diff --git a/mrdna/readers/segmentmodel_from_scadnano.py b/mrdna/readers/segmentmodel_from_scadnano.py
index f47b9d3bbcb683e75448d9f335aad792404680b6..a2ae7bfaf80b00172660d43d8132726fe19e5afc 100644
--- a/mrdna/readers/segmentmodel_from_scadnano.py
+++ b/mrdna/readers/segmentmodel_from_scadnano.py
@@ -122,10 +122,10 @@ def gen_prop_table(fname):
nt_prop["bp"]=bp
non_stack_ind,=np.where(nt_prop["stack"]==-1)
for i in non_stack_ind:
- zid=int(nt_prop.loc[i]["zid"])+int(nt_prop.loc[i]["fwd"])*2-1
- try:
- nt_prop["stack"][i]=bp_map[(nt_prop.loc[i]["vh"],str(zid),nt_prop.loc[i]["fwd"])]
- except:
+ zid=int(nt_prop.loc[i]["zid"])+int(nt_prop.loc[i]["fwd"])*2.0-1.0
+ if (nt_prop.loc[i]["vh"],zid,nt_prop.loc[i]["fwd"]) in bp_map.keys():
+ nt_prop["stack"][i]=bp_map[(nt_prop.loc[i]["vh"],zid,nt_prop.loc[i]["fwd"])]
+ else:
continue
nt_prop["r"]=list(np.array([nt_prop["x"],nt_prop["y"],nt_prop["z"]],dtype="<f4").T)
diff --git a/mrdna/readers/test/Untitled.ipynb b/mrdna/readers/test/Untitled.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..b76be740b4212cb66f134a256eb698a4e5819fbf
--- /dev/null
+++ b/mrdna/readers/test/Untitled.ipynb
@@ -0,0 +1,580 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "b3d4de16",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " _\n",
+ " _____ ___ _| |___ ___\n",
+ "| | _| . | | .'|\n",
+ "|_|_|_|_| |___|_|_|__,| v1.0a.dev121 \n",
+ "it/its\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "from mrdna import logger, devlogger\n",
+ "import pickle\n",
+ "import pandas as pd\n",
+ "import sys\n",
+ "import mrdna.readers.libs as libs\n",
+ "import numpy as np\n",
+ "from scipy.spatial import distance_matrix\n",
+ "import mrdna"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "85f99c60",
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "from mrdna.readers.segmentmodel_from_oxdna_pinyi import*"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "409255b3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "virt2nuc=\"test_insert.json.virt2nuc\"\n",
+ "top_data = np.loadtxt(\"test_insert.json.top\", skiprows=1,\n",
+ " unpack=True,\n",
+ " dtype=np.dtype('i4,U1,i4,i4')\n",
+ " )\n",
+ "def _find_vh_vb_table(s,is_scaf):\n",
+ " L=[]\n",
+ " for i in list(s.keys()):\n",
+ " vh,zid=i\n",
+ " strand,indices=s[i]\n",
+ " if len(indices)==0:\n",
+ " continue\n",
+ " else:\n",
+ " if len(indices)==1:\n",
+ " zids=[str(zid)]\n",
+ " else:\n",
+ " zids=[str(zid)+\".\"+str(j) for j in range(len(indices))]\n",
+ " for index,z in zip(indices,zids):\n",
+ " L.append(pd.Series({\"index\":index,\"vh\":vh,\"zid\":z,\"strand\":strand,\"is_scaf\":bool(is_scaf)}))\n",
+ " return L\n",
+ "\n",
+ "virt_pickle=open(virt2nuc,\"rb\")\n",
+ "vh_vb,pattern=pickle.load(virt_pickle)\n",
+ "L1=_find_vh_vb_table(vh_vb._scaf,1)\n",
+ "L2=_find_vh_vb_table(vh_vb._stap,0)\n",
+ "nt_prop=pd.DataFrame(L1+L2)\n",
+ "nt_prop.set_index(\"index\",inplace=True)\n",
+ "nt_prop.sort_index(inplace=True)\n",
+ "nt_prop[\"threeprime\"]=top_data[2]\n",
+ "nt_prop[\"stack\"]=top_data[2]\n",
+ "vh_bool=1-(nt_prop[\"vh\"]%2)*2\n",
+ "is_scaf_bool=nt_prop[\"is_scaf\"]*2-1\n",
+ "nt_prop[\"fwd\"]=np.array((is_scaf_bool.T*vh_bool+1)/2,dtype=bool)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "9649d37f",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "stack_map=dict(zip(zip(nt_prop[\"vh\"],nt_prop[\"zid\"],nt_prop[\"fwd\"]),nt_prop.index,))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "dfe5ba1e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "bp_map=dict(zip(zip(nt_prop[\"vh\"],nt_prop[\"zid\"],nt_prop[\"fwd\"]),nt_prop.index))\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "0b94dcec",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "non_stack_ind,=np.where(nt_prop[\"stack\"]==-1)\n",
+ "for i in non_stack_ind:\n",
+ " zid=int(nt_prop.loc[i][\"zid\"])+int(nt_prop.loc[i][\"fwd\"])*2-1\n",
+ " try:\n",
+ " nt_prop[\"stack\"][i]=bp_map[(nt_prop.loc[i][\"vh\"],str(zid),nt_prop.loc[i][\"fwd\"])]\n",
+ " except:\n",
+ " continue\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "d17224f8",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "n,=np.where(nt_prop[\"vh\"]==0)\n",
+ "t,=np.where(nt_prop[\"fwd\"][n]==True)\n",
+ "f,=np.where(nt_prop[\"fwd\"][n]==False)\n",
+ "\n",
+ "dt=nt_prop.loc[n[t]]\n",
+ "dt.set_index([\"vh\",\"zid\"],inplace=True)\n",
+ "df=nt_prop.loc[n[f]]\n",
+ "df.set_index([\"vh\",\"zid\"],inplace=True)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "b2e7198d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "vh 0\n",
+ "zid 24\n",
+ "strand 10\n",
+ "is_scaf False\n",
+ "threeprime -1\n",
+ "stack 332\n",
+ "fwd False\n",
+ "Name: 333, dtype: object"
+ ]
+ },
+ "execution_count": 9,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nt_prop.loc[333]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "169aa122",
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "strand 9\n",
+ "is_scaf False\n",
+ "threeprime 329\n",
+ "stack 329\n",
+ "Name: (0, 21, False), dtype: object strand 8\n",
+ "is_scaf False\n",
+ "threeprime 291\n",
+ "stack 291\n",
+ "Name: (0, 20, False), dtype: object\n"
+ ]
+ }
+ ],
+ "source": [
+ "n=nt_prop.set_index([\"vh\",\"zid\",\"fwd\"])\n",
+ "print(n.loc[(0,\"21\",False)],n.loc[(0,\"20\",False)])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 56,
+ "id": "c0605ccd",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "strand 9\n",
+ "is_scaf False\n",
+ "threeprime 328\n",
+ "stack 328\n",
+ "Name: (1, 21, True), dtype: object strand 8\n",
+ "is_scaf False\n",
+ "threeprime 292\n",
+ "stack 292\n",
+ "Name: (1, 20, True), dtype: object\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(n.loc[(1,\"21\",True)],n.loc[(1,\"20\",True)])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "d787b235",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>vh</th>\n",
+ " <th>zid</th>\n",
+ " <th>strand</th>\n",
+ " <th>is_scaf</th>\n",
+ " <th>threeprime</th>\n",
+ " <th>stack</th>\n",
+ " <th>fwd</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>index</th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>327</th>\n",
+ " <td>1</td>\n",
+ " <td>23</td>\n",
+ " <td>9</td>\n",
+ " <td>False</td>\n",
+ " <td>326</td>\n",
+ " <td>326</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>328</th>\n",
+ " <td>1</td>\n",
+ " <td>22</td>\n",
+ " <td>9</td>\n",
+ " <td>False</td>\n",
+ " <td>327</td>\n",
+ " <td>327</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>290</th>\n",
+ " <td>0</td>\n",
+ " <td>18</td>\n",
+ " <td>8</td>\n",
+ " <td>False</td>\n",
+ " <td>289</td>\n",
+ " <td>289</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>291</th>\n",
+ " <td>0</td>\n",
+ " <td>19</td>\n",
+ " <td>8</td>\n",
+ " <td>False</td>\n",
+ " <td>290</td>\n",
+ " <td>290</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>292</th>\n",
+ " <td>0</td>\n",
+ " <td>20</td>\n",
+ " <td>8</td>\n",
+ " <td>False</td>\n",
+ " <td>291</td>\n",
+ " <td>291</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>293</th>\n",
+ " <td>1</td>\n",
+ " <td>20</td>\n",
+ " <td>8</td>\n",
+ " <td>False</td>\n",
+ " <td>292</td>\n",
+ " <td>292</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " vh zid strand is_scaf threeprime stack fwd\n",
+ "index \n",
+ "327 1 23 9 False 326 326 True\n",
+ "328 1 22 9 False 327 327 True\n",
+ "290 0 18 8 False 289 289 False\n",
+ "291 0 19 8 False 290 290 False\n",
+ "292 0 20 8 False 291 291 False\n",
+ "293 1 20 8 False 292 292 True"
+ ]
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nt_prop.loc[[327,328,290,291,292,293]]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "id": "9088a520",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([['0', '41', 'True'],\n",
+ " ['1', '39', 'False'],\n",
+ " ['2', '41', 'True'],\n",
+ " ['2', '0', 'False'],\n",
+ " ['3', '37', 'False'],\n",
+ " ['4', '3', 'True'],\n",
+ " ['5', '0', 'False'],\n",
+ " ['5', '23', 'False'],\n",
+ " ['0', '2', 'False'],\n",
+ " ['1', '38', 'True'],\n",
+ " ['0', '24', 'False'],\n",
+ " ['5', '39', 'True'],\n",
+ " ['4', '9', 'False'],\n",
+ " ['3', '34', 'True']], dtype='<U21')"
+ ]
+ },
+ "execution_count": 28,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "n,=np.where(nt_prop[\"stack\"]==-1)\n",
+ "for vh,zid,fwd in stack[n]:\n",
+ " if fwd==True:\n",
+ " zid=str(int(zid)+1)\n",
+ " else:\n",
+ " zid=str(int(zid)-1)\n",
+ " if (vh,zid,fwd) in stack:\n",
+ " nt_prop[]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "6508fe8e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>index</th>\n",
+ " <th>vh</th>\n",
+ " <th>zid</th>\n",
+ " <th>strand</th>\n",
+ " <th>is_scaf</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>2</td>\n",
+ " <td>0</td>\n",
+ " <td>39</td>\n",
+ " <td>0</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>1</td>\n",
+ " <td>0</td>\n",
+ " <td>40</td>\n",
+ " <td>0</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>0</td>\n",
+ " <td>0</td>\n",
+ " <td>41</td>\n",
+ " <td>0</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>5</td>\n",
+ " <td>1</td>\n",
+ " <td>41</td>\n",
+ " <td>1</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>4</td>\n",
+ " <td>1</td>\n",
+ " <td>40</td>\n",
+ " <td>1</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>450</th>\n",
+ " <td>427</td>\n",
+ " <td>3</td>\n",
+ " <td>30</td>\n",
+ " <td>13</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>451</th>\n",
+ " <td>426</td>\n",
+ " <td>3</td>\n",
+ " <td>31</td>\n",
+ " <td>13</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>452</th>\n",
+ " <td>425</td>\n",
+ " <td>3</td>\n",
+ " <td>32</td>\n",
+ " <td>13</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>453</th>\n",
+ " <td>424</td>\n",
+ " <td>3</td>\n",
+ " <td>33</td>\n",
+ " <td>13</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>454</th>\n",
+ " <td>423</td>\n",
+ " <td>3</td>\n",
+ " <td>34</td>\n",
+ " <td>13</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>455 rows × 5 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " index vh zid strand is_scaf\n",
+ "0 2 0 39 0 True\n",
+ "1 1 0 40 0 True\n",
+ "2 0 0 41 0 True\n",
+ "3 5 1 41 1 True\n",
+ "4 4 1 40 1 True\n",
+ ".. ... .. .. ... ...\n",
+ "450 427 3 30 13 False\n",
+ "451 426 3 31 13 False\n",
+ "452 425 3 32 13 False\n",
+ "453 424 3 33 13 False\n",
+ "454 423 3 34 13 False\n",
+ "\n",
+ "[455 rows x 5 columns]"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "e163e703",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.8.18"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/mrdna/readers/test/libs b/mrdna/readers/test/libs
new file mode 120000
index 0000000000000000000000000000000000000000..d4bda9b46951e0c8c2007f84bbc447f93995502d
--- /dev/null
+++ b/mrdna/readers/test/libs
@@ -0,0 +1 @@
+../libs
\ No newline at end of file
diff --git a/mrdna/readers/test/test2.ipynb b/mrdna/readers/test/test2.ipynb
index 825e255b883e0a49cde86e0bb75fda657d1bd01f..d0cca2fb700e21cf8abfd26e49a9f0314ba27da3 100644
--- a/mrdna/readers/test/test2.ipynb
+++ b/mrdna/readers/test/test2.ipynb
@@ -3,7 +3,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "9ea65628",
+ "id": "dc6eff4b",
"metadata": {},
"outputs": [
{
@@ -28,7 +28,7 @@
{
"cell_type": "code",
"execution_count": 585,
- "id": "1aaf81df-7464-4bd0-ace5-3b04e63815ac",
+ "id": "8b2c0150",
"metadata": {},
"outputs": [],
"source": [
@@ -93,7 +93,7 @@
{
"cell_type": "code",
"execution_count": 586,
- "id": "c72e5d53-f082-4daa-8e36-6d74bfe8802b",
+ "id": "03e94b3f",
"metadata": {},
"outputs": [
{
@@ -111,7 +111,7 @@
{
"cell_type": "code",
"execution_count": 587,
- "id": "ff1c4a3c-9dde-4ea1-b360-f5d5d149b7d0",
+ "id": "b4a95a34",
"metadata": {},
"outputs": [],
"source": [
@@ -171,7 +171,7 @@
{
"cell_type": "code",
"execution_count": 612,
- "id": "2356f6ba-8109-4ca1-8704-94f3c6a3bebd",
+ "id": "d917f1db",
"metadata": {},
"outputs": [],
"source": [
@@ -223,7 +223,7 @@
{
"cell_type": "code",
"execution_count": 613,
- "id": "d1e57e0e-efba-43c9-abdb-9fd7a7d0760b",
+ "id": "02380150",
"metadata": {},
"outputs": [
{
@@ -525,7 +525,7 @@
{
"cell_type": "code",
"execution_count": 609,
- "id": "c042b68c-6651-418e-b07c-dc3444afebdd",
+ "id": "1649bd22",
"metadata": {},
"outputs": [
{
@@ -897,7 +897,7 @@
{
"cell_type": "code",
"execution_count": 604,
- "id": "259da9ce-568d-4f9e-9394-bb64e56f0eb2",
+ "id": "ddd2a089",
"metadata": {},
"outputs": [
{
@@ -1207,7 +1207,7 @@
{
"cell_type": "code",
"execution_count": 573,
- "id": "e8fb6171-a275-46b6-ac62-ac2867a30739",
+ "id": "2e5785a9",
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"outputs": [
{
@@ -1228,7 +1228,7 @@
{
"cell_type": "code",
"execution_count": 572,
- "id": "675f4a88-18fe-4d6a-bae9-de364e2f4174",
+ "id": "a7dd2412",
"metadata": {},
"outputs": [
{
@@ -1249,7 +1249,7 @@
{
"cell_type": "code",
"execution_count": 412,
- "id": "946198dc-c458-481f-a9aa-3dd4b0f86676",
+ "id": "c47ecad6",
"metadata": {},
"outputs": [
{
@@ -1283,7 +1283,7 @@
{
"cell_type": "code",
"execution_count": 411,
- "id": "59f3720b-b3c0-44c7-b7ea-6923d2e7f2d6",
+ "id": "960e1971",
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"outputs": [
{
@@ -1305,7 +1305,7 @@
{
"cell_type": "code",
"execution_count": 404,
- "id": "7f94d3f9-2f55-4e25-be6c-735e8de905f2",
+ "id": "ef2bbb72",
"metadata": {},
"outputs": [
{
@@ -1359,7 +1359,7 @@
{
"cell_type": "code",
"execution_count": 340,
- "id": "b29dc9a7-b4cd-43a8-b374-1a6c3c37e326",
+ "id": "78791389",
"metadata": {},
"outputs": [
{
@@ -1390,7 +1390,7 @@
{
"cell_type": "code",
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- "id": "c26b53aa-2b60-4a42-85f0-2cdf626cf14a",
+ "id": "cea2904e",
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"outputs": [],
"source": [
@@ -1423,7 +1423,7 @@
{
"cell_type": "code",
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- "id": "25f9ab74-6b64-4bbf-a6c3-c67c811d42e6",
+ "id": "97741ea0",
"metadata": {},
"outputs": [
{
@@ -1444,7 +1444,7 @@
{
"cell_type": "code",
"execution_count": 342,
- "id": "5d3b60a4-14ec-4723-9693-4b05b95554d1",
+ "id": "8c17bcd4",
"metadata": {},
"outputs": [
{
@@ -1491,7 +1491,7 @@
{
"cell_type": "code",
"execution_count": 343,
- "id": "0ec83cb6-9abf-4fca-a639-ec6aedf1b14a",
+ "id": "7d8e5f7c",
"metadata": {},
"outputs": [
{
@@ -1599,7 +1599,7 @@
{
"cell_type": "code",
"execution_count": 333,
- "id": "fc57ba88-6a6a-4d47-8ac6-da84a9f2ab34",
+ "id": "599ac0c4",
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"outputs": [
{
@@ -1620,7 +1620,7 @@
{
"cell_type": "code",
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- "id": "85312ea2-5b2c-4fff-a44c-c506686d74ca",
+ "id": "fa362209",
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"outputs": [
{
@@ -1641,7 +1641,7 @@
{
"cell_type": "code",
"execution_count": 363,
- "id": "fe8f6f2c-f9ac-48c5-868d-a9e90a4fc675",
+ "id": "75556652",
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"source": [
@@ -1655,7 +1655,7 @@
{
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- "id": "64967867-a819-4345-9153-5dba2ec33ec3",
+ "id": "723a82ee",
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"outputs": [
{
@@ -1796,7 +1796,7 @@
{
"cell_type": "code",
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- "id": "6b942c47-1109-4ac2-ac1b-7210fa7a505e",
+ "id": "f533d602",
"metadata": {},
"outputs": [
{
@@ -1973,7 +1973,7 @@
{
"cell_type": "code",
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- "id": "678e48ea-568b-4ad3-98f3-2556b596b70f",
+ "id": "90373add",
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"outputs": [
{
@@ -1994,7 +1994,7 @@
{
"cell_type": "code",
"execution_count": 339,
- "id": "a27de404-e5c5-4526-9d18-bcff3d8d7b5f",
+ "id": "41730a11",
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"outputs": [
{
@@ -2044,7 +2044,7 @@
{
"cell_type": "code",
"execution_count": 383,
- "id": "02a111ba-ea1e-410b-918e-bccbbdd4141e",
+ "id": "74149aca",
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"outputs": [
{
@@ -2067,7 +2067,7 @@
{
"cell_type": "code",
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- "id": "8a27e1a0-fb25-475d-bc62-0adc23d6b261",
+ "id": "8897c37a",
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"source": [
@@ -2106,7 +2106,7 @@
{
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- "id": "1389dcb5-51f9-480c-b657-aa7abbd4a2fa",
+ "id": "ca5ab939",
"metadata": {},
"outputs": [
{
@@ -2127,7 +2127,7 @@
{
"cell_type": "code",
"execution_count": 242,
- "id": "c817bd74-a725-4520-826c-8c1f80c02d56",
+ "id": "72ff2747",
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"outputs": [
{
@@ -2155,7 +2155,7 @@
{
"cell_type": "code",
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- "id": "ca879ef9-1acc-4943-8c05-62b95558638c",
+ "id": "9c47abe2",
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"outputs": [
{
@@ -2176,7 +2176,7 @@
{
"cell_type": "code",
"execution_count": 134,
- "id": "1b55d792-37eb-453d-a3db-382b239cf62d",
+ "id": "869b4c51",
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"outputs": [
{
@@ -2262,7 +2262,7 @@
{
"cell_type": "code",
"execution_count": 139,
- "id": "f8302226-2614-4d47-8050-e332e0ade9f2",
+ "id": "4a723a6d",
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"outputs": [
{
@@ -2283,7 +2283,7 @@
{
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- "id": "4221131e-75af-4676-bb67-24b91d978f72",
+ "id": "05e4da72",
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"outputs": [
{
@@ -2760,7 +2760,7 @@
{
"cell_type": "code",
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- "id": "bb4c1c28-0bed-4f3a-b046-241137968efd",
+ "id": "f6127aee",
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"source": [
@@ -2770,7 +2770,7 @@
{
"cell_type": "code",
"execution_count": 94,
- "id": "86772cec-5ebd-4a09-9068-3fe5684a8a00",
+ "id": "ebc61bad",
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"source": [
@@ -2785,7 +2785,7 @@
{
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- "id": "ca575331-81bb-4d12-8230-65450bbb7100",
+ "id": "e805d776",
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"outputs": [],
"source": [
@@ -2800,7 +2800,7 @@
{
"cell_type": "code",
"execution_count": 106,
- "id": "9238476c-157b-4e47-bd2d-e2d66ebc91d8",
+ "id": "c4233e44",
"metadata": {},
"outputs": [
{
@@ -2821,7 +2821,7 @@
{
"cell_type": "code",
"execution_count": 77,
- "id": "4ed59693-4783-4dda-bffa-e9f256c3d211",
+ "id": "7f754821",
"metadata": {},
"outputs": [
{
@@ -2844,7 +2844,7 @@
{
"cell_type": "code",
"execution_count": 648,
- "id": "38a3dacc-7991-4475-b356-44043fd90984",
+ "id": "3b2b320c",
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"outputs": [],
"source": [
@@ -2859,7 +2859,7 @@
{
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- "id": "3d9610cb-d6ea-4c56-be9b-1b23f623fe66",
+ "id": "d6f94b1a",
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"source": [
@@ -2936,7 +2936,7 @@
{
"cell_type": "code",
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- "id": "dbcb2c6d-2e3f-4952-b21e-c624ca2026dc",
+ "id": "e8e1e470",
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"source": [
@@ -2946,7 +2946,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "e7b1dda8-1c43-4f22-b7bb-54e006134cb5",
+ "id": "8f43874a",
"metadata": {},
"outputs": [
{
@@ -3121,7 +3121,7 @@
{
"cell_type": "code",
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- "id": "898974c3-dcbb-4374-bf1d-86c87a643d6e",
+ "id": "110d5497",
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"source": [
@@ -3170,7 +3170,7 @@
{
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- "id": "722d5ad3-52bc-4c95-856c-a0766e28c701",
+ "id": "c08f2d64",
"metadata": {},
"outputs": [
{
@@ -3191,7 +3191,7 @@
{
"cell_type": "code",
"execution_count": 67,
- "id": "325c75d6-6951-439d-b2b3-ff2e74cc2245",
+ "id": "6f52e5fd",
"metadata": {},
"outputs": [
{
@@ -3212,7 +3212,7 @@
{
"cell_type": "code",
"execution_count": 151,
- "id": "76d1979d-74c2-4ffb-8dc5-659b889d52b6",
+ "id": "6f3833ba",
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"source": [
@@ -3264,7 +3264,7 @@
{
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- "id": "45e6434e-58a9-4aa2-b1f7-6b871daedba3",
+ "id": "2e9d3446",
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"source": [
@@ -3299,7 +3299,7 @@
{
"cell_type": "code",
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- "id": "44f994b6-6c49-4b8a-916b-7ac224558ded",
+ "id": "48cdbf0e",
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"source": [
@@ -3310,7 +3310,7 @@
{
"cell_type": "code",
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- "id": "fae9db1a-6148-4cd6-9d30-6c6d8ccbcec6",
+ "id": "cecfc5a0",
"metadata": {},
"outputs": [
{
@@ -3345,7 +3345,7 @@
{
"cell_type": "code",
"execution_count": 117,
- "id": "6db39eca-d003-4690-a140-18e6abb6b246",
+ "id": "c5b1e868",
"metadata": {},
"outputs": [
{
@@ -3501,7 +3501,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "4e4ae946-464f-4033-8462-5c5931198123",
+ "id": "071f75e4",
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"source": []
@@ -3509,7 +3509,7 @@
{
"cell_type": "code",
"execution_count": 119,
- "id": "8c52f71c-0333-4d50-a9f7-92dbe60226cb",
+ "id": "48922b22",
"metadata": {},
"outputs": [
{
@@ -3665,7 +3665,7 @@
{
"cell_type": "code",
"execution_count": 355,
- "id": "039b65c8-5a0d-4127-a2dc-2808ce11fba1",
+ "id": "fee43329",
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"outputs": [
{
@@ -3687,7 +3687,7 @@
{
"cell_type": "code",
"execution_count": 368,
- "id": "570999f4-a7b9-400b-a61d-c1d66eaf0999",
+ "id": "a7497054",
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"source": [
@@ -3705,7 +3705,7 @@
{
"cell_type": "code",
"execution_count": 370,
- "id": "b0e5cb3c-8cb4-4fd6-8fcc-1b63c7733acd",
+ "id": "9009e4cd",
"metadata": {},
"outputs": [
{
@@ -3724,7 +3724,7 @@
{
"cell_type": "code",
"execution_count": 371,
- "id": "837c9a06-1e50-434d-b97b-70bfb8d20c42",
+ "id": "e2d6bdf4",
"metadata": {},
"outputs": [
{
@@ -3744,7 +3744,7 @@
{
"cell_type": "code",
"execution_count": 225,
- "id": "998f4321-f520-45f7-bffb-92177b6a0fec",
+ "id": "7d633643",
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"outputs": [
{
@@ -3958,7 +3958,7 @@
{
"cell_type": "code",
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- "id": "10ec47a4-3221-468d-a185-b171c5bd82f6",
+ "id": "85ee4835",
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"outputs": [
{
@@ -4149,7 +4149,7 @@
{
"cell_type": "code",
"execution_count": 216,
- "id": "4a136eaa-919b-4ad7-88be-42169cfab25f",
+ "id": "27e36674",
