From 6312d7b0178525f3757c8924e1c1784bc25c200a Mon Sep 17 00:00:00 2001 From: this-is-sofia Date: Sat, 8 Feb 2025 16:46:21 +0000 Subject: [PATCH] deploy: dd282129a7ec4774d32f468524e75978185d3158 --- .../constraint/orientation_rules/pc.html | 1088 +++++++++-------- causy/graph.html | 12 +- causy/graph_model.html | 2 +- causy/interfaces.html | 2 +- search.js | 2 +- 5 files changed, 559 insertions(+), 547 deletions(-) diff --git a/causy/causal_discovery/constraint/orientation_rules/pc.html b/causy/causal_discovery/constraint/orientation_rules/pc.html index ab27457..bd73e27 100644 --- a/causy/causal_discovery/constraint/orientation_rules/pc.html +++ b/causy/causal_discovery/constraint/orientation_rules/pc.html @@ -344,280 +344,286 @@

249 # It cannot be a collider because we have already oriented all unshielded triples that contain colliders. 250 for z in potential_zs: 251 z = graph.nodes[z] -252 breakflag = False -253 if graph.only_directed_edge_exists(x, z) and graph.undirected_edge_exists( -254 z, y -255 ): -256 for node in graph.nodes: -257 if graph.only_directed_edge_exists(graph.nodes[node], y): -258 breakflag = True -259 break -260 if breakflag is True: -261 return TestResult( -262 u=y, -263 v=z, -264 action=TestResultAction.DO_NOTHING, -265 data={ -266 "orientation_conflict": True, -267 "between": {"x": x, "y": y, "z": z}, -268 }, -269 ) -270 return TestResult( -271 u=y, -272 v=z, -273 action=TestResultAction.REMOVE_EDGE_DIRECTED, -274 data={"between": {"x": x, "y": y, "z": z}}, -275 ) -276 -277 if graph.only_directed_edge_exists(y, z) and graph.undirected_edge_exists( -278 z, x -279 ): -280 for node in graph.nodes: -281 if graph.only_directed_edge_exists(graph.nodes[node], x): -282 breakflag = True -283 break -284 if breakflag is True: -285 return TestResult( -286 u=x, -287 v=z, -288 action=TestResultAction.DO_NOTHING, -289 data={ -290 "orientation_conflict": True, -291 "between": {"x": x, "y": y, "z": z}, -292 }, -293 ) -294 return TestResult( -295 u=x, -296 v=z, -297 action=TestResultAction.REMOVE_EDGE_DIRECTED, -298 data={}, -299 ) -300 -301 -302class FurtherOrientTripleTest( -303 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] -304): -305 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( -306 comparison_settings=ComparisonSettings(min=2, max=2) -307 ) -308 chunk_size_parallel_processing: IntegerParameter = 1 -309 parallel: BoolParameter = False -310 -311 def process( -312 self, nodes: Tuple[str], graph: BaseGraphInterface -313 ) -> Optional[List[TestResult] | TestResult]: -314 """ -315 Further orientation rule. -316 :param nodes: list of nodes -317 :param graph: the current graph -318 :returns: list of actions that will be executed on graph -319 """ -320 -321 x = graph.nodes[nodes[0]] -322 y = graph.nodes[nodes[1]] -323 -324 results = [] -325 for z in graph.nodes: -326 z = graph.nodes[z] -327 # check if it is a potential z -328 if not (graph.edge_exists(y, z) and graph.edge_exists(x, z)): -329 continue -330 -331 if ( -332 graph.undirected_edge_exists(x, y) -333 and graph.only_directed_edge_exists(x, z) -334 and graph.only_directed_edge_exists(z, y) -335 ): -336 results.append( -337 TestResult( -338 u=y, -339 v=x, -340 action=TestResultAction.REMOVE_EDGE_DIRECTED, -341 data={"between": {"x": x, "y": y, "z": z}}, -342 ) -343 ) -344 if ( -345 graph.undirected_edge_exists(x, y) -346 and graph.only_directed_edge_exists(y, z) -347 and graph.only_directed_edge_exists(z, x) -348 ): -349 results.append( -350 TestResult( -351 u=x, -352 v=y, -353 action=TestResultAction.REMOVE_EDGE_DIRECTED, -354 data={"between": {"x": x, "y": y, "z": z}}, -355 ) -356 ) -357 return results -358 -359 -360class OrientQuadrupleTest( -361 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] -362): -363 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( -364 comparison_settings=ComparisonSettings(min=2, max=2) -365 ) -366 chunk_size_parallel_processing: IntegerParameter = 1 -367 parallel: BoolParameter = False -368 -369 def process( -370 self, nodes: Tuple[str], graph: BaseGraphInterface -371 ) -> Optional[List[TestResult] | TestResult]: -372 """ -373 Further orientation rule. -374 :param nodes: list of nodes -375 :param graph: the current graph -376 :returns: list of actions that will be executed on graph -377 """ -378 -379 y = graph.nodes[nodes[0]] -380 w = graph.nodes[nodes[1]] -381 -382 potential_zs = set() -383 -384 # TODO: just iterate over edges -385 for z in graph.nodes: -386 z = graph.nodes[z] -387 if graph.edge_exists(y, z) and graph.edge_exists(z, w): -388 potential_zs.add(z) +252 print(f"x: {x.name}, y: {y.name}, z: {z.name}") +253 breakflag = False +254 if graph.only_directed_edge_exists(x, z) and graph.undirected_edge_exists( +255 z, y +256 ): +257 for node in graph.nodes: +258 if graph.only_directed_edge_exists(graph.nodes[node], y) and not graph.edge_exists(graph.nodes[node], z): +259 breakflag = True +260 break +261 if breakflag is True: +262 return TestResult( +263 u=y, +264 v=z, +265 action=TestResultAction.DO_NOTHING, +266 data={ +267 "orientation_conflict": True, +268 "between": {"x": x, "y": y, "z": z}, +269 }, +270 ) +271 return TestResult( +272 u=y, +273 v=z, +274 action=TestResultAction.REMOVE_EDGE_DIRECTED, +275 data={"between": {"x": x, "y": y, "z": z}}, +276 ) +277 print(graph.only_directed_edge_exists(y, z)) +278 print(graph.undirected_edge_exists(z, x)) +279 if z.name in graph.edges: +280 if x.name in graph.edges[z.name]: +281 print(f"{z.name} -> {x.name}") +282 if graph.only_directed_edge_exists(y, z) and graph.undirected_edge_exists( +283 z, x +284 ): +285 for node in graph.nodes: +286 if graph.only_directed_edge_exists(graph.nodes[node], x): +287 breakflag = True +288 break +289 print(f"breakflag: {breakflag}") +290 if breakflag is True: +291 return TestResult( +292 u=x, +293 v=z, +294 action=TestResultAction.DO_NOTHING, +295 data={ +296 "orientation_conflict": True, +297 "between": {"x": x, "y": y, "z": z}, +298 }, +299 ) +300 return TestResult( +301 u=x, +302 v=z, +303 action=TestResultAction.REMOVE_EDGE_DIRECTED, +304 data={}, +305 ) +306 +307 +308class FurtherOrientTripleTest( +309 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] +310): +311 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( +312 comparison_settings=ComparisonSettings(min=2, max=2) +313 ) +314 chunk_size_parallel_processing: IntegerParameter = 1 +315 parallel: BoolParameter = False +316 +317 def process( +318 self, nodes: Tuple[str], graph: BaseGraphInterface +319 ) -> Optional[List[TestResult] | TestResult]: +320 """ +321 Further orientation rule. +322 :param nodes: list of nodes +323 :param graph: the current graph +324 :returns: list of actions that will be executed on graph +325 """ +326 +327 x = graph.nodes[nodes[0]] +328 y = graph.nodes[nodes[1]] +329 +330 results = [] +331 for z in graph.nodes: +332 z = graph.nodes[z] +333 # check if it is a potential z +334 if not (graph.edge_exists(y, z) and graph.edge_exists(x, z)): +335 continue +336 +337 if ( +338 graph.undirected_edge_exists(x, y) +339 and graph.only_directed_edge_exists(x, z) +340 and graph.only_directed_edge_exists(z, y) +341 ): +342 results.append( +343 TestResult( +344 u=y, +345 v=x, +346 action=TestResultAction.REMOVE_EDGE_DIRECTED, +347 data={"between": {"x": x, "y": y, "z": z}}, +348 ) +349 ) +350 if ( +351 graph.undirected_edge_exists(x, y) +352 and graph.only_directed_edge_exists(y, z) +353 and graph.only_directed_edge_exists(z, x) +354 ): +355 results.append( +356 TestResult( +357 u=x, +358 v=y, +359 action=TestResultAction.REMOVE_EDGE_DIRECTED, +360 data={"between": {"x": x, "y": y, "z": z}}, +361 ) +362 ) +363 return results +364 +365 +366class OrientQuadrupleTest( +367 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] +368): +369 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( +370 comparison_settings=ComparisonSettings(min=2, max=2) +371 ) +372 chunk_size_parallel_processing: IntegerParameter = 1 +373 parallel: BoolParameter = False +374 +375 def process( +376 self, nodes: Tuple[str], graph: BaseGraphInterface +377 ) -> Optional[List[TestResult] | TestResult]: +378 """ +379 Further orientation rule. +380 :param nodes: list of nodes +381 :param graph: the current graph +382 :returns: list of actions that will be executed on graph +383 """ +384 +385 y = graph.nodes[nodes[0]] +386 w = graph.nodes[nodes[1]] +387 +388 potential_zs = set() 389 -390 results = [] -391 for zs in itertools.combinations(potential_zs, 2): -392 x, z = zs -393 if ( -394 not graph.edge_exists(y, w) -395 and graph.only_directed_edge_exists(y, z) -396 and graph.only_directed_edge_exists(w, z) -397 and graph.undirected_edge_exists(x, y) -398 and graph.undirected_edge_exists(x, w) -399 and graph.undirected_edge_exists(x, z) -400 ): -401 results.append( -402 TestResult( -403 u=z, -404 v=x, -405 action=TestResultAction.REMOVE_EDGE_DIRECTED, -406 data={}, -407 ) -408 ) -409 if ( -410 not graph.edge_exists(y, w) -411 and graph.only_directed_edge_exists(y, x) -412 and graph.only_directed_edge_exists(w, x) -413 and graph.undirected_edge_exists(y, z) -414 and graph.undirected_edge_exists(w, z) -415 and graph.undirected_edge_exists(x, z) -416 ): -417 results.append( -418 TestResult( -419 u=x, -420 v=z, -421 action=TestResultAction.REMOVE_EDGE_DIRECTED, -422 data={}, -423 ) -424 ) -425 return results -426 -427 -428class FurtherOrientQuadrupleTest( -429 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] -430): -431 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( -432 comparison_settings=ComparisonSettings(min=2, max=2) -433 ) -434 chunk_size_parallel_processing: int = 1 -435 parallel: bool = False -436 -437 def process( -438 self, nodes: Tuple[str], graph: BaseGraphInterface -439 ) -> Optional[List[TestResult] | TestResult]: -440 """ -441 Further orientation rule. -442 :param nodes: list of nodes -443 :param graph: the current graph -444 :returns: list of actions that will be executed on graph -445 """ -446 -447 x = graph.nodes[nodes[0]] -448 w = graph.nodes[nodes[1]] -449 -450 potential_zs = set() -451 -452 # TODO: just iterate over edges -453 for z in graph.nodes: -454 z = graph.nodes[z] -455 if graph.edge_exists(x, z) and graph.edge_exists(z, w): -456 potential_zs.add(z) +390 # TODO: just iterate over edges +391 for z in graph.nodes: +392 z = graph.nodes[z] +393 if graph.edge_exists(y, z) and graph.edge_exists(z, w): +394 potential_zs.add(z) +395 +396 results = [] +397 for zs in itertools.combinations(potential_zs, 2): +398 x, z = zs +399 if ( +400 not graph.edge_exists(y, w) +401 and graph.only_directed_edge_exists(y, z) +402 and graph.only_directed_edge_exists(w, z) +403 and graph.undirected_edge_exists(x, y) +404 and graph.undirected_edge_exists(x, w) +405 and graph.undirected_edge_exists(x, z) +406 ): +407 results.append( +408 TestResult( +409 u=z, +410 v=x, +411 action=TestResultAction.REMOVE_EDGE_DIRECTED, +412 data={}, +413 ) +414 ) +415 if ( +416 not graph.edge_exists(y, w) +417 and graph.only_directed_edge_exists(y, x) +418 and graph.only_directed_edge_exists(w, x) +419 and graph.undirected_edge_exists(y, z) +420 and graph.undirected_edge_exists(w, z) +421 and graph.undirected_edge_exists(x, z) +422 ): +423 results.append( +424 TestResult( +425 u=x, +426 v=z, +427 action=TestResultAction.REMOVE_EDGE_DIRECTED, +428 data={}, +429 ) +430 ) +431 return results +432 +433 +434class FurtherOrientQuadrupleTest( +435 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] +436): +437 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( +438 comparison_settings=ComparisonSettings(min=2, max=2) +439 ) +440 chunk_size_parallel_processing: int = 1 +441 parallel: bool = False +442 +443 def process( +444 self, nodes: Tuple[str], graph: BaseGraphInterface +445 ) -> Optional[List[TestResult] | TestResult]: +446 """ +447 Further orientation rule. +448 :param nodes: list of nodes +449 :param graph: the current graph +450 :returns: list of actions that will be executed on graph +451 """ +452 +453 x = graph.nodes[nodes[0]] +454 w = graph.nodes[nodes[1]] +455 +456 potential_zs = set() 457 -458 results = [] -459 for zs in itertools.combinations(potential_zs, 2): -460 y, z = zs -461 if ( -462 not graph.edge_exists(y, z) -463 and graph.undirected_edge_exists(x, z) -464 and graph.undirected_edge_exists(x, w) -465 and graph.undirected_edge_exists(x, y) -466 and graph.only_directed_edge_exists(y, w) -467 and graph.only_directed_edge_exists(w, z) -468 ): -469 results.append( -470 TestResult( -471 u=z, -472 v=x, -473 action=TestResultAction.REMOVE_EDGE_DIRECTED, -474 data={}, -475 ) -476 ) -477 elif ( -478 not graph.edge_exists(z, y) -479 and graph.undirected_edge_exists(x, y) -480 and graph.undirected_edge_exists(x, w) -481 and graph.undirected_edge_exists(x, z) -482 and graph.only_directed_edge_exists(z, w) -483 and graph.only_directed_edge_exists(w, y) -484 ): -485 results.append( -486 TestResult( -487 u=y, -488 v=x, -489 action=TestResultAction.REMOVE_EDGE_DIRECTED, -490 data={}, -491 ) -492 ) -493 elif ( -494 not graph.edge_exists(y, z) -495 and graph.undirected_edge_exists(w, z) -496 and graph.undirected_edge_exists(x, w) -497 and graph.undirected_edge_exists(w, y) -498 and graph.only_directed_edge_exists(y, x) -499 and graph.only_directed_edge_exists(x, z) -500 ): -501 results.append( -502 TestResult( -503 u=z, -504 v=w, -505 action=TestResultAction.REMOVE_EDGE_DIRECTED, -506 data={}, -507 ) -508 ) -509 elif ( -510 not graph.edge_exists(z, y) -511 and graph.undirected_edge_exists(w, y) -512 and graph.undirected_edge_exists(x, w) -513 and graph.undirected_edge_exists(w, z) -514 and graph.only_directed_edge_exists(z, x) -515 and graph.only_directed_edge_exists(x, y) -516 ): -517 results.append( -518 TestResult( -519 u=y, -520 v=w, -521 action=TestResultAction.REMOVE_EDGE_DIRECTED, -522 data={}, -523 ) -524 ) -525 return results +458 # TODO: just iterate over edges +459 for z in graph.nodes: +460 z = graph.nodes[z] +461 if graph.edge_exists(x, z) and graph.edge_exists(z, w): +462 potential_zs.add(z) +463 +464 results = [] +465 for zs in itertools.combinations(potential_zs, 2): +466 y, z = zs +467 if ( +468 not graph.edge_exists(y, z) +469 and graph.undirected_edge_exists(x, z) +470 and graph.undirected_edge_exists(x, w) +471 and graph.undirected_edge_exists(x, y) +472 and graph.only_directed_edge_exists(y, w) +473 and graph.only_directed_edge_exists(w, z) +474 ): +475 results.append( +476 TestResult( +477 u=z, +478 v=x, +479 action=TestResultAction.REMOVE_EDGE_DIRECTED, +480 data={}, +481 ) +482 ) +483 elif ( +484 not graph.edge_exists(z, y) +485 and graph.undirected_edge_exists(x, y) +486 and graph.undirected_edge_exists(x, w) +487 and graph.undirected_edge_exists(x, z) +488 and graph.only_directed_edge_exists(z, w) +489 and graph.only_directed_edge_exists(w, y) +490 ): +491 results.append( +492 TestResult( +493 u=y, +494 v=x, +495 action=TestResultAction.REMOVE_EDGE_DIRECTED, +496 data={}, +497 ) +498 ) +499 elif ( +500 not graph.edge_exists(y, z) +501 and graph.undirected_edge_exists(w, z) +502 and graph.undirected_edge_exists(x, w) +503 and graph.undirected_edge_exists(w, y) +504 and graph.only_directed_edge_exists(y, x) +505 and graph.only_directed_edge_exists(x, z) +506 ): +507 results.append( +508 TestResult( +509 u=z, +510 v=w, +511 action=TestResultAction.REMOVE_EDGE_DIRECTED, +512 data={}, +513 ) +514 ) +515 elif ( +516 not graph.edge_exists(z, y) +517 and graph.undirected_edge_exists(w, y) +518 and graph.undirected_edge_exists(x, w) +519 and graph.undirected_edge_exists(w, z) +520 and graph.only_directed_edge_exists(z, x) +521 and graph.only_directed_edge_exists(x, y) +522 ): +523 results.append( +524 TestResult( +525 u=y, +526 v=w, +527 action=TestResultAction.REMOVE_EDGE_DIRECTED, +528 data={}, +529 ) +530 ) +531 return results @@ -1113,54 +1119,60 @@

Inherited Members
250 # It cannot be a collider because we have already oriented all unshielded triples that contain colliders. 251 for z in potential_zs: 252 z = graph.nodes[z] -253 breakflag = False -254 if graph.only_directed_edge_exists(x, z) and graph.undirected_edge_exists( -255 z, y -256 ): -257 for node in graph.nodes: -258 if graph.only_directed_edge_exists(graph.nodes[node], y): -259 breakflag = True -260 break -261 if breakflag is True: -262 return TestResult( -263 u=y, -264 v=z, -265 action=TestResultAction.DO_NOTHING, -266 data={ -267 "orientation_conflict": True, -268 "between": {"x": x, "y": y, "z": z}, -269 }, -270 ) -271 return TestResult( -272 u=y, -273 v=z, -274 action=TestResultAction.REMOVE_EDGE_DIRECTED, -275 data={"between": {"x": x, "y": y, "z": z}}, -276 ) -277 -278 if graph.only_directed_edge_exists(y, z) and graph.undirected_edge_exists( -279 z, x -280 ): -281 for node in graph.nodes: -282 if graph.only_directed_edge_exists(graph.nodes[node], x): -283 breakflag = True -284 break -285 if breakflag is True: -286 return TestResult( -287 u=x, -288 v=z, -289 action=TestResultAction.DO_NOTHING, -290 data={ -291 "orientation_conflict": True, -292 "between": {"x": x, "y": y, "z": z}, -293 }, -294 ) -295 return TestResult( -296 u=x, -297 v=z, -298 action=TestResultAction.REMOVE_EDGE_DIRECTED, -299 data={}, -300 ) +253 print(f"x: {x.name}, y: {y.name}, z: {z.name}") +254 breakflag = False +255 if graph.only_directed_edge_exists(x, z) and graph.undirected_edge_exists( +256 z, y +257 ): +258 for node in graph.nodes: +259 if graph.only_directed_edge_exists(graph.nodes[node], y) and not graph.edge_exists(graph.nodes[node], z): +260 breakflag = True +261 break +262 if breakflag is True: +263 return TestResult( +264 u=y, +265 v=z, +266 action=TestResultAction.DO_NOTHING, +267 data={ +268 "orientation_conflict": True, +269 "between": {"x": x, "y": y, "z": z}, +270 }, +271 ) +272 return TestResult( +273 u=y, +274 v=z, +275 action=TestResultAction.REMOVE_EDGE_DIRECTED, +276 data={"between": {"x": x, "y": y, "z": z}}, +277 ) +278 print(graph.only_directed_edge_exists(y, z)) +279 print(graph.undirected_edge_exists(z, x)) +280 if z.name in graph.edges: +281 if x.name in graph.edges[z.name]: +282 print(f"{z.name} -> {x.name}") +283 if graph.only_directed_edge_exists(y, z) and graph.undirected_edge_exists( +284 z, x +285 ): +286 for node in graph.nodes: +287 if graph.only_directed_edge_exists(graph.nodes[node], x): +288 breakflag = True +289 break +290 print(f"breakflag: {breakflag}") +291 if breakflag is True: +292 return TestResult( +293 u=x, +294 v=z, +295 action=TestResultAction.DO_NOTHING, +296 data={ +297 "orientation_conflict": True, +298 "between": {"x": x, "y": y, "z": z}, +299 }, +300 ) +301 return TestResult( +302 u=x, +303 v=z, +304 action=TestResultAction.REMOVE_EDGE_DIRECTED, +305 data={}, +306 ) @@ -1230,62 +1242,62 @@
Inherited Members
- 
303class FurtherOrientTripleTest(
-304    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
-305):
-306    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
-307        comparison_settings=ComparisonSettings(min=2, max=2)
-308    )
-309    chunk_size_parallel_processing: IntegerParameter = 1
-310    parallel: BoolParameter = False
-311
-312    def process(
-313        self, nodes: Tuple[str], graph: BaseGraphInterface
-314    ) -> Optional[List[TestResult] | TestResult]:
-315        """
-316        Further orientation rule.
-317        :param nodes: list of nodes
-318        :param graph: the current graph
-319        :returns: list of actions that will be executed on graph
-320        """
-321
-322        x = graph.nodes[nodes[0]]
-323        y = graph.nodes[nodes[1]]
-324
-325        results = []
-326        for z in graph.nodes:
-327            z = graph.nodes[z]
-328            # check if it is a potential z
-329            if not (graph.edge_exists(y, z) and graph.edge_exists(x, z)):
-330                continue
-331
-332            if (
-333                graph.undirected_edge_exists(x, y)
-334                and graph.only_directed_edge_exists(x, z)
-335                and graph.only_directed_edge_exists(z, y)
-336            ):
-337                results.append(
-338                    TestResult(
-339                        u=y,
-340                        v=x,
-341                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-342                        data={"between": {"x": x, "y": y, "z": z}},
-343                    )
-344                )
-345            if (
-346                graph.undirected_edge_exists(x, y)
-347                and graph.only_directed_edge_exists(y, z)
-348                and graph.only_directed_edge_exists(z, x)
-349            ):
-350                results.append(
-351                    TestResult(
-352                        u=x,
-353                        v=y,
-354                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-355                        data={"between": {"x": x, "y": y, "z": z}},
-356                    )
-357                )
-358        return results
+            
309class FurtherOrientTripleTest(
+310    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
+311):
+312    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
+313        comparison_settings=ComparisonSettings(min=2, max=2)
+314    )
+315    chunk_size_parallel_processing: IntegerParameter = 1
+316    parallel: BoolParameter = False
+317
+318    def process(
+319        self, nodes: Tuple[str], graph: BaseGraphInterface
+320    ) -> Optional[List[TestResult] | TestResult]:
+321        """
+322        Further orientation rule.
+323        :param nodes: list of nodes
+324        :param graph: the current graph
+325        :returns: list of actions that will be executed on graph
+326        """
+327
+328        x = graph.nodes[nodes[0]]
+329        y = graph.nodes[nodes[1]]
+330
+331        results = []
+332        for z in graph.nodes:
+333            z = graph.nodes[z]
+334            # check if it is a potential z
+335            if not (graph.edge_exists(y, z) and graph.edge_exists(x, z)):
+336                continue
+337
+338            if (
+339                graph.undirected_edge_exists(x, y)
+340                and graph.only_directed_edge_exists(x, z)
+341                and graph.only_directed_edge_exists(z, y)
+342            ):
+343                results.append(
+344                    TestResult(
+345                        u=y,
+346                        v=x,
+347                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+348                        data={"between": {"x": x, "y": y, "z": z}},
+349                    )
+350                )
+351            if (
+352                graph.undirected_edge_exists(x, y)
+353                and graph.only_directed_edge_exists(y, z)
+354                and graph.only_directed_edge_exists(z, x)
+355            ):
+356                results.append(
+357                    TestResult(
+358                        u=x,
+359                        v=y,
+360                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+361                        data={"between": {"x": x, "y": y, "z": z}},
+362                    )
+363                )
+364        return results
 

 
 
@@ -1355,72 +1367,72 @@ 
Inherited Members
- 
361class OrientQuadrupleTest(
-362    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
-363):
-364    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
-365        comparison_settings=ComparisonSettings(min=2, max=2)
-366    )
-367    chunk_size_parallel_processing: IntegerParameter = 1
-368    parallel: BoolParameter = False
-369
-370    def process(
-371        self, nodes: Tuple[str], graph: BaseGraphInterface
-372    ) -> Optional[List[TestResult] | TestResult]:
-373        """
-374        Further orientation rule.
-375        :param nodes: list of nodes
-376        :param graph: the current graph
-377        :returns: list of actions that will be executed on graph
-378        """
-379
-380        y = graph.nodes[nodes[0]]
-381        w = graph.nodes[nodes[1]]
-382
-383        potential_zs = set()
-384
-385        # TODO: just iterate over edges
-386        for z in graph.nodes:
-387            z = graph.nodes[z]
-388            if graph.edge_exists(y, z) and graph.edge_exists(z, w):
-389                potential_zs.add(z)
+            
367class OrientQuadrupleTest(
+368    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
+369):
+370    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
+371        comparison_settings=ComparisonSettings(min=2, max=2)
+372    )
+373    chunk_size_parallel_processing: IntegerParameter = 1
+374    parallel: BoolParameter = False
+375
+376    def process(
+377        self, nodes: Tuple[str], graph: BaseGraphInterface
+378    ) -> Optional[List[TestResult] | TestResult]:
+379        """
+380        Further orientation rule.
+381        :param nodes: list of nodes
+382        :param graph: the current graph
+383        :returns: list of actions that will be executed on graph
+384        """
+385
+386        y = graph.nodes[nodes[0]]
+387        w = graph.nodes[nodes[1]]
+388
+389        potential_zs = set()
 390
-391        results = []
-392        for zs in itertools.combinations(potential_zs, 2):
-393            x, z = zs
-394            if (
-395                not graph.edge_exists(y, w)
-396                and graph.only_directed_edge_exists(y, z)
-397                and graph.only_directed_edge_exists(w, z)
-398                and graph.undirected_edge_exists(x, y)
-399                and graph.undirected_edge_exists(x, w)
-400                and graph.undirected_edge_exists(x, z)
-401            ):
-402                results.append(
-403                    TestResult(
-404                        u=z,
-405                        v=x,
-406                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-407                        data={},
-408                    )
-409                )
-410            if (
-411                not graph.edge_exists(y, w)
-412                and graph.only_directed_edge_exists(y, x)
-413                and graph.only_directed_edge_exists(w, x)
-414                and graph.undirected_edge_exists(y, z)
-415                and graph.undirected_edge_exists(w, z)
-416                and graph.undirected_edge_exists(x, z)
-417            ):
-418                results.append(
-419                    TestResult(
-420                        u=x,
-421                        v=z,
-422                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-423                        data={},
-424                    )
-425                )
-426        return results
+391        # TODO: just iterate over edges
+392        for z in graph.nodes:
+393            z = graph.nodes[z]
+394            if graph.edge_exists(y, z) and graph.edge_exists(z, w):
+395                potential_zs.add(z)
+396
+397        results = []
+398        for zs in itertools.combinations(potential_zs, 2):
+399            x, z = zs
+400            if (
+401                not graph.edge_exists(y, w)
+402                and graph.only_directed_edge_exists(y, z)
+403                and graph.only_directed_edge_exists(w, z)
+404                and graph.undirected_edge_exists(x, y)
+405                and graph.undirected_edge_exists(x, w)
+406                and graph.undirected_edge_exists(x, z)
+407            ):
+408                results.append(
+409                    TestResult(
+410                        u=z,
+411                        v=x,
+412                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+413                        data={},
+414                    )
+415                )
+416            if (
+417                not graph.edge_exists(y, w)
+418                and graph.only_directed_edge_exists(y, x)
+419                and graph.only_directed_edge_exists(w, x)
+420                and graph.undirected_edge_exists(y, z)
+421                and graph.undirected_edge_exists(w, z)
+422                and graph.undirected_edge_exists(x, z)
+423            ):
+424                results.append(
+425                    TestResult(
+426                        u=x,
+427                        v=z,
+428                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+429                        data={},
+430                    )
+431                )
+432        return results
 

 
 
@@ -1490,104 +1502,104 @@ 
Inherited Members
- 
429class FurtherOrientQuadrupleTest(
-430    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
-431):
-432    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
-433        comparison_settings=ComparisonSettings(min=2, max=2)
-434    )
-435    chunk_size_parallel_processing: int = 1
-436    parallel: bool = False
-437
-438    def process(
-439        self, nodes: Tuple[str], graph: BaseGraphInterface
-440    ) -> Optional[List[TestResult] | TestResult]:
-441        """
-442        Further orientation rule.
-443        :param nodes: list of nodes
-444        :param graph: the current graph
-445        :returns: list of actions that will be executed on graph
-446        """
-447
-448        x = graph.nodes[nodes[0]]
-449        w = graph.nodes[nodes[1]]
-450
-451        potential_zs = set()
-452
-453        # TODO: just iterate over edges
-454        for z in graph.nodes:
-455            z = graph.nodes[z]
-456            if graph.edge_exists(x, z) and graph.edge_exists(z, w):
-457                potential_zs.add(z)
+            
435class FurtherOrientQuadrupleTest(
+436    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
+437):
+438    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
+439        comparison_settings=ComparisonSettings(min=2, max=2)
+440    )
+441    chunk_size_parallel_processing: int = 1
+442    parallel: bool = False
+443
+444    def process(
+445        self, nodes: Tuple[str], graph: BaseGraphInterface
+446    ) -> Optional[List[TestResult] | TestResult]:
+447        """
+448        Further orientation rule.
+449        :param nodes: list of nodes
+450        :param graph: the current graph
+451        :returns: list of actions that will be executed on graph
+452        """
+453
+454        x = graph.nodes[nodes[0]]
+455        w = graph.nodes[nodes[1]]
+456
+457        potential_zs = set()
 458
-459        results = []
-460        for zs in itertools.combinations(potential_zs, 2):
-461            y, z = zs
-462            if (
-463                not graph.edge_exists(y, z)
-464                and graph.undirected_edge_exists(x, z)
-465                and graph.undirected_edge_exists(x, w)
-466                and graph.undirected_edge_exists(x, y)
-467                and graph.only_directed_edge_exists(y, w)
-468                and graph.only_directed_edge_exists(w, z)
-469            ):
-470                results.append(
-471                    TestResult(
-472                        u=z,
-473                        v=x,
-474                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-475                        data={},
-476                    )
-477                )
-478            elif (
-479                not graph.edge_exists(z, y)
-480                and graph.undirected_edge_exists(x, y)
-481                and graph.undirected_edge_exists(x, w)
-482                and graph.undirected_edge_exists(x, z)
-483                and graph.only_directed_edge_exists(z, w)
-484                and graph.only_directed_edge_exists(w, y)
-485            ):
-486                results.append(
-487                    TestResult(
-488                        u=y,
-489                        v=x,
-490                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-491                        data={},
-492                    )
-493                )
-494            elif (
-495                not graph.edge_exists(y, z)
-496                and graph.undirected_edge_exists(w, z)
-497                and graph.undirected_edge_exists(x, w)
-498                and graph.undirected_edge_exists(w, y)
-499                and graph.only_directed_edge_exists(y, x)
-500                and graph.only_directed_edge_exists(x, z)
-501            ):
-502                results.append(
-503                    TestResult(
-504                        u=z,
-505                        v=w,
-506                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-507                        data={},
-508                    )
-509                )
-510            elif (
-511                not graph.edge_exists(z, y)
-512                and graph.undirected_edge_exists(w, y)
-513                and graph.undirected_edge_exists(x, w)
-514                and graph.undirected_edge_exists(w, z)
-515                and graph.only_directed_edge_exists(z, x)
-516                and graph.only_directed_edge_exists(x, y)
-517            ):
-518                results.append(
-519                    TestResult(
-520                        u=y,
-521                        v=w,
-522                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-523                        data={},
-524                    )
-525                )
-526        return results
+459        # TODO: just iterate over edges
+460        for z in graph.nodes:
+461            z = graph.nodes[z]
+462            if graph.edge_exists(x, z) and graph.edge_exists(z, w):
+463                potential_zs.add(z)
+464
+465        results = []
+466        for zs in itertools.combinations(potential_zs, 2):
+467            y, z = zs
+468            if (
+469                not graph.edge_exists(y, z)
+470                and graph.undirected_edge_exists(x, z)
+471                and graph.undirected_edge_exists(x, w)
+472                and graph.undirected_edge_exists(x, y)
+473                and graph.only_directed_edge_exists(y, w)
+474                and graph.only_directed_edge_exists(w, z)
+475            ):
+476                results.append(
+477                    TestResult(
+478                        u=z,
+479                        v=x,
+480                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+481                        data={},
+482                    )
+483                )
+484            elif (
+485                not graph.edge_exists(z, y)
+486                and graph.undirected_edge_exists(x, y)
+487                and graph.undirected_edge_exists(x, w)
+488                and graph.undirected_edge_exists(x, z)
+489                and graph.only_directed_edge_exists(z, w)
+490                and graph.only_directed_edge_exists(w, y)
+491            ):
+492                results.append(
+493                    TestResult(
+494                        u=y,
+495                        v=x,
+496                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+497                        data={},
+498                    )
+499                )
+500            elif (
+501                not graph.edge_exists(y, z)
+502                and graph.undirected_edge_exists(w, z)
+503                and graph.undirected_edge_exists(x, w)
+504                and graph.undirected_edge_exists(w, y)
+505                and graph.only_directed_edge_exists(y, x)
+506                and graph.only_directed_edge_exists(x, z)
+507            ):
+508                results.append(
+509                    TestResult(
+510                        u=z,
+511                        v=w,
+512                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+513                        data={},
+514                    )
+515                )
+516            elif (
+517                not graph.edge_exists(z, y)
+518                and graph.undirected_edge_exists(w, y)
+519                and graph.undirected_edge_exists(x, w)
+520                and graph.undirected_edge_exists(w, z)
+521                and graph.only_directed_edge_exists(z, x)
+522                and graph.only_directed_edge_exists(x, y)
+523            ):
+524                results.append(
+525                    TestResult(
+526                        u=y,
+527                        v=w,
+528                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+529                        data={},
+530                    )
+531                )
+532        return results
 

 
 
diff --git a/causy/graph.html b/causy/graph.html
index 7a3ff22..e94bf12 100644
--- a/causy/graph.html
+++ b/causy/graph.html
@@ -3120,7 +3120,7 @@ 
Returns

 

             
     class
-    Graph(GraphBaseAccessMixin, causy.interfaces.ExtensionInterface.GraphAccessMixin, causy.interfaces.EdgeTypeInterface.GraphAccessMixin, pydantic.main.BaseModel, causy.edge_types.DirectedEdge.GraphAccessMixin):
+    Graph(causy.interfaces.EdgeTypeInterface.GraphAccessMixin, causy.edge_types.DirectedEdge.GraphAccessMixin, GraphBaseAccessMixin, causy.interfaces.ExtensionInterface.GraphAccessMixin, pydantic.main.BaseModel):
 
                 
 
@@ -3293,6 +3293,11 @@ 
Inherited Members

                 
validate

                 
update_forward_refs

 
+            

+            
causy.edge_types.DirectedEdge.GraphAccessMixin

+                                
only_directed_edge_exists

+                
directed_paths

+
             

             
GraphBaseAccessMixin

                                 
directed_edge_is_soft_deleted

@@ -3313,11 +3318,6 @@ 
Inherited Members

                 
all_paths_on_underlying_undirected_graph

                 
retrieve_edges

 
-            

-            
causy.edge_types.DirectedEdge.GraphAccessMixin

-                                
only_directed_edge_exists

-                
directed_paths

-
diff --git a/causy/graph_model.html b/causy/graph_model.html index 26c6c7f..29c074c 100644 --- a/causy/graph_model.html +++ b/causy/graph_model.html @@ -1268,7 +1268,7 @@

- pool: <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7eff2b8dd7f0>> + pool: <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f03cc4c8fe0>>
diff --git a/causy/interfaces.html b/causy/interfaces.html index 2171980..70e6581 100644 --- a/causy/interfaces.html +++ b/causy/interfaces.html @@ -2706,7 +2706,7 @@
Inherited Members
- pool: <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7eff2b8dd7f0>> + pool: <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f03cc4c8fe0>>
diff --git a/search.js b/search.js index 90c5173..f9b6510 100644 --- a/search.js +++ b/search.js @@ -1,6 +1,6 @@ window.pdocSearch = (function(){ /** elasticlunr - http://weixsong.github.io * Copyright (C) 2017 Oliver Nightingale * Copyright (C) 2017 Wei Song * MIT Licensed */!function(){function e(e){if(null===e||"object"!=typeof e)return e;var t=e.constructor();for(var n in e)e.hasOwnProperty(n)&&(t[n]=e[n]);return t}var t=function(e){var n=new t.Index;return n.pipeline.add(t.trimmer,t.stopWordFilter,t.stemmer),e&&e.call(n,n),n};t.version="0.9.5",lunr=t,t.utils={},t.utils.warn=function(e){return function(t){e.console&&console.warn&&console.warn(t)}}(this),t.utils.toString=function(e){return void 0===e||null===e?"":e.toString()},t.EventEmitter=function(){this.events={}},t.EventEmitter.prototype.addListener=function(){var e=Array.prototype.slice.call(arguments),t=e.pop(),n=e;if("function"!=typeof t)throw new TypeError("last argument must be a function");n.forEach(function(e){this.hasHandler(e)||(this.events[e]=[]),this.events[e].push(t)},this)},t.EventEmitter.prototype.removeListener=function(e,t){if(this.hasHandler(e)){var n=this.events[e].indexOf(t);-1!==n&&(this.events[e].splice(n,1),0==this.events[e].length&&delete this.events[e])}},t.EventEmitter.prototype.emit=function(e){if(this.hasHandler(e)){var t=Array.prototype.slice.call(arguments,1);this.events[e].forEach(function(e){e.apply(void 0,t)},this)}},t.EventEmitter.prototype.hasHandler=function(e){return e in this.events},t.tokenizer=function(e){if(!arguments.length||null===e||void 0===e)return[];if(Array.isArray(e)){var n=e.filter(function(e){return null===e||void 0===e?!1:!0});n=n.map(function(e){return t.utils.toString(e).toLowerCase()});var i=[];return n.forEach(function(e){var n=e.split(t.tokenizer.seperator);i=i.concat(n)},this),i}return e.toString().trim().toLowerCase().split(t.tokenizer.seperator)},t.tokenizer.defaultSeperator=/[\s\-]+/,t.tokenizer.seperator=t.tokenizer.defaultSeperator,t.tokenizer.setSeperator=function(e){null!==e&&void 0!==e&&"object"==typeof e&&(t.tokenizer.seperator=e)},t.tokenizer.resetSeperator=function(){t.tokenizer.seperator=t.tokenizer.defaultSeperator},t.tokenizer.getSeperator=function(){return t.tokenizer.seperator},t.Pipeline=function(){this._queue=[]},t.Pipeline.registeredFunctions={},t.Pipeline.registerFunction=function(e,n){n in t.Pipeline.registeredFunctions&&t.utils.warn("Overwriting existing registered function: "+n),e.label=n,t.Pipeline.registeredFunctions[n]=e},t.Pipeline.getRegisteredFunction=function(e){return e in t.Pipeline.registeredFunctions!=!0?null:t.Pipeline.registeredFunctions[e]},t.Pipeline.warnIfFunctionNotRegistered=function(e){var n=e.label&&e.label in this.registeredFunctions;n||t.utils.warn("Function is not registered with pipeline. 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e.elements=this.toArray(),e.length=e.elements.length,e},lunr.SortedSet.prototype.union=function(e){var t,n,i;this.length>=e.length?(t=this,n=e):(t=e,n=this),i=t.clone();for(var o=0,r=n.toArray();ocausy

\n\n

Causal discovery made easy. Causy allows you to use and implement causal discovery algorithms with easy to use, extend and maintain pipelines. It is built based on pytorch which allows you to run the algorithms on CPUs as well as GPUs seamlessly.

