syn_org_prom_inputs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook is a continuation of cluster_deep_dive.ipynb, input_cluster_2.ipynb, and input_cluster_3.ipynb. It needs some work though."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
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If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. 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      "application/vnd.bokehjs_load.v0+json": ""
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import important stuff here\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib\n",
    "\n",
    "import bokeh\n",
    "import bokeh.palettes\n",
    "from bokeh.plotting import figure, show, output_notebook\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "\n",
       "  <img src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACMAAAAjCAYAAAAe2bNZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAK6wAACusBgosNWgAAABx0RVh0U29mdHdhcmUAQWRvYmUgRmlyZXdvcmtzIENTNui8sowAAAf9SURBVFiFvZh7cFTVHcc/59y7793sJiFAwkvAYDRqFWwdraLVlj61diRYsDjqCFbFKrYo0CltlSq1tLaC2GprGIriGwqjFu10OlrGv8RiK/IICYECSWBDkt3s695zTv9IAtlHeOn0O7Mzu797z+/3Ob/z+p0VfBq9doNFljuABwAXw2PcvGHt6bgwxhz7Ls4YZNVXxxANLENwE2D1W9PAGmAhszZ0/X9gll5yCbHoOirLzmaQs0F6F8QMZq1v/8xgNm7DYwwjgXJLYL4witQ16+sv/U9HdDmV4WrKw6B06cZC/RMrM4MZ7xz61DAbtzEXmAvUAX4pMOVecg9/MFFu3j3Gz7gQBLygS2RGumBkL0cubiFRsR3LzVBV1UMk3IrW73PT9C2lYOwhQB4ClhX1AuKpjLcV27oEjyUpNUJCg1CvcejykWTCXyQgzic2HIIBjg3pS6+uRLKAhumZvD4U+tq0jTrgkVKQQtLekfTtxIPAkhTNF6G7kZm7aPp6M9myKVQEoaYaIhEQYvD781DML/RfBGNZXAl4irJiwBa07e/y7cQnBaJghIX6ENl2GR/fGCBoz6cm5qeyEqQA5ZYA5x5eeiV0Qph4gjFAUSwAr6QllQgcxS/Jm25Cr2Tmpsk03XI9NfI31FTZBEOgVOk51adqDBNPCNPSRlkiDXbBEwOU2WxH+I7itQZ62g56OjM33suq1YsZHVtGZSUI2QdyYgkgOthQNIF7BIGDnRAJgJSgj69cUx1gB8PkOGwL4E1gPrM27gIg7NlGKLQApc7BmEnAxP5g/rw4YqBrCDB5xHkw5rdR/1qTrN/hKNo6YUwVDNpFsnjYS8RbidBPcPXFP6R6yfExuOXmN4A3jv1+8ZUwgY9D2OWjUZE6lO88jDwHI8ZixGiMKSeYTBamCoDk6kDAb6y1OcH1a6KpD/fZesoFw5FlIXAVCIiH4PxrV+p2npVDToTBmtjY8t1swh2V61E9KqWiyuPEjM8dbfxuvfa49Zayf9R136Wr8mBSf/T7bNteA8zwaGEUbFpckWwq95n59dUIywKl2fbOIS5e8bWSu0tJ1a5redAYfqkdjesodFajcgaVNWhXo1C9SrkN3Usmv3UMJrc6/DDwkwEntkEJLe67tSLhvyzK8rHDQWleve5CGk4VZEB1r+5bg2E2si+Y0QatDK6jUVkX5eg2YYlp++ZM+rfMNYamAj8Y7MAVWFqaR1f/t2xzU4IHjybBtthzuiAASqv7jTF7jOqDMAakFHgDNsFyP+FhwZHBmH9F7cutIYkQCylYYv1AZSqsn1/+bX51OMMjPSl2nAnM7hnjOx2v53YgNWAzHM9Q/9l0lQWPSCBSyokAtOBC1Rj+w/1Xs+STDp4/E5g7Rs2zm2+oeVd7PUuHKDf6A4r5EsPT5K3gfCnBXNUYnvGzb+KcCczYYWOnLpy4eOXuG2oec0PBN8XQQAnpvS35AvAykr56rWhPBiV4MvtceGLxk5Mr6A1O8IfK7rl7xJ0r9kyumuP4fa0lMqTBLJIAJqEf1J3qE92lMBndlyfRD2YBghHC4hlny7ASqCeWo5zaoDdIWfnIefNGTb9fC73QDfhyBUCNOxrGPSUBfPem9us253YTV+3mcBbdkUYfzmHiLqZbYdIGHHON2ZlemXouaJUOO6TqtdHEQuXYY8Yt+EbDgmlS6RdzkaDTv2P9A3gICiq93sWhb5mc5wVhuU3Y7m5hOc3So7qFT3SLgOXHb/cyOfMn7xROegoC/PTcn3v8gbKPgDopJFk3R/uBPWQiwQ+2/GJevRMObLUzqe/saJjQUQTTftEVMW9tWxPgAocwcj9abNcZe7s+6t2R2xXZG7zyYLp8Q1PiRBBHym5bYuXi8Qt+/LvGu9f/5YDAxABsaRNPH6Xr4D4Sk87a897SOy9v/fKwjoF2eQel95yDESGEF6gEMwKhLwKus3wOVjTtes7qzgLdXTMnNCNoEpbcrtNuq6N7Xh/+eqcbj94xQkp7mdKpW5XbtbR8Z26kgMCAf2UU5YEovRUVRHbu2b3vK1UdDFkDCyMRQxbpdv8nhKAGIa7QaQedzT07fFPny53R738JoVYBdVrnsNx9XZ9v33UeGO+AA2MMUkgqQ5UcdDLZSFeVgONnXeHqSAC5Ew1BXwko0D1Zct3dT1duOjS3MzZnEUJtBuoQAq3SGOLR4ekjn9NC5nVOaYXf9lETrUkmOJy3pOz8OKIb2A1cWhJCCEzOxU2mUPror+2/L3yyM3pkM7jTjr1nBOgkGeyQ7erxpdJsMAS9wb2F9rzMxNY1K2PMU0WtZV82VU8Wp6vbKJVo9Lx/+4cydORdxCCQ/kDGTZCWsRpLu7VD7bfKqL8V2orKTp/PtzaXy42jr6TwAuisi+7JolUG4wY+8vyrISCMtRrLKWpvjAOqx/QGhp0rjRo5xD3x98CWQuOQN8qumRMmI7jKZPUEpzNVZsj4Zbaq1to5tZZsKIydLWojhIXrJnES79EaOzv3du2NytKuxzJKAA6wF8xqEE8s2jo/1wd/khslQGxd81Zg62Bbp31XBH+iETt7Y3ELA0iU6iGDlQ5mexe0VEx4a3x8V1AaYwFJgTiwaOsDmeK2J8nMUOqsnB1A+dcA04ucCYt0urkjmflk9iT2v30q/gZn5rQPvor4n9Ou634PeBzoznes/iot/7WnClKoM/+zCIjH5kwT8ChQjTHPIPTjFV3PpU/Hx+DM/A9U3IXI4SPCYAAAAABJRU5ErkJggg=='\n",
       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
       "  \n",
       "\n",
       "\n",
       "\n",
       "\n",
       "</div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import holoviews as hv\n",
    "from holoviews import opts, dim\n",
    "hv.extension('bokeh')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.1.0'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from neuprint import Client\n",
    "# remove my token before making notebook public\n",
    "c = Client('neuprint.janelia.org', dataset='hemibrain:v1.2.1', token='eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJlbWFpbCI6ImdnMjExNEBjb2x1bWJpYS5lZHUiLCJsZXZlbCI6Im5vYXV0aCIsImltYWdlLXVybCI6Imh0dHBzOi8vbGgzLmdvb2dsZXVzZXJjb250ZW50LmNvbS9hLS9BT2gxNEdpb1lJLUVPLWdidGxPRTh6SmQ0eF9ZQ1Y4ZHF0YVFjWGlHeG5CMz1zOTYtYz9zej01MD9zej01MCIsImV4cCI6MTgxMDUyOTYzNH0.jv9eR0SH5RhfBdXrtp4r-dDFOhcsT8GBbE4v69ysCKs') \n",
    "c.fetch_version()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# body IDs of oviINs from Neuprint\n",
    "oviINr_bodyID = 423101189\n",
    "oviINl_bodyID = 485934965"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>id</th>\n",
       "      <th>key</th>\n",
       "      <th>0.0</th>\n",
       "      <th>0.05</th>\n",
       "      <th>0.1</th>\n",
       "      <th>0.5</th>\n",
       "      <th>0.75</th>\n",
       "      <th>1.0</th>\n",
       "      <th>instance</th>\n",
       "      <th>celltype</th>\n",
       "      <th>...</th>\n",
       "      <th>status</th>\n",
       "      <th>cropped</th>\n",
       "      <th>statusLabel</th>\n",
       "      <th>cellBodyFiber</th>\n",
       "      <th>somaRadius</th>\n",
       "      <th>somaLocation</th>\n",
       "      <th>roiInfo</th>\n",
       "      <th>notes</th>\n",
       "      <th>inputRois</th>\n",
       "      <th>outputRois</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1003215282</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CL229_R</td>\n",
       "      <td>CL229</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM19</td>\n",
       "      <td>301.0</td>\n",
       "      <td>[23044, 14981, 11600]</td>\n",
       "      <td>{'INP': {'pre': 87, 'post': 351, 'downstream':...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['EPA(R)', 'GOR(R)', 'IB', 'ICL(R)', 'INP', 'S...</td>\n",
       "      <td>['GOR(R)', 'IB', 'ICL(R)', 'INP', 'SCL(R)', 'S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1005952640</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>IB058_R</td>\n",
       "      <td>IB058</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PVL20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'INP': {'pre': 464, 'post': 1327, 'downstream...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['ATL(R)', 'IB', 'ICL(R)', 'INP', 'PLP(R)', 'S...</td>\n",
       "      <td>['ATL(R)', 'IB', 'ICL(R)', 'INP', 'PLP(R)', 'S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1006928515</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>CL300_R</td>\n",
       "      <td>CL300</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PVL13</td>\n",
       "      <td>236.0</td>\n",
       "      <td>[12083, 10523, 16816]</td>\n",
       "      <td>{'INP': {'pre': 79, 'post': 126, 'downstream':...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['ATL(R)', 'IB', 'ICL(R)', 'INP', 'SCL(R)', 'S...</td>\n",
       "      <td>['ATL(R)', 'IB', 'ICL(R)', 'INP', 'SCL(R)', 'S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1007260806</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>CL301_R</td>\n",
       "      <td>CL301</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PVL13</td>\n",
       "      <td>236.0</td>\n",
       "      <td>[13524, 10108, 16480]</td>\n",
       "      <td>{'INP': {'pre': 40, 'post': 128, 'downstream':...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['GOR(R)', 'IB', 'ICL(R)', 'INP', 'PLP(R)', 'S...</td>\n",
       "      <td>['IB', 'ICL(R)', 'INP', 'PLP(R)', 'SCL(R)', 'S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1008024276</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>FB5N_R</td>\n",
       "      <td>FB5N</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>AVM08</td>\n",
       "      <td>472.5</td>\n",
       "      <td>[19178, 29711, 37312]</td>\n",
       "      <td>{'SNP(L)': {'post': 5, 'upstream': 5, 'mito': ...</td>\n",
       "      <td>SMPCREFB5_4</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</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>2506</th>\n",
       "      <td>987273073</td>\n",
       "      <td>2507</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>409</td>\n",
       "      <td>604</td>\n",
       "      <td>629</td>\n",
       "      <td>(PVL05)_L</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'SNP(R)': {'pre': 65, 'post': 52, 'downstream...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2507</th>\n",
       "      <td>987842109</td>\n",
       "      <td>2508</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>23</td>\n",
       "      <td>533</td>\n",
       "      <td>780</td>\n",
       "      <td>815</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>Orphan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Orphan hotknife</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'SNP(R)': {'pre': 2, 'post': 13, 'downstream'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['SMP(R)', 'SNP(R)']</td>\n",
       "      <td>['SMP(R)', 'SNP(R)']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2508</th>\n",
       "      <td>988567837</td>\n",
       "      <td>2509</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>58</td>\n",
       "      <td>63</td>\n",
       "      <td>FB4G_R</td>\n",
       "      <td>FB4G</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>AVM08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'SNP(R)': {'pre': 6, 'post': 73, 'downstream'...</td>\n",
