04 Running PCSE in batch mode.ipynb

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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# A Jupyter notebook demonstrating how to run multiple simulations with PCSE/WOFOST\n",
    "\n",
    "This Jupyter notebook will demonstrate how to implement a loop that can run multiple simulations using PCSE/WOFOST for water-limited conditions. Results are exported to an Excel file.\n",
    "\n",
    "**Prerequisites for running this notebook**\n",
    "\n",
    "Several packages need to be installed for running PCSE/WOFOST:\n",
    "\n",
    "  1. PCSE and its dependencies. See the [PCSE user guide](http://pcse.readthedocs.io/en/stable/installing.html) for more information;\n",
    "  2. The `pandas` module for processing and storing WOFOST output;\n",
    "\n",
    "Finally, you need a working internet connection."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing the relevant modules\n",
    "\n",
    "First the required modules need to be imported. These include the CGMS8 data providers for PCSE as well as other relevant modules.\n",
    "\n",
    "**Important:** For the example we will assume that data files are in the data directory within the directory where this notebook is located. This will be the case if you downloaded the notebooks from github."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This notebook was built with:\n",
      "python version: 3.6.7 |Anaconda, Inc.| (default, Oct 24 2018, 09:45:24) [MSC v.1912 64 bit (AMD64)] \n",
      "PCSE version: 5.4.1\n"
     ]
    }
   ],
   "source": [
    "import os, sys\n",
    "data_dir = os.path.join(os.getcwd(), \"data\")\n",
    "\n",
    "import yaml\n",
    "import pandas as pd\n",
    "\n",
    "import pcse\n",
    "from pcse.fileinput import CABOFileReader\n",
    "from pcse.models import Wofost71_WLP_FD\n",
    "from pcse.base import ParameterProvider\n",
    "from pcse.exceptions import WeatherDataProviderError\n",
    "from pcse.util import WOFOST71SiteDataProvider\n",
    "from pcse.db import NASAPowerWeatherDataProvider\n",
    "\n",
    "print(\"This notebook was built with:\")\n",
    "print(\"python version: %s \" % sys.version)\n",
    "print(\"PCSE version: %s\" %  pcse.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting up the parameters for crop, soil and site\n",
    "\n",
    "Parameter files for crop and soil were taken from the [WOFOST Control Centre](http://www.wageningenur.nl/en/Expertise-Services/Research-Institutes/alterra/Facilities-Products/Software-and-models/WOFOST/Downloads.htm). These parameter file are in the `CABO` format which can be read the with `CABOFileReader` module.\n",
    "### Crop parameter files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "crop_dir = os.path.join(data_dir, 'crop')\n",
    "crop_files = [CABOFileReader(os.path.join(crop_dir,f)) for f in os.listdir(crop_dir) if f.endswith(\"CAB\")]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Soil parameter files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "soil_dir = os.path.join(data_dir, 'soil')\n",
    "soil_files = [CABOFileReader(os.path.join(soil_dir,f)) for f in os.listdir(soil_dir) if f.startswith(\"ec\")]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Site parameters\n",
    "Site parameters are an ancillary class of parameters that are related to a given site. For example, an important parameter is the initial amount of moisture in the soil profile (`WAV`) and the atmospheric CO2 concentration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sited = WOFOST71SiteDataProvider(WAV=100, CO2=360., SMLIM=0.35)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Agromanagement\n",
    "Agromanagement can be defined in a file but often it is easier to define it directly as a string in the YAML format. Because the agromanagement needs to be updated for each year. It can thus be manipulated by string replacement and then parsed by the yaml parser. \n",
    "\n",
    "Here we define three agromanagement scenarios which define a crop calendar (no state or timed events) with suitable sowing dates for maize, potato and sugar beet in the Netherlands."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "agro_maize = \"\"\"\n",
    "- {year}-03-01:\n",
    "    CropCalendar:\n",
    "        crop_name: '{crop}'\n",
    "        variety_name: 'maize'\n",
    "        crop_start_date: {year}-04-15\n",
    "        crop_start_type: sowing\n",
    "        crop_end_date:\n",