\n\n

Learn more at https://causy.dev.

\n"}, "causy.causal_discovery": {"fullname": "causy.causal_discovery", "modulename": "causy.causal_discovery", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint": {"fullname": "causy.causal_discovery.constraint", "modulename": "causy.causal_discovery.constraint", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms": {"fullname": "causy.causal_discovery.constraint.algorithms", "modulename": "causy.causal_discovery.constraint.algorithms", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.AVAILABLE_ALGORITHMS": {"fullname": "causy.causal_discovery.constraint.algorithms.AVAILABLE_ALGORITHMS", "modulename": "causy.causal_discovery.constraint.algorithms", "qualname": "AVAILABLE_ALGORITHMS", "kind": "variable", "doc": "

\n", "default_value": "{'PC': <class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>, 'ParallelPC': <class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>}"}, "causy.causal_discovery.constraint.algorithms.fci": {"fullname": "causy.causal_discovery.constraint.algorithms.fci", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, typing.Generic[~ExtensionType]"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension.GraphAccessMixin", "kind": "class", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin.inducing_path_exists": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin.inducing_path_exists", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension.GraphAccessMixin.inducing_path_exists", "kind": "function", "doc": "

Check if an inducing path from u to v exists.\nAn inducing path from u to v is a directed reference from u to v on which all mediators are colliders.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if an inducing path exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.causal_discovery.constraint.algorithms.pc": {"fullname": "causy.causal_discovery.constraint.algorithms.pc", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.pc.PC_DEFAULT_THRESHOLD": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_DEFAULT_THRESHOLD", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_DEFAULT_THRESHOLD", "kind": "variable", "doc": "

\n", "default_value": "0.05"}, "causy.causal_discovery.constraint.algorithms.pc.PC_ORIENTATION_RULES": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_ORIENTATION_RULES", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_ORIENTATION_RULES", "kind": "variable", "doc": "

\n", "default_value": "[ColliderTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Collider Test', needs_unapplied_actions=True, apply_synchronous=False, conflict_resolution_strategy=<ColliderTestConflictResolutionStrategies.KEEP_FIRST: 'KEEP_FIRST'>, name='causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest'), Loop(pipeline_steps=[NonColliderTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Non-Collider Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest'), FurtherOrientTripleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Further Orient Triple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest'), OrientQuadrupleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Orient Quadruple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest'), FurtherOrientQuadrupleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Further Orient Quadruple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest')], exit_condition=ExitOnNoActions(name='causy.common_pipeline_steps.exit_conditions.ExitOnNoActions'), display_name='Orientation Rules Loop', name='causy.common_pipeline_steps.logic.Loop')]"}, "causy.causal_discovery.constraint.algorithms.pc.PC_GRAPH_UI_EXTENSION": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_GRAPH_UI_EXTENSION", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_GRAPH_UI_EXTENSION", "kind": "variable", "doc": "

\n", "default_value": "GraphUIExtension(edges=[DirectedEdgeUIConfig(edge_type='DIRECTED', default_ui_config=EdgeUIConfig(color='#333', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='correlation', animated=True, label='Direct Effect: ${correlation.toFixed(4)}'), conditional_ui_configs=[ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#f00000', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.LESS: 'LESS'>), ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#0f0fff', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.GREATER: 'GREATER'>)]), UndirectedEdgeUIConfig(edge_type='UNDIRECTED', default_ui_config=EdgeUIConfig(color='#333', width=4, style='solid', marker_start=None, marker_end=None, label_field='direct_effect', animated=False, label='Correlation: ${correlation.toFixed(4)}'), conditional_ui_configs=None)], name='causy.contrib.graph_ui.GraphUIExtension')"}, "causy.causal_discovery.constraint.algorithms.pc.PC_EDGE_TYPES": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_EDGE_TYPES", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_EDGE_TYPES", "kind": "variable", "doc": "

\n", "default_value": "[DIRECTED, UNDIRECTED]"}, "causy.causal_discovery.constraint.algorithms.pc.PC": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.PCClassic": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PCClassic", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PCClassic", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.PCStable": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PCStable", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PCStable", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.ParallelPC": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.ParallelPC", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "ParallelPC", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.independence_tests": {"fullname": "causy.causal_discovery.constraint.independence_tests", "modulename": "causy.causal_discovery.constraint.independence_tests", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.independence_tests.common": {"fullname": "causy.causal_discovery.constraint.independence_tests.common", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.independence_tests.common.logger": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.logger", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.causal_discovery.constraint.independence_tests.common (WARNING)>"}, "causy.causal_discovery.constraint.independence_tests.common.CorrelationCoefficientTest": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.CorrelationCoefficientTest", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "CorrelationCoefficientTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.PartialCorrelationTest": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.PartialCorrelationTest", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "PartialCorrelationTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestMatrix": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestMatrix", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "ExtendedPartialCorrelationTestMatrix", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.partial_correlation_regression": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.partial_correlation_regression", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "partial_correlation_regression", "kind": "function", "doc": "

Compute the partial correlation coefficient between x and y controlling for other variables in z using linear regression.

\n\n

Arguments:\nx, y : torch.Tensor : Variables for which the partial correlation is computed.\nz : torch.Tensor : Other variables used to control for in the partial correlation.

\n\n

Returns:\npartial_corr : torch.Tensor : Partial correlation coefficient between x and y.

\n", "signature": "(x, y, z):", "funcdef": "def"}, "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestLinearRegression": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestLinearRegression", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "ExtendedPartialCorrelationTestLinearRegression", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules": {"fullname": "causy.causal_discovery.constraint.orientation_rules", "modulename": "causy.causal_discovery.constraint.orientation_rules", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.fci": {"fullname": "causy.causal_discovery.constraint.orientation_rules.fci", "modulename": "causy.causal_discovery.constraint.orientation_rules.fci", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.fci.ColliderRuleFCI": {"fullname": "causy.causal_discovery.constraint.orientation_rules.fci.ColliderRuleFCI", "modulename": "causy.causal_discovery.constraint.orientation_rules.fci", "qualname": "ColliderRuleFCI", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.pc.logger": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.logger", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.causal_discovery.constraint.orientation_rules.pc (WARNING)>"}, "causy.causal_discovery.constraint.orientation_rules.pc.filter_unapplied_actions": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.filter_unapplied_actions", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "filter_unapplied_actions", "kind": "function", "doc": "

Filter out actions that have not been applied to the graph yet.

\n\n
Parameters
\n\n
    \n
  • actions: list of actions
    • \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

list of actions that have not been applied to the graph yet

\n
\n", "signature": "(actions, u, v):", "funcdef": "def"}, "causy.causal_discovery.constraint.orientation_rules.pc.generate_restores": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.generate_restores", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "generate_restores", "kind": "function", "doc": "

Generate restore actions for unapplied actions.

\n\n
Parameters
\n\n
    \n
  • unapplied_actions: list of unapplied actions
    • \n
  • x: node x
    • \n
  • y: node y
    • \n
\n\n
Returns
\n\n
\n

list of restore actions

\n
\n", "signature": "(unapplied_actions):", "funcdef": "def"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies", "kind": "class", "doc": "

Enum for the conflict resolution strategies for the ColliderTest.

\n", "bases": "builtins.str, enum.Enum"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_FIRST": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_FIRST", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies.KEEP_FIRST", "kind": "variable", "doc": "

\n", "default_value": "<ColliderTestConflictResolutionStrategies.KEEP_FIRST: 'KEEP_FIRST'>"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_LAST": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_LAST", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies.KEEP_LAST", "kind": "variable", "doc": "

\n", "default_value": "<ColliderTestConflictResolutionStrategies.KEEP_LAST: 'KEEP_LAST'>"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest.conflict_resolution_strategy": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest.conflict_resolution_strategy", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTest.conflict_resolution_strategy", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference]"}, "causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "NonColliderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "FurtherOrientTripleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "OrientQuadrupleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "FurtherOrientQuadrupleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.cli": {"fullname": "causy.cli", "modulename": "causy.cli", "kind": "module", "doc": "

\n"}, "causy.cli.app": {"fullname": "causy.cli.app", "modulename": "causy.cli", "qualname": "app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.cli.eject": {"fullname": "causy.cli.eject", "modulename": "causy.cli", "qualname": "eject", "kind": "function", "doc": "

\n", "signature": "(algorithm: str, output_file: str):", "funcdef": "def"}, "causy.cli.execute": {"fullname": "causy.cli.execute", "modulename": "causy.cli", "qualname": "execute", "kind": "function", "doc": "

\n", "signature": "(\tdata_file: str,\tpipeline: str = None,\talgorithm: str = None,\toutput_file: str = None,\tlog_level: str = 'ERROR'):", "funcdef": "def"}, "causy.common_pipeline_steps": {"fullname": "causy.common_pipeline_steps", "modulename": "causy.common_pipeline_steps", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.calculation": {"fullname": "causy.common_pipeline_steps.calculation", "modulename": "causy.common_pipeline_steps.calculation", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.calculation.CalculatePearsonCorrelations": {"fullname": "causy.common_pipeline_steps.calculation.CalculatePearsonCorrelations", "modulename": "causy.common_pipeline_steps.calculation", "qualname": "CalculatePearsonCorrelations", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.common_pipeline_steps.exit_conditions": {"fullname": "causy.common_pipeline_steps.exit_conditions", "modulename": "causy.common_pipeline_steps.exit_conditions", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.ExitConditionInterface"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.check": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.check", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.check", "kind": "function", "doc": "

Check if there are no actions taken in the last iteration and if so, break the loop\nIf it is the first iteration, do not break the loop (we need to execute the first step)

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • graph_model_instance_: the graph model instance
    • \n
  • actions_taken: the actions taken in the last iteration
    • \n
  • iteration: iteration number
    • \n
\n\n
Returns
\n\n
\n

True if you want to break an iteration, False otherwise

\n
\n", "signature": "(self, graph, graph_model_instance_, actions_taken, iteration) -> bool:", "funcdef": "def"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_config": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_config", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_fields": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_fields", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_computed_fields": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_computed_fields", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.common_pipeline_steps.logic": {"fullname": "causy.common_pipeline_steps.logic", "modulename": "causy.common_pipeline_steps.logic", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.logic.Loop": {"fullname": "causy.common_pipeline_steps.logic.Loop", "modulename": "causy.common_pipeline_steps.logic", "qualname": "Loop", "kind": "class", "doc": "

A loop which executes a list of pipeline_steps until the exit_condition is met.

\n", "bases": "causy.interfaces.LogicStepInterface, typing.Generic[~LogicStepInterfaceType]"}, "causy.common_pipeline_steps.logic.ApplyActionsTogether": {"fullname": "causy.common_pipeline_steps.logic.ApplyActionsTogether", "modulename": "causy.common_pipeline_steps.logic", "qualname": "ApplyActionsTogether", "kind": "class", "doc": "

A logic step which collects all actions and only takes them at the end of the pipeline

\n", "bases": "causy.interfaces.LogicStepInterface, typing.Generic[~LogicStepInterfaceType]"}, "causy.common_pipeline_steps.placeholder": {"fullname": "causy.common_pipeline_steps.placeholder", "modulename": "causy.common_pipeline_steps.placeholder", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.placeholder.logger": {"fullname": "causy.common_pipeline_steps.placeholder.logger", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.common_pipeline_steps.placeholder (WARNING)>"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_str": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_str", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_str", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.StringVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_int": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_int", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_int", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.IntegerVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_float": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_float", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_float", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.FloatVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_bool": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_bool", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_bool", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.BoolVariable]"}, "causy.data_loader": {"fullname": "causy.data_loader", "modulename": "causy.data_loader", "kind": "module", "doc": "

\n"}, "causy.data_loader.DataLoaderType": {"fullname": "causy.data_loader.DataLoaderType", "modulename": "causy.data_loader", "qualname": "DataLoaderType", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.data_loader.DataLoaderType.DYNAMIC": {"fullname": "causy.data_loader.DataLoaderType.DYNAMIC", "modulename": "causy.data_loader", "qualname": "DataLoaderType.DYNAMIC", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.DYNAMIC: 'dynamic'>"}, "causy.data_loader.DataLoaderType.JSON": {"fullname": "causy.data_loader.DataLoaderType.JSON", "modulename": "causy.data_loader", "qualname": "DataLoaderType.JSON", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.JSON: 'json'>"}, "causy.data_loader.DataLoaderType.JSONL": {"fullname": "causy.data_loader.DataLoaderType.JSONL", "modulename": "causy.data_loader", "qualname": "DataLoaderType.JSONL", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.JSONL: 'jsonl'>"}, "causy.data_loader.DataLoaderReference": {"fullname": "causy.data_loader.DataLoaderReference", "modulename": "causy.data_loader", "qualname": "DataLoaderReference", "kind": "class", "doc": "

represents a single data loader

\n\n
Parameters
\n\n
    \n
  • type: the type of dataloader
    • \n
  • reference: path to either the python class which can be executed to load the data or the data source file itself
    • \n
\n", "bases": "pydantic.main.BaseModel"}, "causy.data_loader.DataLoaderReference.type": {"fullname": "causy.data_loader.DataLoaderReference.type", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.type", "kind": "variable", "doc": "

\n", "annotation": ": causy.data_loader.DataLoaderType"}, "causy.data_loader.DataLoaderReference.reference": {"fullname": "causy.data_loader.DataLoaderReference.reference", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.DataLoaderReference.options": {"fullname": "causy.data_loader.DataLoaderReference.options", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.options", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]"}, "causy.data_loader.DataLoaderReference.model_config": {"fullname": "causy.data_loader.DataLoaderReference.model_config", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.data_loader.DataLoaderReference.model_fields": {"fullname": "causy.data_loader.DataLoaderReference.model_fields", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'type': FieldInfo(annotation=DataLoaderType, required=True), 'reference': FieldInfo(annotation=str, required=True), 'options': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None)}"}, "causy.data_loader.DataLoaderReference.model_computed_fields": {"fullname": "causy.data_loader.DataLoaderReference.model_computed_fields", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.data_loader.AbstractDataLoader": {"fullname": "causy.data_loader.AbstractDataLoader", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.data_loader.AbstractDataLoader.reference": {"fullname": "causy.data_loader.AbstractDataLoader.reference", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.AbstractDataLoader.options": {"fullname": "causy.data_loader.AbstractDataLoader.options", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.options", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]", "default_value": "None"}, "causy.data_loader.AbstractDataLoader.load": {"fullname": "causy.data_loader.AbstractDataLoader.load", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.AbstractDataLoader.hash": {"fullname": "causy.data_loader.AbstractDataLoader.hash", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.hash", "kind": "function", "doc": "

returns a hash of the data that is loaded

\n\n
Returns
\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.data_loader.FileDataLoader": {"fullname": "causy.data_loader.FileDataLoader", "modulename": "causy.data_loader", "qualname": "FileDataLoader", "kind": "class", "doc": "

A data loader which loads data from a file reference (e.g. json, csv, etc.)

\n", "bases": "AbstractDataLoader, abc.ABC"}, "causy.data_loader.FileDataLoader.reference": {"fullname": "causy.data_loader.FileDataLoader.reference", "modulename": "causy.data_loader", "qualname": "FileDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.FileDataLoader.options": {"fullname": "causy.data_loader.FileDataLoader.options", "modulename": "causy.data_loader", "qualname": "FileDataLoader.options", "kind": "variable", "doc": "

\n", "default_value": "None"}, "causy.data_loader.FileDataLoader.hash": {"fullname": "causy.data_loader.FileDataLoader.hash", "modulename": "causy.data_loader", "qualname": "FileDataLoader.hash", "kind": "function", "doc": "

returns a hash of the data that is loaded

\n\n
Returns
\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.data_loader.JSONDataLoader": {"fullname": "causy.data_loader.JSONDataLoader", "modulename": "causy.data_loader", "qualname": "JSONDataLoader", "kind": "class", "doc": "

A data loader which loads data from a json file

\n", "bases": "FileDataLoader"}, "causy.data_loader.JSONDataLoader.load": {"fullname": "causy.data_loader.JSONDataLoader.load", "modulename": "causy.data_loader", "qualname": "JSONDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.JSONLDataLoader": {"fullname": "causy.data_loader.JSONLDataLoader", "modulename": "causy.data_loader", "qualname": "JSONLDataLoader", "kind": "class", "doc": "

A data loader which loads data from a jsonl file

\n", "bases": "FileDataLoader"}, "causy.data_loader.JSONLDataLoader.load": {"fullname": "causy.data_loader.JSONLDataLoader.load", "modulename": "causy.data_loader", "qualname": "JSONLDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.DynamicDataLoader": {"fullname": "causy.data_loader.DynamicDataLoader", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader", "kind": "class", "doc": "

A data loader which loads another data loader dynamically based on the reference

\n", "bases": "AbstractDataLoader"}, "causy.data_loader.DynamicDataLoader.reference": {"fullname": "causy.data_loader.DynamicDataLoader.reference", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.DynamicDataLoader.data_loader": {"fullname": "causy.data_loader.DynamicDataLoader.data_loader", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.data_loader", "kind": "variable", "doc": "

\n", "annotation": ": causy.data_loader.AbstractDataLoader"}, "causy.data_loader.DynamicDataLoader.options": {"fullname": "causy.data_loader.DynamicDataLoader.options", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.options", "kind": "variable", "doc": "

\n", "default_value": "None"}, "causy.data_loader.DynamicDataLoader.load": {"fullname": "causy.data_loader.DynamicDataLoader.load", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.DATA_LOADERS": {"fullname": "causy.data_loader.DATA_LOADERS", "modulename": "causy.data_loader", "qualname": "DATA_LOADERS", "kind": "variable", "doc": "

\n", "default_value": "{<DataLoaderType.JSON: 'json'>: <class 'causy.data_loader.JSONDataLoader'>, <DataLoaderType.JSONL: 'jsonl'>: <class 'causy.data_loader.JSONLDataLoader'>, <DataLoaderType.DYNAMIC: 'dynamic'>: <class 'causy.data_loader.DynamicDataLoader'>}"}, "causy.data_loader.load_data_loader": {"fullname": "causy.data_loader.load_data_loader", "modulename": "causy.data_loader", "qualname": "load_data_loader", "kind": "function", "doc": "

loads the data loader based on the reference

\n\n
Parameters
\n\n
    \n
  • reference: a data loader reference
    • \n
\n\n
Returns
\n", "signature": "(\treference: causy.data_loader.DataLoaderReference) -> causy.data_loader.AbstractDataLoader:", "funcdef": "def"}, "causy.edge_types": {"fullname": "causy.edge_types", "modulename": "causy.edge_types", "kind": "module", "doc": "

\n"}, "causy.edge_types.EdgeTypeEnum": {"fullname": "causy.edge_types.EdgeTypeEnum", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.edge_types.EdgeTypeEnum.DIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.DIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.DIRECTED: 'directed'>"}, "causy.edge_types.EdgeTypeEnum.UNDIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.UNDIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.UNDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.UNDIRECTED: 'undirected'>"}, "causy.edge_types.EdgeTypeEnum.BIDIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.BIDIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.BIDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.BIDIRECTED: 'bidirected'>"}, "causy.edge_types.DirectedEdge": {"fullname": "causy.edge_types.DirectedEdge", "modulename": "causy.edge_types", "qualname": "DirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.DirectedEdgeUIConfig": {"fullname": "causy.edge_types.DirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.DirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.DirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.DirectedEdgeUIConfig.conditional_ui_configs": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.conditional_ui_configs", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.conditional_ui_configs", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.contrib.graph_ui.ConditionalEdgeUIConfig]]"}, "causy.edge_types.DirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.DirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='DIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='correlation', animated=True, label='Direct Effect: ${correlation.toFixed(4)}')), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=[ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#f00000', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.LESS: 'LESS'>), ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#0f0fff', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.GREATER: 'GREATER'>)])}"}, "causy.edge_types.DirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.UndirectedEdge": {"fullname": "causy.edge_types.UndirectedEdge", "modulename": "causy.edge_types", "qualname": "UndirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.UndirectedEdgeUIConfig": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.UndirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.UndirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.UndirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.UndirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='UNDIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='solid', marker_start=None, marker_end=None, label_field='direct_effect', animated=False, label='Correlation: ${correlation.toFixed(4)}')), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=None)}"}, "causy.edge_types.UndirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.BiDirectedEdge": {"fullname": "causy.edge_types.BiDirectedEdge", "modulename": "causy.edge_types", "qualname": "BiDirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.BiDirectedEdgeUIConfig": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.BiDirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.BiDirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='BIDIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='solid', marker_start='ArrowClosed', marker_end='ArrowClosed', label_field='direct_effect', animated=False, label=None)), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=None)}"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.EDGE_TYPES": {"fullname": "causy.edge_types.EDGE_TYPES", "modulename": "causy.edge_types", "qualname": "EDGE_TYPES", "kind": "variable", "doc": "

\n", "default_value": "{'DIRECTED': <class 'causy.edge_types.DirectedEdge'>, 'UNDIRECTED': <class 'causy.edge_types.UndirectedEdge'>, 'BIDIRECTED': <class 'causy.edge_types.BiDirectedEdge'>}"}, "causy.generators": {"fullname": "causy.generators", "modulename": "causy.generators", "kind": "module", "doc": "

\n"}, "causy.generators.logger": {"fullname": "causy.generators.logger", "modulename": "causy.generators", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.generators (WARNING)>"}, "causy.generators.AllCombinationsGenerator": {"fullname": "causy.generators.AllCombinationsGenerator", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator", "kind": "class", "doc": "

Generates all combinations of nodes in the graph in accordance with the configured amount of nodes to compare.\nYields node combinations as tuples, but only in one ordering, i.e. mathematically it returns sets.\ne.g. if your graph consists of the nodes [X, Y, Z] and you want to compare 2 nodes,\nit will yield (X, Y), (X, Z), (Y, Z). It will not additionally yield (Y, X), (Z, X), (Z, Y).

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.AllCombinationsGenerator.generate": {"fullname": "causy.generators.AllCombinationsGenerator.generate", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.AllCombinationsGenerator.model_config": {"fullname": "causy.generators.AllCombinationsGenerator.model_config", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.AllCombinationsGenerator.model_fields": {"fullname": "causy.generators.AllCombinationsGenerator.model_fields", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.generators.AllCombinationsGenerator.model_computed_fields": {"fullname": "causy.generators.AllCombinationsGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.PairsWithEdgesInBetweenGenerator": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator", "kind": "class", "doc": "

Generates all pairs of nodes that have edges in between them. It does not matter if the edge is directed or not.\nHowever, if it is an edge which points in both/no directions, it will be iterated over them twice.

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.PairsWithEdgesInBetweenGenerator.__init__": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.__init__", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(\t*args,\tchunk_size: Union[int, causy.variables.VariableReference, NoneType] = None,\tchunked: Union[bool, causy.variables.VariableReference, NoneType] = None,\t**kwargs)"}, "causy.generators.PairsWithEdgesInBetweenGenerator.chunk_size": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.chunk_size", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.chunk_size", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.generators.PairsWithEdgesInBetweenGenerator.chunked": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.chunked", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.generators.PairsWithEdgesInBetweenGenerator.generate": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.generate", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_config": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_config", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_fields": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_fields", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None), 'chunk_size': FieldInfo(annotation=Union[int, VariableReference], required=False, default=100)}"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_computed_fields": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.PairsWithNeighboursGenerator": {"fullname": "causy.generators.PairsWithNeighboursGenerator", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator", "kind": "class", "doc": "

Generates all combinations of pairs of nodes that are neighbours and the neighbours of the first input node.\ne.g. if your graph consists of the nodes [X, Y, Z, W, V] your output could be:\n[X, Y, neighbours(X)], [Y, X, neighbours(Y)], [X, Z, neighbours(X)], [Z, X, neighbours(Z)], ...\n(if, among others, X and Y are neighbours and X and Z are neighbours)

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.PairsWithNeighboursGenerator.__init__": {"fullname": "causy.generators.PairsWithNeighboursGenerator.__init__", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(*args, **kwargs)"}, "causy.generators.PairsWithNeighboursGenerator.shuffle_combinations": {"fullname": "causy.generators.PairsWithNeighboursGenerator.shuffle_combinations", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.shuffle_combinations", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.generators.PairsWithNeighboursGenerator.chunked": {"fullname": "causy.generators.PairsWithNeighboursGenerator.chunked", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.generators.PairsWithNeighboursGenerator.generate": {"fullname": "causy.generators.PairsWithNeighboursGenerator.generate", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.PairsWithNeighboursGenerator.model_config": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_config", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.PairsWithNeighboursGenerator.model_fields": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_fields", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference], required=False, default=True), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference], required=False, default=True)}"}, "causy.generators.PairsWithNeighboursGenerator.model_computed_fields": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.RandomSampleGenerator": {"fullname": "causy.generators.RandomSampleGenerator", "modulename": "causy.generators", "qualname": "RandomSampleGenerator", "kind": "class", "doc": "

Executes another generator and returns a random sample of the results

\n", "bases": "causy.interfaces.GeneratorInterface, pydantic.main.BaseModel"}, "causy.generators.RandomSampleGenerator.__init__": {"fullname": "causy.generators.RandomSampleGenerator.__init__", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(\t*args,\tgenerator: Union[causy.interfaces.GeneratorInterface, Dict[<built-in function any>, <built-in function any>], NoneType] = None,\t**kwargs)"}, "causy.generators.RandomSampleGenerator.every_nth": {"fullname": "causy.generators.RandomSampleGenerator.every_nth", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.every_nth", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.generators.RandomSampleGenerator.generator": {"fullname": "causy.generators.RandomSampleGenerator.generator", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.generators.RandomSampleGenerator.generate": {"fullname": "causy.generators.RandomSampleGenerator.generate", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.generate", "kind": "function", "doc": "

Executes another generator and returns a random sample of the results

\n\n
Parameters
\n\n
    \n
  • graph:
    • \n
  • graph_model_instance_:
    • \n
\n\n
Returns
\n\n
\n

yields a random sample of the results

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.generators.RandomSampleGenerator.model_config": {"fullname": "causy.generators.RandomSampleGenerator.model_config", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.RandomSampleGenerator.model_fields": {"fullname": "causy.generators.RandomSampleGenerator.model_fields", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference], required=False, default=100), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.generators.RandomSampleGenerator.model_computed_fields": {"fullname": "causy.generators.RandomSampleGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.graph": {"fullname": "causy.graph", "modulename": "causy.graph", "kind": "module", "doc": "

\n"}, "causy.graph.logger": {"fullname": "causy.graph.logger", "modulename": "causy.graph", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.graph (WARNING)>"}, "causy.graph.Node": {"fullname": "causy.graph.Node", "modulename": "causy.graph", "qualname": "Node", "kind": "class", "doc": "

A node is a variable in the graph. It has a name, an id and values. The values are stored as a torch.Tensor.\nA node can also have metadata.

\n", "bases": "causy.interfaces.NodeInterface"}, "causy.graph.Node.name": {"fullname": "causy.graph.Node.name", "modulename": "causy.graph", "qualname": "Node.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.graph.Node.id": {"fullname": "causy.graph.Node.id", "modulename": "causy.graph", "qualname": "Node.id", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.graph.Node.values": {"fullname": "causy.graph.Node.values", "modulename": "causy.graph", "qualname": "Node.values", "kind": "variable", "doc": "

\n", "annotation": ": Optional[torch.Tensor]"}, "causy.graph.Node.metadata": {"fullname": "causy.graph.Node.metadata", "modulename": "causy.graph", "qualname": "Node.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]]"}, "causy.graph.Node.model_config": {"fullname": "causy.graph.Node.model_config", "modulename": "causy.graph", "qualname": "Node.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.graph.Node.model_fields": {"fullname": "causy.graph.Node.model_fields", "modulename": "causy.graph", "qualname": "Node.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[Tensor, NoneType], required=False, default=None), 'metadata': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], NoneType], required=False, default=None)}"}, "causy.graph.Node.model_computed_fields": {"fullname": "causy.graph.Node.model_computed_fields", "modulename": "causy.graph", "qualname": "Node.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.Edge": {"fullname": "causy.graph.Edge", "modulename": "causy.graph", "qualname": "Edge", "kind": "class", "doc": "

An edge is a connection between two nodes. It has a direction defined by the edge_type and metadata.\nA metadata example could be the p-value of a statistical test.\nAn edge can be e.g. undirected, directed or bidirected. Which option is available/chosen depends on the algorithm and the current state of the graph.\nBy default an edge always has an undirected and a directed edge_type.

\n", "bases": "causy.interfaces.EdgeInterface"}, "causy.graph.Edge.__init__": {"fullname": "causy.graph.Edge.__init__", "modulename": "causy.graph", "qualname": "Edge.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(*args, **kwargs)"}, "causy.graph.Edge.u": {"fullname": "causy.graph.Edge.u", "modulename": "causy.graph", "qualname": "Edge.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.graph.Edge.v": {"fullname": "causy.graph.Edge.v", "modulename": "causy.graph", "qualname": "Edge.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.graph.Edge.edge_type": {"fullname": "causy.graph.Edge.edge_type", "modulename": "causy.graph", "qualname": "Edge.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.EdgeTypeInterface"}, "causy.graph.Edge.metadata": {"fullname": "causy.graph.Edge.metadata", "modulename": "causy.graph", "qualname": "Edge.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]]"}, "causy.graph.Edge.deleted": {"fullname": "causy.graph.Edge.deleted", "modulename": "causy.graph", "qualname": "Edge.deleted", "kind": "variable", "doc": "

\n", "annotation": ": Optional[bool]"}, "causy.graph.Edge.model_config": {"fullname": "causy.graph.Edge.model_config", "modulename": "causy.graph", "qualname": "Edge.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.graph.Edge.model_fields": {"fullname": "causy.graph.Edge.model_fields", "modulename": "causy.graph", "qualname": "Edge.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'edge_type': FieldInfo(annotation=EdgeTypeInterface, required=True), 'metadata': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], NoneType], required=False, default=None), 'deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False)}"}, "causy.graph.Edge.model_computed_fields": {"fullname": "causy.graph.Edge.model_computed_fields", "modulename": "causy.graph", "qualname": "Edge.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.GraphError": {"fullname": "causy.graph.GraphError", "modulename": "causy.graph", "qualname": "GraphError", "kind": "class", "doc": "

Common base class for all non-exit exceptions.

\n", "bases": "builtins.Exception"}, "causy.graph.GraphBaseAccessMixin": {"fullname": "causy.graph.GraphBaseAccessMixin", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin", "kind": "class", "doc": "

\n"}, "causy.graph.GraphBaseAccessMixin.directed_edge_is_soft_deleted": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_edge_is_soft_deleted", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_edge_is_soft_deleted", "kind": "function", "doc": "

Check if an edge is soft deleted

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.parents_of_node": {"fullname": "causy.graph.GraphBaseAccessMixin.parents_of_node", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.parents_of_node", "kind": "function", "doc": "

Return all parents of a node u

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
\n\n
Returns
\n\n
\n

list of nodes (parents)

\n
\n", "signature": "(self, u: Union[causy.graph.Node, str]):", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_exists", "kind": "function", "doc": "

Check if any edge exists between u and v. Cases: u -> v, u <-> v, u <- v

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if any edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.directed_edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_edge_exists", "kind": "function", "doc": "

Check if a directed edge exists between u and v. Cases: u -> v, u <-> v

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if a directed edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.node_by_id": {"fullname": "causy.graph.GraphBaseAccessMixin.node_by_id", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.node_by_id", "kind": "function", "doc": "

Retrieve a node by its id

\n\n
Parameters
\n\n
    \n
  • id_:
    • \n
\n\n
Returns
\n", "signature": "(self, id_: str) -> Optional[causy.graph.Node]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_value": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_value", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_value", "kind": "function", "doc": "

retrieve the value of an edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> Optional[Dict]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_type": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_type", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_type", "kind": "function", "doc": "

retrieve the value of an edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> Optional[causy.interfaces.EdgeTypeInterface]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.undirected_edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.undirected_edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.undirected_edge_exists", "kind": "function", "doc": "

Check if an undirected edge exists between u and v. Note: currently, an undirected edges is implemented just as\na directed edge. However, they are two functions as they mean different things in different algorithms.\nCurrently, this function is used in the PC algorithm, where an undirected edge is an edge which could not be\noriented in any direction by orientation rules.\nLater, a cohersive naming scheme should be implemented.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if an undirected edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.get_siblings": {"fullname": "causy.graph.GraphBaseAccessMixin.get_siblings", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.get_siblings", "kind": "function", "doc": "

Get the set of nodes that are connected to the node v with an undirected edge.

\n\n
Parameters
\n\n
    \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

A set of nodes that are connected to v with an undirected edge.

