{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2e8c8af7",
   "metadata": {},
   "source": [
    "# Heat Wave and Cold Spells\n",
    "\n",
    "Dieses Skript verarbeitet den Datensatz \"Heat Wave Days\" aus dem Copernics Climate Data Store. Der Datensatz enthält die Anzahl der Hitzewellen-Tage (Heat wave days; HWD), die mit verschiedenen europaweiten sowie nationalen/regionalen Definitionen im Rahmen des C3S European Health Service entwickelt wurden. Diese Tage sind für unterschiedliche zukünftige Zeiträume und Klimawandelszenarien verfügbar.\n",
    "\n",
    "**Informationen zum Datensatz**: \n",
    "\n",
    "* Source: [Heat Wave and Cold Spells](https://cds.climate.copernicus.eu/datasets/sis-heat-and-cold-spells?tab=overview)\n",
    "* Author: T. Tewes (Stadt Konstanz) \n",
    "* Notebook-Version: 1.2 (Aktualisiert: März 05, 2024)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d0ac21f",
   "metadata": {},
   "source": [
    "## 1. Festlegen der Pfade und Arbeitsverzeichnisse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e9c748dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "''' ---- Verzeichnisse hier angeben ---- '''\n",
    "download_folder = r\".\\data\\sis-heat-and-cold-spells\\download\"\n",
    "working_folder = r\".\\data\\sis-heat-and-cold-spells\\working\"\n",
    "geotiff_folder = r\".\\data\\sis-heat-and-cold-spells\\geotiff\"\n",
    "csv_folder = r\".\\data\\sis-heat-and-cold-spells\\csv\"\n",
    "output_folder = r\".\\data\\sis-heat-and-cold-spells\\output\"\n",
    "''' ----- Ende der Angaben ---- '''\n",
    "\n",
    "os.makedirs(download_folder, exist_ok=True)\n",
    "os.makedirs(working_folder, exist_ok=True)\n",
    "os.makedirs(geotiff_folder, exist_ok=True)\n",
    "os.makedirs(csv_folder, exist_ok=True)\n",
    "os.makedirs(output_folder, exist_ok=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bce50101",
   "metadata": {},
   "source": [
    "## 2. Herunterladen und Entpacken des Datensatzes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16866554",
   "metadata": {},
   "source": [
    "### 2.1 Authentifizierung"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3c1303d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cdsapi\n",
    "\n",
    "def main():\n",
    "    # API-Key für die Authentifizierung\n",
    "    api_key = \"fdae60fd-35d4-436f-825c-c63fedab94a4\"\n",
    "    api_url = \"https://cds.climate.copernicus.eu/api\"\n",
    "\n",
    "    # Erstellung des CDS-API-Clients\n",
    "    client = cdsapi.Client(url=api_url, key=api_key)\n",
    "    return client"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f10c07e8",
   "metadata": {},
   "source": [
    "### 2.2 Definieren Sie die „request“ und laden Sie den Datensatz herunter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6e9520c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Definieren der Begrenzungsrahmen-Koordinaten (WGS84-Format)\n",
    "# Das Koordinatenformat lautet: [Norden, Westen, Süden, Osten]\n",
    "bbox_wgs84_deutschland = [56.0, 5.8, 47.2, 15.0]\n",
    "bbox_wgs84_de_standard = [5.7, 47.1, 15.2, 55.2]\n",
    "bbox_wgs84_konstanz = [47.9, 8.9, 47.6, 9.3]\n",
    "bbox_wgs84_konstanz_standard = [9.0, 47.6, 9.3, 47.8]  # [West, South, East, North]\n",
    "\n",
    "# Alternativ können Sie ein Shapefile für eine präzise geografische Filterung verwenden\n",
    "import geopandas as gpd\n",
    "import math\n",
    "\n",
    "# Beispiel: Shapefile von Konstanz laden (WGS84-Projektion)\n",
    "de_shapefile = r\"./shapefiles/de_boundary.shp\"\n",
    "de_gdf = gpd.read_file(de_shapefile)\n",
    "\n",
    "# Extrahieren Sie den Begrenzungsrahmen des Shapefiles\n",
    "de_bounds = de_gdf.total_bounds\n",
    "\n",
    "# Passen Sie den Begrenzungsrahmen an und puffern Sie ihn, um einen etwas größeren\n",
    "de_bounds_adjusted = [(math.floor(de_bounds[0]* 10)/10)-0.1,\n",
    "                      (math.floor(de_bounds[1]* 10)/10)-0.1,\n",
    "                      (math.ceil(de_bounds[2]* 10)/10)+0.1,\n",
    "                      (math.ceil(de_bounds[3]* 10)/10)+0.1]\n",
    "\n",
    "# Ordnen Sie die Koordinaten in das Format: [Nord, West, Süd, Ost] um.\n",
    "bbox_de_bounds_adjusted = [de_bounds_adjusted[3], de_bounds_adjusted[0],\n",
    "                           de_bounds_adjusted[1], de_bounds_adjusted[2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ausgewählte_variable: heat_wave_days\n",