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"outputs": [
{
@@ -4351,7 +4351,7 @@
{
"cell_type": "code",
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- "id": "fc6acf26-2c3a-405b-b905-dd116fc5c875",
+ "id": "21312024",
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"source": [
@@ -4362,7 +4362,7 @@
{
"cell_type": "code",
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- "id": "87066a06-49a9-4cd2-9082-135372adc0d7",
+ "id": "d5d42a45",
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"outputs": [
{
@@ -4383,7 +4383,7 @@
{
"cell_type": "code",
"execution_count": 52,
- "id": "6cf497ad-08f1-4901-b855-bb44be284f87",
+ "id": "a9db4952",
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"outputs": [
{
@@ -4404,7 +4404,7 @@
{
"cell_type": "code",
"execution_count": 43,
- "id": "27717aa9-0a17-444d-866a-50fc3fa31ca2",
+ "id": "0e365769",
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"outputs": [
{
@@ -4425,7 +4425,7 @@
{
"cell_type": "code",
"execution_count": 34,
- "id": "5dc7d2bf-5221-4afd-ad45-e97dab156d83",
+ "id": "fcce904b",
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"outputs": [
{
@@ -4446,7 +4446,7 @@
{
"cell_type": "code",
"execution_count": 33,
- "id": "12fd269b-1dc5-488c-a246-0d91d9e2fdd5",
+ "id": "3df07b51",
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"outputs": [
{
@@ -4468,7 +4468,7 @@
{
"cell_type": "code",
"execution_count": 22,
- "id": "ef80053e-350c-4c5a-ac94-c1ffbedc1e46",
+ "id": "45a7b213",
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"outputs": [
{
@@ -4495,7 +4495,7 @@
{
"cell_type": "code",
"execution_count": 11,
- "id": "4e2dd66e-fe4d-4728-8233-60cb1d9b156a",
+ "id": "8bb0fc3c",
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"source": [
@@ -4505,7 +4505,7 @@
{
"cell_type": "code",
"execution_count": 18,
- "id": "4952a867-7839-4d65-b3d3-228b401fa4de",
+ "id": "22b8b30f",
"metadata": {},
"outputs": [
{
@@ -4527,7 +4527,7 @@
{
"cell_type": "code",
"execution_count": 626,
- "id": "5d1d1bea-7d71-476b-928b-18b5cf0bd2e5",
+ "id": "bd153170",
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"outputs": [
{
@@ -4548,7 +4548,7 @@
{
"cell_type": "code",
"execution_count": 15,
- "id": "91b1be83-f406-47f3-8e63-11a0262a653a",
+ "id": "24f087bc",
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"outputs": [
{
@@ -4569,7 +4569,7 @@
{
"cell_type": "code",
"execution_count": 723,
- "id": "e616db25-a0fa-47ea-917d-28f2ec18c67e",
+ "id": "413d249f",
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"outputs": [
{
@@ -4590,7 +4590,7 @@
{
"cell_type": "code",
"execution_count": 721,
- "id": "216ec8a1-d779-4725-b3c2-4a2f01c3dd52",
+ "id": "f5d6e341",
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"outputs": [
{
@@ -4611,7 +4611,7 @@
{
"cell_type": "code",
"execution_count": 700,
- "id": "0d5d750d-f978-4096-b819-8a26ca2be63d",
+ "id": "533c907f",
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"outputs": [
{
@@ -4632,7 +4632,7 @@
{
"cell_type": "code",
"execution_count": 710,
- "id": "855c45bb-5744-48ff-9ea3-4a7ab6221208",
+ "id": "e09cfdbf",
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"outputs": [
{
@@ -4654,7 +4654,7 @@
{
"cell_type": "code",
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- "id": "7af4b044-e9e9-43e3-ab29-1cac35a9ac46",
+ "id": "2c437b78",
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"source": [
@@ -4698,7 +4698,7 @@
{
"cell_type": "code",
"execution_count": 734,
- "id": "3c488e25-5333-4a34-bbe4-6467dc291894",
+ "id": "f2347ff4",
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"outputs": [
{
@@ -4722,7 +4722,7 @@
{
"cell_type": "code",
"execution_count": 741,
- "id": "d9c3d962-831f-4b5f-b889-e6173f7e2c5c",
+ "id": "7c0c4211",
"metadata": {},
"outputs": [
{
@@ -4743,7 +4743,7 @@
{
"cell_type": "code",
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- "id": "eff8f4a8-a228-40d5-8487-e091b1c425d9",
+ "id": "57fdb681",
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"source": []
@@ -4751,7 +4751,7 @@
{
"cell_type": "code",
"execution_count": 728,
- "id": "eb4f45b4-3064-4238-830b-0dfea9a0e99d",
+ "id": "ef323244",
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"outputs": [
{
@@ -4772,7 +4772,7 @@
{
"cell_type": "code",
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- "id": "42960c56-4516-4021-989a-4e2848ad4215",
+ "id": "d150a90e",
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"outputs": [
{
@@ -4793,7 +4793,7 @@
{
"cell_type": "code",
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- "id": "2c4153a3-88a1-4b6a-ac1d-0bdd3d9ef621",
+ "id": "7f887064",
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"outputs": [
{
@@ -4827,7 +4827,7 @@
{
"cell_type": "code",
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- "id": "83578dcc-15c5-4112-9225-ba93370bfd3c",
+ "id": "d1801a30",
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"source": []
@@ -4835,7 +4835,7 @@
{
"cell_type": "code",
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- "id": "09e48bf8-ae24-4d32-817e-f576a9ca019c",
+ "id": "98228b41",
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"outputs": [
{
@@ -4856,7 +4856,7 @@
{
"cell_type": "code",
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- "id": "9517ec2a-d5f9-4a7f-8af9-1d042486b6c5",
+ "id": "29af8a0b",
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"outputs": [
{
@@ -4936,7 +4936,7 @@
{
"cell_type": "code",
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- "id": "c0e69e86-6319-480e-a781-80c2a3524ea9",
+ "id": "31f41e6f",
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"outputs": [
{
@@ -5022,7 +5022,7 @@
{
"cell_type": "code",
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- "id": "66d0e76d-3ab9-4caf-8a11-e73069372672",
+ "id": "908a6a7c",
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"outputs": [
{
@@ -5054,7 +5054,7 @@
{
"cell_type": "code",
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- "id": "c907f808-bcdc-4157-ac33-508aa748e42e",
+ "id": "1e1b275c",
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{
@@ -5075,7 +5075,7 @@
{
"cell_type": "code",
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- "id": "5d8aeaca-e795-41a0-a9be-f5e5db5e111f",
+ "id": "0877b142",
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"source": [
@@ -5085,7 +5085,7 @@
{
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- "id": "93c6bfde-9974-4b99-b65c-85b99ed70895",
+ "id": "f08e6106",
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{
@@ -5106,7 +5106,7 @@
{
"cell_type": "code",
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- "id": "0dc56391-5cc7-49a5-bdc0-674c1ff93488",
+ "id": "dd1f0da6",
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{
@@ -5132,7 +5132,7 @@
{
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- "id": "522678a9-81e9-40e5-9e56-400f054bd5d4",
+ "id": "781af10a",
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@@ -5140,7 +5140,7 @@
{
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- "id": "39f36967-8c42-45c5-84b5-e1fab790be36",
+ "id": "1ec8afe3",
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@@ -5148,7 +5148,7 @@
{
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- "id": "ab8aa441-4b59-4d54-b44d-f776ab8e9e61",
+ "id": "83841b72",
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"source": [
@@ -5158,7 +5158,7 @@
{
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"execution_count": 91,
- "id": "73e69794-fc0a-486e-85f9-88a57276ee68",
+ "id": "0ffa8dce",
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"outputs": [
{
@@ -6250,7 +6250,7 @@
{
"cell_type": "code",
"execution_count": 92,
- "id": "acf7fe2e-0203-485e-a176-d711c847477a",
+ "id": "8016534d",
"metadata": {},
"outputs": [
{
@@ -6270,7 +6270,7 @@
{
"cell_type": "code",
"execution_count": 962,
- "id": "bce3f7a8-b003-4a82-ade5-37501b68c0f4",
+ "id": "d1b135ec",
"metadata": {},
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{
@@ -6302,7 +6302,7 @@
{
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- "id": "8208056b-181d-43bd-a344-ec6d0a24b7f6",
+ "id": "b9f5de0c",
"metadata": {},
"outputs": [
{
@@ -6324,7 +6324,7 @@
{
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- "id": "f07e1b32",
+ "id": "b716b68c",
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"source": [
@@ -6349,7 +6349,7 @@
{
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"execution_count": 575,
- "id": "6931b352-2f85-4ba1-9de3-a53c24041c0c",
+ "id": "b647bf01",
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"outputs": [
{
@@ -6394,7 +6394,7 @@
{
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- "id": "43cda523-ec1a-42ca-b546-17ffac4dea17",
+ "id": "7658064d",
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"outputs": [
{
@@ -6931,7 +6931,7 @@
{
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- "id": "ec3b6b7c-f03a-4c34-85d9-e4f44ed59792",
+ "id": "92cc1374",
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{
@@ -6952,7 +6952,7 @@
{
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- "id": "dadccba2-b9b3-4110-8328-1076ede1432c",
+ "id": "ef75c586",
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{
@@ -7060,7 +7060,7 @@
{
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- "id": "0db298ba-4f29-49d8-bdc3-a6faa4674e22",
+ "id": "81cbd9b5",
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{
@@ -7114,7 +7114,7 @@
{
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- "id": "72874b29-ac4d-4c89-abd6-187e1d2a99aa",
+ "id": "de5a0dec",
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"source": [
@@ -7124,7 +7124,7 @@
{
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- "id": "4af733b6-ebfd-47fc-aaef-2ee5d4267c88",
+ "id": "02bfe5a7",
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"outputs": [
{
@@ -7145,7 +7145,7 @@
{
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- "id": "828c35da-7c02-469d-9a8e-ee2420bed581",
+ "id": "a1f7b5f7",
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"outputs": [
{
@@ -7199,7 +7199,7 @@
{
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- "id": "ffd99357-946a-4334-8202-4fd78e63e062",
+ "id": "a3b9ba54",
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"outputs": [
{
@@ -7307,7 +7307,7 @@
{
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- "id": "828c7161-0700-4bcd-a51e-eeb195340e35",
+ "id": "855e6ac0",
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{
@@ -7336,7 +7336,7 @@
{
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- "id": "4c0546f8-b0d4-45b2-9d81-d3699ee95921",
+ "id": "24b34ab1",
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"source": [
@@ -7350,7 +7350,7 @@
{
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- "id": "7c15d8bc-7c0e-46bb-860b-cfa5cf5a5a0c",
+ "id": "2a7f64d5",
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"outputs": [
{
@@ -7371,7 +7371,7 @@
{
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- "id": "eaef916c-98d2-47c9-948e-a7fd76a1d3b4",
+ "id": "9625b974",
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"outputs": [
{
@@ -7392,7 +7392,7 @@
{
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- "id": "ca6571df-2523-484a-a5b8-32cf44bb5afc",
+ "id": "b9faf1ec",
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"outputs": [
{
@@ -7428,7 +7428,7 @@
{
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- "id": "b5d1a3b8-f616-4050-ae12-de34bd18b4c9",
+ "id": "e9da09cb",
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{
@@ -7464,7 +7464,7 @@
{
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- "id": "559bab5d-b474-4d30-99dc-e97ae61e39e5",
+ "id": "e3164ef8",
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"source": [
@@ -7479,7 +7479,7 @@
{
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- "id": "a500615f-07df-4e65-9dc6-ef94af3dfcdf",
+ "id": "7db1e084",
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"outputs": [
{
@@ -7501,7 +7501,7 @@
{
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- "id": "69e89135-155f-4413-a4f4-d7323528c211",
+ "id": "c05dcdf7",
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{
@@ -7522,7 +7522,7 @@
{
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- "id": "9139dfed-d055-408f-986f-c96da4cb88af",
+ "id": "d21a4c75",
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{
@@ -7549,7 +7549,7 @@
{
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- "id": "7e39d2ea-b5d7-40a6-b43f-7e43ab26cc4f",
+ "id": "1fc5a43d",
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"source": [
@@ -7560,7 +7560,7 @@
{
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- "id": "a5ba9310-16b1-4faa-b9c7-6ac5073df569",
+ "id": "bad64953",
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"source": [
@@ -7574,7 +7574,7 @@
{
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- "id": "05b7fa7d-5329-4f0c-8a94-c3631494e9bb",
+ "id": "71938d89",
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"source": [
@@ -7584,7 +7584,7 @@
{
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- "id": "cfc0060c-188c-4cc5-9cbe-ff7fa2eb89e4",
+ "id": "3ded5871",
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"outputs": [
{
@@ -7605,7 +7605,7 @@
{
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- "id": "2b8a31bf-f956-4bf1-8546-140ebca169f4",
+ "id": "f51f621d",
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"outputs": [
{
@@ -7626,7 +7626,7 @@
{
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- "id": "36855d5e-c95c-4642-a162-ca1ef378a3d4",
+ "id": "f82ad368",
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"outputs": [
{
@@ -7647,7 +7647,7 @@
{
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- "id": "dfaef123-43a8-43af-869d-cd4407c41e8c",
+ "id": "ceff793a",
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{
@@ -7668,7 +7668,7 @@
{
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- "id": "a9a3b1f8-eae4-42f6-ae88-99832ab47070",
+ "id": "97021a7d",
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"source": [
@@ -7678,7 +7678,7 @@
{
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- "id": "13618171-1df2-4db0-b24c-7a7470a6c615",
+ "id": "a55d6ed0",
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"outputs": [
{
@@ -7699,7 +7699,7 @@
{
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- "id": "d9e4b3c5-cecb-4d1f-a283-6069b6837dad",
+ "id": "ec00022c",
"metadata": {
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},
@@ -7855,7 +7855,7 @@
{
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- "id": "f18fdcc9-6ead-4bd2-ab0e-1c759e328f2f",
+ "id": "f01ff5f5",
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"source": [
@@ -7901,7 +7901,7 @@
{
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- "id": "2d929c54-7b65-48d2-b28b-68562af15104",
+ "id": "209a9ec4",
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"source": [
@@ -7943,7 +7943,7 @@
{
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- "id": "d20b67b7-94fc-4200-a84b-edd66b355c01",
+ "id": "1a4362b4",
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"outputs": [
{
@@ -7965,7 +7965,7 @@
{
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- "id": "5daca1b7-beb5-42ba-94c6-911ab6ca33be",
+ "id": "e75969ed",
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"outputs": [
{
@@ -7983,7 +7983,7 @@
{
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- "id": "d4bc3787-567f-4e57-823e-7c844c7eb262",
+ "id": "fd487bbd",
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"source": [
@@ -7993,7 +7993,7 @@
{
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- "id": "3a01b186-cb93-4f92-b8d0-0db0bc45e104",
+ "id": "c4d6d76f",
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{
@@ -8426,7 +8426,7 @@
{
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- "id": "1d2a4032-a6b6-4ad7-bcf5-03bf37cb68e0",
+ "id": "ab80c811",
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"source": [
@@ -8436,7 +8436,7 @@
{
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- "id": "3cd82283-e341-4dfd-95c4-e789d3630f74",
+ "id": "bdd17c47",
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"outputs": [
{
@@ -8475,7 +8475,7 @@
{
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- "id": "c5eba0d7-3972-4553-a9dd-f6fccaef7a4e",
+ "id": "a6ec640f",
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"source": [
@@ -8485,7 +8485,7 @@
{
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- "id": "a650a181-1258-4dfd-b41c-f4142f6034ef",
+ "id": "866dea3c",
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{
@@ -8509,7 +8509,7 @@
{
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- "id": "324e02ef-7688-45bf-80be-f80d25cc1516",
+ "id": "85107410",
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{
@@ -8530,7 +8530,7 @@
{
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- "id": "6b7d23a1-b66a-47ca-b59e-42d1addabee5",
+ "id": "1d0c53e2",
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"source": [
@@ -8540,7 +8540,7 @@
{
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- "id": "ab0b76c4-c77d-4bbb-9883-bd7b8c1569f2",
+ "id": "7dfcd349",
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"outputs": [
{
@@ -8579,7 +8579,7 @@
{
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- "id": "0e8099a0-70d1-4119-bd56-33b79a83359c",
+ "id": "3463c436",
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{
@@ -8597,7 +8597,7 @@
{
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- "id": "55d4b8da-692a-40ae-9e1a-3030f2dd659f",
+ "id": "2f7b05ea",
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"source": [
@@ -8610,7 +8610,7 @@
{
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- "id": "a7a02cdd-7409-441a-8e60-07b5912d8e56",
+ "id": "aa6a38b4",
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"source": []
@@ -8618,7 +8618,7 @@
{
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- "id": "65ebfe49-aae9-42a3-acb5-0a7afb390e8d",
+ "id": "1cbba0c4",
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"source": [
@@ -8628,7 +8628,7 @@
{
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- "id": "8a5ea8a4-3353-4779-b6aa-98c8919259c9",
+ "id": "77f98a7c",
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"source": [
@@ -8638,7 +8638,7 @@
{
"cell_type": "code",
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- "id": "ff047223-c82c-4ac4-b30e-65c41613a9e4",
+ "id": "d84bbc60",
"metadata": {},
"outputs": [
{
@@ -8656,7 +8656,7 @@
{
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- "id": "c5832bdd-1df9-4af7-8cb7-89d522a33c86",
+ "id": "84c8d193",
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"outputs": [
{
@@ -8718,7 +8718,7 @@
{
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- "id": "a7a8c302-165a-404f-aa98-f857b8839638",
+ "id": "0f676819",
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"outputs": [
{
@@ -8739,7 +8739,7 @@
{
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- "id": "6b6ab174-90a3-4414-a798-806fb1793937",
+ "id": "fb77d05b",
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"source": [
@@ -8749,7 +8749,7 @@
{
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- "id": "843291d1-530f-4c2b-97e3-65b30d814cf9",
+ "id": "8773e21e",
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"outputs": [
{
@@ -8770,7 +8770,7 @@
{
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- "id": "4a4cbdb1-f626-4817-9bee-c2d9fed0675d",
+ "id": "e9474108",
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"outputs": [
{
@@ -8911,7 +8911,7 @@
{
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- "id": "a6e188a0-52c9-4f27-9e91-f9f0f6b43829",
+ "id": "cc427ae3",
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"outputs": [
{
@@ -8932,7 +8932,7 @@
{
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- "id": "6dbd83c9-1542-4acf-8e54-1f279db6da3a",
+ "id": "c9e8ca40",
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"outputs": [
{
@@ -8953,7 +8953,7 @@
{
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- "id": "08856a0e-eb36-4e2f-a68d-55b43ca38a82",
+ "id": "6acfc452",
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{
@@ -8974,7 +8974,7 @@
{
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- "id": "15747c0b-8bcc-414e-b570-03c1a61cf8b9",
+ "id": "b81e769a",
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{
@@ -8995,7 +8995,7 @@
{
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- "id": "5164cbab-4cad-49cb-b578-162f4df8fb3d",
+ "id": "2feba736",
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{
@@ -9016,7 +9016,7 @@
{
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- "id": "9de2a715-9a6d-48ca-98d3-154c6856f73c",
+ "id": "8c43c66a",
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{
@@ -9037,7 +9037,7 @@
{
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- "id": "4fa350d1-50a9-4d03-a808-a948f9db12af",
+ "id": "c901f8b6",
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{
@@ -9058,7 +9058,7 @@
{
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- "id": "f9246900-a13c-40d8-b345-8167199f45de",
+ "id": "b4857eb2",
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{
@@ -9079,7 +9079,7 @@
{
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- "id": "bc02e0de-08a8-42d3-afd8-2b21f616d470",
+ "id": "558950e7",
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{
@@ -9102,7 +9102,7 @@
{
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- "id": "e5238c66-a33b-4e93-ad9a-1a8fefe574cc",
+ "id": "539ce808",
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{
@@ -9123,7 +9123,7 @@
{
"cell_type": "code",
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- "id": "803533ed-9577-4eca-9d51-c106f3efb3d1",
+ "id": "7ead24d8",
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{
@@ -9146,7 +9146,7 @@
{
"cell_type": "code",
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- "id": "75d655fc-46e1-4b4d-9e05-ee1403e2e363",
+ "id": "b3cbd599",
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"outputs": [
{
@@ -9169,7 +9169,7 @@
{
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- "id": "1dda0acd-7dd4-467c-9633-66c5350d1911",
+ "id": "afb4f5a2",
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{
@@ -9449,7 +9449,7 @@
{
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- "id": "67b2283f-b3ec-4941-9753-8939883fc634",
+ "id": "748fe7b3",
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"source": [
@@ -9459,7 +9459,7 @@
{
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- "id": "055da421-6f35-47ba-b54a-dedaff3851f5",
+ "id": "56ca49e4",
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"source": [
@@ -9470,7 +9470,7 @@
{
