notebooks/dfs012_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dfs0/1/2 Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Goal\n",
    "\n",
    "Demonstrate reading in data from DHI MIKE `.dfs0/1/2/` files using `dhitools`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from dhitools import dfs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-------\n",
    "## Outline\n",
    "\n",
    "- Read and plot `dfs0` data\n",
    "- Read and plot `dfs1` data\n",
    "- Read and plot `dfs2` data\n",
    "-------\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Input files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfs0_f = \"data/data_ndr_roese.dfs0\"\n",
    "dfs1_f = \"data/data_moving_bump.dfs1\"\n",
    "dfs2_f = \"data/data_corner.dfs2\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dfs0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read in a `.dfs0` file by parsing the file path to `dfs.Dfs0()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfs0 = dfs.Dfs0(dfs0_f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print out a file summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input file: data/data_ndr_roese.dfs0\n",
      "Time start = 02/12/1993 00:00:00\n",
      "Number of timesteps = 7921\n",
      "Timestep = 120.0\n",
      "Number of items = 5\n",
      "Items:\n",
      "Point 1: Surface elevation, unit = m, index = 0\n",
      "Point 1: U velocity, unit = m/s, index = 1\n",
      "Point 1: V velocity, unit = m/s, index = 2\n",
      "Point 1: Current speed, unit = m/s, index = 3\n",
      "Point 1: Current direction, unit = deg, index = 4\n"
     ]
    }
   ],
   "source": [
    "dfs0.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---------\n",
    "`dfs0` data read in as a `pandas` `DataFrame` indexed by time where each column is one of the `dfs0` items. This is accessed through the `data` attribute:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Point 1: Surface elevation</th>\n",
       "      <th>Point 1: U velocity</th>\n",
       "      <th>Point 1: V velocity</th>\n",
       "      <th>Point 1: Current speed</th>\n",
       "      <th>Point 1: Current direction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1993-12-02 00:00:00</th>\n",
       "      <td>-0.37</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-12-02 00:02:00</th>\n",
       "      <td>-0.37</td>\n",
       "      <td>2.529384e-11</td>\n",
       "      <td>2.248478e-10</td>\n",
       "      <td>2.262660e-10</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-12-02 00:04:00</th>\n",
       "      <td>-0.37</td>\n",
       "      <td>7.784618e-10</td>\n",
       "      <td>6.727129e-09</td>\n",
       "      <td>6.772020e-09</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-12-02 00:06:00</th>\n",
       "      <td>-0.37</td>\n",
       "      <td>5.479619e-09</td>\n",
       "      <td>4.990065e-08</td>\n",
       "      <td>5.020061e-08</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-12-02 00:08:00</th>\n",
       "      <td>-0.37</td>\n",
       "      <td>1.955229e-08</td>\n",
       "      <td>2.072845e-07</td>\n",
       "      <td>2.082046e-07</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Point 1: Surface elevation  Point 1: U velocity  \\\n",
       "1993-12-02 00:00:00                       -0.37         0.000000e+00   \n",
       "1993-12-02 00:02:00                       -0.37         2.529384e-11   \n",
       "1993-12-02 00:04:00                       -0.37         7.784618e-10   \n",
       "1993-12-02 00:06:00                       -0.37         5.479619e-09   \n",
       "1993-12-02 00:08:00                       -0.37         1.955229e-08   \n",
       "\n",
       "                     Point 1: V velocity  Point 1: Current speed  \\\n",
       "1993-12-02 00:00:00         0.000000e+00            0.000000e+00   \n",
       "1993-12-02 00:02:00         2.248478e-10            2.262660e-10   \n",
       "1993-12-02 00:04:00         6.727129e-09            6.772020e-09   \n",
       "1993-12-02 00:06:00         4.990065e-08            5.020061e-08   \n",
       "1993-12-02 00:08:00         2.072845e-07            2.082046e-07   \n",
       "\n",
       "                     Point 1: Current direction  \n",
       "1993-12-02 00:00:00                        90.0  \n",
       "1993-12-02 00:02:00                        90.0  \n",
       "1993-12-02 00:04:00                        90.0  \n",
       "1993-12-02 00:06:00                        90.0  \n",
       "1993-12-02 00:08:00                        90.0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfs0.data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can make use of some of the `pandas` `DataFrame` methods to plot the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfs0_ax = dfs0.data.plot(subplots=True, figsize=(15,15), layout=(5,1))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dfs1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read in a `.dfs1` file by parsing the file path to `dfs.dfs1()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfs1 = dfs.Dfs1(dfs1_f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print out a file summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input file: data/data_moving_bump.dfs1\n",