      "ausgewählte_definition: ['climatological_related', 'health_related', 'country_related']\n"
     ]
    }
   ],
   "source": [
    "# Der Datensatz sis-heat-and-cold-spells ermöglicht die Auswahl zwischen zwei Variablen:\n",
    "# \"Heat wave days\" and \"Cold spell days\".\n",
    "# Abhängig von der gewählten Variablen variieren die Definitionsoptionen.\n",
    "# Für \"heat_wave_days\" sind alle Definitionen verfügbar.\n",
    "# Für \"cold_spell_days\" wird nur die 'landesspezifische' Definition unterstützt.\n",
    "\n",
    "variable_to_definition_map = {\n",
    "    'heat_wave_days': ['climatological_related', 'health_related', 'country_related'],\n",
    "    'cold_spell_days': ['country_related']\n",
    "}\n",
    "\n",
    "# Ausgewählte Variable\n",
    "selected_variable = 'heat_wave_days'\n",
    "\n",
    "# Abrufen der entsprechenden Definitionen basierend auf der ausgewählten Variablen\n",
    "selected_definition = variable_to_definition_map.get(selected_variable, [])\n",
    "\n",
    "# Ausgabe der ausgewählten Definitionen und der Variable\n",
    "print(f\"ausgewählte_variable: {selected_variable}\\nausgewählte_definition: {selected_definition}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bc970752",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Definition des Datensatzes und der Request-Parameter\n",
    "dataset = \"sis-heat-and-cold-spells\"\n",
    "request = {\n",
    "    \"variable\": selected_variable,\n",
    "    \"definition\": selected_definition,\n",
    "    \"experiment\": [\n",
    "        \"rcp4_5\",\n",
    "        \"rcp8_5\"\n",
    "    ],\n",
    "    \"ensemble_statistic\": [\n",
    "        \"ensemble_members_average\",\n",
    "        \"ensemble_members_standard_deviation\"\n",
    "    ],\n",
    "    \"area\": bbox_de_bounds_adjusted\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Datensatz bereits heruntergeladen.\n"
     ]
    }
   ],
   "source": [
    "# Führen Sie es aus, um den Datensatz herunterzuladen:\n",
    "def main_retrieve():\n",
    "    dataset_filename = f\"{dataset}-{selected_definition}.zip\"\n",
    "    dataset_filepath = os.path.join(download_folder, dataset_filename)\n",
    "\n",
    "    # Den Datensatz nur herunterladen, wenn er noch nicht heruntergeladen wurde\n",
    "    if not os.path.isfile(dataset_filepath):\n",
    "        # Rufen Sie den CDS-Client nur auf, wenn der Datensatz noch nicht heruntergeladen wurde.\n",
    "        client = main()\n",
    "        # Den Datensatz mit den definierten Anforderungsparametern herunterladen\n",
    "        client.retrieve(dataset, request, dataset_filepath)\n",
    "    else:\n",
    "        print(\"Datensatz bereits heruntergeladen.\")\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    main_retrieve()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Extrahieren die ZIP-Datei in Ordner"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ordner ist nicht leer. Entpacken überspringen.\n"
     ]
    }
   ],
   "source": [
    "import zipfile\n",
    "\n",
    "# Definieren Sie einen Extraktionsordner für die ZIP-Datei, der dem Arbeitsordner entspricht\n",
    "extract_folder = os.path.join(working_folder, f\"{selected_variable}\")\n",
    "os.makedirs(extract_folder, exist_ok=True)\n",
    "\n",
    "# Extract the zip file\n",
    "try:\n",
    "    if not os.listdir(extract_folder):\n",
    "        dataset_filename = f\"{dataset}-{selected_definition}.zip\"\n",
    "        dataset_filepath = os.path.join(download_folder, dataset_filename)\n",
    "        \n",
    "        with zipfile.ZipFile(dataset_filepath, 'r') as zip_ref:\n",
    "            zip_ref.extractall(extract_folder)\n",
    "            print(f\"Dateien erfolgreich extrahiert nach: {extract_folder}\")\n",
    "    else:\n",
    "        print(\"Ordner ist nicht leer. Entpacken überspringen.\")\n",
    "except FileNotFoundError:\n",
    "    print(f\"Fehler: Die Datei {dataset_filepath} wurde nicht gefunden.\")\n",
    "except zipfile.BadZipFile:\n",
    "    print(f\"Fehler: Die Datei {dataset_filepath} ist keine gültige ZIP-Datei.\")\n",
    "except Exception as e:\n",
    "    print(f\"Ein unerwarteter Fehler ist aufgetreten: {e}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Untersuchen der Metadaten der NetCDF4-Datei\n",
    "\n",
    "⚠️ <span style=\"background-color: red; color: white; padding: 2px 4px;\">Wichtig</span>: Obwohl alle Datensätze zum Download verfügbar sind, konzentriert sich dieses Notebook auf die Analyse der folgenden Auswahl:\n",