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- "id": "b9337cb3-5725-4a22-956d-0f7bfdf98f1e",
+ "id": "aedfee5c",
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"source": [
@@ -9481,7 +9481,7 @@
{
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- "id": "307dcec8-b15f-48c0-895e-b57794d96c1e",
+ "id": "bca51eab",
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{
@@ -9502,7 +9502,7 @@
{
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- "id": "9ff52284-e37d-466c-a844-3cbc929433b8",
+ "id": "e8ded03d",
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{
@@ -9523,7 +9523,7 @@
{
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- "id": "319ede75-f8a8-4f80-9d90-f990d351cc1b",
+ "id": "5bc9446c",
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{
@@ -9542,7 +9542,7 @@
{
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- "id": "9e6bd392-559f-449b-8a4e-049d8b100349",
+ "id": "87a3d3d4",
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{
@@ -9565,7 +9565,7 @@
{
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- "id": "03cc2f40-8c54-44ff-b590-81cf857c2965",
+ "id": "5cf1bda5",
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{
@@ -9588,7 +9588,7 @@
{
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- "id": "6efd2667-59d7-4ad3-b9a9-faf8f003399b",
+ "id": "b5623d70",
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{
@@ -9612,7 +9612,7 @@
{
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- "id": "9063878f-b3bd-4856-9d5b-68f459ea6e06",
+ "id": "252c7557",
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@@ -9622,7 +9622,7 @@
{
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- "id": "69c6d275-9b13-4add-bcb0-75c281628f09",
+ "id": "97b5272f",
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@@ -9630,7 +9630,7 @@
{
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"execution_count": 398,
- "id": "dcba5559-a9c1-40ce-854d-ca2ceefd61d0",
+ "id": "c04586ae",
"metadata": {},
"outputs": [],
"source": [
@@ -9640,7 +9640,7 @@
{
"cell_type": "code",
"execution_count": 401,
- "id": "0b3beb34-9715-4719-b0b2-778c54891555",
+ "id": "38e35695",
"metadata": {},
"outputs": [
{
@@ -9669,7 +9669,7 @@
{
"cell_type": "code",
"execution_count": 258,
- "id": "efdc824b-d784-40c8-98fd-af86f4887319",
+ "id": "fb6c1940",
"metadata": {},
"outputs": [
{
@@ -9690,7 +9690,7 @@
{
"cell_type": "code",
"execution_count": 232,
- "id": "07cb8a8b-32c0-4aac-a8e2-9b10ab938fbc",
+ "id": "c97ca649",
"metadata": {},
"outputs": [
{
@@ -9727,7 +9727,7 @@
{
"cell_type": "code",
"execution_count": 225,
- "id": "fc06b8ed-283f-4365-a063-c87f43598bef",
+ "id": "3f5fd50c",
"metadata": {},
"outputs": [],
"source": [
@@ -9737,7 +9737,7 @@
{
"cell_type": "code",
"execution_count": 64,
- "id": "9c67d96b-a9e9-43cb-8617-bae9d6fb36bf",
+ "id": "a1fa67e1",
"metadata": {},
"outputs": [
{
@@ -9841,7 +9841,7 @@
{
"cell_type": "code",
"execution_count": 26,
- "id": "66a215f5-fac0-455b-b990-a0713a2e3e62",
+ "id": "671c1103",
"metadata": {},
"outputs": [
{
@@ -10121,7 +10121,7 @@
{
"cell_type": "code",
"execution_count": 344,
- "id": "6c6b8a93-aa6d-4a5e-83c9-fb66381c6ce3",
+ "id": "9d40f975",
"metadata": {},
"outputs": [
{
@@ -10144,7 +10144,7 @@
{
"cell_type": "code",
"execution_count": 90,
- "id": "fe082e4f-7622-4a9c-ac54-17cd2cb741d2",
+ "id": "beb6f2e1",
"metadata": {},
"outputs": [
{
@@ -10286,7 +10286,7 @@
{
"cell_type": "code",
"execution_count": 59,
- "id": "4d9e756f-8f34-4738-909c-a1714e4a4459",
+ "id": "b937875e",
"metadata": {},
"outputs": [],
"source": [
@@ -10394,7 +10394,7 @@
{
"cell_type": "code",
"execution_count": 60,
- "id": "dd26d9a2-9676-4286-8032-442997d872c2",
+ "id": "959da213",
"metadata": {},
"outputs": [
{
@@ -10424,7 +10424,7 @@
{
"cell_type": "code",
"execution_count": 16,
- "id": "26d573d8-7e97-40bb-81f2-554009fbe689",
+ "id": "11fe1806",
"metadata": {},
"outputs": [],
"source": [
@@ -10434,7 +10434,7 @@
{
"cell_type": "code",
"execution_count": 141,
- "id": "caa9367f-1047-4d70-b0c0-2ea99015adc9",
+ "id": "9ff3e583",
"metadata": {},
"outputs": [
{
@@ -10869,7 +10869,7 @@
{
"cell_type": "code",
"execution_count": 133,
- "id": "2ac38001-5cb0-4df8-b6ff-0853f3b4a7f3",
+ "id": "e03ffa2d",
"metadata": {},
"outputs": [],
"source": [
@@ -10879,7 +10879,7 @@
{
"cell_type": "code",
"execution_count": 134,
- "id": "7c2c51bb-c1d5-4ec3-abb6-15d7d357cf63",
+ "id": "18babab0",
"metadata": {},
"outputs": [],
"source": [
@@ -10889,7 +10889,7 @@
{
"cell_type": "code",
"execution_count": 126,
- "id": "3fc0b810-6b65-4cbe-adbb-13ebe72ee1b8",
+ "id": "0c86903a",
"metadata": {},
"outputs": [
{
@@ -11324,7 +11324,7 @@
{
"cell_type": "code",
"execution_count": 24,
- "id": "a4d48fe0",
+ "id": "8e415fab",
"metadata": {},
"outputs": [
{
@@ -11350,7 +11350,7 @@
{
"cell_type": "code",
"execution_count": 29,
- "id": "03d8b6e7",
+ "id": "40b69f5d",
"metadata": {},
"outputs": [
{
@@ -11426,7 +11426,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "884f07ed",
+ "id": "e1a470a1",
"metadata": {},
"outputs": [],
"source": []
@@ -11434,7 +11434,7 @@
{
"cell_type": "code",
"execution_count": 92,
- "id": "1e934f2b",
+ "id": "39ca5192",
"metadata": {},
"outputs": [],
"source": [
@@ -11445,7 +11445,7 @@
{
"cell_type": "code",
"execution_count": 94,
- "id": "1f942831-b170-4d1b-b445-1f58565bf2f1",
+ "id": "e7696931",
"metadata": {},
"outputs": [
{
@@ -11479,7 +11479,7 @@
{
"cell_type": "code",
"execution_count": 35,
- "id": "e5b59a91",
+ "id": "28df4d21",
"metadata": {},
"outputs": [
{
@@ -11508,7 +11508,7 @@
{
"cell_type": "code",
"execution_count": 36,
- "id": "78ecf1e1",
+ "id": "f138e2a6",
"metadata": {},
"outputs": [
{
@@ -11616,7 +11616,7 @@
{
"cell_type": "code",
"execution_count": 10,
- "id": "680d09ca",
+ "id": "551b9c83",
"metadata": {},
"outputs": [
{
@@ -11647,7 +11647,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "190a91a3",
+ "id": "16df6d54",
"metadata": {},
"outputs": [
{
@@ -12144,7 +12144,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "ba82a4ed",
+ "id": "78158c38",
"metadata": {},
"outputs": [
{
@@ -12178,7 +12178,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "79e8a471",
+ "id": "aec96741",
"metadata": {},
"outputs": [
{
@@ -12198,7 +12198,7 @@
{
"cell_type": "code",
"execution_count": 5,
- "id": "71b7ffdc",
+ "id": "e444c4d7",
"metadata": {},
"outputs": [],
"source": [
@@ -12208,7 +12208,7 @@
{
"cell_type": "code",
"execution_count": 6,
- "id": "f7c95c63",
+ "id": "10f8f13b",
"metadata": {},
"outputs": [
{
@@ -12229,7 +12229,7 @@
{
"cell_type": "code",
"execution_count": 7,
- "id": "e905bb35",
+ "id": "999e4520",
"metadata": {},
"outputs": [
{
@@ -12256,7 +12256,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "8964b3a5",
+ "id": "58798ad1",
"metadata": {},
"outputs": [],
"source": []
@@ -12264,7 +12264,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3 (ipykernel)",
+ "display_name": "Python 3",
"language": "python",
"name": "python3"
},
diff --git a/mrdna/readers/test/test3.ipynb b/mrdna/readers/test/test3.ipynb
index 6f0498793c5889dcbb67d320129db43b5861fe21..9af0e8487266696db83962d5a9c9b839b752a5d3 100644
--- a/mrdna/readers/test/test3.ipynb
+++ b/mrdna/readers/test/test3.ipynb
@@ -2,36 +2,25 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 124,
- "id": "303b2da7",
+ "execution_count": 15,
+ "id": "47cc3f7f",
"metadata": {
"scrolled": true
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "dict_keys(['row', 'col', 'num', 'scaf', 'stap', 'loop', 'skip', 'scafLoop', 'stapLoop', 'stap_colors'])"
- ]
- },
- "execution_count": 124,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"import pandas as pd\n",
"import pickle\n",
- "import numpy as np\n",
- "df=pd.read_json(\"test.json\")\n",
- "df[\"vstrands\"][0].keys()"
+ "import numpy as np\n"
]
},
{
"cell_type": "code",
"execution_count": 164,
- "id": "2d42bba6",
- "metadata": {},
+ "id": "b993f66a",
+ "metadata": {
+ "scrolled": true
+ },
"outputs": [
{
"data": {
@@ -91,107 +80,433 @@
},
{
"cell_type": "code",
- "execution_count": 65,
- "id": "5e1ea864",
+ "execution_count": 21,
+ "id": "5361b91a",
"metadata": {},
- "outputs": [
- {
- "ename": "UnicodeDecodeError",
- "evalue": "'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mUnicodeDecodeError\u001b[0m Traceback (most recent call last)",
- "\u001b[0;32m<ipython-input-65-71f198107f5e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"test.virt2nuc\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\"r\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
- "\u001b[0;32m/data/server1/cmaffeo2/miniconda3/lib/python3.8/codecs.py\u001b[0m in \u001b[0;36mdecode\u001b[0;34m(self, input, final)\u001b[0m\n\u001b[1;32m 320\u001b[0m \u001b[0;31m# decode input (taking the buffer into account)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 321\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 322\u001b[0;31m \u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconsumed\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer_decode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfinal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 323\u001b[0m \u001b[0;31m# keep undecoded input until the next call\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 324\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mconsumed\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte"
- ]
- }
- ],
+ "outputs": [],
"source": [
- "f=open(\"test.virt2nuc\",\"r\")\n",
- "pickle.load(f)"
+ "import pickle\n",
+ "f=open(\"test.virt2nuc\",\"rb\")\n",
+ "vh_vb,pattern=pickle.load(f)\n",
+ "def find_vh_vb_table(s,is_scaf):\n",
+ " L=[]\n",
+ " for i in list(s.keys()):\n",
+ " vh,zid=i\n",
+ " strand,indices=s[i]\n",
+ " if len(indices)==0:\n",
+ " continue\n",
+ " else:\n",
+ " if len(indices)==1:\n",
+ " zids=[str(zid)]\n",
+ " else:\n",
+ " zids=[str(zid)+\".\"+str(j) for j in range(len(indices))]\n",
+ " for index,z in zip(indices,zids):\n",
+ " L.append(pd.Series({\"index\":index,\"vh\":vh,\"zid\":z,\"strand\":strand,\"is_scaf\":bool(is_scaf)}))\n",
+ " return L\n",
+ "L1=find_vh_vb_table(vh_vb._scaf,1)\n",
+ "L2=find_vh_vb_table(vh_vb._stap,0)\n",
+ "nt_prop=pd.DataFrame(L1+L2,dtype=object)"
]
},
{
"cell_type": "code",
- "execution_count": 119,
- "id": "86a109f4",
- "metadata": {},
+ "execution_count": 22,
+ "id": "a10c3f52",
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "find_vh_vb_table(vh_vb._stap,0)\n",
+ "nt_prop=pd.DataFrame(L1+L2,dtype=object)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "id": "6c4a0fa6",
+ "metadata": {
+ "scrolled": true
+ },
"outputs": [
{
"data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>index</th>\n",
+ " <th>vh</th>\n",
+ " <th>zid</th>\n",
+ " <th>strand</th>\n",
+ " <th>is_scaf</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>2</td>\n",
+ " <td>0</td>\n",
+ " <td>39</td>\n",
+ " <td>0</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>1</td>\n",
+ " <td>0</td>\n",
+ " <td>40</td>\n",
+ " <td>0</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>0</td>\n",
+ " <td>0</td>\n",
+ " <td>41</td>\n",
+ " <td>0</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>5</td>\n",
+ " <td>1</td>\n",
+ " <td>41</td>\n",
+ " <td>1</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>4</td>\n",
+ " <td>1</td>\n",
+ " <td>40</td>\n",
+ " <td>1</td>\n",
+ " <td>True</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>410</th>\n",
+ " <td>386</td>\n",
+ " <td>3</td>\n",
+ " <td>30</td>\n",
+ " <td>13</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>411</th>\n",
+ " <td>385</td>\n",
+ " <td>3</td>\n",
+ " <td>31</td>\n",
+ " <td>13</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>412</th>\n",
+ " <td>384</td>\n",
+ " <td>3</td>\n",
+ " <td>32</td>\n",
+ " <td>13</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>413</th>\n",
+ " <td>383</td>\n",
+ " <td>3</td>\n",
+ " <td>33</td>\n",
+ " <td>13</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>414</th>\n",
+ " <td>382</td>\n",
+ " <td>3</td>\n",
+ " <td>34</td>\n",
+ " <td>13</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>415 rows × 5 columns</p>\n",
+ "</div>"
+ ],
"text/plain": [
- "210"
+ " index vh zid strand is_scaf\n",
+ "0 2 0 39 0 True\n",
+ "1 1 0 40 0 True\n",
+ "2 0 0 41 0 True\n",
+ "3 5 1 41 1 True\n",
+ "4 4 1 40 1 True\n",
+ ".. ... .. .. ... ...\n",
+ "410 386 3 30 13 False\n",
+ "411 385 3 31 13 False\n",
+ "412 384 3 32 13 False\n",
+ "413 383 3 33 13 False\n",
+ "414 382 3 34 13 False\n",
+ "\n",
+ "[415 rows x 5 columns]"
]
},
- "execution_count": 119,
+ "execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "vh_vb,pattern=pd.read_pickle(\"test.virt2nuc\")\n",
- "len(vh_vb._scaf)"
+ "nt_prop[]"
]
},
{
"cell_type": "code",
- "execution_count": 66,
- "id": "ab020675",
+ "execution_count": 12,
+ "id": "0d9ff4d1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "{0: (12, 16), 1: (12, 15), 2: (13, 15), 3: (13, 16), 4: (13, 17), 5: (12, 17)}"
+ "{(2, 34): (3, [43]),\n",
+ " (2, 33): (3, [42]),\n",
+ " (2, 32): (3, [41]),\n",
+ " (2, 31): (3, [40]),\n",
+ " (2, 30): (3, [39]),\n",
+ " (2, 29): (3, [38]),\n",
+ " (2, 28): (3, [37]),\n",
+ " (2, 27): (3, [36]),\n",
+ " (2, 26): (3, [35]),\n",
+ " (2, 25): (3, [34]),\n",
+ " (2, 24): (3, [33]),\n",
+ " (2, 23): (3, [32]),\n",
+ " (2, 22): (3, [31]),\n",
+ " (2, 21): (3, [30]),\n",
+ " (2, 20): (3, [29]),\n",
+ " (2, 19): (3, [28]),\n",
+ " (2, 18): (3, [27]),\n",
+ " (2, 17): (3, [26]),\n",
+ " (2, 16): (3, [25]),\n",
+ " (2, 15): (3, [24]),\n",
+ " (2, 14): (3, [23]),\n",
+ " (2, 13): (3, [22]),\n",
+ " (2, 12): (3, [21]),\n",
+ " (2, 11): (3, [20]),\n",
+ " (2, 10): (3, [19]),\n",
+ " (2, 9): (3, [18]),\n",
+ " (2, 8): (3, [17]),\n",
+ " (2, 7): (3, [16]),\n",
+ " (2, 6): (3, [15]),\n",
+ " (2, 5): (3, [14]),\n",
+ " (2, 4): (3, [13]),\n",
+ " (2, 3): (3, [12]),\n",
+ " (2, 2): (3, [11]),\n",
+ " (2, 1): (3, [10]),\n",
+ " (2, 0): (3, [9]),\n",
+ " (1, 3): (8, [281]),\n",
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+ " (1, 6): (8, [278]),\n",
+ " (1, 7): (8, [277]),\n",
+ " (1, 8): (8, [276]),\n",
+ " (1, 9): (8, [275]),\n",
+ " (1, 10): (8, [274]),\n",
+ " (1, 11): (8, [273]),\n",
+ " (1, 12): (8, [272]),\n",
+ " (1, 13): (8, [271]),\n",
+ " (1, 14): (8, [270]),\n",
+ " (1, 15): (8, [269]),\n",
+ " (1, 16): (8, [268]),\n",
+ " (1, 17): (8, [267]),\n",
+ " (1, 18): (8, [266]),\n",
+ " (1, 19): (8, [265]),\n",
+ " (1, 20): (8, [264]),\n",
+ " (0, 20): (8, [263]),\n",
+ " (0, 19): (8, [262]),\n",
+ " (0, 18): (8, [261]),\n",
+ " (0, 17): (8, [260]),\n",
+ " (0, 16): (8, [259]),\n",
+ " (0, 15): (8, [258]),\n",
+ " (0, 14): (8, [257]),\n",
+ " (0, 13): (8, [256]),\n",
+ " (0, 12): (8, [255]),\n",
+ " (0, 11): (8, [254]),\n",
+ " (0, 10): (8, [253]),\n",
+ " (0, 9): (8, [252]),\n",
+ " (0, 8): (8, [251]),\n",
+ " (0, 7): (8, [250]),\n",
+ " (0, 6): (8, [249]),\n",
+ " (0, 5): (8, [248]),\n",
+ " (0, 4): (8, [247]),\n",
+ " (0, 3): (8, [246]),\n",
+ " (0, 2): (8, [245]),\n",
+ " (0, 23): (9, [302]),\n",
+ " (0, 22): (9, [301]),\n",
+ " (0, 21): (9, [300]),\n",
+ " (1, 21): (9, [299]),\n",
+ " (1, 22): (9, [298]),\n",
+ " (1, 23): (9, [297]),\n",
+ " (1, 24): (9, [296]),\n",
+ " (1, 25): (9, [295]),\n",
+ " (1, 26): (9, [294]),\n",
+ " (1, 27): (9, [293]),\n",
+ " (1, 28): (9, [292]),\n",
+ " (1, 29): (9, [291]),\n",
+ " (1, 30): (9, [290]),\n",
+ " (1, 31): (9, [289]),\n",
+ " (1, 32): (9, [288]),\n",
+ " (1, 33): (9, [287]),\n",
+ " (1, 34): (9, [286]),\n",
+ " (1, 35): (9, [285]),\n",
+ " (1, 36): (9, [284]),\n",
+ " (1, 37): (9, [283]),\n",
+ " (1, 38): (9, [282]),\n",
+ " (5, 9): (10, [325]),\n",
+ " (5, 10): (10, [324]),\n",
+ " (5, 11): (10, [323]),\n",
+ " (5, 12): (10, [322]),\n",
+ " (5, 13): (10, [321]),\n",
+ " (5, 14): (10, [320]),\n",
+ " (5, 15): (10, [319]),\n",
+ " (5, 16): (10, [318]),\n",
+ " (5, 17): (10, [317]),\n",
+ " (5, 18): (10, [316]),\n",
+ " (5, 19): (10, [315]),\n",
+ " (5, 20): (10, [314]),\n",
+ " (5, 21): (10, [313]),\n",
+ " (5, 22): (10, [312]),\n",
+ " (5, 23): (10, [311]),\n",
+ " (5, 24): (10, [310]),\n",
+ " (5, 25): (10, [309]),\n",
+ " (5, 26): (10, [308]),\n",
+ " (5, 27): (10, [307]),\n",
+ " (0, 27): (10, [306]),\n",
+ " (0, 26): (10, [305]),\n",
+ " (0, 25): (10, [304]),\n",
+ " (0, 24): (10, [303]),\n",
+ " (0, 38): (11, [348]),\n",
+ " (0, 37): (11, [347]),\n",
+ " (0, 36): (11, [346]),\n",
+ " (0, 35): (11, [345]),\n",
+ " (0, 34): (11, [344]),\n",
+ " (0, 33): (11, [343]),\n",
+ " (0, 32): (11, [342]),\n",
+ " (0, 31): (11, [341]),\n",
+ " (0, 30): (11, [340]),\n",
+ " (0, 29): (11, [339]),\n",
+ " (0, 28): (11, [338]),\n",
+ " (5, 28): (11, [337]),\n",
+ " (5, 29): (11, [336]),\n",
+ " (5, 30): (11, [335]),\n",
+ " (5, 31): (11, [334]),\n",
+ " (5, 32): (11, [333]),\n",
+ " (5, 33): (11, [332]),\n",
+ " (5, 34): (11, [331]),\n",
+ " (5, 35): (11, [330]),\n",
+ " (5, 36): (11, [329]),\n",
+ " (5, 37): (11, [328]),\n",
+ " (5, 38): (11, [327]),\n",
+ " (5, 39): (11, [326]),\n",
+ " (3, 0): (12, [381]),\n",
+ " (3, 1): (12, [380]),\n",
+ " (3, 2): (12, [379]),\n",
+ " (3, 3): (12, [378]),\n",
+ " (3, 4): (12, [377]),\n",
+ " (3, 5): (12, [376]),\n",
+ " (3, 6): (12, [375]),\n",
+ " (3, 7): (12, [374]),\n",
+ " (3, 8): (12, [373]),\n",
+ " (3, 9): (12, [372]),\n",
+ " (3, 10): (12, [371]),\n",
+ " (3, 11): (12, [370]),\n",
+ " (3, 12): (12, [369]),\n",
+ " (3, 13): (12, [368]),\n",
+ " (3, 14): (12, [367]),\n",
+ " (3, 15): (12, [366]),\n",
+ " (3, 16): (12, [365]),\n",
+ " (3, 17): (12, [364]),\n",
+ " (3, 18): (12, [363]),\n",
+ " (3, 19): (12, [362]),\n",
+ " (3, 20): (12, [361]),\n",
+ " (4, 20): (12, [360]),\n",
+ " (4, 19): (12, [359]),\n",
+ " (4, 18): (12, [358]),\n",
+ " (4, 17): (12, [357]),\n",
+ " (4, 16): (12, [356]),\n",
+ " (4, 15): (12, [355]),\n",
+ " (4, 14): (12, [354]),\n",
+ " (4, 13): (12, [353]),\n",
+ " (4, 12): (12, [352]),\n",
+ " (4, 11): (12, [351]),\n",
+ " (4, 10): (12, [350]),\n",
+ " (4, 9): (12, [349]),\n",
+ " (4, 39): (13, [414]),\n",
+ " (4, 38): (13, [413]),\n",
+ " (4, 37): (13, [412]),\n",
+ " (4, 36): (13, [411]),\n",
+ " (4, 35): (13, [410]),\n",
+ " (4, 34): (13, [409]),\n",
+ " (4, 33): (13, [408]),\n",
+ " (4, 32): (13, [407]),\n",
+ " (4, 31): (13, [406]),\n",
+ " (4, 30): (13, [405]),\n",
+ " (4, 29): (13, [404]),\n",
+ " (4, 28): (13, [403]),\n",
+ " (4, 27): (13, [402]),\n",
+ " (4, 26): (13, [401]),\n",
+ " (4, 25): (13, [400]),\n",
+ " (4, 24): (13, [399]),\n",
+ " (4, 23): (13, [398]),\n",
+ " (4, 22): (13, [397]),\n",
+ " (4, 21): (13, [396]),\n",
+ " (3, 21): (13, [395]),\n",
+ " (3, 22): (13, [394]),\n",
+ " (3, 23): (13, [393]),\n",
+ " (3, 24): (13, [392]),\n",
+ " (3, 25): (13, [391]),\n",
+ " (3, 26): (13, [390]),\n",
+ " (3, 27): (13, [389]),\n",
+ " (3, 28): (13, [388]),\n",
+ " (3, 29): (13, [387]),\n",
+ " (3, 30): (13, [386]),\n",
+ " (3, 31): (13, [385]),\n",
+ " (3, 32): (13, [384]),\n",
+ " (3, 33): (13, [383]),\n",
+ " (3, 34): (13, [382])}"
]
},
- "execution_count": 66,
+ "execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "pattern"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 141,
- "id": "0b152186",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "(0, 40)\n",
- "(0, 41)\n"
- ]
- },
- {
- "ename": "AttributeError",
- "evalue": "'NoneType' object has no attribute 'append'",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
- "\u001b[0;32m<ipython-input-141-a0e59df19136>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ms\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdecode_vh_vb\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"test.virt2nuc\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_dict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;32m<ipython-input-140-99891f72666f>\u001b[0m in \u001b[0;36mdecode_vh_vb\u001b[0;34m(virt2nuc)\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0mscafs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvh_vb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_scaf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[0mstaps\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvh_vb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_stap\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 23\u001b[0;31m \u001b[0mscaf_strands\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfind_segs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscafs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 24\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 25\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mvh_list\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;32m<ipython-input-140-99891f72666f>\u001b[0m in \u001b[0;36mfind_segs\u001b[0;34m(vir2nuc_scaf)\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvir2nuc_scaf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0moligos\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0moligo\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0moligos\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0moligo\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvir2nuc_scaf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 11\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0moligos\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'append'"
- ]
- }
- ],
- "source": [
- "s=decode_vh_vb(\"test.virt2nuc\")[0]\n"
+ "n=list(vh_vb._stap.keys())\n",
+ "vh_vb._stap"
]
},
{
"cell_type": "code",
"execution_count": 165,
- "id": "852198d8",
+ "id": "cd863c53",
"metadata": {},
"outputs": [],
"source": [
@@ -229,7 +544,7 @@
{
"cell_type": "code",
"execution_count": 160,
- "id": "b4064749",
+ "id": "4f91e6e1",
"metadata": {},
"outputs": [],
"source": [
@@ -273,7 +588,7 @@
{
"cell_type": "code",
"execution_count": 163,
- "id": "ae57cd6f",
+ "id": "7b654425",
"metadata": {},
"outputs": [
{
@@ -490,7 +805,7 @@
{
"cell_type": "code",
"execution_count": 157,
- "id": "d4698785",
+ "id": "0b77e10b",
"metadata": {},
"outputs": [
{
@@ -514,7 +829,7 @@
{
"cell_type": "code",
"execution_count": 152,
- "id": "2b98d0e2",
+ "id": "afd7317c",
"metadata": {},
"outputs": [
{
@@ -535,7 +850,7 @@
{
"cell_type": "code",
"execution_count": 62,
- "id": "f666ffb1",
+ "id": "c65032d0",
"metadata": {},
"outputs": [
{
@@ -763,7 +1078,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "04da1a1e",
+ "id": "e15d2aa1",
"metadata": {},
"outputs": [],
"source": [
@@ -889,7 +1204,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "c168b2f4",
+ "id": "c6dfa08f",
"metadata": {},
"outputs": [],
"source": [
@@ -910,7 +1225,7 @@
{
"cell_type": "code",
"execution_count": 20,
- "id": "1e29e6a7",
+ "id": "4dcbd8e3",
"metadata": {},
"outputs": [