    "        crop_end_type: maturity\n",
    "        max_duration: 300\n",
    "    TimedEvents: null\n",
    "    StateEvents: null\n",
    "- {year}-12-01: null\n",
    "\"\"\"\n",
    "\n",
    "agro_potato = \"\"\"\n",
    "- {year}-03-01:\n",
    "    CropCalendar:\n",
    "        crop_name: '{crop}'\n",
    "        variety_name: 'potato'\n",
    "        crop_start_date: {year}-05-01\n",
    "        crop_start_type: sowing\n",
    "        crop_end_date:\n",
    "        crop_end_type: maturity\n",
    "        max_duration: 300\n",
    "    TimedEvents: null\n",
    "    StateEvents: null\n",
    "- {year}-12-01: null\n",
    "\"\"\"\n",
    "\n",
    "agro_sugarbeet = \"\"\"\n",
    "- {year}-03-01:\n",
    "    CropCalendar:\n",
    "        crop_name: '{crop}'\n",
    "        variety_name: 'sugar_beet'\n",
    "        crop_start_date: {year}-05-01\n",
    "        crop_start_type: sowing\n",
    "        crop_end_date: {year}-10-15\n",
    "        crop_end_type: harvest\n",
    "        max_duration: 300\n",
    "    TimedEvents: null\n",
    "    StateEvents: null\n",
    "- {year}-12-01: null\n",
    "\"\"\"\n",
    "agro_templates = [agro_maize, agro_potato, agro_sugarbeet]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Daily weather data\n",
    "\n",
    "Weather data will be derived from the NASA POWER database which provides weather data at a resolution of 0.5x0.5 degree."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Weather data provided by: NASAPowerWeatherDataProvider\n",
      "--------Description---------\n",
      "NASA/POWER SRB/FLASHFlux/MERRA2/GEOS 5.12.4 (FP-IT) 0.5 x 0.5 Degree Daily Averaged Data\n",
      "----Site characteristics----\n",
      "Elevation:    4.7\n",
      "Latitude:  52.000\n",
      "Longitude:  5.000\n",
      "Data available for 1983-07-01 - 2018-10-24\n",
      "Number of missing days: 6\n",
      "\n"
     ]
    }
   ],
   "source": [
    "weatherdata = NASAPowerWeatherDataProvider(longitude=5, latitude=52)\n",
    "print(weatherdata)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exporting weather data\n",
    "Weather data can also be easily exported to a dataframe for further analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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",
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       "    }\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>E0</th>\n",
       "      <th>ELEV</th>\n",
       "      <th>ES0</th>\n",
       "      <th>ET0</th>\n",
       "      <th>IRRAD</th>\n",
       "      <th>LAT</th>\n",
       "      <th>LON</th>\n",
       "      <th>RAIN</th>\n",
       "      <th>TEMP</th>\n",
       "      <th>TMAX</th>\n",
       "      <th>TMIN</th>\n",
       "      <th>VAP</th>\n",
       "      <th>WIND</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DAY</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1983-07-01</th>\n",
       "      <td>0.454710</td>\n",
       "      <td>4.71</td>\n",
       "      <td>0.393797</td>\n",
       "      <td>0.355663</td>\n",
       "      <td>24880000.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.041</td>\n",
       "      <td>13.97</td>\n",
       "      <td>17.42</td>\n",
       "      <td>9.43</td>\n",
       "      <td>12.140438</td>\n",
       "      <td>2.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983-07-02</th>\n",
       "      <td>0.269726</td>\n",
       "      <td>4.71</td>\n",
       "      <td>0.242419</td>\n",
       "      <td>0.238727</td>\n",
       "      <td>10730000.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.023</td>\n",
       "      <td>15.47</td>\n",
       "      <td>19.69</td>\n",
       "      <td>10.67</td>\n",
       "      <td>14.118391</td>\n",
       "      <td>3.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983-07-03</th>\n",
       "      <td>0.461912</td>\n",
       "      <td>4.71</td>\n",
       "      <td>0.401604</td>\n",
       "      <td>0.386445</td>\n",
       "      <td>22930000.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.004</td>\n",
       "      <td>16.68</td>\n",
       "      <td>20.66</td>\n",
       "      <td>12.91</td>\n",
       "      <td>14.062675</td>\n",
       "      <td>1.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983-07-04</th>\n",
       "      <td>0.504645</td>\n",
       "      <td>4.71</td>\n",
       "      <td>0.435744</td>\n",
       "      <td>0.423567</td>\n",