\n
\n", "signature": "(\tself,\tv: Union[causy.graph.Node, str]) -> Set[Union[causy.graph.Node, str]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.retrieve_edge_history": {"fullname": "causy.graph.GraphBaseAccessMixin.retrieve_edge_history", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.retrieve_edge_history", "kind": "function", "doc": "

Retrieve the edge history

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • action:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\taction: causy.models.TestResultAction = None) -> List[causy.models.TestResult]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.directed_path_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_path_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_path_exists", "kind": "function", "doc": "

Check if a directed path from u to v exists

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if a directed path exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_of_type_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_of_type_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_of_type_exists", "kind": "function", "doc": "

Check if an edge of a specific type exists between u and v.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
  • edge_type: the type of the edge to check for
    • \n
\n\n
Returns
\n\n
\n

True if an edge of this type exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tedge_type: causy.interfaces.EdgeTypeInterface = DIRECTED) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.descendants_of_node": {"fullname": "causy.graph.GraphBaseAccessMixin.descendants_of_node", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.descendants_of_node", "kind": "function", "doc": "

Returns a list of all descendants of the given node in a directed graph, including the input node itself.

\n\n
Parameters
\n\n
    \n
  • u: The node or node ID to find descendants for.
    • \n
\n\n
Returns
\n\n
\n

A list of descendants of a node including the input node itself.

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tvisited=None) -> List[Union[causy.graph.Node, str]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_dag": {"fullname": "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_dag", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.are_nodes_d_separated_dag", "kind": "function", "doc": "

Check if nodes u and v are d-separated given a conditioning set in a DAG. We check whether there is an open path, i.e. a path on which all colliders are in the conditioning set and all non-colliders are not in the conditioning set. If there is no open path, u and v are d-separated.

\n\n
Parameters
\n\n
    \n
  • u: First node
    • \n
  • v: Second node
    • \n
  • conditioning_set: Set of nodes to condition on
    • \n
\n\n
Returns
\n\n
\n

True if u and v are d-separated given conditioning_set, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tconditioning_set: List[Union[causy.graph.Node, str]]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_cpdag": {"fullname": "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_cpdag", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.are_nodes_d_separated_cpdag", "kind": "function", "doc": "

Check if nodes u and v are d-separated given a conditioning set in a CPDAG following Perkovic, 2020. (Identifying causal effects in maximally oriented partially directed acyclic graphs)

\n\n
Parameters
\n\n
    \n
  • u: First node
    • \n
  • v: Second node
    • \n
  • conditioning_set: Set of nodes to condition on
    • \n
\n\n
Returns
\n\n
\n

True if u and v are d-separated given conditioning_set, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tconditioning_set: List[Union[causy.graph.Node, str]]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph": {"fullname": "causy.graph.GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph", "kind": "function", "doc": "

\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tvisited=None,\tpath=None) -> List[List[causy.graph.Node]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.retrieve_edges": {"fullname": "causy.graph.GraphBaseAccessMixin.retrieve_edges", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.retrieve_edges", "kind": "function", "doc": "

Retrieve all edges

\n\n
Returns
\n\n
\n

all edges

\n
\n", "signature": "(self) -> List[causy.graph.Edge]:", "funcdef": "def"}, "causy.graph.Graph": {"fullname": "causy.graph.Graph", "modulename": "causy.graph", "qualname": "Graph", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "GraphBaseAccessMixin, causy.interfaces.ExtensionInterface.GraphAccessMixin, causy.interfaces.EdgeTypeInterface.GraphAccessMixin, pydantic.main.BaseModel, causy.edge_types.DirectedEdge.GraphAccessMixin"}, "causy.graph.Graph.nodes": {"fullname": "causy.graph.Graph.nodes", "modulename": "causy.graph", "qualname": "Graph.nodes", "kind": "variable", "doc": "

\n", "annotation": ": OrderedDict[str, causy.graph.Node]"}, "causy.graph.Graph.edges": {"fullname": "causy.graph.Graph.edges", "modulename": "causy.graph", "qualname": "Graph.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, causy.graph.Edge]]"}, "causy.graph.Graph.edge_history": {"fullname": "causy.graph.Graph.edge_history", "modulename": "causy.graph", "qualname": "Graph.edge_history", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Tuple[str, str], List[causy.models.TestResult]]"}, "causy.graph.Graph.action_history": {"fullname": "causy.graph.Graph.action_history", "modulename": "causy.graph", "qualname": "Graph.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.models.ActionHistoryStep]"}, "causy.graph.Graph.model_config": {"fullname": "causy.graph.Graph.model_config", "modulename": "causy.graph", "qualname": "Graph.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.Graph.model_post_init": {"fullname": "causy.graph.Graph.model_post_init", "modulename": "causy.graph", "qualname": "Graph.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.graph.Graph.model_fields": {"fullname": "causy.graph.Graph.model_fields", "modulename": "causy.graph", "qualname": "Graph.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'nodes': FieldInfo(annotation=OrderedDict[str, Node], required=False, default=OrderedDict()), 'edges': FieldInfo(annotation=Dict[str, Dict[str, Edge]], required=False, default={}), 'edge_history': FieldInfo(annotation=Dict[Tuple[str, str], List[TestResult]], required=False, default={}), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=False, default=[])}"}, "causy.graph.Graph.model_computed_fields": {"fullname": "causy.graph.Graph.model_computed_fields", "modulename": "causy.graph", "qualname": "Graph.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.GraphManager": {"fullname": "causy.graph.GraphManager", "modulename": "causy.graph", "qualname": "GraphManager", "kind": "class", "doc": "

The graph represents the internal data structure of causy. It is a simple graph with nodes and edges.\nBut it supports to be handled as a directed graph, undirected graph and bidirected graph, which is important to implement different algorithms in different stages.\nIt also stores the history of the actions taken on the graph.

\n", "bases": "GraphBaseAccessMixin, causy.interfaces.BaseGraphInterface"}, "causy.graph.GraphManager.__init__": {"fullname": "causy.graph.GraphManager.__init__", "modulename": "causy.graph", "qualname": "GraphManager.__init__", "kind": "function", "doc": "

\n", "signature": "(graph_class=<class 'causy.graph.Graph'>)"}, "causy.graph.GraphManager.nodes": {"fullname": "causy.graph.GraphManager.nodes", "modulename": "causy.graph", "qualname": "GraphManager.nodes", "kind": "variable", "doc": "

\n", "annotation": ": OrderedDict[str, causy.graph.Node]"}, "causy.graph.GraphManager.edges": {"fullname": "causy.graph.GraphManager.edges", "modulename": "causy.graph", "qualname": "GraphManager.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, causy.graph.Edge]]"}, "causy.graph.GraphManager.edge_history": {"fullname": "causy.graph.GraphManager.edge_history", "modulename": "causy.graph", "qualname": "GraphManager.edge_history", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Tuple[str, str], List[causy.models.TestResult]]"}, "causy.graph.GraphManager.action_history": {"fullname": "causy.graph.GraphManager.action_history", "modulename": "causy.graph", "qualname": "GraphManager.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[Dict[str, List[causy.models.TestResult]]]"}, "causy.graph.GraphManager.graph": {"fullname": "causy.graph.GraphManager.graph", "modulename": "causy.graph", "qualname": "GraphManager.graph", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.graph.Graph]", "default_value": "None"}, "causy.graph.GraphManager.get_edge": {"fullname": "causy.graph.GraphManager.get_edge", "modulename": "causy.graph", "qualname": "GraphManager.get_edge", "kind": "function", "doc": "

Get an edge between two nodes

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n\n
\n

the edge

\n
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node) -> causy.graph.Edge:", "funcdef": "def"}, "causy.graph.GraphManager.add_edge": {"fullname": "causy.graph.GraphManager.add_edge", "modulename": "causy.graph", "qualname": "GraphManager.add_edge", "kind": "function", "doc": "

Add an edge to the graph

\n\n
Parameters
\n\n
    \n
  • edge_type: the type of the edge (e.g. undirected, directed, bidirected)
    • \n
  • u: u node
    • \n
  • v: v node
    • \n
  • metadata: metadata of the edge
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict,\tedge_type: causy.interfaces.EdgeTypeInterface = UNDIRECTED):", "funcdef": "def"}, "causy.graph.GraphManager.add_directed_edge": {"fullname": "causy.graph.GraphManager.add_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.add_directed_edge", "kind": "function", "doc": "

Add a directed edge from u to v to the graph

\n\n
Parameters
\n\n
    \n
  • edge_type:
    • \n
  • u: u node
    • \n
  • v: v node
    • \n
  • metadata: metadata of the edge
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict,\tedge_type: causy.interfaces.EdgeTypeInterface = DIRECTED):", "funcdef": "def"}, "causy.graph.GraphManager.add_edge_history": {"fullname": "causy.graph.GraphManager.add_edge_history", "modulename": "causy.graph", "qualname": "GraphManager.add_edge_history", "kind": "function", "doc": "

Add an action to the edge history

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • action:
    • \n
\n\n
Returns
\n", "signature": "(self, u, v, action: causy.models.TestResult):", "funcdef": "def"}, "causy.graph.GraphManager.remove_edge": {"fullname": "causy.graph.GraphManager.remove_edge", "modulename": "causy.graph", "qualname": "GraphManager.remove_edge", "kind": "function", "doc": "

Remove an edge from the graph (undirected)

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tsoft_delete: bool = False):", "funcdef": "def"}, "causy.graph.GraphManager.restore_edge": {"fullname": "causy.graph.GraphManager.restore_edge", "modulename": "causy.graph", "qualname": "GraphManager.restore_edge", "kind": "function", "doc": "

Restore a deleted edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node):", "funcdef": "def"}, "causy.graph.GraphManager.remove_directed_edge": {"fullname": "causy.graph.GraphManager.remove_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.remove_directed_edge", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • soft_delete: does not remove the edge, but marks it as deleted (useful in multithreading)
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tsoft_delete: bool = False):", "funcdef": "def"}, "causy.graph.GraphManager.restore_directed_edge": {"fullname": "causy.graph.GraphManager.restore_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.restore_directed_edge", "kind": "function", "doc": "

Restore a soft deleted edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node):", "funcdef": "def"}, "causy.graph.GraphManager.update_edge": {"fullname": "causy.graph.GraphManager.update_edge", "modulename": "causy.graph", "qualname": "GraphManager.update_edge", "kind": "function", "doc": "

Update an undirected edge in the graph

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
  • value:
    • \n
  • edge_type:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict = None,\tedge_type: causy.interfaces.EdgeTypeInterface = None):", "funcdef": "def"}, "causy.graph.GraphManager.update_directed_edge": {"fullname": "causy.graph.GraphManager.update_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.update_directed_edge", "kind": "function", "doc": "

Update an edge in the graph

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict = None,\tedge_type: causy.interfaces.EdgeTypeInterface = None):", "funcdef": "def"}, "causy.graph.GraphManager.purge_soft_deleted_edges": {"fullname": "causy.graph.GraphManager.purge_soft_deleted_edges", "modulename": "causy.graph", "qualname": "GraphManager.purge_soft_deleted_edges", "kind": "function", "doc": "

Remove all edges that are marked as soft deleted from the graph

\n", "signature": "(self):", "funcdef": "def"}, "causy.graph.GraphManager.add_node": {"fullname": "causy.graph.GraphManager.add_node", "modulename": "causy.graph", "qualname": "GraphManager.add_node", "kind": "function", "doc": "

Add a node to the graph

\n\n
Parameters
\n\n
    \n
  • metadata: add metadata to the node
    • \n
  • name: name of the node
    • \n
  • values: values of the node
    • \n
  • id_: id_ of the node\n:param : node
    • \n
\n\n
Returns
\n\n
\n

created Node

\n
\n", "signature": "(\tself,\tname: str,\tvalues: Union[List[float], torch.Tensor],\tid_: str = None,\tmetadata: Optional[Dict[str, Any]] = None) -> causy.graph.Node:", "funcdef": "def"}, "causy.graph_model": {"fullname": "causy.graph_model", "modulename": "causy.graph_model", "kind": "module", "doc": "

\n"}, "causy.graph_model.logger": {"fullname": "causy.graph_model.logger", "modulename": "causy.graph_model", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.graph_model (WARNING)>"}, "causy.graph_model.AbstractGraphModel": {"fullname": "causy.graph_model.AbstractGraphModel", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel", "kind": "class", "doc": "

The graph model is the main class of causy. It is responsible for creating a graph from data and executing the pipeline_steps.

\n\n

The graph model is responsible for the following tasks:

\n\n
    \n
  • Create a graph from data (create_graph_from_data)
    • \n
  • Execute the pipeline_steps (execute_pipeline_steps)
    • \n
  • Take actions on the graph (execute_pipeline_step & _take_action which is called by execute_pipeline_step)
    • \n
\n\n

It also initializes and takes care of the multiprocessing pool.

\n", "bases": "causy.interfaces.GraphModelInterface, abc.ABC"}, "causy.graph_model.AbstractGraphModel.__init__": {"fullname": "causy.graph_model.AbstractGraphModel.__init__", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.__init__", "kind": "function", "doc": "

\n", "signature": "(graph=None, algorithm: causy.models.Algorithm = None)"}, "causy.graph_model.AbstractGraphModel.algorithm": {"fullname": "causy.graph_model.AbstractGraphModel.algorithm", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.algorithm", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.Algorithm"}, "causy.graph_model.AbstractGraphModel.pipeline_steps": {"fullname": "causy.graph_model.AbstractGraphModel.pipeline_steps", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.interfaces.PipelineStepInterface]"}, "causy.graph_model.AbstractGraphModel.graph": {"fullname": "causy.graph_model.AbstractGraphModel.graph", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.graph", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.BaseGraphInterface"}, "causy.graph_model.AbstractGraphModel.pool": {"fullname": "causy.graph_model.AbstractGraphModel.pool", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.pool", "kind": "variable", "doc": "

\n", "annotation": ": <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7eff2b8dd7f0>>"}, "causy.graph_model.AbstractGraphModel.create_graph_from_data": {"fullname": "causy.graph_model.AbstractGraphModel.create_graph_from_data", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.create_graph_from_data", "kind": "function", "doc": "

Create a graph from data

\n\n
Parameters
\n\n
    \n
  • data: is a list of dictionaries or a dictionary with lists
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tdata: Union[List[Dict[str, float]], Dict[str, List[float]], causy.data_loader.AbstractDataLoader]):", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.create_all_possible_edges": {"fullname": "causy.graph_model.AbstractGraphModel.create_all_possible_edges", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.create_all_possible_edges", "kind": "function", "doc": "

Create all possible edges on a graph\nTODO: replace me with the skeleton builders

\n\n
Returns
\n", "signature": "(self):", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_steps": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_steps", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_steps", "kind": "function", "doc": "

Execute all pipeline_steps

\n\n
Returns
\n\n
\n

the steps taken during the step execution

\n
\n", "signature": "(self) -> List[causy.models.ActionHistoryStep]:", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_step_with_progress": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_step_with_progress", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_step_with_progress", "kind": "function", "doc": "

\n", "signature": "(self) -> Generator:", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_step": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_step", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_step", "kind": "function", "doc": "

Execute a single pipeline_step on the graph. either in parallel or in a single process depending on the test_fn.parallel flag

\n\n
Parameters
\n\n
    \n
  • apply_to_graph: if the action should be applied to the graph
    • \n
  • test_fn: the test function
    • \n
  • threshold: the threshold
    • \n
\n\n
Returns
\n", "signature": "(\tself,\ttest_fn: causy.interfaces.PipelineStepInterface,\tapply_to_graph=True) -> Tuple[List[causy.models.TestResultAction], List[causy.models.TestResultAction]]:", "funcdef": "def"}, "causy.graph_model.graph_model_factory": {"fullname": "causy.graph_model.graph_model_factory", "modulename": "causy.graph_model", "qualname": "graph_model_factory", "kind": "function", "doc": "

Create a graph model based on a List of pipeline_steps

\n\n
Parameters
\n\n
    \n
  • algorithm: the algorithm which should be used to create the graph model
    • \n
\n\n
Returns
\n\n
\n

the graph model

\n
\n", "signature": "(\talgorithm: causy.models.Algorithm = None,\tvariables: Dict[str, causy.variables.VariableTypes] = None) -> type[causy.graph_model.AbstractGraphModel]:", "funcdef": "def"}, "causy.graph_utils": {"fullname": "causy.graph_utils", "modulename": "causy.graph_utils", "kind": "module", "doc": "

\n"}, "causy.graph_utils.unpack_run": {"fullname": "causy.graph_utils.unpack_run", "modulename": "causy.graph_utils", "qualname": "unpack_run", "kind": "function", "doc": "

\n", "signature": "(args):", "funcdef": "def"}, "causy.graph_utils.serialize_module_name": {"fullname": "causy.graph_utils.serialize_module_name", "modulename": "causy.graph_utils", "qualname": "serialize_module_name", "kind": "function", "doc": "

\n", "signature": "(cls):", "funcdef": "def"}, "causy.graph_utils.load_pipeline_artefact_by_definition": {"fullname": "causy.graph_utils.load_pipeline_artefact_by_definition", "modulename": "causy.graph_utils", "qualname": "load_pipeline_artefact_by_definition", "kind": "function", "doc": "

\n", "signature": "(step):", "funcdef": "def"}, "causy.graph_utils.load_pipeline_steps_by_definition": {"fullname": "causy.graph_utils.load_pipeline_steps_by_definition", "modulename": "causy.graph_utils", "qualname": "load_pipeline_steps_by_definition", "kind": "function", "doc": "

\n", "signature": "(steps):", "funcdef": "def"}, "causy.graph_utils.retrieve_edges": {"fullname": "causy.graph_utils.retrieve_edges", "modulename": "causy.graph_utils", "qualname": "retrieve_edges", "kind": "function", "doc": "

Returns a list of edges from the graph

\n\n
Parameters
\n\n
    \n
  • graph: a graph
    • \n
\n\n
Returns
\n\n
\n

a list of edges

\n
\n", "signature": "(graph) -> List[Tuple[str, str]]:", "funcdef": "def"}, "causy.graph_utils.hash_dictionary": {"fullname": "causy.graph_utils.hash_dictionary", "modulename": "causy.graph_utils", "qualname": "hash_dictionary", "kind": "function", "doc": "

Hash a dictionary using SHA256 (e.g. for caching)

\n\n
Parameters
\n\n
    \n
  • dct:
    • \n
\n\n
Returns
\n", "signature": "(dct: Dict):", "funcdef": "def"}, "causy.interfaces": {"fullname": "causy.interfaces", "modulename": "causy.interfaces", "kind": "module", "doc": "

\n"}, "causy.interfaces.logger": {"fullname": "causy.interfaces.logger", "modulename": "causy.interfaces", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.interfaces (WARNING)>"}, "causy.interfaces.DEFAULT_THRESHOLD": {"fullname": "causy.interfaces.DEFAULT_THRESHOLD", "modulename": "causy.interfaces", "qualname": "DEFAULT_THRESHOLD", "kind": "variable", "doc": "

\n", "default_value": "0.01"}, "causy.interfaces.AS_MANY_AS_FIELDS": {"fullname": "causy.interfaces.AS_MANY_AS_FIELDS", "modulename": "causy.interfaces", "qualname": "AS_MANY_AS_FIELDS", "kind": "variable", "doc": "

\n", "default_value": "0"}, "causy.interfaces.MetadataBaseType": {"fullname": "causy.interfaces.MetadataBaseType", "modulename": "causy.interfaces", "qualname": "MetadataBaseType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool]"}, "causy.interfaces.MetadataType": {"fullname": "causy.interfaces.MetadataType", "modulename": "causy.interfaces", "qualname": "MetadataType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool, typing.List[typing.Union[str, int, float, bool]], typing.Dict[str, typing.Union[str, int, float, bool]]]"}, "causy.interfaces.ComparisonSettingsInterface": {"fullname": "causy.interfaces.ComparisonSettingsInterface", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.ComparisonSettingsInterface.min": {"fullname": "causy.interfaces.ComparisonSettingsInterface.min", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.min", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.ComparisonSettingsInterface.max": {"fullname": "causy.interfaces.ComparisonSettingsInterface.max", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.max", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.ComparisonSettingsInterface.name": {"fullname": "causy.interfaces.ComparisonSettingsInterface.name", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ComparisonSettingsInterface.model_config": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_config", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ComparisonSettingsInterface.model_fields": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_fields", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'min': FieldInfo(annotation=Union[int, VariableReference], required=True), 'max': FieldInfo(annotation=Union[int, VariableReference], required=True)}"}, "causy.interfaces.ComparisonSettingsInterface.model_computed_fields": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.NodeInterface": {"fullname": "causy.interfaces.NodeInterface", "modulename": "causy.interfaces", "qualname": "NodeInterface", "kind": "class", "doc": "

Node interface for the graph. A node is defined by a name and a value.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.NodeInterface.name": {"fullname": "causy.interfaces.NodeInterface.name", "modulename": "causy.interfaces", "qualname": "NodeInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.NodeInterface.id": {"fullname": "causy.interfaces.NodeInterface.id", "modulename": "causy.interfaces", "qualname": "NodeInterface.id", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.NodeInterface.values": {"fullname": "causy.interfaces.NodeInterface.values", "modulename": "causy.interfaces", "qualname": "NodeInterface.values", "kind": "variable", "doc": "

\n", "annotation": ": Annotated[Optional[torch.DoubleTensor], WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)]"}, "causy.interfaces.NodeInterface.Config": {"fullname": "causy.interfaces.NodeInterface.Config", "modulename": "causy.interfaces", "qualname": "NodeInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.NodeInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.NodeInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "NodeInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.NodeInterface.model_config": {"fullname": "causy.interfaces.NodeInterface.model_config", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.NodeInterface.model_fields": {"fullname": "causy.interfaces.NodeInterface.model_fields", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[DoubleTensor, NoneType], required=False, default=None, exclude=True, metadata=[WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)])}"}, "causy.interfaces.NodeInterface.model_computed_fields": {"fullname": "causy.interfaces.NodeInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.EdgeTypeInterface": {"fullname": "causy.interfaces.EdgeTypeInterface", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.interfaces.EdgeTypeInterface.name": {"fullname": "causy.interfaces.EdgeTypeInterface.name", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.EdgeTypeInterface.IS_DIRECTED": {"fullname": "causy.interfaces.EdgeTypeInterface.IS_DIRECTED", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.IS_DIRECTED", "kind": "variable", "doc": "

\n", "annotation": ": bool"}, "causy.interfaces.EdgeTypeInterface.STR_REPRESENTATION": {"fullname": "causy.interfaces.EdgeTypeInterface.STR_REPRESENTATION", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.STR_REPRESENTATION", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.EdgeTypeInterface.GraphAccessMixin": {"fullname": "causy.interfaces.EdgeTypeInterface.GraphAccessMixin", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.GraphAccessMixin", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.EdgeTypeInterface.pre_edge_remove_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_remove_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_remove_hook", "kind": "function", "doc": "

Hook that is executed before an edge is deleted.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_remove_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_remove_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_remove_hook", "kind": "function", "doc": "

Hook that is executed after an edge is deleted.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_add_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_add_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_add_hook", "kind": "function", "doc": "

Hook that is executed before an edge is added.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_add_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_add_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_add_hook", "kind": "function", "doc": "

Hook that is executed after an edge is added.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_update_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_update_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_update_hook", "kind": "function", "doc": "

Hook that is executed before an edge is updated.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_update_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_update_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_update_hook", "kind": "function", "doc": "

Hook that is executed after an edge is updated.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_type_change_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_type_change_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_type_change_hook", "kind": "function", "doc": "

Hook that is executed before an edge type is changed.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_type_change_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_type_change_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_type_change_hook", "kind": "function", "doc": "

Hook that is executed after an edge type is changed.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeInterface": {"fullname": "causy.interfaces.EdgeInterface", "modulename": "causy.interfaces", "qualname": "EdgeInterface", "kind": "class", "doc": "

Edge interface for the graph\nA graph edge is defined by two nodes and an edge type. It can also have metadata.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.EdgeInterface.u": {"fullname": "causy.interfaces.EdgeInterface.u", "modulename": "causy.interfaces", "qualname": "EdgeInterface.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.EdgeInterface.v": {"fullname": "causy.interfaces.EdgeInterface.v", "modulename": "causy.interfaces", "qualname": "EdgeInterface.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.EdgeInterface.edge_type": {"fullname": "causy.interfaces.EdgeInterface.edge_type", "modulename": "causy.interfaces", "qualname": "EdgeInterface.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.EdgeTypeInterface"}, "causy.interfaces.EdgeInterface.metadata": {"fullname": "causy.interfaces.EdgeInterface.metadata", "modulename": "causy.interfaces", "qualname": "EdgeInterface.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]"}, "causy.interfaces.EdgeInterface.Config": {"fullname": "causy.interfaces.EdgeInterface.Config", "modulename": "causy.interfaces", "qualname": "EdgeInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.EdgeInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.EdgeInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "EdgeInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.EdgeInterface.is_connection_between_same_nodes": {"fullname": "causy.interfaces.EdgeInterface.is_connection_between_same_nodes", "modulename": "causy.interfaces", "qualname": "EdgeInterface.is_connection_between_same_nodes", "kind": "function", "doc": "

\n", "signature": "(self, edge):", "funcdef": "def"}, "causy.interfaces.EdgeInterface.model_config": {"fullname": "causy.interfaces.EdgeInterface.model_config", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.EdgeInterface.model_fields": {"fullname": "causy.interfaces.EdgeInterface.model_fields", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'edge_type': FieldInfo(annotation=EdgeTypeInterface, required=True), 'metadata': FieldInfo(annotation=Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], required=False, default=None)}"}, "causy.interfaces.EdgeInterface.model_computed_fields": {"fullname": "causy.interfaces.EdgeInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.TestResultInterface": {"fullname": "causy.interfaces.TestResultInterface", "modulename": "causy.interfaces", "qualname": "TestResultInterface", "kind": "class", "doc": "

Test result interface for the graph\nA test result is defined by two nodes and an action. It can also have metadata.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.TestResultInterface.u": {"fullname": "causy.interfaces.TestResultInterface.u", "modulename": "causy.interfaces", "qualname": "TestResultInterface.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.TestResultInterface.v": {"fullname": "causy.interfaces.TestResultInterface.v", "modulename": "causy.interfaces", "qualname": "TestResultInterface.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.TestResultInterface.action": {"fullname": "causy.interfaces.TestResultInterface.action", "modulename": "causy.interfaces", "qualname": "TestResultInterface.action", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.TestResultInterface.data": {"fullname": "causy.interfaces.TestResultInterface.data", "modulename": "causy.interfaces", "qualname": "TestResultInterface.data", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict]"}, "causy.interfaces.TestResultInterface.Config": {"fullname": "causy.interfaces.TestResultInterface.Config", "modulename": "causy.interfaces", "qualname": "TestResultInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.TestResultInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.TestResultInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "TestResultInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.TestResultInterface.model_config": {"fullname": "causy.interfaces.TestResultInterface.model_config", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.TestResultInterface.model_fields": {"fullname": "causy.interfaces.TestResultInterface.model_fields", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'action': FieldInfo(annotation=str, required=True), 'data': FieldInfo(annotation=Union[Dict, NoneType], required=False, default=None)}"}, "causy.interfaces.TestResultInterface.model_computed_fields": {"fullname": "causy.interfaces.TestResultInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.BaseGraphInterface": {"fullname": "causy.interfaces.BaseGraphInterface", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.BaseGraphInterface.nodes": {"fullname": "causy.interfaces.BaseGraphInterface.nodes", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, causy.interfaces.NodeInterface]"}, "causy.interfaces.BaseGraphInterface.edges": {"fullname": "causy.interfaces.BaseGraphInterface.edges", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, Dict]]"}, "causy.interfaces.BaseGraphInterface.retrieve_edge_history": {"fullname": "causy.interfaces.BaseGraphInterface.retrieve_edge_history", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.retrieve_edge_history", "kind": "function", "doc": "

\n", "signature": "(self, u, v, action: str) -> List[causy.interfaces.TestResultInterface]:", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_edge_history": {"fullname": "causy.interfaces.BaseGraphInterface.add_edge_history", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_edge_history", "kind": "function", "doc": "

\n", "signature": "(self, u, v, action: causy.interfaces.TestResultInterface):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_edge": {"fullname": "causy.interfaces.BaseGraphInterface.add_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.remove_edge": {"fullname": "causy.interfaces.BaseGraphInterface.remove_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.remove_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.remove_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.remove_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.remove_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.update_edge": {"fullname": "causy.interfaces.BaseGraphInterface.update_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.update_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata=None, edge_type=None):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.update_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.update_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.update_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata=None, edge_type=None):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_node": {"fullname": "causy.interfaces.BaseGraphInterface.add_node", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_node", "kind": "function", "doc": "

\n", "signature": "(self, name, values) -> causy.interfaces.NodeInterface:", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.edge_value": {"fullname": "causy.interfaces.BaseGraphInterface.edge_value", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edge_value", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.undirected_edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.undirected_edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.undirected_edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.directed_edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.directed_edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.directed_edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v, ignore_soft_deleted=False):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.restore_edge": {"fullname": "causy.interfaces.BaseGraphInterface.restore_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.restore_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.restore_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.restore_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.restore_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface": {"fullname": "causy.interfaces.GraphModelInterface", "modulename": "causy.interfaces", "qualname": "GraphModelInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.GraphModelInterface.pool": {"fullname": "causy.interfaces.GraphModelInterface.pool", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.pool", "kind": "variable", "doc": "

\n", "annotation": ": <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7eff2b8dd7f0>>"}, "causy.interfaces.GraphModelInterface.create_graph_from_data": {"fullname": "causy.interfaces.GraphModelInterface.create_graph_from_data", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.create_graph_from_data", "kind": "function", "doc": "

\n", "signature": "(self, data: List[Dict]):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface.execute_pipeline_steps": {"fullname": "causy.interfaces.GraphModelInterface.execute_pipeline_steps", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.execute_pipeline_steps", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface.execute_pipeline_step": {"fullname": "causy.interfaces.GraphModelInterface.execute_pipeline_step", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.execute_pipeline_step", "kind": "function", "doc": "

\n", "signature": "(self, step, apply_to_graph: bool = True):", "funcdef": "def"}, "causy.interfaces.GeneratorInterface": {"fullname": "causy.interfaces.GeneratorInterface", "modulename": "causy.interfaces", "qualname": "GeneratorInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel"}, "causy.interfaces.GeneratorInterface.comparison_settings": {"fullname": "causy.interfaces.GeneratorInterface.comparison_settings", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.comparison_settings", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.ComparisonSettingsInterface]"}, "causy.interfaces.GeneratorInterface.chunked": {"fullname": "causy.interfaces.GeneratorInterface.chunked", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.every_nth": {"fullname": "causy.interfaces.GeneratorInterface.every_nth", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.every_nth", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.generator": {"fullname": "causy.interfaces.GeneratorInterface.generator", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.interfaces.GeneratorInterface.shuffle_combinations": {"fullname": "causy.interfaces.GeneratorInterface.shuffle_combinations", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.shuffle_combinations", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.generate": {"fullname": "causy.interfaces.GeneratorInterface.generate", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.interfaces.GeneratorInterface.name": {"fullname": "causy.interfaces.GeneratorInterface.name", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.GeneratorInterface.model_config": {"fullname": "causy.interfaces.GeneratorInterface.model_config", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GeneratorInterface.model_fields": {"fullname": "causy.interfaces.GeneratorInterface.model_fields", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.interfaces.GeneratorInterface.model_computed_fields": {"fullname": "causy.interfaces.GeneratorInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.PipelineStepInterface": {"fullname": "causy.interfaces.PipelineStepInterface", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~PipelineStepInterfaceType]"}, "causy.interfaces.PipelineStepInterface.generator": {"fullname": "causy.interfaces.PipelineStepInterface.generator", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.interfaces.PipelineStepInterface.threshold": {"fullname": "causy.interfaces.PipelineStepInterface.threshold", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.threshold", "kind": "variable", "doc": "

\n", "annotation": ": Union[float, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.chunk_size_parallel_processing": {"fullname": "causy.interfaces.PipelineStepInterface.chunk_size_parallel_processing", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.chunk_size_parallel_processing", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.PipelineStepInterface.parallel": {"fullname": "causy.interfaces.PipelineStepInterface.parallel", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.parallel", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.interfaces.PipelineStepInterface.display_name": {"fullname": "causy.interfaces.PipelineStepInterface.display_name", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.display_name", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.needs_unapplied_actions": {"fullname": "causy.interfaces.PipelineStepInterface.needs_unapplied_actions", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.needs_unapplied_actions", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.apply_synchronous": {"fullname": "causy.interfaces.PipelineStepInterface.apply_synchronous", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.apply_synchronous", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.name": {"fullname": "causy.interfaces.PipelineStepInterface.name", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.PipelineStepInterface.process": {"fullname": "causy.interfaces.PipelineStepInterface.process", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.process", "kind": "function", "doc": "

Test if u and v are independent

\n\n
Parameters
\n\n
    \n
  • u: u values
    • \n
  • v: v values
    • \n
\n\n
Returns
\n\n
\n

True if independent, False otherwise

\n
\n", "signature": "(\tself,\tnodes: List[str],\tgraph: causy.interfaces.BaseGraphInterface,\tunapplied_actions: Optional[List[causy.interfaces.TestResultInterface]] = None) -> Optional[causy.interfaces.TestResultInterface]:", "funcdef": "def"}, "causy.interfaces.ExitConditionInterface": {"fullname": "causy.interfaces.ExitConditionInterface", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel"}, "causy.interfaces.ExitConditionInterface.check": {"fullname": "causy.interfaces.ExitConditionInterface.check", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.check", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • graph:
    • \n
  • graph_model_instance_:
    • \n
  • actions_taken:
    • \n
  • iteration:
    • \n
\n\n
Returns
\n\n
\n

True if you want to break an iteration, False otherwise

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface,\tactions_taken: List[causy.interfaces.TestResultInterface],\titeration: Union[int, causy.variables.VariableReference]) -> bool:", "funcdef": "def"}, "causy.interfaces.ExitConditionInterface.name": {"fullname": "causy.interfaces.ExitConditionInterface.name", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExitConditionInterface.model_config": {"fullname": "causy.interfaces.ExitConditionInterface.model_config", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ExitConditionInterface.model_fields": {"fullname": "causy.interfaces.ExitConditionInterface.model_fields", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ExitConditionInterface.model_computed_fields": {"fullname": "causy.interfaces.ExitConditionInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.LogicStepInterface": {"fullname": "causy.interfaces.LogicStepInterface", "modulename": "causy.interfaces", "qualname": "LogicStepInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~LogicStepInterfaceType]"}, "causy.interfaces.LogicStepInterface.pipeline_steps": {"fullname": "causy.interfaces.LogicStepInterface.pipeline_steps", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~PipelineStepInterfaceType]]"}, "causy.interfaces.LogicStepInterface.exit_condition": {"fullname": "causy.interfaces.LogicStepInterface.exit_condition", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.exit_condition", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.ExitConditionInterface]"}, "causy.interfaces.LogicStepInterface.display_name": {"fullname": "causy.interfaces.LogicStepInterface.display_name", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.display_name", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.LogicStepInterface.execute": {"fullname": "causy.interfaces.LogicStepInterface.execute", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.execute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.interfaces.LogicStepInterface.name": {"fullname": "causy.interfaces.LogicStepInterface.name", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExtensionInterface": {"fullname": "causy.interfaces.ExtensionInterface", "modulename": "causy.interfaces", "qualname": "ExtensionInterface", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, typing.Generic[~ExtensionType]"}, "causy.interfaces.ExtensionInterface.name": {"fullname": "causy.interfaces.ExtensionInterface.name", "modulename": "causy.interfaces", "qualname": "ExtensionInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExtensionInterface.GraphAccessMixin": {"fullname": "causy.interfaces.ExtensionInterface.GraphAccessMixin", "modulename": "causy.interfaces", "qualname": "ExtensionInterface.GraphAccessMixin", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.GraphUpdateHook": {"fullname": "causy.interfaces.GraphUpdateHook", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook", "kind": "class", "doc": "

A hook that is executed before or after the graph is updated. This can be used to modify the graph before or after an update.

\n", "bases": "pydantic.main.BaseModel"}, "causy.interfaces.GraphUpdateHook.execute": {"fullname": "causy.interfaces.GraphUpdateHook.execute", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.execute", "kind": "function", "doc": "

Execute the hook.

\n\n
Parameters
\n\n
    \n
  • graph: current state of the graph.
    • \n
  • updates: the planned/taken actions
    • \n
\n\n
Returns
\n\n
\n

A list of updates that should be applied to the graph if it is a pre hook. If it is a post hook, it should return None.

