test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import networkx as nx\n",
    "import plotly.io as pio\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "import igviz as ig\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>Cell_ID</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Cell_Type</th>\n",
       "      <th>Ace2</th>\n",
       "      <th>Adora2a</th>\n",
       "      <th>Aldh1l1</th>\n",
       "      <th>Amigo2</th>\n",
       "      <th>Ano3</th>\n",
       "      <th>Aqp4</th>\n",
       "      <th>...</th>\n",
       "      <th>Penk</th>\n",
       "      <th>Scg2</th>\n",
       "      <th>Sln</th>\n",
       "      <th>Sst</th>\n",
       "      <th>Tac1</th>\n",
       "      <th>Tac2</th>\n",
       "      <th>Th</th>\n",
       "      <th>Trh</th>\n",
       "      <th>Ucn3</th>\n",
       "      <th>Vgf</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>None</td>\n",
       "      <td>935.427246</td>\n",
       "      <td>2535.858258</td>\n",
       "      <td>None</td>\n",
       "      <td>-0.196646</td>\n",
       "      <td>-0.127793</td>\n",
       "      <td>-0.848176</td>\n",
       "      <td>-0.643967</td>\n",
       "      <td>-0.309448</td>\n",
       "      <td>0.321098</td>\n",
       "      <td>...</td>\n",
       "      <td>0.209571</td>\n",
       "      <td>-0.370390</td>\n",
       "      <td>-0.419159</td>\n",
       "      <td>0.125842</td>\n",
       "      <td>-0.306247</td>\n",
       "      <td>-0.042923</td>\n",
       "      <td>-0.188105</td>\n",
       "      <td>0.112193</td>\n",
       "      <td>-0.340421</td>\n",
       "      <td>-0.152851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>None</td>\n",
       "      <td>938.350560</td>\n",
       "      <td>2453.827185</td>\n",
       "      <td>None</td>\n",
       "      <td>-0.262087</td>\n",
       "      <td>-0.193582</td>\n",
       "      <td>-0.910324</td>\n",
       "      <td>-0.707148</td>\n",
       "      <td>-0.374318</td>\n",
       "      <td>0.958285</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.012169</td>\n",
       "      <td>-0.434953</td>\n",
       "      <td>-0.483476</td>\n",
       "      <td>0.230435</td>\n",
       "      <td>-0.371134</td>\n",
       "      <td>-0.109141</td>\n",
       "      <td>-0.253589</td>\n",
       "      <td>0.188663</td>\n",
       "      <td>-0.405135</td>\n",
       "      <td>-0.218513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>None</td>\n",
       "      <td>944.161206</td>\n",
       "      <td>2514.274329</td>\n",
       "      <td>None</td>\n",
       "      <td>-0.084652</td>\n",
       "      <td>-0.016211</td>\n",
       "      <td>1.593100</td>\n",
       "      <td>-0.529298</td>\n",
       "      <td>-0.196779</td>\n",
       "      <td>-0.663755</td>\n",
       "      <td>...</td>\n",
       "      <td>0.222952</td>\n",
       "      <td>-0.257357</td>\n",
       "      <td>-0.305835</td>\n",
       "      <td>0.426606</td>\n",
       "      <td>-0.193597</td>\n",
       "      <td>0.068152</td>\n",
       "      <td>-0.063028</td>\n",
       "      <td>0.443077</td>\n",
       "      <td>-0.227567</td>\n",
       "      <td>-0.041119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>None</td>\n",
       "      <td>942.020650</td>\n",
       "      <td>2392.668177</td>\n",
       "      <td>None</td>\n",
       "      <td>-0.530920</td>\n",
       "      <td>-0.469567</td>\n",
       "      <td>0.718321</td>\n",
       "      <td>-0.929519</td>\n",
       "      <td>-0.631435</td>\n",
       "      <td>-1.050051</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.346343</td>\n",
       "      <td>-0.685740</td>\n",
       "      <td>1.300830</td>\n",
       "      <td>-0.243558</td>\n",
       "      <td>0.480653</td>\n",
       "      <td>-0.105235</td>\n",
       "      <td>1.541595</td>\n",
       "      <td>-0.366553</td>\n",
       "      <td>-0.251640</td>\n",
       "      <td>-0.491896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>None</td>\n",
       "      <td>951.649350</td>\n",
       "      <td>2392.131835</td>\n",
       "      <td>None</td>\n",
       "      <td>-0.154489</td>\n",
       "      <td>-0.086315</td>\n",
       "      <td>-0.799595</td>\n",
       "      <td>-0.597400</td>\n",
       "      <td>-0.266178</td>\n",
       "      <td>-0.731331</td>\n",
       "      <td>...</td>\n",
       "      <td>0.050608</td>\n",
       "      <td>-0.326520</td>\n",
       "      <td>0.843952</td>\n",
       "      <td>0.164820</td>\n",
       "      <td>-0.263009</td>\n",
       "      <td>-0.002281</td>\n",
       "      <td>2.191446</td>\n",
       "      <td>0.028151</td>\n",
       "      <td>-0.296846</td>\n",
       "      <td>-0.111126</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",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>None</td>\n",
       "      <td>1696.175729</td>\n",
       "      <td>2765.694420</td>\n",
       "      <td>None</td>\n",
       "      <td>1.776708</td>\n",
       "      <td>-0.768905</td>\n",
       "      <td>-1.433067</td>\n",
       "      <td>0.177617</td>\n",
       "      <td>-0.936383</td>\n",
       "      <td>-1.369504</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.641411</td>\n",
       "      <td>-0.968731</td>\n",
       "      <td>2.106805</td>\n",
       "      <td>-0.535065</td>\n",
       "      <td>1.671731</td>\n",
       "      <td>-0.354325</td>\n",
       "      <td>-0.824510</td>\n",
       "      <td>-0.662322</td>\n",
       "      <td>0.064318</td>\n",
       "      <td>-0.792008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>None</td>\n",
       "      <td>1612.735269</td>\n",
       "      <td>2672.525827</td>\n",
       "      <td>None</td>\n",
       "      <td>2.382819</td>\n",
       "      <td>-0.364223</td>\n",
       "      <td>0.804347</td>\n",
       "      <td>1.854826</td>\n",
       "      <td>-0.537228</td>\n",
       "      <td>0.477488</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.232520</td>\n",
       "      <td>1.109034</td>\n",
       "      <td>-0.641717</td>\n",
       "      <td>-0.122663</td>\n",
       "      <td>-0.534180</td>\n",
       "      <td>-0.283393</td>\n",
       "      <td>-0.374052</td>\n",
       "      <td>-0.254121</td>\n",
       "      <td>-0.566727</td>\n",
       "      <td>-0.388088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>None</td>\n",
       "      <td>1615.408794</td>\n",
       "      <td>2615.949851</td>\n",
       "      <td>None</td>\n",
       "      <td>-0.004462</td>\n",
       "      <td>0.082418</td>\n",
       "      <td>2.300502</td>\n",
       "      <td>2.160774</td>\n",
       "      <td>-0.146797</td>\n",
       "      <td>-0.739581</td>\n",
       "      <td>...</td>\n",
       "      <td>0.399367</td>\n",
       "      <td>-0.223696</td>\n",
       "      <td>-0.285234</td>\n",
       "      <td>0.404401</td>\n",
       "      <td>-0.142759</td>\n",
       "      <td>0.189509</td>\n",
       "      <td>0.006315</td>\n",
       "      <td>0.820336</td>\n",
       "      <td>-0.185880</td>\n",
       "      <td>0.050799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>None</td>\n",
       "      <td>1670.871454</td>\n",
       "      <td>2609.363083</td>\n",
       "      <td>None</td>\n",
       "      <td>3.986632</td>\n",
       "      <td>-0.168161</td>\n",
       "      <td>-0.776926</td>\n",
       "      <td>-0.604358</td>\n",
       "      <td>-0.321670</td>\n",
       "      <td>-0.718665</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.051301</td>\n",
       "      <td>-0.373170</td>\n",
       "      <td>-0.414383</td>\n",
       "      <td>0.046175</td>\n",
       "      <td>-0.318965</td>\n",
       "      <td>0.182196</td>\n",
       "      <td>1.057627</td>\n",
       "      <td>0.045401</td>\n",
       "      <td>-0.347844</td>\n",
       "      <td>-0.189337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>None</td>\n",
       "      <td>1698.229603</td>\n",
       "      <td>2636.604141</td>\n",
       "      <td>None</td>\n",
       "      <td>-0.267716</td>\n",
       "      <td>-0.212189</td>\n",
       "      <td>-0.793153</td>\n",
       "      <td>1.014932</td>\n",
       "      <td>-0.358687</td>\n",
       "      <td>-0.737553</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.100666</td>\n",
       "      <td>-0.407835</td>\n",
       "      <td>-0.118154</td>\n",
       "      <td>-0.007641</td>\n",
       "      <td>-0.356106</td>\n",
       "      <td>-0.058177</td>\n",
       "      <td>-0.260828</td>\n",
       "      <td>-0.083278</td>\n",
       "      <td>-0.383666</td>\n",
       "      <td>-0.232398</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 164 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Cell_ID            X            Y Cell_Type      Ace2   Adora2a  \\\n",
       "0       None   935.427246  2535.858258      None -0.196646 -0.127793   \n",
       "1       None   938.350560  2453.827185      None -0.262087 -0.193582   \n",
       "2       None   944.161206  2514.274329      None -0.084652 -0.016211   \n",
       "3       None   942.020650  2392.668177      None -0.530920 -0.469567   \n",
       "4       None   951.649350  2392.131835      None -0.154489 -0.086315   \n",
       "...      ...          ...          ...       ...       ...       ...   \n",
       "1995    None  1696.175729  2765.694420      None  1.776708 -0.768905   \n",
       "1996    None  1612.735269  2672.525827      None  2.382819 -0.364223   \n",
       "1997    None  1615.408794  2615.949851      None -0.004462  0.082418   \n",
       "1998    None  1670.871454  2609.363083      None  3.986632 -0.168161   \n",
       "1999    None  1698.229603  2636.604141      None -0.267716 -0.212189   \n",
       "\n",
       "       Aldh1l1    Amigo2      Ano3      Aqp4  ...      Penk      Scg2  \\\n",
       "0    -0.848176 -0.643967 -0.309448  0.321098  ...  0.209571 -0.370390   \n",
       "1    -0.910324 -0.707148 -0.374318  0.958285  ... -0.012169 -0.434953   \n",
       "2     1.593100 -0.529298 -0.196779 -0.663755  ...  0.222952 -0.257357   \n",
       "3     0.718321 -0.929519 -0.631435 -1.050051  ... -0.346343 -0.685740   \n",
       "4    -0.799595 -0.597400 -0.266178 -0.731331  ...  0.050608 -0.326520   \n",
       "...        ...       ...       ...       ...  ...       ...       ...   \n",
       "1995 -1.433067  0.177617 -0.936383 -1.369504  ... -0.641411 -0.968731   \n",
       "1996  0.804347  1.854826 -0.537228  0.477488  ... -0.232520  1.109034   \n",
       "1997  2.300502  2.160774 -0.146797 -0.739581  ...  0.399367 -0.223696   \n",
       "1998 -0.776926 -0.604358 -0.321670 -0.718665  ... -0.051301 -0.373170   \n",
