{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from idf_analysis.idf_class import IntensityDurationFrequencyAnalyse\n",
    "from idf_analysis.definitions import *\n",
    "import pandas as pd\n",
    "from os import path\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('bmh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Intensity Duration Frequency Analyse"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parameter\n",
    "\n",
    "**series_kind**:\n",
    "\n",
    "`SERIES.PARTIAL` = Partielle Serie (partial duration series, PDS) (peak over threshold, POT)\n",
    "\n",
    "`SERIES.ANNUAL` = Jährliche Serie (annual maximum series, AMS)\n",
    "\n",
    "**worksheet**:\n",
    "\n",
    "`METHOD.KOSTRA`:\n",
    "- DWA-A 531\n",
    "- KOSTRA - empfohlen\n",
    "- Stützstellen: 60 min und 12 h\n",
    "\n",
    "`METHOD.CONVECTIVE_ADVECTIVE`:\n",
    "- DWA-A 531\n",
    "- Unterscheidung in überwiegend konvektiv und advektiv verursachte Starkregen\n",
    "- Stützstellen: 3 h und 24 h\n",
    "\n",
    "`METHOD.ATV`:\n",
    "- ATV-A 121\n",
    "- Stützstellen: 3 h und 48 h\n",
    "\n",
    "**extended_durations** = Inkludiert die Dauerstufen `[0.75d, 1d, 2d, 3d, 4d, 5d, 6d]` in der Analyse (in d=Tage)\n",
    "\n",
    "Standardmäßig berechnete Dauerstufen `[5m, 10m, 15m, 20m, 30m, 45m, 60m, 1.5h, 3h, 4.5h, 6h, 7.5h, 10h, 12h]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "idf = IntensityDurationFrequencyAnalyse(series_kind=SERIES.PARTIAL, worksheet=METHOD.KOSTRA, extended_durations=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I used the rain-time-series from ehyd.gv.at with the ID 112086 (Graz-Andritz) [created with the ehyd-tools package](https://github.com/MarkusPic/ehyd_tools/blob/main/example/example_python_api.ipynb). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "data = pd.read_parquet('ehyd_112086.parquet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "output_directory = 'ehyd_112086_idf_data'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": "                     precipitation\ndatetime                          \n2007-09-18 11:09:00            0.1\n2007-09-18 11:12:00            0.1\n2007-09-18 11:13:00            0.1\n2007-09-18 11:14:00            0.1\n2007-09-18 11:20:00            0.1",
      "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>precipitation</th>\n    </tr>\n    <tr>\n      <th>datetime</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2007-09-18 11:09:00</th>\n      <td>0.1</td>\n    </tr>\n    <tr>\n      <th>2007-09-18 11:12:00</th>\n      <td>0.1</td>\n    </tr>\n    <tr>\n      <th>2007-09-18 11:13:00</th>\n      <td>0.1</td>\n    </tr>\n    <tr>\n      <th>2007-09-18 11:14:00</th>\n      <td>0.1</td>\n    </tr>\n    <tr>\n      <th>2007-09-18 11:20:00</th>\n      <td>0.1</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": "                     precipitation\ndatetime                          \n2016-12-28 22:24:00          0.006\n2016-12-28 22:25:00          0.092\n2016-12-28 22:26:00          0.006\n2016-12-28 22:45:00          0.090\n2016-12-28 22:46:00          0.006",
      "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>precipitation</th>\n    </tr>\n    <tr>\n      <th>datetime</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2016-12-28 22:24:00</th>\n      <td>0.006</td>\n    </tr>\n    <tr>\n      <th>2016-12-28 22:25:00</th>\n      <td>0.092</td>\n    </tr>\n    <tr>\n      <th>2016-12-28 22:26:00</th>\n      <td>0.006</td>\n    </tr>\n    <tr>\n      <th>2016-12-28 22:45:00</th>\n      <td>0.090</td>\n    </tr>\n    <tr>\n      <th>2016-12-28 22:46:00</th>\n      <td>0.006</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "idf.set_series(data['precipitation'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bei jeder neuen Berechnung werden Zwischenergebnisse erstellt, welche nur abhängig von der gewählten Serie `series_kind` und der angegebenen/benötigten Dauerstufen sind. Dieser Vorgang dauert einige Sekunden.\n",