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tupdates: List[causy.interfaces.TestResultInterface]) -> Optional[List[causy.interfaces.TestResultInterface]]:", "funcdef": "def"}, "causy.interfaces.GraphUpdateHook.model_config": {"fullname": "causy.interfaces.GraphUpdateHook.model_config", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GraphUpdateHook.model_fields": {"fullname": "causy.interfaces.GraphUpdateHook.model_fields", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GraphUpdateHook.model_computed_fields": {"fullname": "causy.interfaces.GraphUpdateHook.model_computed_fields", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.math_utils": {"fullname": "causy.math_utils", "modulename": "causy.math_utils", "kind": "module", "doc": "

\n"}, "causy.math_utils.logger": {"fullname": "causy.math_utils.logger", "modulename": "causy.math_utils", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.math_utils (WARNING)>"}, "causy.math_utils.sum_lists": {"fullname": "causy.math_utils.sum_lists", "modulename": "causy.math_utils", "qualname": "sum_lists", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • lists: lists of numbers
    • \n
\n\n
Returns
\n\n
\n

list (sum of lists)

\n
\n", "signature": "(*lists):", "funcdef": "def"}, "causy.math_utils.get_t_and_critical_t": {"fullname": "causy.math_utils.get_t_and_critical_t", "modulename": "causy.math_utils", "qualname": "get_t_and_critical_t", "kind": "function", "doc": "

\n", "signature": "(sample_size, nb_of_control_vars, par_corr, threshold):", "funcdef": "def"}, "causy.models": {"fullname": "causy.models", "modulename": "causy.models", "kind": "module", "doc": "

\n"}, "causy.models.ComparisonSettings": {"fullname": "causy.models.ComparisonSettings", "modulename": "causy.models", "qualname": "ComparisonSettings", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.interfaces.ComparisonSettingsInterface"}, "causy.models.ComparisonSettings.min": {"fullname": "causy.models.ComparisonSettings.min", "modulename": "causy.models", "qualname": "ComparisonSettings.min", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.models.ComparisonSettings.max": {"fullname": "causy.models.ComparisonSettings.max", "modulename": "causy.models", "qualname": "ComparisonSettings.max", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.models.ComparisonSettings.name": {"fullname": "causy.models.ComparisonSettings.name", "modulename": "causy.models", "qualname": "ComparisonSettings.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.ComparisonSettings.model_config": {"fullname": "causy.models.ComparisonSettings.model_config", "modulename": "causy.models", "qualname": "ComparisonSettings.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ComparisonSettings.model_fields": {"fullname": "causy.models.ComparisonSettings.model_fields", "modulename": "causy.models", "qualname": "ComparisonSettings.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'min': FieldInfo(annotation=Union[int, VariableReference], required=False, default=2), 'max': FieldInfo(annotation=Union[int, VariableReference], required=False, default=0)}"}, "causy.models.ComparisonSettings.model_computed_fields": {"fullname": "causy.models.ComparisonSettings.model_computed_fields", "modulename": "causy.models", "qualname": "ComparisonSettings.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.models.TestResultAction": {"fullname": "causy.models.TestResultAction", "modulename": "causy.models", "qualname": "TestResultAction", "kind": "class", "doc": "

Actions that can be taken on the graph. These actions are used to keep track of the history of the graph.

\n", "bases": "builtins.str, enum.Enum"}, "causy.models.TestResultAction.UPDATE_EDGE": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE: 'UPDATE_EDGE'>"}, "causy.models.TestResultAction.UPDATE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_DIRECTED: 'UPDATE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.UPDATE_EDGE_TYPE": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_TYPE", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_TYPE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_TYPE: 'UPDATE_EDGE_TYPE'>"}, "causy.models.TestResultAction.UPDATE_EDGE_TYPE_DIRECTED": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_TYPE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_TYPE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_TYPE_DIRECTED: 'UPDATE_EDGE_TYPE_DIRECTED'>"}, "causy.models.TestResultAction.REMOVE_EDGE_UNDIRECTED": {"fullname": "causy.models.TestResultAction.REMOVE_EDGE_UNDIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.REMOVE_EDGE_UNDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.REMOVE_EDGE_UNDIRECTED: 'REMOVE_EDGE_UNDIRECTED'>"}, "causy.models.TestResultAction.REMOVE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.REMOVE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.REMOVE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.REMOVE_EDGE_DIRECTED: 'REMOVE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.RESTORE_EDGE": {"fullname": "causy.models.TestResultAction.RESTORE_EDGE", "modulename": "causy.models", "qualname": "TestResultAction.RESTORE_EDGE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.RESTORE_EDGE: 'RESTORE_EDGE'>"}, "causy.models.TestResultAction.RESTORE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.RESTORE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.RESTORE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.RESTORE_EDGE_DIRECTED: 'RESTORE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.DO_NOTHING": {"fullname": "causy.models.TestResultAction.DO_NOTHING", "modulename": "causy.models", "qualname": "TestResultAction.DO_NOTHING", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.DO_NOTHING: 'DO_NOTHING'>"}, "causy.models.TestResult": {"fullname": "causy.models.TestResult", "modulename": "causy.models", "qualname": "TestResult", "kind": "class", "doc": "

Test result interface for the graph\nA test result is defined by two nodes and an action. It can also have metadata.

\n", "bases": "causy.interfaces.TestResultInterface"}, "causy.models.TestResult.u": {"fullname": "causy.models.TestResult.u", "modulename": "causy.models", "qualname": "TestResult.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.models.TestResult.v": {"fullname": "causy.models.TestResult.v", "modulename": "causy.models", "qualname": "TestResult.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.models.TestResult.action": {"fullname": "causy.models.TestResult.action", "modulename": "causy.models", "qualname": "TestResult.action", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.TestResultAction"}, "causy.models.TestResult.data": {"fullname": "causy.models.TestResult.data", "modulename": "causy.models", "qualname": "TestResult.data", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict]"}, "causy.models.TestResult.model_config": {"fullname": "causy.models.TestResult.model_config", "modulename": "causy.models", "qualname": "TestResult.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.models.TestResult.model_fields": {"fullname": "causy.models.TestResult.model_fields", "modulename": "causy.models", "qualname": "TestResult.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'action': FieldInfo(annotation=TestResultAction, required=True), 'data': FieldInfo(annotation=Union[Dict, NoneType], required=False, default=None)}"}, "causy.models.TestResult.model_computed_fields": {"fullname": "causy.models.TestResult.model_computed_fields", "modulename": "causy.models", "qualname": "TestResult.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.AlgorithmReferenceType": {"fullname": "causy.models.AlgorithmReferenceType", "modulename": "causy.models", "qualname": "AlgorithmReferenceType", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.models.AlgorithmReferenceType.FILE": {"fullname": "causy.models.AlgorithmReferenceType.FILE", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.FILE", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.FILE: 'file'>"}, "causy.models.AlgorithmReferenceType.NAME": {"fullname": "causy.models.AlgorithmReferenceType.NAME", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.NAME", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.NAME: 'name'>"}, "causy.models.AlgorithmReferenceType.PYTHON_MODULE": {"fullname": "causy.models.AlgorithmReferenceType.PYTHON_MODULE", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.PYTHON_MODULE", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.PYTHON_MODULE: 'python_module'>"}, "causy.models.AlgorithmReference": {"fullname": "causy.models.AlgorithmReference", "modulename": "causy.models", "qualname": "AlgorithmReference", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.AlgorithmReference.reference": {"fullname": "causy.models.AlgorithmReference.reference", "modulename": "causy.models", "qualname": "AlgorithmReference.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.AlgorithmReference.type": {"fullname": "causy.models.AlgorithmReference.type", "modulename": "causy.models", "qualname": "AlgorithmReference.type", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.AlgorithmReferenceType"}, "causy.models.AlgorithmReference.model_config": {"fullname": "causy.models.AlgorithmReference.model_config", "modulename": "causy.models", "qualname": "AlgorithmReference.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.AlgorithmReference.model_fields": {"fullname": "causy.models.AlgorithmReference.model_fields", "modulename": "causy.models", "qualname": "AlgorithmReference.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'reference': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=AlgorithmReferenceType, required=True)}"}, "causy.models.AlgorithmReference.model_computed_fields": {"fullname": "causy.models.AlgorithmReference.model_computed_fields", "modulename": "causy.models", "qualname": "AlgorithmReference.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Algorithm": {"fullname": "causy.models.Algorithm", "modulename": "causy.models", "qualname": "Algorithm", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.Algorithm.name": {"fullname": "causy.models.Algorithm.name", "modulename": "causy.models", "qualname": "Algorithm.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.Algorithm.pipeline_steps": {"fullname": "causy.models.Algorithm.pipeline_steps", "modulename": "causy.models", "qualname": "Algorithm.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": List[Union[~PipelineStepInterfaceType, causy.interfaces.LogicStepInterface]]"}, "causy.models.Algorithm.edge_types": {"fullname": "causy.models.Algorithm.edge_types", "modulename": "causy.models", "qualname": "Algorithm.edge_types", "kind": "variable", "doc": "

\n", "annotation": ": List[~EdgeTypeInterfaceType]"}, "causy.models.Algorithm.extensions": {"fullname": "causy.models.Algorithm.extensions", "modulename": "causy.models", "qualname": "Algorithm.extensions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~ExtensionType]]"}, "causy.models.Algorithm.variables": {"fullname": "causy.models.Algorithm.variables", "modulename": "causy.models", "qualname": "Algorithm.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~VariableInterfaceType]]"}, "causy.models.Algorithm.pre_graph_update_hooks": {"fullname": "causy.models.Algorithm.pre_graph_update_hooks", "modulename": "causy.models", "qualname": "Algorithm.pre_graph_update_hooks", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.interfaces.GraphUpdateHook]]"}, "causy.models.Algorithm.post_graph_update_hooks": {"fullname": "causy.models.Algorithm.post_graph_update_hooks", "modulename": "causy.models", "qualname": "Algorithm.post_graph_update_hooks", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.interfaces.GraphUpdateHook]]"}, "causy.models.Algorithm.hash": {"fullname": "causy.models.Algorithm.hash", "modulename": "causy.models", "qualname": "Algorithm.hash", "kind": "function", "doc": "

\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.models.Algorithm.model_config": {"fullname": "causy.models.Algorithm.model_config", "modulename": "causy.models", "qualname": "Algorithm.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Algorithm.model_fields": {"fullname": "causy.models.Algorithm.model_fields", "modulename": "causy.models", "qualname": "Algorithm.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'pipeline_steps': FieldInfo(annotation=List[Union[TypeVar, LogicStepInterface]], required=True), 'edge_types': FieldInfo(annotation=List[TypeVar], required=True), 'extensions': FieldInfo(annotation=Union[List[TypeVar], NoneType], required=False, default=None), 'variables': FieldInfo(annotation=Union[List[TypeVar], NoneType], required=False, default=None), 'pre_graph_update_hooks': FieldInfo(annotation=Union[List[GraphUpdateHook], NoneType], required=False, default=None), 'post_graph_update_hooks': FieldInfo(annotation=Union[List[GraphUpdateHook], NoneType], required=False, default=None)}"}, "causy.models.Algorithm.model_computed_fields": {"fullname": "causy.models.Algorithm.model_computed_fields", "modulename": "causy.models", "qualname": "Algorithm.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ActionHistoryStep": {"fullname": "causy.models.ActionHistoryStep", "modulename": "causy.models", "qualname": "ActionHistoryStep", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.ActionHistoryStep.name": {"fullname": "causy.models.ActionHistoryStep.name", "modulename": "causy.models", "qualname": "ActionHistoryStep.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.ActionHistoryStep.duration": {"fullname": "causy.models.ActionHistoryStep.duration", "modulename": "causy.models", "qualname": "ActionHistoryStep.duration", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.models.ActionHistoryStep.actions": {"fullname": "causy.models.ActionHistoryStep.actions", "modulename": "causy.models", "qualname": "ActionHistoryStep.actions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.TestResult]]"}, "causy.models.ActionHistoryStep.all_proposed_actions": {"fullname": "causy.models.ActionHistoryStep.all_proposed_actions", "modulename": "causy.models", "qualname": "ActionHistoryStep.all_proposed_actions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.TestResult]]"}, "causy.models.ActionHistoryStep.steps": {"fullname": "causy.models.ActionHistoryStep.steps", "modulename": "causy.models", "qualname": "ActionHistoryStep.steps", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.ActionHistoryStep]]"}, "causy.models.ActionHistoryStep.model_config": {"fullname": "causy.models.ActionHistoryStep.model_config", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ActionHistoryStep.model_fields": {"fullname": "causy.models.ActionHistoryStep.model_fields", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'duration': FieldInfo(annotation=Union[float, NoneType], required=False, default=None), 'actions': FieldInfo(annotation=Union[List[TestResult], NoneType], required=False, default=[]), 'all_proposed_actions': FieldInfo(annotation=Union[List[TestResult], NoneType], required=False, default=[]), 'steps': FieldInfo(annotation=Union[List[ActionHistoryStep], NoneType], required=False, default=[])}"}, "causy.models.ActionHistoryStep.model_computed_fields": {"fullname": "causy.models.ActionHistoryStep.model_computed_fields", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Result": {"fullname": "causy.models.Result", "modulename": "causy.models", "qualname": "Result", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.Result.algorithm": {"fullname": "causy.models.Result.algorithm", "modulename": "causy.models", "qualname": "Result.algorithm", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.AlgorithmReference"}, "causy.models.Result.created_at": {"fullname": "causy.models.Result.created_at", "modulename": "causy.models", "qualname": "Result.created_at", "kind": "variable", "doc": "

\n", "annotation": ": datetime.datetime"}, "causy.models.Result.nodes": {"fullname": "causy.models.Result.nodes", "modulename": "causy.models", "qualname": "Result.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, causy.interfaces.NodeInterface]"}, "causy.models.Result.edges": {"fullname": "causy.models.Result.edges", "modulename": "causy.models", "qualname": "Result.edges", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.interfaces.EdgeInterface]"}, "causy.models.Result.action_history": {"fullname": "causy.models.Result.action_history", "modulename": "causy.models", "qualname": "Result.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.models.ActionHistoryStep]"}, "causy.models.Result.variables": {"fullname": "causy.models.Result.variables", "modulename": "causy.models", "qualname": "Result.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]"}, "causy.models.Result.data_loader_hash": {"fullname": "causy.models.Result.data_loader_hash", "modulename": "causy.models", "qualname": "Result.data_loader_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.algorithm_hash": {"fullname": "causy.models.Result.algorithm_hash", "modulename": "causy.models", "qualname": "Result.algorithm_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.variables_hash": {"fullname": "causy.models.Result.variables_hash", "modulename": "causy.models", "qualname": "Result.variables_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.model_config": {"fullname": "causy.models.Result.model_config", "modulename": "causy.models", "qualname": "Result.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Result.model_fields": {"fullname": "causy.models.Result.model_fields", "modulename": "causy.models", "qualname": "Result.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'algorithm': FieldInfo(annotation=AlgorithmReference, required=True), 'created_at': FieldInfo(annotation=datetime, required=False, default_factory=builtin_function_or_method), 'nodes': FieldInfo(annotation=Dict[str, NodeInterface], required=True), 'edges': FieldInfo(annotation=List[EdgeInterface], required=True), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'data_loader_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'algorithm_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'variables_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}"}, "causy.models.Result.model_computed_fields": {"fullname": "causy.models.Result.model_computed_fields", "modulename": "causy.models", "qualname": "Result.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.sample_generator": {"fullname": "causy.sample_generator", "modulename": "causy.sample_generator", "kind": "module", "doc": "

\n"}, "causy.sample_generator.logger": {"fullname": "causy.sample_generator.logger", "modulename": "causy.sample_generator", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.sample_generator (WARNING)>"}, "causy.sample_generator.random_normal": {"fullname": "causy.sample_generator.random_normal", "modulename": "causy.sample_generator", "qualname": "random_normal", "kind": "function", "doc": "

Returns a random number from a normal distribution

\n\n
Returns
\n\n
\n

the random number as a float

\n
\n", "signature": "() -> float:", "funcdef": "def"}, "causy.sample_generator.NodeReference": {"fullname": "causy.sample_generator.NodeReference", "modulename": "causy.sample_generator", "qualname": "NodeReference", "kind": "class", "doc": "

A reference to a node in the sample generator

\n"}, "causy.sample_generator.NodeReference.__init__": {"fullname": "causy.sample_generator.NodeReference.__init__", "modulename": "causy.sample_generator", "qualname": "NodeReference.__init__", "kind": "function", "doc": "

\n", "signature": "(node: str)"}, "causy.sample_generator.NodeReference.node": {"fullname": "causy.sample_generator.NodeReference.node", "modulename": "causy.sample_generator", "qualname": "NodeReference.node", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.sample_generator.TimeAwareNodeReference": {"fullname": "causy.sample_generator.TimeAwareNodeReference", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference", "kind": "class", "doc": "

A reference to a node in the sample generator

\n", "bases": "NodeReference"}, "causy.sample_generator.TimeAwareNodeReference.__init__": {"fullname": "causy.sample_generator.TimeAwareNodeReference.__init__", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference.__init__", "kind": "function", "doc": "

\n", "signature": "(node: str, point_in_time: int = 0)"}, "causy.sample_generator.TimeAwareNodeReference.point_in_time": {"fullname": "causy.sample_generator.TimeAwareNodeReference.point_in_time", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference.point_in_time", "kind": "variable", "doc": "

\n", "annotation": ": int", "default_value": "0"}, "causy.sample_generator.SampleEdge": {"fullname": "causy.sample_generator.SampleEdge", "modulename": "causy.sample_generator", "qualname": "SampleEdge", "kind": "class", "doc": "

An edge in the sample generator that references a node and a lag

\n"}, "causy.sample_generator.SampleEdge.__init__": {"fullname": "causy.sample_generator.SampleEdge.__init__", "modulename": "causy.sample_generator", "qualname": "SampleEdge.__init__", "kind": "function", "doc": "

\n", "signature": "(\tfrom_node: causy.sample_generator.NodeReference,\tto_node: causy.sample_generator.NodeReference,\tvalue: float = 0)"}, "causy.sample_generator.SampleEdge.from_node": {"fullname": "causy.sample_generator.SampleEdge.from_node", "modulename": "causy.sample_generator", "qualname": "SampleEdge.from_node", "kind": "variable", "doc": "

\n", "annotation": ": causy.sample_generator.NodeReference"}, "causy.sample_generator.SampleEdge.to_node": {"fullname": "causy.sample_generator.SampleEdge.to_node", "modulename": "causy.sample_generator", "qualname": "SampleEdge.to_node", "kind": "variable", "doc": "

\n", "annotation": ": causy.sample_generator.NodeReference"}, "causy.sample_generator.SampleEdge.value": {"fullname": "causy.sample_generator.SampleEdge.value", "modulename": "causy.sample_generator", "qualname": "SampleEdge.value", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "0"}, "causy.sample_generator.TimeTravelingError": {"fullname": "causy.sample_generator.TimeTravelingError", "modulename": "causy.sample_generator", "qualname": "TimeTravelingError", "kind": "class", "doc": "

An error that is raised when a TimeProxy tries to access a value from the future

\n", "bases": "builtins.Exception"}, "causy.sample_generator.AbstractSampleGenerator": {"fullname": "causy.sample_generator.AbstractSampleGenerator", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.sample_generator.AbstractSampleGenerator.random_fn": {"fullname": "causy.sample_generator.AbstractSampleGenerator.random_fn", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator.random_fn", "kind": "variable", "doc": "

\n"}, "causy.sample_generator.AbstractSampleGenerator.generate": {"fullname": "causy.sample_generator.AbstractSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size: int) -> types.SimpleNamespace:", "funcdef": "def"}, "causy.sample_generator.IIDSampleGenerator": {"fullname": "causy.sample_generator.IIDSampleGenerator", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator", "kind": "class", "doc": "

A sample generator that generates data from i.i.d multivariate Gaussians.

\n\n

A variable can not depend on itself.

\n\n

Example:

\n\n
\n
>>> sg = IIDSampleGenerator(\n>>>     edges=[\n>>>      SampleEdge(NodeReference("X"), NodeReference("Y"), 5),\n>>>      SampleEdge(NodeReference("Y"), NodeReference("Z"), 7),\n>>>      ],\n>>> )\n
\n
\n", "bases": "AbstractSampleGenerator"}, "causy.sample_generator.IIDSampleGenerator.__init__": {"fullname": "causy.sample_generator.IIDSampleGenerator.__init__", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tedges: List[causy.sample_generator.SampleEdge],\trandom: Callable = <function random_normal>)"}, "causy.sample_generator.IIDSampleGenerator.topologic_sort": {"fullname": "causy.sample_generator.IIDSampleGenerator.topologic_sort", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.topologic_sort", "kind": "function", "doc": "

Sorts the nodes topologically

\n\n
Parameters
\n\n
    \n
  • nodes: list of nodes
    • \n
  • edges: list of edges
    • \n
\n\n
Returns
\n\n
\n

a list of sorted nodes

\n
\n", "signature": "(self, nodes: List[str]):", "funcdef": "def"}, "causy.sample_generator.IIDSampleGenerator.generate": {"fullname": "causy.sample_generator.IIDSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator", "kind": "class", "doc": "

A sample generator that generates data for a sample graph with a time dimension.

\n\n

Edges are defined as SampleLaggedEdges, which define a directed edge from a source node to a target node with a\nag. The lag is the number of time steps between the source and the target.

\n\n

A variable can depend on itself, but only on its past values (with a lag). This corresponds to autoregressive models.

\n\n

Example:

\n\n
\n
>>> sg = TimeseriesSampleGenerator(\n>>>     edges=[\n>>>      SampleEdge(TimeAwareNodeReference("X", -1), TimeAwareNodeReference("X"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Y", -1), TimeAwareNodeReference("Y"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Z", -1), TimeAwareNodeReference("Z"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Z", -1), TimeAwareNodeReference("Y"), 5),\n>>>      SampleEdge(TimeAwareNodeReference("Y", -1), TimeAwareNodeReference("X"), 7),\n>>>      ],\n>>> )\n
\n
\n", "bases": "AbstractSampleGenerator"}, "causy.sample_generator.TimeseriesSampleGenerator.__init__": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.__init__", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tedges: List[causy.sample_generator.SampleEdge],\trandom: Callable = <function random_normal>)"}, "causy.sample_generator.TimeseriesSampleGenerator.generate": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator.custom_block_diagonal": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.custom_block_diagonal", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.custom_block_diagonal", "kind": "function", "doc": "

\n", "signature": "(self, matrices):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator.vectorize_identity_block": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.vectorize_identity_block", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.vectorize_identity_block", "kind": "function", "doc": "

\n", "signature": "(self, n):", "funcdef": "def"}, "causy.serialization": {"fullname": "causy.serialization", "modulename": "causy.serialization", "kind": "module", "doc": "

\n"}, "causy.serialization.serialize_algorithm": {"fullname": "causy.serialization.serialize_algorithm", "modulename": "causy.serialization", "qualname": "serialize_algorithm", "kind": "function", "doc": "

Serialize the model into a dictionary.

\n", "signature": "(model, algorithm_name: str = None):", "funcdef": "def"}, "causy.serialization.load_algorithm_from_specification": {"fullname": "causy.serialization.load_algorithm_from_specification", "modulename": "causy.serialization", "qualname": "load_algorithm_from_specification", "kind": "function", "doc": "

Load the model from a dictionary.

\n", "signature": "(algorithm_dict: Dict[str, Any]):", "funcdef": "def"}, "causy.serialization.load_algorithm_by_reference": {"fullname": "causy.serialization.load_algorithm_by_reference", "modulename": "causy.serialization", "qualname": "load_algorithm_by_reference", "kind": "function", "doc": "

\n", "signature": "(reference_type: str, algorithm: str):", "funcdef": "def"}, "causy.serialization.CausyJSONEncoder": {"fullname": "causy.serialization.CausyJSONEncoder", "modulename": "causy.serialization", "qualname": "CausyJSONEncoder", "kind": "class", "doc": "

Extensible JSON https://json.org encoder for Python data structures.

\n\n

Supports the following objects and types by default:

\n\n

+-------------------+---------------+\n| Python | JSON |\n+===================+===============+\n| dict | object |\n+-------------------+---------------+\n| list, tuple | array |\n+-------------------+---------------+\n| str | string |\n+-------------------+---------------+\n| int, float | number |\n+-------------------+---------------+\n| True | true |\n+-------------------+---------------+\n| False | false |\n+-------------------+---------------+\n| None | null |\n+-------------------+---------------+

\n\n

To extend this to recognize other objects, subclass and implement a\n.default() method with another method that returns a serializable\nobject for o if possible, otherwise it should call the superclass\nimplementation (to raise TypeError).

\n", "bases": "json.encoder.JSONEncoder"}, "causy.serialization.CausyJSONEncoder.default": {"fullname": "causy.serialization.CausyJSONEncoder.default", "modulename": "causy.serialization", "qualname": "CausyJSONEncoder.default", "kind": "function", "doc": "

Implement this method in a subclass such that it returns\na serializable object for o, or calls the base implementation\n(to raise a TypeError).

\n\n

For example, to support arbitrary iterators, you could\nimplement default like this::

\n\n
def default(self, o):\n    try:\n        iterable = iter(o)\n    except TypeError:\n        pass\n    else:\n        return list(iterable)\n    # Let the base class default method raise the TypeError\n    return super().default(o)\n
\n", "signature": "(self, obj):", "funcdef": "def"}, "causy.serialization.load_json": {"fullname": "causy.serialization.load_json", "modulename": "causy.serialization", "qualname": "load_json", "kind": "function", "doc": "

\n", "signature": "(pipeline_file: str):", "funcdef": "def"}, "causy.serialization.deserialize_result": {"fullname": "causy.serialization.deserialize_result", "modulename": "causy.serialization", "qualname": "deserialize_result", "kind": "function", "doc": "

Deserialize the result.

\n", "signature": "(result: Dict[str, Any], klass=<class 'causy.models.Result'>):", "funcdef": "def"}, "causy.ui": {"fullname": "causy.ui", "modulename": "causy.ui", "kind": "module", "doc": "

\n"}, "causy.ui.cli": {"fullname": "causy.ui.cli", "modulename": "causy.ui.cli", "kind": "module", "doc": "

\n"}, "causy.ui.cli.ui": {"fullname": "causy.ui.cli.ui", "modulename": "causy.ui.cli", "qualname": "ui", "kind": "function", "doc": "

Start the causy UI.

\n", "signature": "(result_file: str = None):", "funcdef": "def"}, "causy.ui.models": {"fullname": "causy.ui.models", "modulename": "causy.ui.models", "kind": "module", "doc": "

\n"}, "causy.ui.models.NodePosition": {"fullname": "causy.ui.models.NodePosition", "modulename": "causy.ui.models", "qualname": "NodePosition", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.ui.models.NodePosition.x": {"fullname": "causy.ui.models.NodePosition.x", "modulename": "causy.ui.models", "qualname": "NodePosition.x", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.ui.models.NodePosition.y": {"fullname": "causy.ui.models.NodePosition.y", "modulename": "causy.ui.models", "qualname": "NodePosition.y", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.ui.models.NodePosition.model_config": {"fullname": "causy.ui.models.NodePosition.model_config", "modulename": "causy.ui.models", "qualname": "NodePosition.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.NodePosition.model_fields": {"fullname": "causy.ui.models.NodePosition.model_fields", "modulename": "causy.ui.models", "qualname": "NodePosition.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'x': FieldInfo(annotation=Union[float, NoneType], required=True), 'y': FieldInfo(annotation=Union[float, NoneType], required=True)}"}, "causy.ui.models.NodePosition.model_computed_fields": {"fullname": "causy.ui.models.NodePosition.model_computed_fields", "modulename": "causy.ui.models", "qualname": "NodePosition.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExperimentVersion": {"fullname": "causy.ui.models.ExperimentVersion", "modulename": "causy.ui.models", "qualname": "ExperimentVersion", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.ui.models.ExperimentVersion.version": {"fullname": "causy.ui.models.ExperimentVersion.version", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.version", "kind": "variable", "doc": "

\n", "annotation": ": int"}, "causy.ui.models.ExperimentVersion.name": {"fullname": "causy.ui.models.ExperimentVersion.name", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.ui.models.ExperimentVersion.model_config": {"fullname": "causy.ui.models.ExperimentVersion.model_config", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExperimentVersion.model_fields": {"fullname": "causy.ui.models.ExperimentVersion.model_fields", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'version': FieldInfo(annotation=int, required=True), 'name': FieldInfo(annotation=str, required=True)}"}, "causy.ui.models.ExperimentVersion.model_computed_fields": {"fullname": "causy.ui.models.ExperimentVersion.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedExperiment": {"fullname": "causy.ui.models.ExtendedExperiment", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment", "kind": "class", "doc": "

represents a single experiment

\n\n
Parameters
\n\n
    \n
  • name: name of the experiment
    • \n
  • pipeline: the name of the pipeline used
    • \n
\n", "bases": "causy.workspaces.models.Experiment"}, "causy.ui.models.ExtendedExperiment.versions": {"fullname": "causy.ui.models.ExtendedExperiment.versions", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.versions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.ui.models.ExperimentVersion]]"}, "causy.ui.models.ExtendedExperiment.name": {"fullname": "causy.ui.models.ExtendedExperiment.name", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.ui.models.ExtendedExperiment.model_config": {"fullname": "causy.ui.models.ExtendedExperiment.model_config", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedExperiment.model_fields": {"fullname": "causy.ui.models.ExtendedExperiment.model_fields", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'pipeline': FieldInfo(annotation=str, required=True), 'dataloader': FieldInfo(annotation=str, required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool]], NoneType], required=False, default={}), 'versions': FieldInfo(annotation=Union[List[ExperimentVersion], NoneType], required=False, default=None), 'name': FieldInfo(annotation=str, required=False, default=None)}"}, "causy.ui.models.ExtendedExperiment.model_computed_fields": {"fullname": "causy.ui.models.ExtendedExperiment.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.PositionedNode": {"fullname": "causy.ui.models.PositionedNode", "modulename": "causy.ui.models", "qualname": "PositionedNode", "kind": "class", "doc": "

Node interface for the graph. A node is defined by a name and a value.

\n", "bases": "causy.interfaces.NodeInterface"}, "causy.ui.models.PositionedNode.position": {"fullname": "causy.ui.models.PositionedNode.position", "modulename": "causy.ui.models", "qualname": "PositionedNode.position", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.ui.models.NodePosition]"}, "causy.ui.models.PositionedNode.model_config": {"fullname": "causy.ui.models.PositionedNode.model_config", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.ui.models.PositionedNode.model_fields": {"fullname": "causy.ui.models.PositionedNode.model_fields", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[DoubleTensor, NoneType], required=False, default=None, exclude=True, metadata=[WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)]), 'position': FieldInfo(annotation=Union[NodePosition, NoneType], required=False, default=None)}"}, "causy.ui.models.PositionedNode.model_computed_fields": {"fullname": "causy.ui.models.PositionedNode.model_computed_fields", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedResult": {"fullname": "causy.ui.models.ExtendedResult", "modulename": "causy.ui.models", "qualname": "ExtendedResult", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.models.Result"}, "causy.ui.models.ExtendedResult.nodes": {"fullname": "causy.ui.models.ExtendedResult.nodes", "modulename": "causy.ui.models", "qualname": "ExtendedResult.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Union[Annotated[uuid.UUID, UuidVersion(uuid_version=4)], str], causy.ui.models.PositionedNode]"}, "causy.ui.models.ExtendedResult.version": {"fullname": "causy.ui.models.ExtendedResult.version", "modulename": "causy.ui.models", "qualname": "ExtendedResult.version", "kind": "variable", "doc": "

\n", "annotation": ": Optional[int]"}, "causy.ui.models.ExtendedResult.model_config": {"fullname": "causy.ui.models.ExtendedResult.model_config", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedResult.model_fields": {"fullname": "causy.ui.models.ExtendedResult.model_fields", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'algorithm': FieldInfo(annotation=AlgorithmReference, required=True), 'created_at': FieldInfo(annotation=datetime, required=False, default_factory=builtin_function_or_method), 'nodes': FieldInfo(annotation=Dict[Union[Annotated[UUID, UuidVersion], str], PositionedNode], required=True), 'edges': FieldInfo(annotation=List[EdgeInterface], required=True), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'data_loader_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'algorithm_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'variables_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'version': FieldInfo(annotation=Union[int, NoneType], required=False, default=None)}"}, "causy.ui.models.ExtendedResult.model_computed_fields": {"fullname": "causy.ui.models.ExtendedResult.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.server": {"fullname": "causy.ui.server", "modulename": "causy.ui.server", "kind": "module", "doc": "

\n"}, "causy.ui.server.logger": {"fullname": "causy.ui.server.logger", "modulename": "causy.ui.server", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.ui.server (WARNING)>"}, "causy.ui.server.API_ROUTES": {"fullname": "causy.ui.server.API_ROUTES", "modulename": "causy.ui.server", "qualname": "API_ROUTES", "kind": "variable", "doc": "

\n", "default_value": "<fastapi.routing.APIRouter object>"}, "causy.ui.server.MODEL": {"fullname": "causy.ui.server.MODEL", "modulename": "causy.ui.server", "qualname": "MODEL", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.ui.models.ExtendedResult]", "default_value": "None"}, "causy.ui.server.WORKSPACE": {"fullname": "causy.ui.server.WORKSPACE", "modulename": "causy.ui.server", "qualname": "WORKSPACE", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.workspaces.models.Workspace]", "default_value": "None"}, "causy.ui.server.get_status": {"fullname": "causy.ui.server.get_status", "modulename": "causy.ui.server", "qualname": "get_status", "kind": "function", "doc": "

Get the current status of the API.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_model": {"fullname": "causy.ui.server.get_model", "modulename": "causy.ui.server", "qualname": "get_model", "kind": "function", "doc": "

Get the current model.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_workspace": {"fullname": "causy.ui.server.get_workspace", "modulename": "causy.ui.server", "qualname": "get_workspace", "kind": "function", "doc": "

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_latest_experiment": {"fullname": "causy.ui.server.get_latest_experiment", "modulename": "causy.ui.server", "qualname": "get_latest_experiment", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "(experiment_name: str):", "funcdef": "async def"}, "causy.ui.server.get_experiment": {"fullname": "causy.ui.server.get_experiment", "modulename": "causy.ui.server", "qualname": "get_experiment", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "(experiment_name: str, version_number: int):", "funcdef": "async def"}, "causy.ui.server.get_experiments": {"fullname": "causy.ui.server.get_experiments", "modulename": "causy.ui.server", "qualname": "get_experiments", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_algorithm": {"fullname": "causy.ui.server.get_algorithm", "modulename": "causy.ui.server", "qualname": "get_algorithm", "kind": "function", "doc": "

Get the current algorithm.

\n", "signature": "(reference_type: str, reference: str):", "funcdef": "async def"}, "causy.ui.server.is_port_in_use": {"fullname": "causy.ui.server.is_port_in_use", "modulename": "causy.ui.server", "qualname": "is_port_in_use", "kind": "function", "doc": "

\n", "signature": "(host: str, port: int) -> bool:", "funcdef": "def"}, "causy.ui.server.server": {"fullname": "causy.ui.server.server", "modulename": "causy.ui.server", "qualname": "server", "kind": "function", "doc": "

Create the FastAPI server.

\n", "signature": "(\tresult: Dict[str, Any] = None,\tworkspace: causy.workspaces.models.Workspace = None):", "funcdef": "def"}, "causy.variables": {"fullname": "causy.variables", "modulename": "causy.variables", "kind": "module", "doc": "

\n"}, "causy.variables.VariableType": {"fullname": "causy.variables.VariableType", "modulename": "causy.variables", "qualname": "VariableType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool]"}, "causy.variables.VariableTypes": {"fullname": "causy.variables.VariableTypes", "modulename": "causy.variables", "qualname": "VariableTypes", "kind": "class", "doc": "

\n", "bases": "enum.Enum"}, "causy.variables.VariableTypes.String": {"fullname": "causy.variables.VariableTypes.String", "modulename": "causy.variables", "qualname": "VariableTypes.String", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.String: 'string'>"}, "causy.variables.VariableTypes.Integer": {"fullname": "causy.variables.VariableTypes.Integer", "modulename": "causy.variables", "qualname": "VariableTypes.Integer", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Integer: 'integer'>"}, "causy.variables.VariableTypes.Float": {"fullname": "causy.variables.VariableTypes.Float", "modulename": "causy.variables", "qualname": "VariableTypes.Float", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Float: 'float'>"}, "causy.variables.VariableTypes.Bool": {"fullname": "causy.variables.VariableTypes.Bool", "modulename": "causy.variables", "qualname": "VariableTypes.Bool", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Bool: 'bool'>"}, "causy.variables.BaseVariable": {"fullname": "causy.variables.BaseVariable", "modulename": "causy.variables", "qualname": "BaseVariable", "kind": "class", "doc": "

Represents a single variable. It can be a string, int, float or bool. The type of the variable is determined by the\ntype attribute.