{
@@ -972,7 +1287,7 @@
{
"cell_type": "code",
"execution_count": 25,
- "id": "fd26bfad",
+ "id": "9404f68b",
"metadata": {},
"outputs": [
{
@@ -1034,7 +1349,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "438d3345",
+ "id": "c758c48e",
"metadata": {},
"outputs": [],
"source": [
@@ -1047,7 +1362,7 @@
{
"cell_type": "code",
"execution_count": 13,
- "id": "595fa2ff",
+ "id": "14885dc7",
"metadata": {},
"outputs": [
{
@@ -1068,7 +1383,7 @@
{
"cell_type": "code",
"execution_count": 7,
- "id": "3d614740",
+ "id": "2d9f9b60",
"metadata": {},
"outputs": [
{
@@ -1117,7 +1432,7 @@
{
"cell_type": "code",
"execution_count": 36,
- "id": "831d5ea6",
+ "id": "c82d79df",
"metadata": {},
"outputs": [
{
@@ -1179,7 +1494,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "7831eb35",
+ "id": "6fe9bc07",
"metadata": {},
"outputs": [
{
@@ -1205,7 +1520,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "28c9253b",
+ "id": "99e0edfc",
"metadata": {},
"outputs": [],
"source": []
@@ -1213,7 +1528,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "a018193b",
+ "id": "6b01ed08",
"metadata": {},
"outputs": [
{
@@ -1233,7 +1548,7 @@
{
"cell_type": "code",
"execution_count": 13,
- "id": "2bc520fd",
+ "id": "ada91cfc",
"metadata": {},
"outputs": [
{
@@ -1254,7 +1569,7 @@
{
"cell_type": "code",
"execution_count": 15,
- "id": "117520a1",
+ "id": "5545caf9",
"metadata": {},
"outputs": [
{
@@ -1324,7 +1639,7 @@
{
"cell_type": "code",
"execution_count": 16,
- "id": "d8eb98b3",
+ "id": "86b74eac",
"metadata": {},
"outputs": [],
"source": [
@@ -1335,7 +1650,7 @@
{
"cell_type": "code",
"execution_count": 26,
- "id": "44db9666",
+ "id": "1e2447da",
"metadata": {},
"outputs": [
{
@@ -1444,7 +1759,7 @@
{
"cell_type": "code",
"execution_count": 25,
- "id": "52ccbb65",
+ "id": "9ae6bbc0",
"metadata": {},
"outputs": [
{
@@ -1465,7 +1780,7 @@
{
"cell_type": "code",
"execution_count": 10,
- "id": "66171e52",
+ "id": "1f66b770",
"metadata": {},
"outputs": [
{
@@ -1496,7 +1811,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "34ff0906",
+ "id": "71886708",
"metadata": {},
"outputs": [
{
@@ -1993,7 +2308,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "53a3183e",
+ "id": "639aea0c",
"metadata": {},
"outputs": [
{
@@ -2027,7 +2342,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "fdcadbe9",
+ "id": "457d395d",
"metadata": {},
"outputs": [
{
@@ -2047,7 +2362,7 @@
{
"cell_type": "code",
"execution_count": 5,
- "id": "d27fd998",
+ "id": "3c98514b",
"metadata": {},
"outputs": [],
"source": [
@@ -2057,7 +2372,7 @@
{
"cell_type": "code",
"execution_count": 6,
- "id": "fe094a9b",
+ "id": "490f9736",
"metadata": {},
"outputs": [
{
@@ -2078,7 +2393,7 @@
{
"cell_type": "code",
"execution_count": 7,
- "id": "5e54cf99",
+ "id": "c6058056",
"metadata": {},
"outputs": [
{
@@ -2105,7 +2420,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "bbeb8724",
+ "id": "07504a71",
"metadata": {},
"outputs": [],
"source": []
@@ -2113,21 +2428,9 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3 (ipykernel)",
+ "display_name": "Python 3",
"language": "python",
"name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.8.19"
}
},
"nbformat": 4,
diff --git a/mrdna/readers/test/tests.ipynb b/mrdna/readers/test/tests.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..3de002b34ac0c2434e62c062f5b2f71852aff4cd
--- /dev/null
+++ b/mrdna/readers/test/tests.ipynb
@@ -0,0 +1,5758 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 52,
+ "id": "0ed58664",
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "import pickle\n",
+ "import numpy as np\n",
+ "import json\n",
+ "import re\n",
+ "import cadnano\n",
+ "from cadnano.document import Document\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "10b47d85",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from cadnano.views.pathview import pathstyles"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "fa8a0a91",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " _\n",
+ " _____ ___ _| |___ ___\n",
+ "| | _| . | | .'|\n",
+ "|_|_|_|_| |___|_|_|__,| v1.0a.dev116 \n",
+ "it/its\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "import cadnano\n",
+ "from cadnano.document import Document\n",
+ "from mrdna.arbdmodel.coords import readArbdCoords, readAvgArbdCoords, rotationAboutAxis"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "05a6db77",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_lattice(part):\n",
+ " lattice_type = None\n",
+ " _gt = part.getGridType()\n",
+ " try:\n",
+ " lattice_type = _gt.name.lower()\n",
+ " except:\n",
+ " if _gt == 1:\n",
+ " lattice_type = 'square'\n",
+ " elif _gt == 2:\n",
+ " lattice_type = 'honeycomb'\n",
+ " else:\n",
+ " print(lattice_type)\n",
+ " return lattice_type\n",
+ "\n",
+ "\n",
+ "def read_json_file(filename):\n",
+ " import cadnano\n",
+ " from cadnano.document import Document\n",
+ "\n",
+ " try:\n",
+ " with open(filename) as ch:\n",
+ " json_data = json.load(ch)\n",
+ " except:\n",
+ " with open(filename) as ch:\n",
+ " content = \"\"\n",
+ " for l in ch:\n",
+ " l = re.sub(r\"'\", r'\"', l)\n",
+ " # https://stackoverflow.com/questions/4033633/handling-lazy-json-in-python-expecting-property-name\n",
+ " # l = re.sub(r\"{\\s*(\\w)\", r'{\"\\1', l)\n",
+ " # l = re.sub(r\",\\s*(\\w)\", r',\"\\1', l)\n",
+ " # l = re.sub(r\"(\\w):\", r'\\1\":', l)\n",
+ " content += l+\"\\n\"\n",
+ " json_data = json.loads(content)\n",
+ "\n",
+ " try:\n",
+ " doc = Document()\n",
+ " cadnano.fileio.v3decode.decode(doc, json_data)\n",
+ " decoder = 3\n",
+ " except:\n",
+ " doc = Document()\n",
+ " cadnano.fileio.v2decode.decode(doc, json_data)\n",
+ " decoder = 2\n",
+ "\n",
+ " parts = [p for p in doc.getParts()]\n",
+ " if len(parts) != 1:\n",
+ " raise Exception(\"Only documents containing a single cadnano part are implemented at this time.\")\n",
+ " part = parts[0]\n",
+ "\n",
+ " if decoder == 2:\n",
+ " \"\"\" It seems cadnano2.5 (as of ce6ff019) does not set the EulerZ for square lattice structures correctly, doing so here \"\"\"\n",
+ " l = get_lattice(part)\n",
+ " if l == 'square':\n",
+ " for id_num in part.getIdNums():\n",
+ " if part.vh_properties.loc[id_num,'eulerZ'] == 0:\n",
+ " part.vh_properties.loc[id_num,'eulerZ'] = 360*(6/10.5)\n",
+ " df=pd.DataFrame(json_data[\"vstrands\"])\n",
+ " n_df=df.set_index(\"num\")\n",
+ " return part\n",
+ "\n",
+ "def get_helix_angle(part, helix_id, indices):\n",
+ " \"\"\" Get \"start_orientation\" for helix \"\"\"\n",
+ " # import ipdb\n",
+ " # ipdb.set_trace()\n",
+ "\n",
+ " \"\"\" FROM CADNANO2.5\n",
+ " + angle is CCW\n",
+ " - angle is CW\n",
+ " Right handed DNA rotates clockwise from 5' to 3'\n",
+ " we use the convention the 5' end starts at 0 degrees\n",
+ " and it's pair is minor_groove_angle degrees away\n",
+ " direction, hence the minus signs. eulerZ\n",
+ " \"\"\"\n",
+ "\n",
+ " hp, bpr, tpr, eulerZ, mgroove = part.vh_properties.loc[helix_id,\n",
+ " ['helical_pitch',\n",
+ " 'bases_per_repeat',\n",
+ " 'turns_per_repeat',\n",
+ " 'eulerZ',\n",
+ " 'minor_groove_angle']]\n",
+ " twist_per_base = tpr*360./bpr\n",
+ " # angle = eulerZ - twist_per_base*indices + 0.5*mgroove + 180\n",
+ " angle = eulerZ + twist_per_base*indices - 0.5*mgroove\n",
+ " return angle\n",
+ "\n",
+ "def gen_id_series(strand,part):\n",
+ " df=pd.DataFrame(columns=[\"vh\",\"zid\",\"fwd\",\"stack_tuple\",\"threeprime_tuple\",\"x\",\"y\",\"z\"],index=range(strand.totalLength()),dtype=object)\n",
+ " df[\"vh\"]=strand._id_num\n",
+ " df[\"fwd\"]=strand.isForward()\n",
+ " df[\"x\"]=part.getVirtualHelixOrigin(strand._id_num)[0]*10\n",
+ " df[\"y\"]=part.getVirtualHelixOrigin(strand._id_num)[1]*10\n",
+ " id_lo,id_hi=strand.idxs()\n",
+ " zids=[str(i) for i in range(id_lo,id_hi+1)]\n",
+ " insert_dict={}\n",
+ " insert_dict=dict([(j.idx(),j.length()) for j in strand.insertionsOnStrand()])\n",
+ " z=np.arange(id_lo,id_hi+1)\n",
+ " zids=[str(i) for i in range(id_lo,id_hi+1)]\n",
+ " z=list(np.arange(id_lo,id_hi+1))\n",
+ " zids=[str(i) for i in range(id_lo,id_hi+1)]\n",
+ " for insert_base in insert_dict:\n",
+ " z_ind=zids.index(str(insert_base))\n",
+ " z_val=insert_dict[insert_base]\n",
+ " z_pos_ind=z.index(insert_base)\n",
+ " zids.pop(z_ind)\n",
+ " z.pop(z_pos_ind)\n",
+ " if z_val!=-1:\n",
+ " #l=[str(insert_base)+\".\"+str(i) for i in range(z_val+1)]\n",
+ " l=list(range(z_val+1))\n",
+ " l.reverse()\n",
+ " for k in l: \n",
+ " zids.insert(z_ind,str(insert_base)+\".\"+str(k))\n",
+ " z.insert(z_pos_ind,insert_base+k/(z_val+1))\n",
+ " df[\"zid\"]=zids\n",
+ " df[\"z\"]=np.array(z)*3.4\n",
+ " \n",
+ " \n",
+ " L=[(df[\"vh\"][i],df[\"zid\"][i],df[\"fwd\"][i]) for i in df.index]\n",
+ " if strand.isForward()==True:\n",
+ " df[\"stack_tuple\"]=L[1:]+[-1]\n",
+ " if strand.connection3p() is None:\n",
+ " df[\"threeprime_tuple\"]=L[1:]+[-1]\n",
+ " else:\n",
+ " df[\"threeprime_tuple\"]=L[1:]+[(strand.connection3p().idNum(),str(strand.connection3p().idx5Prime()),strand.connection3p().isForward())]\n",
+ " \n",
+ " \n",
+ " else:\n",
+ " df[\"stack_tuple\"]=[-1]+L[0:-1]\n",
+ " if strand.connection3p() is None:\n",
+ " df[\"threeprime_tuple\"]=[-1]+L[0:-1]\n",
+ " else:\n",
+ " df[\"threeprime_tuple\"]=[(strand.connection3p().idNum(),str(strand.connection3p().idx5Prime()),strand.connection3p().isForward())]+L[0:-1]\n",
+ " ## cadnano 3.1 sequence assign is wrong if there is insertion or deletion. \n",
+ " df[\"r\"]=[np.array([df[\"x\"][i],df[\"y\"][i],df[\"z\"][i]],dtype=np.float32) for i in df.index]\n",
+ " \n",
+ " return [pd.Series(df.loc[i]) for i in df.index]\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 44,
+ "id": "e13a5231",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Found cadnano version 2 file\n"
+ ]
+ }
+ ],
+ "source": [
+ "n=read_json_file(\"test_insert.json\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 45,
+ "id": "d41d4f68",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "<ipython-input-43-f3af6cfd4751>:25: SettingWithCopyWarning: \n",
+ "A value is trying to be set on a copy of a slice from a DataFrame\n",
+ "\n",
+ "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+ " nt_prop[\"stack_tuple\"][i]=(nt_prop.loc[i][\"vh\"],str(zid),fwd)\n"
+ ]
+ }
+ ],
+ "source": [
+ "m=gen_prop_table(n)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 50,
+ "id": "e4da7f1c",
+ "metadata": {},
+ "outputs": [
+ {
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+ " (5, '38', False)]"
+ ]
+ },
+ "execution_count": 50,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "list(m[\"stack_tuple\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "id": "4ba4afde",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "vhzid=list(zip(m[\"vh\"],m[\"zid\"],m[\"fwd\"]))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "id": "4f08e344",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "86"
+ ]
+ },
+ "execution_count": 22,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "vhzid.index((0,str(int(\"21\")+1),False))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "id": "a6597822",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ind,=np.where(m[\"stack_tuple\"]==-1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 42,
+ "id": "d5c11476",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "<ipython-input-42-30730821dc20>:10: SettingWithCopyWarning: \n",
+ "A value is trying to be set on a copy of a slice from a DataFrame\n",
+ "\n",
+ "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+ " m[\"stack_tuple\"][i]=(vh,str(zid),fwd)\n"
+ ]
+ }
+ ],
+ "source": [
+ "for i in ind:\n",
+ " vh,zid,fwd=m[\"vh\"][i],int(m[\"zid\"][i]),m[\"fwd\"][i]\n",
+ " if fwd is True:\n",
+ " print(fwd)\n",
+ " zid+=1\n",
+ " else:\n",
+ " zid-=1\n",
+ " try:\n",
+ " n=vhzid.index((vh,str(zid),fwd))\n",
+ " m[\"stack_tuple\"][i]=(vh,str(zid),fwd)\n",
+ " except:\n",
+ " continue"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 41,
+ "id": "4703a0b8",
+ "metadata": {},
+ "outputs": [
+ {
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+ " <td>77.942295</td>\n",
+ " <td>45.00</td>\n",
+ " <td>125.8</td>\n",
+ " <td>[77.94229, 45.0, 125.8]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>1178.571429</td>\n",
+ " <td>-1</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>326</th>\n",
+ " <td>3</td>\n",
+ " <td>4</td>\n",
+ " <td>3</td>\n",
+ " <td>True</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>97.427869</td>\n",
+ " <td>56.25</td>\n",
+ " <td>10.2</td>\n",
+ " <td>[97.42787, 56.25, 10.2]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>12.857143</td>\n",
+ " <td>-1</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>333</th>\n",
+ " <td>6</td>\n",
+ " <td>4</td>\n",
+ " <td>15</td>\n",
+ " <td>True</td>\n",
+ " <td>(4, 16, True)</td>\n",
+ " <td>(3, 15, False)</td>\n",
+ " <td>97.427869</td>\n",
+ " <td>56.25</td>\n",
+ " <td>51.0</td>\n",
+ " <td>[97.42787, 56.25, 51.0]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>301</td>\n",
+ " <td>424.285714</td>\n",
+ " <td>364</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>357</th>\n",
+ " <td>23</td>\n",
+ " <td>4</td>\n",
+ " <td>39</td>\n",
+ " <td>True</td>\n",
+ " <td>-1</td>\n",
+ " <td>(5, 39, False)</td>\n",
+ " <td>97.427869</td>\n",
+ " <td>56.25</td>\n",
+ " <td>132.6</td>\n",
+ " <td>[97.42787, 56.25, 132.6]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>454</td>\n",
+ " <td>1247.142857</td>\n",
+ " <td>388</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>358</th>\n",
+ " <td>0</td>\n",
+ " <td>4</td>\n",
+ " <td>9</td>\n",
+ " <td>False</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>97.427869</td>\n",
+ " <td>56.25</td>\n",
+ " <td>30.6</td>\n",
+ " <td>[97.42787, 56.25, 30.6]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>218.571429</td>\n",
+ " <td>327</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>370</th>\n",
+ " <td>0</td>\n",
+ " <td>4</td>\n",
+ " <td>21</td>\n",
+ " <td>False</td>\n",
+ " <td>(4, 20, False)</td>\n",
+ " <td>(3, 21, True)</td>\n",
+ " <td>97.427869</td>\n",
+ " <td>56.25</td>\n",
+ " <td>71.4</td>\n",
+ " <td>[97.42787, 56.25, 71.4]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>275</td>\n",
+ " <td>630.000000</td>\n",
+ " <td>339</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>407</th>\n",
+ " <td>18</td>\n",
+ " <td>5</td>\n",
+ " <td>27</td>\n",
+ " <td>True</td>\n",
+ " <td>(5, 28, True)</td>\n",
+ " <td>(0, 27, False)</td>\n",
+ " <td>97.427869</td>\n",
+ " <td>78.75</td>\n",
+ " <td>91.8</td>\n",
+ " <td>[97.42787, 78.75, 91.8]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>91</td>\n",
+ " <td>835.714286</td>\n",
+ " <td>442</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>419</th>\n",
+ " <td>11</td>\n",
+ " <td>5</td>\n",
+ " <td>39</td>\n",
+ " <td>True</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>97.427869</td>\n",
+ " <td>78.75</td>\n",
+ " <td>132.6</td>\n",
+ " <td>[97.42787, 78.75, 132.6]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>1247.142857</td>\n",
+ " <td>454</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>420</th>\n",
+ " <td>0</td>\n",
+ " <td>5</td>\n",
+ " <td>0</td>\n",
+ " <td>False</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>97.427869</td>\n",
+ " <td>78.75</td>\n",
+ " <td>0.0</td>\n",
+ " <td>[97.42787, 78.75, 0.0]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>-90.000000</td>\n",
+ " <td>-1</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>424</th>\n",
+ " <td>0</td>\n",
+ " <td>5</td>\n",
+ " <td>9</td>\n",
+ " <td>False</td>\n",
+ " <td>-1</td>\n",
+ " <td>(4, 9, True)</td>\n",
+ " <td>97.427869</td>\n",
+ " <td>78.75</td>\n",
+ " <td>30.6</td>\n",
+ " <td>[97.42787, 78.75, 30.6]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>327</td>\n",
+ " <td>218.571429</td>\n",
+ " <td>389</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>438</th>\n",
+ " <td>0</td>\n",
+ " <td>5</td>\n",
+ " <td>23</td>\n",
+ " <td>False</td>\n",
+ " <td>(5, 22, False)</td>\n",
+ " <td>-1</td>\n",
+ " <td>97.427869</td>\n",
+ " <td>78.75</td>\n",
+ " <td>78.2</td>\n",
+ " <td>[97.42787, 78.75, 78.2]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>698.571429</td>\n",
+ " <td>403</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " index vh zid fwd stack_tuple threeprime_tuple x y \\\n",
+ "52 52 0 36 True -1 (1, 36, False) 77.942295 90.00 \n",
+ "55 2 0 41 True -1 -1 77.942295 90.00 \n",
+ "56 0 0 2 False -1 -1 77.942295 90.00 \n",
+ "85 0 0 21 False (0, 20, False) (1, 21, True) 77.942295 90.00 \n",
+ "88 0 0 24 False (0, 23, False) -1 77.942295 90.00 \n",
+ "92 0 0 28 False (0, 27, False) (5, 28, True) 77.942295 90.00 \n",
+ "132 18 1 20 True (1, 21, True) (0, 20, False) 58.456721 78.75 \n",
+ "150 17 1 38 True -1 -1 58.456721 78.75 \n",
+ "151 0 1 5 False -1 (0, 5, True) 58.456721 78.75 \n",
+ "166 0 1 19 False (1, 18, False) (2, 19, True) 58.456721 78.75 \n",
+ "184 0 1 39 False -1 -1 58.456721 78.75 \n",
+ "202 15 2 18 True (2, 19, True) (1, 18, False) 58.456721 56.25 \n",
+ "216 13 2 32 True -1 (3, 32, False) 58.456721 56.25 \n",
+ "219 2 2 41 True -1 -1 58.456721 56.25 \n",
+ "220 0 2 0 False -1 -1 58.456721 56.25 \n",
+ "274 20 3 20 True (3, 21, True) (4, 20, False) 77.942295 45.00 \n",
+ "287 12 3 34 True -1 -1 77.942295 45.00 \n",
+ "288 0 3 2 False -1 (2, 2, True) 77.942295 45.00 \n",
+ "302 0 3 16 False (3, 15, False) (4, 16, True) 77.942295 45.00 \n",
+ "318 0 3 37 False -1 -1 77.942295 45.00 \n",
+ "326 3 4 3 True -1 -1 97.427869 56.25 \n",
+ "333 6 4 15 True (4, 16, True) (3, 15, False) 97.427869 56.25 \n",
+ "357 23 4 39 True -1 (5, 39, False) 97.427869 56.25 \n",
+ "358 0 4 9 False -1 -1 97.427869 56.25 \n",
+ "370 0 4 21 False (4, 20, False) (3, 21, True) 97.427869 56.25 \n",
+ "407 18 5 27 True (5, 28, True) (0, 27, False) 97.427869 78.75 \n",
+ "419 11 5 39 True -1 -1 97.427869 78.75 \n",
+ "420 0 5 0 False -1 -1 97.427869 78.75 \n",
+ "424 0 5 9 False -1 (4, 9, True) 97.427869 78.75 \n",
+ "438 0 5 23 False (5, 22, False) -1 97.427869 78.75 \n",
+ "\n",
+ " z r seq stack threeprime orientation \\\n",
+ "52 122.4 [77.94229, 90.0, 122.4] -1 -1 183 1144.285714 \n",
+ "55 139.4 [77.94229, 90.0, 139.4] -1 -1 -1 1315.714286 \n",
+ "56 6.8 [77.94229, 90.0, 6.8] -1 -1 -1 -21.428571 \n",
+ "85 71.4 [77.94229, 90.0, 71.4] -1 -1 133 630.000000 \n",
+ "88 81.6 [77.94229, 90.0, 81.6] -1 -1 -1 732.857143 \n",
+ "92 95.2 [77.94229, 90.0, 95.2] -1 -1 408 870.000000 \n",
+ "132 68.0 [58.456722, 78.75, 68.0] -1 -1 84 595.714286 \n",
+ "150 129.2 [58.456722, 78.75, 129.2] -1 -1 -1 1212.857143 \n",
+ "151 17.0 [58.456722, 78.75, 17.0] -1 -1 0 81.428571 \n",
+ "166 64.6 [58.456722, 78.75, 64.6] -1 -1 203 561.428571 \n",
+ "184 132.6 [58.456722, 78.75, 132.6] -1 -1 -1 1247.142857 \n",
+ "202 61.2 [58.456722, 56.25, 61.2] -1 -1 165 527.142857 \n",
+ "216 108.8 [58.456722, 56.25, 108.8] -1 -1 317 1007.142857 \n",
+ "219 139.4 [58.456722, 56.25, 139.4] -1 -1 -1 1315.714286 \n",
+ "220 0.0 [58.456722, 56.25, 0.0] -1 -1 -1 -90.000000 \n",
+ "274 68.0 [77.94229, 45.0, 68.0] -1 -1 369 595.714286 \n",
+ "287 115.6 [77.94229, 45.0, 115.6] -1 -1 -1 1075.714286 \n",
+ "288 6.8 [77.94229, 45.0, 6.8] -1 -1 187 -21.428571 \n",
+ "302 54.4 [77.94229, 45.0, 54.4] -1 -1 334 458.571429 \n",
+ "318 125.8 [77.94229, 45.0, 125.8] -1 -1 -1 1178.571429 \n",
+ "326 10.2 [97.42787, 56.25, 10.2] -1 -1 -1 12.857143 \n",
+ "333 51.0 [97.42787, 56.25, 51.0] -1 -1 301 424.285714 \n",
+ "357 132.6 [97.42787, 56.25, 132.6] -1 -1 454 1247.142857 \n",
+ "358 30.6 [97.42787, 56.25, 30.6] -1 -1 -1 218.571429 \n",
+ "370 71.4 [97.42787, 56.25, 71.4] -1 -1 275 630.000000 \n",
+ "407 91.8 [97.42787, 78.75, 91.8] -1 -1 91 835.714286 \n",
+ "419 132.6 [97.42787, 78.75, 132.6] -1 -1 -1 1247.142857 \n",
+ "420 0.0 [97.42787, 78.75, 0.0] -1 -1 -1 -90.000000 \n",
+ "424 30.6 [97.42787, 78.75, 30.6] -1 -1 327 218.571429 \n",
+ "438 78.2 [97.42787, 78.75, 78.2] -1 -1 -1 698.571429 \n",
+ "\n",
+ " bp \n",
+ "52 111 \n",
+ "55 -1 \n",
+ "56 -1 \n",
+ "85 26 \n",
+ "88 29 \n",
+ "92 33 \n",
+ "132 167 \n",
+ "150 -1 \n",
+ "151 116 \n",
+ "166 131 \n",
+ "184 -1 \n",
+ "202 237 \n",
+ "216 251 \n",
+ "219 -1 \n",
+ "220 -1 \n",
+ "274 306 \n",
+ "287 -1 \n",
+ "288 256 \n",
+ "302 270 \n",
+ "318 -1 \n",
+ "326 -1 \n",
+ "333 364 \n",
+ "357 388 \n",
+ "358 327 \n",
+ "370 339 \n",
+ "407 442 \n",
+ "419 454 \n",
+ "420 -1 \n",
+ "424 389 \n",
+ "438 403 "
+ ]
+ },
+ "execution_count": 41,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "m.loc[ind]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 43,
+ "id": "f16c2de5",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def gen_prop_table(part):\n",
+ " strand_set=[]\n",
+ " for i in part.getidNums():\n",
+ " fwd,rev=part.getStrandSets(i)\n",
+ " [strand_set.append(i) for i in fwd.strands()]\n",
+ " [strand_set.append(i) for i in rev.strands()]\n",
+ " id_series=[]\n",
+ " for i in strand_set:\n",
+ " id_series=id_series+gen_id_series(i,part)\n",
+ " \n",
+ " nt_prop=pd.DataFrame(id_series)\n",
+ " nt_prop.reset_index(inplace=True)\n",
+ " nt_prop[\"seq\"]=-1\n",
+ " ind_tuple=list(zip(nt_prop[\"vh\"],nt_prop[\"zid\"],nt_prop[\"fwd\"]))\n",
+ " not_stacked,=np.where(nt_prop[\"stack_tuple\"]==-1)\n",
+ " for i in not_stacked:\n",
+ " zid=int(nt_prop.loc[i][\"zid\"])\n",
+ " fwd=nt_prop.loc[i][\"fwd\"]\n",
+ " if fwd == True:\n",
+ " zid+=1\n",
+ " else:\n",
+ " zid-=1\n",
+ " try:\n",
+ " ind_tuple.index((nt_prop.loc[i][\"vh\"],str(zid),fwd))\n",
+ " nt_prop[\"stack_tuple\"][i]=(nt_prop.loc[i][\"vh\"],str(zid),fwd)\n",
+ " except:\n",
+ " continue\n",
+ " stacks=[]\n",
+ " for i in list(nt_prop[\"stack_tuple\"]):\n",
+ " if i ==-1:\n",
+ " stacks.append(i)\n",
+ " else:\n",
+ " stacks.append(ind_tuple.index(i))\n",
+ " nt_prop[\"stack\"]=stacks\n",
+ " tprime=[]\n",
+ " for i in list(nt_prop[\"threeprime_tuple\"]):\n",
+ " if i ==-1:\n",
+ " tprime.append(i)\n",
+ " else:\n",
+ " tprime.append(ind_tuple.index(i))\n",
+ " nt_prop[\"threeprime\"]=tprime\n",
+ " vhzid=list(zip(nt_prop[\"vh\"],nt_prop[\"zid\"]))\n",
+ " nt_prop[\"orientation\"]=[get_helix_angle(part, helix_id, int(float(indices))) for helix_id,indices in vhzid]\n",
+ " nt_prop=nt_prop.fillna(-1)\n",
+ " counter=-1\n",
+ " bp=-np.ones(len(nt_prop.index),dtype=int)\n",
+ " bp_map=dict(zip(ind_tuple,nt_prop.index))\n",
+ " for i,j,k in ind_tuple:\n",
+ " counter+=1\n",
+ " try:\n",
+ " bp[counter]=bp_map[(i,j,not(k))]\n",
+ " except:\n",
+ " pass\n",
+ " nt_prop[\"bp\"]=bp\n",
+ "\n",
