create_edgelist_file.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b17f6962-a251-4502-863b-103c8555c699",
   "metadata": {},
   "source": [
    "This notebook creates a sample edgelist file from the hemibrain data to use with the generalized modularity code from https://github.com/gabrielle9/generalized-modularity-density/tree/main. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "65906f50-5e05-4abc-8eb8-9762f08bac25",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.1.0'"
      ]
     },
     "execution_count": 1,
     "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": 2,
   "id": "02000d4c-7f15-4bb8-9982-51d1251cad25",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "60d1fe24-86ca-4ff1-a3ab-02ab0219f573",
   "metadata": {},
   "outputs": [],
   "source": [
    "# bodyID of oviIN(right)\n",
    "oviINr_bodyID = 423101189"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db32c7be-dffc-487e-bfab-0471fb14b6d5",
   "metadata": {},
   "source": [
    "From prameshsingh's instructions: \"Use an edgelist file including 3 columns (separated by space or tab with no header) with the last one representing the weight. (If the network is unweighted, just put 1 to the whole column. The network should be undirected. Self-loops will be ignored. See example in karate.txt)\"\n",
    "\n",
    "The table created below will be for inputs to oviIN. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eb3e2b57-7355-4837-8fc0-dbe5d0344b9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a table with a column that is oviIN's bodyID, a column that has the bodyIDs of its inputs, and a column of weights\n",
    "\n",
    "from neuprint import fetch_adjacencies\n",
    "\n",
    "neuron_df, conn_df = fetch_adjacencies(None, oviINr_bodyID)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "85465ca3-131e-4753-b88e-8e3e28ffe5bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "edgelist = conn_df[['bodyId_pre','bodyId_post','weight']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2426f463-f700-4897-b656-ea67a970c52d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# export this edgelist without indices or headers\n",
    "edgelist.to_csv('ovi_edgelist.txt', sep=' ', header=False, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d7ec8f6-9a5d-46b3-9fe2-d00f4d26ee8c",
   "metadata": {},
   "source": [
    "Use the exported txt file to run the modularity C code. For my Mac Studio set up, I had to modify the compile command to:\n",
    "`clang main.c help.c rg.c -Xpreprocessor -fopenmp -lomp -lm`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "420e4ea1-e3c8-4b76-9d4d-9e3e2828bf06",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "\n"
     ]
    }
   ],
   "source": [
    "# to preview what the exported edgelist will look like\n",
    "print(edgelist.to_csv(sep=' ',header=False, index=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "913609af-8a10-4240-b81f-184ac7077b85",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "name": "python",
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