\n", "bases": "pydantic.main.BaseModel, typing.Generic[~VariableInterfaceType]"}, "causy.variables.BaseVariable.name": {"fullname": "causy.variables.BaseVariable.name", "modulename": "causy.variables", "qualname": "BaseVariable.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.BaseVariable.value": {"fullname": "causy.variables.BaseVariable.value", "modulename": "causy.variables", "qualname": "BaseVariable.value", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, int, float, bool]"}, "causy.variables.BaseVariable.choices": {"fullname": "causy.variables.BaseVariable.choices", "modulename": "causy.variables", "qualname": "BaseVariable.choices", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[Union[str, int, float, bool]]]"}, "causy.variables.BaseVariable.is_valid": {"fullname": "causy.variables.BaseVariable.is_valid", "modulename": "causy.variables", "qualname": "BaseVariable.is_valid", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "causy.variables.BaseVariable.is_valid_value": {"fullname": "causy.variables.BaseVariable.is_valid_value", "modulename": "causy.variables", "qualname": "BaseVariable.is_valid_value", "kind": "function", "doc": "

\n", "signature": "(self, value):", "funcdef": "def"}, "causy.variables.BaseVariable.validate_value": {"fullname": "causy.variables.BaseVariable.validate_value", "modulename": "causy.variables", "qualname": "BaseVariable.validate_value", "kind": "function", "doc": "

\n", "signature": "(self, value):", "funcdef": "def"}, "causy.variables.BaseVariable.type": {"fullname": "causy.variables.BaseVariable.type", "modulename": "causy.variables", "qualname": "BaseVariable.type", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.variables.StringVariable": {"fullname": "causy.variables.StringVariable", "modulename": "causy.variables", "qualname": "StringVariable", "kind": "class", "doc": "

Represents a single string variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.StringVariable.model_post_init": {"fullname": "causy.variables.StringVariable.model_post_init", "modulename": "causy.variables", "qualname": "StringVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.IntegerVariable": {"fullname": "causy.variables.IntegerVariable", "modulename": "causy.variables", "qualname": "IntegerVariable", "kind": "class", "doc": "

Represents a single int variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.IntegerVariable.model_post_init": {"fullname": "causy.variables.IntegerVariable.model_post_init", "modulename": "causy.variables", "qualname": "IntegerVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.FloatVariable": {"fullname": "causy.variables.FloatVariable", "modulename": "causy.variables", "qualname": "FloatVariable", "kind": "class", "doc": "

Represents a single float variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.FloatVariable.model_post_init": {"fullname": "causy.variables.FloatVariable.model_post_init", "modulename": "causy.variables", "qualname": "FloatVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.BoolVariable": {"fullname": "causy.variables.BoolVariable", "modulename": "causy.variables", "qualname": "BoolVariable", "kind": "class", "doc": "

Represents a single bool variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.BoolVariable.model_post_init": {"fullname": "causy.variables.BoolVariable.model_post_init", "modulename": "causy.variables", "qualname": "BoolVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.VariableReference": {"fullname": "causy.variables.VariableReference", "modulename": "causy.variables", "qualname": "VariableReference", "kind": "class", "doc": "

Represents a reference to a variable.

\n", "bases": "pydantic.main.BaseModel, typing.Generic[~VariableInterfaceType]"}, "causy.variables.VariableReference.name": {"fullname": "causy.variables.VariableReference.name", "modulename": "causy.variables", "qualname": "VariableReference.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.VariableReference.type": {"fullname": "causy.variables.VariableReference.type", "modulename": "causy.variables", "qualname": "VariableReference.type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.VARIABLE_MAPPING": {"fullname": "causy.variables.VARIABLE_MAPPING", "modulename": "causy.variables", "qualname": "VARIABLE_MAPPING", "kind": "variable", "doc": "

\n", "default_value": "{'string': <class 'causy.variables.StringVariable'>, 'integer': <class 'causy.variables.IntegerVariable'>, 'float': <class 'causy.variables.FloatVariable'>, 'bool': <class 'causy.variables.BoolVariable'>}"}, "causy.variables.BoolParameter": {"fullname": "causy.variables.BoolParameter", "modulename": "causy.variables", "qualname": "BoolParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bool, causy.variables.VariableReference]"}, "causy.variables.IntegerParameter": {"fullname": "causy.variables.IntegerParameter", "modulename": "causy.variables", "qualname": "IntegerParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[int, causy.variables.VariableReference]"}, "causy.variables.FloatParameter": {"fullname": "causy.variables.FloatParameter", "modulename": "causy.variables", "qualname": "FloatParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[float, causy.variables.VariableReference]"}, "causy.variables.StringParameter": {"fullname": "causy.variables.StringParameter", "modulename": "causy.variables", "qualname": "StringParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, causy.variables.VariableReference]"}, "causy.variables.CausyParameter": {"fullname": "causy.variables.CausyParameter", "modulename": "causy.variables", "qualname": "CausyParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bool, causy.variables.VariableReference, int, float, str]"}, "causy.variables.validate_variable_values": {"fullname": "causy.variables.validate_variable_values", "modulename": "causy.variables", "qualname": "validate_variable_values", "kind": "function", "doc": "

Validate the variable values for the algorithm.

\n\n
Parameters
\n\n
    \n
  • algorithm:
    • \n
  • variable_values:
    • \n
\n\n
Returns
\n", "signature": "(algorithm, variable_values: Dict[str, Union[str, int, float, bool]]):", "funcdef": "def"}, "causy.variables.resolve_variables": {"fullname": "causy.variables.resolve_variables", "modulename": "causy.variables", "qualname": "resolve_variables", "kind": "function", "doc": "

Resolve the variables from the list of variables and the variable values coming from the user.

\n\n
Parameters
\n\n
    \n
  • variables:
    • \n
  • variable_values:
    • \n
\n\n
Returns
\n", "signature": "(\tvariables: List[causy.variables.BaseVariable],\tvariable_values: Dict[str, Union[str, int, float, bool]]) -> Dict[str, Union[str, int, float, bool]]:", "funcdef": "def"}, "causy.variables.resolve_variable_to_object": {"fullname": "causy.variables.resolve_variable_to_object", "modulename": "causy.variables", "qualname": "resolve_variable_to_object", "kind": "function", "doc": "

Resolve the variables to the object.

\n\n
Parameters
\n\n
    \n
  • obj:
    • \n
  • variables:
    • \n
\n\n
Returns
\n", "signature": "(obj: Any, variables):", "funcdef": "def"}, "causy.variables.resolve_variables_to_algorithm_for_pipeline_steps": {"fullname": "causy.variables.resolve_variables_to_algorithm_for_pipeline_steps", "modulename": "causy.variables", "qualname": "resolve_variables_to_algorithm_for_pipeline_steps", "kind": "function", "doc": "

Resolve the variables to the algorithm.

\n\n
Parameters
\n\n
    \n
  • pipeline_steps:
    • \n
  • variables:
    • \n
\n\n
Returns
\n", "signature": "(pipeline_steps, variables):", "funcdef": "def"}, "causy.variables.deserialize_variable": {"fullname": "causy.variables.deserialize_variable", "modulename": "causy.variables", "qualname": "deserialize_variable", "kind": "function", "doc": "

Deserialize the variable from the dictionary.

\n\n
Parameters
\n\n
    \n
  • variable_dict:
    • \n
\n\n
Returns
\n", "signature": "(\tvariable_dict: Dict[str, Union[str, int, float, bool]]) -> causy.variables.BaseVariable:", "funcdef": "def"}, "causy.variables.deserialize_variable_references": {"fullname": "causy.variables.deserialize_variable_references", "modulename": "causy.variables", "qualname": "deserialize_variable_references", "kind": "function", "doc": "

Deserialize the variable references from the pipeline step.

\n\n
Parameters
\n\n
    \n
  • pipeline_step:
    • \n
\n\n
Returns
\n", "signature": "(element: object) -> object:", "funcdef": "def"}, "causy.workspaces": {"fullname": "causy.workspaces", "modulename": "causy.workspaces", "kind": "module", "doc": "

Representation of a causy workspace.

\n\n

Exemplary folder structure

\n\n
    \n
  • causy.yaml (contains workspace wide settings for stuff like name, author, pipeline definitions)
    • \n
  • any_pipeline.yaml (seperate pipeline definition referenced by causy.yaml)
    • \n
  • custom_pipeline_step.py (a project specific pipeline step)
    • \n
  • some_data_loader.py (a data loader to ship data into causy)
    • \n
  • tune_pipeline_1709406402/ (a single experiment)\n
      \n
    • causy_experiment.json (contains the full definition of everything used)
      • \n
    • causy_model.json (the actual generated model)
      • \n
    • \n
\n\n

Examples

\n\n
    \n
  • the user generates a new workspace because they want to work on a new causal discovery project (causy workspace create)
    • \n
  • they add a custom data loader, pipeline steps and extend an existing pipeline (causy workspace data-loaders create)
    • \n
  • they run multiple experiments (causy workspace experiments create, causy workspace experiments execute $EXPERIMENT_NAME)
    • \n
\n"}, "causy.workspaces.cli": {"fullname": "causy.workspaces.cli", "modulename": "causy.workspaces.cli", "kind": "module", "doc": "

\n"}, "causy.workspaces.cli.workspace_app": {"fullname": "causy.workspaces.cli.workspace_app", "modulename": "causy.workspaces.cli", "qualname": "workspace_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.pipeline_app": {"fullname": "causy.workspaces.cli.pipeline_app", "modulename": "causy.workspaces.cli", "qualname": "pipeline_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.experiment_app": {"fullname": "causy.workspaces.cli.experiment_app", "modulename": "causy.workspaces.cli", "qualname": "experiment_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.dataloader_app": {"fullname": "causy.workspaces.cli.dataloader_app", "modulename": "causy.workspaces.cli", "qualname": "dataloader_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.logger": {"fullname": "causy.workspaces.cli.logger", "modulename": "causy.workspaces.cli", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.workspaces.cli (WARNING)>"}, "causy.workspaces.cli.NO_COLOR": {"fullname": "causy.workspaces.cli.NO_COLOR", "modulename": "causy.workspaces.cli", "qualname": "NO_COLOR", "kind": "variable", "doc": "

\n", "default_value": "False"}, "causy.workspaces.cli.WORKSPACE_FILE_NAME": {"fullname": "causy.workspaces.cli.WORKSPACE_FILE_NAME", "modulename": "causy.workspaces.cli", "qualname": "WORKSPACE_FILE_NAME", "kind": "variable", "doc": "

\n", "default_value": "'workspace.yml'"}, "causy.workspaces.cli.JINJA_ENV": {"fullname": "causy.workspaces.cli.JINJA_ENV", "modulename": "causy.workspaces.cli", "qualname": "JINJA_ENV", "kind": "variable", "doc": "

\n", "default_value": "<jinja2.environment.Environment object>"}, "causy.workspaces.cli.WorkspaceNotFoundError": {"fullname": "causy.workspaces.cli.WorkspaceNotFoundError", "modulename": "causy.workspaces.cli", "qualname": "WorkspaceNotFoundError", "kind": "class", "doc": "

Common base class for all non-exit exceptions.

\n", "bases": "builtins.Exception"}, "causy.workspaces.cli.show_error": {"fullname": "causy.workspaces.cli.show_error", "modulename": "causy.workspaces.cli", "qualname": "show_error", "kind": "function", "doc": "

\n", "signature": "(message: str):", "funcdef": "def"}, "causy.workspaces.cli.show_success": {"fullname": "causy.workspaces.cli.show_success", "modulename": "causy.workspaces.cli", "qualname": "show_success", "kind": "function", "doc": "

\n", "signature": "(message: str):", "funcdef": "def"}, "causy.workspaces.cli.write_to_workspace": {"fullname": "causy.workspaces.cli.write_to_workspace", "modulename": "causy.workspaces.cli", "qualname": "write_to_workspace", "kind": "function", "doc": "

\n", "signature": "(workspace: causy.workspaces.models.Workspace):", "funcdef": "def"}, "causy.workspaces.cli.create_pipeline": {"fullname": "causy.workspaces.cli.create_pipeline", "modulename": "causy.workspaces.cli", "qualname": "create_pipeline", "kind": "function", "doc": "

Create a new pipeline in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_pipeline": {"fullname": "causy.workspaces.cli.remove_pipeline", "modulename": "causy.workspaces.cli", "qualname": "remove_pipeline", "kind": "function", "doc": "

Remove a pipeline from the current workspace.

\n", "signature": "(pipeline_name: str):", "funcdef": "def"}, "causy.workspaces.cli.create_experiment": {"fullname": "causy.workspaces.cli.create_experiment", "modulename": "causy.workspaces.cli", "qualname": "create_experiment", "kind": "function", "doc": "

Create a new experiment in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_experiment": {"fullname": "causy.workspaces.cli.remove_experiment", "modulename": "causy.workspaces.cli", "qualname": "remove_experiment", "kind": "function", "doc": "

Remove an experiment from the current workspace.

\n", "signature": "(experiment_name: str):", "funcdef": "def"}, "causy.workspaces.cli.clear_experiment": {"fullname": "causy.workspaces.cli.clear_experiment", "modulename": "causy.workspaces.cli", "qualname": "clear_experiment", "kind": "function", "doc": "

Clear all versions of an experiment.

\n", "signature": "(experiment_name: str):", "funcdef": "def"}, "causy.workspaces.cli.update_experiment_variable": {"fullname": "causy.workspaces.cli.update_experiment_variable", "modulename": "causy.workspaces.cli", "qualname": "update_experiment_variable", "kind": "function", "doc": "

Update a variable in an experiment.

\n", "signature": "(experiment_name: str, variable_name: str, variable_value: str):", "funcdef": "def"}, "causy.workspaces.cli.create_data_loader": {"fullname": "causy.workspaces.cli.create_data_loader", "modulename": "causy.workspaces.cli", "qualname": "create_data_loader", "kind": "function", "doc": "

Create a new data loader in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_data_loader": {"fullname": "causy.workspaces.cli.remove_data_loader", "modulename": "causy.workspaces.cli", "qualname": "remove_data_loader", "kind": "function", "doc": "

Remove a data loader from the current workspace.

\n", "signature": "(data_loader_name: str):", "funcdef": "def"}, "causy.workspaces.cli.info": {"fullname": "causy.workspaces.cli.info", "modulename": "causy.workspaces.cli", "qualname": "info", "kind": "function", "doc": "

Show general information about the workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.init": {"fullname": "causy.workspaces.cli.init", "modulename": "causy.workspaces.cli", "qualname": "init", "kind": "function", "doc": "

Initialize a new workspace in the current directory.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.execute": {"fullname": "causy.workspaces.cli.execute", "modulename": "causy.workspaces.cli", "qualname": "execute", "kind": "function", "doc": "

Execute an experiment or all experiments in the workspace.

\n", "signature": "(experiment_name: str = None, force_reexecution: bool = False):", "funcdef": "def"}, "causy.workspaces.cli.diff": {"fullname": "causy.workspaces.cli.diff", "modulename": "causy.workspaces.cli", "qualname": "diff", "kind": "function", "doc": "

Show the differences between multiple experiment results.

\n", "signature": "(experiment_names: List[str], only_differences: bool = False):", "funcdef": "def"}, "causy.workspaces.models": {"fullname": "causy.workspaces.models", "modulename": "causy.workspaces.models", "kind": "module", "doc": "

\n"}, "causy.workspaces.models.Experiment": {"fullname": "causy.workspaces.models.Experiment", "modulename": "causy.workspaces.models", "qualname": "Experiment", "kind": "class", "doc": "

represents a single experiment

\n\n
Parameters
\n\n
    \n
  • name: name of the experiment
    • \n
  • pipeline: the name of the pipeline used
    • \n
\n", "bases": "pydantic.main.BaseModel"}, "causy.workspaces.models.Experiment.pipeline": {"fullname": "causy.workspaces.models.Experiment.pipeline", "modulename": "causy.workspaces.models", "qualname": "Experiment.pipeline", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.workspaces.models.Experiment.dataloader": {"fullname": "causy.workspaces.models.Experiment.dataloader", "modulename": "causy.workspaces.models", "qualname": "Experiment.dataloader", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.workspaces.models.Experiment.variables": {"fullname": "causy.workspaces.models.Experiment.variables", "modulename": "causy.workspaces.models", "qualname": "Experiment.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool]]]"}, "causy.workspaces.models.Experiment.model_config": {"fullname": "causy.workspaces.models.Experiment.model_config", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.workspaces.models.Experiment.model_fields": {"fullname": "causy.workspaces.models.Experiment.model_fields", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'pipeline': FieldInfo(annotation=str, required=True), 'dataloader': FieldInfo(annotation=str, required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool]], NoneType], required=False, default={})}"}, "causy.workspaces.models.Experiment.model_computed_fields": {"fullname": "causy.workspaces.models.Experiment.model_computed_fields", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.workspaces.models.Workspace": {"fullname": "causy.workspaces.models.Workspace", "modulename": "causy.workspaces.models", "qualname": "Workspace", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.workspaces.models.Workspace.name": {"fullname": "causy.workspaces.models.Workspace.name", "modulename": "causy.workspaces.models", "qualname": "Workspace.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.workspaces.models.Workspace.author": {"fullname": "causy.workspaces.models.Workspace.author", "modulename": "causy.workspaces.models", "qualname": "Workspace.author", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.workspaces.models.Workspace.pipelines": {"fullname": "causy.workspaces.models.Workspace.pipelines", "modulename": "causy.workspaces.models", "qualname": "Workspace.pipelines", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, causy.models.Algorithm | causy.models.AlgorithmReference]]"}, "causy.workspaces.models.Workspace.dataloaders": {"fullname": "causy.workspaces.models.Workspace.dataloaders", "modulename": "causy.workspaces.models", "qualname": "Workspace.dataloaders", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, causy.data_loader.DataLoaderReference]]"}, "causy.workspaces.models.Workspace.experiments": {"fullname": "causy.workspaces.models.Workspace.experiments", "modulename": "causy.workspaces.models", "qualname": "Workspace.experiments", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, causy.workspaces.models.Experiment]]"}, "causy.workspaces.models.Workspace.model_config": {"fullname": "causy.workspaces.models.Workspace.model_config", "modulename": "causy.workspaces.models", "qualname": "Workspace.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.workspaces.models.Workspace.model_fields": {"fullname": "causy.workspaces.models.Workspace.model_fields", "modulename": "causy.workspaces.models", "qualname": "Workspace.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'author': FieldInfo(annotation=Union[str, NoneType], required=True), 'pipelines': FieldInfo(annotation=Union[Dict[str, Union[Algorithm, AlgorithmReference]], NoneType], required=True), 'dataloaders': FieldInfo(annotation=Union[Dict[str, DataLoaderReference], NoneType], required=True), 'experiments': FieldInfo(annotation=Union[Dict[str, Experiment], NoneType], required=True)}"}, "causy.workspaces.models.Workspace.model_computed_fields": {"fullname": "causy.workspaces.models.Workspace.model_computed_fields", "modulename": "causy.workspaces.models", "qualname": "Workspace.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}}, "docInfo": {"causy": {"qualname": 0, "fullname": 1, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 58}, "causy.causal_discovery": {"qualname": 0, "fullname": 3, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint": {"qualname": 0, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms": {"qualname": 0, "fullname": 5, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.AVAILABLE_ALGORITHMS": {"qualname": 2, "fullname": 7, "annotation": 0, "default_value": 40, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.fci": {"qualname": 0, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension": {"qualname": 1, "fullname": 7, "annotation": 0, "default_value": 0, "signature": 0, "bases": 5, "doc": 277}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin": {"qualname": 2, "fullname": 8, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin.inducing_path_exists": {"qualname": 5, "fullname": 11, "annotation": 0, "default_value": 0, "signature": 81, "bases": 0, "doc": 72}, "causy.causal_discovery.constraint.algorithms.pc": {"qualname": 0, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.PC_DEFAULT_THRESHOLD": {"qualname": 3, "fullname": 9, "annotation": 0, "default_value": 2, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.PC_ORIENTATION_RULES": {"qualname": 3, "fullname": 9, "annotation": 0, 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{"docs": {}, "df": 0, "t": {"docs": {"causy.sample_generator.IIDSampleGenerator": {"tf": 2.8284271247461903}, "causy.sample_generator.TimeseriesSampleGenerator": {"tf": 4.47213595499958}}, "df": 2}}}}}}}, "pipeline": ["trimmer"], "_isPrebuiltIndex": true}; + /** pdoc search index */const docs = {"version": "0.9.5", "fields": ["qualname", "fullname", "annotation", "default_value", "signature", "bases", "doc"], "ref": "fullname", "documentStore": {"docs": {"causy": {"fullname": "causy", "modulename": "causy", "kind": "module", "doc": "

causy

\n\n

Causal discovery made easy. Causy allows you to use and implement causal discovery algorithms with easy to use, extend and maintain pipelines. It is built based on pytorch which allows you to run the algorithms on CPUs as well as GPUs seamlessly.

\n\n

Learn more at https://causy.dev.

\n"}, "causy.causal_discovery": {"fullname": "causy.causal_discovery", "modulename": "causy.causal_discovery", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint": {"fullname": "causy.causal_discovery.constraint", "modulename": "causy.causal_discovery.constraint", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms": {"fullname": "causy.causal_discovery.constraint.algorithms", "modulename": "causy.causal_discovery.constraint.algorithms", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.AVAILABLE_ALGORITHMS": {"fullname": "causy.causal_discovery.constraint.algorithms.AVAILABLE_ALGORITHMS", "modulename": "causy.causal_discovery.constraint.algorithms", "qualname": "AVAILABLE_ALGORITHMS", "kind": "variable", "doc": "

\n", "default_value": "{'PC': <class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>, 'ParallelPC': <class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>}"}, "causy.causal_discovery.constraint.algorithms.fci": {"fullname": "causy.causal_discovery.constraint.algorithms.fci", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, typing.Generic[~ExtensionType]"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension.GraphAccessMixin", "kind": "class", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin.inducing_path_exists": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin.inducing_path_exists", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension.GraphAccessMixin.inducing_path_exists", "kind": "function", "doc": "

Check if an inducing path from u to v exists.\nAn inducing path from u to v is a directed reference from u to v on which all mediators are colliders.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if an inducing path exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.causal_discovery.constraint.algorithms.pc": {"fullname": "causy.causal_discovery.constraint.algorithms.pc", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.pc.PC_DEFAULT_THRESHOLD": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_DEFAULT_THRESHOLD", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_DEFAULT_THRESHOLD", "kind": "variable", "doc": "

\n", "default_value": "0.05"}, "causy.causal_discovery.constraint.algorithms.pc.PC_ORIENTATION_RULES": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_ORIENTATION_RULES", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_ORIENTATION_RULES", "kind": "variable", "doc": "

\n", "default_value": "[ColliderTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Collider Test', needs_unapplied_actions=True, apply_synchronous=False, conflict_resolution_strategy=<ColliderTestConflictResolutionStrategies.KEEP_FIRST: 'KEEP_FIRST'>, name='causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest'), Loop(pipeline_steps=[NonColliderTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Non-Collider Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest'), FurtherOrientTripleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Further Orient Triple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest'), OrientQuadrupleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Orient Quadruple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest'), FurtherOrientQuadrupleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Further Orient Quadruple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest')], exit_condition=ExitOnNoActions(name='causy.common_pipeline_steps.exit_conditions.ExitOnNoActions'), display_name='Orientation Rules Loop', name='causy.common_pipeline_steps.logic.Loop')]"}, "causy.causal_discovery.constraint.algorithms.pc.PC_GRAPH_UI_EXTENSION": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_GRAPH_UI_EXTENSION", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_GRAPH_UI_EXTENSION", "kind": "variable", "doc": "

\n", "default_value": "GraphUIExtension(edges=[DirectedEdgeUIConfig(edge_type='DIRECTED', default_ui_config=EdgeUIConfig(color='#333', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='correlation', animated=True, label='Direct Effect: ${correlation.toFixed(4)}'), conditional_ui_configs=[ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#f00000', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.LESS: 'LESS'>), ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#0f0fff', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.GREATER: 'GREATER'>)]), UndirectedEdgeUIConfig(edge_type='UNDIRECTED', default_ui_config=EdgeUIConfig(color='#333', width=4, style='solid', marker_start=None, marker_end=None, label_field='direct_effect', animated=False, label='Correlation: ${correlation.toFixed(4)}'), conditional_ui_configs=None)], name='causy.contrib.graph_ui.GraphUIExtension')"}, "causy.causal_discovery.constraint.algorithms.pc.PC_EDGE_TYPES": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_EDGE_TYPES", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_EDGE_TYPES", "kind": "variable", "doc": "

\n", "default_value": "[DIRECTED, UNDIRECTED]"}, "causy.causal_discovery.constraint.algorithms.pc.PC": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.PCClassic": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PCClassic", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PCClassic", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.PCStable": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PCStable", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PCStable", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.ParallelPC": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.ParallelPC", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "ParallelPC", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.independence_tests": {"fullname": "causy.causal_discovery.constraint.independence_tests", "modulename": "causy.causal_discovery.constraint.independence_tests", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.independence_tests.common": {"fullname": "causy.causal_discovery.constraint.independence_tests.common", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.independence_tests.common.logger": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.logger", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.causal_discovery.constraint.independence_tests.common (WARNING)>"}, "causy.causal_discovery.constraint.independence_tests.common.CorrelationCoefficientTest": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.CorrelationCoefficientTest", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "CorrelationCoefficientTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.PartialCorrelationTest": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.PartialCorrelationTest", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "PartialCorrelationTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestMatrix": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestMatrix", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "ExtendedPartialCorrelationTestMatrix", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.partial_correlation_regression": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.partial_correlation_regression", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "partial_correlation_regression", "kind": "function", "doc": "

Compute the partial correlation coefficient between x and y controlling for other variables in z using linear regression.

\n\n

Arguments:\nx, y : torch.Tensor : Variables for which the partial correlation is computed.\nz : torch.Tensor : Other variables used to control for in the partial correlation.

\n\n

Returns:\npartial_corr : torch.Tensor : Partial correlation coefficient between x and y.

\n", "signature": "(x, y, z):", "funcdef": "def"}, "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestLinearRegression": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestLinearRegression", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "ExtendedPartialCorrelationTestLinearRegression", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules": {"fullname": "causy.causal_discovery.constraint.orientation_rules", "modulename": "causy.causal_discovery.constraint.orientation_rules", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.fci": {"fullname": "causy.causal_discovery.constraint.orientation_rules.fci", "modulename": "causy.causal_discovery.constraint.orientation_rules.fci", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.fci.ColliderRuleFCI": {"fullname": "causy.causal_discovery.constraint.orientation_rules.fci.ColliderRuleFCI", "modulename": "causy.causal_discovery.constraint.orientation_rules.fci", "qualname": "ColliderRuleFCI", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.pc.logger": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.logger", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.causal_discovery.constraint.orientation_rules.pc (WARNING)>"}, "causy.causal_discovery.constraint.orientation_rules.pc.filter_unapplied_actions": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.filter_unapplied_actions", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "filter_unapplied_actions", "kind": "function", "doc": "

Filter out actions that have not been applied to the graph yet.

\n\n
Parameters
\n\n
    \n
  • actions: list of actions
    • \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

list of actions that have not been applied to the graph yet

\n
\n", "signature": "(actions, u, v):", "funcdef": "def"}, "causy.causal_discovery.constraint.orientation_rules.pc.generate_restores": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.generate_restores", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "generate_restores", "kind": "function", "doc": "

Generate restore actions for unapplied actions.

\n\n
Parameters
\n\n
    \n
  • unapplied_actions: list of unapplied actions
    • \n
  • x: node x
    • \n
  • y: node y
    • \n
\n\n
Returns
\n\n
\n

list of restore actions

\n
\n", "signature": "(unapplied_actions):", "funcdef": "def"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies", "kind": "class", "doc": "

Enum for the conflict resolution strategies for the ColliderTest.

\n", "bases": "builtins.str, enum.Enum"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_FIRST": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_FIRST", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies.KEEP_FIRST", "kind": "variable", "doc": "

\n", "default_value": "<ColliderTestConflictResolutionStrategies.KEEP_FIRST: 'KEEP_FIRST'>"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_LAST": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_LAST", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies.KEEP_LAST", "kind": "variable", "doc": "

\n", "default_value": "<ColliderTestConflictResolutionStrategies.KEEP_LAST: 'KEEP_LAST'>"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest.conflict_resolution_strategy": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest.conflict_resolution_strategy", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTest.conflict_resolution_strategy", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference]"}, "causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "NonColliderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "FurtherOrientTripleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "OrientQuadrupleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "FurtherOrientQuadrupleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.cli": {"fullname": "causy.cli", "modulename": "causy.cli", "kind": "module", "doc": "

\n"}, "causy.cli.app": {"fullname": "causy.cli.app", "modulename": "causy.cli", "qualname": "app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.cli.eject": {"fullname": "causy.cli.eject", "modulename": "causy.cli", "qualname": "eject", "kind": "function", "doc": "

\n", "signature": "(algorithm: str, output_file: str):", "funcdef": "def"}, "causy.cli.execute": {"fullname": "causy.cli.execute", "modulename": "causy.cli", "qualname": "execute", "kind": "function", "doc": "

\n", "signature": "(\tdata_file: str,\tpipeline: str = None,\talgorithm: str = None,\toutput_file: str = None,\tlog_level: str = 'ERROR'):", "funcdef": "def"}, "causy.common_pipeline_steps": {"fullname": "causy.common_pipeline_steps", "modulename": "causy.common_pipeline_steps", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.calculation": {"fullname": "causy.common_pipeline_steps.calculation", "modulename": "causy.common_pipeline_steps.calculation", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.calculation.CalculatePearsonCorrelations": {"fullname": "causy.common_pipeline_steps.calculation.CalculatePearsonCorrelations", "modulename": "causy.common_pipeline_steps.calculation", "qualname": "CalculatePearsonCorrelations", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.common_pipeline_steps.exit_conditions": {"fullname": "causy.common_pipeline_steps.exit_conditions", "modulename": "causy.common_pipeline_steps.exit_conditions", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.ExitConditionInterface"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.check": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.check", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.check", "kind": "function", "doc": "

Check if there are no actions taken in the last iteration and if so, break the loop\nIf it is the first iteration, do not break the loop (we need to execute the first step)

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • graph_model_instance_: the graph model instance
    • \n
  • actions_taken: the actions taken in the last iteration
    • \n
  • iteration: iteration number
    • \n
\n\n
Returns
\n\n
\n

True if you want to break an iteration, False otherwise

\n
\n", "signature": "(self, graph, graph_model_instance_, actions_taken, iteration) -> bool:", "funcdef": "def"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_config": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_config", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_fields": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_fields", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_computed_fields": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_computed_fields", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.common_pipeline_steps.logic": {"fullname": "causy.common_pipeline_steps.logic", "modulename": "causy.common_pipeline_steps.logic", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.logic.Loop": {"fullname": "causy.common_pipeline_steps.logic.Loop", "modulename": "causy.common_pipeline_steps.logic", "qualname": "Loop", "kind": "class", "doc": "

A loop which executes a list of pipeline_steps until the exit_condition is met.

\n", "bases": "causy.interfaces.LogicStepInterface, typing.Generic[~LogicStepInterfaceType]"}, "causy.common_pipeline_steps.logic.ApplyActionsTogether": {"fullname": "causy.common_pipeline_steps.logic.ApplyActionsTogether", "modulename": "causy.common_pipeline_steps.logic", "qualname": "ApplyActionsTogether", "kind": "class", "doc": "

A logic step which collects all actions and only takes them at the end of the pipeline

\n", "bases": "causy.interfaces.LogicStepInterface, typing.Generic[~LogicStepInterfaceType]"}, "causy.common_pipeline_steps.placeholder": {"fullname": "causy.common_pipeline_steps.placeholder", "modulename": "causy.common_pipeline_steps.placeholder", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.placeholder.logger": {"fullname": "causy.common_pipeline_steps.placeholder.logger", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.common_pipeline_steps.placeholder (WARNING)>"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_str": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_str", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_str", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.StringVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_int": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_int", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_int", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.IntegerVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_float": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_float", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_float", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.FloatVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_bool": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_bool", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_bool", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.BoolVariable]"}, "causy.data_loader": {"fullname": "causy.data_loader", "modulename": "causy.data_loader", "kind": "module", "doc": "

\n"}, "causy.data_loader.DataLoaderType": {"fullname": "causy.data_loader.DataLoaderType", "modulename": "causy.data_loader", "qualname": "DataLoaderType", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.data_loader.DataLoaderType.DYNAMIC": {"fullname": "causy.data_loader.DataLoaderType.DYNAMIC", "modulename": "causy.data_loader", "qualname": "DataLoaderType.DYNAMIC", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.DYNAMIC: 'dynamic'>"}, "causy.data_loader.DataLoaderType.JSON": {"fullname": "causy.data_loader.DataLoaderType.JSON", "modulename": "causy.data_loader", "qualname": "DataLoaderType.JSON", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.JSON: 'json'>"}, "causy.data_loader.DataLoaderType.JSONL": {"fullname": "causy.data_loader.DataLoaderType.JSONL", "modulename": "causy.data_loader", "qualname": "DataLoaderType.JSONL", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.JSONL: 'jsonl'>"}, "causy.data_loader.DataLoaderReference": {"fullname": "causy.data_loader.DataLoaderReference", "modulename": "causy.data_loader", "qualname": "DataLoaderReference", "kind": "class", "doc": "

represents a single data loader

\n\n
Parameters
\n\n
    \n
  • type: the type of dataloader
    • \n
  • reference: path to either the python class which can be executed to load the data or the data source file itself
    • \n
\n", "bases": "pydantic.main.BaseModel"}, "causy.data_loader.DataLoaderReference.type": {"fullname": "causy.data_loader.DataLoaderReference.type", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.type", "kind": "variable", "doc": "

\n", "annotation": ": causy.data_loader.DataLoaderType"}, "causy.data_loader.DataLoaderReference.reference": {"fullname": "causy.data_loader.DataLoaderReference.reference", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.DataLoaderReference.options": {"fullname": "causy.data_loader.DataLoaderReference.options", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.options", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]"}, "causy.data_loader.DataLoaderReference.model_config": {"fullname": "causy.data_loader.DataLoaderReference.model_config", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.data_loader.DataLoaderReference.model_fields": {"fullname": "causy.data_loader.DataLoaderReference.model_fields", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'type': FieldInfo(annotation=DataLoaderType, required=True), 'reference': FieldInfo(annotation=str, required=True), 'options': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None)}"}, "causy.data_loader.DataLoaderReference.model_computed_fields": {"fullname": "causy.data_loader.DataLoaderReference.model_computed_fields", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.data_loader.AbstractDataLoader": {"fullname": "causy.data_loader.AbstractDataLoader", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.data_loader.AbstractDataLoader.reference": {"fullname": "causy.data_loader.AbstractDataLoader.reference", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.AbstractDataLoader.options": {"fullname": "causy.data_loader.AbstractDataLoader.options", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.options", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]", "default_value": "None"}, "causy.data_loader.AbstractDataLoader.load": {"fullname": "causy.data_loader.AbstractDataLoader.load", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.AbstractDataLoader.hash": {"fullname": "causy.data_loader.AbstractDataLoader.hash", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.hash", "kind": "function", "doc": "

returns a hash of the data that is loaded

\n\n
Returns
\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.data_loader.FileDataLoader": {"fullname": "causy.data_loader.FileDataLoader", "modulename": "causy.data_loader", "qualname": "FileDataLoader", "kind": "class", "doc": "

A data loader which loads data from a file reference (e.g. json, csv, etc.)