    "Auserdem enthalten diese Zwischenergebnisse die Parameter, die zur Berechnung der Regenhöhe und Regenspende benötigt werden.\n",
    "Hier sind bereist die Berechnungsverfahren und Stückpunkte laut dem gewählten `worksheet` berücksichtigt."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Um Zeit zu sparen, gibt es die Möglichkeit, die Parameter zwischenzuspeichern und bei erneutem Aufrufen des Skripts werden diese Parameter nicht mehr berechnet, sondern aus der Datei gelesen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "idf.auto_save_parameters(path.join(output_directory, 'idf_parameters.yaml'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Abgerufen können diese Zwischenergebnisse mit:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<idf_analysis.idf_parameters.IdfParameters at 0x1a767557310>"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idf.parameters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Berechnungen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": "19.031596336052708"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idf.depth_of_rainfall(duration=15, return_period=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Resultierende Regenhöhe h_N(T_n=1.0a, D=15.0min) = 19.03 mm\n"
     ]
    }
   ],
   "source": [
    "print('Resultierende Regenhöhe h_N(T_n={t:0.1f}a, D={d:0.1f}min) = {h:0.2f} mm'\n",
    "      ''.format(t=1, d=15, h=idf.depth_of_rainfall(15, 1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": "211.46218151169674"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idf.rain_flow_rate(duration=15, return_period=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Resultierende Regenspende r_N(T_n=1.0a, D=15.0min) = 211.46 L/(s*ha)\n"
     ]
    }
   ],
   "source": [
    "print('Resultierende Regenspende r_N(T_n={t:0.1f}a, D={d:0.1f}min) = {r:0.2f} L/(s*ha)'\n",
    "      ''.format(t=1, d=15, r=idf.rain_flow_rate(15, 1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": "11.410836729727"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idf.r_720_1()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": "0.1430180144131331"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idf.get_return_period(height_of_rainfall=10, duration=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": "5.433080747189968"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idf.get_duration(height_of_rainfall=10, return_period=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "        1       2       3       5       10      20      25      30      50   \\\n5      9.39   10.97   11.89   13.04   14.61   16.19   16.69   17.11   18.26   \n10    15.15   17.62   19.06   20.88   23.35   25.82   26.62   27.27   29.09   \n15    19.03   22.25   24.13   26.51   29.72   32.94   33.98   34.83   37.20   \n20    21.83   25.71   27.99   30.85   34.73   38.62   39.87   40.89   43.75   \n30    25.60   30.66   33.62   37.35   42.41   47.47   49.10   50.43   54.16   \n45    28.92   35.51   39.37   44.23   50.83   57.42   59.54   61.28   66.14   \n60    30.93   38.89   43.54   49.40   57.36   65.31   67.88   69.97   75.83   \n90    33.37   41.74   46.64   52.80   61.17   69.54   72.23   74.43   80.60   \n120   35.22   43.90   