      "Time start = 01/01/2004 00:00:00\n",
      "Number of timesteps = 161\n",
      "Timestep = 0.01\n",
      "Number of items = 1\n",
      "number of profile points = 2400\n",
      "Items:\n",
      "Concentration - component 1, unit = kg/m^3, index = 0\n"
     ]
    }
   ],
   "source": [
    "dfs1.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "------------\n",
    "Since `.dfs1` files create a profile output for each item (variable) accessing the data is different to `dfs0`. We can see that we have one item in the loaded `dfs1` - \"Concentration - component 1\". To access this call the method `item_data()` with the `item_name` as input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "item_name = dfs1.items[\"names\"][0]\n",
    "concentration_df = dfs1.item_data(item_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This returns a `pandas` `DataFrame` for the requested item indexed by time where each column is an output point along the `dfs1` profile."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>2390</th>\n",
       "      <th>2391</th>\n",
       "      <th>2392</th>\n",
       "      <th>2393</th>\n",
       "      <th>2394</th>\n",
       "      <th>2395</th>\n",
       "      <th>2396</th>\n",
       "      <th>2397</th>\n",
       "      <th>2398</th>\n",
       "      <th>2399</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2004-01-01 00:00:00.000</th>\n",
       "      <td>0.012434</td>\n",
       "      <td>0.013513</td>\n",
       "      <td>0.014592</td>\n",
       "      <td>0.015672</td>\n",
       "      <td>0.016751</td>\n",
       "      <td>0.017830</td>\n",
       "      <td>0.018909</td>\n",
       "      <td>0.019988</td>\n",
       "      <td>0.021067</td>\n",
       "      <td>0.023163</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-01-01 00:00:00.010</th>\n",
       "      <td>0.000296</td>\n",
       "      <td>0.000637</td>\n",
       "      <td>0.000978</td>\n",
       "      <td>0.001319</td>\n",
       "      <td>0.001659</td>\n",
       "      <td>0.002000</td>\n",
       "      <td>0.002341</td>\n",
       "      <td>0.002682</td>\n",
       "      <td>0.003023</td>\n",
       "      <td>0.004083</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-01-01 00:00:00.020</th>\n",
       "      <td>-0.000011</td>\n",
       "      <td>-0.000010</td>\n",
       "      <td>-0.000009</td>\n",
       "      <td>-0.000009</td>\n",
       "      <td>-0.000008</td>\n",
       "      <td>-0.000007</td>\n",
       "      <td>-0.000006</td>\n",
       "      <td>-0.000006</td>\n",
       "      <td>-0.000005</td>\n",
       "      <td>0.000078</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-01-01 00:00:00.030</th>\n",
       "      <td>-0.000005</td>\n",
       "      <td>-0.000006</td>\n",
       "      <td>-0.000006</td>\n",
       "      <td>-0.000007</td>\n",
       "      <td>-0.000007</td>\n",
       "      <td>-0.000008</td>\n",
       "      <td>-0.000008</td>\n",
       "      <td>-0.000009</td>\n",
       "      <td>-0.000009</td>\n",
       "      <td>-0.000010</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-01-01 00:00:00.040</th>\n",
       "      <td>-0.000002</td>\n",
       "      <td>-0.000003</td>\n",
       "      <td>-0.000003</td>\n",
       "      <td>-0.000003</td>\n",
       "      <td>-0.000004</td>\n",
       "      <td>-0.000004</td>\n",
       "      <td>-0.000004</td>\n",
       "      <td>-0.000005</td>\n",
       "      <td>-0.000005</td>\n",
       "      <td>-0.000003</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 2400 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             0         1         2         3         4     \\\n",
       "2004-01-01 00:00:00.000  0.012434  0.013513  0.014592  0.015672  0.016751   \n",
       "2004-01-01 00:00:00.010  0.000296  0.000637  0.000978  0.001319  0.001659   \n",
       "2004-01-01 00:00:00.020 -0.000011 -0.000010 -0.000009 -0.000009 -0.000008   \n",
       "2004-01-01 00:00:00.030 -0.000005 -0.000006 -0.000006 -0.000007 -0.000007   \n",
       "2004-01-01 00:00:00.040 -0.000002 -0.000003 -0.000003 -0.000003 -0.000004   \n",
       "\n",
       "                             5         6         7         8         9     \\\n",
       "2004-01-01 00:00:00.000  0.017830  0.018909  0.019988  0.021067  0.023163   \n",
       "2004-01-01 00:00:00.010  0.002000  0.002341  0.002682  0.003023  0.004083   \n",
       "2004-01-01 00:00:00.020 -0.000007 -0.000006 -0.000006 -0.000005  0.000078   \n",
       "2004-01-01 00:00:00.030 -0.000008 -0.000008 -0.000009 -0.000009 -0.000010   \n",