\n", "bases": "AbstractDataLoader, abc.ABC"}, "causy.data_loader.FileDataLoader.reference": {"fullname": "causy.data_loader.FileDataLoader.reference", "modulename": "causy.data_loader", "qualname": "FileDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.FileDataLoader.options": {"fullname": "causy.data_loader.FileDataLoader.options", "modulename": "causy.data_loader", "qualname": "FileDataLoader.options", "kind": "variable", "doc": "

\n", "default_value": "None"}, "causy.data_loader.FileDataLoader.hash": {"fullname": "causy.data_loader.FileDataLoader.hash", "modulename": "causy.data_loader", "qualname": "FileDataLoader.hash", "kind": "function", "doc": "

returns a hash of the data that is loaded

\n\n
Returns
\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.data_loader.JSONDataLoader": {"fullname": "causy.data_loader.JSONDataLoader", "modulename": "causy.data_loader", "qualname": "JSONDataLoader", "kind": "class", "doc": "

A data loader which loads data from a json file

\n", "bases": "FileDataLoader"}, "causy.data_loader.JSONDataLoader.load": {"fullname": "causy.data_loader.JSONDataLoader.load", "modulename": "causy.data_loader", "qualname": "JSONDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.JSONLDataLoader": {"fullname": "causy.data_loader.JSONLDataLoader", "modulename": "causy.data_loader", "qualname": "JSONLDataLoader", "kind": "class", "doc": "

A data loader which loads data from a jsonl file

\n", "bases": "FileDataLoader"}, "causy.data_loader.JSONLDataLoader.load": {"fullname": "causy.data_loader.JSONLDataLoader.load", "modulename": "causy.data_loader", "qualname": "JSONLDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.DynamicDataLoader": {"fullname": "causy.data_loader.DynamicDataLoader", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader", "kind": "class", "doc": "

A data loader which loads another data loader dynamically based on the reference

\n", "bases": "AbstractDataLoader"}, "causy.data_loader.DynamicDataLoader.reference": {"fullname": "causy.data_loader.DynamicDataLoader.reference", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.DynamicDataLoader.data_loader": {"fullname": "causy.data_loader.DynamicDataLoader.data_loader", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.data_loader", "kind": "variable", "doc": "

\n", "annotation": ": causy.data_loader.AbstractDataLoader"}, "causy.data_loader.DynamicDataLoader.options": {"fullname": "causy.data_loader.DynamicDataLoader.options", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.options", "kind": "variable", "doc": "

\n", "default_value": "None"}, "causy.data_loader.DynamicDataLoader.load": {"fullname": "causy.data_loader.DynamicDataLoader.load", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.DATA_LOADERS": {"fullname": "causy.data_loader.DATA_LOADERS", "modulename": "causy.data_loader", "qualname": "DATA_LOADERS", "kind": "variable", "doc": "

\n", "default_value": "{<DataLoaderType.JSON: 'json'>: <class 'causy.data_loader.JSONDataLoader'>, <DataLoaderType.JSONL: 'jsonl'>: <class 'causy.data_loader.JSONLDataLoader'>, <DataLoaderType.DYNAMIC: 'dynamic'>: <class 'causy.data_loader.DynamicDataLoader'>}"}, "causy.data_loader.load_data_loader": {"fullname": "causy.data_loader.load_data_loader", "modulename": "causy.data_loader", "qualname": "load_data_loader", "kind": "function", "doc": "

loads the data loader based on the reference

\n\n
Parameters
\n\n
    \n
  • reference: a data loader reference
    • \n
\n\n
Returns
\n", "signature": "(\treference: causy.data_loader.DataLoaderReference) -> causy.data_loader.AbstractDataLoader:", "funcdef": "def"}, "causy.edge_types": {"fullname": "causy.edge_types", "modulename": "causy.edge_types", "kind": "module", "doc": "

\n"}, "causy.edge_types.EdgeTypeEnum": {"fullname": "causy.edge_types.EdgeTypeEnum", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.edge_types.EdgeTypeEnum.DIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.DIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.DIRECTED: 'directed'>"}, "causy.edge_types.EdgeTypeEnum.UNDIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.UNDIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.UNDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.UNDIRECTED: 'undirected'>"}, "causy.edge_types.EdgeTypeEnum.BIDIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.BIDIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.BIDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.BIDIRECTED: 'bidirected'>"}, "causy.edge_types.DirectedEdge": {"fullname": "causy.edge_types.DirectedEdge", "modulename": "causy.edge_types", "qualname": "DirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.DirectedEdgeUIConfig": {"fullname": "causy.edge_types.DirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.DirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.DirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.DirectedEdgeUIConfig.conditional_ui_configs": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.conditional_ui_configs", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.conditional_ui_configs", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.contrib.graph_ui.ConditionalEdgeUIConfig]]"}, "causy.edge_types.DirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.DirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='DIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='correlation', animated=True, label='Direct Effect: ${correlation.toFixed(4)}')), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=[ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#f00000', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.LESS: 'LESS'>), ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#0f0fff', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.GREATER: 'GREATER'>)])}"}, "causy.edge_types.DirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.UndirectedEdge": {"fullname": "causy.edge_types.UndirectedEdge", "modulename": "causy.edge_types", "qualname": "UndirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.UndirectedEdgeUIConfig": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.UndirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.UndirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.UndirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.UndirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='UNDIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='solid', marker_start=None, marker_end=None, label_field='direct_effect', animated=False, label='Correlation: ${correlation.toFixed(4)}')), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=None)}"}, "causy.edge_types.UndirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.BiDirectedEdge": {"fullname": "causy.edge_types.BiDirectedEdge", "modulename": "causy.edge_types", "qualname": "BiDirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.BiDirectedEdgeUIConfig": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.BiDirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.BiDirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='BIDIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='solid', marker_start='ArrowClosed', marker_end='ArrowClosed', label_field='direct_effect', animated=False, label=None)), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=None)}"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.EDGE_TYPES": {"fullname": "causy.edge_types.EDGE_TYPES", "modulename": "causy.edge_types", "qualname": "EDGE_TYPES", "kind": "variable", "doc": "

\n", "default_value": "{'DIRECTED': <class 'causy.edge_types.DirectedEdge'>, 'UNDIRECTED': <class 'causy.edge_types.UndirectedEdge'>, 'BIDIRECTED': <class 'causy.edge_types.BiDirectedEdge'>}"}, "causy.generators": {"fullname": "causy.generators", "modulename": "causy.generators", "kind": "module", "doc": "

\n"}, "causy.generators.logger": {"fullname": "causy.generators.logger", "modulename": "causy.generators", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.generators (WARNING)>"}, "causy.generators.AllCombinationsGenerator": {"fullname": "causy.generators.AllCombinationsGenerator", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator", "kind": "class", "doc": "

Generates all combinations of nodes in the graph in accordance with the configured amount of nodes to compare.\nYields node combinations as tuples, but only in one ordering, i.e. mathematically it returns sets.\ne.g. if your graph consists of the nodes [X, Y, Z] and you want to compare 2 nodes,\nit will yield (X, Y), (X, Z), (Y, Z). It will not additionally yield (Y, X), (Z, X), (Z, Y).

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.AllCombinationsGenerator.generate": {"fullname": "causy.generators.AllCombinationsGenerator.generate", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.AllCombinationsGenerator.model_config": {"fullname": "causy.generators.AllCombinationsGenerator.model_config", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.AllCombinationsGenerator.model_fields": {"fullname": "causy.generators.AllCombinationsGenerator.model_fields", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.generators.AllCombinationsGenerator.model_computed_fields": {"fullname": "causy.generators.AllCombinationsGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.PairsWithEdgesInBetweenGenerator": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator", "kind": "class", "doc": "

Generates all pairs of nodes that have edges in between them. It does not matter if the edge is directed or not.\nHowever, if it is an edge which points in both/no directions, it will be iterated over them twice.

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.PairsWithEdgesInBetweenGenerator.__init__": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.__init__", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(\t*args,\tchunk_size: Union[int, causy.variables.VariableReference, NoneType] = None,\tchunked: Union[bool, causy.variables.VariableReference, NoneType] = None,\t**kwargs)"}, "causy.generators.PairsWithEdgesInBetweenGenerator.chunk_size": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.chunk_size", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.chunk_size", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.generators.PairsWithEdgesInBetweenGenerator.chunked": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.chunked", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.generators.PairsWithEdgesInBetweenGenerator.generate": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.generate", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_config": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_config", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_fields": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_fields", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None), 'chunk_size': FieldInfo(annotation=Union[int, VariableReference], required=False, default=100)}"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_computed_fields": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.PairsWithNeighboursGenerator": {"fullname": "causy.generators.PairsWithNeighboursGenerator", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator", "kind": "class", "doc": "

Generates all combinations of pairs of nodes that are neighbours and the neighbours of the first input node.\ne.g. if your graph consists of the nodes [X, Y, Z, W, V] your output could be:\n[X, Y, neighbours(X)], [Y, X, neighbours(Y)], [X, Z, neighbours(X)], [Z, X, neighbours(Z)], ...\n(if, among others, X and Y are neighbours and X and Z are neighbours)

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.PairsWithNeighboursGenerator.__init__": {"fullname": "causy.generators.PairsWithNeighboursGenerator.__init__", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(*args, **kwargs)"}, "causy.generators.PairsWithNeighboursGenerator.shuffle_combinations": {"fullname": "causy.generators.PairsWithNeighboursGenerator.shuffle_combinations", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.shuffle_combinations", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.generators.PairsWithNeighboursGenerator.chunked": {"fullname": "causy.generators.PairsWithNeighboursGenerator.chunked", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.generators.PairsWithNeighboursGenerator.generate": {"fullname": "causy.generators.PairsWithNeighboursGenerator.generate", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.PairsWithNeighboursGenerator.model_config": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_config", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.PairsWithNeighboursGenerator.model_fields": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_fields", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference], required=False, default=True), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference], required=False, default=True)}"}, "causy.generators.PairsWithNeighboursGenerator.model_computed_fields": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.RandomSampleGenerator": {"fullname": "causy.generators.RandomSampleGenerator", "modulename": "causy.generators", "qualname": "RandomSampleGenerator", "kind": "class", "doc": "

Executes another generator and returns a random sample of the results

\n", "bases": "causy.interfaces.GeneratorInterface, pydantic.main.BaseModel"}, "causy.generators.RandomSampleGenerator.__init__": {"fullname": "causy.generators.RandomSampleGenerator.__init__", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(\t*args,\tgenerator: Union[causy.interfaces.GeneratorInterface, Dict[<built-in function any>, <built-in function any>], NoneType] = None,\t**kwargs)"}, "causy.generators.RandomSampleGenerator.every_nth": {"fullname": "causy.generators.RandomSampleGenerator.every_nth", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.every_nth", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.generators.RandomSampleGenerator.generator": {"fullname": "causy.generators.RandomSampleGenerator.generator", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.generators.RandomSampleGenerator.generate": {"fullname": "causy.generators.RandomSampleGenerator.generate", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.generate", "kind": "function", "doc": "

Executes another generator and returns a random sample of the results

\n\n
Parameters
\n\n
    \n
  • graph:
    • \n
  • graph_model_instance_:
    • \n
\n\n
Returns
\n\n
\n

yields a random sample of the results

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.generators.RandomSampleGenerator.model_config": {"fullname": "causy.generators.RandomSampleGenerator.model_config", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.RandomSampleGenerator.model_fields": {"fullname": "causy.generators.RandomSampleGenerator.model_fields", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference], required=False, default=100), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.generators.RandomSampleGenerator.model_computed_fields": {"fullname": "causy.generators.RandomSampleGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.graph": {"fullname": "causy.graph", "modulename": "causy.graph", "kind": "module", "doc": "

\n"}, "causy.graph.logger": {"fullname": "causy.graph.logger", "modulename": "causy.graph", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.graph (WARNING)>"}, "causy.graph.Node": {"fullname": "causy.graph.Node", "modulename": "causy.graph", "qualname": "Node", "kind": "class", "doc": "

A node is a variable in the graph. It has a name, an id and values. The values are stored as a torch.Tensor.\nA node can also have metadata.

\n", "bases": "causy.interfaces.NodeInterface"}, "causy.graph.Node.name": {"fullname": "causy.graph.Node.name", "modulename": "causy.graph", "qualname": "Node.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.graph.Node.id": {"fullname": "causy.graph.Node.id", "modulename": "causy.graph", "qualname": "Node.id", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.graph.Node.values": {"fullname": "causy.graph.Node.values", "modulename": "causy.graph", "qualname": "Node.values", "kind": "variable", "doc": "

\n", "annotation": ": Optional[torch.Tensor]"}, "causy.graph.Node.metadata": {"fullname": "causy.graph.Node.metadata", "modulename": "causy.graph", "qualname": "Node.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]]"}, "causy.graph.Node.model_config": {"fullname": "causy.graph.Node.model_config", "modulename": "causy.graph", "qualname": "Node.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.graph.Node.model_fields": {"fullname": "causy.graph.Node.model_fields", "modulename": "causy.graph", "qualname": "Node.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[Tensor, NoneType], required=False, default=None), 'metadata': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], NoneType], required=False, default=None)}"}, "causy.graph.Node.model_computed_fields": {"fullname": "causy.graph.Node.model_computed_fields", "modulename": "causy.graph", "qualname": "Node.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.Edge": {"fullname": "causy.graph.Edge", "modulename": "causy.graph", "qualname": "Edge", "kind": "class", "doc": "

An edge is a connection between two nodes. It has a direction defined by the edge_type and metadata.\nA metadata example could be the p-value of a statistical test.\nAn edge can be e.g. undirected, directed or bidirected. Which option is available/chosen depends on the algorithm and the current state of the graph.\nBy default an edge always has an undirected and a directed edge_type.

\n", "bases": "causy.interfaces.EdgeInterface"}, "causy.graph.Edge.__init__": {"fullname": "causy.graph.Edge.__init__", "modulename": "causy.graph", "qualname": "Edge.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(*args, **kwargs)"}, "causy.graph.Edge.u": {"fullname": "causy.graph.Edge.u", "modulename": "causy.graph", "qualname": "Edge.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.graph.Edge.v": {"fullname": "causy.graph.Edge.v", "modulename": "causy.graph", "qualname": "Edge.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.graph.Edge.edge_type": {"fullname": "causy.graph.Edge.edge_type", "modulename": "causy.graph", "qualname": "Edge.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.EdgeTypeInterface"}, "causy.graph.Edge.metadata": {"fullname": "causy.graph.Edge.metadata", "modulename": "causy.graph", "qualname": "Edge.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]]"}, "causy.graph.Edge.deleted": {"fullname": "causy.graph.Edge.deleted", "modulename": "causy.graph", "qualname": "Edge.deleted", "kind": "variable", "doc": "

\n", "annotation": ": Optional[bool]"}, "causy.graph.Edge.model_config": {"fullname": "causy.graph.Edge.model_config", "modulename": "causy.graph", "qualname": "Edge.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.graph.Edge.model_fields": {"fullname": "causy.graph.Edge.model_fields", "modulename": "causy.graph", "qualname": "Edge.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'edge_type': FieldInfo(annotation=EdgeTypeInterface, required=True), 'metadata': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], NoneType], required=False, default=None), 'deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False)}"}, "causy.graph.Edge.model_computed_fields": {"fullname": "causy.graph.Edge.model_computed_fields", "modulename": "causy.graph", "qualname": "Edge.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.GraphError": {"fullname": "causy.graph.GraphError", "modulename": "causy.graph", "qualname": "GraphError", "kind": "class", "doc": "

Common base class for all non-exit exceptions.

\n", "bases": "builtins.Exception"}, "causy.graph.GraphBaseAccessMixin": {"fullname": "causy.graph.GraphBaseAccessMixin", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin", "kind": "class", "doc": "

\n"}, "causy.graph.GraphBaseAccessMixin.directed_edge_is_soft_deleted": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_edge_is_soft_deleted", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_edge_is_soft_deleted", "kind": "function", "doc": "

Check if an edge is soft deleted

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.parents_of_node": {"fullname": "causy.graph.GraphBaseAccessMixin.parents_of_node", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.parents_of_node", "kind": "function", "doc": "

Return all parents of a node u

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
\n\n
Returns
\n\n
\n

list of nodes (parents)

\n
\n", "signature": "(self, u: Union[causy.graph.Node, str]):", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_exists", "kind": "function", "doc": "

Check if any edge exists between u and v. Cases: u -> v, u <-> v, u <- v

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if any edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.directed_edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_edge_exists", "kind": "function", "doc": "

Check if a directed edge exists between u and v. Cases: u -> v, u <-> v

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if a directed edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.node_by_id": {"fullname": "causy.graph.GraphBaseAccessMixin.node_by_id", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.node_by_id", "kind": "function", "doc": "

Retrieve a node by its id

\n\n
Parameters
\n\n
    \n
  • id_:
    • \n
\n\n
Returns
\n", "signature": "(self, id_: str) -> Optional[causy.graph.Node]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_value": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_value", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_value", "kind": "function", "doc": "

retrieve the value of an edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> Optional[Dict]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_type": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_type", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_type", "kind": "function", "doc": "

retrieve the value of an edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> Optional[causy.interfaces.EdgeTypeInterface]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.undirected_edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.undirected_edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.undirected_edge_exists", "kind": "function", "doc": "

Check if an undirected edge exists between u and v. Note: currently, an undirected edges is implemented just as\na directed edge. However, they are two functions as they mean different things in different algorithms.\nCurrently, this function is used in the PC algorithm, where an undirected edge is an edge which could not be\noriented in any direction by orientation rules.\nLater, a cohersive naming scheme should be implemented.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if an undirected edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.get_siblings": {"fullname": "causy.graph.GraphBaseAccessMixin.get_siblings", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.get_siblings", "kind": "function", "doc": "

Get the set of nodes that are connected to the node v with an undirected edge.

\n\n
Parameters
\n\n
    \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

A set of nodes that are connected to v with an undirected edge.

\n
\n", "signature": "(\tself,\tv: Union[causy.graph.Node, str]) -> Set[Union[causy.graph.Node, str]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.retrieve_edge_history": {"fullname": "causy.graph.GraphBaseAccessMixin.retrieve_edge_history", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.retrieve_edge_history", "kind": "function", "doc": "

Retrieve the edge history

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • action:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\taction: causy.models.TestResultAction = None) -> List[causy.models.TestResult]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.directed_path_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_path_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_path_exists", "kind": "function", "doc": "

Check if a directed path from u to v exists

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if a directed path exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_of_type_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_of_type_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_of_type_exists", "kind": "function", "doc": "

Check if an edge of a specific type exists between u and v.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
  • edge_type: the type of the edge to check for
    • \n
\n\n
Returns
\n\n
\n

True if an edge of this type exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tedge_type: causy.interfaces.EdgeTypeInterface = DIRECTED) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.descendants_of_node": {"fullname": "causy.graph.GraphBaseAccessMixin.descendants_of_node", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.descendants_of_node", "kind": "function", "doc": "

Returns a list of all descendants of the given node in a directed graph, including the input node itself.

\n\n
Parameters
\n\n
    \n
  • u: The node or node ID to find descendants for.
    • \n
\n\n
Returns
\n\n
\n

A list of descendants of a node including the input node itself.

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tvisited=None) -> List[Union[causy.graph.Node, str]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_dag": {"fullname": "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_dag", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.are_nodes_d_separated_dag", "kind": "function", "doc": "

Check if nodes u and v are d-separated given a conditioning set in a DAG. We check whether there is an open path, i.e. a path on which all colliders are in the conditioning set and all non-colliders are not in the conditioning set. If there is no open path, u and v are d-separated.

\n\n
Parameters
\n\n
    \n
  • u: First node
    • \n
  • v: Second node
    • \n
  • conditioning_set: Set of nodes to condition on
    • \n
\n\n
Returns
\n\n
\n

True if u and v are d-separated given conditioning_set, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tconditioning_set: List[Union[causy.graph.Node, str]]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_cpdag": {"fullname": "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_cpdag", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.are_nodes_d_separated_cpdag", "kind": "function", "doc": "

Check if nodes u and v are d-separated given a conditioning set in a CPDAG following Perkovic, 2020. (Identifying causal effects in maximally oriented partially directed acyclic graphs)

\n\n
Parameters
\n\n
    \n
  • u: First node
    • \n
  • v: Second node
    • \n
  • conditioning_set: Set of nodes to condition on
    • \n
\n\n
Returns
\n\n
\n

True if u and v are d-separated given conditioning_set, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tconditioning_set: List[Union[causy.graph.Node, str]]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph": {"fullname": "causy.graph.GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph", "kind": "function", "doc": "

\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tvisited=None,\tpath=None) -> List[List[causy.graph.Node]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.retrieve_edges": {"fullname": "causy.graph.GraphBaseAccessMixin.retrieve_edges", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.retrieve_edges", "kind": "function", "doc": "

Retrieve all edges

\n\n
Returns
\n\n
\n

all edges

\n
\n", "signature": "(self) -> List[causy.graph.Edge]:", "funcdef": "def"}, "causy.graph.Graph": {"fullname": "causy.graph.Graph", "modulename": "causy.graph", "qualname": "Graph", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.EdgeTypeInterface.GraphAccessMixin, causy.edge_types.DirectedEdge.GraphAccessMixin, GraphBaseAccessMixin, causy.interfaces.ExtensionInterface.GraphAccessMixin, pydantic.main.BaseModel"}, "causy.graph.Graph.nodes": {"fullname": "causy.graph.Graph.nodes", "modulename": "causy.graph", "qualname": "Graph.nodes", "kind": "variable", "doc": "

\n", "annotation": ": OrderedDict[str, causy.graph.Node]"}, "causy.graph.Graph.edges": {"fullname": "causy.graph.Graph.edges", "modulename": "causy.graph", "qualname": "Graph.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, causy.graph.Edge]]"}, "causy.graph.Graph.edge_history": {"fullname": "causy.graph.Graph.edge_history", "modulename": "causy.graph", "qualname": "Graph.edge_history", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Tuple[str, str], List[causy.models.TestResult]]"}, "causy.graph.Graph.action_history": {"fullname": "causy.graph.Graph.action_history", "modulename": "causy.graph", "qualname": "Graph.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.models.ActionHistoryStep]"}, "causy.graph.Graph.model_config": {"fullname": "causy.graph.Graph.model_config", "modulename": "causy.graph", "qualname": "Graph.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.Graph.model_post_init": {"fullname": "causy.graph.Graph.model_post_init", "modulename": "causy.graph", "qualname": "Graph.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.graph.Graph.model_fields": {"fullname": "causy.graph.Graph.model_fields", "modulename": "causy.graph", "qualname": "Graph.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'nodes': FieldInfo(annotation=OrderedDict[str, Node], required=False, default=OrderedDict()), 'edges': FieldInfo(annotation=Dict[str, Dict[str, Edge]], required=False, default={}), 'edge_history': FieldInfo(annotation=Dict[Tuple[str, str], List[TestResult]], required=False, default={}), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=False, default=[])}"}, "causy.graph.Graph.model_computed_fields": {"fullname": "causy.graph.Graph.model_computed_fields", "modulename": "causy.graph", "qualname": "Graph.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.GraphManager": {"fullname": "causy.graph.GraphManager", "modulename": "causy.graph", "qualname": "GraphManager", "kind": "class", "doc": "

The graph represents the internal data structure of causy. It is a simple graph with nodes and edges.\nBut it supports to be handled as a directed graph, undirected graph and bidirected graph, which is important to implement different algorithms in different stages.\nIt also stores the history of the actions taken on the graph.

\n", "bases": "GraphBaseAccessMixin, causy.interfaces.BaseGraphInterface"}, "causy.graph.GraphManager.__init__": {"fullname": "causy.graph.GraphManager.__init__", "modulename": "causy.graph", "qualname": "GraphManager.__init__", "kind": "function", "doc": "

\n", "signature": "(graph_class=<class 'causy.graph.Graph'>)"}, "causy.graph.GraphManager.nodes": {"fullname": "causy.graph.GraphManager.nodes", "modulename": "causy.graph", "qualname": "GraphManager.nodes", "kind": "variable", "doc": "

\n", "annotation": ": OrderedDict[str, causy.graph.Node]"}, "causy.graph.GraphManager.edges": {"fullname": "causy.graph.GraphManager.edges", "modulename": "causy.graph", "qualname": "GraphManager.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, causy.graph.Edge]]"}, "causy.graph.GraphManager.edge_history": {"fullname": "causy.graph.GraphManager.edge_history", "modulename": "causy.graph", "qualname": "GraphManager.edge_history", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Tuple[str, str], List[causy.models.TestResult]]"}, "causy.graph.GraphManager.action_history": {"fullname": "causy.graph.GraphManager.action_history", "modulename": "causy.graph", "qualname": "GraphManager.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[Dict[str, List[causy.models.TestResult]]]"}, "causy.graph.GraphManager.graph": {"fullname": "causy.graph.GraphManager.graph", "modulename": "causy.graph", "qualname": "GraphManager.graph", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.graph.Graph]", "default_value": "None"}, "causy.graph.GraphManager.get_edge": {"fullname": "causy.graph.GraphManager.get_edge", "modulename": "causy.graph", "qualname": "GraphManager.get_edge", "kind": "function", "doc": "

Get an edge between two nodes

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n\n
\n

the edge

\n
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node) -> causy.graph.Edge:", "funcdef": "def"}, "causy.graph.GraphManager.add_edge": {"fullname": "causy.graph.GraphManager.add_edge", "modulename": "causy.graph", "qualname": "GraphManager.add_edge", "kind": "function", "doc": "

Add an edge to the graph

\n\n
Parameters
\n\n
    \n
  • edge_type: the type of the edge (e.g. undirected, directed, bidirected)
    • \n
  • u: u node
    • \n
  • v: v node
    • \n
  • metadata: metadata of the edge
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict,\tedge_type: causy.interfaces.EdgeTypeInterface = UNDIRECTED):", "funcdef": "def"}, "causy.graph.GraphManager.add_directed_edge": {"fullname": "causy.graph.GraphManager.add_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.add_directed_edge", "kind": "function", "doc": "

Add a directed edge from u to v to the graph

\n\n
Parameters
\n\n
    \n
  • edge_type:
    • \n
  • u: u node
    • \n
  • v: v node
    • \n
  • metadata: metadata of the edge
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict,\tedge_type: causy.interfaces.EdgeTypeInterface = DIRECTED):", "funcdef": "def"}, "causy.graph.GraphManager.add_edge_history": {"fullname": "causy.graph.GraphManager.add_edge_history", "modulename": "causy.graph", "qualname": "GraphManager.add_edge_history", "kind": "function", "doc": "

Add an action to the edge history

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • action:
    • \n
\n\n
Returns
\n", "signature": "(self, u, v, action: causy.models.TestResult):", "funcdef": "def"}, "causy.graph.GraphManager.remove_edge": {"fullname": "causy.graph.GraphManager.remove_edge", "modulename": "causy.graph", "qualname": "GraphManager.remove_edge", "kind": "function", "doc": "

Remove an edge from the graph (undirected)

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tsoft_delete: bool = False):", "funcdef": "def"}, "causy.graph.GraphManager.restore_edge": {"fullname": "causy.graph.GraphManager.restore_edge", "modulename": "causy.graph", "qualname": "GraphManager.restore_edge", "kind": "function", "doc": "

Restore a deleted edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node):", "funcdef": "def"}, "causy.graph.GraphManager.remove_directed_edge": {"fullname": "causy.graph.GraphManager.remove_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.remove_directed_edge", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • soft_delete: does not remove the edge, but marks it as deleted (useful in multithreading)
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tsoft_delete: bool = False):", "funcdef": "def"}, "causy.graph.GraphManager.restore_directed_edge": {"fullname": "causy.graph.GraphManager.restore_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.restore_directed_edge", "kind": "function", "doc": "

Restore a soft deleted edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node):", "funcdef": "def"}, "causy.graph.GraphManager.update_edge": {"fullname": "causy.graph.GraphManager.update_edge", "modulename": "causy.graph", "qualname": "GraphManager.update_edge", "kind": "function", "doc": "

Update an undirected edge in the graph

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
  • value:
    • \n
  • edge_type:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict = None,\tedge_type: causy.interfaces.EdgeTypeInterface = None):", "funcdef": "def"}, "causy.graph.GraphManager.update_directed_edge": {"fullname": "causy.graph.GraphManager.update_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.update_directed_edge", "kind": "function", "doc": "

Update an edge in the graph

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict = None,\tedge_type: causy.interfaces.EdgeTypeInterface = None):", "funcdef": "def"}, "causy.graph.GraphManager.purge_soft_deleted_edges": {"fullname": "causy.graph.GraphManager.purge_soft_deleted_edges", "modulename": "causy.graph", "qualname": "GraphManager.purge_soft_deleted_edges", "kind": "function", "doc": "

Remove all edges that are marked as soft deleted from the graph

\n", "signature": "(self):", "funcdef": "def"}, "causy.graph.GraphManager.add_node": {"fullname": "causy.graph.GraphManager.add_node", "modulename": "causy.graph", "qualname": "GraphManager.add_node", "kind": "function", "doc": "

Add a node to the graph

\n\n
Parameters
\n\n
    \n
  • metadata: add metadata to the node
    • \n
  • name: name of the node
    • \n
  • values: values of the node
    • \n
  • id_: id_ of the node\n:param : node
    • \n
\n\n
Returns
\n\n
\n

created Node

\n
\n", "signature": "(\tself,\tname: str,\tvalues: Union[List[float], torch.Tensor],\tid_: str = None,\tmetadata: Optional[Dict[str, Any]] = None) -> causy.graph.Node:", "funcdef": "def"}, "causy.graph_model": {"fullname": "causy.graph_model", "modulename": "causy.graph_model", "kind": "module", "doc": "

\n"}, "causy.graph_model.logger": {"fullname": "causy.graph_model.logger", "modulename": "causy.graph_model", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.graph_model (WARNING)>"}, "causy.graph_model.AbstractGraphModel": {"fullname": "causy.graph_model.AbstractGraphModel", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel", "kind": "class", "doc": "

The graph model is the main class of causy. It is responsible for creating a graph from data and executing the pipeline_steps.

\n\n

The graph model is responsible for the following tasks:

\n\n
    \n
  • Create a graph from data (create_graph_from_data)
    • \n
  • Execute the pipeline_steps (execute_pipeline_steps)
    • \n
  • Take actions on the graph (execute_pipeline_step & _take_action which is called by execute_pipeline_step)
    • \n
\n\n

It also initializes and takes care of the multiprocessing pool.

\n", "bases": "causy.interfaces.GraphModelInterface, abc.ABC"}, "causy.graph_model.AbstractGraphModel.__init__": {"fullname": "causy.graph_model.AbstractGraphModel.__init__", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.__init__", "kind": "function", "doc": "

\n", "signature": "(graph=None, algorithm: causy.models.Algorithm = None)"}, "causy.graph_model.AbstractGraphModel.algorithm": {"fullname": "causy.graph_model.AbstractGraphModel.algorithm", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.algorithm", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.Algorithm"}, "causy.graph_model.AbstractGraphModel.pipeline_steps": {"fullname": "causy.graph_model.AbstractGraphModel.pipeline_steps", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.interfaces.PipelineStepInterface]"}, "causy.graph_model.AbstractGraphModel.graph": {"fullname": "causy.graph_model.AbstractGraphModel.graph", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.graph", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.BaseGraphInterface"}, "causy.graph_model.AbstractGraphModel.pool": {"fullname": "causy.graph_model.AbstractGraphModel.pool", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.pool", "kind": "variable", "doc": "

\n", "annotation": ": <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f03cc4c8fe0>>"}, "causy.graph_model.AbstractGraphModel.create_graph_from_data": {"fullname": "causy.graph_model.AbstractGraphModel.create_graph_from_data", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.create_graph_from_data", "kind": "function", "doc": "

Create a graph from data

\n\n
Parameters
\n\n
    \n
  • data: is a list of dictionaries or a dictionary with lists
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tdata: Union[List[Dict[str, float]], Dict[str, List[float]], causy.data_loader.AbstractDataLoader]):", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.create_all_possible_edges": {"fullname": "causy.graph_model.AbstractGraphModel.create_all_possible_edges", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.create_all_possible_edges", "kind": "function", "doc": "

Create all possible edges on a graph\nTODO: replace me with the skeleton builders

\n\n
Returns
\n", "signature": "(self):", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_steps": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_steps", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_steps", "kind": "function", "doc": "

Execute all pipeline_steps

\n\n
Returns
\n\n
\n

the steps taken during the step execution

\n
\n", "signature": "(self) -> List[causy.models.ActionHistoryStep]:", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_step_with_progress": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_step_with_progress", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_step_with_progress", "kind": "function", "doc": "

\n", "signature": "(self) -> Generator:", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_step": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_step", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_step", "kind": "function", "doc": "

Execute a single pipeline_step on the graph. either in parallel or in a single process depending on the test_fn.parallel flag

\n\n
Parameters
\n\n
    \n
  • apply_to_graph: if the action should be applied to the graph
    • \n
  • test_fn: the test function
    • \n
  • threshold: the threshold
    • \n
\n\n
Returns
\n", "signature": "(\tself,\ttest_fn: causy.interfaces.PipelineStepInterface,\tapply_to_graph=True) -> Tuple[List[causy.models.TestResultAction], List[causy.models.TestResultAction]]:", "funcdef": "def"}, "causy.graph_model.graph_model_factory": {"fullname": "causy.graph_model.graph_model_factory", "modulename": "causy.graph_model", "qualname": "graph_model_factory", "kind": "function", "doc": "

Create a graph model based on a List of pipeline_steps

\n\n
Parameters
\n\n
    \n
  • algorithm: the algorithm which should be used to create the graph model
    • \n
\n\n
Returns
\n\n
\n

the graph model

\n
\n", "signature": "(\talgorithm: causy.models.Algorithm = None,\tvariables: Dict[str, causy.variables.VariableTypes] = None) -> type[causy.graph_model.AbstractGraphModel]:", "funcdef": "def"}, "causy.graph_utils": {"fullname": "causy.graph_utils", "modulename": "causy.graph_utils", "kind": "module", "doc": "

\n"}, "causy.graph_utils.unpack_run": {"fullname": "causy.graph_utils.unpack_run", "modulename": "causy.graph_utils", "qualname": "unpack_run", "kind": "function", "doc": "

\n", "signature": "(args):", "funcdef": "def"}, "causy.graph_utils.serialize_module_name": {"fullname": "causy.graph_utils.serialize_module_name", "modulename": "causy.graph_utils", "qualname": "serialize_module_name", "kind": "function", "doc": "

\n", "signature": "(cls):", "funcdef": "def"}, "causy.graph_utils.load_pipeline_artefact_by_definition": {"fullname": "causy.graph_utils.load_pipeline_artefact_by_definition", "modulename": "causy.graph_utils", "qualname": "load_pipeline_artefact_by_definition", "kind": "function", "doc": "

\n", "signature": "(step):", "funcdef": "def"}, "causy.graph_utils.load_pipeline_steps_by_definition": {"fullname": "causy.graph_utils.load_pipeline_steps_by_definition", "modulename": "causy.graph_utils", "qualname": "load_pipeline_steps_by_definition", "kind": "function", "doc": "

\n", "signature": "(steps):", "funcdef": "def"}, "causy.graph_utils.retrieve_edges": {"fullname": "causy.graph_utils.retrieve_edges", "modulename": "causy.graph_utils", "qualname": "retrieve_edges", "kind": "function", "doc": "

Returns a list of edges from the graph

\n\n
Parameters
\n\n
    \n
  • graph: a graph
    • \n
\n\n
Returns
\n\n
\n

a list of edges

\n
\n", "signature": "(graph) -> List[Tuple[str, str]]:", "funcdef": "def"}, "causy.graph_utils.hash_dictionary": {"fullname": "causy.graph_utils.hash_dictionary", "modulename": "causy.graph_utils", "qualname": "hash_dictionary", "kind": "function", "doc": "

Hash a dictionary using SHA256 (e.g. for caching)

\n\n
Parameters
\n\n
    \n
  • dct:
    • \n
\n\n
Returns
\n", "signature": "(dct: Dict):", "funcdef": "def"}, "causy.interfaces": {"fullname": "causy.interfaces", "modulename": "causy.interfaces", "kind": "module", "doc": "

\n"}, "causy.interfaces.logger": {"fullname": "causy.interfaces.logger", "modulename": "causy.interfaces", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.interfaces (WARNING)>"}, "causy.interfaces.DEFAULT_THRESHOLD": {"fullname": "causy.interfaces.DEFAULT_THRESHOLD", "modulename": "causy.interfaces", "qualname": "DEFAULT_THRESHOLD", "kind": "variable", "doc": "

\n", "default_value": "0.01"}, "causy.interfaces.AS_MANY_AS_FIELDS": {"fullname": "causy.interfaces.AS_MANY_AS_FIELDS", "modulename": "causy.interfaces", "qualname": "AS_MANY_AS_FIELDS", "kind": "variable", "doc": "

\n", "default_value": "0"}, "causy.interfaces.MetadataBaseType": {"fullname": "causy.interfaces.MetadataBaseType", "modulename": "causy.interfaces", "qualname": "MetadataBaseType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool]"}, "causy.interfaces.MetadataType": {"fullname": "causy.interfaces.MetadataType", "modulename": "causy.interfaces", "qualname": "MetadataType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool, typing.List[typing.Union[str, int, float, bool]], typing.Dict[str, typing.Union[str, int, float, bool]]]"}, "causy.interfaces.ComparisonSettingsInterface": {"fullname": "causy.interfaces.ComparisonSettingsInterface", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.ComparisonSettingsInterface.min": {"fullname": "causy.interfaces.ComparisonSettingsInterface.min", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.min", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.ComparisonSettingsInterface.max": {"fullname": "causy.interfaces.ComparisonSettingsInterface.max", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.max", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.ComparisonSettingsInterface.name": {"fullname": "causy.interfaces.ComparisonSettingsInterface.name", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ComparisonSettingsInterface.model_config": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_config", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ComparisonSettingsInterface.model_fields": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_fields", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'min': FieldInfo(annotation=Union[int, VariableReference], required=True), 'max': FieldInfo(annotation=Union[int, VariableReference], required=True)}"}, "causy.interfaces.ComparisonSettingsInterface.model_computed_fields": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.NodeInterface": {"fullname": "causy.interfaces.NodeInterface", "modulename": "causy.interfaces", "qualname": "NodeInterface", "kind": "class", "doc": "

Node interface for the graph. A node is defined by a name and a value.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.NodeInterface.name": {"fullname": "causy.interfaces.NodeInterface.name", "modulename": "causy.interfaces", "qualname": "NodeInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.NodeInterface.id": {"fullname": "causy.interfaces.NodeInterface.id", "modulename": "causy.interfaces", "qualname": "NodeInterface.id", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.NodeInterface.values": {"fullname": "causy.interfaces.NodeInterface.values", "modulename": "causy.interfaces", "qualname": "NodeInterface.values", "kind": "variable", "doc": "