48.97   55.36   64.03   72.70   75.49   77.78   84.17   \n180   38.01   47.13   52.46   59.18   68.30   77.42   80.36   82.76   89.48   \n240   40.12   49.57   55.10   62.06   71.51   80.97   84.01   86.49   93.46   \n360   43.29   53.23   59.04   66.37   76.31   86.25   89.45   92.06   99.39   \n540   46.71   57.16   63.27   70.98   81.43   91.89   95.25   98.00  105.71   \n720   49.29   60.13   66.47   74.45   85.29   96.12   99.61  102.46  110.44   \n1080  54.41   64.97   71.15   78.94   89.50  100.06  103.46  106.24  114.02   \n1440  58.02   67.72   73.39   80.54   90.24   99.93  103.05  105.61  112.75   \n2880  66.70   77.41   83.68   91.57  102.29  113.00  116.45  119.26  127.16   \n4320  71.93   85.72   93.78  103.95  117.73  131.52  135.96  139.58  149.75   \n5760  78.95   95.65  105.42  117.72  134.43  151.13  156.50  160.89  173.20   \n7200  83.53  101.38  111.82  124.98  142.83  160.68  166.43  171.12  184.28   \n8640  85.38  104.95  116.40  130.82  150.38  169.95  176.25  181.40  195.82   \n\n         75      100  \n5      19.18   19.83  \n10     30.54   31.56  \n15     39.08   40.42  \n20     46.02   47.63  \n30     57.12   59.22  \n45     69.99   72.73  \n60     80.49   83.79  \n90     85.49   88.96  \n120    89.24   92.84  \n180    94.81   98.60  \n240    98.99  102.91  \n360   105.20  109.33  \n540   111.82  116.16  \n720   116.78  121.28  \n1080  120.20  124.58  \n1440  118.42  122.45  \n2880  133.42  137.87  \n4320  157.81  163.53  \n5760  182.97  189.90  \n7200  194.72  202.13  \n8640  207.27  215.39  ",
      "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>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>5</th>\n      <th>10</th>\n      <th>20</th>\n      <th>25</th>\n      <th>30</th>\n      <th>50</th>\n      <th>75</th>\n      <th>100</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>5</th>\n      <td>9.39</td>\n      <td>10.97</td>\n      <td>11.89</td>\n      <td>13.04</td>\n      <td>14.61</td>\n      <td>16.19</td>\n      <td>16.69</td>\n      <td>17.11</td>\n      <td>18.26</td>\n      <td>19.18</td>\n      <td>19.83</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>15.15</td>\n      <td>17.62</td>\n      <td>19.06</td>\n      <td>20.88</td>\n      <td>23.35</td>\n      <td>25.82</td>\n      <td>26.62</td>\n      <td>27.27</td>\n      <td>29.09</td>\n      <td>30.54</td>\n      <td>31.56</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>19.03</td>\n      <td>22.25</td>\n      <td>24.13</td>\n      <td>26.51</td>\n      <td>29.72</td>\n      <td>32.94</td>\n      <td>33.98</td>\n      <td>34.83</td>\n      <td>37.20</td>\n      <td>39.08</td>\n      <td>40.42</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>21.83</td>\n      <td>25.71</td>\n      <td>27.99</td>\n      <td>30.85</td>\n      <td>34.73</td>\n      <td>38.62</td>\n      <td>39.87</td>\n      <td>40.89</td>\n      <td>43.75</td>\n      <td>46.02</td>\n      <td>47.63</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>25.60</td>\n      <td>30.66</td>\n      <td>33.62</td>\n      <td>37.35</td>\n      <td>42.41</td>\n      <td>47.47</td>\n      <td>49.10</td>\n      <td>50.43</td>\n      <td>54.16</td>\n      <td>57.12</td>\n      <td>59.22</td>\n    </tr>\n    <tr>\n      <th>45</th>\n      <td>28.92</td>\n      <td>35.51</td>\n      <td>39.37</td>\n      <td>44.23</td>\n      <td>50.83</td>\n      <td>57.42</td>\n      <td>59.54</td>\n      <td>61.28</td>\n      <td>66.14</td>\n      <td>69.99</td>\n      <td>72.73</td>\n    </tr>\n    <tr>\n      <th>60</th>\n      <td>30.93</td>\n      <td>38.89</td>\n      <td>43.54</td>\n      <td>49.40</td>\n      <td>57.36</td>\n      <td>65.31</td>\n      <td>67.88</td>\n      <td>69.97</td>\n      <td>75.83</td>\n      <td>80.49</td>\n      <td>83.79</td>\n    </tr>\n    <tr>\n      <th>90</th>\n      <td>33.37</td>\n      <td>41.74</td>\n      <td>46.64</td>\n      <td>52.80</td>\n      <td>61.17</td>\n      <td>69.54</td>\n      <td>72.23</td>\n      <td>74.43</td>\n      <td>80.60</td>\n      <td>85.49</td>\n      <td>88.96</td>\n    </tr>\n    <tr>\n      <th>120</th>\n      <td>35.22</td>\n      <td>43.90</td>\n      <td>48.97</td>\n      <td>55.36</td>\n      <td>64.03</td>\n      <td>72.70</td>\n      <td>75.49</td>\n      <td>77.78</td>\n      <td>84.17</td>\n      <td>89.24</td>\n      <td>92.84</td>\n    </tr>\n    <tr>\n      <th>180</th>\n      <td>38.01</td>\n      <td>47.13</td>\n      <td>52.46</td>\n      <td>59.18</td>\n      <td>68.30</td>\n      <td>77.42</td>\n      <td>80.36</td>\n      <td>82.76</td>\n      <td>89.48</td>\n      <td>94.81</td>\n      <td>98.60</td>\n    </tr>\n    <tr>\n      <th>240</th>\n      <td>40.12</td>\n      <td>49.57</td>\n      <td>55.10</td>\n      <td>62.06</td>\n      <td>71.51</td>\n      <td>80.97</td>\n      <td>84.01</td>\n      <td>86.49</td>\n      <td>93.46</td>\n      <td>98.99</td>\n      <td>102.91</td>\n    </tr>\n    <tr>\n      <th>360</th>\n      <td>43.29</td>\n      <td>53.23</td>\n      <td>59.04</td>\n      <td>66.37</td>\n      <td>76.31</td>\n      <td>86.25</td>\n      <td>89.45</td>\n      <td>92.06</td>\n      <td>99.39</td>\n      <td>105.20</td>\n      <td>109.33</td>\n    </tr>\n    <tr>\n      <th>540</th>\n      <td>46.71</td>\n      <td>57.16</td>\n      <td>63.27</td>\n      <td>70.98</td>\n      <td>81.43</td>\n      <td>91.89</td>\n      <td>95.25</td>\n      <td>98.00</td>\n      <td>105.71</td>\n      <td>111.82</td>\n      <td>116.16</td>\n    </tr>\n    <tr>\n      <th>720</th>\n      <td>49.29</td>\n      <td>60.13</td>\n      <td>66.47</td>\n      <td>74.45</td>\n      <td>85.29</td>\n      <td>96.12</td>\n      <td>99.61</td>\n      <td>102.46</td>\n      <td>110.44</td>\n      <td>116.78</td>\n      <td>121.28</td>\n    </tr>\n    <tr>\n      <th>1080</th>\n      <td>54.41</td>\n      <td>64.97</td>\n      <td>71.15</td>\n      <td>78.94</td>\n      <td>89.50</td>\n      <td>100.06</td>\n      <td>103.46</td>\n      <td>106.24</td>\n      <td>114.02</td>\n      <td>120.20</td>\n      <td>124.58</td>\n    </tr>\n    <tr>\n      <th>1440</th>\n      <td>58.02</td>\n      <td>67.72</td>\n      <td>73.39</td>\n      <td>80.54</td>\n      <td>90.24</td>\n      <td>99.93</td>\n      <td>103.05</td>\n      <td>105.61</td>\n      <td>112.75</td>\n      <td>118.42</td>\n      <td>122.45</td>\n    </tr>\n    <tr>\n      <th>2880</th>\n      <td>66.70</td>\n      <td>77.41</td>\n      <td>83.68</td>\n      <td>91.57</td>\n      <td>102.29</td>\n      <td>113.00</td>\n      <td>116.45</td>\n      <td>119.26</td>\n      <td>127.16</td>\n      <td>133.42</td>\n      <td>137.87</td>\n    </tr>\n    <tr>\n      <th>4320</th>\n      <td>71.93</td>\n      <td>85.72</td>\n      <td>93.78</td>\n      <td>103.95</td>\n      <td>117.73</td>\n      <td>131.52</td>\n      <td>135.96</td>\n      <td>139.58</td>\n      <td>149.75</td>\n      <td>157.81</td>\n      <td>163.53</td>\n    </tr>\n    <tr>\n      <th>5760</th>\n      <td>78.95</td>\n      <td>95.65</td>\n      <td>105.42</td>\n      <td>117.72</td>\n      <td>134.43</td>\n      <td>151.13</td>\n      <td>156.50</td>\n      <td>160.89</td>\n      <td>173.20</td>\n      <td>182.97</td>\n      <td>189.90</td>\n    </tr>\n    <tr>\n      <th>7200</th>\n      <td>83.53</td>\n      <td>101.38</td>\n      <td>111.82</td>\n      <td>124.98</td>\n      <td>142.83</td>\n      <td>160.68</td>\n      <td>166.43</td>\n      <td>171.12</td>\n      <td>184.28</td>\n      <td>194.72</td>\n      <td>202.13</td>\n    </tr>\n    <tr>\n      <th>8640</th>\n      <td>85.38</td>\n      <td>104.95</td>\n      <td>116.40</td>\n      <td>130.82</td>\n      <td>150.38</td>\n      <td>169.95</td>\n      <td>176.25</td>\n      <td>181.40</td>\n      <td>195.82</td>\n      <td>207.27</td>\n      <td>215.39</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idf.result_table().round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "return period (a)    1       2       3       5       10      20      25   \\\nfrequency (1/a)    1.000   0.500   0.333   0.200   0.100   0.050   0.040   \nduration (min)                                                             \n5                   9.39   10.97   11.89   13.04   14.61   16.19   16.69   \n10                 15.15   17.62   19.06   20.88   23.35   25.82   26.62   \n15                 19.03   22.25   24.13   26.51   29.72   32.94   33.98   \n20                 21.83   25.71   27.99   30.85   34.73   38.62   39.87   \n30                 25.60   30.66   33.62   37.35   42.41   47.47   49.10   \n45                 28.92   35.51   39.37   44.23   50.83   57.42   59.54   \n60                 30.93   38.89   43.54   49.40   57.36   65.31   67.88   \n90                 33.37   41.74   46.64   52.80   61.17   69.54   72.23   \n120                35.22   43.90   48.97   55.36   64.03   72.70   75.49   \n180                38.01   47.13   52.46   59.18   68.30   77.42   80.36   \n240                40.12   49.57   55.10   62.06   71.51   80.97   84.01   \n360                43.29   53.23   59.04   66.37   76.31   86.25   89.45   \n540                46.71   57.16   63.27   70.98   81.43   91.89   95.25   \n720                49.29   60.13   66.47   74.45   85.29   96.12   99.61   \n1080               54.41   64.97   71.15   78.94   89.50  100.06  103.46   \n1440               58.02   67.72   73.39   80.54   90.24   99.93  103.05   \n2880               66.70   77.41   83.68   91.57  102.29  113.00  116.45   \n4320               71.93   85.72   93.78  103.95  117.73  131.52  135.96   \n5760               78.95   95.65  105.42  117.72  134.43  151.13  156.50   \n7200               83.53  101.38  111.82  124.98  142.83  160.68  166.43   \n8640               85.38  104.95  116.40  130.82  150.38  169.95  176.25   \n\nreturn period (a)     30      50      75      100  \nfrequency (1/a)     0.033   0.020   0.013   0.010  \nduration (min)                                     \n5                   17.11   18.26   19.18   19.83  \n10                  27.27   29.09   30.54   31.56  \n15                  34.83   37.20   39.08   40.42  \n20                  40.89   43.75   46.02   47.63  \n30                  50.43   54.16   57.12   59.22  \n45                  61.28   66.14   69.99   72.73  \n60                  69.97   75.83   80.49   83.79  \n90                  74.43   80.60   85.49   88.96  \n120                 77.78   84.17   89.24   92.84  \n180                 82.76   89.48   94.81   98.60  \n240                 86.49   93.46   98.99  102.91  \n360                 92.06   99.39  105.20  109.33  \n540                 98.00  105.71  111.82  116.16  \n720                102.46  110.44  116.78  121.28  \n1080               106.24  114.02  120.20  124.58  \n1440               105.61  112.75  118.42  122.45  \n2880               119.26  127.16  133.42  137.87  \n4320               139.58  149.75  157.81  163.53  \n5760               160.89  173.20  182.97  189.90  \n7200               171.12  184.28  194.72  202.13  \n8640               181.40  195.82  207.27  215.39  ",
