720575940620740432 #> [16687] 720575940608122498 720575940645933079 720575940616514370 #> [16690] 720575940642439899 720575940622172854 720575940624196095 #> [16693] 720575940621685595 720575940634577633 720575940625473772 #> [16696] 720575940646459502 720575940632393258 720575940627900056 #> [16699] 720575940618897492 720575940628592917 720575940625009917 #> [16702] 720575940635005347 720575940619556416 720575940618851585 #> [16705] 720575940620410161 720575940636922735 720575940624931509 #> [16708] 720575940616580930 720575940626927664 720575940621720747 #> [16711] 720575940635514775 720575940621235732 720575940612286670 #> [16714] 720575940631912389 720575940605998508 720575940632853816 #> [16717] 720575940616408223 720575940624088319 720575940623062817 #> [16720] 720575940645877271 720575940636658100 720575940631278807 #> [16723] 720575940635753312 720575940613087962 720575940623072801 #> [16726] 720575940624089855 720575940622635135 720575940623051297 #> [16729] 720575940630865602 720575940618050363 720575940613061781 #> [16732] 720575940619195677 720575940622872816 720575940637538958 #> [16735] 720575940640690339 720575940632930188 720575940618353369 #> [16738] 720575940616193386 720575940624032013 720575940647842356 #> [16741] 720575940621742189 720575940625686759 720575940622139056 #> [16744] 720575940626014759 720575940624368934 720575940623559804 #> [16747] 720575940613397221 720575940629252170 720575940640206781 #> [16750] 720575940612334178 720575940633017415 720575940632242450 #> [16753] 720575940650042233 720575940621286053 720575940616835014 #> [16756] 720575940639018468 720575940624153599 720575940624370628 #> [16759] 720575940625026557 720575940625327368 720575940630097307 #> [16762] 720575940628134410 720575940632243218 720575940625855420 #> [16765] 720575940628240906 720575940635771287 720575940628337541 #> [16768] 720575940620789720 720575940628620565 720575940621297032 #> [16771] 720575940632714823 720575940651015289 720575940614392547 #> [16774] 720575940625302280 720575940627455234 720575940637002351 #> [16777] 720575940610358723 720575940606830950 720575940620936784 #> [16780] 720575940633988179 720575940640315701 720575940627496537 #> [16783] 720575940627135674 720575940615659682 720575940619473221 #> [16786] 720575940624978357 720575940637181815 720575940626892581 #> [16789] 720575940641300096 720575940623611094 720575940621142036 #> [16792] 720575940634840345 720575940644545952 720575940618989725 #> [16795] 720575940633918803 720575940639368937 720575940637804206 #> [16798] 720575940616946886 720575940631913047 720575940614717736 #> [16801] 720575940630630782 720575940625954744 720575940626854842 #> [16804] 720575940620222034 720575940628520767 720575940618193881 #> [16807] 720575940627050954 720575940633161799 720575940633588900 #> [16810] 720575940620810443 720575940613601765 720575940618412125 #> [16813] 720575940621667462 720575940609928459 720575940624028003 #> [16816] 720575940633341521 720575940621016912 720575940637640293 #> [16819] 720575940621017680 720575940612990101 720575940617341883 #> [16822] 720575940627225274 720575940621668742 720575940632467498 #> [16825] 720575940626408525 720575940628409989 720575940614736365 #> [16828] 720575940637641573 720575940611082564 720575940633343825 #> [16831] 720575940631998149 720575940631388887 720575940633561887 #> [16834] 720575940621696448 720575940631484119 720575940624172824 #> [16837] 720575940613619353 720575940613619865 720575940630688762 #> [16840] 720575940628266066 720575940627223482 720575940624602406 #> [16843] 720575940627789401 720575940620030518 720575940626038460 #> [16846] 720575940613621145 720575940631176960 720575940639155433 #> [16849] 720575940615153071 720575940625714446 720575940625114877 #> [16852] 720575940625115133 720575940623458124 720575940632520040 #> [16855] 720575940608368050 720575940640218702 720575940618591920 #> [16858] 720575940628232467 720575940640885336 720575940618396628 #> [16861] 720575940614704424 720575940618323641 720575940613166042 #> [16864] 720575940629425994 720575940622011969 720575940631815161 #> [16867] 720575940642656219 720575940632001733 720575940628816917 #> [16870] 720575940633049912 720575940616030358 720575940622464383 #> [16873] 720575940627258810 720575940615244851 720575940615571966 #> [16876] 720575940628429445 720575940627807065 720575940630824130 #> [16879] 720575940631717996 720575940617947275 720575940622484852 #> [16882] 720575940622616670 720575940630981623 720575940616252010 #> [16885] 720575940624455050 720575940634427603 720575940628737679 #> [16888] 720575940629158140 720575940639185242 720575940631205888 #> [16891] 720575940628100489 720575940625093813 720575940621324564 #> [16894] 720575940620069430 720575940631186176 720575940609726731 #> [16897] 720575940615115059 720575940631281463 720575940639062106 #> [16900] 720575940615592354 720575940632649795 720575940640655779 #> [16903] 720575940615303475 720575940623589708 720575940631771735 #> [16906] 720575940623201404 # note that side is defined by soma position (not arbour side) flywire_ids(\"class:MBON_R\", integer64=TRUE) #> integer64 #> [1] 720575940623472716 720575940638526278 720575940629585602 720575940637934308 #> [5] 720575940630496374 720575940611344078 720575940634822751 720575940617552340 #> [9] 720575940624280328 720575940643700640 720575940615221811 720575940614026193 #> [13] 720575940623001480 720575940613070485 720575940636992368 720575940639697827 #> [17] 720575940618249797 720575940623905719 720575940624590316 720575940612196850 #> [21] 720575940627144069 720575940610647416 720575940622093436 720575940647328900 #> [25] 720575940639556467 720575940636120986 720575940617749538 720575940617760257 #> [29] 720575940619810389 720575940634482783 720575940626109315 720575940626744921 #> [33] 720575940623464316 720575940614892182 720575940621777391 720575940606953858 #> [37] 720575940635063135 720575940626315010 720575940632943277 720575940628783363 #> [41] 720575940635651680 720575940628734376 720575940610964946 720575940607155890 #> [45] 720575940623381956 720575940628487813 720575940638028607 720575940622306625 # superclass can also have a side specified flywire_ids(\"super:motor_R\", integer64=TRUE) #> integer64 #> [1] 720575940660219265 720575940644726432 720575940624342569 720575940631715896 #> [5] 720575940635360924 720575940624967612 720575940626939737 720575940621169690 #> [9] 720575940620025620 720575940614734754 720575940645697828 720575940622235930 #> [13] 720575940621499412 720575940611008718 720575940621126384 720575940616570966 #> [17] 720575940623137818 720575940607193986 720575940629561347 720575940637662697 #> [21] 720575940617403622 720575940629810748 720575940620982966 720575940628096586 #> [25] 720575940615596850 720575940607880578 720575940631023099 720575940628781333 #> [29] 720575940629936348 720575940623415849 720575940661338497 720575940605287358 #> [33] 720575940645528430 720575940622989300 720575940631999080 720575940628743752 #> [37] 720575940632304711 720575940634385875 720575940612888178 720575940626094350 #> [41] 720575940623457535 720575940628826128 720575940628164612 720575940629778554 #> [45] 720575940630868793 720575940645527918 720575940634813536 720575940650119289 #> [49] 720575940630233404 720575940624327572 720575940626149671 720575940620182181 #> [53] 720575940622168052 720575940627214282 # you can also use a comma/space delimited list flywire_ids(\"1234, 123456\") #> [1] \"1234\" \"123456\" # ... which could come from the clipboard if (FALSE) { flywire_ids(clipr::read_clip()) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":null,"dir":"Reference","previous_headings":"","what":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"can think flywire_islatest returning whether root id valid given timestamp (default now). corresponding object edited, invalidating root id, (yet) exist ","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"","code":"flywire_islatest( x, cloudvolume.url = NULL, timestamp = NULL, version = NULL, cache = NA, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"x FlyWire rootids format understandable ngl_segments including integer64 cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. timestamp (optional) argument set endpoint - edits time ignored (see details). version optional CAVE materialisation version number. See details examples. cache Whether cache result - default value NA timestamp version argument supplied. ... Additional arguments flywire_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"logical vector length matching input. NA/0 input values return NA output.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"call quite fast (think thousands ids per second). current implementation also de-duplicates input automatically. can pass vector containing duplicates unique ids passed server. provide input integer64 data sent binary form flywire server. can significant time saving large queries (think 10000+). timestamp version provided, edits time point considered. Note since August 2022 flywire_islatest return FALSE case rootid created timestamp. Formerly returned TRUE (see seung-lab/PyChunkedGraph#412)","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_islatest.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check that one or more FlyWire root ids have not been further edited — flywire_islatest","text":"","code":"# \\donttest{ flywire_islatest(\"720575940621039145\") #> [1] FALSE flywire_islatest(c(\"720575940619073968\", \"720575940637707136\")) #> [1] FALSE FALSE # check the first id up to a given timestamp # when was it created (= last modified) flywire_last_modified('720575940619073968') #> [1] \"2020-12-02 11:43:01 UTC\" # TRUE flywire_islatest('720575940619073968', timestamp = '2020-12-03 UTC') #> [1] TRUE # FALSE since it didn't exist flywire_islatest(\"720575940619073968\", timestamp = \"2020-12-01 UTC\") #> [1] FALSE # } if (FALSE) { latest=flywire_latestid(\"720575940619073968\") flywire_islatest(latest) # compare checking roots downstream of two large bilateral neurons blids=c(\"720575940619073968\", \"720575940637707136\") blidsout=flywire_partners(blids) # 3.2 vs 4.7s in my test bench::mark(bin=flywire_islatest(blidsout$post_id), str=flywire_islatest(as.character(blidsout$post_id))) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_l2ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Return level 2 supervoxel ids for neurons — flywire_l2ids","title":"Return level 2 supervoxel ids for neurons — flywire_l2ids","text":"Level 2 supervoxel ids one step terminal supervoxel ids (level 1) finest resolution chunked graph. Like root ids, level 2 supervoxels can edited: results level 2 id destroyed two new ones created. Unlike root id merge split, l2 ids edit location change, others remain .","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_l2ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return level 2 supervoxel ids for neurons — flywire_l2ids","text":"","code":"flywire_l2ids(x, integer64 = TRUE, cache = TRUE)"},{"path":"https://natverse.org/fafbseg/reference/flywire_l2ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return level 2 supervoxel ids for neurons — flywire_l2ids","text":"x root ids including neuroglancer scene URLs integer64 Whether return ids integer64 type (compact little fragile) rather character (default FALSE). cache Whether cache results disk","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_l2ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return level 2 supervoxel ids for neurons — flywire_l2ids","text":"vector ids (usually 64 bit integers); named list vectors x length >1.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_l2ids.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return level 2 supervoxel ids for neurons — flywire_l2ids","text":"","code":"if (FALSE) { length(flywire_l2ids(\"720575940604351334\")) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":null,"dir":"Reference","previous_headings":"","what":"Check when a root id was last edited — flywire_last_modified","title":"Check when a root id was last edited — flywire_last_modified","text":"Check root id last edited","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check when a root id was last edited — flywire_last_modified","text":"","code":"flywire_last_modified(x, tz = \"UTC\", cloudvolume.url = NULL, ...)"},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check when a root id was last edited — flywire_last_modified","text":"x set flywire ids tz timezone display modification time; defaults UTC (~ proper name GMT). cloudvolume.url segmentation source URL cloudvolume. Normally can ignore rely default segmentation chosen choose_segmentation ... additional arguments passed low-level flywire_fetch function","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check when a root id was last edited — flywire_last_modified","text":"vector POSIXct timestamps, default standard UTC timezone.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check when a root id was last edited — flywire_last_modified","text":"raw information call seconds since epoch, 00:00 1 January 1970 UTC. Specifying tz argument changes display actual time event .e. Princeton typically display 5h behind Cambridge corresponding physical time.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_last_modified.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check when a root id was last edited — flywire_last_modified","text":"","code":"# \\donttest{ flywire_last_modified(\"720575940639218165\") #> [1] \"2021-05-07 09:50:36 UTC\" # Your local time zone flywire_last_modified(\"720575940639218165\", tz=\"\") #> [1] \"2021-05-07 09:50:36 UTC\" # Cambridge (the original one) flywire_last_modified(\"720575940639218165\", tz=\"GB\") #> [1] \"2021-05-07 10:50:36 BST\" # Princeton flywire_last_modified(\"720575940639218165\", tz=\"US/Eastern\") #> [1] \"2021-05-07 05:50:36 EDT\" # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_latestid.html","id":null,"dir":"Reference","previous_headings":"","what":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","title":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","text":"Finds supervoxel ids input rootid maps current rootid simple majority vote.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_latestid.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","text":"","code":"flywire_latestid( rootid, sample = 100L, level = 2L, timestamp = NULL, version = NULL, cloudvolume.url = NULL, Verbose = FALSE, method = c(\"auto\", \"leaves\", \"cave\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_latestid.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","text":"rootid One ore FlyWire rootids defining segment (form interpretable ngl_segments) sample absolute fractional number supervoxel ids map rootids FALSE (see details). level resolution level chunked graph use calculating identity changes. integer 1 2. default (2, implying slightly larger supervoxels) considerably faster gives good results smallest fragments. See flywire_l2ids. timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. version optional CAVE materialisation version number. See details examples. cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. Verbose set TRUE prints information fraction method \"cave\" uses caveclient python module, generally faster, disadvantage disambiguate two options split. \"auto\" chooses cave available \"leaves\" otherwise. ... Additional arguments passed flywire_leaves","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_latestid.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","text":"character vector rootids. input 0 NA rootid exist chunked graph, output 0.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_latestid.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find the most up to date FlyWire rootid for one or more input rootids — flywire_latestid","text":"default sample input rootids used since step time consuming part. sample can defined fraction (0 [1] \"720575940611617617\" if (FALSE) { with_segmentation('sandbox', flywire_latestid('720575940625602908', Verbose = T)) # check every supervoxel (slow for bigger neurons, but this KC is smallish) flywire_latestid('720575940616243077', sample=FALSE) # update a neuroglancer URL with the most up to date segment ids # nb this is slow since it looks at all supervoxels - much more efficient to # store a single xyz location or supervoxel id u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5695907068641280\" ngl_segments(u) <- flywire_latestid(ngl_segments(u)) # open modified URL in your browser browseURL(u) } # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_leaves.html","id":null,"dir":"Reference","previous_headings":"","what":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","title":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","text":"workhorse function underlies ability define synaptic connections neurotransmitter predictions flywire neurons.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_leaves.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","text":"","code":"flywire_leaves( x, cloudvolume.url = NULL, integer64 = FALSE, mip = 0L, bbox = NULL, cache = TRUE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_leaves.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","text":"x One FlyWire segment ids cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. integer64 Whether return ids integer64 type (default, compact little fragile) rather character (FALSE). mip mip level segmentation (expert use ) bbox bounding box within find supervoxels (default = NULL whole brain. Expert use .) cache Whether cache results flywire_leaves calls. See details. ... Additional arguments passed pbsapply eventually flywire_fetch method=\"flywire\" cv$CloudVolume method=\"cloudvolume\"","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_leaves.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","text":"default repeated calls flywire_leaves cached disk. functionality provided cachem package now used memoise package. default cache expand 1.5GB start pruning least recently used basis (LRU). 1.5GB might store 10-20,000 results flywire_leaves calls depending size corresponding neurons. Since root id can map hundreds thousands supervoxel ids, space implications. order save space, results stored compressed 64 bit integers (~30x smaller character vectors). compression step add extra ~ 5 100x + faster cache hit. default compression based suggested brotli library available, gzip otherwise. functionality memory cache top disk cache, currently exposed disk read time appears small compared time uncompressing overheads. cache can controlled two package options: fafbseg.cachedir location disk. previously set, set appropriate user folder package load using rappdirs::user_data_dir. Note cache function located inside folder called flywire_leaves. fafbseg.flcachesize maximum cache size bytes. storage space exceeds results pruned using LRU algorithm. Defaults 1.5 * 1024^3 unset. Note default configuration means cache shared given user across R sessions. worth bearing mind possibility race conditions multiple applications writing/pruning cache. example fafbseg.flcachesize different values different sessions, session smallest value start pruning files disk session.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_leaves.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find all the supervoxel (leaf) ids that are part of a FlyWire object — flywire_leaves","text":"","code":"# \\donttest{ kcid=\"720575940623755722\" length(flywire_leaves(kcid)) #> [1] 8536 # } if (FALSE) { # developer function to check cache status fafbseg:::flywire_leaves_cache_info() }"},{"path":"https://natverse.org/fafbseg/reference/flywire_neurons_add_synapses.html","id":null,"dir":"Reference","previous_headings":"","what":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","title":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","text":"Attach appropriate input output synapses flywire neuron skeleton neuronlist.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_neurons_add_synapses.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","text":"","code":"flywire_neurons_add_synapses( x, connectors = NULL, cloudvolume.url = NULL, method = c(\"auto\", \"spine\", \"sqlite\"), remove_autapses = TRUE, cleft.threshold = 0, Verbose = TRUE, transmitters = FALSE, local = NULL, ... ) # S3 method for neuron flywire_neurons_add_synapses( x, connectors = NULL, cloudvolume.url = NULL, method = c(\"auto\", \"spine\", \"sqlite\"), remove_autapses = TRUE, cleft.threshold = 0, Verbose = TRUE, transmitters = FALSE, local = NULL, ... ) # S3 method for neuronlist flywire_neurons_add_synapses( x, connectors = NULL, cloudvolume.url = NULL, method = c(\"auto\", \"spine\", \"sqlite\"), remove_autapses = TRUE, cleft.threshold = 0, Verbose = TRUE, transmitters = FALSE, local = NULL, ... ) flywire_synapse_annotations( x, file = NULL, scale = 1/c(4, 4, 40), sample = NULL, best = TRUE, cleft.threshold = 30, remove_autapses = TRUE, local = NULL, cloudvolume.url = NULL )"},{"path":"https://natverse.org/fafbseg/reference/flywire_neurons_add_synapses.