tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyswmm5 as ps\n",
    "from pyswmm5.plot_publication import *\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read .inp file\n",
    "Read .inp file and store data as Pandas dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>raingage</th>\n",
       "      <th>outlet</th>\n",
       "      <th>area</th>\n",
       "      <th>imperv</th>\n",
       "      <th>width</th>\n",
       "      <th>slope</th>\n",
       "      <th>curblen</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A1</th>\n",
       "      <td>YLJ1</td>\n",
       "      <td>J14</td>\n",
       "      <td>0.32</td>\n",
       "      <td>56.8</td>\n",
       "      <td>63.0</td>\n",
       "      <td>0.480</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A2</th>\n",
       "      <td>YLJ1</td>\n",
       "      <td>J17</td>\n",
       "      <td>0.28</td>\n",
       "      <td>65.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>0.900</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A3</th>\n",
       "      <td>YLJ1</td>\n",
       "      <td>J20</td>\n",
       "      <td>0.44</td>\n",
       "      <td>65.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.410</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A4</th>\n",
       "      <td>YLJ1</td>\n",
       "      <td>J29</td>\n",
       "      <td>0.32</td>\n",
       "      <td>55.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0.670</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A5</th>\n",
       "      <td>YLJ1</td>\n",
       "      <td>J35</td>\n",
       "      <td>0.50</td>\n",
       "      <td>65.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZHS41</th>\n",
       "      <td>YLJ1</td>\n",
       "      <td>JB37</td>\n",
       "      <td>0.50</td>\n",
       "      <td>41.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>0.590</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZHS42</th>\n",
       "      <td>YLJ1</td>\n",
       "      <td>JB38</td>\n",
       "      <td>0.86</td>\n",
       "      <td>50.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.620</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZHS43</th>\n",
       "      <td>YLJ1</td>\n",
       "      <td>JB39</td>\n",
       "      <td>0.80</td>\n",
       "      <td>57.6</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0.798</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZHS44</th>\n",
       "      <td>YLJ1</td>\n",
       "      <td>JB40</td>\n",
       "      <td>0.84</td>\n",
       "      <td>60.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.813</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZHS45</th>\n",
       "      <td>YLJ1</td>\n",
       "      <td>JB41</td>\n",
       "      <td>0.23</td>\n",
       "      <td>58.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>102 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      raingage outlet  area  imperv  width  slope  curblen\n",
       "name                                                      \n",
       "A1        YLJ1    J14  0.32    56.8   63.0  0.480      0.0\n",
       "A2        YLJ1    J17  0.28    65.0   60.0  0.900      0.0\n",
       "A3        YLJ1    J20  0.44    65.0   64.0  0.410      0.0\n",
       "A4        YLJ1    J29  0.32    55.0   54.0  0.670      0.0\n",
       "A5        YLJ1    J35  0.50    65.0   60.0  1.000      0.0\n",
       "...        ...    ...   ...     ...    ...    ...      ...\n",
       "ZHS41     YLJ1   JB37  0.50    41.0   55.0  0.590      0.0\n",
       "ZHS42     YLJ1   JB38  0.86    50.0   56.0  0.620      0.0\n",
       "ZHS43     YLJ1   JB39  0.80    57.6   61.0  0.798      0.0\n",
       "ZHS44     YLJ1   JB40  0.84    60.0   64.0  0.813      0.0\n",
       "ZHS45     YLJ1   JB41  0.23    58.0   60.0  0.380      0.0\n",
       "\n",
       "[102 rows x 7 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read inp file\n",
    "swmmInp = ps.SwmmInp('input/uds1.inp')\n",
    "# data were stored in a Pandas dataframe like a spreedsheet.\n",
    "swmmInp.subcatch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 415.44x195.35 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# * visualize distribution of some attributes that you are interested.\n",
    "Fig = FigurePublication(1, 2)\n",
    "sns.set_style('darkgrid')\n",
    "sns.kdeplot(swmmInp.subcatch['area'], ax=Fig.ax[0])\n",
    "sns.histplot(swmmInp.subcatch['area'], ax=Fig.ax[1])\n",
    "Fig.save('output/subcatch.svg')\n",
    "# # improve figure format\n",
    "# Fig.update()\n",
    "# matplotlib.rc('font', **font)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Modify .inp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Change some parameters and options\n",