       "      <td>CRELALFB4_3</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2509</th>\n",
       "      <td>988909130</td>\n",
       "      <td>2510</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>389</td>\n",
       "      <td>559</td>\n",
       "      <td>572</td>\n",
       "      <td>FB5V_R</td>\n",
       "      <td>FB5V</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>AVM10</td>\n",
       "      <td>296.5</td>\n",
       "      <td>[13226, 32024, 18600]</td>\n",
       "      <td>{'SNP(R)': {'pre': 1, 'post': 28, 'downstream'...</td>\n",
       "      <td>CRELALFB5</td>\n",
       "      <td>['AB(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX',...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2510</th>\n",
       "      <td>989228019</td>\n",
       "      <td>2511</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>389</td>\n",
       "      <td>559</td>\n",
       "      <td>572</td>\n",
       "      <td>FB5V_R</td>\n",
       "      <td>FB5V</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>AVM10</td>\n",
       "      <td>296.5</td>\n",
       "      <td>[12516, 33587, 18648]</td>\n",
       "      <td>{'SNP(R)': {'pre': 1, 'post': 45, 'downstream'...</td>\n",
       "      <td>CRELALFB5</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2511 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              id   key  0.0  0.05  0.1  0.5  0.75  1.0   instance celltype  \\\n",
       "0     1003215282     1    1     1    1    1     1    1    CL229_R    CL229   \n",
       "1     1005952640     2    2     1    1    2     2    2    IB058_R    IB058   \n",
       "2     1006928515     3    1     1    1    3     3    3    CL300_R    CL300   \n",
       "3     1007260806     4    2     1    1    4     4    4    CL301_R    CL301   \n",
       "4     1008024276     5    3     2    2    5     5    5     FB5N_R     FB5N   \n",
       "...          ...   ...  ...   ...  ...  ...   ...  ...        ...      ...   \n",
       "2506   987273073  2507    3     8    8  409   604  629  (PVL05)_L     None   \n",
       "2507   987842109  2508    3     9   23  533   780  815       None     None   \n",
       "2508   988567837  2509    2     3    4   16    58   63     FB4G_R     FB4G   \n",
       "2509   988909130  2510    2     3    4  389   559  572     FB5V_R     FB5V   \n",
       "2510   989228019  2511    2     3    4  389   559  572     FB5V_R     FB5V   \n",
       "\n",
       "      ...  status  cropped      statusLabel  cellBodyFiber  somaRadius  \\\n",
       "0     ...  Traced    False   Roughly traced          PDM19       301.0   \n",
       "1     ...  Traced    False   Roughly traced          PVL20         NaN   \n",
       "2     ...  Traced    False   Roughly traced          PVL13       236.0   \n",
       "3     ...  Traced    False   Roughly traced          PVL13       236.0   \n",
       "4     ...  Traced    False   Roughly traced          AVM08       472.5   \n",
       "...   ...     ...      ...              ...            ...         ...   \n",
       "2506  ...  Traced    False   Roughly traced            NaN         NaN   \n",
       "2507  ...  Orphan      NaN  Orphan hotknife            NaN         NaN   \n",
       "2508  ...  Traced    False   Roughly traced          AVM08         NaN   \n",
       "2509  ...  Traced    False   Roughly traced          AVM10       296.5   \n",
       "2510  ...  Traced    False   Roughly traced          AVM10       296.5   \n",
       "\n",
       "               somaLocation  \\\n",
       "0     [23044, 14981, 11600]   \n",
       "1                       NaN   \n",
       "2     [12083, 10523, 16816]   \n",
       "3     [13524, 10108, 16480]   \n",
       "4     [19178, 29711, 37312]   \n",
       "...                     ...   \n",
       "2506                    NaN   \n",
       "2507                    NaN   \n",
       "2508                    NaN   \n",
       "2509  [13226, 32024, 18600]   \n",
       "2510  [12516, 33587, 18648]   \n",
       "\n",
       "                                                roiInfo        notes  \\\n",
       "0     {'INP': {'pre': 87, 'post': 351, 'downstream':...          NaN   \n",
       "1     {'INP': {'pre': 464, 'post': 1327, 'downstream...          NaN   \n",
       "2     {'INP': {'pre': 79, 'post': 126, 'downstream':...          NaN   \n",
       "3     {'INP': {'pre': 40, 'post': 128, 'downstream':...          NaN   \n",
       "4     {'SNP(L)': {'post': 5, 'upstream': 5, 'mito': ...  SMPCREFB5_4   \n",
       "...                                                 ...          ...   \n",
       "2506  {'SNP(R)': {'pre': 65, 'post': 52, 'downstream...          NaN   \n",
       "2507  {'SNP(R)': {'pre': 2, 'post': 13, 'downstream'...          NaN   \n",
       "2508  {'SNP(R)': {'pre': 6, 'post': 73, 'downstream'...  CRELALFB4_3   \n",
       "2509  {'SNP(R)': {'pre': 1, 'post': 28, 'downstream'...    CRELALFB5   \n",
       "2510  {'SNP(R)': {'pre': 1, 'post': 45, 'downstream'...    CRELALFB5   \n",
       "\n",
       "                                              inputRois  \\\n",
       "0     ['EPA(R)', 'GOR(R)', 'IB', 'ICL(R)', 'INP', 'S...   \n",
       "1     ['ATL(R)', 'IB', 'ICL(R)', 'INP', 'PLP(R)', 'S...   \n",
       "2     ['ATL(R)', 'IB', 'ICL(R)', 'INP', 'SCL(R)', 'S...   \n",
       "3     ['GOR(R)', 'IB', 'ICL(R)', 'INP', 'PLP(R)', 'S...   \n",
       "4     ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...   \n",
       "...                                                 ...   \n",
       "2506  ['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...   \n",
       "2507                               ['SMP(R)', 'SNP(R)']   \n",
       "2508  ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...   \n",
       "2509  ['AB(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX',...   \n",
       "2510  ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...   \n",
       "\n",
       "                                             outputRois  \n",
       "0     ['GOR(R)', 'IB', 'ICL(R)', 'INP', 'SCL(R)', 'S...  \n",
       "1     ['ATL(R)', 'IB', 'ICL(R)', 'INP', 'PLP(R)', 'S...  \n",
       "2     ['ATL(R)', 'IB', 'ICL(R)', 'INP', 'SCL(R)', 'S...  \n",
       "3     ['IB', 'ICL(R)', 'INP', 'PLP(R)', 'SCL(R)', 'S...  \n",
       "4     ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...  \n",
       "...                                                 ...  \n",
       "2506  ['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...  \n",
       "2507                               ['SMP(R)', 'SNP(R)']  \n",
       "2508  ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...  \n",
       "2509  ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...  \n",
       "2510  ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...  \n",
       "\n",
       "[2511 rows x 26 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "\n",
    "# file path for oviIN modularity data for ovi input connectome\n",
    "os.chdir('/Users/ggutierr/My Drive (ggutierr@barnard.edu)/GitHub/oviIN-analyses-gabrielle/ovi_preprocessed/preprocessed_inputs-v1.2.1')\n",
    "\n",
    "ovi_in_node_df = pd.read_csv('preprocessed_nodes.csv')\n",
    "ovi_in_node_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "os.chdir('/Users/ggutierr/My Drive (ggutierr@barnard.edu)/GitHub/oviIN-analyses-gabrielle/oviIN_specs')\n",
    "\n",
    "# to load the saved dataframe of oviINr presynapses\n",
    "ovi_pre_syns = pd.read_csv('ovi_pre_syns.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# return to cd\n",
    "os.chdir('/Users/ggutierr/My Drive (ggutierr@barnard.edu)/GitHub/oviIN-analyses-gabrielle')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get coarse cluster 2 \n",
    "cluster2 = ovi_in_node_df[ovi_in_node_df['0.0']==2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get coarse cluster 3\n",
    "cluster3 = ovi_in_node_df[ovi_in_node_df['0.0']==3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Synaptic organization of prominent inputs\n",
    "I want to see only the most prominent inputs since any shunting patterns would be likely to be significant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# had to write these out by hand because neuprint is down\n",
    "prom_input_types = ['FS1A','IB017','SMP052','SMP176','FC2B','SMP383','SMP554','LAL134','SMP550','CRE075','SMP566','LAL022','SMP237','FC2C','SMP551','SMP051','SMP386','pC1e','pC1d','SMP112']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>id</th>\n",
       "      <th>key</th>\n",
       "      <th>0.0</th>\n",
       "      <th>0.05</th>\n",
       "      <th>0.1</th>\n",
       "      <th>0.5</th>\n",
       "      <th>0.75</th>\n",
       "      <th>1.0</th>\n",
       "      <th>instance</th>\n",
       "      <th>celltype</th>\n",
       "      <th>...</th>\n",
       "      <th>status</th>\n",
       "      <th>cropped</th>\n",
       "      <th>statusLabel</th>\n",
       "      <th>cellBodyFiber</th>\n",
       "      <th>somaRadius</th>\n",
       "      <th>somaLocation</th>\n",
       "      <th>roiInfo</th>\n",
       "      <th>notes</th>\n",
       "      <th>inputRois</th>\n",
       "      <th>outputRois</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>357</th>\n",
       "      <td>1598011458</td>\n",
       "      <td>358</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>36</td>\n",
       "      <td>184</td>\n",
       "      <td>118</td>\n",
       "      <td>LAL134_R</td>\n",
       "      <td>LAL134</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM27</td>\n",
       "      <td>411.0</td>\n",
       "      <td>[22801, 18998, 9264]</td>\n",
       "      <td>{'SNP(R)': {'pre': 140, 'post': 1082, 'downstr...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['ATL(L)', 'ATL(R)', 'CAN(R)', 'CRE(-ROB,-RUB)...</td>\n",