       "1999 -0.793153  1.014932 -0.358687 -0.737553  ... -0.100666 -0.407835   \n",
       "\n",
       "           Sln       Sst      Tac1      Tac2        Th       Trh      Ucn3  \\\n",
       "0    -0.419159  0.125842 -0.306247 -0.042923 -0.188105  0.112193 -0.340421   \n",
       "1    -0.483476  0.230435 -0.371134 -0.109141 -0.253589  0.188663 -0.405135   \n",
       "2    -0.305835  0.426606 -0.193597  0.068152 -0.063028  0.443077 -0.227567   \n",
       "3     1.300830 -0.243558  0.480653 -0.105235  1.541595 -0.366553 -0.251640   \n",
       "4     0.843952  0.164820 -0.263009 -0.002281  2.191446  0.028151 -0.296846   \n",
       "...        ...       ...       ...       ...       ...       ...       ...   \n",
       "1995  2.106805 -0.535065  1.671731 -0.354325 -0.824510 -0.662322  0.064318   \n",
       "1996 -0.641717 -0.122663 -0.534180 -0.283393 -0.374052 -0.254121 -0.566727   \n",
       "1997 -0.285234  0.404401 -0.142759  0.189509  0.006315  0.820336 -0.185880   \n",
       "1998 -0.414383  0.046175 -0.318965  0.182196  1.057627  0.045401 -0.347844   \n",
       "1999 -0.118154 -0.007641 -0.356106 -0.058177 -0.260828 -0.083278 -0.383666   \n",
       "\n",
       "           Vgf  \n",
       "0    -0.152851  \n",
       "1    -0.218513  \n",
       "2    -0.041119  \n",
       "3    -0.491896  \n",
       "4    -0.111126  \n",
       "...        ...  \n",
       "1995 -0.792008  \n",
       "1996 -0.388088  \n",
       "1997  0.050799  \n",
       "1998 -0.189337  \n",
       "1999 -0.232398  \n",
       "\n",
       "[2000 rows x 164 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merfish_counts_df = pd.read_csv(\"./data/MERFISH/counts.csv\")\n",
    "merfish_coords_df = pd.read_csv(\"./data/MERFISH/coord.csv\")\n",
    "merfish_df = merfish_counts_df.copy()\n",
    "\n",
    "numcells, numgenes = merfish_counts_df.shape\n",
    "numgenes = 45\n",
    "\n",
    "none_arr = [None]* len(merfish_counts_df)\n",
    "\n",
    "merfish_df.insert(0,'Cell_ID',none_arr )\n",
    "merfish_df.insert(1,'X', merfish_coords_df[\"X\"])\n",
    "merfish_df.insert(2,'Y', merfish_coords_df[\"Y\"])\n",
    "merfish_df.insert(3,'Cell_Type', none_arr)\n",
    "merfish_df = merfish_df[:2000]\n",
    "merfish_df.to_csv(\"data/MERFISH/merfish_dataframe.csv\", index=False)\n",
    "merfish_df.iloc[:,4:].to_csv(\"data/MERFISH/counts.csv\", index=False)\n",
    "merfish_coords_df[:2000].to_csv(\"data/MERFISH/coord.csv\", index=False)\n",
    "\n",
    "merfish_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\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>Cell_ID</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Cell_Type</th>\n",
       "      <th>4931431F19Rik</th>\n",
       "      <th>4932429P05Rik</th>\n",
       "      <th>Abca15</th>\n",
       "      <th>Abca9</th>\n",
       "      <th>Adcy4</th>\n",
       "      <th>Aldh3b2</th>\n",
       "      <th>...</th>\n",
       "      <th>calb1</th>\n",
       "      <th>gda</th>\n",
       "      <th>slc5a7</th>\n",
       "      <th>sema3e</th>\n",
       "      <th>mfge8</th>\n",
       "      <th>lyve1</th>\n",
       "      <th>loxl1</th>\n",
       "      <th>slco1c1</th>\n",
       "      <th>amigo2</th>\n",
       "      <th>kcnip</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>265.76</td>\n",
       "      <td>-231.14</td>\n",
       "      <td>neuron</td>\n",
       "      <td>1.83</td>\n",
       "      <td>1.52</td>\n",
       "      <td>2.41</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.28</td>\n",
       "      <td>1.95</td>\n",
       "      <td>...</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-1.32</td>\n",
       "      <td>-2.06</td>\n",
       "      <td>-1.32</td>\n",
       "      <td>0.19</td>\n",
       "      <td>-2.20</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>-1.40</td>\n",
       "      <td>2.51</td>\n",
       "      <td>0.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>290.48</td>\n",
       "      <td>-261.52</td>\n",
       "      <td>neuron</td>\n",
       "      <td>0.38</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.49</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.64</td>\n",
       "      <td>-2.47</td>\n",
       "      <td>-1.34</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.22</td>\n",
       "      <td>-1.46</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.88</td>\n",
       "      <td>2.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>257.12</td>\n",
       "      <td>-133.35</td>\n",
       "      <td>neuron</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.67</td>\n",
       "      <td>-0.29</td>\n",
       "      <td>-0.42</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.66</td>\n",
       "      <td>-0.78</td>\n",
       "      <td>-1.07</td>\n",
       "      <td>-2.09</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.32</td>\n",
       "      <td>-2.29</td>\n",
       "      <td>0.15</td>\n",
       "      <td>3.20</td>\n",
       "      <td>2.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>753.46</td>\n",
       "      <td>-261.14</td>\n",
       "      <td>neuron</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-1.27</td>\n",
       "      <td>-0.30</td>\n",
       "      <td>-0.52</td>\n",
       "      <td>-2.08</td>\n",
       "      <td>0.92</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.85</td>\n",
       "      <td>-1.16</td>\n",
       "      <td>-1.29</td>\n",
       "      <td>-0.57</td>\n",
       "      <td>0.99</td>\n",
       "      <td>-0.19</td>\n",
       "      <td>-1.49</td>\n",
       "      <td>0.65</td>\n",
       "      <td>3.04</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>700.01</td>\n",
       "      <td>-169.05</td>\n",
       "      <td>neuron</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.44</td>\n",
       "      <td>-1.05</td>\n",
       "      <td>0.48</td>\n",
       "      <td>-0.49</td>\n",
       "      <td>2.29</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.65</td>\n",
       "      <td>-0.97</td>\n",
       "      <td>-1.29</td>\n",
       "      <td>-1.77</td>\n",
       "      <td>1.09</td>\n",
       "      <td>-1.17</td>\n",
       "      <td>-2.11</td>\n",
       "      <td>0.36</td>\n",
       "      <td>2.47</td>\n",
       "      <td>1.83</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",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1592</th>\n",
       "      <td>1593</td>\n",
       "      <td>1129.06</td>\n",
       "      <td>-1669.57</td>\n",
       "      <td>neuron</td>\n",
       "      <td>-0.17</td>\n",
       "      <td>-0.50</td>\n",
       "      <td>1.03</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.48</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.79</td>\n",
       "      <td>-0.31</td>\n",
       "      <td>-3.45</td>\n",
       "      <td>-2.60</td>\n",
       "      <td>-1.13</td>\n",
       "      <td>-1.97</td>\n",
       "      <td>-0.82</td>\n",
       "      <td>-1.53</td>\n",
       "      <td>2.21</td>\n",
       "      <td>0.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1593</th>\n",
       "      <td>1594</td>\n",
       "      <td>1044.02</td>\n",
       "      <td>-1872.66</td>\n",
       "      <td>neuron</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.77</td>\n",
       "      <td>-2.34</td>\n",
       "      <td>-0.29</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.57</td>\n",
       "      <td>-0.33</td>\n",
       "      <td>-1.13</td>\n",
       "      <td>-0.68</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>-1.55</td>\n",
       "      <td>-0.43</td>\n",
       "      <td>-0.60</td>\n",
       "      <td>2.66</td>\n",
       "      <td>0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1594</th>\n",
       "      <td>1595</td>\n",
       "      <td>1388.76</td>\n",
       "      <td>-1880.47</td>\n",
       "      <td>neuron</td>\n",
       "      <td>-1.06</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>-0.33</td>\n",
       "      <td>-0.05</td>\n",
       "      <td>-0.26</td>\n",
       "      <td>-0.22</td>\n",
       "      <td>...</td>\n",
       "      <td>1.04</td>\n",
       "      <td>0.54</td>\n",
       "      <td>1.38</td>\n",
       "      <td>0.90</td>\n",
       "      <td>-0.41</td>\n",
       "      <td>-1.69</td>\n",
       "      <td>0.36</td>\n",
       "      <td>-0.49</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1595</th>\n",
       "      <td>1596</td>\n",
       "      <td>5172.85</td>\n",
       "      <td>-1340.96</td>\n",
       "      <td>neuron</td>\n",
       "      <td>-1.99</td>\n",
       "      <td>-0.25</td>\n",
       "      <td>1.34</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.95</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.28</td>\n",
       "      <td>-1.25</td>\n",
       "      <td>1.58</td>\n",
       "      <td>-2.68</td>\n",
       "      <td>-0.77</td>\n",
       "      <td>0.27</td>\n",
       "      <td>-0.60</td>\n",
       "      <td>-0.14</td>\n",
       "      <td>-2.66</td>\n",
       "      <td>0.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1596</th>\n",
       "      <td>1597</td>\n",
       "      <td>5220.60</td>\n",
       "      <td>-1523.37</td>\n",
       "      <td>neuron</td>\n",
       "      <td>-1.69</td>\n",
       "      <td>0.94</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>-0.21</td>\n",
       "      <td>-0.82</td>\n",
       "      <td>0.36</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.28</td>\n",
       "      <td>-2.20</td>\n",
       "      <td>0.24</td>\n",
       "      <td>-1.44</td>\n",
       "      <td>0.16</td>\n",
       "      <td>-1.36</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-0.61</td>\n",
       "      <td>-0.14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1597 rows × 129 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Cell_ID        X        Y Cell_Type  4931431F19Rik  4932429P05Rik  \\\n",
       "0           1   265.76  -231.14    neuron           1.83           1.52   \n",
       "1           2   290.48  -261.52    neuron           0.38          -0.04   \n",
       "2           3   257.12  -133.35    neuron           0.82           0.12   \n",
       "3           4   753.46  -261.14    neuron           0.04          -1.27   \n",
       "4           5   700.01  -169.05    neuron           0.52           0.44   \n",
       "...       ...      ...      ...       ...            ...            ...   \n",
       "1592     1593  1129.06 -1669.57    neuron          -0.17          -0.50   \n",
       "1593     1594  1044.02 -1872.66    neuron           0.20           0.95   \n",
       "1594     1595  1388.76 -1880.47    neuron          -1.06          -0.18   \n",