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","text":"x nat::neuronlist flywire neurons FlyWire FAFB14 brainspace. skeletons can created using skeletor, retrieved using hemibrainr::flywire_neurons. using flywire_synapse_annotations can data.frame synapses, e.g. flywire_ntpred need formatted FlyWire annotations. connectors data.frame FAFB synapses, XYZ coordinates, attach x. NULL (default) synapses fetched, flywire_partners. cloudvolume.url segmentation source URL cloudvolume. Normally can ignore rely default segmentation chosen choose_segmentation method Whether use local SQLite database remote spine service synapse data. default auto uses local database available (45GB faster). remove_autapses whether remove autapses (defaults TRUE). cleft.threshold select synaptic connections exceeding confidence threshold (default 0 uses synapses; values range 30-100 seem make sense). Verbose Whether print status messages transmitters TRUE also attempt retrieve neurotransmitter predictions Eckstein et al. 2020, flywire neuron question. local path SQLite synapse data. Evaluated fafbseg:::local_or_google. Work progress. Default download data place ~/projects/JanFunke. ... methods sent nat::nlapply. file using flywire_synapse_annotations, file path output .csv. NULL, data.frame formatted like annotations CSV FlyWire, returned. scale scale factor applied XYZ coordinates synapses. Default moves nanometre FlyWire space raw voxel FlyWire space, appropriate FlyWire annotations. sample integer, number synapses sampled x. best logical. TRUE sample integer, synapses highest cleft scores chosen, 1:sample.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_neurons_add_synapses.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","text":"nat::neuronlist object, neuron neuronlist data.frame synapses neuron$connectors.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_neurons_add_synapses.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Attach synapses to flywire neuron skeletons — flywire_neurons_add_synapses","text":"","code":"# \\donttest{ if (FALSE) { choose_segmentation(\"flywire\") nx=xform_brain(elmr::dense_core_neurons, ref=\"FlyWire\", sample=\"FAFB14\") xyz = xyzmatrix(nx) ids = unique(flywire_xyz2id(xyz[sample(nrow(xyz),100),])) neurons = skeletor(ids, brain = elmr::FAFB14.surf) neurons.syns = flywire_neurons_add_synapses(neurons, transmitters = TRUE) neurons.syns[,] # Plot in 3D library(catmaid) nopen3d() plot3d(neurons.syns, WithConnectors = TRUE) # Axon-dendrite split library(hemibrainr) neurons.flow = flow_centrality(neurons.syns, polypre = TRUE, mode = \"centrifugal\") clear3d() plot3d_split(neurons.flow, WithConnectors = TRUE, transmitter = TRUE, radius = 1000, soma = 4000) # Save .csv of synapses as FlyWire annotations flywire_synapse_annotations(ids[1], file=\"annotations1.csv\", cleft.threshold=30) # And similar, from a neuronlist syns = hemibrainr::hemibrain_extract_synapses(neurons.flow, .parallel = TRUE, OmitFailures = TRUE) flywire_synapse_annotations(syns, file=\"annotations2.csv\", cleft.threshold=30) } # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_ntplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","title":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","text":"flywire_ntplot plots ggplot2 histogram predicted neurotransmitter vs prediction probability. flywire_ntplot3d makes 3D plot synapse location","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ntplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","text":"","code":"flywire_ntplot( x, nts = c(\"gaba\", \"acetylcholine\", \"glutamate\", \"octopamine\", \"serotonin\", \"dopamine\", \"neither\"), cleft.threshold = 0, local = NULL, cloudvolume.url = NULL ) flywire_ntplot3d( x, nts = c(\"gaba\", \"acetylcholine\", \"glutamate\", \"octopamine\", \"serotonin\", \"dopamine\"), plot = c(\"points\", \"spheres\"), cleft.threshold = 0, local = NULL, cloudvolume.url = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_ntplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","text":"x flywire rootid data.frame neurotransmitter predictions returned flywire_ntpred nts character vector neurotransmitters include plot (default 6) cleft.threshold threshold cleft score calculated Buhmann et al 2019 (default 0, used 30-100 increase specificity) local path SQLite synapse data. Evaluated fafbseg:::local_or_google. Work progress. Default download data place ~/projects/JanFunke. cloudvolume.url segmentation source URL cloudvolume. Normally can ignore rely default segmentation chosen choose_segmentation plot Whether plot points spheres (\"points\" size=5 works quite well) ... additional arguments passed spheres3d points3d","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ntplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","text":"flywire_ntplot returns ggplot2::ggplot object can customised modify plot (see examples).","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_ntplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot neurotransmitter prediction summaries or synapses in 3D — flywire_ntplot","text":"","code":"# \\donttest{ # a cholinergic olfactory projection neuron ntp=flywire_ntpred(\"720575940615237849\") #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist flywire_ntplot(ntp) #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. flywire_ntplot(ntp, nts=c(\"gaba\", \"acetylcholine\", \"glutamate\")) #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. flywire_ntplot(ntp, nts=c(\"gaba\", \"acetylcholine\", \"glutamate\"), cleft.threshold=100) #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. # ids for several Kenyon cells kcsel=c(\"720575940623755722\", \"720575940609992371\", \"720575940625494549\", \"720575940619442047\", \"720575940620517656\", \"720575940609793429\", \"720575940617265029\", \"720575940631869024\", \"720575940637441955\", \"720575940638892789\") kcpreds=flywire_ntpred(kcsel) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist # collect the ggplot object p <- flywire_ntplot(kcpreds) # print it to see the aggregate plot (all neurons together) p #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. # ... or use ggplot facets to separate by query neuron p+ggplot2::facet_wrap(query~.) #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. # } if (FALSE) { flywire_ntplot3d(ntp, nts=c(\"gaba\", \"acetylcholine\", \"glutamate\"), plot='points', cleft.threshold=30, size=5) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_ntpred.html","id":null,"dir":"Reference","previous_headings":"","what":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","title":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","text":"print.ntprediction method provides quick summary neurotransmitter prediction output synapses.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ntpred.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","text":"","code":"flywire_ntpred( x, cleft.threshold = 0, remove_autapses = TRUE, local = NULL, cloudvolume.url = NULL ) # S3 method for ntprediction print(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/flywire_ntpred.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","text":"x single root id string data.frame output (downstream) partners returned flywire_partners. cleft.threshold threshold cleft score calculated Buhmann et al 2019 (default 0, used 30-100 increase specificity) remove_autapses flywire_partner_summary whether remove autapses (defaults TRUE) local path SQLite synapse data. Evaluated fafbseg:::local_or_google. Work progress. Default download data place ~/projects/JanFunke. cloudvolume.url segmentation source URL cloudvolume. Normally can ignore rely default segmentation chosen choose_segmentation ... additional arguments passed print","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_ntpred.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","text":"data.frame neurotransmitter predictions","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_ntpred.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return raw neurotransmitter prediction results for output of flywire neuron — flywire_ntpred","text":"","code":"# \\donttest{ # an olfactory projection neuron flywire_ntpred(\"720575940615237849\") #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Warning: /home/runner/projects/JanFunke//20191211_fafbv14_buhmann2019_li20190805_nt20201223.db does not exist #> neuron 720575940615237849 with 23081 output synapses: #> acetylcholine serotonin dopamine gaba glutamate #> 94.658 2.158 1.447 0.737 0.607 #> octopamine #> 0.394 # alternatively if (FALSE) { flywire_ntpred(flywire_xyz2id(cbind(116923, 61378, 1474), rawcoords = T)) } # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":null,"dir":"Reference","previous_headings":"","what":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"flywire_nuclei finds nuclei based known rootids nucleus_ids flywire_nearest_nuclei returns nearest nucleus query xyz location. rawcoords=T input output positions raw voxels. Note however distances still calculated nm. xyz may contain single points unless k>1, case one query point allowed.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"","code":"flywire_nuclei(rootids = NULL, nucleus_ids = NULL, rawcoords = FALSE, ...) flywire_nearest_nuclei(xyz, rawcoords = F, k = 1)"},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"rootids Character vector specifying one flywire rootids. convenience flywire_partner_summary argument passed flywire_ids allowing pass data.frames, flywire URLs cell type queries. nucleus_ids ids nucleus table return (optional, NB one rootids nucleus_ids can provided). rawcoords Whether return coordinates raw form rather nm (default FALSE) ... Additional arguments passed flywire_cave_query xyz One (k=1) query points. raw coordinates rawcoords=T k number nearest nuclei return query position. k>1 currently limited one query point.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"data.frame containing information nuclei including id nucleus id pt_position XYZ position centre nucleus. always nm rawcoords=FALSE even remote table stores raw (uncalibrated) voxel coordinates. comma separated string rawcoords=TRUE since convenient pasting applications. pt_supervoxel_id corresponding nucleus may missing segmentation disrupted location nucleus e.g. masking issues, missing sections etc. pt_root_id current root id (pt_position maps onto segmentation.) volume volume cubic microns nucleus flywire_nearest_nuclei rawcoords=T input output positions raw voxels. Note however distances still calculated nm.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"flywire_nearest_nuclei caches nucleus table updates ids selected values. saves time subsequent queries assuming returning less half total rows.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_nuclei.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Queries for information about flywire nuclei (helpful for finding somata) — flywire_nuclei","text":"","code":"# \\donttest{ # an example where there are two nucleus matches flywire_nuclei(flywire_xyz2id(c(120152, 22864, 3564), rawcoords = TRUE)) #> # A tibble: 3 × 10 #> id created superceded_id valid volume pt_supervoxel_id #> #> 1 4390074 2021-06-23 19:56:08 NA t 0.172 7e16 #> 2 3533175 2021-06-23 20:01:43 NA t 21.0 7e16 #> 3 3533210 2021-06-23 19:57:49 NA t 6.74 7e16 #> # ℹ 4 more variables: pt_root_id , pt_position >, #> # bb_start_position >, bb_end_position > # } # \\donttest{ nn=flywire_nearest_nuclei(c(480608, 91456, 142560), k=2) as.data.frame(nn) #> id created superceded_id valid volume pt_supervoxel_id #> 1 3533210 2021-06-23 19:57:49 NA t 6.735708 78884462138180472 #> 2 3533175 2021-06-23 20:01:43 NA t 20.972257 78884462138083227 #> pt_root_id pt_position bb_start_position #> 1 720575940624943800 480608, 91456, 142560 478432, 89952, 142120 #> 2 720575940624943800 480512, 90784, 140360 478176, 89184, 138720 #> bb_end_position dist #> 1 482784, 92736, 143440 0.000 #> 2 482944, 92608, 141480 2302.347 flywire_nearest_nuclei('163113, 59074, 5295', rawcoords = TRUE) #> # A tibble: 1 × 11 #> id created superceded_id valid volume pt_supervoxel_id #> #> 1 6865768 2021-06-23 20:01:53 NA t 21.7 8e16 #> # ℹ 5 more variables: pt_root_id , pt_position , #> # bb_start_position , bb_end_position , dist # } if (FALSE) { # from clipboard e.g. copied from flywire flywire_nearest_nuclei(clipr::read_clip(), rawcoords = TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":null,"dir":"Reference","previous_headings":"","what":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"Rapid flywire connectivity summaries using cached connectome data","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"","code":"flywire_partner_summary2( ids, partners = c(\"outputs\", \"inputs\"), add_cell_types = TRUE, by.roi = FALSE, summarise = FALSE, threshold = 0, version = NULL )"},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"ids Root ids query (passed flywire_ids) partners Whether fetch input output synapses . add_cell_types Whether add cell type information result .roi Whether break connectivity rows neuropil region containing synapses. summarise Whether collapse results multiple query neurons single entry partner neuron. threshold flywire_partner_summary return partners greater number connections query neuron(s) (default 0 returns connections) version Optional CAVE version. default value NULL uses latest data dump available unless options(fafbseg.flywire_connectome_data_version) set (can conveniently using flywire_connectome_data_version()).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"data.frame","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"Note threshold applied row left grouping operations. Therefore .roi=TRUE neuropil regions exceeding threshold returned. CAVE specifies versions (effectively timestamps) connectome data. Every often Sven makes dump connectivity synapse information proofread neurons. order use data","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partner_summary2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rapid flywire connectivity summaries using cached connectome data — flywire_partner_summary2","text":"","code":"if (FALSE) { flywire_partner_summary2('DA2_lPN', partners='out') flywire_partner_summary2('DA2_lPN', partners='out', summarise=T) flywire_partner_summary2('DA2_lPN', partners='out', summarise=T, by.roi=T) flywire_partner_summary2('DA2_lPN', partners='out', summarise=T, by.roi=T, add_cell_types=F) %>% filter(!grepl(\"AL\", neuropil)) %>% group_by(post_pt_root_id) %>% summarise(weight = sum(weight), top_np = neuropil[1]) %>% arrange(desc(weight)) %>% # nb version = TRUE will use ensure that ids match the default CAVE version add_celltype_info(version=TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":null,"dir":"Reference","previous_headings":"","what":"Find the input/output partners for a flywire neuron — flywire_partners","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"flywire_partners low level function returning one row every synapse. flywire_partner_summary summarises connectivity one flywire neurons.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"","code":"flywire_partners( rootids, partners = c(\"outputs\", \"inputs\", \"both\"), details = FALSE, roots = TRUE, reference = c(\"either\", \"FAFB14\", \"FlyWire\"), cloudvolume.url = NULL, method = c(\"auto\", \"spine\", \"sqlite\"), Verbose = TRUE, local = NULL, ... ) flywire_partner_summary( rootids, partners = c(\"outputs\", \"inputs\"), threshold = 0, remove_autapses = TRUE, cleft.threshold = 0, summarise = FALSE, surf = NULL, version = NULL, timestamp = NULL, method = c(\"auto\", \"spine\", \"sqlite\", \"cave\"), Verbose = NA, local = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"rootids Character vector specifying one flywire rootids. convenience flywire_partner_summary argument passed flywire_ids allowing pass data.frames, flywire URLs cell type queries. partners Whether fetch input output synapses . details Whether include additional details X Y Z location (default FALSE) roots Whether fetch flywire rootids partner neurons (default TRUE) reference character vector templatebrain object specifying reference template brain 3D coordinate information. default value \"either\" use natural reference space data source (FAFB14 SQLite tables, FlyWire spine service). cloudvolume.url segmentation source URL cloudvolume. Normally can ignore rely default segmentation chosen choose_segmentation method Whether use local SQLite database remote spine service synapse data. default auto uses local database available (45GB faster). Verbose Whether print status messages local path SQLite synapse data. Evaluated fafbseg:::local_or_google. Work progress. Default download data place ~/projects/JanFunke. ... Additional arguments passed pbsapply threshold flywire_partner_summary return partners greater number connections query neuron(s) (default 0 returns connections) remove_autapses flywire_partner_summary whether remove autapses (defaults TRUE) cleft.threshold threshold cleft score calculated Buhmann et al 2019 (default 0, used 30-100 increase specificity) summarise Whether collapse results multiple query neurons single entry partner neuron. surf object defining 3D ROI inside presynaptic position must located. Can mesh3d object, object .mesh3d can handle including hxsurf boundingbox objects. See pointsinside details. version Integer materialisation version timestamp timestamp normalise R Python timestamp UTC. special value 'now' means current time UTC.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"data.frame regtemplate attribute specifying reference brain space xyz points. Columns vary slightly depending whether data fetched spine/ITANNA local sqlite database. obscure ones include: prepost partners = \"\" column present. given row (synapse), prepost=1 initial query neuron downstream (postsynaptic) partner upstream. score came straight Buhmann et al supposed indicate confidence score predicted synapse. cleft_score useful one later addition Stephan Gerhard asks whether pre post synapses positioned sensible distances side cleft defined separate neural network Larissa Heinrich Stephan Saalfeld’s group.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"FIXME behaviour partners well-defined. Note many duplicated connections raw output, false autapses (.e. neuron connected ) false positives. See Buhmann et al details ideas cleaning results. Also note ids returned class integer64 flywire_partners one row synapses/connection; flywire_partner_summary rows report number connections pairs neurons, type character. integer64 type compact less robust base R type instead provided bit64 package. R functions sapply strip class integer64 vectors, treating doubles completely different value. flywire_partners flywire_partner_summary default report active connectivity state neurons. present flywire_partner_summary allows time travel historic materialisations using version timestamp arguments (see flywire_timestamp details). support actually depends cave backend (automatically selected method='auto').","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_partners.