\n", "annotation": ": Annotated[Optional[torch.DoubleTensor], WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)]"}, "causy.interfaces.NodeInterface.Config": {"fullname": "causy.interfaces.NodeInterface.Config", "modulename": "causy.interfaces", "qualname": "NodeInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.NodeInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.NodeInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "NodeInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.NodeInterface.model_config": {"fullname": "causy.interfaces.NodeInterface.model_config", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.NodeInterface.model_fields": {"fullname": "causy.interfaces.NodeInterface.model_fields", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[DoubleTensor, NoneType], required=False, default=None, exclude=True, metadata=[WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)])}"}, "causy.interfaces.NodeInterface.model_computed_fields": {"fullname": "causy.interfaces.NodeInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.EdgeTypeInterface": {"fullname": "causy.interfaces.EdgeTypeInterface", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.interfaces.EdgeTypeInterface.name": {"fullname": "causy.interfaces.EdgeTypeInterface.name", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.EdgeTypeInterface.IS_DIRECTED": {"fullname": "causy.interfaces.EdgeTypeInterface.IS_DIRECTED", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.IS_DIRECTED", "kind": "variable", "doc": "

\n", "annotation": ": bool"}, "causy.interfaces.EdgeTypeInterface.STR_REPRESENTATION": {"fullname": "causy.interfaces.EdgeTypeInterface.STR_REPRESENTATION", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.STR_REPRESENTATION", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.EdgeTypeInterface.GraphAccessMixin": {"fullname": "causy.interfaces.EdgeTypeInterface.GraphAccessMixin", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.GraphAccessMixin", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.EdgeTypeInterface.pre_edge_remove_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_remove_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_remove_hook", "kind": "function", "doc": "

Hook that is executed before an edge is deleted.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_remove_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_remove_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_remove_hook", "kind": "function", "doc": "

Hook that is executed after an edge is deleted.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_add_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_add_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_add_hook", "kind": "function", "doc": "

Hook that is executed before an edge is added.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_add_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_add_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_add_hook", "kind": "function", "doc": "

Hook that is executed after an edge is added.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_update_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_update_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_update_hook", "kind": "function", "doc": "

Hook that is executed before an edge is updated.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_update_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_update_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_update_hook", "kind": "function", "doc": "

Hook that is executed after an edge is updated.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_type_change_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_type_change_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_type_change_hook", "kind": "function", "doc": "

Hook that is executed before an edge type is changed.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_type_change_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_type_change_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_type_change_hook", "kind": "function", "doc": "

Hook that is executed after an edge type is changed.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeInterface": {"fullname": "causy.interfaces.EdgeInterface", "modulename": "causy.interfaces", "qualname": "EdgeInterface", "kind": "class", "doc": "

Edge interface for the graph\nA graph edge is defined by two nodes and an edge type. It can also have metadata.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.EdgeInterface.u": {"fullname": "causy.interfaces.EdgeInterface.u", "modulename": "causy.interfaces", "qualname": "EdgeInterface.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.EdgeInterface.v": {"fullname": "causy.interfaces.EdgeInterface.v", "modulename": "causy.interfaces", "qualname": "EdgeInterface.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.EdgeInterface.edge_type": {"fullname": "causy.interfaces.EdgeInterface.edge_type", "modulename": "causy.interfaces", "qualname": "EdgeInterface.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.EdgeTypeInterface"}, "causy.interfaces.EdgeInterface.metadata": {"fullname": "causy.interfaces.EdgeInterface.metadata", "modulename": "causy.interfaces", "qualname": "EdgeInterface.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]"}, "causy.interfaces.EdgeInterface.Config": {"fullname": "causy.interfaces.EdgeInterface.Config", "modulename": "causy.interfaces", "qualname": "EdgeInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.EdgeInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.EdgeInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "EdgeInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.EdgeInterface.is_connection_between_same_nodes": {"fullname": "causy.interfaces.EdgeInterface.is_connection_between_same_nodes", "modulename": "causy.interfaces", "qualname": "EdgeInterface.is_connection_between_same_nodes", "kind": "function", "doc": "

\n", "signature": "(self, edge):", "funcdef": "def"}, "causy.interfaces.EdgeInterface.model_config": {"fullname": "causy.interfaces.EdgeInterface.model_config", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.EdgeInterface.model_fields": {"fullname": "causy.interfaces.EdgeInterface.model_fields", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'edge_type': FieldInfo(annotation=EdgeTypeInterface, required=True), 'metadata': FieldInfo(annotation=Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], required=False, default=None)}"}, "causy.interfaces.EdgeInterface.model_computed_fields": {"fullname": "causy.interfaces.EdgeInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.TestResultInterface": {"fullname": "causy.interfaces.TestResultInterface", "modulename": "causy.interfaces", "qualname": "TestResultInterface", "kind": "class", "doc": "

Test result interface for the graph\nA test result is defined by two nodes and an action. It can also have metadata.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.TestResultInterface.u": {"fullname": "causy.interfaces.TestResultInterface.u", "modulename": "causy.interfaces", "qualname": "TestResultInterface.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.TestResultInterface.v": {"fullname": "causy.interfaces.TestResultInterface.v", "modulename": "causy.interfaces", "qualname": "TestResultInterface.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.TestResultInterface.action": {"fullname": "causy.interfaces.TestResultInterface.action", "modulename": "causy.interfaces", "qualname": "TestResultInterface.action", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.TestResultInterface.data": {"fullname": "causy.interfaces.TestResultInterface.data", "modulename": "causy.interfaces", "qualname": "TestResultInterface.data", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict]"}, "causy.interfaces.TestResultInterface.Config": {"fullname": "causy.interfaces.TestResultInterface.Config", "modulename": "causy.interfaces", "qualname": "TestResultInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.TestResultInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.TestResultInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "TestResultInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.TestResultInterface.model_config": {"fullname": "causy.interfaces.TestResultInterface.model_config", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.TestResultInterface.model_fields": {"fullname": "causy.interfaces.TestResultInterface.model_fields", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'action': FieldInfo(annotation=str, required=True), 'data': FieldInfo(annotation=Union[Dict, NoneType], required=False, default=None)}"}, "causy.interfaces.TestResultInterface.model_computed_fields": {"fullname": "causy.interfaces.TestResultInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.BaseGraphInterface": {"fullname": "causy.interfaces.BaseGraphInterface", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.BaseGraphInterface.nodes": {"fullname": "causy.interfaces.BaseGraphInterface.nodes", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, causy.interfaces.NodeInterface]"}, "causy.interfaces.BaseGraphInterface.edges": {"fullname": "causy.interfaces.BaseGraphInterface.edges", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, Dict]]"}, "causy.interfaces.BaseGraphInterface.retrieve_edge_history": {"fullname": "causy.interfaces.BaseGraphInterface.retrieve_edge_history", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.retrieve_edge_history", "kind": "function", "doc": "

\n", "signature": "(self, u, v, action: str) -> List[causy.interfaces.TestResultInterface]:", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_edge_history": {"fullname": "causy.interfaces.BaseGraphInterface.add_edge_history", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_edge_history", "kind": "function", "doc": "

\n", "signature": "(self, u, v, action: causy.interfaces.TestResultInterface):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_edge": {"fullname": "causy.interfaces.BaseGraphInterface.add_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.remove_edge": {"fullname": "causy.interfaces.BaseGraphInterface.remove_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.remove_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.remove_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.remove_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.remove_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.update_edge": {"fullname": "causy.interfaces.BaseGraphInterface.update_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.update_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata=None, edge_type=None):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.update_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.update_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.update_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata=None, edge_type=None):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_node": {"fullname": "causy.interfaces.BaseGraphInterface.add_node", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_node", "kind": "function", "doc": "

\n", "signature": "(self, name, values) -> causy.interfaces.NodeInterface:", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.edge_value": {"fullname": "causy.interfaces.BaseGraphInterface.edge_value", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edge_value", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.undirected_edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.undirected_edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.undirected_edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.directed_edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.directed_edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.directed_edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v, ignore_soft_deleted=False):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.restore_edge": {"fullname": "causy.interfaces.BaseGraphInterface.restore_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.restore_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.restore_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.restore_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.restore_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface": {"fullname": "causy.interfaces.GraphModelInterface", "modulename": "causy.interfaces", "qualname": "GraphModelInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.GraphModelInterface.pool": {"fullname": "causy.interfaces.GraphModelInterface.pool", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.pool", "kind": "variable", "doc": "

\n", "annotation": ": <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f03cc4c8fe0>>"}, "causy.interfaces.GraphModelInterface.create_graph_from_data": {"fullname": "causy.interfaces.GraphModelInterface.create_graph_from_data", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.create_graph_from_data", "kind": "function", "doc": "

\n", "signature": "(self, data: List[Dict]):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface.execute_pipeline_steps": {"fullname": "causy.interfaces.GraphModelInterface.execute_pipeline_steps", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.execute_pipeline_steps", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface.execute_pipeline_step": {"fullname": "causy.interfaces.GraphModelInterface.execute_pipeline_step", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.execute_pipeline_step", "kind": "function", "doc": "

\n", "signature": "(self, step, apply_to_graph: bool = True):", "funcdef": "def"}, "causy.interfaces.GeneratorInterface": {"fullname": "causy.interfaces.GeneratorInterface", "modulename": "causy.interfaces", "qualname": "GeneratorInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel"}, "causy.interfaces.GeneratorInterface.comparison_settings": {"fullname": "causy.interfaces.GeneratorInterface.comparison_settings", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.comparison_settings", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.ComparisonSettingsInterface]"}, "causy.interfaces.GeneratorInterface.chunked": {"fullname": "causy.interfaces.GeneratorInterface.chunked", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.every_nth": {"fullname": "causy.interfaces.GeneratorInterface.every_nth", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.every_nth", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.generator": {"fullname": "causy.interfaces.GeneratorInterface.generator", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.interfaces.GeneratorInterface.shuffle_combinations": {"fullname": "causy.interfaces.GeneratorInterface.shuffle_combinations", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.shuffle_combinations", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.generate": {"fullname": "causy.interfaces.GeneratorInterface.generate", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.interfaces.GeneratorInterface.name": {"fullname": "causy.interfaces.GeneratorInterface.name", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.GeneratorInterface.model_config": {"fullname": "causy.interfaces.GeneratorInterface.model_config", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GeneratorInterface.model_fields": {"fullname": "causy.interfaces.GeneratorInterface.model_fields", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.interfaces.GeneratorInterface.model_computed_fields": {"fullname": "causy.interfaces.GeneratorInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.PipelineStepInterface": {"fullname": "causy.interfaces.PipelineStepInterface", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~PipelineStepInterfaceType]"}, "causy.interfaces.PipelineStepInterface.generator": {"fullname": "causy.interfaces.PipelineStepInterface.generator", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.interfaces.PipelineStepInterface.threshold": {"fullname": "causy.interfaces.PipelineStepInterface.threshold", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.threshold", "kind": "variable", "doc": "

\n", "annotation": ": Union[float, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.chunk_size_parallel_processing": {"fullname": "causy.interfaces.PipelineStepInterface.chunk_size_parallel_processing", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.chunk_size_parallel_processing", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.PipelineStepInterface.parallel": {"fullname": "causy.interfaces.PipelineStepInterface.parallel", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.parallel", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.interfaces.PipelineStepInterface.display_name": {"fullname": "causy.interfaces.PipelineStepInterface.display_name", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.display_name", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.needs_unapplied_actions": {"fullname": "causy.interfaces.PipelineStepInterface.needs_unapplied_actions", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.needs_unapplied_actions", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.apply_synchronous": {"fullname": "causy.interfaces.PipelineStepInterface.apply_synchronous", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.apply_synchronous", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.name": {"fullname": "causy.interfaces.PipelineStepInterface.name", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.PipelineStepInterface.process": {"fullname": "causy.interfaces.PipelineStepInterface.process", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.process", "kind": "function", "doc": "

Test if u and v are independent

\n\n
Parameters
\n\n
    \n
  • u: u values
    • \n
  • v: v values
    • \n
\n\n
Returns
\n\n
\n

True if independent, False otherwise

\n
\n", "signature": "(\tself,\tnodes: List[str],\tgraph: causy.interfaces.BaseGraphInterface,\tunapplied_actions: Optional[List[causy.interfaces.TestResultInterface]] = None) -> Optional[causy.interfaces.TestResultInterface]:", "funcdef": "def"}, "causy.interfaces.ExitConditionInterface": {"fullname": "causy.interfaces.ExitConditionInterface", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel"}, "causy.interfaces.ExitConditionInterface.check": {"fullname": "causy.interfaces.ExitConditionInterface.check", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.check", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • graph:
    • \n
  • graph_model_instance_:
    • \n
  • actions_taken:
    • \n
  • iteration:
    • \n
\n\n
Returns
\n\n
\n

True if you want to break an iteration, False otherwise

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface,\tactions_taken: List[causy.interfaces.TestResultInterface],\titeration: Union[int, causy.variables.VariableReference]) -> bool:", "funcdef": "def"}, "causy.interfaces.ExitConditionInterface.name": {"fullname": "causy.interfaces.ExitConditionInterface.name", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExitConditionInterface.model_config": {"fullname": "causy.interfaces.ExitConditionInterface.model_config", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ExitConditionInterface.model_fields": {"fullname": "causy.interfaces.ExitConditionInterface.model_fields", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ExitConditionInterface.model_computed_fields": {"fullname": "causy.interfaces.ExitConditionInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.LogicStepInterface": {"fullname": "causy.interfaces.LogicStepInterface", "modulename": "causy.interfaces", "qualname": "LogicStepInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~LogicStepInterfaceType]"}, "causy.interfaces.LogicStepInterface.pipeline_steps": {"fullname": "causy.interfaces.LogicStepInterface.pipeline_steps", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~PipelineStepInterfaceType]]"}, "causy.interfaces.LogicStepInterface.exit_condition": {"fullname": "causy.interfaces.LogicStepInterface.exit_condition", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.exit_condition", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.ExitConditionInterface]"}, "causy.interfaces.LogicStepInterface.display_name": {"fullname": "causy.interfaces.LogicStepInterface.display_name", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.display_name", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.LogicStepInterface.execute": {"fullname": "causy.interfaces.LogicStepInterface.execute", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.execute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.interfaces.LogicStepInterface.name": {"fullname": "causy.interfaces.LogicStepInterface.name", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExtensionInterface": {"fullname": "causy.interfaces.ExtensionInterface", "modulename": "causy.interfaces", "qualname": "ExtensionInterface", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, typing.Generic[~ExtensionType]"}, "causy.interfaces.ExtensionInterface.name": {"fullname": "causy.interfaces.ExtensionInterface.name", "modulename": "causy.interfaces", "qualname": "ExtensionInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExtensionInterface.GraphAccessMixin": {"fullname": "causy.interfaces.ExtensionInterface.GraphAccessMixin", "modulename": "causy.interfaces", "qualname": "ExtensionInterface.GraphAccessMixin", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.GraphUpdateHook": {"fullname": "causy.interfaces.GraphUpdateHook", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook", "kind": "class", "doc": "

A hook that is executed before or after the graph is updated. This can be used to modify the graph before or after an update.

\n", "bases": "pydantic.main.BaseModel"}, "causy.interfaces.GraphUpdateHook.execute": {"fullname": "causy.interfaces.GraphUpdateHook.execute", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.execute", "kind": "function", "doc": "

Execute the hook.

\n\n
Parameters
\n\n
    \n
  • graph: current state of the graph.
    • \n
  • updates: the planned/taken actions
    • \n
\n\n
Returns
\n\n
\n

A list of updates that should be applied to the graph if it is a pre hook. If it is a post hook, it should return None.

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tupdates: List[causy.interfaces.TestResultInterface]) -> Optional[List[causy.interfaces.TestResultInterface]]:", "funcdef": "def"}, "causy.interfaces.GraphUpdateHook.model_config": {"fullname": "causy.interfaces.GraphUpdateHook.model_config", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GraphUpdateHook.model_fields": {"fullname": "causy.interfaces.GraphUpdateHook.model_fields", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GraphUpdateHook.model_computed_fields": {"fullname": "causy.interfaces.GraphUpdateHook.model_computed_fields", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.math_utils": {"fullname": "causy.math_utils", "modulename": "causy.math_utils", "kind": "module", "doc": "

\n"}, "causy.math_utils.logger": {"fullname": "causy.math_utils.logger", "modulename": "causy.math_utils", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.math_utils (WARNING)>"}, "causy.math_utils.sum_lists": {"fullname": "causy.math_utils.sum_lists", "modulename": "causy.math_utils", "qualname": "sum_lists", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • lists: lists of numbers
    • \n
\n\n
Returns
\n\n
\n

list (sum of lists)

\n
\n", "signature": "(*lists):", "funcdef": "def"}, "causy.math_utils.get_t_and_critical_t": {"fullname": "causy.math_utils.get_t_and_critical_t", "modulename": "causy.math_utils", "qualname": "get_t_and_critical_t", "kind": "function", "doc": "

\n", "signature": "(sample_size, nb_of_control_vars, par_corr, threshold):", "funcdef": "def"}, "causy.models": {"fullname": "causy.models", "modulename": "causy.models", "kind": "module", "doc": "

\n"}, "causy.models.ComparisonSettings": {"fullname": "causy.models.ComparisonSettings", "modulename": "causy.models", "qualname": "ComparisonSettings", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.interfaces.ComparisonSettingsInterface"}, "causy.models.ComparisonSettings.min": {"fullname": "causy.models.ComparisonSettings.min", "modulename": "causy.models", "qualname": "ComparisonSettings.min", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.models.ComparisonSettings.max": {"fullname": "causy.models.ComparisonSettings.max", "modulename": "causy.models", "qualname": "ComparisonSettings.max", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.models.ComparisonSettings.name": {"fullname": "causy.models.ComparisonSettings.name", "modulename": "causy.models", "qualname": "ComparisonSettings.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.ComparisonSettings.model_config": {"fullname": "causy.models.ComparisonSettings.model_config", "modulename": "causy.models", "qualname": "ComparisonSettings.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ComparisonSettings.model_fields": {"fullname": "causy.models.ComparisonSettings.model_fields", "modulename": "causy.models", "qualname": "ComparisonSettings.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'min': FieldInfo(annotation=Union[int, VariableReference], required=False, default=2), 'max': FieldInfo(annotation=Union[int, VariableReference], required=False, default=0)}"}, "causy.models.ComparisonSettings.model_computed_fields": {"fullname": "causy.models.ComparisonSettings.model_computed_fields", "modulename": "causy.models", "qualname": "ComparisonSettings.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.models.TestResultAction": {"fullname": "causy.models.TestResultAction", "modulename": "causy.models", "qualname": "TestResultAction", "kind": "class", "doc": "

Actions that can be taken on the graph. These actions are used to keep track of the history of the graph.

\n", "bases": "builtins.str, enum.Enum"}, "causy.models.TestResultAction.UPDATE_EDGE": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE: 'UPDATE_EDGE'>"}, "causy.models.TestResultAction.UPDATE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_DIRECTED: 'UPDATE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.UPDATE_EDGE_TYPE": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_TYPE", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_TYPE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_TYPE: 'UPDATE_EDGE_TYPE'>"}, "causy.models.TestResultAction.UPDATE_EDGE_TYPE_DIRECTED": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_TYPE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_TYPE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_TYPE_DIRECTED: 'UPDATE_EDGE_TYPE_DIRECTED'>"}, "causy.models.TestResultAction.REMOVE_EDGE_UNDIRECTED": {"fullname": "causy.models.TestResultAction.REMOVE_EDGE_UNDIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.REMOVE_EDGE_UNDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.REMOVE_EDGE_UNDIRECTED: 'REMOVE_EDGE_UNDIRECTED'>"}, "causy.models.TestResultAction.REMOVE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.REMOVE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.REMOVE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.REMOVE_EDGE_DIRECTED: 'REMOVE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.RESTORE_EDGE": {"fullname": "causy.models.TestResultAction.RESTORE_EDGE", "modulename": "causy.models", "qualname": "TestResultAction.RESTORE_EDGE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.RESTORE_EDGE: 'RESTORE_EDGE'>"}, "causy.models.TestResultAction.RESTORE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.RESTORE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.RESTORE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.RESTORE_EDGE_DIRECTED: 'RESTORE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.DO_NOTHING": {"fullname": "causy.models.TestResultAction.DO_NOTHING", "modulename": "causy.models", "qualname": "TestResultAction.DO_NOTHING", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.DO_NOTHING: 'DO_NOTHING'>"}, "causy.models.TestResult": {"fullname": "causy.models.TestResult", "modulename": "causy.models", "qualname": "TestResult", "kind": "class", "doc": "

Test result interface for the graph\nA test result is defined by two nodes and an action. It can also have metadata.

\n", "bases": "causy.interfaces.TestResultInterface"}, "causy.models.TestResult.u": {"fullname": "causy.models.TestResult.u", "modulename": "causy.models", "qualname": "TestResult.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.models.TestResult.v": {"fullname": "causy.models.TestResult.v", "modulename": "causy.models", "qualname": "TestResult.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.models.TestResult.action": {"fullname": "causy.models.TestResult.action", "modulename": "causy.models", "qualname": "TestResult.action", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.TestResultAction"}, "causy.models.TestResult.data": {"fullname": "causy.models.TestResult.data", "modulename": "causy.models", "qualname": "TestResult.data", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict]"}, "causy.models.TestResult.model_config": {"fullname": "causy.models.TestResult.model_config", "modulename": "causy.models", "qualname": "TestResult.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.models.TestResult.model_fields": {"fullname": "causy.models.TestResult.model_fields", "modulename": "causy.models", "qualname": "TestResult.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'action': FieldInfo(annotation=TestResultAction, required=True), 'data': FieldInfo(annotation=Union[Dict, NoneType], required=False, default=None)}"}, "causy.models.TestResult.model_computed_fields": {"fullname": "causy.models.TestResult.model_computed_fields", "modulename": "causy.models", "qualname": "TestResult.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.AlgorithmReferenceType": {"fullname": "causy.models.AlgorithmReferenceType", "modulename": "causy.models", "qualname": "AlgorithmReferenceType", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.models.AlgorithmReferenceType.FILE": {"fullname": "causy.models.AlgorithmReferenceType.FILE", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.FILE", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.FILE: 'file'>"}, "causy.models.AlgorithmReferenceType.NAME": {"fullname": "causy.models.AlgorithmReferenceType.NAME", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.NAME", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.NAME: 'name'>"}, "causy.models.AlgorithmReferenceType.PYTHON_MODULE": {"fullname": "causy.models.AlgorithmReferenceType.PYTHON_MODULE", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.PYTHON_MODULE", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.PYTHON_MODULE: 'python_module'>"}, "causy.models.AlgorithmReference": {"fullname": "causy.models.AlgorithmReference", "modulename": "causy.models", "qualname": "AlgorithmReference", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.AlgorithmReference.reference": {"fullname": "causy.models.AlgorithmReference.reference", "modulename": "causy.models", "qualname": "AlgorithmReference.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.AlgorithmReference.type": {"fullname": "causy.models.AlgorithmReference.type", "modulename": "causy.models", "qualname": "AlgorithmReference.type", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.AlgorithmReferenceType"}, "causy.models.AlgorithmReference.model_config": {"fullname": "causy.models.AlgorithmReference.model_config", "modulename": "causy.models", "qualname": "AlgorithmReference.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.AlgorithmReference.model_fields": {"fullname": "causy.models.AlgorithmReference.model_fields", "modulename": "causy.models", "qualname": "AlgorithmReference.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'reference': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=AlgorithmReferenceType, required=True)}"}, "causy.models.AlgorithmReference.model_computed_fields": {"fullname": "causy.models.AlgorithmReference.model_computed_fields", "modulename": "causy.models", "qualname": "AlgorithmReference.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Algorithm": {"fullname": "causy.models.Algorithm", "modulename": "causy.models", "qualname": "Algorithm", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.Algorithm.name": {"fullname": "causy.models.Algorithm.name", "modulename": "causy.models", "qualname": "Algorithm.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.Algorithm.pipeline_steps": {"fullname": "causy.models.Algorithm.pipeline_steps", "modulename": "causy.models", "qualname": "Algorithm.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": List[Union[~PipelineStepInterfaceType, causy.interfaces.LogicStepInterface]]"}, "causy.models.Algorithm.edge_types": {"fullname": "causy.models.Algorithm.edge_types", "modulename": "causy.models", "qualname": "Algorithm.edge_types", "kind": "variable", "doc": "

\n", "annotation": ": List[~EdgeTypeInterfaceType]"}, "causy.models.Algorithm.extensions": {"fullname": "causy.models.Algorithm.extensions", "modulename": "causy.models", "qualname": "Algorithm.extensions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~ExtensionType]]"}, "causy.models.Algorithm.variables": {"fullname": "causy.models.Algorithm.variables", "modulename": "causy.models", "qualname": "Algorithm.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~VariableInterfaceType]]"}, "causy.models.Algorithm.pre_graph_update_hooks": {"fullname": "causy.models.Algorithm.pre_graph_update_hooks", "modulename": "causy.models", "qualname": "Algorithm.pre_graph_update_hooks", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.interfaces.GraphUpdateHook]]"}, "causy.models.Algorithm.post_graph_update_hooks": {"fullname": "causy.models.Algorithm.post_graph_update_hooks", "modulename": "causy.models", "qualname": "Algorithm.post_graph_update_hooks", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.interfaces.GraphUpdateHook]]"}, "causy.models.Algorithm.hash": {"fullname": "causy.models.Algorithm.hash", "modulename": "causy.models", "qualname": "Algorithm.hash", "kind": "function", "doc": "

\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.models.Algorithm.model_config": {"fullname": "causy.models.Algorithm.model_config", "modulename": "causy.models", "qualname": "Algorithm.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Algorithm.model_fields": {"fullname": "causy.models.Algorithm.model_fields", "modulename": "causy.models", "qualname": "Algorithm.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'pipeline_steps': FieldInfo(annotation=List[Union[TypeVar, LogicStepInterface]], required=True), 'edge_types': FieldInfo(annotation=List[TypeVar], required=True), 'extensions': FieldInfo(annotation=Union[List[TypeVar], NoneType], required=False, default=None), 'variables': FieldInfo(annotation=Union[List[TypeVar], NoneType], required=False, default=None), 'pre_graph_update_hooks': FieldInfo(annotation=Union[List[GraphUpdateHook], NoneType], required=False, default=None), 'post_graph_update_hooks': FieldInfo(annotation=Union[List[GraphUpdateHook], NoneType], required=False, default=None)}"}, "causy.models.Algorithm.model_computed_fields": {"fullname": "causy.models.Algorithm.model_computed_fields", "modulename": "causy.models", "qualname": "Algorithm.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ActionHistoryStep": {"fullname": "causy.models.ActionHistoryStep", "modulename": "causy.models", "qualname": "ActionHistoryStep", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.ActionHistoryStep.name": {"fullname": "causy.models.ActionHistoryStep.name", "modulename": "causy.models", "qualname": "ActionHistoryStep.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.ActionHistoryStep.duration": {"fullname": "causy.models.ActionHistoryStep.duration", "modulename": "causy.models", "qualname": "ActionHistoryStep.duration", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.models.ActionHistoryStep.actions": {"fullname": "causy.models.ActionHistoryStep.actions", "modulename": "causy.models", "qualname": "ActionHistoryStep.actions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.TestResult]]"}, "causy.models.ActionHistoryStep.all_proposed_actions": {"fullname": "causy.models.ActionHistoryStep.all_proposed_actions", "modulename": "causy.models", "qualname": "ActionHistoryStep.all_proposed_actions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.TestResult]]"}, "causy.models.ActionHistoryStep.steps": {"fullname": "causy.models.ActionHistoryStep.steps", "modulename": "causy.models", "qualname": "ActionHistoryStep.steps", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.ActionHistoryStep]]"}, "causy.models.ActionHistoryStep.model_config": {"fullname": "causy.models.ActionHistoryStep.model_config", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ActionHistoryStep.model_fields": {"fullname": "causy.models.ActionHistoryStep.model_fields", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'duration': FieldInfo(annotation=Union[float, NoneType], required=False, default=None), 'actions': FieldInfo(annotation=Union[List[TestResult], NoneType], required=False, default=[]), 'all_proposed_actions': FieldInfo(annotation=Union[List[TestResult], NoneType], required=False, default=[]), 'steps': FieldInfo(annotation=Union[List[ActionHistoryStep], NoneType], required=False, default=[])}"}, "causy.models.ActionHistoryStep.model_computed_fields": {"fullname": "causy.models.ActionHistoryStep.model_computed_fields", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Result": {"fullname": "causy.models.Result", "modulename": "causy.models", "qualname": "Result", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.Result.algorithm": {"fullname": "causy.models.Result.algorithm", "modulename": "causy.models", "qualname": "Result.algorithm", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.AlgorithmReference"}, "causy.models.Result.created_at": {"fullname": "causy.models.Result.created_at", "modulename": "causy.models", "qualname": "Result.created_at", "kind": "variable", "doc": "

\n", "annotation": ": datetime.datetime"}, "causy.models.Result.nodes": {"fullname": "causy.models.Result.nodes", "modulename": "causy.models", "qualname": "Result.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, causy.interfaces.NodeInterface]"}, "causy.models.Result.edges": {"fullname": "causy.models.Result.edges", "modulename": "causy.models", "qualname": "Result.edges", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.interfaces.EdgeInterface]"}, "causy.models.Result.action_history": {"fullname": "causy.models.Result.action_history", "modulename": "causy.models", "qualname": "Result.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.models.ActionHistoryStep]"}, "causy.models.Result.variables": {"fullname": "causy.models.Result.variables", "modulename": "causy.models", "qualname": "Result.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]"}, "causy.models.Result.data_loader_hash": {"fullname": "causy.models.Result.data_loader_hash", "modulename": "causy.models", "qualname": "Result.data_loader_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.algorithm_hash": {"fullname": "causy.models.Result.algorithm_hash", "modulename": "causy.models", "qualname": "Result.algorithm_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.variables_hash": {"fullname": "causy.models.Result.variables_hash", "modulename": "causy.models", "qualname": "Result.variables_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.model_config": {"fullname": "causy.models.Result.model_config", "modulename": "causy.models", "qualname": "Result.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Result.model_fields": {"fullname": "causy.models.Result.model_fields", "modulename": "causy.models", "qualname": "Result.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'algorithm': FieldInfo(annotation=AlgorithmReference, required=True), 'created_at': FieldInfo(annotation=datetime, required=False, default_factory=builtin_function_or_method), 'nodes': FieldInfo(annotation=Dict[str, NodeInterface], required=True), 'edges': FieldInfo(annotation=List[EdgeInterface], required=True), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'data_loader_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'algorithm_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'variables_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}"}, "causy.models.Result.model_computed_fields": {"fullname": "causy.models.Result.model_computed_fields", "modulename": "causy.models", "qualname": "Result.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.sample_generator": {"fullname": "causy.sample_generator", "modulename": "causy.sample_generator", "kind": "module", "doc": "

\n"}, "causy.sample_generator.logger": {"fullname": "causy.sample_generator.logger", "modulename": "causy.sample_generator", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.sample_generator (WARNING)>"}, "causy.sample_generator.random_normal": {"fullname": "causy.sample_generator.random_normal", "modulename": "causy.sample_generator", "qualname": "random_normal", "kind": "function", "doc": "

Returns a random number from a normal distribution

\n\n
Returns
\n\n
\n

the random number as a float

\n
\n", "signature": "() -> float:", "funcdef": "def"}, "causy.sample_generator.NodeReference": {"fullname": "causy.sample_generator.NodeReference", "modulename": "causy.sample_generator", "qualname": "NodeReference", "kind": "class", "doc": "

A reference to a node in the sample generator

\n"}, "causy.sample_generator.NodeReference.__init__": {"fullname": "causy.sample_generator.NodeReference.__init__", "modulename": "causy.sample_generator", "qualname": "NodeReference.__init__", "kind": "function", "doc": "

\n", "signature": "(node: str)"}, "causy.sample_generator.NodeReference.node": {"fullname": "causy.sample_generator.NodeReference.node", "modulename": "causy.sample_generator", "qualname": "NodeReference.node", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.sample_generator.TimeAwareNodeReference": {"fullname": "causy.sample_generator.TimeAwareNodeReference", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference", "kind": "class", "doc": "

A reference to a node in the sample generator

\n", "bases": "NodeReference"}, "causy.sample_generator.TimeAwareNodeReference.__init__": {"fullname": "causy.sample_generator.TimeAwareNodeReference.__init__", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference.__init__", "kind": "function", "doc": "

\n", "signature": "(node: str, point_in_time: int = 0)"}, "causy.sample_generator.TimeAwareNodeReference.point_in_time": {"fullname": "causy.sample_generator.TimeAwareNodeReference.point_in_time", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference.point_in_time", "kind": "variable", "doc": "

\n", "annotation": ": int", "default_value": "0"}, "causy.sample_generator.SampleEdge": {"fullname": "causy.sample_generator.SampleEdge", "modulename": "causy.sample_generator", "qualname": "SampleEdge", "kind": "class", "doc": "

An edge in the sample generator that references a node and a lag

\n"}, "causy.sample_generator.SampleEdge.__init__": {"fullname": "causy.sample_generator.SampleEdge.__init__", "modulename": "causy.sample_generator", "qualname": "SampleEdge.__init__", "kind": "function", "doc": "

\n", "signature": "(\tfrom_node: causy.sample_generator.NodeReference,\tto_node: causy.sample_generator.NodeReference,\tvalue: float = 0)"}, "causy.sample_generator.SampleEdge.from_node": {"fullname": "causy.sample_generator.SampleEdge.from_node", "modulename": "causy.sample_generator", "qualname": "SampleEdge.from_node", "kind": "variable", "doc": "

\n", "annotation": ": causy.sample_generator.NodeReference"}, "causy.sample_generator.SampleEdge.to_node": {"fullname": "causy.sample_generator.SampleEdge.to_node", "modulename": "causy.sample_generator", "qualname": "SampleEdge.to_node", "kind": "variable", "doc": "

\n", "annotation": ": causy.sample_generator.NodeReference"}, "causy.sample_generator.SampleEdge.value": {"fullname": "causy.sample_generator.SampleEdge.value", "modulename": "causy.sample_generator", "qualname": "SampleEdge.value", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "0"}, "causy.sample_generator.TimeTravelingError": {"fullname": "causy.sample_generator.TimeTravelingError", "modulename": "causy.sample_generator", "qualname": "TimeTravelingError", "kind": "class", "doc": "

An error that is raised when a TimeProxy tries to access a value from the future

\n", "bases": "builtins.Exception"}, "causy.sample_generator.AbstractSampleGenerator": {"fullname": "causy.sample_generator.AbstractSampleGenerator", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.sample_generator.AbstractSampleGenerator.random_fn": {"fullname": "causy.sample_generator.AbstractSampleGenerator.random_fn", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator.random_fn", "kind": "variable", "doc": "

\n"}, "causy.sample_generator.AbstractSampleGenerator.generate": {"fullname": "causy.sample_generator.AbstractSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size: int) -> types.SimpleNamespace:", "funcdef": "def"}, "causy.sample_generator.IIDSampleGenerator": {"fullname": "causy.sample_generator.IIDSampleGenerator", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator", "kind": "class", "doc": "

A sample generator that generates data from i.i.d multivariate Gaussians.

\n\n

A variable can not depend on itself.

\n\n

Example:

\n\n
\n
>>> sg = IIDSampleGenerator(\n>>>     edges=[\n>>>      SampleEdge(NodeReference("X"), NodeReference("Y"), 5),\n>>>      SampleEdge(NodeReference("Y"), NodeReference("Z"), 7),\n>>>      ],\n>>> )\n
\n
\n", "bases": "AbstractSampleGenerator"}, "causy.sample_generator.IIDSampleGenerator.__init__": {"fullname": "causy.sample_generator.IIDSampleGenerator.__init__", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tedges: List[causy.sample_generator.SampleEdge],\trandom: Callable = <function random_normal>)"}, "causy.sample_generator.IIDSampleGenerator.topologic_sort": {"fullname": "causy.sample_generator.IIDSampleGenerator.topologic_sort", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.topologic_sort", "kind": "function", "doc": "

Sorts the nodes topologically

\n\n
Parameters
\n\n
    \n
  • nodes: list of nodes
    • \n
  • edges: list of edges
    • \n
\n\n
Returns
\n\n
\n

a list of sorted nodes

\n
\n", "signature": "(self, nodes: List[str]):", "funcdef": "def"}, "causy.sample_generator.IIDSampleGenerator.generate": {"fullname": "causy.sample_generator.IIDSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator", "kind": "class", "doc": "

A sample generator that generates data for a sample graph with a time dimension.

\n\n

Edges are defined as SampleLaggedEdges, which define a directed edge from a source node to a target node with a\nag. The lag is the number of time steps between the source and the target.

\n\n

A variable can depend on itself, but only on its past values (with a lag). This corresponds to autoregressive models.