      "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 tr th {\n        text-align: left;\n    }\n\n    .dataframe thead tr:last-of-type th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr>\n      <th>return period (a)</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>5</th>\n      <th>10</th>\n      <th>20</th>\n      <th>25</th>\n      <th>30</th>\n      <th>50</th>\n      <th>75</th>\n      <th>100</th>\n    </tr>\n    <tr>\n      <th>frequency (1/a)</th>\n      <th>1.000</th>\n      <th>0.500</th>\n      <th>0.333</th>\n      <th>0.200</th>\n      <th>0.100</th>\n      <th>0.050</th>\n      <th>0.040</th>\n      <th>0.033</th>\n      <th>0.020</th>\n      <th>0.013</th>\n      <th>0.010</th>\n    </tr>\n    <tr>\n      <th>duration (min)</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>5</th>\n      <td>9.39</td>\n      <td>10.97</td>\n      <td>11.89</td>\n      <td>13.04</td>\n      <td>14.61</td>\n      <td>16.19</td>\n      <td>16.69</td>\n      <td>17.11</td>\n      <td>18.26</td>\n      <td>19.18</td>\n      <td>19.83</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>15.15</td>\n      <td>17.62</td>\n      <td>19.06</td>\n      <td>20.88</td>\n      <td>23.35</td>\n      <td>25.82</td>\n      <td>26.62</td>\n      <td>27.27</td>\n      <td>29.09</td>\n      <td>30.54</td>\n      <td>31.56</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>19.03</td>\n      <td>22.25</td>\n      <td>24.13</td>\n      <td>26.51</td>\n      <td>29.72</td>\n      <td>32.94</td>\n      <td>33.98</td>\n      <td>34.83</td>\n      <td>37.20</td>\n      <td>39.08</td>\n      <td>40.42</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>21.83</td>\n      <td>25.71</td>\n      <td>27.99</td>\n      <td>30.85</td>\n      <td>34.73</td>\n      <td>38.62</td>\n      <td>39.87</td>\n      <td>40.89</td>\n      <td>43.75</td>\n      <td>46.02</td>\n      <td>47.63</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>25.60</td>\n      <td>30.66</td>\n      <td>33.62</td>\n      <td>37.35</td>\n      <td>42.41</td>\n      <td>47.47</td>\n      <td>49.10</td>\n      <td>50.43</td>\n      <td>54.16</td>\n      <td>57.12</td>\n      <td>59.22</td>\n    </tr>\n    <tr>\n      <th>45</th>\n      <td>28.92</td>\n      <td>35.51</td>\n      <td>39.37</td>\n      <td>44.23</td>\n      <td>50.83</td>\n      <td>57.42</td>\n      <td>59.54</td>\n      <td>61.28</td>\n      <td>66.14</td>\n      <td>69.99</td>\n      <td>72.73</td>\n    </tr>\n    <tr>\n      <th>60</th>\n      <td>30.93</td>\n      <td>38.89</td>\n      <td>43.54</td>\n      <td>49.40</td>\n      <td>57.36</td>\n      <td>65.31</td>\n      <td>67.88</td>\n      <td>69.97</td>\n      <td>75.83</td>\n      <td>80.49</td>\n      <td>83.79</td>\n    </tr>\n    <tr>\n      <th>90</th>\n      <td>33.37</td>\n      <td>41.74</td>\n      <td>46.64</td>\n      <td>52.80</td>\n      <td>61.17</td>\n      <td>69.54</td>\n      <td>72.23</td>\n      <td>74.43</td>\n      <td>80.60</td>\n      <td>85.49</td>\n      <td>88.96</td>\n    </tr>\n    <tr>\n      <th>120</th>\n      <td>35.22</td>\n      <td>43.90</td>\n      <td>48.97</td>\n      <td>55.36</td>\n      <td>64.03</td>\n      <td>72.70</td>\n      <td>75.49</td>\n      <td>77.78</td>\n      <td>84.17</td>\n      <td>89.24</td>\n      <td>92.84</td>\n    </tr>\n    <tr>\n      <th>180</th>\n      <td>38.01</td>\n      <td>47.13</td>\n      <td>52.46</td>\n      <td>59.18</td>\n      <td>68.30</td>\n      <td>77.42</td>\n      <td>80.36</td>\n      <td>82.76</td>\n      <td>89.48</td>\n      <td>94.81</td>\n      <td>98.60</td>\n    </tr>\n    <tr>\n      <th>240</th>\n      <td>40.12</td>\n      <td>49.57</td>\n      <td>55.10</td>\n      <td>62.06</td>\n      <td>71.51</td>\n      <td>80.97</td>\n      <td>84.01</td>\n      <td>86.49</td>\n      <td>93.46</td>\n      <td>98.99</td>\n      <td>102.91</td>\n    </tr>\n    <tr>\n      <th>360</th>\n      <td>43.29</td>\n      <td>53.23</td>\n      <td>59.04</td>\n      <td>66.37</td>\n      <td>76.31</td>\n      <td>86.25</td>\n      <td>89.45</td>\n      <td>92.06</td>\n      <td>99.39</td>\n      <td>105.20</td>\n      <td>109.33</td>\n    </tr>\n    <tr>\n      <th>540</th>\n      <td>46.71</td>\n      <td>57.16</td>\n      <td>63.27</td>\n      <td>70.98</td>\n      <td>81.43</td>\n      <td>91.89</td>\n      <td>95.25</td>\n      <td>98.00</td>\n      <td>105.71</td>\n      <td>111.82</td>\n      <td>116.16</td>\n    </tr>\n    <tr>\n      <th>720</th>\n      <td>49.29</td>\n      <td>60.13</td>\n      <td>66.47</td>\n      <td>74.45</td>\n      <td>85.29</td>\n      <td>96.12</td>\n      <td>99.61</td>\n      <td>102.46</td>\n      <td>110.44</td>\n      <td>116.78</td>\n      <td>121.28</td>\n    </tr>\n    <tr>\n      <th>1080</th>\n      <td>54.41</td>\n      <td>64.97</td>\n      <td>71.15</td>\n      <td>78.94</td>\n      <td>89.50</td>\n      <td>100.06</td>\n      <td>103.46</td>\n      <td>106.24</td>\n      <td>114.02</td>\n      <td>120.20</td>\n      <td>124.58</td>\n    </tr>\n    <tr>\n      <th>1440</th>\n      <td>58.02</td>\n      <td>67.72</td>\n      <td>73.39</td>\n      <td>80.54</td>\n      <td>90.24</td>\n      <td>99.93</td>\n      <td>103.05</td>\n      <td>105.61</td>\n      <td>112.75</td>\n      <td>118.42</td>\n      <td>122.45</td>\n    </tr>\n    <tr>\n      <th>2880</th>\n      <td>66.70</td>\n      <td>77.41</td>\n      <td>83.68</td>\n      <td>91.57</td>\n      <td>102.29</td>\n      <td>113.00</td>\n      <td>116.45</td>\n      <td>119.26</td>\n      <td>127.16</td>\n      <td>133.42</td>\n      <td>137.87</td>\n    </tr>\n    <tr>\n      <th>4320</th>\n      <td>71.93</td>\n      <td>85.72</td>\n      <td>93.78</td>\n      <td>103.95</td>\n      <td>117.73</td>\n      <td>131.52</td>\n      <td>135.96</td>\n      <td>139.58</td>\n      <td>149.75</td>\n      <td>157.81</td>\n      <td>163.53</td>\n    </tr>\n    <tr>\n      <th>5760</th>\n      <td>78.95</td>\n      <td>95.65</td>\n      <td>105.42</td>\n      <td>117.72</td>\n      <td>134.43</td>\n      <td>151.13</td>\n      <td>156.50</td>\n      <td>160.89</td>\n      <td>173.20</td>\n      <td>182.97</td>\n      <td>189.90</td>\n    </tr>\n    <tr>\n      <th>7200</th>\n      <td>83.53</td>\n      <td>101.38</td>\n      <td>111.82</td>\n      <td>124.98</td>\n      <td>142.83</td>\n      <td>160.68</td>\n      <td>166.43</td>\n      <td>171.12</td>\n      <td>184.28</td>\n      <td>194.72</td>\n      <td>202.13</td>\n    </tr>\n    <tr>\n      <th>8640</th>\n      <td>85.38</td>\n      <td>104.95</td>\n      <td>116.40</td>\n      <td>130.82</td>\n      <td>150.38</td>\n      <td>169.95</td>\n      <td>176.25</td>\n      <td>181.40</td>\n      <td>195.82</td>\n      <td>207.27</td>\n      <td>215.39</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idf.result_table(add_names=True).round(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "To save the table as a csv:"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "idf.result_table(add_names=True).round(2).to_csv(path.join(output_directory, 'idf_table_UNIX.csv'), sep=',', decimal='.', float_format='%0.2f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "return period (a)    1       2       3       5       10      20      25      30      50      75      100\n",