       "      <td>25700000.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>18.28</td>\n",
       "      <td>23.48</td>\n",
       "      <td>12.07</td>\n",
       "      <td>15.882603</td>\n",
       "      <td>1.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983-07-05</th>\n",
       "      <td>0.558129</td>\n",
       "      <td>4.71</td>\n",
       "      <td>0.486323</td>\n",
       "      <td>0.450428</td>\n",
       "      <td>26030000.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.001</td>\n",
       "      <td>20.07</td>\n",
       "      <td>25.29</td>\n",
       "      <td>13.38</td>\n",
       "      <td>18.217738</td>\n",
       "      <td>2.49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  E0  ELEV       ES0       ET0       IRRAD   LAT  LON   RAIN  \\\n",
       "DAY                                                                            \n",
       "1983-07-01  0.454710  4.71  0.393797  0.355663  24880000.0  52.0  5.0  0.041   \n",
       "1983-07-02  0.269726  4.71  0.242419  0.238727  10730000.0  52.0  5.0  0.023   \n",
       "1983-07-03  0.461912  4.71  0.401604  0.386445  22930000.0  52.0  5.0  0.004   \n",
       "1983-07-04  0.504645  4.71  0.435744  0.423567  25700000.0  52.0  5.0  0.000   \n",
       "1983-07-05  0.558129  4.71  0.486323  0.450428  26030000.0  52.0  5.0  0.001   \n",
       "\n",
       "             TEMP   TMAX   TMIN        VAP  WIND  \n",
       "DAY                                               \n",
       "1983-07-01  13.97  17.42   9.43  12.140438  2.48  \n",
       "1983-07-02  15.47  19.69  10.67  14.118391  3.27  \n",
       "1983-07-03  16.68  20.66  12.91  14.062675  1.68  \n",
       "1983-07-04  18.28  23.48  12.07  15.882603  1.17  \n",
       "1983-07-05  20.07  25.29  13.38  18.217738  2.49  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(weatherdata.export()).set_index(\"DAY\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulating with WOFOST\n",
    "\n",
    "### Implementing the main loop\n",
    "The following example implements a loop running over all years, crops and soil types. Daily output for each run is converted to a Pandas DataFrame and written as a separate excel file to an output folder. Summary results from all simulations is written to a separate excel file at the end of the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Placeholder for storing summary results\n",
    "summary_results = []\n",
    "\n",
    "# Years to simulate\n",
    "years = range(2004, 2008)\n",
    "\n",
    "# Loop over crops, soils and years\n",
    "for cropd, agro in zip(crop_files, agro_templates):\n",
    "    crop_type = cropd['CRPNAM']\n",
    "    for soild in soil_files:\n",
    "        soil_type = soild['SOLNAM']\n",
    "        for year in years:\n",
    "            # String to identify this run\n",
    "            run_id = \"{crop}_{soil}_{year}\".format(crop=crop_type, soil=soil_type, year=year)\n",
    "            \n",
    "            # Set the agromanagement with correct year and crop\n",
    "            agromanagement = yaml.load(agro.format(year=year, crop=crop_type))\n",
    "            \n",
    "            # Encapsulate parameters\n",
    "            parameters = ParameterProvider(sitedata=sited, soildata=soild, cropdata=cropd)\n",
    "            \n",
    "            # Start WOFOST, run the simulation \n",
    "            try:\n",
    "                wofost = Wofost71_WLP_FD(parameters, weatherdata, agromanagement)\n",
    "                wofost.run_till_terminate()\n",
    "            except WeatherDataProviderError as e:\n",
    "                msg = \"Runid '%s' failed because of missing weather data.\" % run_id\n",
    "                print(msg)\n",
    "                continue\n",
    "\n",
    "            # convert daily output to Pandas DataFrame and store it\n",
    "            df = pd.DataFrame(wofost.get_output()).set_index(\"day\")\n",
    "            fname = os.path.join(data_dir, \"output\", run_id + \".xls\")\n",
    "            df.to_excel(fname)\n",
    "            \n",
    "            # Collect summary results\n",
    "            r = wofost.get_summary_output()[0]\n",
    "            r['run_id'] = run_id\n",
    "            summary_results.append(r)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Looking at the summary results\n",