       "      <td>['ATL(R)', 'CAN(R)', 'CRE(-ROB,-RUB)(R)', 'CRE...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>811</th>\n",
       "      <td>448342846</td>\n",
       "      <td>812</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>305</td>\n",
       "      <td>415</td>\n",
       "      <td>382</td>\n",
       "      <td>CRE075_R</td>\n",
       "      <td>CRE075</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM08</td>\n",
       "      <td>435.5</td>\n",
       "      <td>[21536, 17607, 7720]</td>\n",
       "      <td>{'SNP(R)': {'pre': 77, 'post': 1623, 'downstre...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['AOTU(R)', 'ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CR...</td>\n",
       "      <td>['ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(R)', 'GOR...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>941</th>\n",
       "      <td>514850616</td>\n",
       "      <td>942</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>336</td>\n",
       "      <td>455</td>\n",
       "      <td>435</td>\n",
       "      <td>pC1e_R</td>\n",
       "      <td>pC1e</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Traced</td>\n",
       "      <td>PDM09</td>\n",
       "      <td>356.0</td>\n",
       "      <td>[23338, 10397, 17648]</td>\n",
       "      <td>{'SNP(R)': {'pre': 387, 'post': 1777, 'downstr...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['AOTU(R)', 'AVLP(R)', 'EPA(R)', 'ICL(R)', 'IN...</td>\n",
       "      <td>['AOTU(R)', 'AVLP(R)', 'EPA(R)', 'ICL(R)', 'IN...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1298</th>\n",
       "      <td>5813022375</td>\n",
       "      <td>1299</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>331</td>\n",
       "      <td>448</td>\n",
       "      <td>563</td>\n",
       "      <td>IB017_R</td>\n",
       "      <td>IB017</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM08</td>\n",
       "      <td>301.0</td>\n",
       "      <td>[20296, 15956, 8416]</td>\n",
       "      <td>{'SNP(R)': {'pre': 338, 'post': 381, 'downstre...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)'...</td>\n",
       "      <td>['ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1413</th>\n",
       "      <td>5813063587</td>\n",
       "      <td>1414</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>178</td>\n",
       "      <td>515</td>\n",
       "      <td>515</td>\n",
       "      <td>pC1d_R</td>\n",
       "      <td>pC1d</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Traced</td>\n",
       "      <td>PDM09</td>\n",
       "      <td>376.0</td>\n",
       "      <td>[20475, 11420, 15072]</td>\n",
       "      <td>{'SNP(R)': {'pre': 582, 'post': 1728, 'downstr...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['AOTU(R)', 'AVLP(R)', 'EPA(R)', 'GOR(R)', 'IC...</td>\n",
       "      <td>['AOTU(R)', 'AVLP(R)', 'EPA(R)', 'GOR(R)', 'IC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1824</th>\n",
       "      <td>674108802</td>\n",
       "      <td>1825</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>374</td>\n",
       "      <td>635</td>\n",
       "      <td>667</td>\n",
       "      <td>SMP112_R</td>\n",
       "      <td>SMP112</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>ADM05</td>\n",
       "      <td>292.5</td>\n",
       "      <td>[16219, 34970, 16696]</td>\n",
       "      <td>{'SNP(R)': {'pre': 155, 'post': 939, 'downstre...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'INP', 'LAL(-G...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'INP', 'LAL(-G...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>730006122</td>\n",
       "      <td>1994</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>66</td>\n",
       "      <td>5</td>\n",
       "      <td>214</td>\n",
       "      <td>LAL022_R</td>\n",
       "      <td>LAL022</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>ADM05</td>\n",
       "      <td>354.0</td>\n",
       "      <td>[22175, 34366, 11168]</td>\n",
       "      <td>{'SNP(R)': {'pre': 27, 'post': 899, 'downstrea...</td>\n",
       "      <td>C-LSm</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'EPA(R)', 'INP...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'EPA(R)', 'GNG...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2033</th>\n",
       "      <td>735488299</td>\n",
       "      <td>2034</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>214</td>\n",
       "      <td>LAL022_R</td>\n",
       "      <td>LAL022</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>ADM05</td>\n",
       "      <td>292.5</td>\n",
       "      <td>[17990, 34913, 15312]</td>\n",
       "      <td>{'SNP(R)': {'pre': 39, 'post': 847, 'downstrea...</td>\n",
       "      <td>C-LSm</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'EPA(R)', 'GNG...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'EPA(R)', 'GNG...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              id   key  0.0  0.05  0.1  0.5  0.75  1.0  instance celltype  \\\n",
       "357   1598011458   358    2     7    7   36   184  118  LAL134_R   LAL134   \n",
       "811    448342846   812    2     3    4  305   415  382  CRE075_R   CRE075   \n",
       "941    514850616   942    2     1    6  336   455  435    pC1e_R     pC1e   \n",
       "1298  5813022375  1299    2     3    4  331   448  563   IB017_R    IB017   \n",
       "1413  5813063587  1414    2     1    6  178   515  515    pC1d_R     pC1d   \n",
       "1824   674108802  1825    2     8    8  374   635  667  SMP112_R   SMP112   \n",
       "1993   730006122  1994    2     7    7   66     5  214  LAL022_R   LAL022   \n",
       "2033   735488299  2034    2     7    7    5     5  214  LAL022_R   LAL022   \n",
       "\n",
       "      ...  status  cropped     statusLabel  cellBodyFiber  somaRadius  \\\n",
       "357   ...  Traced    False  Roughly traced          PDM27       411.0   \n",
       "811   ...  Traced    False  Roughly traced          PDM08       435.5   \n",
       "941   ...  Traced    False          Traced          PDM09       356.0   \n",
       "1298  ...  Traced    False  Roughly traced          PDM08       301.0   \n",
       "1413  ...  Traced    False          Traced          PDM09       376.0   \n",
       "1824  ...  Traced    False  Roughly traced          ADM05       292.5   \n",
       "1993  ...  Traced    False  Roughly traced          ADM05       354.0   \n",
       "2033  ...  Traced    False  Roughly traced          ADM05       292.5   \n",
       "\n",
       "               somaLocation  \\\n",
       "357    [22801, 18998, 9264]   \n",
       "811    [21536, 17607, 7720]   \n",
       "941   [23338, 10397, 17648]   \n",
       "1298   [20296, 15956, 8416]   \n",
       "1413  [20475, 11420, 15072]   \n",
       "1824  [16219, 34970, 16696]   \n",
       "1993  [22175, 34366, 11168]   \n",
       "2033  [17990, 34913, 15312]   \n",
       "\n",
       "                                                roiInfo  notes  \\\n",
       "357   {'SNP(R)': {'pre': 140, 'post': 1082, 'downstr...    NaN   \n",
       "811   {'SNP(R)': {'pre': 77, 'post': 1623, 'downstre...    NaN   \n",
       "941   {'SNP(R)': {'pre': 387, 'post': 1777, 'downstr...    NaN   \n",
       "1298  {'SNP(R)': {'pre': 338, 'post': 381, 'downstre...    NaN   \n",
       "1413  {'SNP(R)': {'pre': 582, 'post': 1728, 'downstr...    NaN   \n",
       "1824  {'SNP(R)': {'pre': 155, 'post': 939, 'downstre...    NaN   \n",
       "1993  {'SNP(R)': {'pre': 27, 'post': 899, 'downstrea...  C-LSm   \n",
       "2033  {'SNP(R)': {'pre': 39, 'post': 847, 'downstrea...  C-LSm   \n",
       "\n",
       "                                              inputRois  \\\n",
       "357   ['ATL(L)', 'ATL(R)', 'CAN(R)', 'CRE(-ROB,-RUB)...   \n",
       "811   ['AOTU(R)', 'ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CR...   \n",
       "941   ['AOTU(R)', 'AVLP(R)', 'EPA(R)', 'ICL(R)', 'IN...   \n",
       "1298  ['ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)'...   \n",
       "1413  ['AOTU(R)', 'AVLP(R)', 'EPA(R)', 'GOR(R)', 'IC...   \n",
       "1824  ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'INP', 'LAL(-G...   \n",
       "1993  ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'EPA(R)', 'INP...   \n",
       "2033  ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'EPA(R)', 'GNG...   \n",
       "\n",
       "                                             outputRois  \n",
       "357   ['ATL(R)', 'CAN(R)', 'CRE(-ROB,-RUB)(R)', 'CRE...  \n",
       "811   ['ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(R)', 'GOR...  \n",
       "941   ['AOTU(R)', 'AVLP(R)', 'EPA(R)', 'ICL(R)', 'IN...  \n",
       "1298  ['ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)'...  \n",
       "1413  ['AOTU(R)', 'AVLP(R)', 'EPA(R)', 'GOR(R)', 'IC...  \n",
       "1824  ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'INP', 'LAL(-G...  \n",
       "1993  ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'EPA(R)', 'GNG...  \n",
       "2033  ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'EPA(R)', 'GNG...  \n",
       "\n",
       "[8 rows x 26 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the prominent inputs in cluster 2\n",
    "cluster2[cluster2['celltype'].isin(prom_input_types)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['FC2B', 'FC2C', 'FS1A', 'SMP566', 'SMP386', 'SMP112', 'LAL022'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the prominent inputs in cluster 3\n",
    "cluster3[cluster3['celltype'].isin(prom_input_types)]['celltype'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>id</th>\n",