+ " return nt_prop\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ce93cf6e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import mrdna\n",
+ "from mrdna.readers import read_list"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "id": "c9ca5e1b",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(415,)"
+ ]
+ },
+ "execution_count": 29,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.array(list(nt_prop['bp'])).shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 560,
+ "id": "c9a33ae6",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(array([ 12, 13, 14, ..., 13920, 13921, 13922]),)"
+ ]
+ },
+ "execution_count": 560,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.where(np.array(nt_prop[\"bp\"])!=-1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "id": "4454b0e1",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "NameError",
+ "evalue": "name 'nt_prop' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-51-602cce887422>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwhere\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnt_prop\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"bp\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m!=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnt_prop\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"stack\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m!=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m: name 'nt_prop' is not defined"
+ ]
+ }
+ ],
+ "source": [
+ "np.where(np.array(nt_prop[\"bp\"])!=-1 and np.array(nt_prop[\"stack\"])!=-1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "id": "5a43528b",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>vh</th>\n",
+ " <th>zid</th>\n",
+ " <th>is_scaf</th>\n",
+ " <th>r</th>\n",
+ " <th>bp</th>\n",
+ " <th>stack</th>\n",
+ " <th>threeprime</th>\n",
+ " <th>seq</th>\n",
+ " <th>orientation</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>0</td>\n",
+ " <td>5</td>\n",
+ " <td>True</td>\n",
+ " <td>[0.0, 2.25, 1.7000000000000002]</td>\n",
+ " <td>213</td>\n",
+ " <td>-1</td>\n",
+ " <td>1</td>\n",
+ " <td>-1</td>\n",
+ " <td>[[0.14904226617617466, -0.9888308262251284, 0....</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>0</td>\n",
+ " <td>6</td>\n",
+ " <td>True</td>\n",
+ " <td>[0.0, 2.25, 2.04]</td>\n",
+ " <td>214</td>\n",
+ " <td>-1</td>\n",
+ " <td>2</td>\n",
+ " <td>-1</td>\n",
+ " <td>[[-0.4338837391175583, -0.900968867902419, 0.0...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>0</td>\n",
+ " <td>7</td>\n",
+ " <td>True</td>\n",
+ " <td>[0.0, 2.25, 2.3800000000000003]</td>\n",
+ " <td>215</td>\n",
+ " <td>-1</td>\n",
+ " <td>3</td>\n",
+ " <td>-1</td>\n",
+ " <td>[[-0.8660254037844388, -0.49999999999999994, 0...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>0</td>\n",
+ " <td>8</td>\n",
+ " <td>True</td>\n",
+ " <td>[0.0, 2.25, 2.72]</td>\n",
+ " <td>216</td>\n",
+ " <td>-1</td>\n",
+ " <td>4</td>\n",
+ " <td>-1</td>\n",
+ " <td>[[-0.9972037971811805, 0.07473009358642399, 0....</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>0</td>\n",
+ " <td>9</td>\n",
+ " <td>True</td>\n",
+ " <td>[0.0, 2.25, 3.06]</td>\n",
+ " <td>217</td>\n",
+ " <td>-1</td>\n",
+ " <td>5</td>\n",
+ " <td>-1</td>\n",
+ " <td>[[-0.7818314824680299, 0.6234898018587334, 0.0...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>410</th>\n",
+ " <td>5</td>\n",
+ " <td>35</td>\n",
+ " <td>False</td>\n",
+ " <td>[1.948557375, 1.125, 11.9]</td>\n",
+ " <td>205</td>\n",
+ " <td>-1</td>\n",
+ " <td>411</td>\n",
+ " <td>-1</td>\n",
+ " <td>[[0.8660254037844375, -0.5000000000000019, 0.0...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>411</th>\n",
+ " <td>5</td>\n",
+ " <td>36</td>\n",
+ " <td>False</td>\n",
+ " <td>[1.948557375, 1.125, 12.24]</td>\n",
+ " <td>206</td>\n",
+ " <td>-1</td>\n",
+ " <td>412</td>\n",
+ " <td>-1</td>\n",
+ " <td>[[0.4338837391175605, -0.900968867902418, 0.0]...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>412</th>\n",
+ " <td>5</td>\n",
+ " <td>37</td>\n",
+ " <td>False</td>\n",
+ " <td>[1.948557375, 1.125, 12.58]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>413</td>\n",
+ " <td>-1</td>\n",
+ " <td>[[-0.14904226617617078, -0.9888308262251292, 0...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>413</th>\n",
+ " <td>5</td>\n",
+ " <td>38</td>\n",
+ " <td>False</td>\n",
+ " <td>[1.948557375, 1.125, 12.920000000000002]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>414</td>\n",
+ " <td>-1</td>\n",
+ " <td>[[-0.6801727377709186, -0.7330518718298275, 0....</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>414</th>\n",
+ " <td>5</td>\n",
+ " <td>39</td>\n",
+ " <td>False</td>\n",
+ " <td>[1.948557375, 1.125, 13.260000000000002]</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>-1</td>\n",
+ " <td>[[-0.9749279121818233, -0.222520933956317, 0.0...</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>415 rows × 9 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " vh zid is_scaf r bp stack \\\n",
+ "0 0 5 True [0.0, 2.25, 1.7000000000000002] 213 -1 \n",
+ "1 0 6 True [0.0, 2.25, 2.04] 214 -1 \n",
+ "2 0 7 True [0.0, 2.25, 2.3800000000000003] 215 -1 \n",
+ "3 0 8 True [0.0, 2.25, 2.72] 216 -1 \n",
+ "4 0 9 True [0.0, 2.25, 3.06] 217 -1 \n",
+ ".. .. ... ... ... ... ... \n",
+ "410 5 35 False [1.948557375, 1.125, 11.9] 205 -1 \n",
+ "411 5 36 False [1.948557375, 1.125, 12.24] 206 -1 \n",
+ "412 5 37 False [1.948557375, 1.125, 12.58] -1 -1 \n",
+ "413 5 38 False [1.948557375, 1.125, 12.920000000000002] -1 -1 \n",
+ "414 5 39 False [1.948557375, 1.125, 13.260000000000002] -1 -1 \n",
+ "\n",
+ " threeprime seq orientation \n",
+ "0 1 -1 [[0.14904226617617466, -0.9888308262251284, 0.... \n",
+ "1 2 -1 [[-0.4338837391175583, -0.900968867902419, 0.0... \n",
+ "2 3 -1 [[-0.8660254037844388, -0.49999999999999994, 0... \n",
+ "3 4 -1 [[-0.9972037971811805, 0.07473009358642399, 0.... \n",
+ "4 5 -1 [[-0.7818314824680299, 0.6234898018587334, 0.0... \n",
+ ".. ... ... ... \n",
+ "410 411 -1 [[0.8660254037844375, -0.5000000000000019, 0.0... \n",
+ "411 412 -1 [[0.4338837391175605, -0.900968867902418, 0.0]... \n",
+ "412 413 -1 [[-0.14904226617617078, -0.9888308262251292, 0... \n",
+ "413 414 -1 [[-0.6801727377709186, -0.7330518718298275, 0.... \n",
+ "414 -1 -1 [[-0.9749279121818233, -0.222520933956317, 0.0... \n",
+ "\n",
+ "[415 rows x 9 columns]"
+ ]
+ },
+ "execution_count": 21,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nt_prop"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 468,
+ "id": "17167c74",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "scaf_id=[nttype(vslist['scaf'][i]) for i in vslist.index]\n",
+ "stap_id=[nttype(vslist['stap'][i]) for i in vslist.index]\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 500,
+ "id": "bab6c65d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "1"
+ ]
+ },
+ "execution_count": 500,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nttype(vslist[\"scaf\"][30])[146]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 498,
+ "id": "0f62f6cd",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "0"
+ ]
+ },
+ "execution_count": 498,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "vhi,zidi=np.where(np.array(scaf_id)==1)\n",
+ "scaf_id[30][146]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 480,
+ "id": "bc2021f6",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "True"
+ ]
+ },
+ "execution_count": 480,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "scaf_id[30][146]==np.array(scaf_id)[0][9]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 549,
+ "id": "a747eb2e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Int64Index([ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
+ " ...\n",
+ " 39, 39, 39, 39, 39, 39, 39, 39, 39, 39],\n",
+ " dtype='int64', name='num', length=7560)"
+ ]
+ },
+ "execution_count": 549,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "def nttype(scafs):\n",
+ " def judge(i):\n",
+ " if i ==[-1,-1,-1,-1]:\n",
+ " return 0\n",
+ " else: return 1\n",
+ " n=np.array([judge(i) for i in scafs])\n",
+ " return n\n",
+ "d={}\n",
+ "vslist.index[vhi]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 544,
+ "id": "6f50d801",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(array([7394, 7395, 7396, 7397, 7398, 7399, 7400, 7401, 7402, 7403, 7404,\n",
+ " 7405, 7406, 7407, 7408, 7409, 7410, 7411, 7412, 7413, 7414, 7415,\n",
+ " 7416, 7417, 7418, 7419, 7420, 7421, 7422, 7423, 7424, 7425, 7426,\n",
+ " 7427, 7428, 7429, 7430, 7431, 7432, 7433]),)"
+ ]
+ },
+ "execution_count": 544,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.where(vslist.index[vhi]!=vhi)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 550,
+ "id": "423e7163",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "vh 29\n",
+ "zid 83\n",
+ "is_scaf True\n",
+ "r [-17.537016375, 28.125, 28.220000000000002]\n",
+ "bp -1\n",
+ "stack -1\n",
+ "threeprime -1\n",
+ "seq -1\n",
+ "orientation [[-0.5633200580636211, 0.8262387743159955, 0.0...\n",
+ "Name: 7394, dtype: object"
+ ]
+ },
+ "execution_count": 550,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nt_prop.loc[7394]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 548,
+ "id": "f523be6f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Int64Index([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,\n",
+ " 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 30, 29, 31, 32, 33,\n",
+ " 34, 35, 36, 37, 38, 39, 41, 40, 42, 44, 46, 48, 50],\n",
+ " dtype='int64', name='num')"
+ ]
+ },
+ "execution_count": 548,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "vslist.index"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 527,
+ "id": "d61008dd",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(array([7394, 7395, 7396, 7397, 7398, 7399, 7400, 7401, 7402, 7403, 7404,\n",
+ " 7405, 7406, 7407, 7408, 7409, 7410, 7411, 7412, 7413, 7414, 7415,\n",
+ " 7416, 7417, 7418, 7419, 7420, 7421, 7422, 7423, 7424, 7425, 7426,\n",
+ " 7427, 7428, 7429, 7430, 7431, 7432, 7433]),)"
+ ]
+ },
+ "execution_count": 527,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "n=list(nt_prop[\"zid\"])\n",
+ "np.where(np.array(list(nt_prop[\"vh\"]))==29)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 503,
+ "id": "0176640a",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "ValueError",
+ "evalue": "((30, 146), True) is not in list",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-503-1b9956d4cdaf>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mtprime_list\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mones\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnt_prop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m30\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m146\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mValueError\u001b[0m: ((30, 146), True) is not in list"
+ ]
+ }
+ ],
+ "source": [
+ "vhzid=list(zip(nt_prop[\"vh\"],nt_prop[\"zid\"]))\n",
+ "index2=list(zip(vhzid,nt_prop[\"is_scaf\"]))\n",
+ "tprime_list=-np.ones(len(nt_prop.index),dtype=int)\n",
+ " \n",
+ "print(index2.index(((30,146),(True))))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 537,
+ "id": "daab30d3",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "11 135 30 146 3010\n"
+ ]
+ },
+ {
+ "ename": "ValueError",
+ "evalue": "((30, 146), True) is not in list",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-537-f07d5cbf0867>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mm\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m!=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0ml\u001b[0m\u001b[0;34m!=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 9\u001b[0m \u001b[0mtprime_list\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mValueError\u001b[0m: ((30, 146), True) is not in list"
+ ]
+ }
+ ],
+ "source": [
+ " \n",
+ "for i in range(len(nt_prop.index)):\n",
+ " ((m,n),p)=list(zip(vhzid,nt_prop[\"is_scaf\"]))[i]\n",
+ " if p==True:\n",
+ " k,l=(vslist[\"scaf\"][m])[n][2:]\n",
+ " if k==30 and l==146:\n",
+ " print(m,n,k,l,i)\n",
+ " if k!=-1 and l!=-1:\n",
+ " n=index2.index(((k,l),True))\n",
+ " tprime_list[i]=int(n)\n",
+ "\n",
+ " else:\n",
+ " k,l=(vslist[\"stap\"][m])[n][2:]\n",
+ " if k!=-1 and l!=-1:\n",
+ " n=index2.index(((k,l),False))\n",
+ " tprime_list[i]=int(n)\n",
+ "nt_prop[\"threeprime\"]=tprime_list\n",
+ "(n,)=np.where(nt_prop[\"threeprime\"]==-1)\n",
+ "stackid=nt_prop[\"bp\"][[list(nt_prop[\"threeprime\"]).index(i) for i in n]]\n",
+ "nt_prop[\"stack\"][stackid.index[np.where(np.array(stackid)!=-1)]]=nt_prop[\"threeprime\"][stackid.index[np.where(np.array(stackid)!=-1)]]\n",
+ " ## Todo: sequence "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 491,
+ "id": "c41afe8c",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[11, 135, 30, 147]"
+ ]
+ },
+ "execution_count": 491,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "list(vslist.loc[30][\"scaf\"])[146]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 493,
+ "id": "3f525aa9",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "ValueError",
+ "evalue": "(30, 146) is not in list",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-493-d1dd239124c3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mvhzid\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m30\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m146\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mValueError\u001b[0m: (30, 146) is not in list"
+ ]
+ }
+ ],
+ "source": [
+ "vhzid.index((30,146))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "a78afb7a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df=pd.DataFrame(data=d)\n",
+ "df=df.set_index(\"num\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "43ec49f1",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "id": "121d4fb1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_lattice(part):\n",
+ " lattice_type = None\n",
+ " _gt = part.getGridType()\n",
+ " try:\n",
+ " lattice_type = _gt.name.lower()\n",
+ " except:\n",
+ " if _gt == 1:\n",
+ " lattice_type = 'square'\n",
+ " elif _gt == 2:\n",
+ " lattice_type = 'honeycomb'\n",
+ " else:\n",
+ " print(\"WARNING: unable to determine cadnano part lattice type\")\n",
+ " return lattice_type\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "eac77008",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Found cadnano version 2 file\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "NucleicAcidPart_-1_2800"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "p=read_json_file(\"test/test.json\")\n",
+ "p"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 441,
+ "id": "4626babf",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
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+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
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+ " <th>col</th>\n",
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+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ...</td>\n",
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+ " <td>[[23, 13369809], [38, 12060012]]</td>\n",
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+ " <td>[[3, 1501302]]</td>\n",
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+ " <td>13</td>\n",
+ " <td>15</td>\n",
+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [3, 2, 2,...</td>\n",
+ " <td>[[2, 1, -1, -1], [2, 2, 2, 0], [2, 3, 2, 1], [...</td>\n",
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+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[]</td>\n",
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+ " <td>[[34, 8947848]]</td>\n",
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+ " <td>[[-1, -1, 3, 1], [3, 0, 3, 2], [3, 1, 3, 3], [...</td>\n",
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+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[]</td>\n",
+ " <td>[]</td>\n",
+ " <td>[[0, 13369344]]</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>13</td>\n",
+ " <td>17</td>\n",
+ " <td>[[-1, -1, 4, 1], [4, 0, 4, 2], [4, 1, 4, 3], [...</td>\n",
+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[]</td>\n",
+ " <td>[]</td>\n",
+ " <td>[[39, 8947848]]</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>5</th>\n",
+ " <td>12</td>\n",
+ " <td>17</td>\n",
+ " <td>[[5, 1, -1, -1], [5, 2, 5, 0], [5, 3, 5, 1], [...</td>\n",
+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[]</td>\n",
+ " <td>[]</td>\n",
+ " <td>[[9, 0]]</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " row col scaf \\\n",
+ "num \n",
+ "0 12 16 [[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ... \n",
+ "1 12 15 [[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ... \n",
+ "2 13 15 [[-1, -1, -1, -1], [-1, -1, -1, -1], [3, 2, 2,... \n",
+ "3 13 16 [[-1, -1, -1, -1], [-1, -1, -1, -1], [3, 3, 2,... \n",
+ "4 13 17 [[-1, -1, 4, 1], [4, 0, 4, 2], [4, 1, 4, 3], [... \n",
+ "5 12 17 [[5, 1, -1, -1], [5, 2, 5, 0], [5, 3, 5, 1], [... \n",
+ "\n",
+ " stap \\\n",
+ "num \n",
+ "0 [[-1, -1, -1, -1], [-1, -1, -1, -1], [0, 3, -1... \n",
+ "1 [[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ... \n",
+ "2 [[2, 1, -1, -1], [2, 2, 2, 0], [2, 3, 2, 1], [... \n",
+ "3 [[-1, -1, 3, 1], [3, 0, 3, 2], [3, 1, 3, 3], [... \n",
+ "4 [[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ... \n",
+ "5 [[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ... \n",
+ "\n",
+ " loop \\\n",
+ "num \n",
+ "0 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "1 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "2 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "3 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "4 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "5 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "\n",
+ " skip scafLoop stapLoop \\\n",
+ "num \n",
+ "0 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "1 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "2 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "3 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "4 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "5 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "\n",
+ " stap_colors \n",
+ "num \n",
+ "0 [[23, 13369809], [38, 12060012]] \n",
+ "1 [[3, 1501302]] \n",
+ "2 [[34, 8947848]] \n",
+ "3 [[0, 13369344]] \n",
+ "4 [[39, 8947848]] \n",
+ "5 [[9, 0]] "
+ ]
+ },
+ "execution_count": 441,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "f"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 199,
+ "id": "9126a63f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([0. , 2.25, 3.4 ])"
+ ]
+ },
+ "execution_count": 199,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "p.getCoordinate(0,10)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 434,
+ "id": "7840798e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def mrdna_model_from_cadnano(json_file,**model_parameters):\n",
+ " part,vslist=read_json_file(json_file)\n",
+ " props = part.getModelProperties().copy()\n",
+ " try:\n",
+ " if props.get('point_type') == PointType.ARBITRARY:\n",
+ " # TODO add code to encode Parts with ARBITRARY point configurations\n",
+ " raise NotImplementedError(\"Not implemented\")\n",
+ " except:\n",
+ " try:\n",
+ " vh_props, origins = part.helixPropertiesAndOrigins()\n",
+ " except:\n",
+ " origins = {hid:part.getVirtualHelixOrigin(hid)[:2] for hid in part.getidNums()}\n",
+ " scaf_id=[nttype(vslist['scaf'][i]) for i in vslist.index]\n",
+ " stap_id=[nttype(vslist['stap'][i]) for i in vslist.index]\n",
+ " cad_bps=part.getIndices(0)\n",
+ " vslist[\"scafnt\"]=np.sum(np.array(scaf_id),axis=1)\n",
+ " vslist[\"stapnt\"]=np.sum(np.array(stap_id),axis=1)\n",
+ " totnt=np.sum(vslist[\"scafnt\"])+np.sum(vslist[\"stapnt\"])\n",
+ " is_scaf=np.zeros(totnt,dtype=bool)\n",
+ " is_scaf[0:np.sum(vslist[\"scafnt\"])]=1\n",
+ " nt_prop=pd.DataFrame(index=range(totnt),columns=[\"vh\",\"zid\",\"is_scaf\",\"r\",\"bp\",\"stack\",\"threeprime\",\"seq\",\"orientation\"])\n",
+ " nt_prop[\"is_scaf\"]=is_scaf\n",
+ " tot_id=scaf_id+stap_id\n",
+ " vhi,zidi=np.where(np.array(scaf_id)==1)\n",
+ " vhj,zidj=np.where(np.array(stap_id)==1)\n",
+ " nt_prop[\"vh\"]=list(vhi)+list(vhj)\n",
+ " nt_prop[\"zid\"]=list(zidi)+list(zidj)\n",
+ " vhzid=list(zip(nt_prop[\"vh\"],nt_prop[\"zid\"]))\n",
+ " nt_prop[\"r\"]=[part.getCoordinate(i,j) for i,j in zip(nt_prop[\"vh\"],nt_prop[\"zid\"])]\n",
+ " nt_prop[\"orientation\"]=[get_helix_angle(part, helix_id, indices) for i,j in zip(nt_prop[\"vh\"],nt_prop[\"zid\"])]\n",
+ " nt_prop=nt_prop.fillna(-1)\n",
+ " for i in range(int(len(vhzid)/2)):\n",
+ " try:\n",
+ " bp1,bp2=(i,1+i+vhzid[i+1:].index(vhzid[i]))\n",
+ " nt_prop[\"bp\"][bp1]=bp2\n",
+ " nt_prop[\"bp\"][bp2]=bp1\n",
+ " except:\n",
+ " pass\n",
+ " tprime_list=-np.ones(len(nt_prop.index),dtype=int)\n",
+ " for i in range(len(nt_prop.index)):\n",
+ " ((m,n),p)=list(zip(vhzid,nt_prop[\"is_scaf\"]))[i]\n",
+ " if p==True:\n",
+ " k,l=(vslist[\"scaf\"][m])[n][2:]\n",
+ " if k!=-1 and l!=-1:\n",
+ " n=index2.index(((k,l),True))\n",
+ " tprime_list[i]=int(n)\n",
+ "\n",
+ " else:\n",
+ " k,l=(vslist[\"stap\"][m])[n][2:]\n",
+ " if k!=-1 and l!=-1:\n",
+ " n=index2.index(((k,l),False))\n",
+ " tprime_list[i]=int(n)\n",
+ " nt_prop[\"threeprime\"]=tprime_list\n",
+ " (n,)=np.where(nt_prop[\"threeprime\"]==-1)\n",
+ " stackid=nt_prop[\"bp\"][[list(nt_prop[\"threeprime\"]).index(i) for i in n]]\n",
+ " nt_prop[\"stack\"][stackid.index[np.where(np.array(stackid)!=-1)]]=nt_prop[\"threeprime\"][stackid.index[np.where(np.array(stackid)!=-1)]]\n",
+ "\n",
+ "\n",
+ " return nt_prop\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 442,
+ "id": "1a1c4e53",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
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+ " -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,\n",
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+ " -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,\n",
+ " -1, -1, -1, -1, -1, -1, -1])"
+ ]
+ },
+ "execution_count": 442,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.array(nt_prop[\"seq\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 302,
+ "id": "02d50bab",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "tprime_list=-np.ones(len(nt_prop.index),dtype=int)\n",
+ "for i in range(len(nt_prop.index)):\n",
+ " ((m,n),p)=list(zip(vhzid,nt_prop[\"is_scaf\"]))[i]\n",
+ " if p==True:\n",
+ " k,l=(vslist[\"scaf\"][m])[n][2:]\n",
+ " if k!=-1 and l!=-1:\n",
+ " n=index2.index(((k,l),True))\n",
+ " tprime_list[i]=int(n)\n",