    "The summary results output provides a concise overview of the results of all simulations. If you are interested only in the final simulation results it is often more convenient to use the summary results. Moreover, some output (such as the date of anthesis - `DOA`) that is provided in the summary results cannot be easily gathered from the daily output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CTRAT</th>\n",
       "      <th>DOA</th>\n",
       "      <th>DOE</th>\n",
       "      <th>DOH</th>\n",
       "      <th>DOM</th>\n",
       "      <th>DOS</th>\n",
       "      <th>DOV</th>\n",
       "      <th>DVS</th>\n",
       "      <th>LAIMAX</th>\n",
       "      <th>RD</th>\n",
       "      <th>TAGP</th>\n",
       "      <th>TWLV</th>\n",
       "      <th>TWRT</th>\n",
       "      <th>TWSO</th>\n",
       "      <th>TWST</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>run_id</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",
       "      <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>Grain maize 201, N-Germany, Luxembourg_EC1-coarse_2004</th>\n",
       "      <td>28.655894</td>\n",
       "      <td>2004-07-23</td>\n",
       "      <td>2004-04-30</td>\n",
       "      <td>None</td>\n",
       "      <td>2004-10-06</td>\n",
       "      <td>2004-04-15</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.472462</td>\n",
       "      <td>100.0</td>\n",
       "      <td>23116.011118</td>\n",
       "      <td>3742.278665</td>\n",
       "      <td>2014.890189</td>\n",
       "      <td>10889.863394</td>\n",
       "      <td>8483.869059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grain maize 201, N-Germany, Luxembourg_EC1-coarse_2005</th>\n",
       "      <td>27.747049</td>\n",
       "      <td>2005-07-21</td>\n",
       "      <td>2005-05-02</td>\n",
       "      <td>None</td>\n",
       "      <td>2005-10-10</td>\n",
       "      <td>2005-04-15</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.893520</td>\n",
       "      <td>100.0</td>\n",
       "      <td>23553.842350</td>\n",
       "      <td>3363.579026</td>\n",
       "      <td>1835.849464</td>\n",
       "      <td>12706.248769</td>\n",
       "      <td>7484.014555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grain maize 201, N-Germany, Luxembourg_EC1-coarse_2006</th>\n",
       "      <td>20.133870</td>\n",
       "      <td>2006-07-14</td>\n",
       "      <td>2006-05-04</td>\n",
       "      <td>None</td>\n",
       "      <td>2006-09-17</td>\n",
       "      <td>2006-04-15</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.870312</td>\n",
       "      <td>100.0</td>\n",
       "      <td>16019.973791</td>\n",
       "      <td>3503.754233</td>\n",
       "      <td>2254.225934</td>\n",
       "      <td>7457.018841</td>\n",
       "      <td>5059.200717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grain maize 201, N-Germany, Luxembourg_EC1-coarse_2007</th>\n",
       "      <td>30.025318</td>\n",
       "      <td>2007-07-12</td>\n",
       "      <td>2007-04-28</td>\n",
       "      <td>None</td>\n",
       "      <td>2007-09-28</td>\n",
       "      <td>2007-04-15</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.663145</td>\n",
       "      <td>100.0</td>\n",
       "      <td>26315.415801</td>\n",
       "      <td>3800.572923</td>\n",
       "      <td>2085.756642</td>\n",
       "      <td>13959.813172</td>\n",
       "      <td>8555.029706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grain maize 201, N-Germany, Luxembourg_EC2-medium_2004</th>\n",
       "      <td>29.172785</td>\n",
       "      <td>2004-07-23</td>\n",
       "      <td>2004-04-30</td>\n",
       "      <td>None</td>\n",
       "      <td>2004-10-06</td>\n",
       "      <td>2004-04-15</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.472462</td>\n",
       "      <td>100.0</td>\n",
       "      <td>23459.903976</td>\n",
       "      <td>3742.278665</td>\n",
       "      <td>2014.890189</td>\n",
       "      <td>11233.756251</td>\n",
       "      <td>8483.869059</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                        CTRAT         DOA  \\\n",
       "run_id                                                                      \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  28.655894  2004-07-23   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  27.747049  2005-07-21   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  20.133870  2006-07-14   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  30.025318  2007-07-12   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC2-medi...  29.172785  2004-07-23   \n",