       "      <th>key</th>\n",
       "      <th>0.0</th>\n",
       "      <th>0.05</th>\n",
       "      <th>0.1</th>\n",
       "      <th>0.5</th>\n",
       "      <th>0.75</th>\n",
       "      <th>1.0</th>\n",
       "      <th>instance</th>\n",
       "      <th>celltype</th>\n",
       "      <th>...</th>\n",
       "      <th>status</th>\n",
       "      <th>cropped</th>\n",
       "      <th>statusLabel</th>\n",
       "      <th>cellBodyFiber</th>\n",
       "      <th>somaRadius</th>\n",
       "      <th>somaLocation</th>\n",
       "      <th>roiInfo</th>\n",
       "      <th>notes</th>\n",
       "      <th>inputRois</th>\n",
       "      <th>outputRois</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1008391068</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>FC2B(FQ7)_C6_L</td>\n",
       "      <td>FC2B</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM03</td>\n",
       "      <td>325.5</td>\n",
       "      <td>[29681, 16321, 7328]</td>\n",
       "      <td>{'CX': {'pre': 167, 'post': 2135, 'downstream'...</td>\n",
       "      <td>FB1d356CRE</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1008693605</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>FC2C(FQ7)_C7_L</td>\n",
       "      <td>FC2C</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM03</td>\n",
       "      <td>291.0</td>\n",
       "      <td>[32830, 14210, 12336]</td>\n",
       "      <td>{'CX': {'pre': 91, 'post': 1051, 'downstream':...</td>\n",
       "      <td>FB1d367CRE</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1009371535</td>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>FC2B(FQ7)_C3_L</td>\n",
       "      <td>FC2B</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM01</td>\n",
       "      <td>277.5</td>\n",
       "      <td>[28298, 18341, 7600]</td>\n",
       "      <td>{'CX': {'pre': 130, 'post': 2051, 'downstream'...</td>\n",
       "      <td>FB1d356CRE</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1010437434</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>FC2C(FQ7)_C7_L</td>\n",
       "      <td>FC2C</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM03</td>\n",
       "      <td>291.0</td>\n",
       "      <td>[33870, 12655, 13640]</td>\n",
       "      <td>{'CX': {'pre': 83, 'post': 980, 'downstream': ...</td>\n",
       "      <td>FB1d367CRE</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1014102651</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>FS1A(FQ9)_C2_L</td>\n",
       "      <td>FS1A</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM01</td>\n",
       "      <td>301.0</td>\n",
       "      <td>[26807, 16994, 11456]</td>\n",
       "      <td>{'SNP(R)': {'pre': 45, 'post': 34, 'downstream...</td>\n",
       "      <td>FB2-6SMPSMP</td>\n",
       "      <td>['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FB-col...</td>\n",
       "      <td>['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FB-col...</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>2475</th>\n",
       "      <td>978681977</td>\n",
       "      <td>2476</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>75</td>\n",
       "      <td>FC2C(FQ7)_C3_L</td>\n",
       "      <td>FC2C</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM01</td>\n",
       "      <td>316.0</td>\n",
       "      <td>[28321, 16270, 9104]</td>\n",
       "      <td>{'CX': {'pre': 114, 'post': 1408, 'downstream'...</td>\n",
       "      <td>FB1d367CRE</td>\n",
       "      <td>['AB(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX',...</td>\n",
       "      <td>['AB(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX',...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2487</th>\n",
       "      <td>983067799</td>\n",
       "      <td>2488</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>FS1A(FQ9)_C3_L</td>\n",
       "      <td>FS1A</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM01</td>\n",
       "      <td>291.0</td>\n",
       "      <td>[29498, 16181, 12232]</td>\n",
       "      <td>{'SNP(R)': {'pre': 48, 'post': 37, 'downstream...</td>\n",
       "      <td>FB2-6SMPSMP</td>\n",
       "      <td>['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FB-col...</td>\n",
       "      <td>['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FB-col...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2488</th>\n",
       "      <td>983093876</td>\n",
       "      <td>2489</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>51</td>\n",
       "      <td>FS1A(FQ9)_C8_L</td>\n",
       "      <td>FS1A</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM04</td>\n",
       "      <td>261.5</td>\n",
       "      <td>[32853, 11568, 18616]</td>\n",
       "      <td>{'SNP(R)': {'pre': 54, 'post': 50, 'downstream...</td>\n",
       "      <td>FB2-6SMPSMP</td>\n",
       "      <td>['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FBl1',...</td>\n",
       "      <td>['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FBl2',...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2490</th>\n",
       "      <td>983426636</td>\n",
       "      <td>2491</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>77</td>\n",
       "      <td>FS1A(FQ9)_C6_L</td>\n",
       "      <td>FS1A</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM03</td>\n",
       "      <td>271.0</td>\n",
       "      <td>[30775, 16354, 10640]</td>\n",
       "      <td>{'SNP(L)': {'pre': 19, 'post': 14, 'downstream...</td>\n",
       "      <td>FB2-6SMPSMP</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2491</th>\n",
       "      <td>983430664</td>\n",
       "      <td>2492</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>FS1A(FQ9)_C3_R</td>\n",
       "      <td>FS1A</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM03</td>\n",
       "      <td>236.0</td>\n",
       "      <td>[16993, 11130, 15072]</td>\n",
       "      <td>{'SNP(R)': {'pre': 37, 'post': 32, 'downstream...</td>\n",
       "      <td>FB2-6SMPSMP</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>87 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              id   key  0.0  0.05  0.1  0.5  0.75  1.0        instance  \\\n",
       "8     1008391068     9    3     2    2    5     5    5  FC2B(FQ7)_C6_L   \n",
       "9     1008693605    10    3     2    2    5     5    9  FC2C(FQ7)_C7_L   \n",
       "12    1009371535    13    3     2    2    5     5   10  FC2B(FQ7)_C3_L   \n",
       "16    1010437434    17    3     2    2    5     5    9  FC2C(FQ7)_C7_L   \n",
       "26    1014102651    27    3     2    2    5     5   20  FS1A(FQ9)_C2_L   \n",
       "...          ...   ...  ...   ...  ...  ...   ...  ...             ...   \n",
       "2475   978681977  2476    3     2    2    5     5   75  FC2C(FQ7)_C3_L   \n",
       "2487   983067799  2488    3     2    2    5     5   20  FS1A(FQ9)_C3_L   \n",
       "2488   983093876  2489    3     2    2    5     5   51  FS1A(FQ9)_C8_L   \n",
       "2490   983426636  2491    3     2    2    5     5   77  FS1A(FQ9)_C6_L   \n",
       "2491   983430664  2492    3     2    2    5     5   20  FS1A(FQ9)_C3_R   \n",
       "\n",
       "     celltype  ...  status  cropped     statusLabel  cellBodyFiber  \\\n",
       "8        FC2B  ...  Traced    False  Roughly traced          PDM03   \n",
       "9        FC2C  ...  Traced    False  Roughly traced          PDM03   \n",
       "12       FC2B  ...  Traced    False  Roughly traced          PDM01   \n",
       "16       FC2C  ...  Traced    False  Roughly traced          PDM03   \n",
       "26       FS1A  ...  Traced    False  Roughly traced          PDM01   \n",
       "...       ...  ...     ...      ...             ...            ...   \n",
       "2475     FC2C  ...  Traced    False  Roughly traced          PDM01   \n",
       "2487     FS1A  ...  Traced    False  Roughly traced          PDM01   \n",
       "2488     FS1A  ...  Traced    False  Roughly traced          PDM04   \n",
       "2490     FS1A  ...  Traced    False  Roughly traced          PDM03   \n",
       "2491     FS1A  ...  Traced    False  Roughly traced          PDM03   \n",
       "\n",
       "      somaRadius           somaLocation  \\\n",
       "8          325.5   [29681, 16321, 7328]   \n",
       "9          291.0  [32830, 14210, 12336]   \n",
       "12         277.5   [28298, 18341, 7600]   \n",
       "16         291.0  [33870, 12655, 13640]   \n",
       "26         301.0  [26807, 16994, 11456]   \n",
       "...          ...                    ...   \n",
       "2475       316.0   [28321, 16270, 9104]   \n",
       "2487       291.0  [29498, 16181, 12232]   \n",
       "2488       261.5  [32853, 11568, 18616]   \n",
       "2490       271.0  [30775, 16354, 10640]   \n",
       "2491       236.0  [16993, 11130, 15072]   \n",
       "\n",
       "                                                roiInfo        notes  \\\n",
       "8     {'CX': {'pre': 167, 'post': 2135, 'downstream'...   FB1d356CRE   \n",
       "9     {'CX': {'pre': 91, 'post': 1051, 'downstream':...   FB1d367CRE   \n",
       "12    {'CX': {'pre': 130, 'post': 2051, 'downstream'...   FB1d356CRE   \n",
       "16    {'CX': {'pre': 83, 'post': 980, 'downstream': ...   FB1d367CRE   \n",
       "26    {'SNP(R)': {'pre': 45, 'post': 34, 'downstream...  FB2-6SMPSMP   \n",
       "...                                                 ...          ...   \n",
       "2475  {'CX': {'pre': 114, 'post': 1408, 'downstream'...   FB1d367CRE   \n",
       "2487  {'SNP(R)': {'pre': 48, 'post': 37, 'downstream...  FB2-6SMPSMP   \n",
       "2488  {'SNP(R)': {'pre': 54, 'post': 50, 'downstream...  FB2-6SMPSMP   \n",