    "* selected_variable = 'heat_wave_days'\n",
    "* selected_definition = 'climatological related'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Variable und Definition definieren\n",
    "selected_variable = 'heat_wave_days'\n",
    "selected_definition = 'climatological_related'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 Erstellen eines DataFrame mit verfügbaren NetCDF-Dateien"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>filename</th>\n",
       "      <th>ds_variable</th>\n",
       "      <th>ds_definition</th>\n",
       "      <th>variable_name</th>\n",
       "      <th>rcp</th>\n",
       "      <th>rcp_statistic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HWD_EU_climate_rcp45...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>EU_climate</td>\n",
       "      <td>HWD_EU_climate</td>\n",
       "      <td>rcp45</td>\n",
       "      <td>mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HWD_EU_climate_rcp45...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>EU_climate</td>\n",
       "      <td>HWD_EU_climate</td>\n",
       "      <td>rcp45</td>\n",
       "      <td>stdev</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HWD_EU_climate_rcp85...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>EU_climate</td>\n",
       "      <td>HWD_EU_climate</td>\n",
       "      <td>rcp85</td>\n",
       "      <td>mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HWD_EU_climate_rcp85...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>EU_climate</td>\n",
       "      <td>HWD_EU_climate</td>\n",
       "      <td>rcp85</td>\n",
       "      <td>stdev</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HWD_EU_health_rcp45_...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>EU_health</td>\n",
       "      <td>HWD_EU_health</td>\n",
       "      <td>rcp45</td>\n",
       "      <td>mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>HWD_EU_health_rcp45_...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>EU_health</td>\n",
       "      <td>HWD_EU_health</td>\n",
       "      <td>rcp45</td>\n",
       "      <td>stdev</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>HWD_EU_health_rcp85_...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>EU_health</td>\n",
       "      <td>HWD_EU_health</td>\n",
       "      <td>rcp85</td>\n",
       "      <td>mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>HWD_EU_health_rcp85_...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>EU_health</td>\n",
       "      <td>HWD_EU_health</td>\n",
       "      <td>rcp85</td>\n",
       "      <td>stdev</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>HWD_national_rcp45_m...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>national</td>\n",
       "      <td>HWD_merged</td>\n",
       "      <td>rcp45</td>\n",
       "      <td>mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>HWD_national_rcp45_s...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>national</td>\n",
       "      <td>HWD_merged</td>\n",
       "      <td>rcp45</td>\n",
       "      <td>stdev</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>HWD_national_rcp85_m...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>national</td>\n",
       "      <td>HWD_merged</td>\n",
       "      <td>rcp85</td>\n",
       "      <td>mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>HWD_national_rcp85_s...</td>\n",
       "      <td>HWD</td>\n",
       "      <td>national</td>\n",
       "      <td>HWD_merged</td>\n",
       "      <td>rcp85</td>\n",
       "      <td>stdev</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   filename ds_variable ds_definition   variable_name    rcp  \\\n",
       "0   HWD_EU_climate_rcp45...         HWD    EU_climate  HWD_EU_climate  rcp45   \n",
       "1   HWD_EU_climate_rcp45...         HWD    EU_climate  HWD_EU_climate  rcp45   \n",
       "2   HWD_EU_climate_rcp85...         HWD    EU_climate  HWD_EU_climate  rcp85   \n",
       "3   HWD_EU_climate_rcp85...         HWD    EU_climate  HWD_EU_climate  rcp85   \n",
       "4   HWD_EU_health_rcp45_...         HWD     EU_health   HWD_EU_health  rcp45   \n",
       "5   HWD_EU_health_rcp45_...         HWD     EU_health   HWD_EU_health  rcp45   \n",
       "6   HWD_EU_health_rcp85_...         HWD     EU_health   HWD_EU_health  rcp85   \n",
       "7   HWD_EU_health_rcp85_...         HWD     EU_health   HWD_EU_health  rcp85   \n",