       "1595     1596  5172.85 -1340.96    neuron          -1.99          -0.25   \n",
       "1596     1597  5220.60 -1523.37    neuron          -1.69           0.94   \n",
       "\n",
       "      Abca15  Abca9  Adcy4  Aldh3b2  ...  calb1   gda  slc5a7  sema3e  mfge8  \\\n",
       "0       2.41  -0.02  -0.28     1.95  ...   0.12 -1.32   -2.06   -1.32   0.19   \n",
       "1       0.59   0.03   0.93     0.49  ...  -1.60 -0.64   -2.47   -1.34   0.00   \n",
       "2       0.67  -0.29  -0.42    -0.04  ...  -0.66 -0.78   -1.07   -2.09   0.09   \n",
       "3      -0.30  -0.52  -2.08     0.92  ...  -0.85 -1.16   -1.29   -0.57   0.99   \n",
       "4      -1.05   0.48  -0.49     2.29  ...  -0.65 -0.97   -1.29   -1.77   1.09   \n",
       "...      ...    ...    ...      ...  ...    ...   ...     ...     ...    ...   \n",
       "1592    1.03   0.90   0.23     0.48  ...  -0.79 -0.31   -3.45   -2.60  -1.13   \n",
       "1593    0.57   0.77  -2.34    -0.29  ...  -0.57 -0.33   -1.13   -0.68  -0.06   \n",
       "1594   -0.33  -0.05  -0.26    -0.22  ...   1.04  0.54    1.38    0.90  -0.41   \n",
       "1595    1.34   0.00  -0.01     0.95  ...  -1.28 -1.25    1.58   -2.68  -0.77   \n",
       "1596   -0.12  -0.21  -0.82     0.36  ...  -0.28 -2.20    0.24   -1.44   0.16   \n",
       "\n",
       "      lyve1  loxl1  slco1c1  amigo2  kcnip  \n",
       "0     -2.20  -1.54    -1.40    2.51   0.60  \n",
       "1      0.22  -1.46     0.22    1.88   2.05  \n",
       "2      0.32  -2.29     0.15    3.20   2.30  \n",
       "3     -0.19  -1.49     0.65    3.04   2.00  \n",
       "4     -1.17  -2.11     0.36    2.47   1.83  \n",
       "...     ...    ...      ...     ...    ...  \n",
       "1592  -1.97  -0.82    -1.53    2.21   0.54  \n",
       "1593  -1.55  -0.43    -0.60    2.66   0.23  \n",
       "1594  -1.69   0.36    -0.49    0.80   0.39  \n",
       "1595   0.27  -0.60    -0.14   -2.66   0.37  \n",
       "1596  -1.36  -0.04     0.04   -0.61  -0.14  \n",
       "\n",
       "[1597 rows x 129 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seqfish_df = pd.read_csv(\"./data/seqFISH/seqfish_dataframe.csv\")\n",
    "seqfish_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cell_ID</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Cell_Type</th>\n",
       "      <th>Ace2</th>\n",
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       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>938.350560</td>\n",
       "      <td>2453.827185</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.262087</td>\n",
       "      <td>-0.193582</td>\n",
       "      <td>-0.910324</td>\n",
       "      <td>-0.707148</td>\n",
       "      <td>-0.374318</td>\n",
       "      <td>0.958285</td>\n",
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       "      <td>-0.483476</td>\n",
       "      <td>0.230435</td>\n",
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       "      <td>-0.109141</td>\n",
       "      <td>-0.253589</td>\n",
       "      <td>0.188663</td>\n",
       "      <td>-0.405135</td>\n",
       "      <td>-0.218513</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>944.161206</td>\n",
       "      <td>2514.274329</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.084652</td>\n",
       "      <td>-0.016211</td>\n",
       "      <td>1.593100</td>\n",
       "      <td>-0.529298</td>\n",
       "      <td>-0.196779</td>\n",
       "      <td>-0.663755</td>\n",
       "      <td>...</td>\n",
       "      <td>0.222952</td>\n",
       "      <td>-0.257357</td>\n",
       "      <td>-0.305835</td>\n",
       "      <td>0.426606</td>\n",
       "      <td>-0.193597</td>\n",
       "      <td>0.068152</td>\n",
       "      <td>-0.063028</td>\n",
       "      <td>0.443077</td>\n",
       "      <td>-0.227567</td>\n",
       "      <td>-0.041119</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>942.020650</td>\n",
       "      <td>2392.668177</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.530920</td>\n",
       "      <td>-0.469567</td>\n",
       "      <td>0.718321</td>\n",
       "      <td>-0.929519</td>\n",
       "      <td>-0.631435</td>\n",
       "      <td>-1.050051</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.346343</td>\n",
       "      <td>-0.685740</td>\n",
       "      <td>1.300830</td>\n",
       "      <td>-0.243558</td>\n",
       "      <td>0.480653</td>\n",
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       "      <td>1.541595</td>\n",
       "      <td>-0.366553</td>\n",
       "      <td>-0.251640</td>\n",
       "      <td>-0.491896</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>0.164820</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1696.175729</td>\n",
       "      <td>2765.694420</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.776708</td>\n",
       "      <td>-0.768905</td>\n",
       "      <td>-1.433067</td>\n",
       "      <td>0.177617</td>\n",
       "      <td>-0.936383</td>\n",
       "      <td>-1.369504</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.641411</td>\n",
       "      <td>-0.968731</td>\n",
       "      <td>2.106805</td>\n",
       "      <td>-0.535065</td>\n",
       "      <td>1.671731</td>\n",
       "      <td>-0.354325</td>\n",
       "      <td>-0.824510</td>\n",
       "      <td>-0.662322</td>\n",
       "      <td>0.064318</td>\n",
       "      <td>-0.792008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1612.735269</td>\n",
       "      <td>2672.525827</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.382819</td>\n",
       "      <td>-0.364223</td>\n",
       "      <td>0.804347</td>\n",
       "      <td>1.854826</td>\n",
       "      <td>-0.537228</td>\n",
       "      <td>0.477488</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.232520</td>\n",
       "      <td>1.109034</td>\n",
       "      <td>-0.641717</td>\n",
       "      <td>-0.122663</td>\n",
       "      <td>-0.534180</td>\n",
       "      <td>-0.283393</td>\n",
       "      <td>-0.374052</td>\n",
       "      <td>-0.254121</td>\n",
       "      <td>-0.566727</td>\n",
       "      <td>-0.388088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1615.408794</td>\n",
       "      <td>2615.949851</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.004462</td>\n",
       "      <td>0.082418</td>\n",
       "      <td>2.300502</td>\n",
       "      <td>2.160774</td>\n",
       "      <td>-0.146797</td>\n",
       "      <td>-0.739581</td>\n",
       "      <td>...</td>\n",
       "      <td>0.399367</td>\n",
       "      <td>-0.223696</td>\n",
       "      <td>-0.285234</td>\n",
       "      <td>0.404401</td>\n",
       "      <td>-0.142759</td>\n",
       "      <td>0.189509</td>\n",
       "      <td>0.006315</td>\n",
       "      <td>0.820336</td>\n",
       "      <td>-0.185880</td>\n",
       "      <td>0.050799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1670.871454</td>\n",
       "      <td>2609.363083</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.986632</td>\n",
       "      <td>-0.168161</td>\n",
       "      <td>-0.776926</td>\n",
       "      <td>-0.604358</td>\n",
       "      <td>-0.321670</td>\n",
       "      <td>-0.718665</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.051301</td>\n",
       "      <td>-0.373170</td>\n",
       "      <td>-0.414383</td>\n",
       "      <td>0.046175</td>\n",
       "      <td>-0.318965</td>\n",
       "      <td>0.182196</td>\n",
       "      <td>1.057627</td>\n",
       "      <td>0.045401</td>\n",
       "      <td>-0.347844</td>\n",
       "      <td>-0.189337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1698.229603</td>\n",
       "      <td>2636.604141</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.267716</td>\n",
       "      <td>-0.212189</td>\n",
       "      <td>-0.793153</td>\n",
       "      <td>1.014932</td>\n",
       "      <td>-0.358687</td>\n",
       "      <td>-0.737553</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.100666</td>\n",
       "      <td>-0.407835</td>\n",
       "      <td>-0.118154</td>\n",
       "      <td>-0.007641</td>\n",
       "      <td>-0.356106</td>\n",
       "      <td>-0.058177</td>\n",
       "      <td>-0.260828</td>\n",
       "      <td>-0.083278</td>\n",
       "      <td>-0.383666</td>\n",
       "      <td>-0.232398</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 164 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Cell_ID            X            Y  Cell_Type      Ace2   Adora2a  \\\n",
       "0         NaN   935.427246  2535.858258        NaN -0.196646 -0.127793   \n",
       "1         NaN   938.350560  2453.827185        NaN -0.262087 -0.193582   \n",
       "2         NaN   944.161206  2514.274329        NaN -0.084652 -0.016211   \n",
       "3         NaN   942.020650  2392.668177        NaN -0.530920 -0.469567   \n",
       "4         NaN   951.649350  2392.131835        NaN -0.154489 -0.086315   \n",
       "...       ...          ...          ...        ...       ...       ...   \n",
       "1995      NaN  1696.175729  2765.694420        NaN  1.776708 -0.768905   \n",
       "1996      NaN  1612.735269  2672.525827        NaN  2.382819 -0.364223   \n",
       "1997      NaN  1615.408794  2615.949851        NaN -0.004462  0.082418   \n",
       "1998      NaN  1670.871454  2609.363083        NaN  3.986632 -0.168161   \n",
       "1999      NaN  1698.229603  2636.604141        NaN -0.267716 -0.212189   \n",
       "\n",
       "       Aldh1l1    Amigo2      Ano3      Aqp4  ...      Penk      Scg2  \\\n",
       "0    -0.848176 -0.643967 -0.309448  0.321098  ...  0.209571 -0.370390   \n",
       "1    -0.910324 -0.707148 -0.374318  0.958285  ... -0.012169 -0.434953   \n",
       "2     1.593100 -0.529298 -0.196779 -0.663755  ...  0.222952 -0.257357   \n",
       "3     0.718321 -0.929519 -0.631435 -1.050051  ... -0.346343 -0.685740   \n",
       "4    -0.799595 -0.597400 -0.266178 -0.731331  ...  0.050608 -0.326520   \n",
       "...        ...       ...       ...       ...  ...       ...       ...   \n",
       "1995 -1.433067  0.177617 -0.936383 -1.369504  ... -0.641411 -0.968731   \n",
       "1996  0.804347  1.854826 -0.537228  0.477488  ... -0.232520  1.109034   \n",
       "1997  2.300502  2.160774 -0.146797 -0.739581  ...  0.399367 -0.223696   \n",
       "1998 -0.776926 -0.604358 -0.321670 -0.718665  ... -0.051301 -0.373170   \n",
       "1999 -0.793153  1.014932 -0.358687 -0.737553  ... -0.100666 -0.407835   \n",
       "\n",
       "           Sln       Sst      Tac1      Tac2        Th       Trh      Ucn3  \\\n",
       "0    -0.419159  0.125842 -0.306247 -0.042923 -0.188105  0.112193 -0.340421   \n",