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find the input/output partners for a flywire neuron — flywire_partners","text":"","code":"# \\donttest{ pp=flywire_partners(\"720575940621039145\") #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Fetching supervoxel ids for id: 720575940621039145 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids head(pp) #> offset scores cleft_scores pre_svid post_svid #> 1 152196 9.542592 117 81491472725509269 81491472725509199 #> 2 828599 93.800766 0 81561978908660664 81561978908653994 #> 3 828625 93.588776 1 81561978908669037 81561978908667521 #> 4 1236913 54.307476 1 81631042385463742 81631042385462154 #> 5 1236914 33.748131 0 81631042385459399 81631042385454876 #> 6 1236915 6.670522 0 81631042385462087 81631042385470852 #> post_id pre_id #> 1 720575940623607372 720575940621039145 #> 2 720575940632985261 720575940621039145 #> 3 720575940589754844 720575940621039145 #> 4 720575940623607372 720575940621039145 #> 5 720575940623607372 720575940621039145 #> 6 720575940623607372 720575940621039145 class(pp$post_id) #> [1] \"integer64\" # } # \\donttest{ # Note that post_id is of type character flywire_partner_summary(\"720575940621039145\", partners='out') #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Fetching supervoxel ids for id: 720575940621039145 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids #> # A tibble: 1,215 × 3 #> post_id weight n #> #> 1 720575940623607372 891 1 #> 2 720575940630149419 172 1 #> 3 720575940622838154 62 1 #> 4 720575940631200327 62 1 #> 5 720575940631914700 34 1 #> 6 720575940628412732 31 1 #> 7 720575940619553671 30 1 #> 8 720575940621000831 29 1 #> 9 720575940611428761 27 1 #> 10 720575940624743946 27 1 #> # ℹ 1,205 more rows flywire_partner_summary(\"720575940621039145\", partners='in') #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Fetching supervoxel ids for id: 720575940621039145 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids #> # A tibble: 620 × 3 #> pre_id weight n #> #> 1 720575940623607372 891 1 #> 2 720575940613380914 90 1 #> 3 720575940631842360 88 1 #> 4 720575940621000831 77 1 #> 5 720575940613056149 74 1 #> 6 720575940631200327 69 1 #> 7 720575940624377224 62 1 #> 8 720575940613603737 60 1 #> 9 720575940635047672 57 1 #> 10 720575940621717469 56 1 #> # ℹ 610 more rows flywire_partner_summary(\"720575940621039145\") #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Fetching supervoxel ids for id: 720575940621039145 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids #> # A tibble: 1,215 × 3 #> post_id weight n #> #> 1 720575940623607372 891 1 #> 2 720575940630149419 172 1 #> 3 720575940622838154 62 1 #> 4 720575940631200327 62 1 #> 5 720575940631914700 34 1 #> 6 720575940628412732 31 1 #> 7 720575940619553671 30 1 #> 8 720575940621000831 29 1 #> 9 720575940611428761 27 1 #> 10 720575940624743946 27 1 #> # ℹ 1,205 more rows # summary for neuron at a XYZ location (in this case in raw coordinates) flywire_partner_summary(flywire_xyz2id(cbind(155682, 58180, 3215), rawcoords = TRUE)) #> Warning: /home/runner/projects/JanFunke//flywire_synapses.db does not exist #> Fetching supervoxel ids for id: 720575940623607372 #> Finding synapses for supervoxels #> Reading synapse data #> Fetching root ids #> # A tibble: 1,214 × 3 #> post_id weight n #> #> 1 720575940630149419 172 1 #> 2 720575940622838154 62 1 #> 3 720575940631200327 62 1 #> 4 720575940631914700 34 1 #> 5 720575940628412732 31 1 #> 6 720575940619553671 30 1 #> 7 720575940621000831 29 1 #> 8 720575940611428761 27 1 #> 9 720575940624743946 27 1 #> 10 720575940650971257 27 1 #> # ℹ 1,204 more rows if (FALSE) { # Use Ctrl+Shift+J to share a flywire scene and then do this to get partner # summary for that URL flywire_partner_summary(clipr::read_clip()) cct=flywire_cave_query('cambridge_celltypes', live = T) dl1.lh=flywire_partner_summary(cct$pt_root_id[grep(\"DL1\", cct$cell_type)], surf=subset(elmr::FAFB14NP.surf, \"LH_R\")) # use a rectangular bounding box around LH instead dl1.lhbb=flywire_partner_summary(cct$pt_root_id[grep(\"DL1\", cct$cell_type)], surf=boundingbox(subset(elmr::FAFB14NP.surf, \"LH_R\"))) } # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":null,"dir":"Reference","previous_headings":"","what":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"Find root_id FlyWire segment / supervoxel.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"","code":"flywire_rootid( x, method = c(\"auto\", \"cave\", \"cloudvolume\", \"flywire\"), integer64 = FALSE, timestamp = NULL, version = NULL, cache = FALSE, stop_layer = NULL, cloudvolume.url = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"x One FlyWire segment ids method Whether use flywire API (slow python required) cave/cloudvolume (faster many input ids, requires python). \"auto\" (default) choose \"cave\" \"cloudvolume\" (order) available flywire otherwise. integer64 Whether return ids integer64 type (compact little fragile) rather character (default FALSE). timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. version optional CAVE materialisation version number. See details examples. cache Whether cache supervoxel id -> rootid mappings. Default FALSE works version timestamp available. Note cache held memory therefore regenerated R session. stop_layer layer chunked graph stop . default NULL equivalent layer 1 full root id. Coarser layer 2 IDs can useful intermediate operations. cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. ... Additional arguments passed pbsapply eventually flywire_fetch method=\"flywire\" cv$CloudVolume method=\"cloudvolume\"","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"vector root ids character vectors.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"main purpose function convert supervoxel current root id whole segment. segment id updated due editing, calling original segment id still return segment id (although calling supervoxel return new segment id). wish find latest root id, can use flywire_latestid, fairly slow (think 1 second per neuron). However general best select XYZ location defining neuron interest, associated supervoxel id store , since can rapidly looked flywire_xyz2id flywire_rootid. three methods. \"flywire\" simpler much slower many supervoxels since id requires separate http request. \"cave\" method much faster can process hundreds ids per second. order avoid sending many requests one go (limit post message size), id lookups chunked maximum 50,000 lookups single call. can modified passing chunksize argument setting fafbseg.flywire_roots.chunksize option. Set smaller queries time / give \"Request Entity Large\" errors. Larger settings unlikely much speed impact. cloudvolume method default August 2022. uses server endpoint tests 2x slower cave (still much faster method='flywire')","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_rootid.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find the root_id of a FlyWire segment / supervoxel. — flywire_rootid","text":"","code":"# \\donttest{ flywire_rootid(c(\"81489548781649724\", \"80011805220634701\")) #> [1] \"720575940628309186\" \"720575940630034127\" # same but using the flywire sandbox segmentation with_segmentation('sandbox', { flywire_rootid(c(\"81489548781649724\", \"80011805220634701\")) }) #> [1] \"720575940626292279\" \"720575940618460245\" # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_scene.html","id":null,"dir":"Reference","previous_headings":"","what":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","title":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","text":"Return sample Neuroglancer scene URL FlyWire dataset","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_scene.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","text":"","code":"flywire_scene( ids = NULL, annotations = NULL, open = FALSE, shorten = FALSE, segmentation = \"flywire31\", ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_scene.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","text":"ids set root ids include scene. Also accepts data.frame containing column rootid, root_id, id form acceptable ngl_segments including neuroglancer scene URLs. annotations data.frame matrix position information annotation layers. See ngl_annotation_layers details. open Whether open scene default browser shorten currently implemented segmentation Defaults 'flywire31'. See choose_segmentation options. ... Passed ngl_annotation_layers","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_scene.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","text":"character vector containing single Neuroglancer URL (invisibly open=TRUE)","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_scene.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return a sample Neuroglancer scene URL for FlyWire dataset — flywire_scene","text":"","code":"if (FALSE) { flywire_scene(open=T) # top 20 partners of a neuron flywire_scene(flywire_partner_summary(\"720575940621039145\", partners='out')$partner[1:20], open=T) # using the ability to query flytable for cell types flywire_scene('DA2_lPN', open=TRUE) flywire_scene('class:MBON_R', open=TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":null,"dir":"Reference","previous_headings":"","what":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"chunkedgraph_token returns current chunked graph token, optionally specified URL / domain name. Writes token standard location disk found cloudvolume python package well fafbseg package used authenticate https://flywire.ai.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"","code":"chunkedgraph_token(url = NULL, cached = TRUE) flywire_set_token(token = NULL, domain = NULL)"},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"url URL domain name defines scope token cached Whether use cached version token (default yes speed, set FALSE reload writing new token disk). token Optional character vector containing token. missing, new token requested (note invalidate previous token) domain Optional fully qualified domain name, prepended filename token stored.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"character vector containing token (typically 32-44 bytes) path file storing token (invisibly)","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"Since cloudvolume 3.10.0 April 2021, recommended token filenames look like 'cave-secret.json' 'cave-secret.json'","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_set_token.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Record (and if necessary create) a FlyWire chunkedgraph token — chunkedgraph_token","text":"","code":"if (FALSE) { # Will open browser to get new token flywire_set_token() # Writes a known token to correct location flywire_set_token(\"2f88e16c4f21bfcb290b2a8288c05bd0\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_shortenurl.html","id":null,"dir":"Reference","previous_headings":"","what":"Shorten or expand neuroglancer URLs — flywire_shortenurl","title":"Shorten or expand neuroglancer URLs — flywire_shortenurl","text":"flywire_shortenurl makes short URLs long URLs ngscene objects may constructed R. flywire_expandurl expands shortened URLs full neuroglancer JSON scene specification. active segmentation (choose_segmentation) flywire segmentation used define initial part output URL, otherwise flywire31 segmentation used. flywire_expandurl also expand tinyurl.com URLs.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_shortenurl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Shorten or expand neuroglancer URLs — flywire_shortenurl","text":"","code":"flywire_shortenurl(x, include_base = TRUE, baseurl = NULL, cache = TRUE, ...) flywire_expandurl(x, json.only = FALSE, cache = TRUE, ...)"},{"path":"https://natverse.org/fafbseg/reference/flywire_shortenurl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Shorten or expand neuroglancer URLs — flywire_shortenurl","text":"x One neuroglancer URLs (flywire_expandurl) ngscene parsed scene description. include_base Whether return full URL open neuroglancer session (default) component defines scene (display JSON browser). baseurl Optional URL defining neuroglancer browser use shortened URLs. cache Whether cache calls flywire state server shortening expanding URLs. Default TRUE. NB cache active current session. ... Additional arguments passed pbsapply (multiple URLs process) ngl_encode_url (generating short URL ngscene list object) flywire_fetch using flywire_expandurl. json.return JSON fragment rather neuroglancer URL","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_shortenurl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Shorten or expand neuroglancer URLs — flywire_shortenurl","text":"character vector containing one URLs.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_shortenurl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Shorten or expand neuroglancer URLs — flywire_shortenurl","text":"","code":"if (FALSE) { sc=ngl_blank_scene() short=flywire_shortenurl(sc) long=flywire_expandurl(short) } # \\donttest{ flywire_expandurl(\"https://globalv1.flywire-daf.com/nglstate/5747205470158848\") #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22tab%22%3A%22graph%22%2C%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprodv1.flywire-daf.com%2Fsegmentation%2F1.0%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22selectedAlpha%22%3A0.62%2C%22colorSeed%22%3A1358768360%2C%22segments%22%3A%5B%22720575940619527173%22%2C%22720575940628130268%22%2C%22720575940630484179%22%5D%2C%22hiddenSegments%22%3A%5B%22720575940634222734%22%2C%22720575940636364870%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B115198%2C55453%2C1537%5D%7D%7D%2C%22zoomFactor%22%3A4.145162302892657%7D%2C%22perspectiveOrientation%22%3A%5B-0.22566604614257812%2C-0.034010399132966995%2C-0.07959923148155212%2C0.97035151720047%5D%2C%22perspectiveZoom%22%3A4888.123757966904%2C%22showSlices%22%3Afalse%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" flywire_expandurl(\"https://tinyurl.com/rmr58jpn\") #> [1] \"https://neuroglancer-demo.appspot.com/#!%7B%22dimensions%22:%7B%22x%22:%5B1.6e-8%2C%22m%22%5D%2C%22y%22:%5B1.6e-8%2C%22m%22%5D%2C%22z%22:%5B4e-8%2C%22m%22%5D%7D%2C%22position%22:%5B35783.34765625%2C10234.412109375%2C3672.360107421875%5D%2C%22crossSectionScale%22:1.2071435133745394%2C%22projectionOrientation%22:%5B0.3210762143135071%2C-0.019618114456534386%2C-0.03835516422986984%2C-0.9460729956626892%5D%2C%22projectionScale%22:17861.319479912258%2C%22layers%22:%5B%7B%22type%22:%22image%22%2C%22source%22:%22precomputed://gs://flywire_em/aligned/v1%22%2C%22tab%22:%22source%22%2C%22name%22:%22v1%22%7D%2C%7B%22type%22:%22segmentation%22%2C%22source%22:%22graphene://middleauth+https://prod.flywire-daf.com/segmentation/1.0/fly_v31%22%2C%22tab%22:%22segments%22%2C%22segments%22:%5B%22720575940626927366%22%2C%22720575940632115923%22%5D%2C%22segmentQuery%22:%22720575940626927366%20720575940632115923%22%2C%22colorSeed%22:3185436646%2C%22name%22:%22fly_v31%22%7D%2C%7B%22type%22:%22segmentation%22%2C%22source%22:%7B%22url%22:%22graphene://middleauth+https://prod.flywire-daf.com/segmentation/1.0/fly_v31%22%2C%22transform%22:%7B%22matrix%22:%5B%5B-0.9923%2C-0.0451%2C0.0652%2C65672.5875%5D%2C%5B-0.0765%2C0.9961%2C0.0048%2C2454.31625%5D%2C%5B0.167%2C0.0059%2C0.9915%2C-2227.49425%5D%5D%2C%22outputDimensions%22:%7B%22x%22:%5B1.6e-8%2C%22m%22%5D%2C%22y%22:%5B1.6e-8%2C%22m%22%5D%2C%22z%22:%5B4e-8%2C%22m%22%5D%7D%7D%2C%22subsources%22:%7B%22default%22:true%2C%22graph%22:true%2C%22bounds%22:true%2C%22mesh%22:true%7D%2C%22enableDefaultSubsources%22:false%7D%2C%22tab%22:%22source%22%2C%22segments%22:%5B%22720575940626927366%22%5D%2C%22segmentQuery%22:%22720575940626927366%20720575940632115923%22%2C%22colorSeed%22:626504786%2C%22name%22:%22fly_v31_mirror%22%2C%22archived%22:true%7D%2C%7B%22type%22:%22segmentation%22%2C%22source%22:%22precomputed://https://spine.itanna.io/files/eric/jfrc_mesh_test%22%2C%22tab%22:%22source%22%2C%22selectedAlpha%22:0.55%2C%22objectAlpha%22:0.09%2C%22segments%22:%5B%221%22%5D%2C%22colorSeed%22:2225652644%2C%22segmentColors%22:%7B%221%22:%22#cacdd8%22%7D%2C%22name%22:%22jfrc_mesh_test1%22%2C%22visible%22:false%7D%5D%2C%22showAxisLines%22:false%2C%22selectedLayer%22:%7B%22size%22:646%2C%22visible%22:true%2C%22layer%22:%22fly_v31_mirror%22%7D%2C%22layout%22:%7B%22type%22:%223d%22%2C%22orthographicProjection%22:true%7D%2C%22selection%22:%7B%22size%22:646%2C%22visible%22:false%7D%2C%22layerListPanel%22:%7B%22visible%22:true%7D%7D\" # }"},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":null,"dir":"Reference","previous_headings":"","what":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"flywire_sirepo_file_memo() memoised version 5 minute timeout","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"","code":"flywire_sirepo_file( p, mustWork = NA, read = FALSE, version = c(783L, 630L), ... ) flywire_sirepo_file_memo( p, mustWork = NA, read = FALSE, version = c(783L, 630L), ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"p Relative path file within flywire_annotations repository mustWork Whether path must exists (default NA => TRUE reading file) read Whether read file. Either logical value function. TRUE p tsv csv file default read function used (see details). version integer CAVE materialisation version (see flywire_connectome_data_version) ... Additional arguments passed function determined read argument (typically data.table::fread).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"path (read=TRUE function) result reading file (data.table csv/tsv files).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"TRUE p tsv csv file data.table::fread function used order ensure 64 bit integers correctly parsed. default behaviour read ids character vectors can overridden (see examples).","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_sirepo_file.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read or return path to FlyWire annotations manuscript supplementary file — flywire_sirepo_file","text":"","code":"if (FALSE) { annpath=flywire_sirepo_file('supplemental_files/Supplemental_file1_annotations.tsv', read=FALSE) # read in annotation file anns=flywire_sirepo_file('supplemental_files/Supplemental_file1_annotations.tsv', read = TRUE) # read in annotation file with ids as 64 bit integers rather than strings anns=flywire_sirepo_file('supplemental_files/Supplemental_file1_annotations.tsv', read = TRUE, integer64=\"integer64\") # same but memoised to avoid checking github / re-reading file anns=flywire_sirepo_file_memo('supplemental_files/Supplemental_file1_annotations.tsv', read = TRUE, integer64=\"integer64\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":null,"dir":"Reference","previous_headings":"","what":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"Find standard UTC timestamp flywire materialisation version timestamp","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"","code":"flywire_timestamp( version = NULL, timestamp = NULL, convert = TRUE, datastack_name = getOption(\"fafbseg.cave.datastack_name\", \"flywire_fafb_production\") )"},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"version Integer materialisation version timestamp timestamp normalise R Python timestamp UTC. special value 'now' means current time UTC. convert Whether convert Python R timestamp (default: TRUE) datastack_name defaults \"flywire_fafb_production\". See https://global.daf-apis.com/info/ options.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"POSIXct object Python datetime object UTC timezone.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"Note CAVE timestamps UTC. timestamp argument character vector assumed UTC regardless timezone specification. Unless input character vector contains string \"UTC\" warning issued.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_timestamp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find standard UTC timestamp for flywire materialisation version or timestamp — flywire_timestamp","text":"","code":"# \\donttest{ ts=flywire_timestamp(349) ts #> [1] \"2022-04-18 08:10:00 UTC\" # As a unix timestamp (number of seconds since 00:00 on 1970-01-01) as.numeric(ts) #> [1] 1650269400 tsp=flywire_timestamp(349, convert=FALSE) # should be same as the numeric timestamp above tsp$timestamp() #> [1] 1650269400 flywire_timestamp(timestamp=\"2022-08-28 17:04:49 UTC\") #> [1] \"2022-08-28 17:04:49 UTC\" # nb this will return the current time *in UTC* regardless of your timezone flywire_timestamp(timestamp=\"now\") #> [1] \"2024-01-26 23:36:51 UTC\" # } if (FALSE) { # same but gives a warning flywire_timestamp(timestamp=\"2022-08-28 17:04:49\") }"},{"path":"https://natverse.org/fafbseg/reference/flywire_updateids.html","id":null,"dir":"Reference","previous_headings":"","what":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","title":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","text":"flywire_updateids updates root ids latest version (arbitrary integer materialisation version / timestamp specify). efficient possible, use supervoxel ids, XYZ positions failing slower flywire_latestid. November 2022 default behaviour use per-session supervoxel id root id cache order speed repeated lookups root id / supervoxel id pairs given timestamp/version. See flywire_rootid details.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_updateids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","text":"","code":"flywire_updateids( x, svids = NULL, xyz = NULL, rawcoords = FALSE, voxdims = c(4, 4, 40), cache = NA, version = NULL, timestamp = NULL, Verbose = TRUE, ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_updateids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","text":"x Current root ids svids optional supervoxel ids xyz optional xyz locations form understood xyzmatrix rawcoords whether input values raw voxel indices nm voxdims voxel dimensions nm used convert raw coordinates. cache Whether cache supervoxel id root id mappings. default value NA version timestamp argument specified. See flywire_rootid details. version optional CAVE materialisation version number. See details examples. timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. Verbose Whether print message console updates required. ... Additional arguments passed flywire_islatest flywire_latestid","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_updateids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","text":"vector form x updated ids.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_updateids.