+ " \n",
+ " else:\n",
+ " k,l=(vslist[\"stap\"][m])[n][2:]\n",
+ " if k!=-1 and l!=-1:\n",
+ " n=index2.index(((k,l),False))\n",
+ " tprime_list[i]=int(n)\n",
+ "nt_prop[\"threeprime\"]=tprime_list"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 368,
+ "id": "5b3cff6b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_helix_angle(part, helix_id, indices):\n",
+ " \"\"\" Get \"start_orientation\" for helix \"\"\"\n",
+ " # import ipdb\n",
+ " # ipdb.set_trace()\n",
+ "\n",
+ " \"\"\" FROM CADNANO2.5\n",
+ " + angle is CCW\n",
+ " - angle is CW\n",
+ " Right handed DNA rotates clockwise from 5' to 3'\n",
+ " we use the convention the 5' end starts at 0 degrees\n",
+ " and it's pair is minor_groove_angle degrees away\n",
+ " direction, hence the minus signs. eulerZ\n",
+ " \"\"\"\n",
+ "\n",
+ " hp, bpr, tpr, eulerZ, mgroove = part.vh_properties.loc[helix_id,\n",
+ " ['helical_pitch',\n",
+ " 'bases_per_repeat',\n",
+ " 'turns_per_repeat',\n",
+ " 'eulerZ',\n",
+ " 'minor_groove_angle']]\n",
+ " twist_per_base = tpr*360./bpr\n",
+ " # angle = eulerZ - twist_per_base*indices + 0.5*mgroove + 180\n",
+ " angle = eulerZ + twist_per_base*indices - 0.5*mgroove\n",
+ " return rotationAboutAxis(np.array((0,0,1)),angle)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 429,
+ "id": "c27027df",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\n",
+ "(n,)=np.where(nt_prop[\"threeprime\"]==-1)\n",
+ "\n",
+ "stackid=nt_prop[\"bp\"][[list(nt_prop[\"threeprime\"]).index(i) for i in n]]\n",
+ "\n",
+ "nt_prop[\"stack\"][stackid.index[np.where(np.array(stackid)!=-1)]]=nt_prop[\"threeprime\"][stackid.index[np.where(np.array(stackid)!=-1)]]\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 430,
+ "id": "a943a204",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "33 -1\n",
+ "68 -1\n",
+ "102 -1\n",
+ "136 -1\n",
+ "142 -1\n",
+ "176 -1\n",
+ "194 399\n",
+ "211 -1\n",
+ "233 20\n",
+ "281 -1\n",
+ "284 -1\n",
+ "351 -1\n",
+ "354 145\n",
+ "413 -1\n",
+ "Name: bp, dtype: int64"
+ ]
+ },
+ "execution_count": 430,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "stackid"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 431,
+ "id": "c1d76688",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "232"
+ ]
+ },
+ "execution_count": 431,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nt_prop[\"stack\"][233]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 433,
+ "id": "163d7316",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "353"
+ ]
+ },
+ "execution_count": 433,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nt_prop[\"stack\"][354]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 167,
+ "id": "5731c87a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "scaf_id=[nttype(vslist[\"scaf\"][i]) for i in vslist.index]\n",
+ "stap_id=[nttype(vslist[\"stap\"][i]) for i in vslist.index]\n",
+ "nts=scaf_id+stap_id"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 360,
+ "id": "c3faf3f7",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "nt_prop[\"orientation\"]=[get_helix_angle(p,i,j) for i,j in zip(nt_prop[\"vh\"],nt_prop[\"zid\"])]\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 190,
+ "id": "c66f7e42",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
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+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
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+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>row</th>\n",
+ " <th>col</th>\n",
+ " <th>scaf</th>\n",
+ " <th>stap</th>\n",
+ " <th>loop</th>\n",
+ " <th>skip</th>\n",
+ " <th>scafLoop</th>\n",
+ " <th>stapLoop</th>\n",
+ " <th>stap_colors</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>num</th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>12</td>\n",
+ " <td>16</td>\n",
+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ...</td>\n",
+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [0, 3, -1...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[]</td>\n",
+ " <td>[]</td>\n",
+ " <td>[[23, 13369809], [38, 12060012]]</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>12</td>\n",
+ " <td>15</td>\n",
+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ...</td>\n",
+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[]</td>\n",
+ " <td>[]</td>\n",
+ " <td>[[3, 1501302]]</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>13</td>\n",
+ " <td>15</td>\n",
+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [3, 2, 2,...</td>\n",
+ " <td>[[2, 1, -1, -1], [2, 2, 2, 0], [2, 3, 2, 1], [...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[]</td>\n",
+ " <td>[]</td>\n",
+ " <td>[[34, 8947848]]</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>13</td>\n",
+ " <td>16</td>\n",
+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [3, 3, 2,...</td>\n",
+ " <td>[[-1, -1, 3, 1], [3, 0, 3, 2], [3, 1, 3, 3], [...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[]</td>\n",
+ " <td>[]</td>\n",
+ " <td>[[0, 13369344]]</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>13</td>\n",
+ " <td>17</td>\n",
+ " <td>[[-1, -1, 4, 1], [4, 0, 4, 2], [4, 1, 4, 3], [...</td>\n",
+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[]</td>\n",
+ " <td>[]</td>\n",
+ " <td>[[39, 8947848]]</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>5</th>\n",
+ " <td>12</td>\n",
+ " <td>17</td>\n",
+ " <td>[[5, 1, -1, -1], [5, 2, 5, 0], [5, 3, 5, 1], [...</td>\n",
+ " <td>[[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+ " <td>[]</td>\n",
+ " <td>[]</td>\n",
+ " <td>[[9, 0]]</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " row col scaf \\\n",
+ "num \n",
+ "0 12 16 [[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ... \n",
+ "1 12 15 [[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ... \n",
+ "2 13 15 [[-1, -1, -1, -1], [-1, -1, -1, -1], [3, 2, 2,... \n",
+ "3 13 16 [[-1, -1, -1, -1], [-1, -1, -1, -1], [3, 3, 2,... \n",
+ "4 13 17 [[-1, -1, 4, 1], [4, 0, 4, 2], [4, 1, 4, 3], [... \n",
+ "5 12 17 [[5, 1, -1, -1], [5, 2, 5, 0], [5, 3, 5, 1], [... \n",
+ "\n",
+ " stap \\\n",
+ "num \n",
+ "0 [[-1, -1, -1, -1], [-1, -1, -1, -1], [0, 3, -1... \n",
+ "1 [[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ... \n",
+ "2 [[2, 1, -1, -1], [2, 2, 2, 0], [2, 3, 2, 1], [... \n",
+ "3 [[-1, -1, 3, 1], [3, 0, 3, 2], [3, 1, 3, 3], [... \n",
+ "4 [[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ... \n",
+ "5 [[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, ... \n",
+ "\n",
+ " loop \\\n",
+ "num \n",
+ "0 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "1 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "2 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "3 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "4 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "5 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
+ "\n",
+ " skip scafLoop stapLoop \\\n",
+ "num \n",
+ "0 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "1 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "2 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "3 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "4 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "5 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... [] [] \n",
+ "\n",
+ " stap_colors \n",
+ "num \n",
+ "0 [[23, 13369809], [38, 12060012]] \n",
+ "1 [[3, 1501302]] \n",
+ "2 [[34, 8947848]] \n",
+ "3 [[0, 13369344]] \n",
+ "4 [[39, 8947848]] \n",
+ "5 [[9, 0]] "
+ ]
+ },
+ "execution_count": 190,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "vslist"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 200,
+ "id": "b8b5f079",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def mrdna_model_from_cadnano(json_data,**model_parameters):\n",
+ " part,vslist=decode_cadnano_part(json_data)\n",
+ " props = part.getModelProperties().copy()\n",
+ "\n",
+ " if props.get('point_type') == PointType.ARBITRARY:\n",
+ " # TODO add code to encode Parts with ARBITRARY point configurations\n",
+ " raise NotImplementedError(\"Not implemented\")\n",
+ " else:\n",
+ " try:\n",
+ " vh_props, origins = part.helixPropertiesAndOrigins()\n",
+ " except:\n",
+ " origins = {hid:part.getVirtualHelixOrigin(hid)[:2] for hid in part.getidNums()}\n",
+ " scaf_id=np.array([nttype(vslist['scaf'][i]) for i in vslist.index])\n",
+ " stap_id=np.array([nttype(vslist['stap'][i]) for i in vslist.index])\n",
+ " cad_bps=part.getIndices(0)\n",
+ " vslist[\"scafnt\"]=np.sum(scaf_id,axis=1)\n",
+ " vslist[\"stapnt\"]=np.sum(stap_id,axis=1)\n",
+ " totnt=np.sum(vslist[\"scafnt\"])+np.sum(vslist[\"stapnt\"])\n",
+ " is_scaf=np.zeros(totnt)\n",
+ " is_scaf[0:np.sum(vslist[\"scafnt\"])]=1\n",
+ " nt_prop=pd.DataFrame(index=range(totnt),columns=[\"vh\",\"zid\",\"is_scaf\",\"r\",\"bp\",\"stack\",\"threeprime\",\"seq\",\"orientation\"])\n",
+ " nt_prop[\"is_scaf\"]=is_scaf\n",
+ " vhi,zids=np.where(np.array(scaf_id+stap_id)==1)\n",
+ " nt_prop[\"vh\"]=vhi\n",
+ " nt_prop[\"zid\"]=zids\n",
+ " nt_prop[\"r\"] =part.getCoordinate(nt_prop[\"vh\"],nt_prop[\"zid\"])\n",
+ " return nt_prop\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 201,
+ "id": "a6f87acc",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "NameError",
+ "evalue": "name 'decode_cadnano_part' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-201-c5d589a8b80d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmrdna_model_from_cadnano\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"test.json\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;32m<ipython-input-200-181a924488ad>\u001b[0m in \u001b[0;36mmrdna_model_from_cadnano\u001b[0;34m(json_data, **model_parameters)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mmrdna_model_from_cadnano\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson_data\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mmodel_parameters\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mpart\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mvslist\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdecode_cadnano_part\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson_data\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mprops\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpart\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetModelProperties\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mprops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'point_type'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mPointType\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mARBITRARY\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mNameError\u001b[0m: name 'decode_cadnano_part' is not defined"
+ ]
+ }
+ ],
+ "source": [
+ "mrdna_model_from_cadnano(\"test.json\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 146,
+ "id": "d3be63cc",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "a,b=np.where(np.array(nts)==1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 148,
+ "id": "8f869fd3",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([ 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,\n",
+ " 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 39, 40,\n",
+ " 41, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,\n",
+ " 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 39,\n",
+ " 40, 41, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,\n",
+ " 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 39,\n",
+ " 40, 41, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,\n",
+ " 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 37,\n",
+ " 38, 39, 40, 41, 0, 1, 2, 3, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ " 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,\n",
+ " 35, 36, 37, 38, 39, 0, 1, 2, 3, 9, 10, 11, 12, 13, 14, 15, 16,\n",
+ " 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
+ " 34, 35, 36, 37, 38, 39])"
+ ]
+ },
+ "execution_count": 148,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nt_prop=pd.DataFrame(index)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 137,
+ "id": "6a623964",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def nttype(scafs):\n",
+ " def judge(i):\n",
+ " if i ==[-1,-1,-1,-1]:\n",
+ " return 0\n",
+ " else: return 1\n",
+ " n=np.array([judge(i) for i in scafs])\n",
+ " return n\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "b2a34380",
+ "metadata": {},
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+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 84,
+ "id": "20260f38",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "b[\"scafnt\"]=[ntcount(b['scaf'][i]) for i in b.index]\n",
+ "b[\"stapnt\"]=[ntcount(b['stap'][i]) for i in b.index]"
+ ]
+ },
+ {
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+ "id": "574e177c",
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+ " <td>NaN</td>\n",
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+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <th>8</th>\n",
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+ " <td>NaN</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " r bp stack threeprime seq orientation\n",
+ "vh zid \n",
+ "0 0 NaN NaN NaN NaN NaN NaN\n",
+ "1 3 NaN NaN NaN NaN NaN NaN\n",
+ "2 1 NaN NaN NaN NaN NaN NaN\n",
+ "3 2 NaN NaN NaN NaN NaN NaN\n",
+ "1 8 NaN NaN NaN NaN NaN NaN"
+ ]
+ },
+ "execution_count": 156,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "i=range(5)\n",
+ "col=[\"vh\",\"zid\",\"r\",\"bp\",\"stack\",\"threeprime\",\"seq\",\"orientation\"]\n",
+ "d=pd.DataFrame(index=i,columns=col)\n",
+ "d['vh']=[0,1,2,3,1]\n",
+ "d['zid']=[0,3,1,2,8]\n",
+ "d.set_index([\"vh\",\"zid\"],inplace=True)\n",
+ "d"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 157,
+ "id": "b8e3a819",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
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+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>vh</th>\n",
+ " <th>zid</th>\n",
+ " <th>r</th>\n",
+ " <th>bp</th>\n",
+ " <th>stack</th>\n",
+ " <th>threeprime</th>\n",
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+ " <th>1</th>\n",
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+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>3</td>\n",
+ " <td>2</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>1</td>\n",
+ " <td>8</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " vh zid r bp stack threeprime seq orientation\n",
+ "0 0 0 NaN NaN NaN NaN NaN NaN\n",
+ "1 1 3 NaN NaN NaN NaN NaN NaN\n",
+ "2 2 1 NaN NaN NaN NaN NaN NaN\n",
+ "3 3 2 NaN NaN NaN NaN NaN NaN\n",
+ "4 1 8 NaN NaN NaN NaN NaN NaN"
+ ]
+ },
+ "execution_count": 157,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "\n",
+ "d=d.reset_index()\n",
+ "d"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 128,
+ "id": "2b3e6e89",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(array([0, 2]),)"
+ ]
+ },
+ "execution_count": 128,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s=[True,False,True,False,False]\n",
+ "np.where(np.array(s)==True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 127,
+ "id": "36d4d897",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
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+ " <th>orientation</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>vh</th>\n",
+ " <th>zid</th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " </tr>\n",
+ " </thead>\n",
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+ " <td>NaN</td>\n",
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+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <th>1</th>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <th>2</th>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <th>8</th>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " r bp stack threeprime seq orientation\n",
+ "vh zid \n",
+ "0 0 NaN NaN NaN NaN NaN NaN\n",
+ "1 3 NaN NaN NaN NaN NaN NaN\n",
+ "2 1 NaN NaN NaN NaN NaN NaN\n",
+ "3 2 NaN NaN NaN NaN NaN NaN\n",
+ "1 8 NaN NaN NaN NaN NaN NaN"
+ ]
+ },
+ "execution_count": 127,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "d"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 100,
+ "id": "f4b4ea63",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "KeyError",
+ "evalue": "\"None of [Int64Index([0, 0], dtype='int64')] are in the [columns]\"",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-100-a349feadc600>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0md\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;32m/data/server1/cmaffeo2/miniconda3/lib/python3.8/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3509\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3510\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3511\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_indexer_strict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"columns\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3512\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3513\u001b[0m \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/data/server1/cmaffeo2/miniconda3/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36m_get_indexer_strict\u001b[0;34m(self, key, axis_name)\u001b[0m\n\u001b[1;32m 5780\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5781\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5782\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_raise_if_missing\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5783\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5784\u001b[0m \u001b[0mkeyarr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/data/server1/cmaffeo2/miniconda3/lib/python3.8/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36m_raise_if_missing\u001b[0;34m(self, key, indexer, axis_name)\u001b[0m\n\u001b[1;32m 5840\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0muse_interval_msg\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5841\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5842\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"None of [{key}] are in the [{axis_name}]\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5843\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5844\u001b[0m \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mKeyError\u001b[0m: \"None of [Int64Index([0, 0], dtype='int64')] are in the [columns]\""
+ ]
+ }
+ ],
+ "source": [
+ "d[[0,0]]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "3c12d5dd",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[[23, 13369809], [38, 12060012]]"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df[\"vstrands\"][0][\"stap_colors\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "40855dd8",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "210"
+ ]
+ },
+ "execution_count": 14,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "vh_vb,pattern=pd.read_pickle(\"test.virt2nuc\")\n",
+ "len(vh_vb._scaf)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 198,
+ "id": "f4ebcdc6",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "TypeError",
+ "evalue": "file must have 'read' and 'readline' attributes",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn[198], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m df \u001b[38;5;241m=\u001b[39m \u001b[43mpickle\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtest.virt2nuc\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
+ "\u001b[0;31mTypeError\u001b[0m: file must have 'read' and 'readline' attributes"
+ ]
+ }
+ ],
+ "source": [
+ "df = pickle.load(\"test.virt2nuc\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "4037f0aa",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{0: (12, 16), 1: (12, 15), 2: (13, 15), 3: (13, 16), 4: (13, 17), 5: (12, 17)}"
+ ]
+ },
+ "execution_count": 15,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "pattern"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 173,
+ "id": "b9ac3514",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class strands():\n",
+ " def __init__(self):\n",
+ " self.row=0 \n",
+ " self.col=0\n",
+ " self.num=0\n",
+ " self.scaf=[]\n",
+ " self.stap=[]\n",
+ " self.loop=[]\n",
+ " self.skip=[]\n",
+ " self.scafLoop=[]\n",
+ " self.stapLoop=[]\n",
+ " self.stap_colors=[]\n",
+ " self.scaf_contact={}\n",
+ " self.stap_connect={}\n",
+ " def to_dict(self):\n",
+ " d={}\n",
+ " d['row']=self.row\n",
+ " d['col']=self.col\n",
+ " d['num']=self.num\n",
+ " d['scaf']=self.scaf\n",
+ " d['stap']=self.stap\n",
+ " d['loop']=self.loop\n",
+ " d['skip']=self.skip\n",
+ " d['scafLoop']=self.scafLoop\n",
+ " d['stapLoop']=self.stapLoop\n",
+ " d['stap_colors']=self.stap_colors\n",
+ " return d\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 177,
+ "id": "e3a81edb",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def find_segs(vir2nuc_scaf):\n",
+ " oligos={}\n",
+ " for i in range(len(vir2nuc_scaf)):\n",
+ " oligo,ox_ind=list(vir2nuc_scaf.values())[i]\n",
+ " if oligo not in oligos.keys():\n",
+ " oligos[oligo]=[]\n",
+ " oligos[oligo].append(list(vir2nuc_scaf.keys())[i])\n",
+ " return oligos\n",
+ "\n",
+ "#class\n",
+ "def decode_vh_vb(virt2nuc):\n",
+ " vh_list={}\n",
+ " vh_vb,pattern=pd.read_pickle(virt2nuc)\n",
+ " for i in pattern.keys():\n",
+ " s=strands()\n",
+ " s.row,s.col=pattern[i]\n",
+ " s.num=i\n",
+ " vh_list[s.num]=s\n",
+ " scafs=vh_vb._scaf\n",
+ " staps=vh_vb._stap\n",
+ " scaf_strands=find_segs(scafs)\n",
+ " scaf_oligos=list(scaf_strands.keys())\n",
+ " for i in scaf_oligos:\n",
+ " pass\n",
+ " \n",
+ " \n",
+ " return vh_list"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 187,
+ "id": "e362ba9e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
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+ " [(3, 0),\n",
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+ " (3, 33),\n",
+ " (3, 34)]]"
+ ]
+ },
+ "execution_count": 187,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s1=decode_vh_vb(\"test.virt2nuc\")\n",
+ "vh_vb,pattern=pd.read_pickle(\"test.virt2nuc\")\n",
+ "list(find_segs(vh_vb._stap).values())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 142,
+ "id": "c0f2e5be",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def find_segs(vir2nuc_scaf):\n",
+ " oligos={}\n",
+ " for i in range(len(vir2nuc_scaf)):\n",
+ " oligo,ox_ind=list(vir2nuc_scaf.values())[i]\n",
+ " if oligo not in oligos.keys():\n",
+ " oligos[oligo]=[]\n",
+ " oligos[oligo].append(list(vir2nuc_scaf.keys())[i])\n",
+ " return oligos\n",
+ "\n",
+ "def decode_vh_vb(virt2nuc):\n",
+ " vh_vb,pattern=pd.read_pickle(virt2nuc)\n",