       "8   HWD_national_rcp45_m...         HWD      national      HWD_merged  rcp45   \n",
       "9   HWD_national_rcp45_s...         HWD      national      HWD_merged  rcp45   \n",
       "10  HWD_national_rcp85_m...         HWD      national      HWD_merged  rcp85   \n",
       "11  HWD_national_rcp85_s...         HWD      national      HWD_merged  rcp85   \n",
       "\n",
       "   rcp_statistic  \n",
       "0           mean  \n",
       "1          stdev  \n",
       "2           mean  \n",
       "3          stdev  \n",
       "4           mean  \n",
       "5          stdev  \n",
       "6           mean  \n",
       "7          stdev  \n",
       "8           mean  \n",
       "9          stdev  \n",
       "10          mean  \n",
       "11         stdev  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "import pandas as pd\n",
    "import netCDF4 as nc\n",
    "\n",
    "def meta(filename):\n",
    "    # Überprüfen, ob der Dateiname dem erwarteten Muster entspricht\n",
    "    match = re.search(r\"(?P<ds_variable>\\w+?)_(?P<ds_definition>\\w+?)_(?P<rcp>rcp\\d+?)_(?P<rcp_statistic>mean|stdev)_v(\\d+\\.\\d+)\\.\", filename)\n",
    "    \n",
    "    # Fehler ausgeben, wenn der Dateiname nicht dem erwarteten Schema entspricht\n",
    "    if not match:\n",
    "        match = re.search(\"Der angegebene Dateiname entspricht nicht dem erwarteten Benennungsschema.\")\n",
    "    \n",
    "    # Funktion zum Extrahieren des Variablennamens aus der NetCDF-Datei\n",
    "    def get_nc_variable():\n",
    "        with nc.Dataset(os.path.join(extract_folder, filename), 'r') as nc_dataset:\n",
    "            nc_variable_name = nc_dataset.variables.keys()\n",
    "            return [*nc_variable_name][0]\n",
    "    \n",
    "    # Metadaten als Dictionary zurückgeben\n",
    "    return dict(\n",
    "        filename=filename,\n",
    "        path=os.path.join(extract_folder, filename),\n",
    "        ds_variable=match.group('ds_variable'),\n",
    "        ds_definition=match.group('ds_definition'),\n",
    "        variable_name=get_nc_variable(),\n",
    "        rcp=match.group('rcp'),\n",
    "        rcp_statistic=match.group('rcp_statistic')\n",
    "    )\n",
    "\n",
    "# Metadaten für alle NetCDF-Dateien im Ordner extrahieren\n",
    "# Das Dictionary 'nc_files' enthält alle relevanten Metadaten der verfügbaren NetCDF4-Dateien\n",
    "# Dieses Dictionary wird später verwendet, um die Dateien in GeoTiff zu konvertieren\n",
    "nc_files = [meta(f) for f in os.listdir(extract_folder) if f.endswith('.nc')]\n",
    "df_nc_files = pd.DataFrame.from_dict(nc_files)\n",
    "\n",
    "# Pandas-Anzeigeoptionen anpassen\n",
    "pd.options.display.max_colwidth = 24\n",
    "\n",
    "# DataFrame anzeigen, ohne die Spalte 'path' darzustellen\n",
    "df_nc_files.loc[:, df_nc_files.columns != 'path']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Einzigartige Variablennamen und verfügbare Variablen ausgeben"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1  HWD_EU_climate    : Verfügbare Variablen: ['HWD_EU_climate', 'height', 'quantile', 'lat', 'lon', 'time']\n",
      "5  HWD_EU_health     : Verfügbare Variablen: ['HWD_EU_health', 'height', 'lat', 'lon', 'time']\n",
      "9  HWD_merged        : Verfügbare Variablen: ['HWD_merged', 'height', 'lat', 'lon', 'time']\n"
     ]
    }
   ],
   "source": [
    "# Variable definieren, um bereits verarbeitete Variablennamen zu speichern und Duplikate zu vermeiden  \n",
    "seen_variables = set()\n",
    "\n",
    "# Alle Variablen in jeder NetCDF-Datei auflisten  \n",
    "for i, nc_file in enumerate(nc_files):\n",
    "    variable_name = nc_file['variable_name']\n",
    "    \n",
    "    # Überspringen, wenn die Variable bereits verarbeitet wurde  \n",
    "    if variable_name in seen_variables:\n",
    "        continue\n",
    "\n",
    "    # NetCDF-Datei im Lesemodus öffnen  \n",
    "    with nc.Dataset(nc_file['path'], mode='r') as nc_dataset:  \n",
    "        # Alle Variablen im aktuellen Datensatz auflisten  \n",
    "        variables_list = list(nc_dataset.variables.keys())  \n",
    "        \n",
    "        # Details der Datei und ihrer Variablen ausgeben  \n",
    "        print(f\"{i + 1:<2} {variable_name:<18}: Verfügbare Variablen: {variables_list}\") \n",
    "    \n",
    "    # Diese Variable als verarbeitet markieren  \n",
    "    seen_variables.add(variable_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1. Zusammenfassung der Variable 'HWD_EU_climate':\n"