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Update flywire root ids to any timestamp using XYZ position or supervoxel ids — flywire_updateids","text":"","code":"kcs=data.frame( rootid=c(\"720575940602553568\", \"720575940602564320\", \"720575940602605536\"), xyz=c(\"(159284,42762,3594)\", \"(159035,41959,3594)\", \"(157715,44345,3594)\") ) # update root ids kcs$rootid=flywire_updateids(kcs$rootid, xyz=kcs$xyz)"},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":null,"dir":"Reference","previous_headings":"","what":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"flywire_voxdims returns image voxel dimensions normally used scale raw nm coordinates.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"","code":"flywire_voxdims(url = getOption(\"fafbseg.sampleurl\")) flywire_nm2raw(x, vd = flywire_voxdims()) flywire_raw2nm(x, vd = flywire_voxdims())"},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"url Optional neuroglancer URL containing voxel size. Defaults getOption(\"fafbseg.sampleurl\") set choose_segmentation. x 3D coordinates form compatible xyzmatrix vd voxel dimensions nm. Expert use . Normally found automatically.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"flywire_voxdims 3-vector flywire_raw2nm flywire_nm2raw Nx3 matrix coordinates","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"relies nat >= 1.10.4","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_voxdims.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Handle raw and nm calibrated flywire coordinates — flywire_voxdims","text":"","code":"flywire_voxdims() #> [1] 4 4 40 # ensure that we use default production flywire scene with_segmentation('flywire', flywire_voxdims()) #> [1] 4 4 40 flywire_raw2nm(c(159144, 22192, 3560)) #> X Y Z #> [1,] 636576 88768 142400 flywire_raw2nm('159144 22192 3560') #> X Y Z #> [1,] 636576 88768 142400 if (FALSE) { flywire_nm2raw(clipr::read_clip()) }"},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":null,"dir":"Reference","previous_headings":"","what":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"Find FlyWire root supervoxel (leaf) ids XYZ locations","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"","code":"flywire_xyz2id( xyz, rawcoords = FALSE, voxdims = c(4, 4, 40), cloudvolume.url = NULL, root = TRUE, timestamp = NULL, version = NULL, stop_layer = NULL, integer64 = FALSE, fast_root = TRUE, method = c(\"auto\", \"cloudvolume\", \"spine\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"xyz One xyz locations Nx3 matrix form compatible xyzmatrix including neuron mesh3d surface objects. rawcoords whether input values raw voxel indices nm voxdims voxel dimensions nm used convert raw coordinates. cloudvolume.url URL CloudVolume fetch segmentation image data. default value NULL chooses flywire production segmentation dataset. root Whether return root id whole segment rather supervoxel id. timestamp optional timestamp string POSIXct, interpreted UTC timezone specified. version optional CAVE materialisation version number. See details examples. stop_layer layer chunked graph stop . default NULL equivalent layer 1 full root id. Coarser layer 2 IDs can useful intermediate operations. integer64 Whether return ids integer64 type (compact little fragile) rather character (default FALSE). fast_root Whether use fast two-step look-procedure finding roots. strongly recommended alternative approach retained validation purposes. method Whether use spine transform-service API cloudvolume lookup. \"auto\" presently synonym \"spine\". ... additional arguments passed pbapply looking multiple positions.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"character vector segment ids, NA lookup fails.","code":""},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"root ids define whole neuron segmented object. supervoxel ids correspond small group voxels assumed must belong object. supervoxel ids change given segmentation, whereas root ids change every time neuron edited. stable way refer FlyWire neuron choose nice safe location arbour (recommend major branch point) store location supervoxel id. can rapidly map supervoxel id current root id using flywire_rootid. November 2020, default approach look supervoxel ids 3D point using spine transform-service API. order 100x faster mapping via cloudvolume (since must make single web request every point) Eric Perlman optimised layout underlying data rapid mapping. Note using slower cloudvolume method (may still required volumes fast lookup via spine available) finding supervoxel given XYZ location order 3x faster finding root id agglomeration super voxels given object. Perhaps less intuitively, want look many root ids, actually quicker flywire_xyz2id(,root=F) followed flywire_rootid since function can look many root ids single call ChunkedGraph server. happens setting fast_root=TRUE, default.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/flywire_xyz2id.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find FlyWire root or supervoxel (leaf) ids for XYZ locations — flywire_xyz2id","text":"","code":"# \\donttest{ if (FALSE) { # example based on defining some sample points from real neurons # sample dataset from FAFB catmaid n=elmr::dense_core_neurons[[1]] set.seed(42) ss=sample(nvertices(n), size=10) # first convert FAF14 points to FlyWire coordinate space nx=xform_brain(elmr::dense_core_neurons[[1]], ref=\"FlyWire\", sample=\"FAFB14\") pts=xyzmatrix(nx)[ss,] } # for simplicity just define those same sample points directly pts = matrix( c(428910.52, 110629.64, 174800, 410201.86, 110419.1, 180400, 337136, 129926.28, 189280, 349981.85, 136041.53, 199280, 398361.74, 110731.26, 182640, 382789.26, 118987.04, 189920, 358033.92, 171592.92, 143960, 360990.48, 140277.42, 201400, 376258.06, 125201.51, 194400, 331370.31, 128338.58, 181760), ncol = 3, byrow = TRUE, dimnames = list(NULL, c(\"X\", \"Y\", \"Z\")) ) #' # Fast and simple appoach to find ids in one (user-facing) step flywire_xyz2id(pts) #> [1] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [4] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [7] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [10] \"720575940634984800\" ## illustrate what's happening under the hood # find the ids for the selected xyz locations # NB fast_root=FALSE was the default behaviour until Nov 2020 flywire_xyz2id(pts, fast_root=FALSE, method=\"cloudvolume\") #> [1] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [4] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [7] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [10] \"720575940634984800\" # we can also find the supervoxels - much faster svids=flywire_xyz2id(pts, root=FALSE) # now look up the root ids - very fast with method=\"cloudvolume\", the default flywire_rootid(svids) #> [1] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [4] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [7] \"720575940634984800\" \"720575940634984800\" \"720575940634984800\" #> [10] \"720575940634984800\" # }"},{"path":"https://natverse.org/fafbseg/reference/make_merge_graph.html","id":null,"dir":"Reference","previous_headings":"","what":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","title":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","text":"make_merge_graph generates graph representation agglomeration merges. merge_graph_components uses full merge graph find connected subgraph corresponding isolated merge groups.","code":""},{"path":"https://natverse.org/fafbseg/reference/make_merge_graph.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","text":"","code":"make_merge_graph(x, n = NA) merge_graph_components(g, n = NA)"},{"path":"https://natverse.org/fafbseg/reference/make_merge_graph.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","text":"x mergeinfo data.frame generated read_mergeinfo n testing purposes, number rows merge information process - default processes rows. g Either graph generated make_merge_graph mergeinfo data.frame generated read_mergeinfo.","code":""},{"path":"https://natverse.org/fafbseg/reference/make_merge_graph.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","text":"make_merge_graph returns igraph object, merge_graph_components returns list elements describing mapping segment ids merge groups.","code":""},{"path":"https://natverse.org/fafbseg/reference/make_merge_graph.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Graph representation of the agglomeration (merge) between raw segments — make_merge_graph","text":"","code":"if (FALSE) { g=make_merge_graph(mergeinfo) gc=merge_graph_components(g) str(gc) }"},{"path":"https://natverse.org/fafbseg/reference/meshparty_skeletonize.html","id":null,"dir":"Reference","previous_headings":"","what":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","title":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","text":"Skeletonize neurons using meshparty python library","code":""},{"path":"https://natverse.org/fafbseg/reference/meshparty_skeletonize.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","text":"","code":"meshparty_skeletonize(segments, savedir = NULL, invalidation_d = 12000, ...)"},{"path":"https://natverse.org/fafbseg/reference/meshparty_skeletonize.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","text":"segments neuron ids form understood ngl_segments paths obj files already saved disk. savedir save SWC files (defaults temporary directory) invalidation_d Distance parameter (nm) controlling skeletonisation level detail. See meshparty docs. ... additional arguments passed save_cloudvolume_meshes","code":""},{"path":"https://natverse.org/fafbseg/reference/meshparty_skeletonize.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","text":"character vector containing path one SWC files. Note SWCs calibrated µm even though input data nm.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/meshparty_skeletonize.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Skeletonize neurons using meshparty python library — meshparty_skeletonize","text":"","code":"if (FALSE) { meshparty_skeletonize(\"720575940614134045\") meshparty_skeletonize(\"720575940614134045.obj\") }"},{"path":"https://natverse.org/fafbseg/reference/ngl_add_colours.html","id":null,"dir":"Reference","previous_headings":"","what":"Add colours to the neuroglancer scene — ngl_add_colours","title":"Add colours to the neuroglancer scene — ngl_add_colours","text":"Add colours neuroglancer scene","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_add_colours.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add colours to the neuroglancer scene — ngl_add_colours","text":"","code":"ngl_add_colours(x, colours, layer = NULL)"},{"path":"https://natverse.org/fafbseg/reference/ngl_add_colours.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add colours to the neuroglancer scene — ngl_add_colours","text":"x neuroglancer scene form acceptable ngl_decode_scene (including URL) colours dataframe two columns, first id second colour, character vector colours named ids one colour added displayed neurons. See col2rgb additional details col can specified. layer Optional character vector specifying layer colour. lyaer=NULL (default) choose layer type segmentation_with_graph one exists.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_add_colours.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add colours to the neuroglancer scene — ngl_add_colours","text":"neuroglancer scene object (see ngl_decode_scene)","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_add_colours.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add colours to the neuroglancer scene — ngl_add_colours","text":"","code":"fw_url=with_segmentation('flywire31', getOption('fafbseg.sampleurl')) ngl_add_colours(fw_url, colours=c(\"720575940614404544\"=\"red\")) #> neuroglancer scene with 2 layers and 2 segments (of which 2 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 2 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31 if (FALSE) { # colour all neurons in the URL on the clipboard red. # Then convert back to URL and open in default browser browseURL(as.character(ngl_add_colours(clipr::read_clip(), col=\"red\"))) # Let's colour neurons from these 3 scenes in red, green and blue u1=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5695474417795072\" u2=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5198787572137984\" u3=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5673953041317888\" # sequentially build up a data.frame with the colour information # note that col will be recycled to the same length as the number of segments colourdf=data.frame(ids=ngl_segments(u1), col='red') colourdf=rbind(colourdf, data.frame(ids=ngl_segments(u2), col='green')) colourdf=rbind(colourdf, data.frame(ids=ngl_segments(u3), col='blue')) # apply that to the first URL sc=ngl_add_colours(u1, colourdf) browseURL(as.character(sc)) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":null,"dir":"Reference","previous_headings":"","what":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"Construct one neuroglancer annotation layers","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"","code":"ngl_annotation_layers(ann, rawcoords = NA, colpal = NULL)"},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"ann annotation dataframe (see details) object containing 3D vertices xyzmatrix can successfully extract points. rawcoords Whether points provided raw (voxel) coordinates calibrated (nm) positions. default NA try infer based coordinate values. colpal function character vector colour names used set colour layer.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"list additional class nglayers can added ngscene object produced ngl_decode_scene.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"ann arguments","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_annotation_layers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Construct one or more neuroglancer annotation layers — ngl_annotation_layers","text":"","code":"if (FALSE) { psp=flywire_cave_query('proofreading_status_public_v1') fwusers=googlesheets4::read_sheet('1G0zqA5DTrfd-a2LuebV4kcqNfl4q1ehlzHBrwT6ZMoc') psp2=left_join(psp, fwusers, by=c(\"user_id\"=\"id\")) psp2$layer=psp2$institution al=ngl_annotation_layers(psp2[c(\"pt_position\", \"layer\")]) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_annotations.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","title":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","text":"Extract annotations neuroglancer scene dataframe","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","text":"","code":"ngl_annotations( x, layer = NULL, types = c(\"point\", \"line\"), points = c(\"collapse\", \"expand\", \"list\") )"},{"path":"https://natverse.org/fafbseg/reference/ngl_annotations.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","text":"x neuroglancer scene URL (passed ngl_decode_scene necessary) layer Optional index vector specifying layers within scene extract annotations. probably safest use character vector layer names (appears neuroglancer). missing annotation layers processed. types annotation types process (currently points lines default) points point coordinates.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotations.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","text":"data.frame columns defined contents annotation layer types/points arguments. Additional attributes stored","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_annotations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract annotations from a neuroglancer scene into a dataframe — ngl_annotations","text":"","code":"# \\donttest{ u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5963849085747200\" adf=ngl_annotations(u) str(attr(adf, 'ann_attrs')) #> List of 1 #> $ lines:List of 9 #> ..$ tool : chr \"annotatePoint\" #> ..$ selectedAnnotation :List of 1 #> .. ..$ id: chr \"c8e65c47e6677d4dcb2bc2846c26ec4b277756c4\" #> ..$ type : chr \"annotation\" #> ..$ annotationTags :List of 3 #> .. ..$ :List of 2 #> .. .. ..$ id : int 1 #> .. .. ..$ label: chr \"good\" #> .. ..$ :List of 2 #> .. .. ..$ id : int 2 #> .. .. ..$ label: chr \"bad\" #> .. ..$ :List of 2 #> .. .. ..$ id : int 3 #> .. .. ..$ label: chr \"ok\" #> ..$ voxelSize : int [1:3] 4 4 40 #> ..$ linkedSegmentationLayer : chr \"Production-segmentation_with_graph\" #> ..$ bracketShortcutsShowSegmentation : logi FALSE #> ..$ annotationSelectionShowsSegmentation: logi FALSE #> ..$ name : chr \"lines\" # }"},{"path":"https://natverse.org/fafbseg/reference/ngl_blank_scene.html","id":null,"dir":"Reference","previous_headings":"","what":"Return a blank neuroglancer scene based on a specified segmentation — ngl_blank_scene","title":"Return a blank neuroglancer scene based on a specified segmentation — ngl_blank_scene","text":"defaults current segmentation defined choose_segmentation release=NULL","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_blank_scene.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return a blank neuroglancer scene based on a specified segmentation — ngl_blank_scene","text":"","code":"ngl_blank_scene(release = NULL, return.url = FALSE)"},{"path":"https://natverse.org/fafbseg/reference/ngl_blank_scene.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return a blank neuroglancer scene based on a specified segmentation — ngl_blank_scene","text":"release character vector specifying released segmentation via known short name sample neuroglancer URL. return.url Whether return URL rather ngscene object.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_blank_scene.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return a blank neuroglancer scene based on a specified segmentation — ngl_blank_scene","text":"","code":"# blank scene for current segmentation ngl_blank_scene() #> neuroglancer scene with 2 layers and 0 segments (of which 0 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 0 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31 # add a specific id ngl_blank_scene()+\"720575940623755722\" #> neuroglancer scene with 2 layers and 1 segments (of which 1 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 1 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31 # a different segmentation ngl_blank_scene(\"202004\") #> neuroglancer scene with 2 layers and 0 segments (of which 0 shown) #> name type visible nsegs nhidden #> 1 fafb_v14_clahe image TRUE 0 0 #> 2 fafb-ffn1-20200412 segmentation TRUE 0 0 #> source #> 1 precomputed://gs://neuroglancer-fafb-data/fafb_v14/fafb_v14_clahe #> 2 precomputed://gs://fafb-ffn1-20200412/segmentation u=ngl_blank_scene(\"202004\", return.url=TRUE) if (FALSE) { u=ngl_blank_scene(\"sandbox\") browseURL(u) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_decode_scene.html","id":null,"dir":"Reference","previous_headings":"","what":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","title":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","text":"ngl_decode_scene takes Neuroglancer scene web browser turns R list object can programmatically manipulated e.g. add/remove segments. Manipulate scenes ngl_segments, ngl_layers. See ngl_encode_url turn scene back URL open browser.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_decode_scene.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","text":"","code":"ngl_decode_scene( x, return.json = FALSE, simplifyVector = TRUE, simplifyDataFrame = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/ngl_decode_scene.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","text":"x Character vector containing single Neuroglancer URL json block return.json TRUE extracts JSON block URL parse R list simplifyVector coerce JSON arrays containing primitives atomic vector simplifyDataFrame coerce JSON arrays containing records (JSON objects) data frame ... additional arguments passed jsonlite::fromJSON","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_decode_scene.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","text":"R list additional class ngscene describing scene, , return.json=TRUE, character vector.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_decode_scene.