{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f8504247",
   "metadata": {},
   "source": [
    "## Network topology"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "import json\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from openpyxl import load_workbook\n",
    "from typing import Dict"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "716f96a9b3ced41e"
  },
  {
   "cell_type": "markdown",
   "source": [
    "##### load input data"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "dcb7731bc5199c48"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "df = pd.read_excel(open('input.xlsx', 'rb'), sheet_name=0)\n",
    "df = df[df.notna()]\n",
    "print(df.columns)"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "9c995a37cd9834ce"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "output = {} # network info"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "fd82ba80087e27ae"
  },
  {
   "cell_type": "markdown",
   "source": [
    "##### topology: edge information"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "72cf999a54207fd3"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "tail = df.t\n",
    "head = df.h\n",
    "tail = tail[~np.isnan(tail)]\n",
    "head = head[~np.isnan(head)]\n",
    "tail = tail.astype(int)\n",
    "head = head.astype(int)\n",
    "ed_ls = [(t, h) for t, h in zip(tail, head)]"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "3b0ea401657601b5"
  },
  {
   "cell_type": "markdown",
   "source": [
    "##### edge attributes (length and diameter)"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "525c2db07f954e25"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "d = df.d\n",
    "l = df.l\n",
    "d = d[~np.isnan(d)]\n",
    "l = l[~np.isnan(l)]"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "169abcb4288e4298"
  },
  {
   "cell_type": "markdown",
   "source": [
    "##### save edge attributes"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "8a2c42d8a124a147"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "output['tail'] = tail\n",
    "output['head'] = head\n",
    "output['l'] = l\n",
    "output['d'] = d\n",
    "output['ed_ls'] = ed_ls"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "4622c3e7c1252482"
  },
  {
   "cell_type": "markdown",
   "source": [
    "##### topology: node information"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "86f0d886edc72d09"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "nodes = df.nodes\n",
    "nodes = nodes[~np.isnan(nodes)]\n",
    "nodes = [int(n) for n in nodes]\n",
    "\n",
    "xpos = df.xpos\n",
    "xpos = xpos[~np.isnan(xpos)]\n",
    "ypos = df.ypos\n",
    "ypos = ypos[~np.isnan(ypos)]\n",
    "zpos = df.zpos\n",
    "zpos = zpos[~np.isnan(zpos)]\n",
    "xyz = [[x, y, z] for x, y, z in zip(xpos, ypos, zpos)]\n"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "8ba9f71e5e72b4fe"
  },
  {
   "cell_type": "markdown",
   "source": [
    "##### save node attributes"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "e1632b1928afe75f"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "output['nodes'] = nodes\n",
    "output['source'] = df.hNode.dropna()\n",
    "output['target'] = df.tNode.dropna()\n",
    "output['xyz'] = xyz"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "3743e0b3ebee71e9"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "with open('input.json', 'w') as f:\n",
    "        json.dump(output, f, indent=2)\n"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "e81e2f213f0a4362"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "28b94ce7-7c0a-4421-ad50-fbe7a0e8c8d5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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