    "swmmInp.option.loc['HEAD_TOLERANCE', 'value'] = '0.0005'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Export .inp to GIS format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All data are saved in .shp format. 2 files are created.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\ruozh\\anaconda3\\envs\\pyswmm5\\lib\\site-packages\\pyproj\\crs\\crs.py:53: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  return _prepare_from_string(\" \".join(pjargs))\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    }\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>elevation</th>\n",
       "      <th>maxDepth</th>\n",
       "      <th>initDepth</th>\n",
       "      <th>surDepth</th>\n",
       "      <th>aponded</th>\n",
       "      <th>objectType</th>\n",
       "      <th>type</th>\n",
       "      <th>gated</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>J2</th>\n",
       "      <td>192.60</td>\n",
       "      <td>8.30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (5409.879 8479.091)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J6</th>\n",
       "      <td>189.10</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (6105.993 8412.896000000001)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J7</th>\n",
       "      <td>191.92</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (6364.672 9457.120999999999)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J8</th>\n",
       "      <td>188.55</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (5930.993 7032.537)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J9</th>\n",
       "      <td>187.85</td>\n",
       "      <td>3.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (6530.541 7072.617)</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JB38</th>\n",
       "      <td>190.72</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (5329.875 6279.833)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JB39</th>\n",
       "      <td>190.99</td>\n",
       "      <td>3.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (5335.102 5955.752)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JB40</th>\n",
       "      <td>191.64</td>\n",
       "      <td>3.80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (5335.102 5605.535)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JB41</th>\n",
       "      <td>192.20</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (5357.463 5375.252)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>O1</th>\n",
       "      <td>186.30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>outfall</td>\n",
       "      <td>FREE</td>\n",
       "      <td>NO</td>\n",
       "      <td>POINT (7423.426 7451.474)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>103 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      elevation  maxDepth  initDepth  surDepth  aponded objectType  type  \\\n",
       "name                                                                       \n",
       "J2       192.60      8.30        0.0       0.0      0.0   junction   NaN   \n",
       "J6       189.10      4.00        0.0       0.0      0.0   junction   NaN   \n",
       "J7       191.92      2.20        0.0       0.0      0.0   junction   NaN   \n",
       "J8       188.55      3.00        0.0       0.0      0.0   junction   NaN   \n",
       "J9       187.85      3.50        0.0       0.0      0.0   junction   NaN   \n",
       "...         ...       ...        ...       ...      ...        ...   ...   \n",
       "JB38     190.72      5.00        0.0       0.0      0.0   junction   NaN   \n",
       "JB39     190.99      3.04        0.0       0.0      0.0   junction   NaN   \n",
       "JB40     191.64      3.80        0.0       0.0      0.0   junction   NaN   \n",
       "JB41     192.20      3.00        0.0       0.0      0.0   junction   NaN   \n",
       "O1       186.30       NaN        NaN       NaN      NaN    outfall  FREE   \n",
       "\n",
       "     gated                            geometry  \n",
       "name                                            \n",
       "J2     NaN           POINT (5409.879 8479.091)  \n",
       "J6     NaN  POINT (6105.993 8412.896000000001)  \n",
       "J7     NaN  POINT (6364.672 9457.120999999999)  \n",
       "J8     NaN           POINT (5930.993 7032.537)  \n",
       "J9     NaN           POINT (6530.541 7072.617)  \n",
       "...    ...                                 ...  \n",
       "JB38   NaN           POINT (5329.875 6279.833)  \n",
       "JB39   NaN           POINT (5335.102 5955.752)  \n",
       "JB40   NaN           POINT (5335.102 5605.535)  \n",
       "JB41   NaN           POINT (5357.463 5375.252)  \n",
       "O1      NO           POINT (7423.426 7451.474)  \n",
       "\n",
       "[103 rows x 9 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GIS = ps.Swmm2Gis(swmmInp)\n",
    "# Before saving, you can make some edit, like add more columns in link.\n",