       "1    -0.483476  0.230435 -0.371134 -0.109141 -0.253589  0.188663 -0.405135   \n",
       "2    -0.305835  0.426606 -0.193597  0.068152 -0.063028  0.443077 -0.227567   \n",
       "3     1.300830 -0.243558  0.480653 -0.105235  1.541595 -0.366553 -0.251640   \n",
       "4     0.843952  0.164820 -0.263009 -0.002281  2.191446  0.028151 -0.296846   \n",
       "...        ...       ...       ...       ...       ...       ...       ...   \n",
       "1995  2.106805 -0.535065  1.671731 -0.354325 -0.824510 -0.662322  0.064318   \n",
       "1996 -0.641717 -0.122663 -0.534180 -0.283393 -0.374052 -0.254121 -0.566727   \n",
       "1997 -0.285234  0.404401 -0.142759  0.189509  0.006315  0.820336 -0.185880   \n",
       "1998 -0.414383  0.046175 -0.318965  0.182196  1.057627  0.045401 -0.347844   \n",
       "1999 -0.118154 -0.007641 -0.356106 -0.058177 -0.260828 -0.083278 -0.383666   \n",
       "\n",
       "           Vgf  \n",
       "0    -0.152851  \n",
       "1    -0.218513  \n",
       "2    -0.041119  \n",
       "3    -0.491896  \n",
       "4    -0.111126  \n",
       "...        ...  \n",
       "1995 -0.792008  \n",
       "1996 -0.388088  \n",
       "1997  0.050799  \n",
       "1998 -0.189337  \n",
       "1999 -0.232398  \n",
       "\n",
       "[2000 rows x 164 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merfish_df = pd.read_csv(\"./data/MERFISH/merfish_dataframe.csv\")\n",
    "merfish_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</table>\n",
       "<p>1600 rows × 1600 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      0  1  2  3  4  5  6  7  8  9  ...  1590  1591  1592  1593  1594  1595  \\\n",
       "0     0  0  1  0  0  1  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     0   \n",
       "2     1  0  0  0  0  0  0  0  1  0  ...     0     0     0     0     0     0   \n",
       "3     0  0  0  0  1  0  0  0  0  0  ...     0     0     0     0     0     0   \n",
       "4     0  0  0  1  0  0  0  0  0  0  ...     0     0     0     0     0     0   \n",
       "...  .. .. .. .. .. .. .. .. .. ..  ...   ...   ...   ...   ...   ...   ...   \n",
       "1595  0  0  0  0  0  0  0  0  0  0  ...     1     0     1     0     1     0   \n",
       "1596  0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     1     0   \n",
       "1597  0  0  0  0  0  0  0  0  0  0  ...     0     0     0     1     0     0   \n",
       "1598  0  0  0  0  0  0  0  0  0  0  ...     1     0     0     0     1     1   \n",
       "1599  0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0     0   \n",
       "\n",
       "      1596  1597  1598  1599  \n",
       "0        0     0     0     0  \n",
       "1        0     0     0     0  \n",
       "2        0     0     0     0  \n",
       "3        0     0     0     0  \n",
       "4        0     0     0     0  \n",
       "...    ...   ...   ...   ...  \n",
       "1595     0     0     1     0  \n",
       "1596     0     0     1     1  \n",
       "1597     0     0     0     0  \n",
       "1598     1     0     0     0  \n",
       "1599     1     0     0     0  \n",
       "\n",
       "[1600 rows x 1600 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merfish_adj = pd.read_csv(\"./data/MERFISH/adj.csv\")\n",
    "merfish_adj\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preprocessing scMultiSim Simulated Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "locations = pd.read_csv(\"./data/scMultiSim/coord.csv\",index_col=None).values\n",
    "distances_from_origin = np.linalg.norm(locations, axis=1)\n",
    "new_indices = np.argsort(distances_from_origin)\n",
    "permutation_dict = {i:new_indices[i] for i in range(len(new_indices))}\n",
    "np.save(\"./data/scMultiSim/permutation_mapping.npy\", permutation_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cell_ID</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Cell_Type</th>\n",
       "      <th>gene1</th>\n",
       "      <th>gene2</th>\n",
       "      <th>gene3</th>\n",
       "      <th>gene4</th>\n",
       "      <th>gene5</th>\n",
       "      <th>gene6</th>\n",
       "      <th>...</th>\n",
       "      <th>gene111</th>\n",
       "      <th>gene112</th>\n",
       "      <th>gene113</th>\n",
       "      <th>gene114</th>\n",
       "      <th>gene115</th>\n",
       "      <th>gene116</th>\n",
       "      <th>gene117</th>\n",
       "      <th>gene118</th>\n",
       "      <th>gene119</th>\n",
       "      <th>gene120</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cell1</th>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>2_1_5</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>2.397895</td>\n",
       "      <td>5.446737</td>\n",
       "      <td>2.944439</td>\n",
       "      <td>1.945910</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>5.429346</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>1.609438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell2</th>\n",
       "      <td>2</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>2_1_5</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>4.430817</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.639057</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>...</td>\n",
       "      <td>2.397895</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.639057</td>\n",
       "      <td>5.241747</td>\n",
       "      <td>2.708050</td>\n",
       "      <td>1.945910</td>\n",
       "      <td>2.079442</td>\n",
       "      <td>5.198497</td>\n",
       "      <td>1.791759</td>\n",
       "      <td>0.693147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell3</th>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>28</td>\n",
       "      <td>2_1_5</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>3.583519</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.302585</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.302585</td>\n",
       "      <td>...</td>\n",
       "      <td>2.197225</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>2.708050</td>\n",
       "      <td>5.627621</td>\n",
       "      <td>2.995732</td>\n",
       "      <td>2.079442</td>\n",
       "      <td>1.791759</td>\n",
       "      <td>4.955827</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>1.098612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell4</th>\n",
       "      <td>4</td>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>2_1_5</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>4.454347</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.945910</td>\n",
       "      <td>...</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>2.397895</td>\n",
       "      <td>5.590987</td>\n",
       "      <td>3.218876</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>2.302585</td>\n",
       "      <td>5.811141</td>\n",
       "      <td>1.791759</td>\n",
       "      <td>1.386294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell5</th>\n",
       "      <td>5</td>\n",
       "      <td>17</td>\n",
       "      <td>19</td>\n",
       "      <td>2_1_5</td>\n",
       "      <td>2.079442</td>\n",
       "      <td>4.290459</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.555348</td>\n",
       "      <td>2.197225</td>\n",
       "      <td>...</td>\n",
       "      <td>2.564949</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>5.765191</td>\n",
       "      <td>3.044522</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>5.808142</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>1.386294</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",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell1196</th>\n",
       "      <td>1196</td>\n",
       "      <td>39</td>\n",
       "      <td>41</td>\n",
       "      <td>2_1_1</td>\n",
       "      <td>1.945910</td>\n",
       "      <td>2.995732</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.397895</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>...</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>2.639057</td>\n",
       "      <td>7.385231</td>\n",
       "      <td>2.833213</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>5.556828</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>0.693147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell1197</th>\n",
       "      <td>1197</td>\n",
       "      <td>35</td>\n",
       "      <td>12</td>\n",
       "      <td>2_1_1</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>3.555348</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.564949</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>2.079442</td>\n",
       "      <td>...</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>2.890372</td>\n",
       "      <td>6.523562</td>\n",
       "      <td>3.258097</td>\n",
       "      <td>2.079442</td>\n",
       "      <td>1.791759</td>\n",
       "      <td>5.170484</td>\n",
       "      <td>2.197225</td>\n",
       "      <td>1.098612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell1198</th>\n",
       "      <td>1198</td>\n",
       "      <td>30</td>\n",
       "      <td>43</td>\n",
       "      <td>2_1_1</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>3.526361</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.564949</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>...</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.044522</td>\n",
       "      <td>5.811141</td>\n",
       "      <td>2.564949</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>5.641907</td>\n",
       "      <td>1.945910</td>\n",
       "      <td>1.098612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell1199</th>\n",
       "      <td>1199</td>\n",
       "      <td>5</td>\n",
       "      <td>33</td>\n",
       "      <td>2_1_1</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>3.178054</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.708050</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.945910</td>\n",
       "      <td>2.708050</td>\n",
       "      <td>6.469250</td>\n",
       "      <td>2.639057</td>\n",
       "      <td>2.302585</td>\n",
       "      <td>2.302585</td>\n",
       "      <td>5.866468</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell1200</th>\n",
       "      <td>1200</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>2_1_1</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>3.295837</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.135494</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>2.564949</td>\n",
       "      <td>6.232448</td>\n",
       "      <td>3.135494</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>2.484907</td>\n",
       "      <td>5.225747</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>0.693147</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1200 rows × 124 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Cell_ID   X   Y Cell_Type     gene1     gene2  gene3     gene4  \\\n",
       "cell1           1  25  25     2_1_5  2.639057  3.951244    0.0  1.386294   \n",
       "cell2           2  29  29     2_1_5  1.098612  4.430817    0.0  2.639057   \n",
       "cell3           3  27  28     2_1_5  1.609438  3.583519    0.0  2.302585   \n",
       "cell4           4  15  16     2_1_5  0.693147  4.454347    0.0  1.609438   \n",
       "cell5           5  17  19     2_1_5  2.079442  4.290459    0.0  1.098612   \n",
       "...           ...  ..  ..       ...       ...       ...    ...       ...   \n",
       "cell1196     1196  39  41     2_1_1  1.945910  2.995732    0.0  2.397895   \n",
       "cell1197     1197  35  12     2_1_1  1.609438  3.555348    0.0  2.564949   \n",
       "cell1198     1198  30  43     2_1_1  0.693147  3.526361    0.0  2.564949   \n",
       "cell1199     1199   5  33     2_1_1  1.386294  3.178054    0.0  2.708050   \n",
       "cell1200     1200   3   5     2_1_1  1.609438  3.295837    0.0  3.135494   \n",
       "\n",
       "             gene5     gene6  ...   gene111   gene112   gene113   gene114  \\\n",
       "cell1     0.000000  0.000000  ...  1.609438  0.693147  2.397895  5.446737   \n",
       "cell2     0.000000  0.693147  ...  2.397895  0.000000  2.639057  5.241747   \n",
       "cell3     0.000000  2.302585  ...  2.197225  1.386294  2.708050  5.627621   \n",
       "cell4     0.000000  1.945910  ...  1.386294  1.609438  2.397895  5.590987   \n",
       "cell5     3.555348  2.197225  ...  2.564949  1.098612  1.386294  5.765191   \n",
       "...            ...       ...  ...       ...       ...       ...       ...   \n",
       "cell1196  0.000000  1.386294  ...  0.693147  0.693147  2.639057  7.385231   \n",
       "cell1197  1.098612  2.079442  ...  1.609438  1.386294  2.890372  6.523562   \n",
       "cell1198  0.693147  1.098612  ...  1.609438  1.098612  3.044522  5.811141   \n",
       "cell1199  0.000000  0.693147  ...  0.000000  1.945910  2.708050  6.469250   \n",
       "cell1200  0.000000  0.000000  ...  1.098612  0.693147  2.564949  6.232448   \n",
       "\n",
       "           gene115   gene116   gene117   gene118   gene119   gene120  \n",
       "cell1     2.944439  1.945910  1.386294  5.429346  1.098612  1.609438  \n",
       "cell2     2.708050  1.945910  2.079442  5.198497  1.791759  0.693147  \n",
       "cell3     2.995732  2.079442  1.791759  4.955827  1.098612  1.098612  \n",
       "cell4     3.218876  1.609438  2.302585  5.811141  1.791759  1.386294  \n",
       "cell5     3.044522  0.693147  1.609438  5.808142  0.693147  1.386294  \n",
       "...            ...       ...       ...       ...       ...       ...  \n",
       "cell1196  2.833213  1.386294  1.098612  5.556828  1.386294  0.693147  \n",
       "cell1197  3.258097  2.079442  1.791759  5.170484  2.197225  1.098612  \n",
       "cell1198  2.564949  1.609438  1.609438  5.641907  1.945910  1.098612  \n",
       "cell1199  2.639057  2.302585  2.302585  5.866468  1.609438  0.000000  \n",
       "cell1200  3.135494  0.693147  2.484907  5.225747  1.609438  0.693147  \n",
       "\n",
       "[1200 rows x 124 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "multisim_name = \"scMultiSim_final\"\n",
    "scmultisim_counts = pd.read_csv(f\"./data/{multisim_name}/simulated/rna.csv\").T\n",
    "scmultisim_counts.columns = [f\"gene{x+1}\" for x in scmultisim_counts.columns]\n",
    "counts = np.sum(scmultisim_counts.values, axis=0)\n",
    "# scmultisim_normalizedcounts = np.log((scmultisim_counts.div(scmultisim_counts.sum(axis=1), axis=0) * 1000)+1)\n",
    "# scmultisim_normalizedcounts = np.log(scmultisim_counts+1).iloc[:, counts>1000]\n",
    "scmultisim_normalizedcounts = np.log(scmultisim_counts+1)\n",
    "# scmultisim_normalizedcounts = scmultisim_counts\n",
    "\n",
    "# print(len(counts[counts>1000]))\n",
    "\n",
    "scmultisim_locations = pd.read_csv(f\"./data/{multisim_name}/simulated/cci_locs.csv\")\n",
    "scmultisim_cellinfo = pd.read_csv(f\"./data/{multisim_name}/simulated/cells.csv\")\n",
    "scmultisim_neighbors = pd.read_csv(f\"./data/{multisim_name}/simulated/neighbors.csv\")\n",
    "\n",
    "scmultisim_df = scmultisim_normalizedcounts.copy()\n",
    "\n",
    "\n",
    "\n",
    "scmultisim_df.insert(0,'X', scmultisim_locations[\"x\"].tolist())\n",
    "scmultisim_df.insert(1,'Y', scmultisim_locations[\"y\"].tolist())\n",
    "scmultisim_df.insert(2,'Cell_Type', scmultisim_cellinfo[\"cell.type\"].tolist())\n",
    "\n",
    "# permute based on distances:\n",
    "# scmultisim_df = scmultisim_df.iloc[new_indices, :]\n",
    "\n",
    "scmultisim_df.insert(0,'Cell_ID', range(1, len(scmultisim_df)+1))\n",
    "\n",
    "scmultisim_df.to_csv(f\"./data/{multisim_name}/scmultisim_dataframe.csv\", index=False)\n",
    "scmultisim_df.iloc[:,4:].to_csv(f\"./data/{multisim_name}/counts.csv\", index=False)\n",
    "scmultisim_df.iloc[:,1:3].to_csv(f\"./data/{multisim_name}/coord.csv\", index=False)\n",
    "\n",
    "scmultisim_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
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       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from src.visualize import visualize_celllevel_graph\n",
    "import sys\n",
    "sys.path.append('./src/')\n",
    "sys.path.append('./src/submodules/CeSpGRN/src/')\n",
    "from src.preprocessing import construct_celllevel_graph\n",
    "\n",
    "\n",
    "celllevel_adj, edges = construct_celllevel_graph(scmultisim_df, 4, get_edges=True)\n",
    "\n",
    "sim_fig = visualize_celllevel_graph(scmultisim_df, gene=\"Cell_Type\",title=\"\",  publication=True)\n",
    "sim_fig.update_layout(\n",
    "    plot_bgcolor=\"white\"\n",
    ")\n",
    "sim_fig.update_xaxes(showline=True, linewidth=1, linecolor='black', mirror=False, ticks='outside')\n",
    "sim_fig.update_yaxes(showline=True, linewidth=1, linecolor='black', mirror=False,ticks='outside')\n",
    "sim_fig.update_coloraxes(showscale=False)\n",
    "sim_fig.update_traces(marker=dict(color='gray'))\n",
    "sim_fig.add_trace(\n",
    "    go.Scatter(\n",
    "    x=edge_x, y=edge_y,\n",
    "    line=dict(width=0.5, color='gray'),\n",
    "    hoverinfo='none',\n",
    "    mode='lines')\n",
    ")\n",
    "sim_fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_3171696/639182730.py:20: DeprecationWarning: elementwise comparison failed; this will raise an error in the future.\n",
      "  indices  = np.argwhere(candidate_genes == selected_lrs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'gene11': 0,\n",
       " 'gene111': 1,\n",
       " 'gene112': 2,\n",
       " 'gene12': 3,\n",
       " 'gene13': 4,\n",
       " 'gene14': 5,\n",
       " 'gene61': 6,\n",
       " 'gene62': 7,\n",
       " 'gene63': 8,\n",
       " 'gene64': 9,\n",
       " 'gene71': 10,\n",
       " 'gene72': 11,\n",
       " 'gene73': 12,\n",
       " 'gene74': 13,\n",
       " 'gene1': 14,\n",
       " 'gene2': 15,\n",
       " 'gene21': 16,\n",
       " 'gene22': 17,\n",
       " 'gene23': 18,\n",
       " 'gene24': 19,\n",
       " 'gene3': 20,\n",
       " 'gene31': 21,\n",
       " 'gene4': 22,\n",
       " 'gene5': 23,\n",
       " 'gene6': 24,\n",
       " 'gene7': 25,\n",
       " 'gene8': 26,\n",
       " 'gene9': 27,\n",
       " 'gene80': 28,\n",
       " 'gene78': 33,\n",
       " 'gene33': 34,\n",
       " 'gene65': 35,\n",
       " 'gene89': 36,\n",
       " 'gene103': 37,\n",
       " 'gene28': 38,\n",
       " 'gene93': 40,\n",
       " 'gene48': 41,\n",
       " 'gene35': 42,\n",
       " 'gene109': 43,\n",
       " 'gene32': 44}"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import random\n",
    "# import os\n",
    "# num_genespercell = 45\n",
    "\n",
    "# data_df = scmultisim_df.copy()\n",
    "\n",
    "\n",
    "\n",
    "# sample_counts = data_df.drop([\"Cell_ID\", \"X\", \"Y\", \"Cell_Type\"], axis = 1)\n",
    "# candidate_genes = sample_counts.columns.to_numpy()\n",
    "# scmultisim_lrs = pd.read_csv(\"./data/scMultiSim/simulated/cci_gt.csv\")[[\"ligand\", \"receptor\"]]\n",
    "# scmultisim_lrs[\"ligand\"] = scmultisim_lrs[\"ligand\"]\n",
    "# scmultisim_lrs[\"receptor\"] = scmultisim_lrs[\"receptor\"]\n",
    "# selected_ligands = np.unique(scmultisim_lrs[\"ligand\"])\n",
    "# selected_receptors = np.unique(scmultisim_lrs[\"receptor\"])\n",
    "# selected_lrs = np.concatenate((selected_ligands,selected_receptors),axis=0)\n",
    "\n",
    "\n",
    "# num_genesleft = num_genespercell - len(selected_ligands) - len(selected_receptors)\n",
    "# indices  = np.argwhere(candidate_genes == selected_lrs)\n",
    "# candidate_genesleft = np.delete(candidate_genes, indices)\n",
    "# selected_randomgenes = random.sample(set(candidate_genesleft), num_genesleft)\n",
    "\n",
    "# selected_genes = np.concatenate((selected_lrs, selected_randomgenes),axis=0)\n",
    "\n",
    "\n",
    "# new_columns = [\"Cell_ID\", \"X\", \"Y\", \"Cell_Type\"] + list(selected_genes)\n",
    "# selected_df = data_df[new_columns]\n",
    "# lr2id = {gene:list(selected_df.columns).index(gene)-4 for gene in selected_genes}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       ...,\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0]])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adj_df = pd.DataFrame(np.load(\"./out/scmultisim/1_preprocessing_output/celllevel_adjacencymatrix.npy\")).astype(int).values\n",
    "adj_df\n",
    "\n",
    "\n",
    "# adj_df.to_csv(\"./data/scMultiSim/adj.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "scmultisim_normalizedcounts.to_csv(\"./data/scMultiSim/counts.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "scmultisim_locations.to_csv(\"./data/scMultiSim/coord.csv\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'adj_df' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn [6], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m old \u001b[39m=\u001b[39m adj_df\u001b[39m.\u001b[39mvalues\n\u001b[1;32m      2\u001b[0m adj_matrix \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39mzeros(old\u001b[39m.\u001b[39mshape)\n\u001b[1;32m      3\u001b[0m \u001b[39mfor\u001b[39;00m i \u001b[39min\u001b[39;00m \u001b[39mrange\u001b[39m(\u001b[39mlen\u001b[39m(old)):\n",
      "\u001b[0;31mNameError\u001b[0m: name 'adj_df' is not defined"
     ]
    }
   ],
   "source": [
    "old = adj_df.values\n",
    "adj_matrix = np.zeros(old.shape)\n",
    "for i in range(len(old)):\n",
    "    for j in range(len(old)):\n",
    "        if old[i][j] == 1:\n",
    "            adj_matrix[i][j] = 1\n",
    "            adj_matrix[j][i] = 1\n",
    "        \n",
    "adj_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(adj_df == adj_matrix).all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "adh = pd.DataFrame(np.load(\"./out/merfish/1_preprocessing_output/celllevel_adjacencymatrix.npy\"))\n",
    "adh.to_csv(\"./data/MERFISH/adj.csv\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"./data/scMultiSim_final/scmultisim_dataframe.csv\")\n",
    "neighbors = pd.read_csv(\"./data/scMultiSim_final/simulated/neighbors.csv\")\n",
    "gt = pd.read_csv(\"./data/scMultiSim_final/simulated/cci_gt.csv\").iloc[:,-2:]\n",
    "combined_ctgt = gt[\"ct1\"].astype(str) + \"|\" + gt[\"ct2\"].astype(str)\n",
    "gt_set = set(combined_ctgt)\n",
    "\n",
    "scmultisim_adj = np.zeros(shape=(len(df),len(df)))\n",
    "\n",
    "edge_list = []\n",
    "\n",
    "edge_x = []\n",
    "edge_y = []\n",
    "\n",
    "for i in range(len(df)):\n",
    "    cell1_row = df.iloc[i]\n",
    "    cell1_neighbors = list(neighbors.iloc[i][neighbors.iloc[i].notnull()].astype(int))\n",
    "    cell1_type = cell1_row[\"Cell_Type\"].split(\"_\")[-1]\n",
    "    \n",
    "    for j in cell1_neighbors:\n",
    "        cell2_idx = int(j)-1\n",
    "        cell2_row = df.iloc[cell2_idx]\n",
    "        cell2_type =  cell2_row[\"Cell_Type\"].split(\"_\")[-1]\n",
    "        \n",
    "        # combined_ct= f\"{cell1_type}|{cell2_type}\"\n",
    "        # # print(cell2_idx,combined_ct)\n",
    "        \n",
    "        # if combined_ct in gt_set:\n",
    "        scmultisim_adj[i][cell2_idx] = 1\n",
    "        scmultisim_adj[cell2_idx][i] = 1\n",
    "        edge_list.append([int(i), int(cell2_idx)])\n",
    "        edge_list.append([int(cell2_idx),int(i)])\n",
    "            \n",
    "        \n",
    "edge_arr = np.array(edge_list).T\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   0,    6,    0, ..., 1137, 1199, 1150],\n",
       "       [   6,    0,   11, ..., 1198, 1150, 1199]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edge_arr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "G = nx.from_edgelist(edge_arr.T)\n",
    "G.add_nodes_from(range(1200))\n",
    "\n",
    "node_positions = df[[\"X\",\"Y\"]]\n",
    "\n",
    "for i, rowloc in node_positions.iterrows():\n",
    "    G.nodes[i]['pos'] = (rowloc[\"X\"],rowloc[\"Y\"])\n",
    "    \n",
    "edge_x = []\n",
    "edge_y = []\n",
    "for edge in G.edges():\n",
    "    x0, y0 = G.nodes[edge[0]]['pos']\n",
    "    x1, y1 = G.nodes[edge[1]]['pos']\n",
    "    edge_x.append(x0)\n",
    "    edge_x.append(x1)\n",
    "    edge_x.append(None)\n",
    "    edge_y.append(y0)\n",
    "    edge_y.append(y1)\n",
    "    edge_y.append(None)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   0,    0,    0, ..., 1165, 1137, 1159],\n",
       "       [   6,   11,   46, ..., 1196, 1198, 1191]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edge_arr = nx.to_pandas_edgelist(G).values.T\n",
    "adjacency = nx.to_pandas_adjacency(G)\n",
    "\n",
    "# adjacency.to_csv(\"./data/scMultiSim_final/adj.csv\",index=False)\n",
    "edge_arr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.save(\"./out/scmultisim_final/1_preprocessing_output/celllevel_adjacencymatrix.npy\",adjacency)\n",
    "np.save(\"./out/scmultisim_final/1_preprocessing_output/celllevel_edgelist.npy\",edge_arr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 6720)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# \n",
    "edge_arr.shape\n",
    "    \n",
    "# for node, neighbors in enumerate(adj_list):\n",
    "#     for neighbor in neighbors:\n",
    "#         edge_list.append([node, neighbor])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1000, 120)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.load(\"./out/scmultisim/1_preprocessing_output/celllevel_features.npy\").shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(neighbors.values == 0).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "adjacency_list = []\n",
    "for i,row in scmultisim_neighbors.iterrows():\n",
    "    adjusted_row = row - 1\n",
    "    neighborlist = adjusted_row.fillna(-1).astype(int).tolist()\n",
    "    adjacency_list.append(neighborlist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1200, 4)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adjacency_list = np.array(adjacency_list)\n",
    "adjacency_list.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.save(f\"./data/scmultisim_final/gt_adjacency_list.npy\",adjacency_list)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>gene1</th>\n",
       "      <th>gene2</th>\n",
       "      <th>gene3</th>\n",
       "      <th>gene4</th>\n",
       "      <th>gene5</th>\n",
       "      <th>gene6</th>\n",
       "      <th>gene7</th>\n",
       "      <th>gene8</th>\n",
       "      <th>gene9</th>\n",
       "      <th>gene10</th>\n",
       "      <th>...</th>\n",
       "      <th>gene111</th>\n",
       "      <th>gene112</th>\n",
       "      <th>gene113</th>\n",
       "      <th>gene114</th>\n",
       "      <th>gene115</th>\n",
       "      <th>gene116</th>\n",
       "      <th>gene117</th>\n",
       "      <th>gene118</th>\n",
       "      <th>gene119</th>\n",
       "      <th>gene120</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.910281</td>\n",
       "      <td>4.135231</td>\n",
       "      <td>0.042036</td>\n",
       "      <td>2.482637</td>\n",
       "      <td>0.516450</td>\n",
       "      <td>1.228738</td>\n",
       "      <td>3.151565</td>\n",
       "      <td>3.178573</td>\n",
       "      <td>1.742491</td>\n",
       "      <td>1.906865</td>\n",
       "      <td>...</td>\n",
       "      <td>1.624570</td>\n",
       "      <td>0.728130</td>\n",
       "      <td>2.589264</td>\n",
       "      <td>5.872145</td>\n",
       "      <td>3.016004</td>\n",
       "      <td>1.744769</td>\n",
       "      <td>1.723877</td>\n",
       "      <td>7.143932</td>\n",
       "      <td>1.282380</td>\n",
       "      <td>0.499699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.193444</td>\n",
       "      <td>0.664207</td>\n",
       "      <td>0.203781</td>\n",
       "      <td>0.654074</td>\n",
       "      <td>1.033436</td>\n",
       "      <td>0.832395</td>\n",
       "      <td>0.318517</td>\n",
       "      <td>0.601289</td>\n",
       "      <td>0.710586</td>\n",
       "      <td>0.612739</td>\n",
       "      <td>...</td>\n",
       "      <td>0.727891</td>\n",
       "      <td>0.710085</td>\n",
       "      <td>0.379004</td>\n",
       "      <td>1.029571</td>\n",
       "      <td>0.223424</td>\n",
       "      <td>0.565081</td>\n",
       "      <td>0.503244</td>\n",
       "      <td>1.048953</td>\n",
       "      <td>0.572435</td>\n",
       "      <td>0.633272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.197225</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.708050</td>\n",
       "      <td>1.791759</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.688879</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.637586</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.079442</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>2.944439</td>\n",
       "      <td>2.833213</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>...</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.397895</td>\n",
       "      <td>5.253558</td>\n",
       "      <td>2.890372</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>6.415097</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.945910</td>\n",
       "      <td>4.127134</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.484907</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>3.135494</td>\n",
       "      <td>3.156774</td>\n",
       "      <td>1.791759</td>\n",
       "      <td>1.945910</td>\n",
       "      <td>...</td>\n",
       "      <td>1.791759</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>2.639057</td>\n",
       "      <td>6.045005</td>\n",
       "      <td>3.044522</td>\n",
       "      <td>1.791759</td>\n",
       "      <td>1.791759</td>\n",
       "      <td>6.944080</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.708050</td>\n",
       "      <td>4.521789</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.833213</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>1.791759</td>\n",
       "      <td>3.332205</td>\n",
       "      <td>3.526361</td>\n",
       "      <td>2.302585</td>\n",
       "      <td>2.302585</td>\n",
       "      <td>...</td>\n",
       "      <td>2.197225</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>2.833213</td>\n",
       "      <td>6.616065</td>\n",
       "      <td>3.178054</td>\n",
       "      <td>2.108887</td>\n",
       "      <td>2.079442</td>\n",
       "      <td>8.215074</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>1.098612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.616771</td>\n",
       "      <td>7.037028</td>\n",
       "      <td>2.197225</td>\n",
       "      <td>5.068904</td>\n",
       "      <td>4.912655</td>\n",
       "      <td>4.043051</td>\n",
       "      <td>4.634729</td>\n",
       "      <td>6.188264</td>\n",
       "      <td>3.295837</td>\n",
       "      <td>3.091042</td>\n",
       "      <td>...</td>\n",
       "      <td>3.178054</td>\n",
       "      <td>2.708050</td>\n",
       "      <td>3.583519</td>\n",
       "      <td>8.445697</td>\n",
       "      <td>3.637586</td>\n",
       "      <td>3.178054</td>\n",
       "      <td>2.944439</td>\n",
       "      <td>8.977525</td>\n",
       "      <td>2.890372</td>\n",
       "      <td>2.708050</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 120 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             gene1        gene2        gene3        gene4        gene5  \\\n",
       "count  1200.000000  1200.000000  1200.000000  1200.000000  1200.000000   \n",
       "mean      1.910281     4.135231     0.042036     2.482637     0.516450   \n",
       "std       1.193444     0.664207     0.203781     0.654074     1.033436   \n",
       "min       0.000000     2.197225     0.000000     0.000000     0.000000   \n",
       "25%       1.098612     3.637586     0.000000     2.079442     0.000000   \n",
       "50%       1.945910     4.127134     0.000000     2.484907     0.000000   \n",
       "75%       2.708050     4.521789     0.000000     2.833213     0.693147   \n",
       "max       5.616771     7.037028     2.197225     5.068904     4.912655   \n",
       "\n",
       "             gene6        gene7        gene8        gene9       gene10  ...  \\\n",
       "count  1200.000000  1200.000000  1200.000000  1200.000000  1200.000000  ...   \n",
       "mean      1.228738     3.151565     3.178573     1.742491     1.906865  ...   \n",
       "std       0.832395     0.318517     0.601289     0.710586     0.612739  ...   \n",
       "min       0.000000     1.098612     0.693147     0.000000     0.000000  ...   \n",
       "25%       0.693147     2.944439     2.833213     1.386294     1.609438  ...   \n",
       "50%       1.386294     3.135494     3.156774     1.791759     1.945910  ...   \n",
       "75%       1.791759     3.332205     3.526361     2.302585     2.302585  ...   \n",
       "max       4.043051     4.634729     6.188264     3.295837     3.091042  ...   \n",
       "\n",
       "           gene111      gene112      gene113      gene114      gene115  \\\n",
       "count  1200.000000  1200.000000  1200.000000  1200.000000  1200.000000   \n",
       "mean      1.624570     0.728130     2.589264     5.872145     3.016004   \n",
       "std       0.727891     0.710085     0.379004     1.029571     0.223424   \n",
       "min       0.000000     0.000000     0.000000     2.708050     1.791759   \n",
       "25%       1.098612     0.000000     2.397895     5.253558     2.890372   \n",
       "50%       1.791759     0.693147     2.639057     6.045005     3.044522   \n",
       "75%       2.197225     1.386294     2.833213     6.616065     3.178054   \n",
       "max       3.178054     2.708050     3.583519     8.445697     3.637586   \n",
       "\n",
       "           gene116      gene117      gene118      gene119      gene120  \n",
       "count  1200.000000  1200.000000  1200.000000  1200.000000  1200.000000  \n",
       "mean      1.744769     1.723877     7.143932     1.282380     0.499699  \n",
       "std       0.565081     0.503244     1.048953     0.572435     0.633272  \n",
       "min       0.000000     0.000000     3.688879     0.000000     0.000000  \n",
       "25%       1.386294     1.386294     6.415097     1.098612     0.000000  \n",
       "50%       1.791759     1.791759     6.944080     1.386294     0.000000  \n",
       "75%       2.108887     2.079442     8.215074     1.609438     1.098612  \n",
       "max       3.178054     2.944439     8.977525     2.890372     2.708050  \n",
       "\n",
       "[8 rows x 120 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "multisim_counts = pd.read_csv(f\"./data/{multisim_name}/scmultisim_dataframe.csv\").iloc[:, 4:]\n",
    "multisim_counts.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>4931431F19Rik</th>\n",
       "      <th>4932429P05Rik</th>\n",
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       "      <th>Abca9</th>\n",
       "      <th>Adcy4</th>\n",
       "      <th>Aldh3b2</th>\n",
       "      <th>Ankle1</th>\n",
       "      <th>Ano7</th>\n",
       "      <th>Anxa9</th>\n",
       "      <th>Arhgef26</th>\n",
       "      <th>...</th>\n",
       "      <th>calb1</th>\n",
       "      <th>gda</th>\n",
       "      <th>slc5a7</th>\n",
       "      <th>sema3e</th>\n",
       "      <th>mfge8</th>\n",
       "      <th>lyve1</th>\n",
       "      <th>loxl1</th>\n",
       "      <th>slco1c1</th>\n",
       "      <th>amigo2</th>\n",
       "      <th>kcnip</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "      <td>1597.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-0.004634</td>\n",
       "      <td>0.000795</td>\n",
       "      <td>-0.006738</td>\n",
       "      <td>-0.002148</td>\n",
       "      <td>0.004101</td>\n",
       "      <td>-0.011146</td>\n",
       "      <td>-0.004890</td>\n",
       "      <td>-0.004959</td>\n",
       "      <td>-0.003431</td>\n",
       "      <td>-0.004909</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010438</td>\n",
       "      <td>0.017101</td>\n",
       "      <td>0.009317</td>\n",
       "      <td>0.011760</td>\n",
       "      <td>-0.004696</td>\n",
       "      <td>0.004759</td>\n",
       "      <td>0.016287</td>\n",
       "      <td>0.003582</td>\n",
       "      <td>0.001202</td>\n",
       "      <td>-0.001816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.004863</td>\n",
       "      <td>1.003174</td>\n",
       "      <td>1.009325</td>\n",
       "      <td>1.002433</td>\n",
       "      <td>0.995672</td>\n",
       "      <td>1.014559</td>\n",
       "      <td>1.005069</td>\n",
       "      <td>1.006324</td>\n",
       "      <td>1.004245</td>\n",
       "      <td>1.012613</td>\n",
       "      <td>...</td>\n",
       "      <td>0.987435</td>\n",
       "      <td>0.972709</td>\n",
       "      <td>0.975218</td>\n",
       "      <td>0.979422</td>\n",
       "      <td>1.015804</td>\n",
       "      <td>0.984703</td>\n",
       "      <td>0.965073</td>\n",
       "      <td>0.987810</td>\n",
       "      <td>0.990594</td>\n",
       "      <td>1.001660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-4.290000</td>\n",
       "      <td>-4.110000</td>\n",
       "      <td>-4.500000</td>\n",
       "      <td>-4.370000</td>\n",
       "      <td>-4.330000</td>\n",
       "      <td>-4.100000</td>\n",
       "      <td>-4.460000</td>\n",
       "      <td>-4.260000</td>\n",
       "      <td>-4.170000</td>\n",
       "      <td>-4.320000</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.170000</td>\n",
       "      <td>-4.600000</td>\n",
       "      <td>-3.580000</td>\n",
       "      <td>-3.810000</td>\n",
       "      <td>-4.520000</td>\n",
       "      <td>-4.700000</td>\n",
       "      <td>-6.160000</td>\n",
       "      <td>-6.030000</td>\n",
       "      <td>-3.610000</td>\n",
       "      <td>-4.360000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.670000</td>\n",
       "      <td>-0.690000</td>\n",
       "      <td>-0.660000</td>\n",
       "      <td>-0.700000</td>\n",
       "      <td>-0.640000</td>\n",
       "      <td>-0.670000</td>\n",
       "      <td>-0.650000</td>\n",
       "      <td>-0.690000</td>\n",
       "      <td>-0.690000</td>\n",
       "      <td>-0.660000</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.610000</td>\n",
       "      <td>-0.630000</td>\n",
       "      <td>-0.590000</td>\n",
       "      <td>-0.590000</td>\n",
       "      <td>-0.620000</td>\n",
       "      <td>-0.510000</td>\n",
       "      <td>-0.560000</td>\n",
       "      <td>-0.450000</td>\n",
       "      <td>-0.590000</td>\n",
       "      <td>-0.580000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.110000</td>\n",
       "      <td>0.120000</td>\n",
       "      <td>0.080000</td>\n",
       "      <td>0.140000</td>\n",
       "      <td>0.170000</td>\n",
       "      <td>0.060000</td>\n",
       "      <td>0.120000</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>0.060000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.070000</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>0.030000</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>0.140000</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>-0.020000</td>\n",
       "      <td>0.080000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.740000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.720000</td>\n",
       "      <td>0.730000</td>\n",
       "      <td>0.740000</td>\n",
       "      <td>0.780000</td>\n",
       "      <td>0.720000</td>\n",
       "      <td>0.760000</td>\n",
       "      <td>0.740000</td>\n",
       "      <td>0.720000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.630000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.710000</td>\n",
       "      <td>0.710000</td>\n",
       "      <td>0.640000</td>\n",
       "      <td>0.680000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.620000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.570000</td>\n",
       "      <td>2.570000</td>\n",
       "      <td>2.410000</td>\n",
       "      <td>2.930000</td>\n",
       "      <td>2.620000</td>\n",
       "      <td>2.630000</td>\n",
       "      <td>2.480000</td>\n",
       "      <td>2.470000</td>\n",
       "      <td>2.430000</td>\n",
       "      <td>2.920000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.790000</td>\n",
       "      <td>2.740000</td>\n",
       "      <td>2.410000</td>\n",
       "      <td>3.070000</td>\n",
       "      <td>2.980000</td>\n",
       "      <td>2.470000</td>\n",
       "      <td>2.370000</td>\n",
       "      <td>3.920000</td>\n",
       "      <td>4.180000</td>\n",
       "      <td>5.150000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 125 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       4931431F19Rik  4932429P05Rik       Abca15        Abca9        Adcy4  \\\n",
       "count    1597.000000    1597.000000  1597.000000  1597.000000  1597.000000   \n",
       "mean       -0.004634       0.000795    -0.006738    -0.002148     0.004101   \n",
       "std         1.004863       1.003174     1.009325     1.002433     0.995672   \n",
       "min        -4.290000      -4.110000    -4.500000    -4.370000    -4.330000   \n",
       "25%        -0.670000      -0.690000    -0.660000    -0.700000    -0.640000   \n",
       "50%         0.110000       0.120000     0.080000     0.140000     0.170000   \n",
       "75%         0.740000       0.700000     0.720000     0.730000     0.740000   \n",
       "max         2.570000       2.570000     2.410000     2.930000     2.620000   \n",
       "\n",
       "           Aldh3b2       Ankle1         Ano7        Anxa9     Arhgef26  ...  \\\n",
       "count  1597.000000  1597.000000  1597.000000  1597.000000  1597.000000  ...   \n",
       "mean     -0.011146    -0.004890    -0.004959    -0.003431    -0.004909  ...   \n",
       "std       1.014559     1.005069     1.006324     1.004245     1.012613  ...   \n",
       "min      -4.100000    -4.460000    -4.260000    -4.170000    -4.320000  ...   \n",
       "25%      -0.670000    -0.650000    -0.690000    -0.690000    -0.660000  ...   \n",
       "50%       0.060000     0.120000     0.090000     0.150000     0.060000  ...   \n",
       "75%       0.780000     0.720000     0.760000     0.740000     0.720000  ...   \n",
       "max       2.630000     2.480000     2.470000     2.430000     2.920000  ...   \n",
       "\n",
       "             calb1          gda       slc5a7       sema3e        mfge8  \\\n",
       "count  1597.000000  1597.000000  1597.000000  1597.000000  1597.000000   \n",
       "mean      0.010438     0.017101     0.009317     0.011760    -0.004696   \n",
       "std       0.987435     0.972709     0.975218     0.979422     1.015804   \n",
       "min      -3.170000    -4.600000    -3.580000    -3.810000    -4.520000   \n",
       "25%      -0.610000    -0.630000    -0.590000    -0.590000    -0.620000   \n",
       "50%       0.020000     0.070000     0.150000     0.090000     0.030000   \n",
       "75%       0.630000     0.700000     0.710000     0.710000     0.640000   \n",