+ " vi={'row':0, 'col':0, 'num':0, 'scaf':dict(), 'stap':dict(), 'loop':[], 'skip':[], 'scafLoop':[],'stapLoop':[], 'stap_colors':[],\"scaf53\":True}\n",
+ " vs=[] \n",
+ " for i in range(len(pattern.keys())):\n",
+ " vhi=vi.copy()\n",
+ " vhi[\"row\"],vhi[\"col\"]=list(pattern.values())[i]\n",
+ " vhi[\"num\"]=list(pattern.keys())[i]\n",
+ " vs.append(vhi)\n",
+ " vhelices=pd.DataFrame(vs)\n",
+ " vhelices=vhelices.set_index('num')\n",
+ " scafs=vh_vb._scaf\n",
+ " staps=vh_vb._stap\n",
+ " scaf_strands=find_segs(scafs)\n",
+ " stap_strands=find_segs(staps)\n",
+ " scaf_oligos=list(scaf_strands.keys())\n",
+ "\n",
+ " \n",
+ " return vhelices"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 117,
+ "id": "9a8a0b95",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def find_base_map(oligo,i,vhx,scaf=True):\n",
+ " vh0,vb0=oligo[i]\n",
+ " vh1,vb1=oligo[i+1]\n",
+ " if scaf==True:\n",
+ " if vb0 not in vhx[\"scaf\"][vh0].keys():\n",
+ " \n",
+ " if vh0==vh1 and scaf==True:\n",
+ " if vb0>vb1:\n",
+ " vhx[vh0][\"scaf\"][vb0]=\n",
+ " \n",
+ "\n",
+ " \n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 116,
+ "id": "deba51fa",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
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+ " (5, 23)]"
+ ]
+ },
+ "execution_count": 116,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "scafs=vh_vb._scaf\n",
+ "s=list(scafs.values())\n",
+ "len(scafs)\n",
+ "ss=find_segs(scafs)[7]\n",
+ "ss"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 157,
+ "id": "b31e177e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[(1, 2)]"
+ ]
+ },
+ "execution_count": 157,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "oligos[0]=[]\n",
+ "L=[]\n",
+ "L.append((1,2))\n",
+ "L"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 152,
+ "id": "87cb62c0",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(0, 39)"
+ ]
+ },
+ "execution_count": 152,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "list(scafs.keys())[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "id": "283ce125",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
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+ " (1, 6): (8, [278]),\n",
+ " (1, 7): (8, [277]),\n",
+ " (1, 8): (8, [276]),\n",
+ " (1, 9): (8, [275]),\n",
+ " (1, 10): (8, [274]),\n",
+ " (1, 11): (8, [273]),\n",
+ " (1, 12): (8, [272]),\n",
+ " (1, 13): (8, [271]),\n",
+ " (1, 14): (8, [270]),\n",
+ " (1, 15): (8, [269]),\n",
+ " (1, 16): (8, [268]),\n",
+ " (1, 17): (8, [267]),\n",
+ " (1, 18): (8, [266]),\n",
+ " (1, 19): (8, [265]),\n",
+ " (1, 20): (8, [264]),\n",
+ " (0, 20): (8, [263]),\n",
+ " (0, 19): (8, [262]),\n",
+ " (0, 18): (8, [261]),\n",
+ " (0, 17): (8, [260]),\n",
+ " (0, 16): (8, [259]),\n",
+ " (0, 15): (8, [258]),\n",
+ " (0, 14): (8, [257]),\n",
+ " (0, 13): (8, [256]),\n",
+ " (0, 12): (8, [255]),\n",
+ " (0, 11): (8, [254]),\n",
+ " (0, 10): (8, [253]),\n",
+ " (0, 9): (8, [252]),\n",
+ " (0, 8): (8, [251]),\n",
+ " (0, 7): (8, [250]),\n",
+ " (0, 6): (8, [249]),\n",
+ " (0, 5): (8, [248]),\n",
+ " (0, 4): (8, [247]),\n",
+ " (0, 3): (8, [246]),\n",
+ " (0, 2): (8, [245]),\n",
+ " (0, 23): (9, [302]),\n",
+ " (0, 22): (9, [301]),\n",
+ " (0, 21): (9, [300]),\n",
+ " (1, 21): (9, [299]),\n",
+ " (1, 22): (9, [298]),\n",
+ " (1, 23): (9, [297]),\n",
+ " (1, 24): (9, [296]),\n",
+ " (1, 25): (9, [295]),\n",
+ " (1, 26): (9, [294]),\n",
+ " (1, 27): (9, [293]),\n",
+ " (1, 28): (9, [292]),\n",
+ " (1, 29): (9, [291]),\n",
+ " (1, 30): (9, [290]),\n",
+ " (1, 31): (9, [289]),\n",
+ " (1, 32): (9, [288]),\n",
+ " (1, 33): (9, [287]),\n",
+ " (1, 34): (9, [286]),\n",
+ " (1, 35): (9, [285]),\n",
+ " (1, 36): (9, [284]),\n",
+ " (1, 37): (9, [283]),\n",
+ " (1, 38): (9, [282]),\n",
+ " (5, 9): (10, [325]),\n",
+ " (5, 10): (10, [324]),\n",
+ " (5, 11): (10, [323]),\n",
+ " (5, 12): (10, [322]),\n",
+ " (5, 13): (10, [321]),\n",
+ " (5, 14): (10, [320]),\n",
+ " (5, 15): (10, [319]),\n",
+ " (5, 16): (10, [318]),\n",
+ " (5, 17): (10, [317]),\n",
+ " (5, 18): (10, [316]),\n",
+ " (5, 19): (10, [315]),\n",
+ " (5, 20): (10, [314]),\n",
+ " (5, 21): (10, [313]),\n",
+ " (5, 22): (10, [312]),\n",
+ " (5, 23): (10, [311]),\n",
+ " (5, 24): (10, [310]),\n",
+ " (5, 25): (10, [309]),\n",
+ " (5, 26): (10, [308]),\n",
+ " (5, 27): (10, [307]),\n",
+ " (0, 27): (10, [306]),\n",
+ " (0, 26): (10, [305]),\n",
+ " (0, 25): (10, [304]),\n",
+ " (0, 24): (10, [303]),\n",
+ " (0, 38): (11, [348]),\n",
+ " (0, 37): (11, [347]),\n",
+ " (0, 36): (11, [346]),\n",
+ " (0, 35): (11, [345]),\n",
+ " (0, 34): (11, [344]),\n",
+ " (0, 33): (11, [343]),\n",
+ " (0, 32): (11, [342]),\n",
+ " (0, 31): (11, [341]),\n",
+ " (0, 30): (11, [340]),\n",
+ " (0, 29): (11, [339]),\n",
+ " (0, 28): (11, [338]),\n",
+ " (5, 28): (11, [337]),\n",
+ " (5, 29): (11, [336]),\n",
+ " (5, 30): (11, [335]),\n",
+ " (5, 31): (11, [334]),\n",
+ " (5, 32): (11, [333]),\n",
+ " (5, 33): (11, [332]),\n",
+ " (5, 34): (11, [331]),\n",
+ " (5, 35): (11, [330]),\n",
+ " (5, 36): (11, [329]),\n",
+ " (5, 37): (11, [328]),\n",
+ " (5, 38): (11, [327]),\n",
+ " (5, 39): (11, [326]),\n",
+ " (3, 0): (12, [381]),\n",
+ " (3, 1): (12, [380]),\n",
+ " (3, 2): (12, [379]),\n",
+ " (3, 3): (12, [378]),\n",
+ " (3, 4): (12, [377]),\n",
+ " (3, 5): (12, [376]),\n",
+ " (3, 6): (12, [375]),\n",
+ " (3, 7): (12, [374]),\n",
+ " (3, 8): (12, [373]),\n",
+ " (3, 9): (12, [372]),\n",
+ " (3, 10): (12, [371]),\n",
+ " (3, 11): (12, [370]),\n",
+ " (3, 12): (12, [369]),\n",
+ " (3, 13): (12, [368]),\n",
+ " (3, 14): (12, [367]),\n",
+ " (3, 15): (12, [366]),\n",
+ " (3, 16): (12, [365]),\n",
+ " (3, 17): (12, [364]),\n",
+ " (3, 18): (12, [363]),\n",
+ " (3, 19): (12, [362]),\n",
+ " (3, 20): (12, [361]),\n",
+ " (4, 20): (12, [360]),\n",
+ " (4, 19): (12, [359]),\n",
+ " (4, 18): (12, [358]),\n",
+ " (4, 17): (12, [357]),\n",
+ " (4, 16): (12, [356]),\n",
+ " (4, 15): (12, [355]),\n",
+ " (4, 14): (12, [354]),\n",
+ " (4, 13): (12, [353]),\n",
+ " (4, 12): (12, [352]),\n",
+ " (4, 11): (12, [351]),\n",
+ " (4, 10): (12, [350]),\n",
+ " (4, 9): (12, [349]),\n",
+ " (4, 39): (13, [414]),\n",
+ " (4, 38): (13, [413]),\n",
+ " (4, 37): (13, [412]),\n",
+ " (4, 36): (13, [411]),\n",
+ " (4, 35): (13, [410]),\n",
+ " (4, 34): (13, [409]),\n",
+ " (4, 33): (13, [408]),\n",
+ " (4, 32): (13, [407]),\n",
+ " (4, 31): (13, [406]),\n",
+ " (4, 30): (13, [405]),\n",
+ " (4, 29): (13, [404]),\n",
+ " (4, 28): (13, [403]),\n",
+ " (4, 27): (13, [402]),\n",
+ " (4, 26): (13, [401]),\n",
+ " (4, 25): (13, [400]),\n",
+ " (4, 24): (13, [399]),\n",
+ " (4, 23): (13, [398]),\n",
+ " (4, 22): (13, [397]),\n",
+ " (4, 21): (13, [396]),\n",
+ " (3, 21): (13, [395]),\n",
+ " (3, 22): (13, [394]),\n",
+ " (3, 23): (13, [393]),\n",
+ " (3, 24): (13, [392]),\n",
+ " (3, 25): (13, [391]),\n",
+ " (3, 26): (13, [390]),\n",
+ " (3, 27): (13, [389]),\n",
+ " (3, 28): (13, [388]),\n",
+ " (3, 29): (13, [387]),\n",
+ " (3, 30): (13, [386]),\n",
+ " (3, 31): (13, [385]),\n",
+ " (3, 32): (13, [384]),\n",
+ " (3, 33): (13, [383]),\n",
+ " (3, 34): (13, [382])}"
+ ]
+ },
+ "execution_count": 62,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s=vh_vb.__dict__\n",
+ "scafs=s[\"_scaf\"]\n",
+ "staps=s[\"_stap\"]\n",
+ "staps"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "549ad98c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class vstrands (object):\n",
+ "\n",
+ " def __init__(self):\n",
+ " self.vhelices = []\n",
+ "\n",
+ " def add_vhelix(self, toadd):\n",
+ " self.vhelices.append(toadd)\n",
+ "\n",
+ " def bbox(self):\n",
+ " rows = []\n",
+ " cols = []\n",
+ " lens = []\n",
+ " for h in self.vhelices:\n",
+ " rows.append(h.row)\n",
+ " cols.append(h.col)\n",
+ " lens.append(len(h.stap))\n",
+ "\n",
+ " dr = DIST_SQUARE * (max(rows) - min(rows) + 2)\n",
+ " dc = DIST_SQUARE * (max(cols) - min(cols) + 2)\n",
+ " dl = 0.34 * (max(lens) + 2)\n",
+ " \n",
+ " return 2 * max([dr, dc, dl]) * BOX_FACTOR\n",
+ " \n",
+ " def __str__(self):\n",
+ " a = '{\\n\"vstrands\":[\\n'\n",
+ " if len(self.vhelices) > 0:\n",
+ " for h in self.vhelices:\n",
+ " a = a + str(h) + ','\n",
+ " a = a[0:len(a) - 1]\n",
+ " a = a + '}\\n'\n",
+ " return a\n",
+ "class vhelix (object):\n",
+ "\n",
+ " def __init__(self):\n",
+ " self.stapLoop = []\n",
+ " self.scafLoop = []\n",
+ " self.skip = []\n",
+ " self.loop = []\n",
+ " self.stap_colors = []\n",
+ " self.row = 0\n",
+ " self.col = 0\n",
+ " self.num = 0\n",
+ " self.stap = []\n",
+ " self.scaf = []\n",
+ " self.cad_index = -1\n",
+ " self.skiploop_bases = 0\n",
+ "\n",
+ " def get_length(self):\n",
+ " return max (len(self.scaf), len(self.stap))\n",
+ "\n",
+ " len = property (get_length)\n",
+ "\n",
+ " def add_square(self, toadd, which):\n",
+ " if which == 'stap':\n",
+ " self.stap.append(toadd)\n",
+ " elif which == 'scaf':\n",
+ " self.scaf.append (toadd)\n",
+ " else:\n",
+ " base.Logger.log(\"Cannot add square that is not scaf or stap. Dying now\", base.Logger.CRITICAL)\n",
+ " sys.exit(1)\n",
+ " \n",
+ " def __str__(self):\n",
+ " a = '{\\n'\n",
+ "\n",
+ " a = a + '\"stapLoop\":['\n",
+ " if len(self.stapLoop) > 0:\n",
+ " for i in self.stapLoop:\n",
+ " a = a + str(i) + ','\n",
+ " a = a[0:len(a) - 1] # remove last comma\n",
+ " a = a + '],\\n'\n",
+ " a = a + '\"skip\":['\n",
+ " if len(self.skip) > 0:\n",
+ " for e in self.skip:\n",
+ " a = a + str(e) + ','\n",
+ " a = a[0:len(a) - 1] # remove last comma\n",
+ " a = a + '],\\n'\n",
+ " \n",
+ " a = a + '\"loop\":['\n",
+ " if len(self.loop) > 0:\n",
+ " for e in self.loop:\n",
+ " a = a + str(e) + ','\n",
+ " a = a[0:len(a) - 1] # remove last comma\n",
+ " a = a + '],\\n'\n",
+ " \n",
+ " a = a + '\"stap_colors\":['\n",
+ " if len (self.stap_colors) > 0:\n",
+ " for e in self.stap_colors:\n",
+ " a = a + str(e) + ','\n",
+ " a = a[0:len(a) - 1] # remove last comma\n",
+ " a = a + '],\\n'\n",
+ "\n",
+ " a = a + '\"row\":' + str(self.row) + ',\\n'\n",
+ " a = a + '\"col\":' + str(self.col) + ',\\n'\n",
+ " a = a + '\"num\":' + str(self.num) + ',\\n'\n",
+ " \n",
+ " a = a + '\"scafLoop\":['\n",
+ " if len(self.scafLoop) > 0:\n",
+ " for i in self.scafLoop:\n",
+ " a = a + str(i) + ','\n",
+ " a = a[0:len(a) - 1] # remove last comma\n",
+ " a = a + '],\\n'\n",
+ " \n",
+ " a = a + '\"stap\":['\n",
+ " if len(self.stap) > 0:\n",
+ " for i in self.stap:\n",
+ " a = a + str(i) + ','\n",
+ " a = a[0:len(a) - 1] # remove last comma\n",
+ " a = a + '],\\n'\n",
+ " \n",
+ " a = a + '\"scaf\":['\n",
+ " if len(self.scaf) > 0:\n",
+ " for i in self.scaf:\n",
+ " a = a + str(i) + ','\n",
+ " a = a[0:len(a) - 1] # remove last comma\n",
+ " a = a + ']\\n}'\n",
+ " return a\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "611050e9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "L=[]\n",
+ "for i in df[\"vstrands\"]:\n",
+ " L.append(i)\n",
+ "\n",
+ "cadsys = vstrands()\n",
+ "vh = vhelix()\n",
+ "for s in L:\n",
+ " \n",
+ " vh.stap = [ i for i in s[\"scaf\"]]\n",
+ " vh.scaf = [i for i in s[\"stap\"]]\n",
+ " vh.skiploop_bases = len(s[\"skip\"]) + sum(s[\"loop\"]) - sum(s[\"skip\"])\n",
+ " cadsys.add_vhelix(vh)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "7511a3e5",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['__class__',\n",
+ " '__delattr__',\n",
+ " '__dict__',\n",
+ " '__dir__',\n",
+ " '__doc__',\n",
+ " '__eq__',\n",
+ " '__format__',\n",
+ " '__ge__',\n",
+ " '__getattribute__',\n",
+ " '__gt__',\n",
+ " '__hash__',\n",
+ " '__init__',\n",
+ " '__init_subclass__',\n",
+ " '__le__',\n",
+ " '__lt__',\n",
+ " '__module__',\n",
+ " '__ne__',\n",
+ " '__new__',\n",
+ " '__reduce__',\n",
+ " '__reduce_ex__',\n",
+ " '__repr__',\n",
+ " '__setattr__',\n",
+ " '__sizeof__',\n",
+ " '__str__',\n",
+ " '__subclasshook__',\n",
+ " '__weakref__',\n",
+ " 'add_square',\n",
+ " 'cad_index',\n",
+ " 'col',\n",
+ " 'get_length',\n",
+ " 'len',\n",
+ " 'loop',\n",
+ " 'num',\n",
+ " 'row',\n",
+ " 'scaf',\n",
+ " 'scafLoop',\n",
+ " 'skip',\n",
+ " 'skiploop_bases',\n",
+ " 'stap',\n",
+ " 'stapLoop',\n",
+ " 'stap_colors']"
+ ]
+ },
+ "execution_count": 20,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s0=cadsys.vhelices[0]\n",
+ "dir(s0)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "id": "06db198d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[[-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, 5, 10],\n",
+ " [5, 9, 5, 11],\n",
+ " [5, 10, 5, 12],\n",
+ " [5, 11, 5, 13],\n",
+ " [5, 12, 5, 14],\n",
+ " [5, 13, 5, 15],\n",
+ " [5, 14, 5, 16],\n",
+ " [5, 15, 5, 17],\n",
+ " [5, 16, 5, 18],\n",
+ " [5, 17, 5, 19],\n",
+ " [5, 18, 5, 20],\n",
+ " [5, 19, 5, 21],\n",
+ " [5, 20, 5, 22],\n",
+ " [5, 21, 5, 23],\n",
+ " [5, 22, 5, 24],\n",
+ " [5, 23, 5, 25],\n",
+ " [5, 24, 5, 26],\n",
+ " [5, 25, 5, 27],\n",
+ " [5, 26, 0, 27],\n",
+ " [0, 28, 5, 29],\n",
+ " [5, 28, 5, 30],\n",
+ " [5, 29, 5, 31],\n",
+ " [5, 30, 5, 32],\n",
+ " [5, 31, 5, 33],\n",
+ " [5, 32, 5, 34],\n",
+ " [5, 33, 5, 35],\n",
+ " [5, 34, 5, 36],\n",
+ " [5, 35, 5, 37],\n",
+ " [5, 36, 5, 38],\n",
+ " [5, 37, 5, 39],\n",
+ " [5, 38, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1]]"
+ ]
+ },
+ "execution_count": 25,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s0.scaf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "064dbe09",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "for s in s0.scaf:\n",
+ " if s[0]==-1 and s[1]==-1:\n",
+ " pass\n",
+ " elif s[2]==len(s0.scaf) and abs(s[3])==1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "30f03d63",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[-1, -1, -1, -1]"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s0.scaf[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "a2b7becf",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['__class__',\n",
+ " '__delattr__',\n",
+ " '__dict__',\n",
+ " '__dir__',\n",
+ " '__doc__',\n",
+ " '__eq__',\n",
+ " '__format__',\n",
+ " '__ge__',\n",
+ " '__getattribute__',\n",
+ " '__gt__',\n",
+ " '__hash__',\n",
+ " '__init__',\n",
+ " '__init_subclass__',\n",
+ " '__le__',\n",
+ " '__lt__',\n",
+ " '__module__',\n",
+ " '__ne__',\n",
+ " '__new__',\n",
+ " '__reduce__',\n",
+ " '__reduce_ex__',\n",
+ " '__repr__',\n",
+ " '__setattr__',\n",
+ " '__sizeof__',\n",
+ " '__str__',\n",
+ " '__subclasshook__',\n",
+ " '__weakref__',\n",
+ " 'add_vhelix',\n",
+ " 'bbox',\n",
+ " 'vhelices']"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "dir(cadsys)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "id": "8fc5529a",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[[5, 1, -1, -1],\n",
+ " [5, 2, 5, 0],\n",
+ " [5, 3, 5, 1],\n",
+ " [-1, -1, 5, 2],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [5, 10, 4, 9],\n",
+ " [5, 11, 5, 9],\n",
+ " [5, 12, 5, 10],\n",
+ " [5, 13, 5, 11],\n",
+ " [5, 14, 5, 12],\n",
+ " [5, 15, 5, 13],\n",
+ " [5, 16, 5, 14],\n",
+ " [5, 17, 5, 15],\n",
+ " [5, 18, 5, 16],\n",
+ " [5, 19, 5, 17],\n",
+ " [5, 20, 5, 18],\n",
+ " [5, 21, 5, 19],\n",
+ " [5, 22, 5, 20],\n",
+ " [-1, -1, 5, 21],\n",
+ " [5, 24, -1, -1],\n",
+ " [5, 25, 5, 23],\n",
+ " [5, 26, 5, 24],\n",
+ " [5, 27, 5, 25],\n",
+ " [5, 28, 5, 26],\n",
+ " [5, 29, 5, 27],\n",
+ " [5, 30, 5, 28],\n",
+ " [5, 31, 5, 29],\n",
+ " [5, 32, 5, 30],\n",
+ " [5, 33, 5, 31],\n",
+ " [5, 34, 5, 32],\n",
+ " [5, 35, 5, 33],\n",
+ " [5, 36, 5, 34],\n",
+ " [5, 37, 5, 35],\n",
+ " [5, 38, 5, 36],\n",
+ " [5, 39, 5, 37],\n",
+ " [4, 39, 5, 38],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1]]"
+ ]
+ },
+ "execution_count": 36,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "vh.stap"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "02959074",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "ModuleNotFoundError",
+ "evalue": "No module named 'mrdna'",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mmrdna\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mreaders\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcadnano_segments\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mcadnano\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdocument\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Document\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mcadnano\u001b[39;00m\n",
+ "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'mrdna'"
+ ]
+ }
+ ],
+ "source": [
+ "\n",
+ "\n",
+ "from mrdna.readers.cadnano_segments import *\n",
+ "from cadnano.document import Document\n",
+ "import cadnano"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "bb9ce180",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "a87de3e3",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Found cadnano version 2 file\n"
+ ]
+ }
+ ],
+ "source": [
+ "json_data=read_json_file(\"test.json\")\n",
+ "part=decode_cadnano_part(json_data)\n",
+ "model=cadnano_part(part)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "ba0073f2",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Found cadnano version 2 file\n"
+ ]
+ }
+ ],
+ "source": [
+ "doc=Document()\n",
+ "cadnano.fileio.v2decode.decode(doc, json_data)\n",
+ "parts = [p for p in doc.getParts()]\n",
+ "part=parts[0]\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "8a45b04f",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oligo_(0.1[38])_1328\t23\t'None\n",
+ "Oligo_(2.1[34])_9584\t35\t'None\n",
+ "Oligo_(1.1[36])_7488\t188\t'None\n",
+ "Oligo_(4.1[39])_4384\t33\t'None\n",
+ "Oligo_(5.0[9])_0240\t23\t'None\n",
+ "Oligo_(1.0[3])_8256\t37\t'None\n",
+ "Oligo_(3.0[0])_3296\t33\t'None\n",
+ "Oligo_(0.1[23])_9088\t21\t'None\n",
+ "VH0\n",
+ "\t <fwd_StrandSet(0)> \t [(5, 36)] \n",
+ "\t\t\t\t ['#0066cc']\n",
+ "\t <rev_StrandSet(0)> \t [(2, 20), (21, 23), (24, 27), (28, 38)] \n",
+ "\t\t\t\t ['#cc0000', '#b8056c', '#f74308', '#1700de']\n",
+ "VH1\n",
+ "\t <fwd_StrandSet(1)> \t [(3, 20), (21, 38)] \n",
+ "\t\t\t\t ['#cc0000', '#b8056c']\n",
+ "\t <rev_StrandSet(1)> \t [(5, 18), (19, 36)] \n",
+ "\t\t\t\t ['#0066cc', '#0066cc']\n",
+ "VH2\n",
+ "\t <fwd_StrandSet(2)> \t [(2, 18), (19, 32)] \n",
+ "\t\t\t\t ['#0066cc', '#0066cc']\n",
+ "\t <rev_StrandSet(2)> \t [(0, 34)] \n",
+ "\t\t\t\t ['#888888']\n",
+ "VH3\n",
+ "\t <fwd_StrandSet(3)> \t [(0, 20), (21, 34)] \n",
+ "\t\t\t\t ['#cc0000', '#888888']\n",
+ "\t <rev_StrandSet(3)> \t [(2, 15), (16, 32)] \n",
+ "\t\t\t\t ['#0066cc', '#0066cc']\n",
+ "VH4\n",
+ "\t <fwd_StrandSet(4)> \t [(9, 15), (16, 39)] \n",
+ "\t\t\t\t ['#0066cc', '#0066cc']\n",
+ "\t <rev_StrandSet(4)> \t [(9, 20), (21, 39)] \n",
+ "\t\t\t\t ['#cc0000', '#888888']\n",
+ "VH5\n",
+ "\t <fwd_StrandSet(5)> \t [(9, 27), (28, 39)] \n",
+ "\t\t\t\t ['#f74308', '#1700de']\n",
+ "\t <rev_StrandSet(5)> \t [(9, 39)] \n",
+ "\t\t\t\t ['#0066cc']\n"
+ ]
+ }
+ ],
+ "source": [
+ "part.__dict__.keys()\n",
+ "\n",
+ "oligos = part.oligos()\n",
+ "for oligo in oligos:\n",
+ " print(\"{0}\\t{1}\\t\\'{2}\".format(oligo,\n",
+ " oligo.length(),\n",
+ " oligo.sequence()))\n",
+ "\n",
+ "vhs = list(part.getIdNums()) # convert set to list\n",
+ "for vh_id in vhs: # display first 3 vhs\n",
+ " fwd_ss, rev_ss = part.getStrandSets(vh_id)\n",
+ " print('VH{0}'.format(vh_id))\n",
+ " print('\\t', fwd_ss, '\\t', [s.idxs() for s in fwd_ss.strands()], '\\n\\t\\t\\t\\t',\n",
+ " [s.getColor() for s in fwd_ss.strands()])\n",
+ " print('\\t', rev_ss, '\\t', [s.idxs() for s in rev_ss.strands()], '\\n\\t\\t\\t\\t',\n",
+ " [s.getColor() for s in rev_ss.strands()])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "12b582e0",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "strands5 = [o.strand5p() for o in part.oligos()]\n",
+ "strands3 = [o.strand3p() for o in part.oligos()]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "id": "0df7bddb",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['__class__',\n",
+ " '__delattr__',\n",
+ " '__dict__',\n",
+ " '__dir__',\n",
+ " '__doc__',\n",
+ " '__eq__',\n",
+ " '__format__',\n",
+ " '__ge__',\n",
+ " '__getattribute__',\n",
+ " '__gt__',\n",
+ " '__hash__',\n",
+ " '__init__',\n",
+ " '__init_subclass__',\n",
+ " '__le__',\n",
+ " '__lt__',\n",
+ " '__module__',\n",
+ " '__ne__',\n",
+ " '__new__',\n",
+ " '__reduce__',\n",
+ " '__reduce_ex__',\n",
+ " '__repr__',\n",
+ " '__setattr__',\n",
+ " '__sizeof__',\n",
+ " '__slots__',\n",
+ " '__str__',\n",
+ " '__subclasshook__',\n",
+ " '__weakref__',\n",
+ " '_decrementLength',\n",
+ " '_incrementLength',\n",
+ " '_is_circular',\n",
+ " '_parent',\n",
+ " '_part',\n",
+ " '_props',\n",
+ " '_setColor',\n",
+ " '_setLength',\n",
+ " '_setLoop',\n",
+ " '_setProperty',\n",
+ " '_signals',\n",
+ " '_strand5p',\n",
+ " '_strandMergeUpdate',\n",
+ " '_strandSplitUpdate',\n",
+ " 'addToPart',\n",
+ " 'applyAbstractSequences',\n",
+ " 'applyColor',\n",
+ " 'applySequence',\n",
+ " 'applySequenceCMD',\n",
+ " 'clearAbstractSequences',\n",
+ " 'connect',\n",
+ " 'deleteLater',\n",
+ " 'destroy',\n",
+ " 'disconnect',\n",
+ " 'displayAbstractSequences',\n",
+ " 'dump',\n",
+ " 'editable_properties',\n",
+ " 'getAbsolutePositionAtLength',\n",
+ " 'getColor',\n",
+ " 'getModelProperties',\n",
+ " 'getName',\n",
+ " 'getNumberOfBasesToEachXover',\n",
+ " 'getOutlineProperties',\n",
+ " 'getProperty',\n",
+ " 'getStrandLengths',\n",
+ " 'isCircular',\n",
+ " 'length',\n",
+ " 'locString',\n",
+ " 'oligoPropertyChangedSignal',\n",
+ " 'oligoRemovedSignal',\n",
+ " 'oligoSelectedChangedSignal',\n",
+ " 'oligoSequenceAddedSignal',\n",
+ " 'oligoSequenceClearedSignal',\n",
+ " 'parent',\n",
+ " 'part',\n",
+ " 'refreshLength',\n",
+ " 'remove',\n",
+ " 'removeFromPart',\n",
+ " 'sequence',\n",
+ " 'sequenceExport',\n",
+ " 'setParent',\n",
+ " 'setPart',\n",
+ " 'setProperty',\n",
+ " 'setStrand5p',\n",
+ " 'shallowCopy',\n",
+ " 'shouldHighlight',\n",
+ " 'signals',\n",
+ " 'splitAtAbsoluteLengths',\n",
+ " 'strand3p',\n",
+ " 'strand5p',\n",
+ " 'undoStack']"
+ ]
+ },
+ "execution_count": 26,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "L=[o for o in part.oligos()]\n",
+ "dir(L[2])\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "id": "fa34a0b6",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "defaultdict(dict, {0: {}, 1: {}, 2: {}, 3: {}, 4: {}, 5: {}})"
+ ]
+ },
+ "execution_count": 25,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "part.insertions()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "fa74a1d1",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{'name': 'NaPart1',\n",
+ " 'color': '#0066cc',\n",
+ " 'is_visible': True,\n",
+ " 'active_phos': None,\n",