    "GIS.save_all('output/test') # files will be stored in this folder\n",
    "GIS.node"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warning: save SYMBOLS section failed.\n",
      "Warning: save TRANSECTS section failed.\n",
      "Warning: save INFLOWS section failed.\n",
      "Warning: save PUMPS section failed.\n",
      "Warning: save ORIFICES section failed.\n",
      "Warning: save WEIRS section failed.\n",
      "Warning: save OUTLETS section failed.\n",
      "Warning: save LOSSES section failed.\n",
      "Warning: save CONTROLS section failed.\n",
      "Warning: save DWF section failed.\n",
      "Warning: save CURVES section failed.\n",
      "Warning: save PATTERNS section failed.\n",
      "The output/testtmp6ad166ae03034d0482663dde564c0158.inp is saved.\n"
     ]
    }
   ],
   "source": [
    "databaseName = swmmInp.run_swmm('output/', filename='test')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Retrieve data from database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>period</th>\n",
       "      <th>precip</th>\n",
       "      <th>loss</th>\n",
       "      <th>runoff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-06-23 00:05:00</td>\n",
       "      <td>23.400000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-06-23 00:10:00</td>\n",
       "      <td>46.799999</td>\n",
       "      <td>9.347492</td>\n",
       "      <td>1.706184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-06-23 00:15:00</td>\n",
       "      <td>61.680000</td>\n",
       "      <td>6.728385</td>\n",
       "      <td>18.085430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-06-23 00:20:00</td>\n",
       "      <td>74.400002</td>\n",
       "      <td>4.851713</td>\n",
       "      <td>30.849947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-06-23 00:25:00</td>\n",
       "      <td>63.720001</td>\n",
       "      <td>3.507019</td>\n",
       "      <td>42.582787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>2014-06-23 11:40:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.108000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2014-06-23 11:45:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.108000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2014-06-23 11:50:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.108000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2014-06-23 11:55:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.108000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2014-06-23 12:00:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.108000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>144 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 period     precip      loss     runoff\n",
       "0   2014-06-23 00:05:00  23.400000  0.000000   0.000000\n",
       "1   2014-06-23 00:10:00  46.799999  9.347492   1.706184\n",
       "2   2014-06-23 00:15:00  61.680000  6.728385  18.085430\n",
       "3   2014-06-23 00:20:00  74.400002  4.851713  30.849947\n",
       "4   2014-06-23 00:25:00  63.720001  3.507019  42.582787\n",
       "..                  ...        ...       ...        ...\n",
       "139 2014-06-23 11:40:00   0.000000  0.108000   0.000000\n",
       "140 2014-06-23 11:45:00   0.000000  0.108000   0.000000\n",
       "141 2014-06-23 11:50:00   0.000000  0.108000   0.000000\n",
       "142 2014-06-23 11:55:00   0.000000  0.108000   0.000000\n",
       "143 2014-06-23 12:00:00   0.000000  0.108000   0.000000\n",
       "\n",
       "[144 rows x 4 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get result\n",
    "swmmRpt = ps.SwmmRpt(databaseName)\n",
    "# get the record of subcatchment A1\n",
    "swmmRpt.get_result_timeseries(objName='A1', objType='subcatch')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initialize visual node: section storage not found.\n",
      "Initialize visual link: section pump not found.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 249.264x209.304 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Fig = FigurePublication(1, 1)\n",
    "# parameter\n",
    "df = swmmRpt.summary_node_flood()\n",
    "floods = df['totalVolume'].tolist()\n",
    "idx = df.index.tolist()\n",
    "# visualize\n",
    "visual = ps.Visualization(swmmInp, ax=Fig.ax, fig=Fig.fig)\n",
    "visual.base_map(linkWidth=1, nodeSize=4)\n",
    "visual.highlight_node(idx, color=floods, nodeSize=16,\n",
    "                      colorbar=True, colorbarRange=(0, 4.5))  # , colorbar=True)\n",
    "Fig.save('output/node.svg')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.11 ('pyswmm5')",
   "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": "3.8.11"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "b997db3363207b7a187f438681103e28f5d8e23c85b532e4703d9f45b34a24e0"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}