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Decode and manipulate Neuroglancer scenes (from URLs or JSON blocks) — ngl_decode_scene","text":"","code":"# \\donttest{ # get sample FlyWire URL fw_url=with_segmentation('flywire31', getOption('fafbseg.sampleurl')) # only a 0 (dummy) segment id present ngl_segments(fw_url) #> [1] \"0\" # fw_sc=ngl_decode_scene(fw_url) fw_sc #> neuroglancer scene with 2 layers and 1 segments (of which 1 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 1 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prod.flywire-daf.com/segmentation/table/fly_v31 # add two segments fw_sc=fw_sc+c(\"720575940621039145\", \"720575940626877799\") ngl_segments(fw_sc) #> [1] \"0\" \"720575940621039145\" \"720575940626877799\" # remove that 0 segment fw_sc=fw_sc-0 ngl_segments(fw_sc) #> [1] \"720575940621039145\" \"720575940626877799\" # repeated segments are ignored i.e. no duplicates ngl_segments(fw_sc+\"720575940621039145\") #> [1] \"720575940621039145\" \"720575940626877799\" # convert back to a URL, nb this depends on choose_segmentation ngl_encode_url(fw_sc) #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprod.flywire-daf.com%2Fsegmentation%2Ftable%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22segments%22%3A%5B%22720575940621039145%22%2C%22720575940626877799%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B108360%2C42086%2C3279%5D%7D%7D%2C%22zoomFactor%22%3A8%7D%2C%22perspectiveZoom%22%3A2230.6094%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" if (FALSE) { # open in your default browser browseURL(ngl_encode_url(fw_sc)) } # } if (FALSE) { ngl_decode_scene(\"\") # decode scene from URL currently on clipboard scene=ngl_decode_scene(clipr::read_clip()) # open a Neuroglancer URL in CATMAID ngu=\"\" library(elmr) open_fafb(ngl_decode_scene(ngu)) # Or store the URL rather than opening it cmu=open_fafb(ngl_decode_scene(ngu), open=FALSE) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":null,"dir":"Reference","previous_headings":"","what":"Encode scene information into a neuroglancer URL — ngl_encode_url","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"ngl_encode_url converts R list containing neuroglancer scene URL can open browser. .character.ngscene another way convert neuroglancer scene object URL.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"","code":"ngl_encode_url(body, baseurl = NULL, auto_unbox = TRUE, ...) # S3 method for ngscene as.character(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"body text file character vector JSON data R list object class ngscene. baseurl URL specifying neuroglancer server (missing, uses URL body decoded recorded , failing , options(\"fafbseg.sampleurl\")). can use neuroglancer URL appropriately truncated encodes scene information. auto_unbox expert use . See toJSON details. ... Additional arguments toJSON x ngscene object converted URL","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"Character vector containing encoded URL","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"take pains ensure entries neuroglancer expects JSON arrays (including segments hiddenSegments) always mapped JSON array (even length 1). default baseurl depends current segmentation chosen choose_segmentation.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_encode_url.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Encode scene information into a neuroglancer URL — ngl_encode_url","text":"","code":"# \\donttest{ # get sample FlyWire URL fw_url=with_segmentation('flywire31', getOption('fafbseg.sampleurl')) # only a 0 (dummy) segment id present ngl_segments(fw_url) #> [1] \"0\" # fw_sc=ngl_decode_scene(fw_url) # add a segment fw_sc$layers[[2]]$segments=union(fw_sc$layers[[2]]$segments, \"720575940626877799\") # convert back to a URL, nb this depends on choose_segmentation ngl_encode_url(fw_sc) #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprod.flywire-daf.com%2Fsegmentation%2Ftable%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22segments%22%3A%5B%220%22%2C%22720575940626877799%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B108360%2C42086%2C3279%5D%7D%7D%2C%22zoomFactor%22%3A8%7D%2C%22perspectiveZoom%22%3A2230.6094%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" # another way to do this, which long time R users may find more intuitive as.character(fw_sc) #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprod.flywire-daf.com%2Fsegmentation%2Ftable%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22segments%22%3A%5B%220%22%2C%22720575940626877799%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B108360%2C42086%2C3279%5D%7D%7D%2C%22zoomFactor%22%3A8%7D%2C%22perspectiveZoom%22%3A2230.6094%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" if (FALSE) { # open in your default browser browseURL(ngl_encode_url(fw_sc)) # ... or browseURL(as.character(fw_sc)) } # } if (FALSE) { # copy JSON scene information from {} symbol at top right of neuroglancer # now make a permanent URL for the scene ngl_encode_url(clipr::read_clip()) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_layers.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","title":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","text":"ngl_layers extract neuroglancer layers convenience options selecting layers characteristics visibility, type etc. ngl_layers<- sets layers element ngscene object, taking care name/class details. +.ngscene adds segments layers neuroglancer scene -.ngscene removes segments whole layers neuroglancer scene. complain segment present.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_layers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","text":"","code":"ngl_layers(x, subset = NULL) ngl_layers(x) <- value # S3 method for ngscene +(x, y) # S3 method for ngscene -(x, y)"},{"path":"https://natverse.org/fafbseg/reference/ngl_layers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","text":"x neuroglancer scene object (see ngscene) subset expression (evaluated style subset.dataframe) defined value list specifying one neuroglancer layers. usually come json fragment another parsed neuroglancer scene. See examples. y Segments layers add remove neuroglancer scene. Segments provided character vectors applying ngl_segments complex object. Layers remove layer name. Layers add form R list returned ng_layers JSON fragment copied neuroglancer.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_layers.html","id":"using-and-","dir":"Reference","previous_headings":"","what":"Using + and -","title":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","text":"shortcut methods allow add subtract segments layers neuroglancer scenes. designed convenience interactive use, may bit fragile unusual inputs.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_layers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract and manipulate layers in a neuroglancer scene — ngl_layers","text":"","code":"# \\donttest{ u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5409525645443072\" sc=ngl_decode_scene(u) sc #> neuroglancer scene with 2 layers and 2 segments (of which 2 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 2 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 names(ngl_layers(sc)) #> [1] \"Production-image\" \"Production-segmentation_with_graph\" str(ngl_layers(sc)) #> List of 2 #> $ Production-image :List of 5 #> ..$ source : chr \"precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked\" #> ..$ type : chr \"image\" #> ..$ blend : chr \"default\" #> ..$ shaderControls: Named list() #> ..$ name : chr \"Production-image\" #> $ Production-segmentation_with_graph:List of 7 #> ..$ source : chr \"graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31\" #> ..$ type : chr \"segmentation_with_graph\" #> ..$ segments : chr [1:2] \"720575940621039145\" \"720575940626877799\" #> ..$ skeletonRendering :List of 2 #> .. ..$ mode2d: chr \"lines_and_points\" #> .. ..$ mode3d: chr \"lines\" #> ..$ graphOperationMarker:List of 2 #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> ..$ pathFinder :List of 2 #> .. ..$ color : chr \"#ffff00\" #> .. ..$ pathObject:List of 2 #> .. .. ..$ annotationPath:List of 2 #> .. .. .. ..$ annotations: list() #> .. .. .. ..$ tags : list() #> .. .. ..$ hasPath : logi FALSE #> ..$ name : chr \"Production-segmentation_with_graph\" #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" str(ngl_layers(sc, nsegs>0)) #> List of 1 #> $ Production-segmentation_with_graph:List of 7 #> ..$ source : chr \"graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31\" #> ..$ type : chr \"segmentation_with_graph\" #> ..$ segments : chr [1:2] \"720575940621039145\" \"720575940626877799\" #> ..$ skeletonRendering :List of 2 #> .. ..$ mode2d: chr \"lines_and_points\" #> .. ..$ mode3d: chr \"lines\" #> ..$ graphOperationMarker:List of 2 #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> ..$ pathFinder :List of 2 #> .. ..$ color : chr \"#ffff00\" #> .. ..$ pathObject:List of 2 #> .. .. ..$ annotationPath:List of 2 #> .. .. .. ..$ annotations: list() #> .. .. .. ..$ tags : list() #> .. .. ..$ hasPath : logi FALSE #> ..$ name : chr \"Production-segmentation_with_graph\" #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" str(ngl_layers(sc, visible==TRUE)) #> List of 2 #> $ Production-image :List of 5 #> ..$ source : chr \"precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked\" #> ..$ type : chr \"image\" #> ..$ blend : chr \"default\" #> ..$ shaderControls: Named list() #> ..$ name : chr \"Production-image\" #> $ Production-segmentation_with_graph:List of 7 #> ..$ source : chr \"graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31\" #> ..$ type : chr \"segmentation_with_graph\" #> ..$ segments : chr [1:2] \"720575940621039145\" \"720575940626877799\" #> ..$ skeletonRendering :List of 2 #> .. ..$ mode2d: chr \"lines_and_points\" #> .. ..$ mode3d: chr \"lines\" #> ..$ graphOperationMarker:List of 2 #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> ..$ pathFinder :List of 2 #> .. ..$ color : chr \"#ffff00\" #> .. ..$ pathObject:List of 2 #> .. .. ..$ annotationPath:List of 2 #> .. .. .. ..$ annotations: list() #> .. .. .. ..$ tags : list() #> .. .. ..$ hasPath : logi FALSE #> ..$ name : chr \"Production-segmentation_with_graph\" #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" str(ngl_layers(sc, !visible)) #> Named list() #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" # flywire segmentation str(ngl_layers(sc, type==\"segmentation_with_graph\")) #> List of 1 #> $ Production-segmentation_with_graph:List of 7 #> ..$ source : chr \"graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31\" #> ..$ type : chr \"segmentation_with_graph\" #> ..$ segments : chr [1:2] \"720575940621039145\" \"720575940626877799\" #> ..$ skeletonRendering :List of 2 #> .. ..$ mode2d: chr \"lines_and_points\" #> .. ..$ mode3d: chr \"lines\" #> ..$ graphOperationMarker:List of 2 #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> ..$ pathFinder :List of 2 #> .. ..$ color : chr \"#ffff00\" #> .. ..$ pathObject:List of 2 #> .. .. ..$ annotationPath:List of 2 #> .. .. .. ..$ annotations: list() #> .. .. .. ..$ tags : list() #> .. .. ..$ hasPath : logi FALSE #> ..$ name : chr \"Production-segmentation_with_graph\" #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" # image or segmentation str(ngl_layers(sc, type %in% c(\"image\", \"segmentation_with_graph\"))) #> List of 2 #> $ Production-image :List of 5 #> ..$ source : chr \"precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked\" #> ..$ type : chr \"image\" #> ..$ blend : chr \"default\" #> ..$ shaderControls: Named list() #> ..$ name : chr \"Production-image\" #> $ Production-segmentation_with_graph:List of 7 #> ..$ source : chr \"graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31\" #> ..$ type : chr \"segmentation_with_graph\" #> ..$ segments : chr [1:2] \"720575940621039145\" \"720575940626877799\" #> ..$ skeletonRendering :List of 2 #> .. ..$ mode2d: chr \"lines_and_points\" #> .. ..$ mode3d: chr \"lines\" #> ..$ graphOperationMarker:List of 2 #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> .. ..$ :List of 2 #> .. .. ..$ annotations: list() #> .. .. ..$ tags : list() #> ..$ pathFinder :List of 2 #> .. ..$ color : chr \"#ffff00\" #> .. ..$ pathObject:List of 2 #> .. .. ..$ annotationPath:List of 2 #> .. .. .. ..$ annotations: list() #> .. .. .. ..$ tags : list() #> .. .. ..$ hasPath : logi FALSE #> ..$ name : chr \"Production-segmentation_with_graph\" #> - attr(*, \"class\")= chr [1:2] \"nglayers\" \"list\" # } # get a sample flywire neuroglancer scene sc=ngl_decode_scene(system.file(\"flywire-annotations.json\" , package = 'fafbseg')) sc #> neuroglancer scene with 4 layers and 43 segments (of which 1 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 1 #> 3 annotation annotation TRUE 0 #> 4 jfrc_mesh_test segmentation FALSE 1 #> nhidden #> 1 0 #> 2 42 #> 3 0 #> 4 1 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 #> 3 #> 4 precomputed://https://spine.itanna.io/files/eric/jfrc_mesh_test # save a copy sc.orig <- sc # remove a layer ngl_layers(sc)=ngl_layers(sc)[-3] # or using convenient - notation sc.noann <- sc.orig - \"annotation\" # reverse layer order ngl_layers(sc)=ngl_layers(sc)[2:1] # keep visible only ngl_layers(sc) <- ngl_layers(sc, visible) # visible + multiple segments ngl_layers(sc) <- ngl_layers(sc, visible & nsegs>0) # flywire segmentation ngl_layers(sc) <- ngl_layers(sc, type==\"segmentation_with_graph\") # combine layers using + convenience method sc.noann + ngl_layers(sc.orig)['annotation'] #> neuroglancer scene with 4 layers and 43 segments (of which 1 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 1 #> 3 jfrc_mesh_test segmentation FALSE 1 #> 4 annotation annotation TRUE 0 #> nhidden #> 1 0 #> 2 42 #> 3 1 #> 4 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 #> 3 precomputed://https://spine.itanna.io/files/eric/jfrc_mesh_test #> 4 if (FALSE) { # combine layers from two scenes ngl_layers(sc) <- c(ngl_layers(sc), ngl_layers(sc2)) ngl_layers(sc) <- c(ngl_layers(sc)[-(3:4)], ngl_layers(sc2)[3:4]) ngl_layers(sc) <- c(ngl_layers(sc), ngl_layers(sc2)[-1]) ngl_layers(sc) <- c(ngl_layers(sc), ngl_layers(sc2)['annotation']) sc # another way to add a single scene ngl_layers(sc)[[4]] <- ngl_layers(sc2)[[4]] # add a new layer to a scene by parsing some JSON from the clipboard # note the double brackets are essential here ngl_layers(sc)[['jfrc_mesh']] <- jsonlite::fromJSON(clipr::read_clip()) }"},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":null,"dir":"Reference","previous_headings":"","what":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"ngl_segments<- replaces neuroglancer segments neuroglancer scene parsed ngl_decode_scene.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"","code":"ngl_segments( x, as_character = TRUE, include_hidden = FALSE, must_work = TRUE, unique = FALSE, ... ) ngl_segments(x) <- value"},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"x Neuroglancer ids either vector ids (character vector integer64 recommended) scene specification raw JSON. format (character vector), path file disk, neuroglancer scene URL (embeds JSON scene specification single URL), R list generated parsing one . as_character Whether return segments character rather numeric vector (default character safety). include_hidden Whether include hiddenSegments (typically flywire scenes). must_work TRUE, default, error generated scene segments invalid ids present. Explicit NAs trigger error must_work=T, returned id 0 without error must_work=F. unique TRUE drops duplicated ids warning ... Additional arguments passed ngl_decode_scene value Segment ids form understandable ngl_segments. can include character/numeric/int64 ids, URL, parsed neuroglancer scene etc.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"Numeric (character) vector segment ids, taken first segmentation layer (warning) scene contains one.","code":""},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"simple vector inputs, ngl_segments treat values \"NA\", \"NAN\", \"NULL\" (case insensitive) \"\" NA. ngl_segments<- chooses FlyWire style segmentation_with_graph layer exists otherwise first visible segmentation layer. Note hiddenSegment removed process.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/ngl_segments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Helper function to turn diverse inputs into neuroglancer segment ids — ngl_segments","text":"","code":"# -> character ngl_segments(c(10950626347, 10952282491, 13307888342)) #> [1] \"10950626347\" \"10952282491\" \"13307888342\" # turns these into numeric ngl_segments(c(\"10950626347\", \"10952282491\", \"13307888342\"), as_character=FALSE) #> [1] 10950626347 10952282491 13307888342 # \\donttest{ u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5409525645443072\" ngl_segments(u, as_character = TRUE) #> [1] \"720575940621039145\" \"720575940626877799\" sc=ngl_decode_scene(u) # set segments ngl_segments(sc) <- c(\"720575940621039145\") # or a shortcut to add ids sc=sc+c(\"720575940621039145\", \"720575940626877799\") sc #> neuroglancer scene with 2 layers and 2 segments (of which 2 shown) #> name type visible nsegs #> 1 Production-image image TRUE 0 #> 2 Production-segmentation_with_graph segmentation_with_graph TRUE 2 #> nhidden #> 1 0 #> 2 0 #> source #> 1 precomputed://gs://microns-seunglab/drosophila_v0/alignment/image_rechunked #> 2 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 if (FALSE) { # paste resultant URL to clipboard to use in neuroglancer clipr::write_clip(as.character(sc)) } # you can also modify the URL directly ngl_segments(u)=c(\"720575940621039145\", \"720575940626877799\") # } if (FALSE) { browseURL(u) ## Summary of different classes of input # from clipboard ngl_segments(clipr::read_clip()) # URL ngl_segments(\"\") # path to file on disk ngl_segments(\"/path/to/scene.json\") # R list ngl_segments(scenelist) }"},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":null,"dir":"Reference","previous_headings":"","what":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"Construct Neuroglancer URL based 3D location data","code":""},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"","code":"open_fafb_ngl( x, s = rgl::select3d(), zoomFactor = 8, coords.only = FALSE, open = interactive() && !coords.only, sample = NULL, reference = NULL, sampleurl = NULL, ... )"},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"x numeric vector object compatible xyzmatrix CATMAID URL (see details) s Optional selection function type returned select3d zoomFactor Neuroglancer zoomFactor (bigger means zoomed ) coords.Return raw coordinate string pasting Neuroglancer position widget (top left screen) open Whether open URL browser - defaults TRUE interactive use. sample, reference Template space input object sample target (reference). See examples xform_brain details specified. sampleurl sample URL defines Neuroglancer dataset. ... Additional arguments passed fromJSON control JSON parsing.","code":""},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"character vector Neuroglancer URL coordinate string (invisibly open=TRUE)","code":""},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"Neuroglancer scenes seem specified single URL encodes json object defining layers display, position etc. function works taking sample URL defining scene editing point new 3D location / adjust zoom. package comes 4 different default scene urls specified via choose_segmentation with_segmentation. easiest way choose particular segmentation. can also specify different sample URL via sampleurl argument; remembered rest R session. regularly use particular kind scene URL, can set options(fafbseg.sampleurl) Rprofile file.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/open_fafb_ngl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Construct Neuroglancer URL based on 3D location data — open_fafb_ngl","text":"","code":"u=paste0(\"https://fafb.catmaid.virtualflybrain.org/?pid=2&zp=131280&\", \"yp=170014.98879622458&xp=426584.81386896875&tool=navigator&sid0=2&s0=-1\") # translate URL but don't open browser open_fafb_ngl(u, open=FALSE) #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprod.flywire-daf.com%2Fsegmentation%2Ftable%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22segments%22%3A%5B%220%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B106646.2035%2C42503.7472%2C3282%5D%7D%7D%2C%22zoomFactor%22%3A8%7D%2C%22perspectiveZoom%22%3A2230.6094%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" # produce an x,y,z string to paste into Neuroglancer open_fafb_ngl(u, coords.only=TRUE) #> [1] \"106646.203467242,42503.7471990561,3282\" # translate URL converting from FAFB14 to FlyWire coordinates # (only a small shift) open_fafb_ngl(u, sample=\"FAFB14\", reference=\"FlyWire\", open=FALSE) #> [1] \"https://ngl.flywire.ai/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fmicrons-seunglab%2Fdrosophila_v0%2Falignment%2Fimage_rechunked%22%2C%22type%22%3A%22image%22%2C%22blend%22%3A%22default%22%2C%22shaderControls%22%3A%7B%7D%2C%22name%22%3A%22Production-image%22%7D%2C%7B%22source%22%3A%22graphene%3A%2F%2Fhttps%3A%2F%2Fprod.flywire-daf.com%2Fsegmentation%2Ftable%2Ffly_v31%22%2C%22type%22%3A%22segmentation_with_graph%22%2C%22segments%22%3A%5B%220%22%5D%2C%22skeletonRendering%22%3A%7B%22mode2d%22%3A%22lines_and_points%22%2C%22mode3d%22%3A%22lines%22%7D%2C%22graphOperationMarker%22%3A%5B%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%5D%2C%22pathFinder%22%3A%7B%22color%22%3A%22%23ffff00%22%2C%22pathObject%22%3A%7B%22annotationPath%22%3A%7B%22annotations%22%3A%5B%5D%2C%22tags%22%3A%5B%5D%7D%2C%22hasPath%22%3Afalse%7D%7D%2C%22name%22%3A%22Production-segmentation_with_graph%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B4%2C4%2C40%5D%2C%22voxelCoordinates%22%3A%5B106560.9535%2C42529.9972%2C3282%5D%7D%7D%2C%22zoomFactor%22%3A8%7D%2C%22perspectiveZoom%22%3A2230.6094%2C%22jsonStateServer%22%3A%22https%3A%2F%2Fglobalv1.flywire-daf.com%2Fnglstate%2Fpost%22%2C%22selectedLayer%22%3A%7B%22layer%22%3A%22Production-segmentation_with_graph%22%2C%22visible%22%3Atrue%7D%2C%22layout%22%3A%22xy-3d%22%7D\" if (FALSE) { # copy CATMAID URL from clipboard and Neuroglancer coords to clipboard clipr::write_clip(open_fafb_ngl(clipr::read_clip(), coords.only=TRUE)) # Open a location in MB peduncle with current preferred segmentation open_fafb_ngl(c(433440, 168344, 131200)) # choose a particular segmentation (Google FAFB) with_segmentation(\"20190805\", open_fafb_ngl(c(433440, 168344, 131200), zoomFactor=2)) # or FlyWire with_segmentation(\"flywire\", open_fafb_ngl(c(433440, 168344, 131200))) # ... and translate FAFB14 to FlyWire coordinates with_segmentation(\"flywire\", open_fafb_ngl(c(433440, 168344, 131200), sample=\"FAFB14\", reference=\"FlyWire\", zoomFactor=2)) # open a CATMAID URL in Neuroglancer open_fafb_ngl(u) # Set an existing scene URL (pointing to any old location) to act as # the template for open_fafb_ngl # nb the package sets one for you on startup if you haven't set yourself options(fafbseg.sampleurl=\"https://\") # Edit your R profile if you want to set a different default usethis::edit_r_profile() }"},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":null,"dir":"Reference","previous_headings":"","what":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"Read skeleton(s) brainmaps API nat::neuron object","code":""},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"","code":"read.neuron.brainmaps(x, ...) read.neurons.brainmaps(x, OmitFailures = NA, df = NULL, ...)"