       "2490  {'SNP(L)': {'pre': 19, 'post': 14, 'downstream...  FB2-6SMPSMP   \n",
       "2491  {'SNP(R)': {'pre': 37, 'post': 32, 'downstream...  FB2-6SMPSMP   \n",
       "\n",
       "                                              inputRois  \\\n",
       "8     ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...   \n",
       "9     ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...   \n",
       "12    ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...   \n",
       "16    ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...   \n",
       "26    ['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FB-col...   \n",
       "...                                                 ...   \n",
       "2475  ['AB(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX',...   \n",
       "2487  ['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FB-col...   \n",
       "2488  ['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FBl1',...   \n",
       "2490  ['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...   \n",
       "2491  ['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...   \n",
       "\n",
       "                                             outputRois  \n",
       "8     ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...  \n",
       "9     ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...  \n",
       "12    ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...  \n",
       "16    ['CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX', 'FB', 'F...  \n",
       "26    ['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FB-col...  \n",
       "...                                                 ...  \n",
       "2475  ['AB(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(R)', 'CX',...  \n",
       "2487  ['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FB-col...  \n",
       "2488  ['CRE(-RUB)(L)', 'CRE(L)', 'CX', 'FB', 'FBl2',...  \n",
       "2490  ['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...  \n",
       "2491  ['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...  \n",
       "\n",
       "[87 rows x 26 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the prominent inputs in cluster 3\n",
    "cluster3[cluster3['celltype'].isin(prom_input_types)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems like input cluster 3 is the FB cluster but it also has some other prominent inputs that were in different clusters when we do the modularity on the full oviINr connectome. Input cluster 2 combines things from full clusters 1 and 5 with a little of 4 and 6. This is starting to make me doubt the full clustering a little bit. Also, LAL022 and SMP112 make an appearance in both input clusters 2 and 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>id</th>\n",
       "      <th>key</th>\n",
       "      <th>0.0</th>\n",
       "      <th>0.05</th>\n",
       "      <th>0.1</th>\n",
       "      <th>0.5</th>\n",
       "      <th>0.75</th>\n",
       "      <th>1.0</th>\n",
       "      <th>instance</th>\n",
       "      <th>celltype</th>\n",
       "      <th>...</th>\n",
       "      <th>status</th>\n",
       "      <th>cropped</th>\n",
       "      <th>statusLabel</th>\n",
       "      <th>cellBodyFiber</th>\n",
       "      <th>somaRadius</th>\n",
       "      <th>somaLocation</th>\n",
       "      <th>roiInfo</th>\n",
       "      <th>notes</th>\n",
       "      <th>inputRois</th>\n",
       "      <th>outputRois</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1298</th>\n",
       "      <td>5813022375</td>\n",
       "      <td>1299</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>331</td>\n",
       "      <td>448</td>\n",
       "      <td>563</td>\n",
       "      <td>IB017_R</td>\n",
       "      <td>IB017</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>False</td>\n",
       "      <td>Roughly traced</td>\n",
       "      <td>PDM08</td>\n",
       "      <td>301.0</td>\n",
       "      <td>[20296, 15956, 8416]</td>\n",
       "      <td>{'SNP(R)': {'pre': 338, 'post': 381, 'downstre...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)'...</td>\n",
       "      <td>['ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1356</th>\n",
       "      <td>5813053712</td>\n",
       "      <td>1357</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>276</td>\n",
       "      <td>100</td>\n",
       "      <td>563</td>\n",
       "      <td>IB017(PDM08)_L</td>\n",
       "      <td>IB017</td>\n",
       "      <td>...</td>\n",
       "      <td>Traced</td>\n",
       "      <td>True</td>\n",
       "      <td>Leaves</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>{'SNP(L)': {'pre': 225, 'post': 185, 'downstre...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...</td>\n",
       "      <td>['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              id   key  0.0  0.05  0.1  0.5  0.75  1.0        instance  \\\n",
       "1298  5813022375  1299    2     3    4  331   448  563         IB017_R   \n",
       "1356  5813053712  1357    4     3    4  276   100  563  IB017(PDM08)_L   \n",
       "\n",
       "     celltype  ...  status  cropped     statusLabel  cellBodyFiber  \\\n",
       "1298    IB017  ...  Traced    False  Roughly traced          PDM08   \n",
       "1356    IB017  ...  Traced     True          Leaves            NaN   \n",
       "\n",
       "      somaRadius          somaLocation  \\\n",
       "1298       301.0  [20296, 15956, 8416]   \n",
       "1356         NaN                   NaN   \n",
       "\n",
       "                                                roiInfo notes  \\\n",
       "1298  {'SNP(R)': {'pre': 338, 'post': 381, 'downstre...   NaN   \n",
       "1356  {'SNP(L)': {'pre': 225, 'post': 185, 'downstre...   NaN   \n",
       "\n",
       "                                              inputRois  \\\n",
       "1298  ['ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)'...   \n",
       "1356  ['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...   \n",
       "\n",
       "                                             outputRois  \n",
       "1298  ['ATL(R)', 'CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)'...  \n",
       "1356  ['CRE(-ROB,-RUB)(R)', 'CRE(-RUB)(L)', 'CRE(L)'...  \n",
       "\n",
       "[2 rows x 26 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ovi_in_node_df[ovi_in_node_df['celltype']=='IB017']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I am choosing IB017 and FS1A as the representatives of clusters 2 and 3, respectively. These are also the top 2 most prominent inputs to oviINr by cell type weight."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bodyId_pre</th>\n",
       "      <th>bodyId_post</th>\n",
       "      <th>weight</th>\n",
       "      <th>type_pre</th>\n",
       "      <th>type_post</th>\n",
       "      <th>instance_pre</th>\n",
       "      <th>instance_post</th>\n",
       "      <th>conn_roiInfo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>611015907</td>\n",
       "      <td>423101189</td>\n",
       "      <td>287</td>\n",
       "      <td>SMP176</td>\n",
       "      <td>oviIN</td>\n",
       "      <td>SMP176_R</td>\n",
       "      <td>oviIN_R</td>\n",
       "      <td>{'INP': {'pre': 54, 'post': 53}, 'CRE(R)': {'p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5813087891</td>\n",
       "      <td>423101189</td>\n",
       "      <td>255</td>\n",
       "      <td>SMP544</td>\n",
       "      <td>oviIN</td>\n",
       "      <td>SMP544_R</td>\n",
       "      <td>oviIN_R</td>\n",
       "      <td>{'LX(R)': {'pre': 66, 'post': 65}, 'LAL(R)': {...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1598011458</td>\n",
       "      <td>423101189</td>\n",
       "      <td>243</td>\n",
       "      <td>LAL134</td>\n",
       "      <td>oviIN</td>\n",
       "      <td>LAL134_R</td>\n",
       "      <td>oviIN_R</td>\n",
       "      <td>{'LX(R)': {'pre': 42, 'post': 42}, 'LAL(R)': {...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5813022375</td>\n",
       "      <td>423101189</td>\n",
       "      <td>236</td>\n",
       "      <td>IB017</td>\n",
       "      <td>oviIN</td>\n",
       "      <td>IB017_R</td>\n",
       "      <td>oviIN_R</td>\n",
       "      <td>{'SNP(R)': {'pre': 97, 'post': 97}, 'SMP(R)': ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>448342846</td>\n",
       "      <td>423101189</td>\n",
       "      <td>225</td>\n",
       "      <td>CRE075</td>\n",
       "      <td>oviIN</td>\n",
       "      <td>CRE075_R</td>\n",
       "      <td>oviIN_R</td>\n",
       "      <td>{'INP': {'pre': 199, 'post': 199}, 'CRE(R)': {...</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2519</th>\n",
       "      <td>5901221890</td>\n",
       "      <td>423101189</td>\n",
       "      <td>1</td>\n",
       "      <td>SLP422</td>\n",
       "      <td>oviIN</td>\n",
       "      <td>SLP422_R</td>\n",
       "      <td>oviIN_R</td>\n",
       "      <td>{'SNP(R)': {'pre': 1, 'post': 1}, 'SMP(R)': {'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2520</th>\n",
       "      <td>5901226036</td>\n",
       "      <td>423101189</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>oviIN</td>\n",
       "      <td>None</td>\n",
       "      <td>oviIN_R</td>\n",
       "      <td>{'SNP(R)': {'pre': 1, 'post': 1}, 'SMP(R)': {'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2521</th>\n",
       "      <td>5901230025</td>\n",
       "      <td>423101189</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>oviIN</td>\n",
       "      <td>None</td>\n",
       "      <td>oviIN_R</td>\n",
       "      <td>{'VMNP': {'pre': 1, 'post': 1}, 'VES(R)': {'pr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2522</th>\n",
