upate AMY1A / HMC / SMN1/2 notebooks generating the GFA files in the new GFA_files directory

Author: cschin

04-AMY1A.ipynb

@@ -38,7 +38,7 @@
     {
      "data": {
       "text/plain": [
-       "'pgrtk 0.3.3 (v0.3.3_dev:675e3c7, release build, linux [x86_64] [rustc 1.62.0 (a8314ef7d 2022-06-27)])'"
+       "'pgrtk 0.3.4 (main:59af6a0, release build, linux [x86_64] [rustc 1.62.0 (a8314ef7d 2022-06-27)])'"
       ]
      },
      "execution_count": 2,
@@ -92,8 +92,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 22.4 s, sys: 6min 13s, total: 6min 35s\n",
-      "Wall time: 31.9 s\n"
+      "CPU times: user 24.2 s, sys: 5min 34s, total: 5min 58s\n",
+      "Wall time: 35.2 s\n"
      ]
     }
    ],
@@ -726,10 +726,12 @@
     "new_sdb = pgrtk.SeqIndexDB() \n",
     "new_sdb.load_from_seq_list(seq_list, w=80, k=56, r=6, min_span=18)\n",
     "new_sdb.generate_mapg_gfa(0, \"/results/AMY1A_region_80_56_6.gfa\")\n",
+    "new_sdb.write_mapg_idx(\"/results/AMY1A_region_80_56_6.gidx\")\n",
     "\n",
     "new_sdb = pgrtk.SeqIndexDB() \n",
     "new_sdb.load_from_seq_list(seq_list, w=80, k=56, r=2, min_span=18)\n",
-    "new_sdb.generate_mapg_gfa(0, \"/results/AMY1A_region_80_56_2.gfa\")"
+    "new_sdb.generate_mapg_gfa(0, \"/results/AMY1A_region_80_56_2.gfa\")\n",
+    "new_sdb.write_mapg_idx(\"/results/AMY1A_region_80_56_2.gidx\")"
    ]
   },
   {
@@ -1004,7 +1006,7 @@
        "<div style=\"vertical-align: middle;\"><strong>nipy_spectral</strong> </div><div class=\"cmap\"><img alt=\"nipy_spectral colormap\" title=\"nipy_spectral\" style=\"border: 1px solid #555;\" src=\"data:image/png;base64,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\"></div><div style=\"vertical-align: middle; max-width: 514px; display: flex; justify-content: space-between;\"><div style=\"float: left;\"><div title=\"#000000ff\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #000000ff;\"></div> under</div><div style=\"margin: 0 auto; display: inline-block;\">bad <div title=\"#00000000\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #00000000;\"></div></div><div style=\"float: right;\">over <div title=\"#ccccccff\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #ccccccff;\"></div></div>"
       ],
       "text/plain": [
-       "<matplotlib.colors.LinearSegmentedColormap at 0x7f77f04261c0>"
+       "<matplotlib.colors.LinearSegmentedColormap at 0x7fa63652eeb0>"
       ]
      },
      "execution_count": 29,
@@ -1051,7 +1053,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1060,7 +1062,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1116,7 +1118,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1131,7 +1133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -1290,7 +1292,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
@@ -1364,14 +1366,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/tmp/ipykernel_2794/3154699274.py:39: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
+      "/tmp/ipykernel_127/3154699274.py:39: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
       "  plt.figure(figsize=(16,2))\n"
      ]
     },
@@ -2501,7 +2503,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2510,7 +2512,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2576,7 +2578,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {