simulations_to_csv.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "pregnant-revelation",
   "metadata": {},
   "source": [
    "# Code used to save simulations as .csv files in order to reduce developement time wasted on running simulations over and over again. Csv files were not uploaded since they weigh > 1 gigabyte."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "related-chosen",
   "metadata": {},
   "outputs": [],
   "source": [
    "import wntr\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import networkx as nx\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "premier-bulgarian",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_file = 'Walkerton_v1.inp'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "developing-begin",
   "metadata": {},
   "source": [
    "# Save 2-week simulation without leaks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ideal-enzyme",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\pc\\anaconda3\\envs\\wodociagi\\lib\\site-packages\\scipy\\optimize\\minpack.py:828: OptimizeWarning: Covariance of the parameters could not be estimated\n",
      "  warnings.warn('Covariance of the parameters could not be estimated',\n"
     ]
    }
   ],
   "source": [
    "wn = wntr.network.WaterNetworkModel(data_file)\n",
    "sim = wntr.sim.WNTRSimulator(wn)\n",
    "sim_results = sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "metric-safety",
   "metadata": {},
   "outputs": [],
   "source": [
    "final = pd.concat([sim_results.node['pressure'], sim_results.link['flowrate']], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "improving-channel",
   "metadata": {},
   "outputs": [],
   "source": [
    "final.to_csv(os.path.join(os.getcwd(),'simulations', 'no_leaks', 'sim_nL.csv'), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "distributed-supervisor",
   "metadata": {},
   "outputs": [
    {
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       "<p>337 rows × 679 columns</p>\n",
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      ],
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       "            J1         J2         J3         J4         J5         J6  \\\n",
       "0    36.011416  30.044852  29.924852  31.958688  32.148688  45.531102   \n",
       "1    36.643471  30.803467  30.683467  32.673468  32.863468  45.903506   \n",
       "2    36.438482  30.598478  30.478478  32.468479  32.658479  45.698517   \n",
       "3    36.233493  30.393490  30.273490  32.263490  32.453490  45.493529   \n",
       "4    36.028505  30.188501  30.068501  32.058502  32.248502  45.288540   \n",
       "..         ...        ...        ...        ...        ...        ...   \n",
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       "333  35.028346  29.195079  29.075079  31.062724  31.252724  44.277401   \n",
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       "335  34.415027  28.572417  28.452417  30.443311  30.633311  43.680726   \n",
       "336  34.559477  28.726919  28.606919  30.594317  30.784317  43.804961   \n",
       "\n",
       "            J7         J8         J9        J10  ...      P548      P549  \\\n",
       "0    31.841401  28.841400  33.861399  43.310270  ...  0.005835 -0.001642   \n",
       "1    32.473456  29.473455  34.493454  43.604068  ...  0.001599 -0.000348   \n",
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       "3    32.063479  29.063478  34.083477  43.194090  ...  0.001599 -0.000348   \n",
       "4    31.858490  28.858489  33.878488  42.989102  ...  0.001599 -0.000348   \n",
       "..         ...        ...        ...        ...  ...       ...       ...   \n",
       "332  31.067235  28.067200  33.087205  42.193966  ...  0.002556 -0.000554   \n",
       "333  30.858022  27.857987  32.877978  41.976184  ...  0.001838 -0.000396   \n",
       "334  30.544018  27.543951  32.564005  41.660273  ...  0.001705 -0.000365   \n",
       "335  30.245013  27.245012  32.265011  41.383795  ...  0.002541 -0.000559   \n",
       "336  30.389462  27.389461  32.409460  41.501642  ... -0.000241  0.000100   \n",
       "\n",
       "         P551      P553     PMP51  PMP63   PMP72     FCV51  FCV63   FCV72  \n",
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       "1    0.000072 -0.000008  0.000000    0.0  0.0000  0.000000    0.0  0.0000  \n",
       "2    0.000072 -0.000008  0.000000    0.0  0.0000  0.000000    0.0  0.0000  \n",
       "3    0.000072 -0.000008  0.000000    0.0  0.0000  0.000000    0.0  0.0000  \n",
       "4    0.000072 -0.000008  0.000000    0.0  0.0000  0.000000    0.0  0.0000  \n",
       "..        ...       ...       ...    ...     ...       ...    ...     ...  \n",
       "332 -0.000079 -0.000022  0.000000    0.0  0.0000  0.000000    0.0  0.0000  \n",
       "333 -0.000148 -0.000022  0.000000    0.0  0.0000  0.000000    0.0  0.0000  \n",
       "334 -0.000160 -0.000022  0.000000    0.0  0.0000  0.000000    0.0  0.0000  \n",
       "335  0.000204 -0.000009  0.000000    0.0  0.0000  0.000000    0.0  0.0000  \n",
       "336 -0.000210 -0.000008  0.000000    0.0  0.0000  0.000000    0.0  0.0000  \n",
       "\n",
       "[337 rows x 679 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv(os.path.join(os.getcwd(),'simulations', 'no_leaks', 'sim_nL.csv'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "improved-hormone",
   "metadata": {},
   "source": [
    "# Save simulations with leaks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "sharp-sugar",
   "metadata": {},
   "outputs": [],
   "source": [
    "from dataclasses import dataclass\n",
    "unknown_pressure = -1\n",
    "junctions_with_no_edges = ['JPMP51', 'JPMP63', 'JPMP72', 'R5', 'R6', 'R7']\t\n",
    "\n",
    "@dataclass\n",
    "class Junction:\n",
    "\tname: str\n",
    "\tx: float\n",
    "\ty: float\n",
    "\tpressure: float\n",
    "\n",
    "@dataclass\n",
    "class Pipe:\n",
    "\tname: str\n",
    "\tnode1: str\n",
    "\tnode2: str\n",
    "\tlength: float\n",
    "\tstatus: str\n",
    "\n",
    "def get_node_data(data_file: str) -> [list, list]:\n",
    "\t\"\"\"\n",
    "\tParses .inp file and finds data on pipes and junctions, creates Pipe and Junction objects\n",
    "\tArguments: \t.inp file (str)\n",
    "\tOutput: \t[junctions, pipes] where pipes is a list of pipes and junctions is a list of junctions\n",
    "\t\"\"\"\n",
    "\tjunctions_found = False\n",
    "\tpipes_found = False\n",
    "\tjunctions = []\n",
    "\tpipes = []\n",
    "\n",
    "\twith open(data_file, 'r') as file:\n",
    "\t\tcontent = iter(file.readlines())\t\t\t\t\t\t\t\t\t\t\t\t\t\t# get all content into single var\n",
    "\t\tfor line in content:\n",
    "\t\t\tcurrent_line = line.split()\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# get rid of whitespaces\n",
    "\n",
    "\t\t\tif current_line == ['[PIPES]']:\t\t\t\t\t\t\t\t\t\t\t\t\t\t# look for pipes info section\n",
    "\t\t\t\t\tpipes_found = True\n",
    "\t\t\t\t\tnext(content)\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# skip a line (column headers)\n",
    "\t\t\t\t\tcontinue\n",
    "\t\t\tif current_line == ['[COORDINATES]']:\t\t\t\t\t\t\t\t\t\t\t\t# look for pipes info section\n",
    "\t\t\t\t\tjunctions_found = True\n",
    "\t\t\t\t\tnext(content)\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# skip a line (column headers)\n",
    "\t\t\t\t\tcontinue\n",
    "\n",
    "\t\t\tif pipes_found and not junctions_found:\t\t\t\t\t\t\t\t\t\t\t\t# if in pipes section\n",
    "\t\t\t\tif current_line == []:\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if end of pipes section\n",
    "\t\t\t\t\tpipes_found = False\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# pipes section ends with \\n\n",
    "\t\t\t\t\tcontinue\n",
    "\t\t\t\telse:\n",
    "\t\t\t\t\tname, node1, node2, length, _, _, _, status, _ = current_line\n",
    "\t\t\t\t\tpipes.append(Pipe(name=name,\n",
    "\t\t\t\t\t\tnode1=node1,\n",
    "\t\t\t\t\t\tnode2=node2,\n",
    "\t\t\t\t\t\tlength=length,\n",
    "\t\t\t\t\t\tstatus=status))\n",
    "\n",
    "\t\t\tif junctions_found and not pipes_found:\t\t\t\t\t\t\t\t\t\t\t\t# if in junctions section\n",
    "\t\t\t\tif current_line == []:\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t# if end of junctions section\n",
    "\t\t\t\t\tjunctions_found = False\t\t\t\t\t\t\t\t\t\t\t\t\t\t# junctions section ends with \\n\n",
    "\t\t\t\t\tcontinue\n",
    "\t\t\t\telse:\n",
    "\t\t\t\t\tname, x, y = current_line\n",
    "\t\t\t\t\tjunctions.append(Junction(name=name,\n",
    "\t\t\t\t\t\tx=x,\n",
    "\t\t\t\t\t\ty=y,\n",
    "\t\t\t\t\t\tpressure=unknown_pressure))\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n",
    "\treturn [junctions, pipes]\n",
    "\n",
    "def create_graph() -> nx.classes.graph.Graph:\n",
    "\t\"\"\"\n",
    "\tCreates a NetworkX graph object from lists of nodes and edges taken from .inp file\n",
    "\tArguments: \tnodes - list of Junction() objects\n",
    "\t\t\t\tedges - list of Pipe() objects\n",
    "\tReturns:\tNetworkX graph (networkx.classes.graph.Graph)\n",
    "\t\"\"\"\n",
    "\n",
    "\tprint(\"Creating a NetworkX graph from .inp file (networkx_graph.py - create_graph())\")\n",
    "\n",
    "\t# get data from .inp file\n",
    "\tnodes, edges = get_node_data(data_file)\n",
    "\n",
    "\t# remove junctions with no edges\n",
    "\tnodes = [i for i in nodes if i.name not in junctions_with_no_edges]\n",
    "\n",
    "\t# create a graph object\n",
    "\tG = nx.Graph()\n",
    "\n",
    "\t# add junctions (nodes), specify their coordinates\n",
    "\tfor node in nodes:\n",
    "\t\tG.add_node(node.name, pos=(float(node.x), float(node.y)))\n",
    "\n",
    "\t# add pipes (edges)\n",
    "\tfor edge in edges:\n",
    "\t\tG.add_edge(edge.node1, edge.node2,\n",
    "\t\t\tweight=float(edge.length), name=edge.name)\n",
    "\n",
    "\treturn G \n",
    "\n",
    "def get_sim_results_LEAK(node: str, area: float, start_time: int, end_time: int):\n",
    "\t\"\"\"\n",
    "\tRuns and returns a hydraulic simulation WNTR object (WITH A LEAK)\n",
    "\tArguments:\tnode - node which will have the leak (str)\n",
    "\t\t\t\tarea - area of the leak in (float, meters squared)\n",
    "\t\t\t\tstart_time - when the leak starts (int, hours)\n",
    "\t\t\t\tend_time - when the leak ends (int, hours)\n",
    "\tReturns:\tSimulation results (wntr.sim.results.SimulationResults)\n",
    "\t\"\"\"\n",
    "\twn_leaks = wntr.network.WaterNetworkModel(data_file)\n",
    "\tleak_node = wn_leaks.get_node(node)\n",
    "\tleak_node.add_leak(wn_leaks, area=area, start_time=start_time*3600, end_time=end_time*3600)\n",
    "\tsim_leaks = wntr.sim.WNTRSimulator(wn_leaks)\n",
    "\treturn sim_leaks.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "emotional-armenia",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating a NetworkX graph from .inp file (networkx_graph.py - create_graph())\n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "'T1'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-56-efbd272f2ca8>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mleak_end\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m270\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mnode\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mG\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnodes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m     \u001b[0msim_results_L\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mget_sim_results_LEAK\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnode\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marea\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mleak_area\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstart_time\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mleak_start\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mend_time\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mleak_end\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      8\u001b[0m     \u001b[0mfinal\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconcat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0msim_results_L\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnode\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'pressure'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msim_results_L\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlink\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'flowrate'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m     \u001b[0mfinal\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgetcwd\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'simulations'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'leaks'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'000.5start118end270'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34mf'{node}.csv'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-52-4728377b16ae>\u001b[0m in \u001b[0;36mget_sim_results_LEAK\u001b[1;34m(node, area, start_time, end_time)\u001b[0m\n\u001b[0;32m    110\u001b[0m         \u001b[0mleak_node\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_leak\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwn_leaks\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marea\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0marea\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstart_time\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mstart_time\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;36m3600\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mend_time\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mend_time\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;36m3600\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    111\u001b[0m         \u001b[0msim_leaks\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mwntr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mWNTRSimulator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwn_leaks\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 112\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0msim_leaks\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun_sim\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mc:\\users\\pc\\anaconda3\\envs\\wodociagi\\lib\\site-packages\\wntr\\sim\\core.py\u001b[0m in \u001b[0;36mrun_sim\u001b[1;34m(self, solver, backup_solver, solver_options, backup_solver_options, convergence_error, HW_approx, diagnostics)\u001b[0m\n\u001b[0;32m    887\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mfirst_step\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mresolve\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    888\u001b[0m                 \u001b[0mwntr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhydraulics\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate_tank_heads\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_wn\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 889\u001b[1;33m             \u001b[0mwntr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhydraulics\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate_model_for_controls\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_model\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_wn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_model_updater\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_presolve_controls\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    890\u001b[0m             \u001b[0mwntr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhydraulics\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate_model_for_controls\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_model\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_wn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_model_updater\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_rules\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    891\u001b[0m             \u001b[0mwntr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhydraulics\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate_model_for_controls\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_model\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_wn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_model_updater\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_feasibility_controls\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\pc\\anaconda3\\envs\\wodociagi\\lib\\site-packages\\wntr\\sim\\hydraulics.py\u001b[0m