       "      <td>5901231318</td>\n",
       "      <td>423101189</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>oviIN</td>\n",
       "      <td>None</td>\n",
       "      <td>oviIN_R</td>\n",
       "      <td>{'SNP(L)': {'pre': 1, 'post': 1}, 'SMP(L)': {'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2523</th>\n",
       "      <td>7112624972</td>\n",
       "      <td>423101189</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>oviIN</td>\n",
       "      <td>None</td>\n",
       "      <td>oviIN_R</td>\n",
       "      <td>{'INP': {'pre': 1, 'post': 1}, 'CRE(R)': {'pre...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2524 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      bodyId_pre  bodyId_post  weight type_pre type_post instance_pre  \\\n",
       "0      611015907    423101189     287   SMP176     oviIN     SMP176_R   \n",
       "1     5813087891    423101189     255   SMP544     oviIN     SMP544_R   \n",
       "2     1598011458    423101189     243   LAL134     oviIN     LAL134_R   \n",
       "3     5813022375    423101189     236    IB017     oviIN      IB017_R   \n",
       "4      448342846    423101189     225   CRE075     oviIN     CRE075_R   \n",
       "...          ...          ...     ...      ...       ...          ...   \n",
       "2519  5901221890    423101189       1   SLP422     oviIN     SLP422_R   \n",
       "2520  5901226036    423101189       1     None     oviIN         None   \n",
       "2521  5901230025    423101189       1     None     oviIN         None   \n",
       "2522  5901231318    423101189       1     None     oviIN         None   \n",
       "2523  7112624972    423101189       1     None     oviIN         None   \n",
       "\n",
       "     instance_post                                       conn_roiInfo  \n",
       "0          oviIN_R  {'INP': {'pre': 54, 'post': 53}, 'CRE(R)': {'p...  \n",
       "1          oviIN_R  {'LX(R)': {'pre': 66, 'post': 65}, 'LAL(R)': {...  \n",
       "2          oviIN_R  {'LX(R)': {'pre': 42, 'post': 42}, 'LAL(R)': {...  \n",
       "3          oviIN_R  {'SNP(R)': {'pre': 97, 'post': 97}, 'SMP(R)': ...  \n",
       "4          oviIN_R  {'INP': {'pre': 199, 'post': 199}, 'CRE(R)': {...  \n",
       "...            ...                                                ...  \n",
       "2519       oviIN_R  {'SNP(R)': {'pre': 1, 'post': 1}, 'SMP(R)': {'...  \n",
       "2520       oviIN_R  {'SNP(R)': {'pre': 1, 'post': 1}, 'SMP(R)': {'...  \n",
       "2521       oviIN_R  {'VMNP': {'pre': 1, 'post': 1}, 'VES(R)': {'pr...  \n",
       "2522       oviIN_R  {'SNP(L)': {'pre': 1, 'post': 1}, 'SMP(L)': {'...  \n",
       "2523       oviIN_R  {'INP': {'pre': 1, 'post': 1}, 'CRE(R)': {'pre...  \n",
       "\n",
       "[2524 rows x 8 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# inputs to oviINr\n",
    "from neuprint import fetch_simple_connections\n",
    "ovi_inputs = fetch_simple_connections(None,oviINr_bodyID)\n",
    "ovi_inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>type_pre</th>\n",
       "      <th>weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FS1A</td>\n",
       "      <td>892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IB017</td>\n",
       "      <td>370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SMP052</td>\n",
       "      <td>361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SMP176</td>\n",
       "      <td>299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FC2B</td>\n",
       "      <td>290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>963</th>\n",
       "      <td>CRE060</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>964</th>\n",
       "      <td>CRE059</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>965</th>\n",
       "      <td>SMP412</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>966</th>\n",
       "      <td>CRE052</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>967</th>\n",
       "      <td>SIP074</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>968 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    type_pre  weight\n",
       "0       FS1A     892\n",
       "1      IB017     370\n",
       "2     SMP052     361\n",
       "3     SMP176     299\n",
       "4       FC2B     290\n",
       "..       ...     ...\n",
       "963   CRE060       1\n",
       "964   CRE059       1\n",
       "965   SMP412       1\n",
       "966   CRE052       1\n",
       "967   SIP074       1\n",
       "\n",
       "[968 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# grab only necessary columns\n",
    "ovi_type_inputs = ovi_inputs[['type_pre','weight']]  \n",
    "\n",
    "# collapse ovi_inputs by cell type and sort in descending order\n",
    "ovi_type_inputs = ovi_type_inputs.groupby('type_pre', as_index=False).sum().sort_values(by='weight', ascending=False,ignore_index=True)\n",
    "\n",
    "ovi_type_inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>type_pre</th>\n",
       "      <th>weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FS1A</td>\n",
       "      <td>892</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SMP052</td>\n",
       "      <td>361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SMP176</td>\n",
       "      <td>299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FC2B</td>\n",
       "      <td>290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>SMP383</td>\n",
       "      <td>281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>SMP544</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>LAL134</td>\n",
       "      <td>247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>SMP550</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>CRE075</td>\n",
       "      <td>225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>SMP566</td>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>LAL022</td>\n",
       "      <td>164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>SMP237</td>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>FC2C</td>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>SMP551</td>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>SMP051</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>SMP386</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>pC1e</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>SMP112</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>pC1d</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   type_pre  weight\n",
       "0      FS1A     892\n",
       "1     IB017     370\n",
       "2    SMP052     361\n",
       "3    SMP176     299\n",
       "4      FC2B     290\n",
       "5    SMP383     281\n",
       "6    SMP544     259\n",
       "7    LAL134     247\n",
       "8    SMP550     234\n",
       "9    CRE075     225\n",
       "10   SMP566     203\n",
       "11   LAL022     164\n",
       "12   SMP237     163\n",
       "13     FC2C     161\n",
       "14   SMP551     159\n",
       "15   SMP051     157\n",
       "16   SMP386     156\n",
       "17     pC1e     148\n",
       "18   SMP112     140\n",
       "19     pC1d     140"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the most prominent inputs to oviINr by cell type\n",
    "prominent_ovi_inputs = ovi_type_inputs.head(20)\n",
    "prominent_ovi_inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>892</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IB017</td>\n",
       "      <td>370</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SMP052</td>\n",
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       "      <th>3</th>\n",
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       "      <td>234</td>\n",
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       "      <td>CRE075</td>\n",
       "      <td>225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>SMP566</td>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>LAL022</td>\n",
       "      <td>164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>SMP237</td>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>FC2C</td>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>SMP551</td>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>SMP051</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>SMP386</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>pC1e</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>SMP112</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>pC1d</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>SMP153</td>\n",
       "      <td>137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>CRE077</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>SMP042</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>SMP185</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>SMP520</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>VES047</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>SMP007</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>SMP314</td>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>SMP179</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>OA-VUMa7</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>SMP175</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>SMP556</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>SMP311</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    type_pre  weight\n",
       "0       FS1A     892\n",
       "1      IB017     370\n",
       "2     SMP052     361\n",
       "3     SMP176     299\n",
       "4       FC2B     290\n",
       "5     SMP383     281\n",
       "6     SMP544     259\n",
       "7     LAL134     247\n",
       "8     SMP550     234\n",
       "9     CRE075     225\n",
       "10    SMP566     203\n",
       "11    LAL022     164\n",
       "12    SMP237     163\n",
       "13      FC2C     161\n",
       "14    SMP551     159\n",
       "15    SMP051     157\n",
       "16    SMP386     156\n",
       "17      pC1e     148\n",
       "18    SMP112     140\n",
       "19      pC1d     140\n",
       "20    SMP153     137\n",
       "21    CRE077     133\n",
       "22    SMP042     132\n",
       "23    SMP185     129\n",
       "24    SMP520     125\n",
       "25    VES047     118\n",
       "26    SMP007     109\n",
       "27    SMP314     106\n",
       "28    SMP179     104\n",
       "29  OA-VUMa7     103\n",
       "30    SMP175     103\n",
       "31    SMP556     102\n",
       "32    SMP311     102"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# strongest input types to oviINr based on weight threshold\n",
    "top_ovi_type_inputs = ovi_type_inputs[ovi_type_inputs['weight'] >= 100]\n",
    "top_ovi_type_inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# grab only the syn sites for the most prominent inputs\n",
    "ovi_pre_syns_top20 = ovi_pre_syns[ovi_pre_syns['type_pre'].isin(prominent_ovi_inputs.type_pre)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'het_clusters' 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[16], line 5\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mrandom\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m shuffle\n\u001b[1;32m      3\u001b[0m \u001b[38;5;66;03m# create a color palette for the clusters\u001b[39;00m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;66;03m#cmap = bokeh.palettes.turbo(ovi_in_node_df[res].max())\u001b[39;00m\n\u001b[0;32m----> 5\u001b[0m cmap \u001b[38;5;241m=\u001b[39m bokeh\u001b[38;5;241m.\u001b[39mpalettes\u001b[38;5;241m.\u001b[39mturbo(\u001b[38;5;28mlen\u001b[39m(\u001b[43mhet_clusters\u001b[49m\u001b[38;5;241m.\u001b[39mindex))\n\u001b[1;32m      7\u001b[0m \u001b[38;5;66;03m# Convert the tuple to a list and shuffle it\u001b[39;00m\n\u001b[1;32m      8\u001b[0m cmap_list \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(cmap)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'het_clusters' is not defined"
     ]
    }
   ],
   "source": [
    "import random\n",
    "from random import shuffle\n",
    "# create a color palette for the clusters\n",
    "#cmap = bokeh.palettes.turbo(ovi_in_node_df[res].max())\n",
    "cmap = bokeh.palettes.turbo(len(het_clusters.index))\n",
    "\n",
    "# Convert the tuple to a list and shuffle it\n",
    "cmap_list = list(cmap)\n",
    "random.shuffle(cmap_list)\n",
    "\n",
    "# Convert the list back to a tuple\n",
    "cmap = tuple(cmap_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'ovi_pre_modules' 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[17], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# create a color palette for the clusters\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m cmap \u001b[38;5;241m=\u001b[39m bokeh\u001b[38;5;241m.\u001b[39mpalettes\u001b[38;5;241m.\u001b[39mtol[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mBright\u001b[39m\u001b[38;5;124m'\u001b[39m][\u001b[43movi_pre_modules\u001b[49m[res]\u001b[38;5;241m.\u001b[39mmax()]\n\u001b[1;32m      4\u001b[0m \u001b[38;5;66;03m# make a dict with this cmap\u001b[39;00m\n\u001b[1;32m      5\u001b[0m colormap \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mdict\u001b[39m(\u001b[38;5;28mzip\u001b[39m(ovi_pre_modules[res]\u001b[38;5;241m.\u001b[39msort_values()\u001b[38;5;241m.\u001b[39munique(), cmap))\n",
      "\u001b[0;31mNameError\u001b[0m: name 'ovi_pre_modules' is not defined"
     ]
    }
   ],
   "source": [
    "# create a color palette for the clusters\n",
    "cmap = bokeh.palettes.tol['Bright'][ovi_pre_modules[res].max()]\n",
    "\n",
    "# make a dict with this cmap\n",
    "colormap = dict(zip(ovi_pre_modules[res].sort_values().unique(), cmap))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add the color information to the df\n",
    "ovi_pre_modules['color'] = ovi_pre_modules[res].map(colormap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.io import export_png\n",
    "from bokeh.plotting import figure\n",
    "\n",
    "# make a pretty skeleton with synapses on it showing inputs and outputs in different colors\n",
    "#pmpre = figure(title=\"Post sites from pre-synaptic partners on oviIN_R according to ovi coarse modules\")\n",
    "pmpre = figure(title=\"Synaptic input sites on oviINr colored by coarse oviINr input modules - FS1A inputs only\")\n",
    "pmpre.y_range.flipped = True\n",
    "\n",
    "pmpre.output_backend = \"svg\"\n",
    "\n",
    "# Plot skeleton segments (in 2D)\n",
    "pmpre.segment(x0='x_child', x1='x_parent',\n",
    "          y0='z_child', y1='z_parent',\n",
    "          color='color_child',\n",
    "          source=segments)\n",
    "\n",
    "# default point size is 4\n",
    "pmpre.scatter('x_post', 'z_post', color='color', legend_group='0.0', source=ovi_pre_modules, size=2)\n",
    "pmpre.legend.location = \"bottom_right\"\n",
    "\n",
    "pmpre.xaxis.visible = False\n",
    "pmpre.xgrid.visible = False\n",
    "\n",
    "pmpre.yaxis.visible = False\n",
    "pmpre.ygrid.visible = False\n",
    "\n",
    "pmpre.legend.title = \"module id\"\n",
    "\n",
    "show(pmpre)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.plotting import figure\n",
    "from bokeh.layouts import gridplot\n",
    "from bokeh.io import show\n",
    "from bokeh.io import export_png\n",
    "\n",
    "# make a pretty skeleton with synapses on it showing inputs and outputs in different colors\n",
    "#pmpre = figure(title=\"Post sites from pre-synaptic partners on oviIN_R according to ovi coarse modules\")\n",
    "pmpre = figure(width=500, height=550, title=\"Synaptic input sites on oviINr colored by coarse oviINr input modules - FS1A inputs only \" + res)\n",
    "pmpre.y_range.flipped = True\n",
    "\n",
    "pmpre.output_backend = \"svg\"\n",
    "\n",
    "# Plot skeleton segments (in 2D)\n",
    "pmpre.segment(x0='x_child', x1='x_parent',\n",
    "          y0='z_child', y1='z_parent',\n",
    "          color='color_child',\n",
    "          source=segments)\n",
    "\n",
    "# default point size is 4\n",
    "pmpre.scatter('x_post', 'z_post', color='color', legend_group=res, source=ovi_pre_modules, size=2)\n",
    "pmpre.legend.location = \"bottom_right\"\n",
    "\n",
    "pmpre.xaxis.visible = False\n",
    "pmpre.xgrid.visible = False\n",
    "\n",
    "pmpre.yaxis.visible = False\n",
    "pmpre.ygrid.visible = False\n",
    "\n",
    "pmpre.legend.title = \"module id\"\n",
    "\n",
    "\n",
    "pmpre1 = figure(width=500, height=550, title=\"Synaptic input sites on oviINr colored by coarse oviINr input modules - FS1A inputs only \" + res)\n",
    "pmpre1.y_range.flipped = True\n",
    "\n",
    "pmpre1.output_backend = \"svg\"\n",
    "\n",
    "# Plot skeleton segments (in 2D)\n",
    "pmpre1.segment(x0='y_child', x1='y_parent',\n",
    "          y0='z_child', y1='z_parent',\n",
    "          color='color_child',\n",
    "          source=segments)\n",
    "\n",
    "# default point size is 4\n",
    "pmpre1.scatter('y_post', 'z_post', color='color', legend_group=res, source=ovi_pre_modules, size=2)\n",
    "pmpre1.legend.location = \"top_left\"\n",
    "\n",
    "pmpre1.xaxis.visible = False\n",
    "pmpre1.xgrid.visible = False\n",
    "\n",
    "pmpre1.yaxis.visible = False\n",
    "pmpre1.ygrid.visible = False\n",
    "\n",
    "pmpre1.legend.title = \"module id\"\n",
    "\n",
    "# Create a gridplot with the figures\n",
    "p = gridplot([[pmpre, pmpre1]])\n",
    "\n",
    "# Show the plot\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that prominent inputs are present in each input cluster and there is nothing too divergent about their synaptic organization compared to the patterns seen when all inputs are included. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Synaptic organization by prominent cell types\n",
    "I was curious whether this would look very different the organization by modules. It does look somewhat less organized, but mainly because there are more cell types than coarse modules."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# grab the modularity data for the resolution we want\n",
    "res = '0.0'\n",
    "modular_df = ovi_in_node_df[['id',res]].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# grab only the syn sites for the most prominent inputs\n",
    "ovi_pre_syns_top20 = ovi_pre_syns[ovi_pre_syns['type_pre'].isin(prom_input_types)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merge modularity data onto the synaptic site data\n",
    "ovi_pre_modules = ovi_pre_syns_top20.merge(modular_df, how='inner', left_on='bodyId_pre', right_on='id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ovi_pre_modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "from random import shuffle\n",
    "# create a color palette for the clusters\n",
    "#cmap = bokeh.palettes.turbo(ovi_in_node_df[res].max())\n",
    "cmap = bokeh.palettes.turbo(len(ovi_pre_modules['type_pre'].unique()))\n",
    "\n",
    "# Convert the tuple to a list and shuffle it\n",
    "cmap_list = list(cmap)\n",
    "random.shuffle(cmap_list)\n",
    "\n",
    "# Convert the list back to a tuple\n",
    "cmap = tuple(cmap_list)\n",
    "\n",
    "# this is the official color palette for the coarse modularity for oviINs full connectome\n",
    "colormap = dict(zip(ovi_pre_modules['type_pre'].unique(), cmap))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add the color information to the df\n",