+ " 'crossover_span_angle': 45,\n",
+ " 'max_vhelix_length': 42,\n",
+ " 'neighbor_active_angle': '',\n",
+ " 'grid_type': <GridEnum.HONEYCOMB: 2>,\n",
+ " 'virtual_helix_order': [0, 1, 2, 3, 4, 5],\n",
+ " 'is_lattice': True,\n",
+ " <GridEnum.HONEYCOMB: 2>: <GridEnum.NONE: 0>}"
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "part.getModelProperties()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "425b6ab6",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " _\n",
+ " _____ ___ _| |___ ___\n",
+ "| | _| . | | .'|\n",
+ "|_|_|_|_| |___|_|_|__,| v1.0a.dev74 \n",
+ "it/its\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "import pdb\n",
+ "import numpy as np\n",
+ "import os,sys\n",
+ "import scipy\n",
+ "\n",
+ "from mrdna import logger, devlogger\n",
+ "from mrdna.segmentmodel import SegmentModel, SingleStrandedSegment, DoubleStrandedSegment\n",
+ "from mrdna.arbdmodel.coords import quaternion_from_matrix, rotationAboutAxis, quaternion_slerp\n",
+ "from mrdna import get_resource_path\n",
+ "\n",
+ "ref_stack_position = np.array((-2.41851735, -0.259761333, 3.39999978))\n",
+ "\n",
+ "def _three_prime_list_to_five_prime(three_prime):\n",
+ " five_prime = -np.ones(three_prime.shape, dtype=int)\n",
+ " has_three_prime = np.where(three_prime >= 0)[0]\n",
+ " five_prime[three_prime[has_three_prime]] = has_three_prime\n",
+ " return five_prime \n",
+ "def _primes_list_to_strands(three_prime, five_prime):\n",
+ " five_prime_ends = np.where(five_prime < 0)[0]\n",
+ " strands = []\n",
+ " strand_is_circular = []\n",
+ " \n",
+ " idx_to_strand = -np.ones(three_prime.shape, dtype=int)\n",
+ "\n",
+ " def build_strand(nt_idx, conditional):\n",
+ " strand = [nt_idx]\n",
+ " idx_to_strand[nt_idx] = len(strands)\n",
+ " while conditional(nt_idx):\n",
+ " nt_idx = three_prime[nt_idx]\n",
+ " strand.append(nt_idx)\n",
+ " idx_to_strand[nt_idx] = len(strands)\n",
+ " strands.append( np.array(strand, dtype=int) )\n",
+ "\n",
+ " for nt_idx in five_prime_ends:\n",
+ " build_strand(nt_idx,\n",
+ " lambda nt: three_prime[nt] >= 0)\n",
+ " strand_is_circular.append(False)\n",
+ "\n",
+ " while True:\n",
+ " ## print(\"WARNING: working on circular strand {}\".format(len(strands)))\n",
+ " ids = np.where(idx_to_strand < 0)[0]\n",
+ " if len(ids) == 0: break\n",
+ " build_strand(ids[0],\n",
+ " lambda nt: three_prime[nt] >= 0 and \\\n",
+ " idx_to_strand[three_prime[nt]] < 0)\n",
+ " strand_is_circular.append(True)\n",
+ "\n",
+ " return strands, strand_is_circular\n",
+ "\n",
+ "def find_stacks(centers, transforms):\n",
+ "\n",
+ " ## Find orientation and center of each nucleotide\n",
+ " expected_stack_positions = []\n",
+ " for R,c in zip(transforms,centers):\n",
+ " expected_stack_positions.append( c + ref_stack_position.dot(R) )\n",
+ "\n",
+ " expected_stack_positions = np.array(expected_stack_positions, dtype=np.float32)\n",
+ "\n",
+ " dists = scipy.spatial.distance_matrix(expected_stack_positions, centers)\n",
+ " dists = dists + 5*np.eye(len(dists))\n",
+ " idx1, idx2 = np.where(dists < 3.5)\n",
+ "\n",
+ " ## Convert distances to stacks\n",
+ " stacks_above = -np.ones(len(centers), dtype=int)\n",
+ " _z = np.array((0,0,1))\n",
+ " for i in np.unique(idx1):\n",
+ " js = idx2[ idx1 == i ]\n",
+ " with np.errstate(divide='ignore',invalid='ignore'):\n",
+ " angles = [np.arccos( transforms[j].T.dot( transforms[i].dot(_z) ).dot( _z ) ) for j in js]\n",
+ " angles = np.array( angles )\n",
+ " tmp = np.argmin(dists[i][js] + 1.0*angles)\n",
+ " j = js[tmp]\n",
+ " stacks_above[i] = j\n",
+ "\n",
+ " return stacks_above\n",
+ "\n",
+ "def basepairs_and_stacks_to_helixmap(basepairs,stacks_above):\n",
+ "\n",
+ " helixmap = -np.ones(basepairs.shape, dtype=int)\n",
+ " helixrank = -np.ones(basepairs.shape)\n",
+ " is_fwd = np.ones(basepairs.shape, dtype=int)\n",
+ " \n",
+ " ## Remove stacks with nts lacking a basepairs\n",
+ " nobp = np.where(basepairs < 0)[0]\n",
+ " stacks_above[nobp] = -1\n",
+ " stacks_with_nobp = np.in1d(stacks_above, nobp)\n",
+ " stacks_above[stacks_with_nobp] = -1\n",
+ "\n",
+ " end_ids = np.where( (stacks_above < 0)*(basepairs >= 0) )[0]\n",
+ "\n",
+ " hid = 0\n",
+ " for end in end_ids:\n",
+ " if helixmap[end] >= 0:\n",
+ " continue\n",
+ " rank = 0\n",
+ " nt = basepairs[end]\n",
+ " bp = basepairs[nt]\n",
+ " assert( bp == end )\n",
+ " if helixmap[nt] >= 0 or helixmap[bp] >= 0:\n",
+ " logger.warning(f'Ill-formed helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')\n",
+ " continue\n",
+ " # assert(helixmap[nt] == -1)\n",
+ " # assert(helixmap[bp] == -1)\n",
+ " helixmap[nt] = helixmap[bp] = hid\n",
+ " helixrank[nt] = helixrank[bp] = rank\n",
+ " is_fwd[bp] = 0\n",
+ " rank +=1\n",
+ "\n",
+ " _tmp = [(nt,bp)]\n",
+ " \n",
+ " while stacks_above[nt] >= 0:\n",
+ " nt = stacks_above[nt]\n",
+ " if basepairs[nt] < 0: break\n",
+ " bp = basepairs[nt]\n",
+ " if helixmap[nt] >= 0 or helixmap[bp] >= 0:\n",
+ " logger.warning(f'Ill-formed helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')\n",
+ " break\n",
+ " helixmap[nt] = helixmap[bp] = hid\n",
+ " helixrank[nt] = helixrank[bp] = rank\n",
+ " is_fwd[bp] = 0\n",
+ " _tmp.append((nt,bp))\n",
+ " rank +=1\n",
+ "\n",
+ " hid += 1\n",
+ "\n",
+ " ## Create \"helix\" for each circular segment\n",
+ " intrahelical = []\n",
+ " processed = set()\n",
+ " unclaimed_bases = np.where( (basepairs >= 0)*(helixmap == -1) )[0]\n",
+ " for nt0 in unclaimed_bases:\n",
+ " if nt0 in processed: continue\n",
+ "\n",
+ " nt = nt0\n",
+ " all_nts = [nt]\n",
+ "\n",
+ " rank = 0\n",
+ " nt = nt0\n",
+ " bp = basepairs[nt]\n",
+ " if helixmap[nt] >= 0 or helixmap[bp] >= 0:\n",
+ " logger.warning(f'Ill-formed cylic helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')\n",
+ " continue\n",
+ " helixmap[nt] = helixmap[bp] = hid\n",
+ " helixrank[nt] = helixrank[bp] = rank\n",
+ " is_fwd[bp] = 0\n",
+ " rank +=1\n",
+ " processed.add(nt)\n",
+ " processed.add(bp)\n",
+ "\n",
+ " counter = 0\n",
+ " while stacks_above[nt] >= 0:\n",
+ " lastnt = nt\n",
+ " nt = stacks_above[nt]\n",
+ " bp = basepairs[nt]\n",
+ " if nt == nt0 or nt == basepairs[nt0]:\n",
+ " intrahelical.append((lastnt,nt0))\n",
+ " break\n",
+ " \n",
+ " assert( bp >= 0 )\n",
+ " if helixmap[nt] >= 0 or helixmap[bp] >= 0:\n",
+ " logger.warning(f'Ill-formed cyclic helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')\n",
+ " break\n",
+ " \n",
+ " helixmap[nt] = helixmap[bp] = hid\n",
+ " helixrank[nt] = helixrank[bp] = rank\n",
+ " is_fwd[bp] = 0\n",
+ " processed.add(nt)\n",
+ " processed.add(bp)\n",
+ " rank +=1\n",
+ " hid += 1\n",
+ "\n",
+ " return helixmap, helixrank, is_fwd, intrahelical\n",
+ "\n",
+ "\n",
+ "def set_splines(seg, coordinate, hid, hmap, hrank, fwd, basepair, orientation=None):\n",
+ " maxrank = np.max( hrank[hmap==hid] )\n",
+ " if maxrank == 0:\n",
+ " ids = np.where((hmap == hid))[0]\n",
+ " pos = np.mean( [coordinate[r,:] for r in ids ], axis=0 )\n",
+ " coords = [pos,pos]\n",
+ " contours = [0,1]\n",
+ " if orientation is not None:\n",
+ " ids = np.where((hmap == hid) * fwd)[0]\n",
+ " assert( len(ids) == 1 )\n",
+ " q = quaternion_from_matrix( orientation[ids[0]] )\n",
+ " quats = [q, q]\n",
+ " coords[-1] = pos + orientation[ids[0]].dot(np.array((0,0,1)))\n",
+ "\n",
+ " else:\n",
+ " coords,contours,quats = [[],[],[]]\n",
+ " last_q = None\n",
+ " for rank in range(int(maxrank)+1):\n",
+ " ids = np.where((hmap == hid) * (hrank == rank))[0]\n",
+ " \n",
+ " coords.append(np.mean( [coordinate[r,:] for r in ids ], axis=0 ))\n",
+ " contours.append( float(rank+0.5)/(maxrank+1) )\n",
+ " if orientation is not None:\n",
+ " ids = np.where((hmap == hid) * (hrank == rank) * fwd)[0]\n",
+ " assert(len(ids) == 1)\n",
+ " q = quaternion_from_matrix( orientation[ids[0]] )\n",
+ "\n",
+ " if last_q is not None and last_q.dot(q) < 0:\n",
+ " q = -q\n",
+ "\n",
+ " ## Average quaterion with reverse direction\n",
+ " bp = basepair[ids[0]]\n",
+ " if bp >= 0:\n",
+ " bp_o = orientation[bp].dot(rotationAboutAxis(np.array((1,0,0)),180))\n",
+ " q2 = quaternion_from_matrix( bp_o )\n",
+ " if q.dot(q2) < 0:\n",
+ " q2 = -q2\n",
+ "\n",
+ " ## probably good enough, but slerp is better: q = (q + q2)*0.5\n",
+ " q = quaternion_slerp(q,q2,0.5)\n",
+ "\n",
+ " quats.append(q)\n",
+ " last_q = q\n",
+ "\n",
+ " coords = np.array(coords)\n",
+ " seg.set_splines(contours,coords)\n",
+ " if orientation is not None:\n",
+ " quats = np.array(quats)\n",
+ " seg.set_orientation_splines(contours,quats)\n",
+ "\n",
+ " seg.start_position = coords[0,:]\n",
+ " seg.end_position = coords[-1,:]\n",
+ "\n",
+ "\n",
+ "def model_from_basepair_stack_3prime(coordinate, basepair, stack, three_prime,\n",
+ " sequence=None, orientation=None,\n",
+ " max_basepairs_per_bead = 5,\n",
+ " max_nucleotides_per_bead = 5,\n",
+ " local_twist = False,\n",
+ " dimensions=(5000,5000,5000),\n",
+ " **model_parameters):\n",
+ " \"\"\" \n",
+ " Creates a SegmentModel object from lists of each nucleotide's\n",
+ " basepair, its stack (on 3' side) and its 3'-connected nucleotide\n",
+ "\n",
+ " The first argument should be an N-by-3 numpy array containing the\n",
+ " coordinate of each nucleotide, where N is the number of\n",
+ " nucleotides. The following three arguments should be integer lists\n",
+ " where the i-th element corresponds to the i-th nucleotide; the\n",
+ " list element should the integer index of the corresponding\n",
+ " basepaired / stacked / phosphodiester-bonded nucleotide. If there\n",
+ " is no such nucleotide, the value should be -1.\n",
+ "\n",
+ " Args:\n",
+ " basepair: List of each nucleotide's basepair's index\n",
+ " stack: List containing index of the nucleotide stacked on the 3' of each nucleotide\n",
+ " three_prime: List of each nucleotide's the 3' end of each nucleotide\n",
+ "\n",
+ " Returns:\n",
+ " SegmentModel\n",
+ " \"\"\"\n",
+ "\n",
+ " \"\"\" Validate Input \"\"\"\n",
+ " inputs = (basepair,three_prime)\n",
+ " try:\n",
+ " basepair,three_prime = [np.array(a,dtype=int) for a in inputs]\n",
+ " except:\n",
+ " raise TypeError(\"One or more of the input lists could not be converted into a numpy array\")\n",
+ " inputs = (basepair,three_prime)\n",
+ " coordinate = np.array(coordinate)\n",
+ "\n",
+ " if np.any( [len(a.shape) > 1 for a in inputs] ):\n",
+ " raise ValueError(\"One or more of the input lists has the wrong dimensionality\")\n",
+ "\n",
+ " if len(coordinate.shape) != 2:\n",
+ " raise ValueError(\"Coordinate array has the wrong dimensionality\")\n",
+ "\n",
+ " inputs = (coordinate,basepair,three_prime)\n",
+ " if not np.all(np.diff([len(a) for a in inputs]) == 0):\n",
+ " raise ValueError(\"Inputs are not the same length\")\n",
+ " \n",
+ " num_nt = len(basepair)\n",
+ " if sequence is not None and len(sequence) != num_nt:\n",
+ " raise ValueError(\"The 'sequence' parameter is the wrong length {} != {}\".format(len(sequence),num_nt))\n",
+ "\n",
+ " if orientation is not None:\n",
+ " orientation = np.array(orientation)\n",
+ " if len(orientation.shape) != 3:\n",
+ " raise ValueError(\"The 'orientation' array has the wrong dimensionality (should be Nx3x3)\")\n",
+ " if orientation.shape != (num_nt,3,3):\n",
+ " raise ValueError(\"The 'orientation' array is not properly formatted\")\n",
+ "\n",
+ " if stack is None:\n",
+ " if orientation is not None:\n",
+ " stack = find_stacks(coordinate, orientation)\n",
+ " else:\n",
+ " ## Guess stacking based on 3' connectivity\n",
+ " stack = np.array(three_prime,dtype=int) # Assume nts on 3' ends are stacked\n",
+ " _stack_below = _three_prime_list_to_five_prime(stack)\n",
+ " _has_bp = (basepair >= 0)\n",
+ " _nostack = np.where( (stack == -1)*_has_bp )[0]\n",
+ " _has_stack_below = _stack_below[basepair[_nostack]] >= 0\n",
+ " _nostack2 = _nostack[_has_stack_below]\n",
+ " stack[_nostack2] = basepair[_stack_below[basepair[_nostack2]]]\n",
+ "\n",
+ " else:\n",
+ " try:\n",
+ " stack = np.array(stack,dtype=int)\n",
+ " except:\n",
+ " raise TypeError(\"The 'stack' array could not be converted into a numpy integer array\")\n",
+ "\n",
+ " if len(stack.shape) != 1:\n",
+ " raise ValueError(\"The 'stack' array has the wrong dimensionality\")\n",
+ "\n",
+ " if len(stack) != num_nt:\n",
+ " raise ValueError(\"The length of the 'stack' array does not match other inputs\")\n",
+ "\n",
+ " bps = basepair # alias\n",
+ "\n",
+ " \"\"\" Fix stacks: require that the stack of a bp of a base's stack is its bp \"\"\"\n",
+ " _has_bp = (bps >= 0)\n",
+ " _has_stack = (stack >= 0)\n",
+ " _stack_has_basepair = (bps[stack] >= 0) * _has_stack\n",
+ " stack = np.where( (stack[bps[stack]] == bps) * _has_bp * _has_stack * _has_bp,\n",
+ " stack, -np.ones(len(stack),dtype=int) )\n",
+ "\n",
+ " five_prime = _three_prime_list_to_five_prime(three_prime)\n",
+ "\n",
+ " \"\"\" Build map of dsDNA helices and strands \"\"\"\n",
+ " hmap,hrank,fwd,intrahelical = basepairs_and_stacks_to_helixmap(bps,stack)\n",
+ " double_stranded_helices = np.unique(hmap[hmap >= 0]) \n",
+ " strands, strand_is_circular = _primes_list_to_strands(three_prime, five_prime)\n",
+ "\n",
+ " \"\"\" Add ssDNA to hmap \"\"\"\n",
+ " if len(double_stranded_helices) > 0:\n",
+ " hid = double_stranded_helices[-1]+1\n",
+ " else:\n",
+ " hid = 0\n",
+ " ss_residues = hmap < 0\n",
+ " #\n",
+ " if np.any(bps[ss_residues] != -1):\n",
+ " logger.warning(f'{np.sum(bps[ss_residues] != -1)} ssDNA nucleotides appear to have basepairs... ignoring')\n",
+ " \n",
+ " for s,c in zip(strands, strand_is_circular):\n",
+ " strand_segment_ends = [i for i in np.where( np.diff(hmap[s]) != 0 )[0]] + [len(s)-1]\n",
+ " seg_start = 0\n",
+ " for i in strand_segment_ends:\n",
+ " if hmap[s[i]] < 0:\n",
+ " ## Found single-stranded segment\n",
+ " ids = s[seg_start:i+1]\n",
+ " assert( np.all(hmap[ids] == -1) )\n",
+ " hmap[ids] = hid\n",
+ " hrank[ids] = np.arange(i+1-seg_start)\n",
+ " hid+=1\n",
+ " seg_start = i+1\n",
+ "\n",
+ " if len(double_stranded_helices) > 0:\n",
+ " single_stranded_helices = np.arange(double_stranded_helices[-1]+1,hid)\n",
+ " else:\n",
+ " single_stranded_helices = np.arange(hid)\n",
+ "\n",
+ " ## Create double-stranded segments\n",
+ " doubleSegments = []\n",
+ " for hid in double_stranded_helices:\n",
+ " seg = DoubleStrandedSegment(name=str(hid),\n",
+ " num_bp = np.sum(hmap==hid)//2)\n",
+ " set_splines(seg, coordinate, hid, hmap, hrank, fwd, basepair, orientation)\n",
+ "\n",
+ " assert(hid == len(doubleSegments))\n",
+ " doubleSegments.append(seg)\n",
+ "\n",
+ " ## Create single-stranded segments\n",
+ " singleSegments = []\n",
+ " for hid in single_stranded_helices:\n",
+ " seg = SingleStrandedSegment(name=str(hid),\n",
+ " num_nt = np.sum(hmap==hid))\n",
+ " set_splines(seg, coordinate, hid, hmap, hrank, fwd, basepair, orientation)\n",
+ "\n",
+ " assert(hid == len(doubleSegments) + len(singleSegments))\n",
+ " singleSegments.append(seg)\n",
+ "\n",
+ " ## Find crossovers and 5prime/3prime ends\n",
+ " crossovers,prime5,prime3 = [[],[],[]]\n",
+ " for s,c in zip(strands,strand_is_circular):\n",
+ " tmp = np.where(np.diff(hmap[s]) != 0)[0]\n",
+ " for i in tmp:\n",
+ " crossovers.append( (s[i],s[i+1]) )\n",
+ " if c:\n",
+ " if hmap[s[-1]] != hmap[s[0]]:\n",
+ " crossovers.append( (s[-1],s[0]) )\n",
+ " else:\n",
+ " prime5.append(s[0])\n",
+ " prime3.append(s[-1])\n",
+ "\n",
+ " ## Add connections\n",
+ " allSegments = doubleSegments+singleSegments\n",
+ "\n",
+ " for r1,r2 in crossovers:\n",
+ " seg1,seg2 = [allSegments[hmap[i]] for i in (r1,r2)]\n",
+ " nt1,nt2 = [hrank[i] for i in (r1,r2)]\n",
+ " f1,f2 = [fwd[i] for i in (r1,r2)]\n",
+ "\n",
+ " ## Handle connections at the ends\n",
+ " is_terminal1 = (nt1,f1) in ((0,0),(seg1.num_nt-1,1))\n",
+ " is_terminal2 = (nt2,f2) in ((0,1),(seg2.num_nt-1,0))\n",
+ "\n",
+ " print(seg1,seg2, r1, r2, is_terminal1, is_terminal2)\n",
+ " if is_terminal1 or is_terminal2:\n",
+ " \"\"\" Ensure that we don't have three-way dsDNA junctions \"\"\"\n",
+ " if is_terminal1 and (bps[r1] >= 0) and (five_prime[bps[r1]] >= 0) and (three_prime[r1] >= 0):\n",
+ " if (bps[five_prime[bps[r1]]] >= 0) and (bps[three_prime[r1]] >= 0):\n",
+ " # is_terminal1 = (three_prime[r1] == bps[five_prime[bps[r1]]])\n",
+ " is_terminal1 = hmap[five_prime[bps[r1]]] == hmap[three_prime[r1]]\n",
+ " if is_terminal2 and (bps[r2] >= 0) and (three_prime[bps[r2]] >= 0) and (five_prime[r2] >= 0):\n",
+ " if (bps[three_prime[bps[r2]]] >= 0) and (bps[five_prime[r2]] >= 0):\n",
+ " # is_terminal2 = (five_prime[r2] == bps[three_prime[bps[r2]]])\n",
+ " is_terminal2 = hmap[three_prime[bps[r2]]] == hmap[five_prime[r2]]\n",
+ " \n",
+ " \"\"\" Place connection \"\"\"\n",
+ " if is_terminal1 and is_terminal2:\n",
+ " end1 = seg1.end3 if f1 else seg1.start3\n",
+ " end2 = seg2.start5 if f2 else seg2.end5\n",
+ " seg1._connect_ends( end1, end2, type_='intrahelical')\n",
+ " else:\n",
+ " seg1.add_crossover(nt1,seg2,nt2,[f1,f2],type_=\"terminal_crossover\")\n",
+ " else:\n",
+ " seg1.add_crossover(nt1,seg2,nt2,[f1,f2])\n",
+ "\n",
+ " ## Add 5prime/3prime ends\n",
+ " for r in prime5:\n",
+ " seg = allSegments[hmap[r]]\n",
+ " seg.add_5prime(hrank[r],fwd[r])\n",
+ " for r in prime3:\n",
+ " seg = allSegments[hmap[r]]\n",
+ " seg.add_3prime(hrank[r],fwd[r])\n",
+ "\n",
+ " ## Add intrahelical connections to circular helical sections\n",
+ " for nt0,nt1 in intrahelical:\n",
+ " seg = allSegments[hmap[nt0]]\n",
+ " assert( seg is allSegments[hmap[nt1]] )\n",
+ " if three_prime[nt0] >= 0:\n",
+ " if hmap[nt0] == hmap[three_prime[nt0]]:\n",
+ " seg.connect_end3(seg.start5)\n",
+ "\n",
+ " bp0,bp1 = [bps[nt] for nt in (nt0,nt1)]\n",
+ " if three_prime[bp1] >= 0:\n",
+ " if hmap[bp1] == hmap[three_prime[bp1]]:\n",
+ " seg.connect_start3(seg.end5)\n",
+ "\n",
+ " ## Assign sequence\n",
+ " if sequence is not None:\n",
+ " for hid in range(len(allSegments)):\n",
+ " resids = np.where( (hmap==hid)*(fwd==1) )[0]\n",
+ " s = allSegments[hid]\n",
+ " s.sequence = [sequence[r] for r in sorted(resids,key=lambda x: hrank[x])]\n",
+ "\n",
+ "\n",
+ " ## Build model\n",
+ " model = SegmentModel( allSegments,\n",
+ " max_basepairs_per_bead = max_basepairs_per_bead,\n",
+ " max_nucleotides_per_bead = max_nucleotides_per_bead,\n",
+ " local_twist = local_twist,\n",
+ " dimensions = dimensions,\n",
+ " **model_parameters )\n",
+ "\n",
+ "\n",
+ " model._reader_list_coordinates = coordinate\n",
+ " model._reader_list_basepair = basepair\n",
+ " model._reader_list_stack = stack\n",
+ " model._reader_list_three_prime = three_prime\n",
+ " model._reader_list_five_prime = five_prime\n",
+ " model._reader_list_sequence = sequence\n",
+ " model._reader_list_orientation = orientation\n",
+ " model._reader_list_hmap = hmap\n",
+ " model._reader_list_fwd = fwd\n",
+ " model._reader_list_hrank = hrank\n",
+ "\n",
+ " if sequence is None:\n",
+ " for s in model.segments:\n",
+ " s.randomize_unset_sequence()\n",
+ "\n",
+ " return model\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "e986bda7",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<DoubleStrandedSegment'> 1[1]> <DoubleStrandedSegment'> 0[1]> 5 3 True True\n",
+ "<SingleStrandedSegment'> 2[2]> <DoubleStrandedSegment'> 0[1]> 1 2 True True\n",
+ "<DoubleStrandedSegment'> 0[1]> <DoubleStrandedSegment'> 1[1]> 2 4 True True\n",
+ "<DoubleStrandedSegment'> 1[1]> <SingleStrandedSegment'> 3[1]> 4 6 True True\n",
+ "<SingleStrandedSegment'> 3[1]> <SingleStrandedSegment'> 2[2]> 6 0 True True\n"
+ ]
+ }
+ ],
+ "source": [
+ "coordinate = [(0,0,3.4*i) for i in range(7)]\n",
+ "three_prime = [ 1, 2, 4,-1, 6, 3, 0]\n",
+ "basepair = [-1,-1, 3, 2, 5, 4,-1]\n",
+ "stack = [-1,-1, -1,-1,-1, -1,-1]\n",
+ "for i in [3,5]:\n",
+ " coordinate[i] = (1,0,3.4*i)\n",
+ "\n",
+ "model = model_from_basepair_stack_3prime(coordinate, basepair, stack, three_prime,\n",
+ " max_basepairs_per_bead=1,\n",
+ " max_nucleotides_per_bead=1,\n",
+ " local_twist=False)\n",
+ "model.writePsf(\"list.psf\")\n",
+ "model.writePdb(\"list.pdb\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "7e1ee20f",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[[<SegmentParticle DNA on <DoubleStrandedSegment'> 0[1]>[1.00]>], [<SegmentParticle DNA on <DoubleStrandedSegment'> 1[1]>[0.00]>, <SegmentParticle DNA on <DoubleStrandedSegment'> 1[1]>[1.00]>], [<SegmentParticle NAS on <SingleStrandedSegment'> 2[2]>[0.00]>, <SegmentParticle NAS on <SingleStrandedSegment'> 2[2]>[0.50]>, <SegmentParticle NAS on <SingleStrandedSegment'> 2[2]>[1.00]>], [<SegmentParticle NAS on <SingleStrandedSegment'> 3[1]>[0.50]>]]\n",
+ "[[<Connection <Location 1.end3[0,on_fwd_strand]>--intrahelical--<Location 0.end5[0,on_fwd_strand]>]>, <Connection <Location 2.end3[1,on_fwd_strand]>--sscrossover--<Location 0.end5[0,on_rev_strand]>]>, <Connection <Location 0.end3[0,on_rev_strand]>--intrahelical--<Location 1.end5[0,on_rev_strand]>]>], [<Connection <Location 1.end3[0,on_fwd_strand]>--intrahelical--<Location 0.end5[0,on_fwd_strand]>]>, <Connection <Location 0.end3[0,on_rev_strand]>--intrahelical--<Location 1.end5[0,on_rev_strand]>]>, <Connection <Location 1.end3[0,on_rev_strand]>--intrahelical--<Location 3.end5[0,on_fwd_strand]>]>], [<Connection <Location 2.end3[1,on_fwd_strand]>--sscrossover--<Location 0.end5[0,on_rev_strand]>]>, <Connection <Location 3.end3[0,on_fwd_strand]>--intrahelical--<Location 2.end5[0,on_fwd_strand]>]>], [<Connection <Location 1.end3[0,on_rev_strand]>--intrahelical--<Location 3.end5[0,on_fwd_strand]>]>, <Connection <Location 3.end3[0,on_fwd_strand]>--intrahelical--<Location 2.end5[0,on_fwd_strand]>]>]]\n"
+ ]
+ }
+ ],
+ "source": [
+ "print([i.children for i in model.children])\n",
+ "print([i.connections for i in model.children])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "2c710b99",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "s=model.children[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "550d0450",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'0'"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s.segname"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "3d2f102f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[(0, 0, 0.0),\n",
+ " (0, 0, 3.4),\n",
+ " (0, 0, 6.8),\n",
+ " (1, 0, 10.2),\n",
+ " (0, 0, 13.6),\n",
+ " (1, 0, 17.0),\n",
+ " (0, 0, 20.4)]"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "coordinate"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "0ba54a37",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.8.18"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}