\n\n

Example:

\n\n
\n
>>> sg = TimeseriesSampleGenerator(\n>>>     edges=[\n>>>      SampleEdge(TimeAwareNodeReference("X", -1), TimeAwareNodeReference("X"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Y", -1), TimeAwareNodeReference("Y"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Z", -1), TimeAwareNodeReference("Z"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Z", -1), TimeAwareNodeReference("Y"), 5),\n>>>      SampleEdge(TimeAwareNodeReference("Y", -1), TimeAwareNodeReference("X"), 7),\n>>>      ],\n>>> )\n
\n
\n", "bases": "AbstractSampleGenerator"}, "causy.sample_generator.TimeseriesSampleGenerator.__init__": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.__init__", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tedges: List[causy.sample_generator.SampleEdge],\trandom: Callable = <function random_normal>)"}, "causy.sample_generator.TimeseriesSampleGenerator.generate": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator.custom_block_diagonal": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.custom_block_diagonal", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.custom_block_diagonal", "kind": "function", "doc": "

\n", "signature": "(self, matrices):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator.vectorize_identity_block": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.vectorize_identity_block", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.vectorize_identity_block", "kind": "function", "doc": "

\n", "signature": "(self, n):", "funcdef": "def"}, "causy.serialization": {"fullname": "causy.serialization", "modulename": "causy.serialization", "kind": "module", "doc": "

\n"}, "causy.serialization.serialize_algorithm": {"fullname": "causy.serialization.serialize_algorithm", "modulename": "causy.serialization", "qualname": "serialize_algorithm", "kind": "function", "doc": "

Serialize the model into a dictionary.

\n", "signature": "(model, algorithm_name: str = None):", "funcdef": "def"}, "causy.serialization.load_algorithm_from_specification": {"fullname": "causy.serialization.load_algorithm_from_specification", "modulename": "causy.serialization", "qualname": "load_algorithm_from_specification", "kind": "function", "doc": "

Load the model from a dictionary.

\n", "signature": "(algorithm_dict: Dict[str, Any]):", "funcdef": "def"}, "causy.serialization.load_algorithm_by_reference": {"fullname": "causy.serialization.load_algorithm_by_reference", "modulename": "causy.serialization", "qualname": "load_algorithm_by_reference", "kind": "function", "doc": "

\n", "signature": "(reference_type: str, algorithm: str):", "funcdef": "def"}, "causy.serialization.CausyJSONEncoder": {"fullname": "causy.serialization.CausyJSONEncoder", "modulename": "causy.serialization", "qualname": "CausyJSONEncoder", "kind": "class", "doc": "

Extensible JSON https://json.org encoder for Python data structures.

\n\n

Supports the following objects and types by default:

\n\n

+-------------------+---------------+\n| Python | JSON |\n+===================+===============+\n| dict | object |\n+-------------------+---------------+\n| list, tuple | array |\n+-------------------+---------------+\n| str | string |\n+-------------------+---------------+\n| int, float | number |\n+-------------------+---------------+\n| True | true |\n+-------------------+---------------+\n| False | false |\n+-------------------+---------------+\n| None | null |\n+-------------------+---------------+

\n\n

To extend this to recognize other objects, subclass and implement a\n.default() method with another method that returns a serializable\nobject for o if possible, otherwise it should call the superclass\nimplementation (to raise TypeError).

\n", "bases": "json.encoder.JSONEncoder"}, "causy.serialization.CausyJSONEncoder.default": {"fullname": "causy.serialization.CausyJSONEncoder.default", "modulename": "causy.serialization", "qualname": "CausyJSONEncoder.default", "kind": "function", "doc": "

Implement this method in a subclass such that it returns\na serializable object for o, or calls the base implementation\n(to raise a TypeError).

\n\n

For example, to support arbitrary iterators, you could\nimplement default like this::

\n\n
def default(self, o):\n    try:\n        iterable = iter(o)\n    except TypeError:\n        pass\n    else:\n        return list(iterable)\n    # Let the base class default method raise the TypeError\n    return super().default(o)\n
\n", "signature": "(self, obj):", "funcdef": "def"}, "causy.serialization.load_json": {"fullname": "causy.serialization.load_json", "modulename": "causy.serialization", "qualname": "load_json", "kind": "function", "doc": "

\n", "signature": "(pipeline_file: str):", "funcdef": "def"}, "causy.serialization.deserialize_result": {"fullname": "causy.serialization.deserialize_result", "modulename": "causy.serialization", "qualname": "deserialize_result", "kind": "function", "doc": "

Deserialize the result.

\n", "signature": "(result: Dict[str, Any], klass=<class 'causy.models.Result'>):", "funcdef": "def"}, "causy.ui": {"fullname": "causy.ui", "modulename": "causy.ui", "kind": "module", "doc": "

\n"}, "causy.ui.cli": {"fullname": "causy.ui.cli", "modulename": "causy.ui.cli", "kind": "module", "doc": "

\n"}, "causy.ui.cli.ui": {"fullname": "causy.ui.cli.ui", "modulename": "causy.ui.cli", "qualname": "ui", "kind": "function", "doc": "

Start the causy UI.

\n", "signature": "(result_file: str = None):", "funcdef": "def"}, "causy.ui.models": {"fullname": "causy.ui.models", "modulename": "causy.ui.models", "kind": "module", "doc": "

\n"}, "causy.ui.models.NodePosition": {"fullname": "causy.ui.models.NodePosition", "modulename": "causy.ui.models", "qualname": "NodePosition", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.ui.models.NodePosition.x": {"fullname": "causy.ui.models.NodePosition.x", "modulename": "causy.ui.models", "qualname": "NodePosition.x", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.ui.models.NodePosition.y": {"fullname": "causy.ui.models.NodePosition.y", "modulename": "causy.ui.models", "qualname": "NodePosition.y", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.ui.models.NodePosition.model_config": {"fullname": "causy.ui.models.NodePosition.model_config", "modulename": "causy.ui.models", "qualname": "NodePosition.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.NodePosition.model_fields": {"fullname": "causy.ui.models.NodePosition.model_fields", "modulename": "causy.ui.models", "qualname": "NodePosition.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'x': FieldInfo(annotation=Union[float, NoneType], required=True), 'y': FieldInfo(annotation=Union[float, NoneType], required=True)}"}, "causy.ui.models.NodePosition.model_computed_fields": {"fullname": "causy.ui.models.NodePosition.model_computed_fields", "modulename": "causy.ui.models", "qualname": "NodePosition.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExperimentVersion": {"fullname": "causy.ui.models.ExperimentVersion", "modulename": "causy.ui.models", "qualname": "ExperimentVersion", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.ui.models.ExperimentVersion.version": {"fullname": "causy.ui.models.ExperimentVersion.version", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.version", "kind": "variable", "doc": "

\n", "annotation": ": int"}, "causy.ui.models.ExperimentVersion.name": {"fullname": "causy.ui.models.ExperimentVersion.name", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.ui.models.ExperimentVersion.model_config": {"fullname": "causy.ui.models.ExperimentVersion.model_config", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExperimentVersion.model_fields": {"fullname": "causy.ui.models.ExperimentVersion.model_fields", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'version': FieldInfo(annotation=int, required=True), 'name': FieldInfo(annotation=str, required=True)}"}, "causy.ui.models.ExperimentVersion.model_computed_fields": {"fullname": "causy.ui.models.ExperimentVersion.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedExperiment": {"fullname": "causy.ui.models.ExtendedExperiment", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment", "kind": "class", "doc": "

represents a single experiment

\n\n
Parameters
\n\n
    \n
  • name: name of the experiment
    • \n
  • pipeline: the name of the pipeline used
    • \n
\n", "bases": "causy.workspaces.models.Experiment"}, "causy.ui.models.ExtendedExperiment.versions": {"fullname": "causy.ui.models.ExtendedExperiment.versions", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.versions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.ui.models.ExperimentVersion]]"}, "causy.ui.models.ExtendedExperiment.name": {"fullname": "causy.ui.models.ExtendedExperiment.name", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.ui.models.ExtendedExperiment.model_config": {"fullname": "causy.ui.models.ExtendedExperiment.model_config", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedExperiment.model_fields": {"fullname": "causy.ui.models.ExtendedExperiment.model_fields", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'pipeline': FieldInfo(annotation=str, required=True), 'dataloader': FieldInfo(annotation=str, required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool]], NoneType], required=False, default={}), 'versions': FieldInfo(annotation=Union[List[ExperimentVersion], NoneType], required=False, default=None), 'name': FieldInfo(annotation=str, required=False, default=None)}"}, "causy.ui.models.ExtendedExperiment.model_computed_fields": {"fullname": "causy.ui.models.ExtendedExperiment.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.PositionedNode": {"fullname": "causy.ui.models.PositionedNode", "modulename": "causy.ui.models", "qualname": "PositionedNode", "kind": "class", "doc": "

Node interface for the graph. A node is defined by a name and a value.

\n", "bases": "causy.interfaces.NodeInterface"}, "causy.ui.models.PositionedNode.position": {"fullname": "causy.ui.models.PositionedNode.position", "modulename": "causy.ui.models", "qualname": "PositionedNode.position", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.ui.models.NodePosition]"}, "causy.ui.models.PositionedNode.model_config": {"fullname": "causy.ui.models.PositionedNode.model_config", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.ui.models.PositionedNode.model_fields": {"fullname": "causy.ui.models.PositionedNode.model_fields", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[DoubleTensor, NoneType], required=False, default=None, exclude=True, metadata=[WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)]), 'position': FieldInfo(annotation=Union[NodePosition, NoneType], required=False, default=None)}"}, "causy.ui.models.PositionedNode.model_computed_fields": {"fullname": "causy.ui.models.PositionedNode.model_computed_fields", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedResult": {"fullname": "causy.ui.models.ExtendedResult", "modulename": "causy.ui.models", "qualname": "ExtendedResult", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.models.Result"}, "causy.ui.models.ExtendedResult.nodes": {"fullname": "causy.ui.models.ExtendedResult.nodes", "modulename": "causy.ui.models", "qualname": "ExtendedResult.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Union[Annotated[uuid.UUID, UuidVersion(uuid_version=4)], str], causy.ui.models.PositionedNode]"}, "causy.ui.models.ExtendedResult.version": {"fullname": "causy.ui.models.ExtendedResult.version", "modulename": "causy.ui.models", "qualname": "ExtendedResult.version", "kind": "variable", "doc": "

\n", "annotation": ": Optional[int]"}, "causy.ui.models.ExtendedResult.model_config": {"fullname": "causy.ui.models.ExtendedResult.model_config", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedResult.model_fields": {"fullname": "causy.ui.models.ExtendedResult.model_fields", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'algorithm': FieldInfo(annotation=AlgorithmReference, required=True), 'created_at': FieldInfo(annotation=datetime, required=False, default_factory=builtin_function_or_method), 'nodes': FieldInfo(annotation=Dict[Union[Annotated[UUID, UuidVersion], str], PositionedNode], required=True), 'edges': FieldInfo(annotation=List[EdgeInterface], required=True), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'data_loader_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'algorithm_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'variables_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'version': FieldInfo(annotation=Union[int, NoneType], required=False, default=None)}"}, "causy.ui.models.ExtendedResult.model_computed_fields": {"fullname": "causy.ui.models.ExtendedResult.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.server": {"fullname": "causy.ui.server", "modulename": "causy.ui.server", "kind": "module", "doc": "

\n"}, "causy.ui.server.logger": {"fullname": "causy.ui.server.logger", "modulename": "causy.ui.server", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.ui.server (WARNING)>"}, "causy.ui.server.API_ROUTES": {"fullname": "causy.ui.server.API_ROUTES", "modulename": "causy.ui.server", "qualname": "API_ROUTES", "kind": "variable", "doc": "

\n", "default_value": "<fastapi.routing.APIRouter object>"}, "causy.ui.server.MODEL": {"fullname": "causy.ui.server.MODEL", "modulename": "causy.ui.server", "qualname": "MODEL", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.ui.models.ExtendedResult]", "default_value": "None"}, "causy.ui.server.WORKSPACE": {"fullname": "causy.ui.server.WORKSPACE", "modulename": "causy.ui.server", "qualname": "WORKSPACE", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.workspaces.models.Workspace]", "default_value": "None"}, "causy.ui.server.get_status": {"fullname": "causy.ui.server.get_status", "modulename": "causy.ui.server", "qualname": "get_status", "kind": "function", "doc": "

Get the current status of the API.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_model": {"fullname": "causy.ui.server.get_model", "modulename": "causy.ui.server", "qualname": "get_model", "kind": "function", "doc": "

Get the current model.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_workspace": {"fullname": "causy.ui.server.get_workspace", "modulename": "causy.ui.server", "qualname": "get_workspace", "kind": "function", "doc": "

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_latest_experiment": {"fullname": "causy.ui.server.get_latest_experiment", "modulename": "causy.ui.server", "qualname": "get_latest_experiment", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "(experiment_name: str):", "funcdef": "async def"}, "causy.ui.server.get_experiment": {"fullname": "causy.ui.server.get_experiment", "modulename": "causy.ui.server", "qualname": "get_experiment", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "(experiment_name: str, version_number: int):", "funcdef": "async def"}, "causy.ui.server.get_experiments": {"fullname": "causy.ui.server.get_experiments", "modulename": "causy.ui.server", "qualname": "get_experiments", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_algorithm": {"fullname": "causy.ui.server.get_algorithm", "modulename": "causy.ui.server", "qualname": "get_algorithm", "kind": "function", "doc": "

Get the current algorithm.

\n", "signature": "(reference_type: str, reference: str):", "funcdef": "async def"}, "causy.ui.server.is_port_in_use": {"fullname": "causy.ui.server.is_port_in_use", "modulename": "causy.ui.server", "qualname": "is_port_in_use", "kind": "function", "doc": "

\n", "signature": "(host: str, port: int) -> bool:", "funcdef": "def"}, "causy.ui.server.server": {"fullname": "causy.ui.server.server", "modulename": "causy.ui.server", "qualname": "server", "kind": "function", "doc": "

Create the FastAPI server.

\n", "signature": "(\tresult: Dict[str, Any] = None,\tworkspace: causy.workspaces.models.Workspace = None):", "funcdef": "def"}, "causy.variables": {"fullname": "causy.variables", "modulename": "causy.variables", "kind": "module", "doc": "

\n"}, "causy.variables.VariableType": {"fullname": "causy.variables.VariableType", "modulename": "causy.variables", "qualname": "VariableType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool]"}, "causy.variables.VariableTypes": {"fullname": "causy.variables.VariableTypes", "modulename": "causy.variables", "qualname": "VariableTypes", "kind": "class", "doc": "

\n", "bases": "enum.Enum"}, "causy.variables.VariableTypes.String": {"fullname": "causy.variables.VariableTypes.String", "modulename": "causy.variables", "qualname": "VariableTypes.String", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.String: 'string'>"}, "causy.variables.VariableTypes.Integer": {"fullname": "causy.variables.VariableTypes.Integer", "modulename": "causy.variables", "qualname": "VariableTypes.Integer", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Integer: 'integer'>"}, "causy.variables.VariableTypes.Float": {"fullname": "causy.variables.VariableTypes.Float", "modulename": "causy.variables", "qualname": "VariableTypes.Float", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Float: 'float'>"}, "causy.variables.VariableTypes.Bool": {"fullname": "causy.variables.VariableTypes.Bool", "modulename": "causy.variables", "qualname": "VariableTypes.Bool", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Bool: 'bool'>"}, "causy.variables.BaseVariable": {"fullname": "causy.variables.BaseVariable", "modulename": "causy.variables", "qualname": "BaseVariable", "kind": "class", "doc": "

Represents a single variable. It can be a string, int, float or bool. The type of the variable is determined by the\ntype attribute.

\n", "bases": "pydantic.main.BaseModel, typing.Generic[~VariableInterfaceType]"}, "causy.variables.BaseVariable.name": {"fullname": "causy.variables.BaseVariable.name", "modulename": "causy.variables", "qualname": "BaseVariable.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.BaseVariable.value": {"fullname": "causy.variables.BaseVariable.value", "modulename": "causy.variables", "qualname": "BaseVariable.value", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, int, float, bool]"}, "causy.variables.BaseVariable.choices": {"fullname": "causy.variables.BaseVariable.choices", "modulename": "causy.variables", "qualname": "BaseVariable.choices", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[Union[str, int, float, bool]]]"}, "causy.variables.BaseVariable.is_valid": {"fullname": "causy.variables.BaseVariable.is_valid", "modulename": "causy.variables", "qualname": "BaseVariable.is_valid", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "causy.variables.BaseVariable.is_valid_value": {"fullname": "causy.variables.BaseVariable.is_valid_value", "modulename": "causy.variables", "qualname": "BaseVariable.is_valid_value", "kind": "function", "doc": "

\n", "signature": "(self, value):", "funcdef": "def"}, "causy.variables.BaseVariable.validate_value": {"fullname": "causy.variables.BaseVariable.validate_value", "modulename": "causy.variables", "qualname": "BaseVariable.validate_value", "kind": "function", "doc": "

\n", "signature": "(self, value):", "funcdef": "def"}, "causy.variables.BaseVariable.type": {"fullname": "causy.variables.BaseVariable.type", "modulename": "causy.variables", "qualname": "BaseVariable.type", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.variables.StringVariable": {"fullname": "causy.variables.StringVariable", "modulename": "causy.variables", "qualname": "StringVariable", "kind": "class", "doc": "

Represents a single string variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.StringVariable.model_post_init": {"fullname": "causy.variables.StringVariable.model_post_init", "modulename": "causy.variables", "qualname": "StringVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.IntegerVariable": {"fullname": "causy.variables.IntegerVariable", "modulename": "causy.variables", "qualname": "IntegerVariable", "kind": "class", "doc": "

Represents a single int variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.IntegerVariable.model_post_init": {"fullname": "causy.variables.IntegerVariable.model_post_init", "modulename": "causy.variables", "qualname": "IntegerVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.FloatVariable": {"fullname": "causy.variables.FloatVariable", "modulename": "causy.variables", "qualname": "FloatVariable", "kind": "class", "doc": "

Represents a single float variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.FloatVariable.model_post_init": {"fullname": "causy.variables.FloatVariable.model_post_init", "modulename": "causy.variables", "qualname": "FloatVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.BoolVariable": {"fullname": "causy.variables.BoolVariable", "modulename": "causy.variables", "qualname": "BoolVariable", "kind": "class", "doc": "

Represents a single bool variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.BoolVariable.model_post_init": {"fullname": "causy.variables.BoolVariable.model_post_init", "modulename": "causy.variables", "qualname": "BoolVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.VariableReference": {"fullname": "causy.variables.VariableReference", "modulename": "causy.variables", "qualname": "VariableReference", "kind": "class", "doc": "

Represents a reference to a variable.

\n", "bases": "pydantic.main.BaseModel, typing.Generic[~VariableInterfaceType]"}, "causy.variables.VariableReference.name": {"fullname": "causy.variables.VariableReference.name", "modulename": "causy.variables", "qualname": "VariableReference.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.VariableReference.type": {"fullname": "causy.variables.VariableReference.type", "modulename": "causy.variables", "qualname": "VariableReference.type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.VARIABLE_MAPPING": {"fullname": "causy.variables.VARIABLE_MAPPING", "modulename": "causy.variables", "qualname": "VARIABLE_MAPPING", "kind": "variable", "doc": "

\n", "default_value": "{'string': <class 'causy.variables.StringVariable'>, 'integer': <class 'causy.variables.IntegerVariable'>, 'float': <class 'causy.variables.FloatVariable'>, 'bool': <class 'causy.variables.BoolVariable'>}"}, "causy.variables.BoolParameter": {"fullname": "causy.variables.BoolParameter", "modulename": "causy.variables", "qualname": "BoolParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bool, causy.variables.VariableReference]"}, "causy.variables.IntegerParameter": {"fullname": "causy.variables.IntegerParameter", "modulename": "causy.variables", "qualname": "IntegerParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[int, causy.variables.VariableReference]"}, "causy.variables.FloatParameter": {"fullname": "causy.variables.FloatParameter", "modulename": "causy.variables", "qualname": "FloatParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[float, causy.variables.VariableReference]"}, "causy.variables.StringParameter": {"fullname": "causy.variables.StringParameter", "modulename": "causy.variables", "qualname": "StringParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, causy.variables.VariableReference]"}, "causy.variables.CausyParameter": {"fullname": "causy.variables.CausyParameter", "modulename": "causy.variables", "qualname": "CausyParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bool, causy.variables.VariableReference, int, float, str]"}, "causy.variables.validate_variable_values": {"fullname": "causy.variables.validate_variable_values", "modulename": "causy.variables", "qualname": "validate_variable_values", "kind": "function", "doc": "

Validate the variable values for the algorithm.

\n\n
Parameters
\n\n
    \n
  • algorithm:
    • \n
  • variable_values:
    • \n
\n\n
Returns
\n", "signature": "(algorithm, variable_values: Dict[str, Union[str, int, float, bool]]):", "funcdef": "def"}, "causy.variables.resolve_variables": {"fullname": "causy.variables.resolve_variables", "modulename": "causy.variables", "qualname": "resolve_variables", "kind": "function", "doc": "

Resolve the variables from the list of variables and the variable values coming from the user.

\n\n
Parameters
\n\n
    \n
  • variables:
    • \n
  • variable_values:
    • \n
\n\n
Returns
\n", "signature": "(\tvariables: List[causy.variables.BaseVariable],\tvariable_values: Dict[str, Union[str, int, float, bool]]) -> Dict[str, Union[str, int, float, bool]]:", "funcdef": "def"}, "causy.variables.resolve_variable_to_object": {"fullname": "causy.variables.resolve_variable_to_object", "modulename": "causy.variables", "qualname": "resolve_variable_to_object", "kind": "function", "doc": "

Resolve the variables to the object.

\n\n
Parameters
\n\n
    \n
  • obj:
    • \n
  • variables:
    • \n
\n\n
Returns
\n", "signature": "(obj: Any, variables):", "funcdef": "def"}, "causy.variables.resolve_variables_to_algorithm_for_pipeline_steps": {"fullname": "causy.variables.resolve_variables_to_algorithm_for_pipeline_steps", "modulename": "causy.variables", "qualname": "resolve_variables_to_algorithm_for_pipeline_steps", "kind": "function", "doc": "

Resolve the variables to the algorithm.

\n\n
Parameters
\n\n
    \n
  • pipeline_steps:
    • \n
  • variables:
    • \n
\n\n
Returns
\n", "signature": "(pipeline_steps, variables):", "funcdef": "def"}, "causy.variables.deserialize_variable": {"fullname": "causy.variables.deserialize_variable", "modulename": "causy.variables", "qualname": "deserialize_variable", "kind": "function", "doc": "

Deserialize the variable from the dictionary.

\n\n
Parameters
\n\n
    \n
  • variable_dict:
    • \n
\n\n
Returns
\n", "signature": "(\tvariable_dict: Dict[str, Union[str, int, float, bool]]) -> causy.variables.BaseVariable:", "funcdef": "def"}, "causy.variables.deserialize_variable_references": {"fullname": "causy.variables.deserialize_variable_references", "modulename": "causy.variables", "qualname": "deserialize_variable_references", "kind": "function", "doc": "

Deserialize the variable references from the pipeline step.

\n\n
Parameters
\n\n
    \n
  • pipeline_step:
    • \n
\n\n
Returns
\n", "signature": "(element: object) -> object:", "funcdef": "def"}, "causy.workspaces": {"fullname": "causy.workspaces", "modulename": "causy.workspaces", "kind": "module", "doc": "

Representation of a causy workspace.

\n\n

Exemplary folder structure

\n\n
    \n
  • causy.yaml (contains workspace wide settings for stuff like name, author, pipeline definitions)
    • \n
  • any_pipeline.yaml (seperate pipeline definition referenced by causy.yaml)
    • \n
  • custom_pipeline_step.py (a project specific pipeline step)
    • \n
  • some_data_loader.py (a data loader to ship data into causy)
    • \n
  • tune_pipeline_1709406402/ (a single experiment)\n
      \n
    • causy_experiment.json (contains the full definition of everything used)
      • \n
    • causy_model.json (the actual generated model)
      • \n
    • \n
\n\n

Examples

\n\n
    \n
  • the user generates a new workspace because they want to work on a new causal discovery project (causy workspace create)
    • \n
  • they add a custom data loader, pipeline steps and extend an existing pipeline (causy workspace data-loaders create)
    • \n
  • they run multiple experiments (causy workspace experiments create, causy workspace experiments execute $EXPERIMENT_NAME)
    • \n
\n"}, "causy.workspaces.cli": {"fullname": "causy.workspaces.cli", "modulename": "causy.workspaces.cli", "kind": "module", "doc": "

\n"}, "causy.workspaces.cli.workspace_app": {"fullname": "causy.workspaces.cli.workspace_app", "modulename": "causy.workspaces.cli", "qualname": "workspace_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.pipeline_app": {"fullname": "causy.workspaces.cli.pipeline_app", "modulename": "causy.workspaces.cli", "qualname": "pipeline_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.experiment_app": {"fullname": "causy.workspaces.cli.experiment_app", "modulename": "causy.workspaces.cli", "qualname": "experiment_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.dataloader_app": {"fullname": "causy.workspaces.cli.dataloader_app", "modulename": "causy.workspaces.cli", "qualname": "dataloader_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.logger": {"fullname": "causy.workspaces.cli.logger", "modulename": "causy.workspaces.cli", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.workspaces.cli (WARNING)>"}, "causy.workspaces.cli.NO_COLOR": {"fullname": "causy.workspaces.cli.NO_COLOR", "modulename": "causy.workspaces.cli", "qualname": "NO_COLOR", "kind": "variable", "doc": "

\n", "default_value": "False"}, "causy.workspaces.cli.WORKSPACE_FILE_NAME": {"fullname": "causy.workspaces.cli.WORKSPACE_FILE_NAME", "modulename": "causy.workspaces.cli", "qualname": "WORKSPACE_FILE_NAME", "kind": "variable", "doc": "

\n", "default_value": "'workspace.yml'"}, "causy.workspaces.cli.JINJA_ENV": {"fullname": "causy.workspaces.cli.JINJA_ENV", "modulename": "causy.workspaces.cli", "qualname": "JINJA_ENV", "kind": "variable", "doc": "

\n", "default_value": "<jinja2.environment.Environment object>"}, "causy.workspaces.cli.WorkspaceNotFoundError": {"fullname": "causy.workspaces.cli.WorkspaceNotFoundError", "modulename": "causy.workspaces.cli", "qualname": "WorkspaceNotFoundError", "kind": "class", "doc": "

Common base class for all non-exit exceptions.

\n", "bases": "builtins.Exception"}, "causy.workspaces.cli.show_error": {"fullname": "causy.workspaces.cli.show_error", "modulename": "causy.workspaces.cli", "qualname": "show_error", "kind": "function", "doc": "

\n", "signature": "(message: str):", "funcdef": "def"}, "causy.workspaces.cli.show_success": {"fullname": "causy.workspaces.cli.show_success", "modulename": "causy.workspaces.cli", "qualname": "show_success", "kind": "function", "doc": "

\n", "signature": "(message: str):", "funcdef": "def"}, "causy.workspaces.cli.write_to_workspace": {"fullname": "causy.workspaces.cli.write_to_workspace", "modulename": "causy.workspaces.cli", "qualname": "write_to_workspace", "kind": "function", "doc": "

\n", "signature": "(workspace: causy.workspaces.models.Workspace):", "funcdef": "def"}, "causy.workspaces.cli.create_pipeline": {"fullname": "causy.workspaces.cli.create_pipeline", "modulename": "causy.workspaces.cli", "qualname": "create_pipeline", "kind": "function", "doc": "

Create a new pipeline in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_pipeline": {"fullname": "causy.workspaces.cli.remove_pipeline", "modulename": "causy.workspaces.cli", "qualname": "remove_pipeline", "kind": "function", "doc": "

Remove a pipeline from the current workspace.

\n", "signature": "(pipeline_name: str):", "funcdef": "def"}, "causy.workspaces.cli.create_experiment": {"fullname": "causy.workspaces.cli.create_experiment", "modulename": "causy.workspaces.cli", "qualname": "create_experiment", "kind": "function", "doc": "

Create a new experiment in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_experiment": {"fullname": "causy.workspaces.cli.remove_experiment", "modulename": "causy.workspaces.cli", "qualname": "remove_experiment", "kind": "function", "doc": "

Remove an experiment from the current workspace.

\n", "signature": "(experiment_name: str):", "funcdef": "def"}, "causy.workspaces.cli.clear_experiment": {"fullname": "causy.workspaces.cli.clear_experiment", "modulename": "causy.workspaces.cli", "qualname": "clear_experiment", "kind": "function", "doc": "

Clear all versions of an experiment.

\n", "signature": "(experiment_name: str):", "funcdef": "def"}, "causy.workspaces.cli.update_experiment_variable": {"fullname": "causy.workspaces.cli.update_experiment_variable", "modulename": "causy.workspaces.cli", "qualname": "update_experiment_variable", "kind": "function", "doc": "

Update a variable in an experiment.

\n", "signature": "(experiment_name: str, variable_name: str, variable_value: str):", "funcdef": "def"}, "causy.workspaces.cli.create_data_loader": {"fullname": "causy.workspaces.cli.create_data_loader", "modulename": "causy.workspaces.cli", "qualname": "create_data_loader", "kind": "function", "doc": "

Create a new data loader in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_data_loader": {"fullname": "causy.workspaces.cli.remove_data_loader", "modulename": "causy.workspaces.cli", "qualname": "remove_data_loader", "kind": "function", "doc": "

Remove a data loader from the current workspace.

\n", "signature": "(data_loader_name: str):", "funcdef": "def"}, "causy.workspaces.cli.info": {"fullname": "causy.workspaces.cli.info", "modulename": "causy.workspaces.cli", "qualname": "info", "kind": "function", "doc": "

Show general information about the workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.init": {"fullname": "causy.workspaces.cli.init", "modulename": "causy.workspaces.cli", "qualname": "init", "kind": "function", "doc": "

Initialize a new workspace in the current directory.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.execute": {"fullname": "causy.workspaces.cli.execute", "modulename": "causy.workspaces.cli", "qualname": "execute", "kind": "function", "doc": "

Execute an experiment or all experiments in the workspace.

\n", "signature": "(experiment_name: str = None, force_reexecution: bool = False):", "funcdef": "def"}, "causy.workspaces.cli.diff": {"fullname": "causy.workspaces.cli.diff", "modulename": "causy.workspaces.cli", "qualname": "diff", "kind": "function", "doc": "

Show the differences between multiple experiment results.

\n", "signature": "(experiment_names: List[str], only_differences: bool = False):", "funcdef": "def"}, "causy.workspaces.models": {"fullname": "causy.workspaces.models", "modulename": "causy.workspaces.models", "kind": "module", "doc": "

\n"}, "causy.workspaces.models.Experiment": {"fullname": "causy.workspaces.models.Experiment", "modulename": "causy.workspaces.models", "qualname": "Experiment", "kind": "class", "doc": "

represents a single experiment

\n\n
Parameters
\n\n
    \n
  • name: name of the experiment
    • \n
  • pipeline: the name of the pipeline used
    • \n
\n", "bases": "pydantic.main.BaseModel"}, "causy.workspaces.models.Experiment.pipeline": {"fullname": "causy.workspaces.models.Experiment.pipeline", "modulename": "causy.workspaces.models", "qualname": "Experiment.pipeline", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.workspaces.models.Experiment.dataloader": {"fullname": "causy.workspaces.models.Experiment.dataloader", "modulename": "causy.workspaces.models", "qualname": "Experiment.dataloader", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.workspaces.models.Experiment.variables": {"fullname": "causy.workspaces.models.Experiment.variables", "modulename": "causy.workspaces.models", "qualname": "Experiment.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool]]]"}, "causy.workspaces.models.Experiment.model_config": {"fullname": "causy.workspaces.models.Experiment.model_config", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.workspaces.models.Experiment.model_fields": {"fullname": "causy.workspaces.models.Experiment.model_fields", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'pipeline': FieldInfo(annotation=str, required=True), 'dataloader': FieldInfo(annotation=str, required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool]], NoneType], required=False, default={})}"}, "causy.workspaces.models.Experiment.model_computed_fields": {"fullname": "causy.workspaces.models.Experiment.model_computed_fields", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.workspaces.models.Workspace": {"fullname": "causy.workspaces.models.Workspace", "modulename": "causy.workspaces.models", "qualname": "Workspace", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.workspaces.models.Workspace.name": {"fullname": "causy.workspaces.models.Workspace.name", "modulename": "causy.workspaces.models", "qualname": "Workspace.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.workspaces.models.Workspace.author": {"fullname": "causy.workspaces.models.Workspace.author", "modulename": "causy.workspaces.models", "qualname": "Workspace.author", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.workspaces.models.Workspace.pipelines": {"fullname": "causy.workspaces.models.Workspace.pipelines", "modulename": "causy.workspaces.models", "qualname": "Workspace.pipelines", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, causy.models.Algorithm | causy.models.AlgorithmReference]]"}, "causy.workspaces.models.Workspace.dataloaders": {"fullname": "causy.workspaces.models.Workspace.dataloaders", "modulename": "causy.workspaces.models", "qualname": "Workspace.dataloaders", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, causy.data_loader.DataLoaderReference]]"}, "causy.workspaces.models.Workspace.experiments": {"fullname": "causy.workspaces.models.Workspace.experiments", "modulename": "causy.workspaces.models", "qualname": "Workspace.experiments", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, causy.workspaces.models.Experiment]]"}, "causy.workspaces.models.Workspace.model_config": {"fullname": "causy.workspaces.models.Workspace.model_config", "modulename": "causy.workspaces.models", "qualname": "Workspace.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.workspaces.models.Workspace.model_fields": {"fullname": "causy.workspaces.models.Workspace.model_fields", "modulename": "causy.workspaces.models", "qualname": "Workspace.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'author': FieldInfo(annotation=Union[str, NoneType], required=True), 'pipelines': FieldInfo(annotation=Union[Dict[str, Union[Algorithm, AlgorithmReference]], NoneType], required=True), 'dataloaders': FieldInfo(annotation=Union[Dict[str, DataLoaderReference], NoneType], required=True), 'experiments': FieldInfo(annotation=Union[Dict[str, Experiment], NoneType], required=True)}"}, "causy.workspaces.models.Workspace.model_computed_fields": {"fullname": "causy.workspaces.models.Workspace.model_computed_fields", "modulename": "causy.workspaces.models", "qualname": "Workspace.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}}, "docInfo": {"causy": {"qualname": 0, "fullname": 1, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 58}, "causy.causal_discovery": {"qualname": 0, "fullname": 3, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint": {"qualname": 0, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms": {"qualname": 0, "fullname": 5, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.AVAILABLE_ALGORITHMS": {"qualname": 2, "fullname": 7, "annotation": 0, "default_value": 40, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.fci": {"qualname": 0, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension": {"qualname": 1, "fullname": 7, "annotation": 0, "default_value": 0, "signature": 0, "bases": 5, "doc": 277}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin": {"qualname": 2, "fullname": 8, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin.inducing_path_exists": {"qualname": 5, "fullname": 11, "annotation": 0, "default_value": 0, "signature": 81, "bases": 0, "doc": 72}, "causy.causal_discovery.constraint.algorithms.pc": {"qualname": 0, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.PC_DEFAULT_THRESHOLD": {"qualname": 3, "fullname": 9, "annotation": 0, "default_value": 2, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.PC_ORIENTATION_RULES": {"qualname": 3, "fullname": 9, "annotation": 0, "default_value": 382, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.PC_GRAPH_UI_EXTENSION": {"qualname": 4, "fullname": 10, "annotation": 0, "default_value": 224, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.PC_EDGE_TYPES": {"qualname": 3, "fullname": 9, "annotation": 0, "default_value": 2, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.PC": {"qualname": 1, "fullname": 7, "annotation": 0, "default_value": 17, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.PCClassic": {"qualname": 1, "fullname": 7, "annotation": 0, "default_value": 17, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.PCStable": {"qualname": 1, "fullname": 7, "annotation": 0, "default_value": 17, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.ParallelPC": {"qualname": 1, "fullname": 7, "annotation": 0, "default_value": 17, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.independence_tests": {"qualname": 0, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.independence_tests.common": {"qualname": 0, "fullname": 7, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.independence_tests.common.logger": {"qualname": 1, "fullname": 8, "annotation": 0, "default_value": 13, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.independence_tests.common.CorrelationCoefficientTest": {"qualname": 1, "fullname": 8, "annotation": 0, "default_value": 0, "signature": 0, "bases": 5, "doc": 16}, "causy.causal_discovery.constraint.independence_tests.common.PartialCorrelationTest": {"qualname": 1, "fullname": 8, "annotation": 0, "default_value": 0, "signature": 0, "bases": 5, "doc": 16}, "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestMatrix": {"qualname": 1, "fullname": 8, "annotation": 0, "default_value": 0, "signature": 0, "bases": 5, "doc": 16}, "causy.causal_discovery.constraint.independence_tests.common.partial_correlation_regression": {"qualname": 3, "fullname": 10, "annotation": 0, "default_value": 0, "signature": 21, "bases": 0, "doc": 71}, "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestLinearRegression": {"qualname": 1, "fullname": 8, "annotation": 0, "default_value": 0, "signature": 0, "bases": 5, "doc": 16}, "causy.causal_discovery.constraint.orientation_rules": {"qualname": 0, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.orientation_rules.fci": {"qualname": 0, "fullname": 7, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, 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