    "ovi_pre_modules['color'] = ovi_pre_modules['type_pre'].map(colormap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.io import export_png\n",
    "from bokeh.plotting import figure\n",
    "\n",
    "# make a pretty skeleton with synapses on it showing inputs and outputs in different colors\n",
    "#pmpre = figure(title=\"Post sites from pre-synaptic partners on oviIN_R according to ovi coarse modules\")\n",
    "pmpre = figure(title=\"Synaptic input sites on oviINr colored by cell type - prominent inputs only\")\n",
    "pmpre.y_range.flipped = True\n",
    "\n",
    "pmpre.output_backend = \"svg\"\n",
    "\n",
    "# Plot skeleton segments (in 2D)\n",
    "# pmpre.segment(x0='x_child', x1='x_parent',\n",
    "#           y0='z_child', y1='z_parent',\n",
    "#           color='color_child',\n",
    "#           source=segments)\n",
    "\n",
    "# default point size is 4\n",
    "pmpre.scatter('x_post', 'z_post', color='color', legend_group='type_pre', source=ovi_pre_modules, size=2)\n",
    "pmpre.legend.location = \"bottom_right\"\n",
    "\n",
    "pmpre.xaxis.visible = False\n",
    "pmpre.xgrid.visible = False\n",
    "\n",
    "pmpre.yaxis.visible = False\n",
    "pmpre.ygrid.visible = False\n",
    "\n",
    "pmpre.legend.title = \"module id\"\n",
    "\n",
    "show(pmpre)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.plotting import figure\n",
    "from bokeh.layouts import gridplot\n",
    "from bokeh.io import show\n",
    "from bokeh.io import export_png\n",
    "\n",
    "# make a pretty skeleton with synapses on it showing inputs and outputs in different colors\n",
    "#pmpre = figure(title=\"Post sites from pre-synaptic partners on oviIN_R according to ovi coarse modules\")\n",
    "pmpre = figure(width=500, height=550, title=\"Synaptic input sites on oviINr colored by cell type - prominent inputs only \" + res)\n",
    "pmpre.y_range.flipped = True\n",
    "\n",
    "pmpre.output_backend = \"svg\"\n",
    "\n",
    "# Plot skeleton segments (in 2D)\n",
    "pmpre.segment(x0='x_child', x1='x_parent',\n",
    "          y0='z_child', y1='z_parent',\n",
    "          color='color_child',\n",
    "          source=segments)\n",
    "\n",
    "# default point size is 4\n",
    "pmpre.scatter('x_post', 'z_post', color='color', legend_group=res, source=ovi_pre_modules, size=2)\n",
    "pmpre.legend.location = \"bottom_right\"\n",
    "\n",
    "pmpre.xaxis.visible = False\n",
    "pmpre.xgrid.visible = False\n",
    "\n",
    "pmpre.yaxis.visible = False\n",
    "pmpre.ygrid.visible = False\n",
    "\n",
    "pmpre.legend.title = \"module id\"\n",
    "\n",
    "\n",
    "pmpre1 = figure(width=500, height=550, title=\"Synaptic input sites on oviINr colored by cell type - prominent inputs only \" + res)\n",
    "pmpre1.y_range.flipped = True\n",
    "\n",
    "pmpre1.output_backend = \"svg\"\n",
    "\n",
    "# Plot skeleton segments (in 2D)\n",
    "pmpre1.segment(x0='y_child', x1='y_parent',\n",
    "          y0='z_child', y1='z_parent',\n",
    "          color='color_child',\n",
    "          source=segments)\n",
    "\n",
    "# default point size is 4\n",
    "pmpre1.scatter('y_post', 'z_post', color='color', legend_group=res, source=ovi_pre_modules, size=2)\n",
    "pmpre1.legend.location = \"top_left\"\n",
    "\n",
    "pmpre1.xaxis.visible = False\n",
    "pmpre1.xgrid.visible = False\n",
    "\n",
    "pmpre1.yaxis.visible = False\n",
    "pmpre1.ygrid.visible = False\n",
    "\n",
    "pmpre1.legend.title = \"module id\"\n",
    "\n",
    "# Create a gridplot with the figures\n",
    "p = gridplot([[pmpre, pmpre1]])\n",
    "\n",
    "# Show the plot\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Wanted to check whether FS1A breaks into separate modules and whether there is anything interesting. It doesn't break up until res 1.0 and there is no perceptible synaptic organization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "syns_FS1A = ovi_pre_syns[ovi_pre_syns['type_pre']=='FS1A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# grab the modularity data for the resolution we want\n",
    "res = '1.0'\n",
    "modular_df = ovi_in_node_df[['id',res]].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ovi_pre_modules = syns_FS1A.merge(modular_df, how='inner', left_on='bodyId_pre', right_on='id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "from random import shuffle\n",
    "# create a color palette for the clusters\n",
    "#cmap = bokeh.palettes.turbo(ovi_in_node_df[res].max())\n",
    "cmap = bokeh.palettes.turbo(len(ovi_pre_modules[res].unique()))\n",
    "\n",
    "# Convert the tuple to a list and shuffle it\n",
    "cmap_list = list(cmap)\n",
    "random.shuffle(cmap_list)\n",
    "\n",
    "# Convert the list back to a tuple\n",
    "cmap = tuple(cmap_list)\n",
    "\n",
    "# this is the official color palette for the coarse modularity for oviINs full connectome\n",
    "colormap = dict(zip(ovi_pre_modules[res].sort_values().unique(), cmap))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add the color information to the df\n",
    "ovi_pre_modules['color'] = ovi_pre_modules[res].map(colormap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.io import export_png\n",
    "from bokeh.plotting import figure\n",
    "\n",
    "# make a pretty skeleton with synapses on it showing inputs and outputs in different colors\n",
    "#pmpre = figure(title=\"Post sites from pre-synaptic partners on oviIN_R according to ovi coarse modules\")\n",
    "pmpre = figure(title=\"Synaptic input sites on oviINr colored by coarse oviINr input modules - FS1A inputs only\")\n",
    "pmpre.y_range.flipped = True\n",
    "\n",
    "pmpre.output_backend = \"svg\"\n",
    "\n",
    "# Plot skeleton segments (in 2D)\n",
    "# pmpre.segment(x0='x_child', x1='x_parent',\n",
    "#           y0='z_child', y1='z_parent',\n",
    "#           color='color_child',\n",
    "#           source=segments)\n",
    "\n",
    "# default point size is 4\n",
    "pmpre.scatter('x_post', 'z_post', color='color', legend_group=res, source=ovi_pre_modules, size=2)\n",
    "pmpre.legend.location = \"bottom_right\"\n",
    "\n",
    "pmpre.xaxis.visible = False\n",
    "pmpre.xgrid.visible = False\n",
    "\n",
    "pmpre.yaxis.visible = False\n",
    "pmpre.ygrid.visible = False\n",
    "\n",
    "pmpre.legend.title = \"module id\"\n",
    "\n",
    "show(pmpre)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.plotting import figure\n",
    "from bokeh.layouts import gridplot\n",
    "from bokeh.io import show\n",
    "from bokeh.io import export_png\n",
    "\n",
    "# make a pretty skeleton with synapses on it showing inputs and outputs in different colors\n",
    "#pmpre = figure(title=\"Post sites from pre-synaptic partners on oviIN_R according to ovi coarse modules\")\n",
    "pmpre = figure(width=500, height=550, title=\"Synaptic input sites on oviINr colored by coarse oviINr input modules - FS1A inputs only \" + res)\n",
    "pmpre.y_range.flipped = True\n",
    "\n",
    "pmpre.output_backend = \"svg\"\n",
    "\n",
    "# Plot skeleton segments (in 2D)\n",
    "pmpre.segment(x0='x_child', x1='x_parent',\n",
    "          y0='z_child', y1='z_parent',\n",
    "          color='color_child',\n",
    "          source=segments)\n",
    "\n",
    "# default point size is 4\n",
    "pmpre.scatter('x_post', 'z_post', color='color', legend_group=res, source=ovi_pre_modules, size=2)\n",
    "pmpre.legend.location = \"bottom_right\"\n",
    "\n",
    "pmpre.xaxis.visible = False\n",
    "pmpre.xgrid.visible = False\n",
    "\n",
    "pmpre.yaxis.visible = False\n",
    "pmpre.ygrid.visible = False\n",
    "\n",
    "pmpre.legend.title = \"module id\"\n",
    "\n",
    "\n",
    "pmpre1 = figure(width=500, height=550, title=\"Synaptic input sites on oviINr colored by coarse oviINr input modules - FS1A inputs only \" + res)\n",
    "pmpre1.y_range.flipped = True\n",
    "\n",
    "pmpre1.output_backend = \"svg\"\n",
    "\n",
    "# Plot skeleton segments (in 2D)\n",
    "pmpre1.segment(x0='y_child', x1='y_parent',\n",
    "          y0='z_child', y1='z_parent',\n",
    "          color='color_child',\n",
    "          source=segments)\n",
    "\n",
    "# default point size is 4\n",
    "pmpre1.scatter('y_post', 'z_post', color='color', legend_group=res, source=ovi_pre_modules, size=2)\n",
    "pmpre1.legend.location = \"top_left\"\n",
    "\n",
    "pmpre1.xaxis.visible = False\n",
    "pmpre1.xgrid.visible = False\n",
    "\n",
    "pmpre1.yaxis.visible = False\n",
    "pmpre1.ygrid.visible = False\n",
    "\n",
    "pmpre1.legend.title = \"module id\"\n",
    "\n",
    "# Create a gridplot with the figures\n",
    "p = gridplot([[pmpre, pmpre1]])\n",
    "\n",
    "# Show the plot\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.plotting import figure\n",
    "from bokeh.layouts import gridplot\n",
    "from bokeh.io import show\n",
    "\n",
    "# Create some data\n",
    "x = list(range(1, 11))\n",
    "y1 = x\n",
    "y2 = [i**2 for i in x]\n",
    "y3 = [i**3 for i in x]\n",
    "\n",
    "# Create three figures\n",
    "p1 = figure(width=250, height=250, title='Linear')\n",
    "p1.line(x, y1, color='red')\n",
    "\n",
    "p2 = figure(width=250, height=250, title='Squared')\n",
    "p2.line(x, y2, color='blue')\n",
    "\n",
    "p3 = figure(width=250, height=250, title='Cubed')\n",
    "p3.line(x, y3, color='green')\n",
    "\n",
    "# Create a gridplot with the figures\n",
    "p = gridplot([[p1, p2], [None, p3]])\n",
    "\n",
    "# Show the plot\n",
    "show(p)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "modularity",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.11"
  }
 },
 "nbformat": 4,
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}