in \u001b[0;36mupdate_model_for_controls\u001b[1;34m(m, wn, model_updater, control_manager)\u001b[0m\n\u001b[0;32m    110\u001b[0m     \"\"\"\n\u001b[0;32m    111\u001b[0m     \u001b[1;32mfor\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mattr\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcontrol_manager\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_changes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 112\u001b[1;33m         \u001b[0mmodel_updater\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mwn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mattr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    113\u001b[0m     \u001b[1;31m# TODO: update model for isolated junctions and links\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    114\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\pc\\anaconda3\\envs\\wodociagi\\lib\\site-packages\\wntr\\sim\\models\\utils.py\u001b[0m in \u001b[0;36mupdate\u001b[1;34m(self, m, wn, obj, attr)\u001b[0m\n\u001b[0;32m     16\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mattr\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate_functions\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     17\u001b[0m             \u001b[1;32mfor\u001b[0m \u001b[0mfunc\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate_functions\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mattr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 18\u001b[1;33m                 \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mwn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mattr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     19\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     20\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\pc\\anaconda3\\envs\\wodociagi\\lib\\site-packages\\wntr\\sim\\models\\utils.py\u001b[0m in \u001b[0;36mupdate\u001b[1;34m(cls, m, wn, updater, obj, attr)\u001b[0m\n\u001b[0;32m     27\u001b[0m     \u001b[1;33m@\u001b[0m\u001b[0mclassmethod\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     28\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mupdate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mwn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mupdater\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mattr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 29\u001b[1;33m         \u001b[0mcls\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbuild\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mwn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mupdater\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindex_over\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     30\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     31\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\pc\\anaconda3\\envs\\wodociagi\\lib\\site-packages\\wntr\\sim\\models\\constraint.py\u001b[0m in \u001b[0;36mbuild\u001b[1;34m(cls, m, wn, updater, index_over)\u001b[0m\n\u001b[0;32m    637\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mnode\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mleak_status\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mnode\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_is_isolated\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    638\u001b[0m                 \u001b[0mleak_rate\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mleak_rate\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mnode_name\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 639\u001b[1;33m                 \u001b[0mh\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mnode_name\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    640\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    641\u001b[0m                 \u001b[0melev\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0melevation\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mnode_name\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\pc\\anaconda3\\envs\\wodociagi\\lib\\site-packages\\wntr\\sim\\aml\\aml.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    405\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    406\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__getitem__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 407\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    408\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    409\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__iter__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 'T1'"
     ]
    }
   ],
   "source": [
    "G = create_graph()\n",
    "\n",
    "leak_area = 0.0005\n",
    "leak_start = 118\n",
    "leak_end = 270\n",
    "for node in G.nodes():\n",
    "    sim_results_L = get_sim_results_LEAK(node=node, area=leak_area, start_time=leak_start, end_time=leak_end)\n",
    "    final = pd.concat([sim_results_L.node['pressure'], sim_results_L.link['flowrate']], axis=1)\n",
    "    final.to_csv(os.path.join(os.getcwd(),'simulations', 'leaks', '000.5start118end270', f'{node}.csv'), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "absent-picnic",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "atlantic-weekly",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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