},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"x vector segment ids Neuroglancer scene specification includes segments ids (see examples ngl_segments details). ... Additional arguments passed brainmaps_skeleton brainmaps_fetch. may include skeletonuri argument, brainmaps URI specifying remote source skeletons. See brainmaps_skeleton details. OmitFailures Whether omit neurons FUN gives error. default value (NA) result nlapply stopping error message moment error. values, see details. df Optional data frame containing information neuron","code":""},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"nat::neuron object","code":""},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"OmitFailures NA, FUN wrapped call try ensure failure single neuron abort nlapply call. OmitFailures=TRUE resultant neuronlist subsetted return values FUN evaluated successfully. OmitFailures=FALSE, \"try-error\" objects left place. either last 2 cases error messages printed call wrapped try(expr, silent=TRUE). optional dataframe (df) detailing neuron rownames match names neuron. also make sense key present column data frame. dataframe contains rows neurons, superfluous rows dropped warning. dataframe missing rows neurons error generated. SortOnUpdate=TRUE updating existing neuronlist result new neuronlist ordering identical reading neurons scratch.","code":""},{"path":"https://natverse.org/fafbseg/reference/read.neuron.brainmaps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read skeleton(s) from brainmaps API into a nat::neuron object — read.neuron.brainmaps","text":"","code":"if (FALSE) { n=read.neuron.brainmaps(22427007374) nm=read.neurons.brainmaps(find_merged_segments(7186840767)) # you would specify a particular skeleton source like so read.neurons.brainmaps(find_merged_segments(7186840767), skeletonuri=\"brainmaps:///\") }"},{"path":"https://natverse.org/fafbseg/reference/read_brainmaps_meshes.html","id":null,"dir":"Reference","previous_headings":"","what":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","title":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","text":"Read 3D meshes via brainmaps API","code":""},{"path":"https://natverse.org/fafbseg/reference/read_brainmaps_meshes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","text":"","code":"read_brainmaps_meshes( x, volume = getOption(\"fafbseg.brainmaps.volume\"), meshName = getOption(\"fafbseg.brainmaps.meshName\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/read_brainmaps_meshes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","text":"x Vector integer segment ids volume String identifier volume containing segments meshName String identifier meshes ... Additional arguments passed brainmaps_fetch","code":""},{"path":"https://natverse.org/fafbseg/reference/read_brainmaps_meshes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","text":"mesh3d object","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_brainmaps_meshes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read 3D meshes via the brainmaps API — read_brainmaps_meshes","text":"","code":"if (FALSE) { segs=find_merged_segments(7186840767) samplemesh=read_brainmaps_meshes(segs) sampleskel=read_segments2(segs) dot3d(samplemesh, col='grey') plot3d(sampleskel, lwd=2) # or compare mesh and skeleton colouring points by distance from skeleton compare_ng_neuron(samplemesh, sampleskel, pointsize=1, sample_dots = 0.3) }"},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":null,"dir":"Reference","previous_headings":"","what":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"save_cloudvolume_meshes saves meshes disk. read_cloudvolume_meshes uses save_cloudvolume_meshes internally save meshes disk reads memory neuronlist.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"","code":"save_cloudvolume_meshes( segments, savedir = tempfile(), OmitFailures = TRUE, Force = FALSE, format = c(\"obj\", \"ply\"), ..., cloudvolume.url = getOption(\"fafbseg.cloudvolume.url\") ) read_cloudvolume_meshes( segments, savedir = NULL, ..., cloudvolume.url = getOption(\"fafbseg.cloudvolume.url\") )"},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"segments segment ids fetch (probably character vector) savedir Optional path directory obj format files stored. specified, temporary directory created removed end call. OmitFailures Whether omit neurons FUN gives error. default value (NA) result nlapply stopping error message moment error. values, see details. Force whether overwrite downloaded mesh name format whether save meshes Wavefront obj Stanford poly format. obj default ply simpler compact format. ... Additional arguments passed save_cloudvolume_meshes eventually Python CloudVolume constructor (see https://github.com/seung-lab/cloud-volume details. cloudvolume.url Optional url fetch meshes normally specified fafbseg.cloudvolume.url option.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"rgl::shapelist3d list containing one mesh3d objects named segment id.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"may use fetch meshes https://flywire.ai among sources. may need select preferred remote data source using choose_segmentation (see examples). hood, uses CloudVolume serverless Python client reading data Neuroglancer compatible formats. therefore need working python3 install CloudVolume. Please install Python CloudVolume module described : https://github.com/seung-lab/cloud-volume#setup. must ensure using python3 (implicitly explicitly) mesh fetching graphene servers depends . normally work: pip3 install cloud-volume. already installed CloudVolume found, recommend editing Renviron file set environment variable pointing correct Python. can usethis::edit_r_environ() setting e.g. RETICULATE_PYTHON=\"/usr/local/bin/python3\". normally need set kind authentication order fetch data. flywire, recommend function flywire_set_token. data sources details, see https://github.com/seung-lab/cloud-volume#chunkedgraph-secretjson get token save . can either save json snippet ~/.cloudvolume/secrets/cave-secret.json set environment variable (CHUNKEDGRAPH_SECRET=\"XXXX\". Finally also need set option pointing server. conveniently achieved using e.g. choose_segmentation('flywire31'), now default, sources without built-support, can also specify full source URL, might look something like options(fafbseg.cloudvolume.url='graphene://https://xxx.dynamicannotationframework.com/segmentation/xxx/xxx') can easily add startup Rprofile usethis::edit_r_profile().","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_cloudvolume_meshes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read meshes from chunked graph (graphene) server via CloudVolume — save_cloudvolume_meshes","text":"","code":"if (FALSE) { kcmesh=save_cloudvolume_meshes(\"720575940623755722\", savedir=\".\") kc=read.neurons(kcmesh) } if (FALSE) { # The very first time you access FlyWire data you need to get/store a token flywire_set_token() # Each R session, you should choose the default segmentation you want choose_segmentation('flywire31') pmn1.flywire=read_cloudvolume_meshes(\"720575940623979522\") pmn1.fafb=read.neuron.catmaid(5321581) # Read and plot sample KCs from a FlyWire (short) URL u=\"https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/6230669436911616\" kcs=read_cloudvolume_meshes(u) kcs plot3d(kcs) nclear3d() plot3d(pmn1.fafb, col='red', lwd=2, WithNodes = F) wire3d(pmn1.flywire) # you can select specific locations like so library(elmr) # CATMAID URL open_fafb(pmn1.flywire[[1]], open=F) # CATMAID coords to paste into PIN location box cat(xyzmatrix(catmaid::catmaid_parse_url(open_fafb(pmn1.flywire[[1]], open=F))), sep=',') # Neuroglancer coords (raw pixels not nm) open_fafb_ngl(pmn1.flywire[[1]], open=F, coords.only = T) }"},{"path":"https://natverse.org/fafbseg/reference/read_l2skel.html","id":null,"dir":"Reference","previous_headings":"","what":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","title":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","text":"read_l2skel reads one neurons simplified L2 skeletons. read_l2dp reads one neurons simplified dotprops format. See details.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_l2skel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","text":"","code":"read_l2skel(id, OmitFailures = TRUE, datastack_name = NULL, ...) read_l2dp(id, OmitFailures = TRUE, datastack_name = NULL, ...)"},{"path":"https://natverse.org/fafbseg/reference/read_l2skel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","text":"id One flywire ids OmitFailures Whether drop neurons read results (rather erroring ). Default TRUE. datastack_name CAVE datastack_name. missing use default implied segmentation chosen choose_segmentation. ... Additional arguments passed fafbseg.flywire.l2_skeleton fafbseg.flywire.l2_dotpropsfunctions.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_l2skel.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","text":"read_l2dp generally recommended rather fetching skeleton calculating dotprops much faster also computes better direction vectors. However wish simplify skeleton (e.g. find cell body fibre) need take two step approach. also possible advantage can specify step size direction vectors generated along neuron. Note also read_l2dp may drop regions neuron (likely thin ones) define small mesh volume. functions depends Philipp Schlegel's fafbseg-py package. can install using simple_python. datastack_name argument optional correct datastack name corresponding cloud volume URL read options set choose_segmentation; generally preferred way end users select active dataset. Neverthless, datastack_name used look correct segmentation URL fafbseg-py correctly set using two pieces information.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_l2skel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read L2 skeleton or dotprops for FlyWire data sources using fafbseg-py — read_l2skel","text":"","code":"if (FALSE) { # install full set of recommended packages including fafbseg-py simple_python(\"full\") kcsvids=c(\"78603674556915608\", \"78462662124123765\", \"77547662357982001\", \"78533168373869635\", \"78251418452635714\", \"78323024281482155\", \"78322062208411707\", \"78533649477402370\", \"77829412279715493\", \"77899643517979532\", \"78814230967028270\", \"78533993141739277\", \"78041274292494941\", \"78252449311896359\", \"77618924522629940\", \"77618237260576979\", \"78673768356594679\", \"78182148951479619\", \"78392293379997680\", \"77688812230426430\") kcids=flywire_rootid(kcsvids) kcs=read_l2skel(kcids) library(nat.nblast) kcdps=read_l2dp(kcids) # nb these are in microns boundingbox(kcdps) kcaba=nblast_allbyall(kcdps) kchc=nhclust(scoremat = kcaba) plot(kchc) # 3d plot using the skeletons rather than dotprops versions of the neurons # gamma neurons seprate from the rest plot3d(kchc, k=2, db=kcs) }"},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":null,"dir":"Reference","previous_headings":"","what":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"Read CSV files containing raw agglomeration (merge) information","code":""},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"","code":"read_mergeinfo(x, pattern = \"10\\\\.csv$\", voxdims = c(16, 16, 40), ...)"},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"x Input directory pattern Optional pattern identify CSV files voxdims Optional voxel dimensions convert raw pixel coordinates physical (nm) coordinates ... Additional arguments passed readr::read_csv","code":""},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"data.frame columns id1,id2 Segment ids merged x,y,z Location (nm) merge point","code":""},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"Peter Li provided 10 CSV files merge information Aug 2018 function tested. merge information processed identify groups segments merged together fafbsegdata package, can accessed using find_merged_segments function.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_mergeinfo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read CSV files containing raw agglomeration (merge) information — read_mergeinfo","text":"","code":"if (FALSE) { csvdir=\"~/projects/fafbseg/fafb14_v00c_split3xfill2x_merges/ffnreseg16nm_ms1000_md0.02_c0.6_iou0.7/\" mergeinfo <- read_mergeinfo(csvdir) # Show 3D position of merge locations for a large merge group containing a # tangential cell (widefield visual interneuron) tang_segs <- find_merged_segments(22139217567) tang_mi <- subset(mergeinfo, id1%in% tang_segs | id2 %in%tang_segs) points3d(xyzmatrix(tang_mi)) # plot brain surface for context library(elmr) plot3d(FAFB) }"},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":null,"dir":"Reference","previous_headings":"","what":"Read neuroglancer data dump from disk / web — read_ng_dump","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"Read neuroglancer data dump disk / web","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"","code":"read_ng_dump(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"x Path directory, zip file, set data files ... Additional argument passed read_ng_raw","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"list class ng_raw_list additional metadata attributes.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"neuroglancer data dump consists mix JSON custom binary data files, together define mesh data (fragments) neurons together associated metadata. See fetch_all_curl prepare data dump.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_ng_dump.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read neuroglancer data dump from disk / web — read_ng_dump","text":"","code":"if (FALSE) { fetch_all_curl(\"all_curl.sh\", outdir=\"alldata\", regex=\"brainmaps.googleapis.com\", fixed=TRUE) meshdata=read_ng_dump(\"alldata\") m=as.mesh3d(meshdata) shade3d(m, col='red') # can also be a (remote) zip file meshdata=read_ng_dump(\"https://myfiles.com/myneuron.zip\") }"},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":null,"dir":"Reference","previous_headings":"","what":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"Read raw neuroglancer data - currently supports mesh format","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"","code":"read_ng_raw(x, read_data = TRUE, Verbose = FALSE)"},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"x Path one files directory (case files read). read_data Whether read data (default TRUE) just header Verbose Whether print status messages (default FALSE)","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"object class 'ng_raw_list' containing one chunks data class 'ng_raw'. x contains multiple files, chunks merged single list.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"See https://github.com/google/neuroglancer","code":""},{"path":"https://natverse.org/fafbseg/reference/read_ng_raw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read raw neuroglancer data - currently only supports mesh format — read_ng_raw","text":"","code":"if (FALSE) { res <- read_ng_raw(\"meshdata/chunk00789.raw\") resh <- read_ng_raw(\"meshdata/chunk00789.raw\", read_data=FALSE) resl <- read_ng_raw(dir(\"meshdata\", full.names = TRUE)) }"},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":null,"dir":"Reference","previous_headings":"","what":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"read_segments2 reworked version read_segments reads skeletons straight zip files memory.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"","code":"read_segments(x, voxdims = c(32, 32, 40), ...) read_segments2( x, voxdims = c(32, 32, 40), minfilesize = 80, datafrac = NULL, coordsonly = FALSE, ... )"},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"x vector segment ids Neuroglancer scene specification includes segments ids (see examples ngl_segments details). voxdims voxel dimensions nm skeletonised data ... additional arguments passed read.neurons minfilesize uncompressed size swc file must >= . cheap way insist >1 point. datafrac Fraction data read based uncompressed file size (see details) coordsonly read XYZ coordinates neurons.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"neuronlist containing one neuron fragment","code":""},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"recommend read_segments2 point. read_segments potential benefit caching SWC files disk rather extracting every time. However large slowdown many filesystems number extracted files enters thousands - something hit times. Furthermore read_segments2 makes easier select fragment files extracting . datafrac number range 0-1 specifies fraction data read. Skeleton fragments placed descending size order read number bytes exceeds datafrac * sum(file sizes). noticed time taken read neuron zip file seems depend largely number fragments read , rather amount data fragment! Reading 90 can take < 10","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_segments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read skeletons for segments by extracting from the corresponding zip file(s) — read_segments","text":"","code":"if (FALSE) { # read neuron using raw segment identifier n <- read_segments2(22427007374) # read a neuron from a scene specification copied from Neuroglancer window # after clicking on the {} icon at top right n <- read_segments2(clipr::read_clip()) summary(n) n2 <- read_segments2(22427007374, datafrac=0.9) summary(n2) }"},{"path":"https://natverse.org/fafbseg/reference/read_topn.html","id":null,"dir":"Reference","previous_headings":"","what":"Find and read the largest n segments from one or more skeleton zip files — read_topn","title":"Find and read the largest n segments from one or more skeleton zip files — read_topn","text":"read_topn calls find_topn find top fragments reads using read_segments2. find_topn finds files, returning tibble (data.frame) results.","code":""},{"path":"https://natverse.org/fafbseg/reference/read_topn.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find and read the largest n segments from one or more skeleton zip files — read_topn","text":"","code":"read_topn(zipfiles, n = 1, ...) find_topn(zipfiles, n = 1, decreasing = TRUE)"},{"path":"https://natverse.org/fafbseg/reference/read_topn.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find and read the largest n segments from one or more skeleton zip files — read_topn","text":"zipfiles path, name, number zipfiles. full path searched location defined options('fafbseg.skelziproot') n Number segments read ... additional arguments passed read_segments2 decreasing Whether sort skeletons decreasing order .e. largest first (default=TRUE)","code":""},{"path":"https://natverse.org/fafbseg/reference/read_topn.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Find and read the largest n segments from one or more skeleton zip files — read_topn","text":"Note read fragment skeletons segment","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/read_topn.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Find and read the largest n segments from one or more skeleton zip files — read_topn","text":"","code":"if (FALSE) { top3=read_topn(\"224270.zip\", n=3) }"},{"path":"https://natverse.org/fafbseg/reference/simple_python.html","id":null,"dir":"Reference","previous_headings":"","what":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","title":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","text":"Installs Python via isolated miniconda environment well recommended packages fafbseg. absolutely want use miniconda (much simpler get started) please read Details section.","code":""},{"path":"https://natverse.org/fafbseg/reference/simple_python.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","text":"","code":"simple_python( pyinstall = c(\"basic\", \"full\", \"extra\", \"cleanenv\", \"blast\", \"none\"), pkgs = NULL, miniconda = TRUE )"},{"path":"https://natverse.org/fafbseg/reference/simple_python.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","text":"pyinstall Whether \"basic\" install (enough functionality) \"full\" install, includes tools accessing fast/simple skeletons \"dotprops\" NBLAST via fafbseg-py package; \"extra\" installs neuron packages enable high resolution skeletonisation really necessary users frankly pain install. \"cleanenv\" show clean Python environment removing packages. \"blast\" show completely remove dedicated miniconda installation. Choosing =\"none\" skips update/install Python recommended packages installing extras defined pkgs. pkgs Additional python packages install. miniconda Whether use reticulate package's default approach dedicated python R based miniconda (recommended, default) allow specification different system installed Python via RETICULATE_PYTHON environment variable.","code":""},{"path":"https://natverse.org/fafbseg/reference/simple_python.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","text":"recommended Python install procedure installs miniconda Python distribution. added system PATH default can used exclusively R. want use miniconda, least ) make Python virtual environment using virtualenv (conda managing conda install) b) specify Python want use RETICULATE_PYTHON environment variable. can set RETICULATE_PYTHON usethis::edit_r_environ(). decided stick miniconda recommended, customisation still possible. halfway house, can set options('fafbseg.condaenv') specify non-standard miniconda virtual environment alternative default \"r-reticulate\". Furthermore can set environment variable RETICULATE_MINICONDA_PYTHON_VERSION=3.10 use newer version Python reticulate package recommends. sounds complicated, strongly suggest sticking default miniconda=TRUE approach. Note installing miniconda Python first time updating miniconda install, likely asked restart R. restart Python interpreter linked R session. Therefore Python already running session, must restart R use new Python install.","code":""},{"path":"https://natverse.org/fafbseg/reference/simple_python.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Simple Python installation for use with R/fafbseg/FlyWire — simple_python","text":"","code":"if (FALSE) { # just the basics simple_python(\"basic\") # if you want to skeletonise meshes simple_python(\"full\") # To install a special package using the recommended approach simple_python(pkgs=\"PyChunkedGraph\") # the same but without touching Python itself or the recommended packages simple_python('none', pkgs='PyChunkedGraph') # install a specific version of cloud-volume package simple_python('none', pkgs='cloud-volume~=3.8.0') # if you really need to insist (e.g. because a newer version is already installed) reticulate::py_install('cloud-volume==8.15.0', pip = TRUE) # install the latest version of a package from github simple_python('none', pkgs=\"git+git://github.com/schlegelp/skeletor@master\") # install a specific earlier version of a package simple_python('none', pkgs=\"git+git://github.com/seung-lab/DracoPy@v0.0.15\") # install all recommended packages but use your existing Python # only do this if you know what you are doing ... simple_python(\"full\", miniconda=FALSE) }"},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":null,"dir":"Reference","previous_headings":"","what":"Skeletonise neuron meshes using skeletor — skeletor","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"can skeletonise complex neuron meshes using skeletor skeletor-1.0.0. Skeletor python library function wraps series skeletor functions order smoothly process neurons use natverse. Note, default settings optimise performance fast skeletonisation flywire meshes. casual users recommend using 'wave' method, fast simple terms parameters, .e. just uses waves step_size. value 1 often works well.","code":""},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"","code":"skeletor( segments = NULL, obj = NULL, mesh3d = FALSE, save.obj = NULL, cloudvolume.url = getOption(\"fafbseg.cloudvolume.url\"), operator = c(\"umbrella\", \"contangent\"), clean = FALSE, remove_disconnected = 10, theta = 0.01, radius = TRUE, ratio = 0.1, SL = 10, WH0 = 2, iter_lim = 4, epsilon = 0.05, precision = 1e-06, validate = TRUE, method.radii = c(\"knn\", \"ray\"), method = c(\"wavefront\", \"vertex_clusters\", \"edge_collapse\", \"teasar\", \"tangent_ball\"), heal = TRUE, heal.k = 10L, heal.threshold = Inf, reroot = TRUE, k.soma.search = 10, radius.soma.search = 2500, brain = NULL, n = 5, n_rays = 20, projection = c(\"sphere\", \"tangents\"), fallback = \"knn\", waves = 2, step_size = 1, sampling_dist = 500, cluster_pos = c(\"median\", \"center\"), shape_weight = 1, sample_weight = 0.1, inv_dist = 100, cpu = Inf, elapsed = Inf, ... ) reroot_hairball(x, k.soma.search = 10, radius.soma.search = 2500, brain = NULL) download_neuron_obj( segments, save.obj = getwd(), ratio = 1, cloudvolume.url = getOption(\"fafbseg.cloudvolume.url\"), ... )"},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"segments segment ids fetch (probably character vector), e.g. flywire IDs hemibrain bodyids. Meshes read specified CloudVolume (cloudvolume.url). obj character. Path obj file folder files. files read meshes skeletonised. segments given, argument overridden. mesh3d logical. TRUE neuron's volume added neuron object resultant neuronlist] neuron$mesh3d. save.obj character. Path save .obj file neuron volumes. NULL, .obj files saved (default). cloudvolume.url Optional url fetch meshes normally specified fafbseg.cloudvolume.url option. operator Laplacian operator use mesh contraction. \"contangent\" takes topology geometry mesh account better descriptor curvature flow. \"umbrella\", 'uniform weighting' operator uses topological features, making robust mesh flaws. clean logical. TRUE , python, skeletor.post.clean_up used collapse twigs line sight move nodes outside mesh back inside. Note magic bullet work (well) original mesh degenerate (e.g. internal faces watertight) begin . need ncollpyde python3 module installed. can get pip3 install ncollpyde. get issues related module, best set FALSE. skeletor.pre.fix_mesh also used remove seemingly erroneous vertices remove common mesh problems. remove_disconnected, integer 'False'. number given clean==TRUE,\\ iterate mesh's connected components remove consisting less given number vertices. example, ``remove_fragments=5`` drop parts mesh consist five less connected vertices. theta numeric. Used clean=TRUE. twig generate dot product tangent vectors parents. line perfectly dot product equal 1. theta determines much value can differ 1 us still prune twig: higher theta = pruning. radius logical. Whether return radius information skeleton node. want make use radii, need ncollpyde python3 module installed. can get pip3 install ncollpyde. get issues related module, best set FALSE. ratio numeric, 0-1. Factor reduce mesh faces. example, ratio 0.5 reduce number faces 50 percent. SL numeric. Factor contraction matrix multiplied iteration. theory, lower values likely get optimal contraction cost needing iterations. WH0 numeric. Initial weight factor attraction constraints. ratio initial weights WL0 (1e-3 * sqrt()) WH0 controls smoothness degree contraction first iteration result, thus determines amount details retained subsequent final contracted meshes. iter_lim integer. Maximum rounds contractions. epsilon numeric. Target contraction rate measured sum face areas contracted versus original mesh. Algorithm stop mesh contracted threshold. Depending mesh (number faces, shape) reaching strong contraction can extremely costly comparatively little benefit subsequent skeletonisation. Note algorithm might stop short target iter_lim reached first sum face areas increasing one iteration next instead decreasing. precision numeric. Sets precision finding least-square solution. main determinant speed vs quality: lower values take (much) longer get closer optimally contracted mesh. Higher values faster iterative contractions might stop early. validate True, try fix potential issues mesh (e.g. infinite values, duplicate vertices, degenerate faces) collapsing. Degenerate meshes can lead effectively infinite runtime function! method.radii method determine node's radius. \"knn\" uses k-nearest-neighbours get radii: fast potential wrong. \"ray\" uses ray-casting get radii: slower sometimes less wrong. method Skeletonisation comes two flavours different Pros Cons. \"vertex_clusters\" groups collapses vertices based geodesic distance along mesh's surface. fast scales well can lead oversimplification. Good quick & dirty skeletonisations. \"edge_collapse\" implements skeleton extraction edge collapse described Au et al. 2008. rather slow scale well really good preserving topology. heal logical. Whether , neuron id fragmented, stitch multiple fragments single neuron using minimum spanning tree. heal.k integer. number nearest neighbours consider trying merge different clusters. heal.threshold numeric. threshold distance new vertices connected (default=Inf disables feature). parameter prevents merging vertices far away main neuron likely spurious. reroot logical. Whether re-root neuron estimated 'soma'. soma usually large ball neuron, skeletonise something hair ball. can try detect quickly reroot skeleton . finding nearest leaf nodes leaf node, seeing going divergent directions. k.soma.search integer. number leaf nodes find, around leaf node radius radius.soma.search, rerooting process. larger number, better slower. radius.soma.search numeric. distance within search fellow leaf nodes rerooting process. inaccurate values high low. size expected soma. brain mesh3d hxsurf object within soma occur. re-rooting process. (Insect somata tend lie outside brain proper) n method.radii = \"knn\". Radius mean n nearest-neighbours. n_rays integer. method.radii = \"knn\".method.radii = \"ray\". Number rays cast node. projection method.radii = \"ray\". Whether cast rays sphere around node circle orthogonally node's tangent vector. fallback method.radii = \"ray\". point outside right surface mesh ray casting return nonsense results. can either ignore cases (\"None\"), assign arbitrary number can fall back radii k-nearest-neighbours (\"knn\"). waves integer. method = \"wavefront\". Number waves run across mesh. wave initialised different vertex produces slightly different rings. final skeleton produced mean across waves. waves produce higher resolution skeletons also introduce noise. step_size integer, Values greater 1 effectively lead binning rings. example stepsize 2 means two adjacent vertex rings collapsed center. can help reduce noise skeleton (counteracts large number waves) sampling_dist numeric. method = \"vertex_clusters\". Maximal distance vertices clustered. parameter tuned based resolution mesh. cluster_pos numeric. method = \"vertex_clusters\". determine x/y/z coordinates collapsed vertex clusters (.e. skeleton's nodes). \"median\": Use vertex closest cluster's centrer mass. \"center\": Use center mass. makes smoother skeletons can lead nodes outside mesh. shape_weight numeric. method = \"edge_collapse\". Weight shape costs penalize collapsing edges drastically change shape object. sample_weight numeric.method = \"edge_collapse\". Weight sampling costs penalise collapses generate prohibitively long edges. inv_dist numeric.method = \"teasar\". Distance along mesh used invalidation vertices. controls detailed (noisy) skeleton . cpu double (length one). Set limit total cpu time seconds. elapsed double (length one). Set limit total elapsed cpu time seconds ... Additional arguments passed reticulate::py_run_string. x nat::neuron object.","code":""},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"nat::neuronlist containing neuron skeleton objects.","code":""},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"pipeline: 1. Reads specified meshes CloudVolume source. 2. Simplifies mesh (python: skeletor.pre.simplify) 3. Contract mesh (python: skeletor.pre.contract) 4. Skeletonises mesh (python: skeletor.skeletonize) 5. Optionally, cleans mesh (python: skeletor.post.clean_up) 6. Optionally, add radius information skeleton (python: skeletor.post.radii) 7. Optionally, heal skeleton breaks (nat::stitch_neurons_mst) 8. Optionally, attempts re-root neuron 'hairball', .e. approximate soma (reroot_hairball). therefore need working python3 install skeletor, uses CloudVolume. require meshparty. Please install Python skeletor module described : https://github.com/schlegelp/skeletor. must ensure using python3 (implicitly explicitly) mesh fetching graphene servers depends . normally work: pip3 install git+git://github.com/schlegelp/skeletor@master. already installed skeletor found, recommend editing Renviron file set environment variable pointing correct Python. can usethis::edit_r_environ() setting e.g. RETICULATE_PYTHON=\"/usr/local/bin/python3\". (Though best practice create conda environment natverse R sessions direct R using environ file.) need set kind authentication order fetch volume data skeletonisation. See https://github.com/seung-lab/cloud-volume#chunkedgraph-secretjson get token save . can either save json snippet ~/.cloudvolume/secrets/cave-secret.json set environment variable (CHUNKEDGRAPH_SECRET=\"XXXX\". Finally also need set option pointing server. server hosting mesh data interested . might look something like: options(fafbseg.cloudvolume.url='graphene://https://xxx.dynamicannotationframework.com/segmentation/xxx/xxx') can easily add startup Rprofile usethis::edit_r_profile(). example, flywire data set, currently: 'graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31'. Roughly decreasing order impact speed: Ratio: lower ratio = less vertices = faster epsilon: lower target contraction rate = less steps = faster SL: faster contraction = pot. less steps target contraction rate = faster precision: lower precision = faster least-square computation = faster sampling_dist: larger dist = faster collapse mesh skeleton = faster","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/skeletor.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Skeletonise neuron meshes using skeletor — skeletor","text":"","code":"if (FALSE) { choose_segmentation(\"flywire\") nx=xform_brain(elmr::dense_core_neurons, ref=\"FlyWire\", sample=\"FAFB14\") xyz = xyzmatrix(nx) ids = unique(flywire_xyz2id(xyz[sample(1:nrow(xyz),100),])) neurons = skeletor(ids, brain = elmr::FAFB14.surf) plot3d(neurons) # note, in flywire space plot3d(nx, col=\"black\", lwd =2) # note, in flywire space # Also plot their meshes neuron.meshes = read_cloudvolume_meshes(ids) # We can also just save the .obj files dir.create(\"obj\") download_neuron_obj(ids, save.obj = \"obj\") # remove unlink(\"obj\", recurvise = TRUE) }"},{"path":"https://natverse.org/fafbseg/reference/skelsforsegment.html","id":null,"dir":"Reference","previous_headings":"","what":"Find all skeleton fragments for one segment — skelsforsegment","title":"Find all skeleton fragments for one segment — skelsforsegment","text":"Find skeleton fragments one segment","code":""},{"path":"https://natverse.org/fafbseg/reference/skelsforsegment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find all skeleton fragments for one segment — skelsforsegment","text":"","code":"skelsforsegment(x, returndetails = FALSE)"},{"path":"https://natverse.org/fafbseg/reference/skelsforsegment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find all skeleton fragments for one segment — skelsforsegment","text":"x segment id returndetails Whether return zip list details","code":""},{"path":"https://natverse.org/fafbseg/reference/skelsforsegment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find all skeleton fragments for one segment — skelsforsegment","text":"character vector fragment names attribute containing path zip file","code":""},{"path":"https://natverse.org/fafbseg/reference/tabify_coords.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","title":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","text":"tabify_coords can used convert comma separated value clipboard e.g. neuroglancer tab separated values needed Seatable coordinates stored 3 separate columns. also words multiple coordinates.","code":""},{"path":"https://natverse.org/fafbseg/reference/tabify_coords.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","text":"","code":"tabify_coords(xyz = NULL, FUN = NULL, write_clip = NULL)"},{"path":"https://natverse.org/fafbseg/reference/tabify_coords.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","text":"xyz 3D Coordinates form compatible xyzmatrix. missing read clipboard. FUN transformer function apply incoming coordinates. convenience FUN missing xyz function function applied coordinates clipboard. write_clip Whether write result clipboard. missing (default) write clipboard coordinates read clipboard xyz=NULL.","code":""},{"path":"https://natverse.org/fafbseg/reference/tabify_coords.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","text":"Character vector tab separated coordinates. xyz missing returned invisibly also written clipboard.","code":""},{"path":"https://natverse.org/fafbseg/reference/tabify_coords.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert coordinates to tab separated values. Useful for copy/paste to\nSeatable — tabify_coords","text":"","code":"# \\donttest{ tabify_coords(1:3) #> [1] \"1\\t2\\t3\" # } if (FALSE) { # copy position from clipboard and write back as TSV tabify_coords() # same but convert from raw coordinates to nm tabify_coords(flywire_raw2nm) }"},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":null,"dir":"Reference","previous_headings":"","what":"Read and write neuroglancer annotation info json files — write_nginfo","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"Read write neuroglancer annotation info json files","code":""},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"","code":"write_nginfo(anndf, f, sep = \"_\")"},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"anndf data.frame first column contains ids neuron additional columns contain annotations joined single string. f Path json file. write_nginfo create enclosing directory necessary. sep separator used paste multiple columns annotations together.","code":""},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"read_nginfo list containing annotations. write_nginfo, path f invisibly.","code":""},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"Note nothing specific flywire two functions - used data source.","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/reference/write_nginfo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read and write neuroglancer annotation info json files — write_nginfo","text":"","code":"# \\donttest{ tf=tempfile(pattern = \"info\") df=data.frame(id=c(10000,10002), type=c(\"DNp01\")) write_nginfo(df, tf) # }"},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":null,"dir":"Reference","previous_headings":"","what":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"Add transformation one layers neuroglancer scene","code":""},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"","code":"# S3 method for ngscene xform(x, reg, layers = NULL, ...)"},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"x neuroglancer scene produced ngl_decode_scene reg registration either reglist containing multiple registrations single registration form handled xform. layers character vector specifying layers scene transform. elements named, names specify new names transformed layer. ... Additional arguments passed fit_xform reg specifies non-rigid registration. See details.","code":""},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"new ngscene object","code":""},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"Neuroglancer implements homogeneous affine transforms layers. However can still quite useful non-rigid transform applied layer e.g. underlying neurons undergoing rapid editing practical generate static set transformed meshes.","code":""},{"path":"https://natverse.org/fafbseg/reference/xform.ngscene.