      "frequency (1/a)    1.000   0.500   0.333   0.200   0.100   0.050   0.040   0.033   0.020   0.013   0.010\n",
      "duration (min)                                                                                          \n",
      "5                   9.39   10.97   11.89   13.04   14.61   16.19   16.69   17.11   18.26   19.18   19.83\n",
      "10                 15.15   17.62   19.06   20.88   23.35   25.82   26.62   27.27   29.09   30.54   31.56\n",
      "15                 19.03   22.25   24.13   26.51   29.72   32.94   33.98   34.83   37.20   39.08   40.42\n",
      "20                 21.83   25.71   27.99   30.85   34.73   38.62   39.87   40.89   43.75   46.02   47.63\n",
      "30                 25.60   30.66   33.62   37.35   42.41   47.47   49.10   50.43   54.16   57.12   59.22\n",
      "45                 28.92   35.51   39.37   44.23   50.83   57.42   59.54   61.28   66.14   69.99   72.73\n",
      "60                 30.93   38.89   43.54   49.40   57.36   65.31   67.88   69.97   75.83   80.49   83.79\n",
      "90                 33.37   41.74   46.64   52.80   61.17   69.54   72.23   74.43   80.60   85.49   88.96\n",
      "120                35.22   43.90   48.97   55.36   64.03   72.70   75.49   77.78   84.17   89.24   92.84\n",
      "180                38.01   47.13   52.46   59.18   68.30   77.42   80.36   82.76   89.48   94.81   98.60\n",
      "240                40.12   49.57   55.10   62.06   71.51   80.97   84.01   86.49   93.46   98.99  102.91\n",
      "360                43.29   53.23   59.04   66.37   76.31   86.25   89.45   92.06   99.39  105.20  109.33\n",
      "540                46.71   57.16   63.27   70.98   81.43   91.89   95.25   98.00  105.71  111.82  116.16\n",
      "720                49.29   60.13   66.47   74.45   85.29   96.12   99.61  102.46  110.44  116.78  121.28\n",
      "1080               54.41   64.97   71.15   78.94   89.50  100.06  103.46  106.24  114.02  120.20  124.58\n",
      "1440               58.02   67.72   73.39   80.54   90.24   99.93  103.05  105.61  112.75  118.42  122.45\n",
      "2880               66.70   77.41   83.68   91.57  102.29  113.00  116.45  119.26  127.16  133.42  137.87\n",
      "4320               71.93   85.72   93.78  103.95  117.73  131.52  135.96  139.58  149.75  157.81  163.53\n",
      "5760               78.95   95.65  105.42  117.72  134.43  151.13  156.50  160.89  173.20  182.97  189.90\n",
      "7200               83.53  101.38  111.82  124.98  142.83  160.68  166.43  171.12  184.28  194.72  202.13\n",
      "8640               85.38  104.95  116.40  130.82  150.38  169.95  176.25  181.40  195.82  207.27  215.39\n"
     ]
    }
   ],
   "source": [
    "print(idf.result_table(add_names=True).round(2).to_string())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To create a color plot of the IDF curves:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 841.89x595.276 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = idf.result_figure(color=True, add_interim=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To create a black/white plot of the IDF curves:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 841.89x595.276 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = idf.result_figure(color=False, add_interim=True)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}