       "\n",
       "                                                           DOE   DOH  \\\n",
       "run_id                                                                 \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  2004-04-30  None   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  2005-05-02  None   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  2006-05-04  None   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  2007-04-28  None   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC2-medi...  2004-04-30  None   \n",
       "\n",
       "                                                           DOM         DOS  \\\n",
       "run_id                                                                       \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  2004-10-06  2004-04-15   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  2005-10-10  2005-04-15   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  2006-09-17  2006-04-15   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  2007-09-28  2007-04-15   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC2-medi...  2004-10-06  2004-04-15   \n",
       "\n",
       "                                                     DOV  DVS    LAIMAX  \\\n",
       "run_id                                                                    \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  None  2.0  5.472462   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  None  2.0  4.893520   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  None  2.0  4.870312   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  None  2.0  5.663145   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC2-medi...  None  2.0  5.472462   \n",
       "\n",
       "                                                       RD          TAGP  \\\n",
       "run_id                                                                    \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  100.0  23116.011118   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  100.0  23553.842350   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  100.0  16019.973791   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  100.0  26315.415801   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC2-medi...  100.0  23459.903976   \n",
       "\n",
       "                                                           TWLV         TWRT  \\\n",
       "run_id                                                                         \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  3742.278665  2014.890189   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  3363.579026  1835.849464   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  3503.754233  2254.225934   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  3800.572923  2085.756642   \n",
       "Grain maize 201, N-Germany, Luxembourg_EC2-medi...  3742.278665  2014.890189   \n",
       "\n",
       "                                                            TWSO         TWST  \n",
       "run_id                                                                         \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  10889.863394  8483.869059  \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  12706.248769  7484.014555  \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...   7457.018841  5059.200717  \n",
       "Grain maize 201, N-Germany, Luxembourg_EC1-coar...  13959.813172  8555.029706  \n",
       "Grain maize 201, N-Germany, Luxembourg_EC2-medi...  11233.756251  8483.869059  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Write the summary results to an excel file\n",
    "df_summary = pd.DataFrame(summary_results).set_index('run_id')\n",
    "fname = os.path.join(data_dir, \"output\", \"summary_results.xls\")\n",
    "df_summary.to_excel(fname)\n",
    "df_summary.head()"
   ]
  },
  {
   "attachments": {
    "batch_output.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Looking at the daily results\n",
    "The excel files with the results from the batch simulation in the output folder should look like the figure below. Each excel file provides the results from a combination of crop, soil type and year: \n",
    "![batch_output.png](attachment:batch_output.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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