       "2004-01-01 00:00:00.040 -0.000004 -0.000004 -0.000005 -0.000005 -0.000003   \n",
       "\n",
       "                         ...   2390  2391  2392  2393  2394  2395  2396  2397  \\\n",
       "2004-01-01 00:00:00.000  ...    0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "2004-01-01 00:00:00.010  ...    0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "2004-01-01 00:00:00.020  ...    0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "2004-01-01 00:00:00.030  ...    0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "2004-01-01 00:00:00.040  ...    0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "\n",
       "                         2398  2399  \n",
       "2004-01-01 00:00:00.000   0.0   0.0  \n",
       "2004-01-01 00:00:00.010   0.0   0.0  \n",
       "2004-01-01 00:00:00.020   0.0   0.0  \n",
       "2004-01-01 00:00:00.030   0.0   0.0  \n",
       "2004-01-01 00:00:00.040   0.0   0.0  \n",
       "\n",
       "[5 rows x 2400 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "concentration_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot a few of the profiles:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,5))\n",
    "concentration_df.plot(y=[100, 500, 1000, 1500, 2000], ax=ax, legend=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dfs2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read in a `.dfs2` file by parsing the file path to `dfs.dfs2()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfs2 = dfs.Dfs2(dfs2_f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print out a file summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input file: data/data_corner.dfs2\n",
      "Time start = 01/01/1990 12:00:00\n",
      "Number of timesteps = 181\n",
      "Timestep = 60.0\n",
      "Number of items = 3\n",
      "\n",
      "Projection = \n",
      " UTM-31\n",
      "\n",
      "Grid:\n",
      "(num_X, num_Y) = (31, 31)\n",
      "(del_X, del_Y) = (50.0, 50.0)\n",
      "(X_min, Y_min) = (0.0, 0.0)\n",
      "(X_max, Y_max) = (1550.0, 1550.0)\n",
      "\n",
      "Items:\n",
      "H Water Depth m, unit = m, index = 0\n",
      "P Flux m^3/s/m, unit = m^3/s/m, index = 1\n",
      "Q Flux m^3/s/m, unit = m^3/s/m, index = 2\n"
     ]
    }
   ],
   "source": [
    "dfs2.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-------\n",
    "`.dfs2` files are regular gridded data for each item (variable) across a range of timesteps. The summary provides specifications on the grid - `X,Y` step size, shape, min and max - which are also accessible through the `dfs2` class attributes. We can see that there are three different items within the loaded `dfs2`. To acess the data we call the method `item_data()` with the `item_name` as input.\n",
    "\n",
    "For example, to acess the \"H Water Depth\" data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'H Water Depth m'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "water_depth_name = dfs2.items[\"names\"][0]\n",
    "water_depth_name"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Item data for all timesteps:**\n",
    "\n",
    "If `step_end` = -1, will get read all data from `tstep_start` to end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "water_depth_data_all = dfs2.item_data(water_depth_name, tstep_end=-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This returns a 3-dimensional array by `(X, Y, time)` - that is the `(X,Y)` gridded data at time `t`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(31, 31, 181)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "water_depth_data_all.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Item data for range of timesteps**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "water_depth_data_range = dfs2.item_data(water_depth_name, tstep_start=100, tstep_end=120)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(31, 31, 21)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "water_depth_data_range.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Item data for single timestep**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "water_depth_data_single = dfs2.item_data(water_depth_name, tstep_start=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(31, 31, 1)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "water_depth_data_single.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`dfs2` attributes `X` and `Y` provided `(X,Y)` [numpy.meshgrids](https://docs.scipy.org/doc/numpy-1.15.0/reference/generated/numpy.meshgrid.html) of the underlying grid so that plotting is straightforward"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "\n",
    "cf = ax.contourf(dfs2.X, dfs2.Y, water_depth_data_single[:,:,0])\n",
    "ax.set_title(\"{}; timestep 90\".format(water_depth_name))\n",
    "ax.grid()\n",
    "\n",
    "plt.colorbar(cf)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "dev3",
   "language": "python",
   "name": "dev3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}