       "max       3.790000     2.740000     2.410000     3.070000     2.980000   \n",
       "\n",
       "             lyve1        loxl1      slco1c1       amigo2        kcnip  \n",
       "count  1597.000000  1597.000000  1597.000000  1597.000000  1597.000000  \n",
       "mean      0.004759     0.016287     0.003582     0.001202    -0.001816  \n",
       "std       0.984703     0.965073     0.987810     0.990594     1.001660  \n",
       "min      -4.700000    -6.160000    -6.030000    -3.610000    -4.360000  \n",
       "25%      -0.510000    -0.560000    -0.450000    -0.590000    -0.580000  \n",
       "50%       0.150000     0.140000     0.090000    -0.020000     0.080000  \n",
       "75%       0.680000     0.700000     0.600000     0.500000     0.620000  \n",
       "max       2.470000     2.370000     3.920000     4.180000     5.150000  \n",
       "\n",
       "[8 rows x 125 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seqfish_counts = pd.read_csv(\"./data/seqFISH/seqfish_dataframe.csv\").iloc[:, 4:]\n",
    "seqfish_counts.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Ace2</th>\n",
       "      <th>Adora2a</th>\n",
       "      <th>Aldh1l1</th>\n",
       "      <th>Amigo2</th>\n",
       "      <th>Ano3</th>\n",
       "      <th>Aqp4</th>\n",
       "      <th>Ar</th>\n",
       "      <th>Arhgap36</th>\n",
       "      <th>Avpr1a</th>\n",
       "      <th>Avpr2</th>\n",
       "      <th>...</th>\n",
       "      <th>Penk</th>\n",
       "      <th>Scg2</th>\n",
       "      <th>Sln</th>\n",
       "      <th>Sst</th>\n",
       "      <th>Tac1</th>\n",
       "      <th>Tac2</th>\n",
       "      <th>Th</th>\n",
       "      <th>Trh</th>\n",
       "      <th>Ucn3</th>\n",
       "      <th>Vgf</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.030584</td>\n",
       "      <td>-0.019348</td>\n",
       "      <td>0.009367</td>\n",
       "      <td>-0.000125</td>\n",
       "      <td>-0.003150</td>\n",
       "      <td>-0.078060</td>\n",
       "      <td>0.124230</td>\n",
       "      <td>-0.034674</td>\n",
       "      <td>0.010249</td>\n",
       "      <td>0.000442</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004783</td>\n",
       "      <td>-0.077296</td>\n",
       "      <td>-0.168275</td>\n",
       "      <td>-0.008412</td>\n",
       "      <td>-0.083951</td>\n",
       "      <td>0.072243</td>\n",
       "      <td>-0.025267</td>\n",
       "      <td>-0.017205</td>\n",
       "      <td>-0.159780</td>\n",
       "      <td>-0.037213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.030377</td>\n",
       "      <td>1.024116</td>\n",
       "      <td>1.214940</td>\n",
       "      <td>0.960918</td>\n",
       "      <td>1.013426</td>\n",
       "      <td>1.135378</td>\n",
       "      <td>0.977096</td>\n",
       "      <td>0.966985</td>\n",
       "      <td>1.021458</td>\n",
       "      <td>0.983296</td>\n",
       "      <td>...</td>\n",
       "      <td>0.991498</td>\n",
       "      <td>0.859355</td>\n",
       "      <td>0.846360</td>\n",
       "      <td>0.872716</td>\n",
       "      <td>0.888690</td>\n",
       "      <td>1.070905</td>\n",
       "      <td>0.857775</td>\n",
       "      <td>0.861893</td>\n",
       "      <td>0.699319</td>\n",
       "      <td>0.913815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.105452</td>\n",
       "      <td>-1.031567</td>\n",
       "      <td>-1.717386</td>\n",
       "      <td>-1.453177</td>\n",
       "      <td>-1.158946</td>\n",
       "      <td>-1.613815</td>\n",
       "      <td>-1.584621</td>\n",
       "      <td>-1.304777</td>\n",
       "      <td>-1.104415</td>\n",
       "      <td>-1.063916</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.883173</td>\n",
       "      <td>-1.238918</td>\n",
       "      <td>-1.275601</td>\n",
       "      <td>-0.759393</td>\n",
       "      <td>-1.155543</td>\n",
       "      <td>-0.940493</td>\n",
       "      <td>-1.096287</td>\n",
       "      <td>-0.907511</td>\n",
       "      <td>-1.205863</td>\n",
       "      <td>-1.058456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.553351</td>\n",
       "      <td>-0.536070</td>\n",
       "      <td>-0.931627</td>\n",
       "      <td>-0.752213</td>\n",
       "      <td>-0.614573</td>\n",
       "      <td>-0.904208</td>\n",
       "      <td>-0.820176</td>\n",
       "      <td>-0.685762</td>\n",
       "      <td>-0.604354</td>\n",
       "      <td>-0.567892</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.430439</td>\n",
       "      <td>-0.601904</td>\n",
       "      <td>-0.694311</td>\n",
       "      <td>-0.348101</td>\n",
       "      <td>-0.585892</td>\n",
       "      <td>-0.267992</td>\n",
       "      <td>-0.484830</td>\n",
       "      <td>-0.464852</td>\n",
       "      <td>-0.563283</td>\n",
       "      <td>-0.490765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-0.326023</td>\n",
       "      <td>-0.308246</td>\n",
       "      <td>-0.349564</td>\n",
       "      <td>-0.511491</td>\n",
       "      <td>-0.398195</td>\n",
       "      <td>-0.575559</td>\n",
       "      <td>0.184140</td>\n",
       "      <td>-0.462900</td>\n",
       "      <td>-0.381143</td>\n",
       "      <td>-0.334803</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.171768</td>\n",
       "      <td>-0.396682</td>\n",
       "      <td>-0.478335</td>\n",
       "      <td>-0.119493</td>\n",
       "      <td>-0.382237</td>\n",
       "      <td>-0.085165</td>\n",
       "      <td>-0.250321</td>\n",
       "      <td>-0.170067</td>\n",
       "      <td>-0.366686</td>\n",
       "      <td>-0.263945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-0.096556</td>\n",
       "      <td>-0.111748</td>\n",
       "      <td>0.689824</td>\n",
       "      <td>0.725953</td>\n",
       "      <td>0.236040</td>\n",
       "      <td>0.542752</td>\n",
       "      <td>0.922570</td>\n",
       "      <td>0.485797</td>\n",
       "      <td>-0.054657</td>\n",
       "      <td>-0.121518</td>\n",
       "      <td>...</td>\n",
       "      <td>0.032045</td>\n",
       "      <td>0.169967</td>\n",
       "      <td>0.083270</td>\n",
       "      <td>0.106547</td>\n",
       "      <td>-0.091472</td>\n",
       "      <td>0.069018</td>\n",
       "      <td>0.068696</td>\n",
       "      <td>0.187930</td>\n",
       "      <td>-0.004669</td>\n",
       "      <td>-0.064402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.144469</td>\n",
       "      <td>6.553675</td>\n",
       "      <td>4.766347</td>\n",
       "      <td>3.119148</td>\n",
       "      <td>4.781226</td>\n",
       "      <td>3.532134</td>\n",
       "      <td>2.715245</td>\n",
       "      <td>3.876638</td>\n",
       "      <td>5.475393</td>\n",
       "      <td>4.791234</td>\n",
       "      <td>...</td>\n",
       "      <td>8.896245</td>\n",
       "      <td>4.057683</td>\n",
       "      <td>4.744431</td>\n",
       "      <td>10.206752</td>\n",
       "      <td>5.432989</td>\n",
       "      <td>8.905978</td>\n",
       "      <td>7.990121</td>\n",
       "      <td>8.456338</td>\n",
       "      <td>7.334901</td>\n",
       "      <td>7.084489</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 160 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Ace2      Adora2a      Aldh1l1       Amigo2         Ano3  \\\n",
       "count  1600.000000  1600.000000  1600.000000  1600.000000  1600.000000   \n",
       "mean      0.030584    -0.019348     0.009367    -0.000125    -0.003150   \n",
       "std       1.030377     1.024116     1.214940     0.960918     1.013426   \n",
       "min      -1.105452    -1.031567    -1.717386    -1.453177    -1.158946   \n",
       "25%      -0.553351    -0.536070    -0.931627    -0.752213    -0.614573   \n",
       "50%      -0.326023    -0.308246    -0.349564    -0.511491    -0.398195   \n",
       "75%      -0.096556    -0.111748     0.689824     0.725953     0.236040   \n",
       "max       5.144469     6.553675     4.766347     3.119148     4.781226   \n",
       "\n",
       "              Aqp4           Ar     Arhgap36       Avpr1a        Avpr2  ...  \\\n",
       "count  1600.000000  1600.000000  1600.000000  1600.000000  1600.000000  ...   \n",
       "mean     -0.078060     0.124230    -0.034674     0.010249     0.000442  ...   \n",
       "std       1.135378     0.977096     0.966985     1.021458     0.983296  ...   \n",
       "min      -1.613815    -1.584621    -1.304777    -1.104415    -1.063916  ...   \n",
       "25%      -0.904208    -0.820176    -0.685762    -0.604354    -0.567892  ...   \n",
       "50%      -0.575559     0.184140    -0.462900    -0.381143    -0.334803  ...   \n",
       "75%       0.542752     0.922570     0.485797    -0.054657    -0.121518  ...   \n",
       "max       3.532134     2.715245     3.876638     5.475393     4.791234  ...   \n",
       "\n",
       "              Penk         Scg2          Sln          Sst         Tac1  \\\n",
       "count  1600.000000  1600.000000  1600.000000  1600.000000  1600.000000   \n",
       "mean      0.004783    -0.077296    -0.168275    -0.008412    -0.083951   \n",
       "std       0.991498     0.859355     0.846360     0.872716     0.888690   \n",
       "min      -0.883173    -1.238918    -1.275601    -0.759393    -1.155543   \n",
       "25%      -0.430439    -0.601904    -0.694311    -0.348101    -0.585892   \n",
       "50%      -0.171768    -0.396682    -0.478335    -0.119493    -0.382237   \n",
       "75%       0.032045     0.169967     0.083270     0.106547    -0.091472   \n",
       "max       8.896245     4.057683     4.744431    10.206752     5.432989   \n",
       "\n",
       "              Tac2           Th          Trh         Ucn3          Vgf  \n",
       "count  1600.000000  1600.000000  1600.000000  1600.000000  1600.000000  \n",
       "mean      0.072243    -0.025267    -0.017205    -0.159780    -0.037213  \n",
       "std       1.070905     0.857775     0.861893     0.699319     0.913815  \n",
       "min      -0.940493    -1.096287    -0.907511    -1.205863    -1.058456  \n",
       "25%      -0.267992    -0.484830    -0.464852    -0.563283    -0.490765  \n",
       "50%      -0.085165    -0.250321    -0.170067    -0.366686    -0.263945  \n",
       "75%       0.069018     0.068696     0.187930    -0.004669    -0.064402  \n",
       "max       8.905978     7.990121     8.456338     7.334901     7.084489  \n",
       "\n",
       "[8 rows x 160 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merfish_counts = pd.read_csv(\"./data/MERFISH/merfish_dataframe.csv\").iloc[:, 4:]\n",
    "merfish_counts.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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