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add a transformation to one or more layers in a neuroglancer scene — xform.ngscene","text":"","code":"# \\donttest{ # flywire scene u='https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/4559706743898112' scf=ngl_decode_scene(u) m=matrix(c(-0.9663, -0.0695, 0.17, 0, 0.0351, 1.043, -0.028, 0, 0.1082, -0.0093, 0.9924, 0, 1021757.1284, 31409.0911, -85626.0572, 1), ncol=4) # nb replaces existing layer of this name xform(scf, m, layers=c('Production-mirrored')) #> neuroglancer scene with 4 layers and 1 segments (of which 1 shown) #> name type visible nsegs nhidden #> 1 Maryland-image image TRUE 0 0 #> 2 Production segmentation_with_graph TRUE 1 0 #> 3 Production-mirrored segmentation_with_graph TRUE 1 0 #> 4 brain_mesh_v141.surf segmentation TRUE 1 0 #> source #> 1 precomputed://https://bossdb-open-data.s3.amazonaws.com/flywire/fafbv14 #> 2 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 #> 3 graphene://https://prodv1.flywire-daf.com/segmentation/1.0/fly_v31 #> 4 precomputed://gs://flywire_neuropil_meshes/whole_neuropil/brain_mesh_v141.surf scu=ngl_decode_scene('https://tinyurl.com/kj9rwn26') # make a new layer mirroring an existing layer scu2=xform(scu, m, layers=c('fly_v31_m'='fly_v31')) scu2 #> neuroglancer scene with 4 layers and 2 segments (of which 2 shown) #> name type visible nsegs nhidden #> 1 v1 image TRUE 0 0 #> 2 fly_v31 segmentation TRUE 2 0 #> 3 jfrc_mesh_test1 segmentation FALSE 1 0 #> 4 fly_v31_m segmentation TRUE 2 0 #> source #> 1 precomputed://gs://flywire_em/aligned/v1 #> 2 graphene://middleauth+https://prod.flywire-daf.com/segmentation/1.0/fly_v31 #> 3 precomputed://https://spine.itanna.io/files/eric/jfrc_mesh_test #> 4 graphene://middleauth+https://prod.flywire-daf.com/segmentation/1.0/fly_v31 # } if (FALSE) { browseURL(as.character(scu2)) } if (FALSE) { # mirror a flywire scene based on points from a specific pair of neurons mbon18.dps=read_l2dp('MBON18') mirror_reg=fit_xform(samplepts = mbon18.dps, refpts = nat.jrcbrains::mirror_fafb(mbon18.dps), subsample = 500) flywire_scene('MBON18') %>% ngl_decode_scene %>% xform(mirror_reg, layers=c(\"mirror\"=\"Production-segmentation_with_graph\")) %>% as.character() %>% browseURL() }"},{"path":"https://natverse.org/fafbseg/reference/xyzmatrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract the XYZ coordinates from neuroglancer mesh objects — xyzmatrix.ng_raw","title":"Extract the XYZ coordinates from neuroglancer mesh objects — xyzmatrix.ng_raw","text":"Extract XYZ coordinates neuroglancer mesh objects","code":""},{"path":"https://natverse.org/fafbseg/reference/xyzmatrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract the XYZ coordinates from neuroglancer mesh objects — xyzmatrix.ng_raw","text":"","code":"# S3 method for ng_raw xyzmatrix(x, ...) # S3 method for ng_raw_list xyzmatrix(x, ...)"},{"path":"https://natverse.org/fafbseg/reference/xyzmatrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract the XYZ coordinates from neuroglancer mesh objects — xyzmatrix.ng_raw","text":"x ng_raw ng_raw_list object ... additional arguments (currently ignored)","code":""},{"path":[]},{"path":[]},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-0130","dir":"Changelog","previous_headings":"","what":"fafbseg 0.13.0","title":"fafbseg 0.13.0","text":"Feature optic info table @jefferis https://github.com/natverse/fafbseg/pull/174 Fix fafbseg inner_join / tests @jefferis https://github.com/natverse/fafbseg/pull/176 Support released cell type / connectivity data @jefferis https://github.com/natverse/fafbseg/pull/177 Add support ito_lee_hemilineage searches (d17a6edfcef0aa2b709797d33117b21c4c59b203) Give add_celltype_info suffix argument (136ecab3ecc149f683a3f81cf1c6cc02ce4c99c8) updates tests FAFB LR swap (afe883e86a8f958437c178a38d0878d47cc7298d) Fix flywire_latestids 64 bit root ids (aa8e560216af0117aed55fb49b222deccd385ccc) Full Changelog: https://github.com/natverse/fafbseg/compare/v0.12.0…v0.13.0","code":""},{"path":[]},{"path":"https://natverse.org/fafbseg/news/index.html","id":"whats-changed-0-12-0","dir":"Changelog","previous_headings":"","what":"What’s Changed","title":"fafbseg 0.12.0","text":"Add support cached flywire connectome dumps (see flywire_connectome_data() flywire_partner_summary2() flywire_adjacency_matrix2()) @jefferis https://github.com/natverse/fafbseg/pull/170 flywire_ids() (fafbseg functions take ids inputs) now supports full regular expressions define id queries. example /type:MBON0[24] (fc9df01b69eb5c540bc0bb1ebec89aad4621c695). flywire_islatest() cache option using specific version/timestamp (4b284d7d86b7e1a6da980c521a282fa693f71456). means flywire_updateids() flywire_partner_summary2() can fast using fixed version. export read_l2dp() read_l2skel() Neuroglancer URL handling (remember baseurl, support tinyurl) @jefferis https://github.com/natverse/fafbseg/pull/167 Make flywire_raw2nm() use vox dims supplied @jefferis https://github.com/natverse/fafbseg/pull/169 Add xform.ngscene() @jefferis https://github.com/natverse/fafbseg/pull/168 Python improvements standardise R-specific miniconda @jefferis https://github.com/natverse/fafbseg/pull/171. includes new fafbseg.condaenv option want specify non-standard miniconda environment. Support flytable super_class @jefferis https://github.com/natverse/fafbseg/pull/172 Export annotations neuroglancer info files (see write_nginfo()) @jefferis https://github.com/natverse/fafbseg/pull/173 add flytable_meta simple interface get flytable cell type information set flywire_ids Full Changelog: https://github.com/natverse/fafbseg/compare/v0.11.1…v0.12.0","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-0111","dir":"Changelog","previous_headings":"","what":"fafbseg 0.11.1","title":"fafbseg 0.11.1","text":"Fix nasty bug adjacency matrix inputids!=outputids @jefferis https://github.com/natverse/fafbseg/pull/165. Also ~2x speedup many use cases. Full Changelog: https://github.com/natverse/fafbseg/compare/v0.11.0…v0.11.1","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-0110","dir":"Changelog","previous_headings":"","what":"fafbseg 0.11.0","title":"fafbseg 0.11.0","text":"Support flytable cell type queries timestamped id updates @jefferis https://github.com/natverse/fafbseg/pull/163 Fix flytable maximum cells error adjusting chunksize @jefferis https://github.com/natverse/fafbseg/pull/147 respect chunksize provided flytable_list_rows @jefferis https://github.com/natverse/fafbseg/pull/148 Add support L2 ids speed flywire_latestid @jefferis https://github.com/natverse/fafbseg/pull/151 Better reporting token locations @jefferis https://github.com/natverse/fafbseg/pull/154 Feature/ng annotations @jefferis https://github.com/natverse/fafbseg/pull/153 Fix doc typo @jefferis https://github.com/natverse/fafbseg/pull/156 Fixes flywire_cave_query timestamp handling @jefferis https://github.com/natverse/fafbseg/pull/159 Feature navis+fafbseg-py reading L2 skeletons @jefferis https://github.com/natverse/fafbseg/pull/160 Teach flywire_cave_query query filter dicts @jefferis https://github.com/natverse/fafbseg/pull/162 Full Changelog: https://github.com/natverse/fafbseg/compare/v0.10.0…v0.11.0","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-0100","dir":"Changelog","previous_headings":"","what":"fafbseg 0.10.0","title":"fafbseg 0.10.0","text":"key change react breaking change URL access spine services. Feature flytable_append_rows @jefferis https://github.com/natverse/fafbseg/pull/132 Update Buhmann ref date @emilkind https://github.com/natverse/fafbseg/pull/138 Feature/misc flywire updates @jefferis https://github.com/natverse/fafbseg/pull/139 Add flywire_nuclei pkgdown @jefferis https://github.com/natverse/fafbseg/pull/140 flytable enhancements / fixes @jefferis https://github.com/natverse/fafbseg/pull/141 Better handling NAs handling body ids @jefferis https://github.com/natverse/fafbseg/pull/142 Fix/spine rename @jefferis https://github.com/natverse/fafbseg/pull/146 spine.janelia.org -> services.itanna.io @perlman https://github.com/natverse/fafbseg/pull/144 changed top.nt top.p top_nt top_p @alexanderbates https://github.com/natverse/fafbseg/pull/143","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"new-contributors-0-10-0","dir":"Changelog","previous_headings":"","what":"New Contributors","title":"fafbseg 0.10.0","text":"@emilkind made first contribution https://github.com/natverse/fafbseg/pull/138 @perlman made first contribution https://github.com/natverse/fafbseg/pull/144 Full Changelog: https://github.com/natverse/fafbseg/compare/v0.9.4…v0.10.0","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-094","dir":"Changelog","previous_headings":"","what":"fafbseg 0.9.4","title":"fafbseg 0.9.4","text":"add support Seung/Allen python CAVE including flywire_cave_client() flywire_cave_query() (#122) add flywire_updateids() (#127) also robustness handling NAs flywire_rootid() first implementation flytable_* functions including flytable_query() flytable_list_rows() flytable_login() (#126) note SSL certificate problem flywire/fanc queries bug (#125) Add ids type info flywire_partners() https://github.com/natverse/fafbseg/issues?q=closed%3A2021-09-20..2021-10-29+","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-093-pre-release-version","dir":"Changelog","previous_headings":"","what":"fafbseg 0.9.3 (pre-release version)","title":"fafbseg 0.9.3 (pre-release version)","text":"pre-release without full release notes, principally support new dependant package, fancr. new flywire_scene() function simple specification flywire neuroglancer scenes. add number features allow programmatic manipulation neuroglancer scenes. includes ngl_segments<-() replace segments scene +.ngscene() -.ngscene() add remove segments scene .character.ngscene() convert scene object URL. See examples ngl_segments() ngl_decode_scene() details (#55, #58). update flywire_set_token() support new cave zetta tokens (FANC dataset) (#119) expose chunkedgraph_token() function (#119) updates token handling handle FANC/FlyWire (#121) Private function check_cloudvolume_reticulate now supports minimum version Handle 1 node neurons (#120) Basic support Python caveclient package. enables fetching range annotation data CAVE (Connectome Annotation Versioning Engine) API including position nuclei user annotations. One notable improvement rapid fetching synaptic partner information. implemented new method=\"cave\" option flywire_partner_summary() (#122). https://github.com/natverse/fafbseg/issues?q=closed%3A2020-12-27..2021-09-20+","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-09","dir":"Changelog","previous_headings":"","what":"fafbseg 0.9","title":"fafbseg 0.9","text":"version change 0.9 reflects small potentially breaking changes user visible behaviour. particular ngl_segments() now returns character default (protect FlyWire ids, expressed 8 byte floating point values). Add flywire_latestid() function map (past) root id current root id. Specifically identifies neuron inheriting largest number super voxels object specified input root id. Support Google ffn1 20200412 segmentation (#14, #46) Make ngl_segments() return ids character vector, rather numeric, default. Also exclude hidden ids default (#50, #51). Allow ngl_segments() (flywire_*) fns accept URLs surface meshes. Previously cause error (#52) Fix ngl_encode_url() tested flywire scenes can parsed R converted back valid URLs can opened flywire.ai (#53) Add print.ngscene method summarise neuroglancer scenes console (#54) flywire_cloudvolume() enables improved low-level support flywire+cloudvolume (exposing reusable cloudvolume object) (#48) full list closed issues GitHub. # fafbseg 0.8.2 Much faster flywire_xyz2id() supervoxel id mapping using spine service (#44) Add new flywire_leaves() function find supervoxels neuron (#43) Fixing typos adding doi TEASAR (#41 @mmc46) Fixing 2 things overlay mesh+skeleton example (#40 @mmc46) Fix flywire_xyz2id eg doc ‘natverse flywire meshes’ returns error (#39) Output dr_fafbseg() points wrong token helper function (#38 @mmc46) can see full list closed issues GitHub.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-081","dir":"Changelog","previous_headings":"","what":"fafbseg 0.8.1","title":"fafbseg 0.8.1","text":"New function skeletor() skeletonise meshes especially flywire neurons based Python package name (#35). Large speed flywire_rootid() (#37) Fix flywire_xyz2id() can actually find supervoxels (well root ids) (#37) function dr_fafbseg() give status update installation (#36) read_cloudvolume_meshes() can now accept flywire URLs (expanded necessary define segments download) can see full list closed issues GitHub.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-080","dir":"Changelog","previous_headings":"","what":"fafbseg 0.8.0","title":"fafbseg 0.8.0","text":"Support basic flywire API calls #31, #34 Better integrate flywire api features Fix/flywire coordinate errors Fix error fafb2flywire() xform_brain #30, #32, #33 Switch transform-service API spine Add support FANC3-FANC4 transforms #28 switch back wire3d #27 Add fafb2flywire() .e. inverse original FlyWire->FAFB transformation #26 Support reading flywire meshes without cloudvolume #25 Flywire API streamlining (@SridharJagannathan) #22 Teach read_cloudvolume_meshes() work flywire URLs #20 ngl_segments() needs able expand flywire URLs #16 can see full list closed issues GitHub.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-070","dir":"Changelog","previous_headings":"","what":"fafbseg 0.7.0","title":"fafbseg 0.7.0","text":"basic support reading meshes via CloudVolume e.g. fetch neurons flywire.ai. See read_cloudvolume_meshes() details including required Python setup. basic support skeletonising neurons meshed (e.g. flywire neurons) via meshparty_skeletonize() add flywire2fafb() support transforming neurons FlyWire->FAFB (loss accuracy reverse) (#11) includes fix NaN values return (#12,#13) much faster FlyWire->FAFB transformation, millions points per minute (#24) moved repo https://github.com/natverse/fafbseg (#19)","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-065","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.5","title":"fafbseg 0.6.5","text":"default chunksize brainmaps_xyz2id() reduce 200 reflect API changes. new functions choose_segmentation() with_segmentation() choose default auto-segmentation New Shiny app (see README https://jefferislab.shinyapps.io/CATMAID-Neuroglancer-Converter/) give brainmaps_fetch() generic cache option ability clear cache brainmaps_clear_cache() (#8) give brainmaps_fetch() retry option help sporadic timeouts (#9) give catmaid2ngl() chunksize option can used reduce timeout issues. simplify package .onLoad retire fafbseg.divisor option (now calculated automatically rather user option) simplify internal brainmaps_voxdims function using cache mechanism","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-064","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.4","title":"fafbseg 0.6.4","text":"fix bug revealed latest public version zip package fix missing import dplyr::n() find_topn()","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-063","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.3","title":"fafbseg 0.6.3","text":"Give find_topn() read_top() ability return segments increasing (rather decreasing) size order.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-062","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.2","title":"fafbseg 0.6.2","text":"fix ngl_encode_url() one segment scene (#5) fix handling neuroglancer URLs two segment sources (#4)","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-061","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.1","title":"fafbseg 0.6.1","text":"New catmaid2ngl() function methods, high level approach converting URLs, neurons etc representations based Neuroglancer / brainmaps data.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-060","dir":"Changelog","previous_headings":"","what":"fafbseg 0.6.0","title":"fafbseg 0.6.0","text":"default remote volume brainmaps_xyz() updated brainmaps://772153499790:fafb_v14:fafb_v14_16nm_v00c_split3xfill2_flatreseg2_skeletons32 volume also used read.neurons.brainmaps()","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-055","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.5","title":"fafbseg 0.5.5","text":"brainmaps_skeleton() read.neurons.brainmaps() now use brainmaps URI specify remote skeleton source. new package option fafbseg.skeletonuri specify default remote skeleton source give brainmaps_xyz2id() chunksize argument handle query points remote API accept single call.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-054","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.4","title":"fafbseg 0.5.4","text":"add read.neuron.brainmaps() read.neurons.brainmaps() read skeletons nat neuron objects web. depends lower level brainmaps_skeleton() function. teach find_merge_groups() return segment ids","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-053","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.3","title":"fafbseg 0.5.3","text":"compare_ng_neuron(): add pointsize sample_dots args doc / example tweaks","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-052","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.2","title":"fafbseg 0.5.2","text":"Support reading 3D meshes directly brainmaps API via read_brainmaps_meshes()","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-051","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.1","title":"fafbseg 0.5.1","text":"export brainmaps_xyz2id() (#2)","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-050","dir":"Changelog","previous_headings":"","what":"fafbseg 0.5.0","title":"fafbseg 0.5.0","text":"Add brainmaps_auth(), brainmaps_fetch() talk brainmaps API Add brainmaps_xyz2id() convert arbitrary XYZ locations corresponding segment id. Teach find_merged_segments() return merge groups","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-041","dir":"Changelog","previous_headings":"","what":"fafbseg 0.4.1","title":"fafbseg 0.4.1","text":"additional functions reading/processing merge (agglomeration) information including read_mergeinfo(), make_merge_graph(), merge_graph_components(). used generate fafbsegdata package useful right.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-040","dir":"Changelog","previous_headings":"","what":"fafbseg 0.4.0","title":"fafbseg 0.4.0","text":"Add find_merged_segments() find raw segments candidate merges agglomeration runs. functionality depends new fafbsegdata package, installed automatically suggested dependency. Switch default zip file divisor 1E6 (actually check contents zip file accommodate new default Peter Li’s 2018-10-02 skeleton release (fafb14_v00c_split3xfill2x_skeleton32nm512_nnconn75_thresh1000_sparse250)","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-035","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.5","title":"fafbseg 0.3.5","text":"fix bug read_segments() datafrac argument logic - reading largest fragment datafrac applies files > minfilesize add internal skelsforsegments() function progress use read_segments2() Turn zip_list memoisation 5 min cache timeout - can speed read_segments2 considerably multiple segments inside zip file.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-034","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.4","title":"fafbseg 0.3.4","text":"turn zip_list memoisation save memory (#1)","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-033","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.3","title":"fafbseg 0.3.3","text":"teach read_segments2() read top n percent skeletons file size additional option read coordinates fix handling zip files >65535 files (see https://github.com/r-lib/zip/issues/11) making use new ziplist64 package available","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-032","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.2","title":"fafbseg 0.3.2","text":"export ngl_decode_scene() function parse neuroglancer URLs JSON scene specifications (turn allowing opened CATMAID) fail better skeleton zip files missing fix bug reading multiple bit64 ids","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-031","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.1","title":"fafbseg 0.3.1","text":"export open_fafb_ngl() teach open_fafb_ngl produce coordinate string paste Neuroglancer add ngl_segments() extract segment ids diverse scene specifications URLs JSON fragments copied Neuroglancer web page","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-030","dir":"Changelog","previous_headings":"","what":"fafbseg 0.3.0","title":"fafbseg 0.3.0","text":"read_segments2() (memory zip extraction) recommended add find_topn() find biggest segments zip files teach read_topn() cope multiple zip files fix sample URL point correct segmentation (fafb_v14_16nm_v00c_split3xfill2) compatible skeletons received.","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-020","dir":"Changelog","previous_headings":"","what":"fafbseg 0.2.0","title":"fafbseg 0.2.0","text":"add support reading neurons zipped skeleton files support mapping ids files vice versa simplify setup neuroglancer URLs improved docs","code":""},{"path":"https://natverse.org/fafbseg/news/index.html","id":"fafbseg-010","dir":"Changelog","previous_headings":"","what":"fafbseg 0.1.0","title":"fafbseg 0.1.0","text":"first version","code":""}]