     ]
    },
    {
     "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>Beschreibung</th>\n",
       "      <th>Bemerkungen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Variablenname</td>\n",
       "      <td>HWD_EU_climate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Datentyp</td>\n",
       "      <td>float32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Form</td>\n",
       "      <td>(100, 82, 95)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Variableninfo</td>\n",
       "      <td>('time', 'lat', 'lon')</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Einheiten</td>\n",
       "      <td>day</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Langer Name</td>\n",
       "      <td>Ensemble members ave...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Beschreibung              Bemerkungen\n",
       "0  Variablenname           HWD_EU_climate\n",
       "1       Datentyp                  float32\n",
       "2           Form            (100, 82, 95)\n",
       "3  Variableninfo   ('time', 'lat', 'lon')\n",
       "4      Einheiten                      day\n",
       "5    Langer Name  Ensemble members ave..."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5. Zusammenfassung der Variable 'HWD_EU_health':\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Beschreibung</th>\n",
       "      <th>Bemerkungen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Variablenname</td>\n",
       "      <td>HWD_EU_health</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Datentyp</td>\n",
       "      <td>float32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Form</td>\n",
       "      <td>(100, 82, 95)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Variableninfo</td>\n",
       "      <td>('time', 'lat', 'lon')</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Einheiten</td>\n",
       "      <td>day</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Langer Name</td>\n",
       "      <td>Ensemble members ave...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Beschreibung              Bemerkungen\n",
       "0  Variablenname            HWD_EU_health\n",
       "1       Datentyp                  float32\n",
       "2           Form            (100, 82, 95)\n",
       "3  Variableninfo   ('time', 'lat', 'lon')\n",
       "4      Einheiten                      day\n",
       "5    Langer Name  Ensemble members ave..."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".... (Ausgabe auf die ersten 2 Variablen gekürzt)\n"
     ]
    }
   ],
   "source": [
    "# Alle Variableninformationen in jeder NetCDF-Datei auflisten  \n",
    "seen_variables = set()\n",
    "\n",
    "# Alle variablen Informationen in jeder NetCDF-Datei auflisten\n",
    "for i, nc_file in enumerate(nc_files):\n",
    "    variable_name = nc_file['variable_name']\n",
    "    \n",
    "    # Überspringen, wenn die Variable bereits verarbeitet wurde\n",
    "    if variable_name in seen_variables:\n",
    "        continue\n",
    "    \n",
    "    # NetCDF-Datei im Lesemodus öffnen\n",
    "    with nc.Dataset(nc_file['path'], mode='r') as nc_dataset:  \n",
    "        # Primärvariable-Daten abrufen  \n",
    "        variable_data = nc_dataset[variable_name]  \n",
    "\n",
    "        # Zusammenfassung der Primärvariable erstellen  \n",
    "        summary = {  \n",
    "            \"Variablenname\": variable_name,  \n",
    "            \"Datentyp\": variable_data.dtype,  \n",
    "            \"Form\": variable_data.shape,  \n",
    "            \"Variableninfo\": f\"{variable_data.dimensions}\",  \n",
    "            \"Einheiten\": getattr(variable_data, \"units\", \"N/A\"),  \n",
    "            \"Langer Name\": getattr(variable_data, \"long_name\", \"N/A\"),  \n",
    "        }  \n",
    "\n",
    "        # Datensatz-Zusammenfassung als DataFrame zur besseren Visualisierung anzeigen  \n",
    "        nc_summary = pd.DataFrame(list(summary.items()), columns=['Beschreibung', 'Bemerkungen'])  \n",
    "        print(f\"{i + 1}. Zusammenfassung der Variable '{variable_name}':\")  \n",
    "        display(nc_summary)  \n",
    "\n",
    "    # Variablenname zur Liste der bereits verarbeiteten Variablen hinzufügen  \n",
    "    seen_variables.add(variable_name)  \n",
    "\n",
    "    # Ausgabe begrenzen  \n",
    "    output_limit = 2  \n",
    "    if len(seen_variables) >= output_limit:  \n",
    "        print(f\".... (Ausgabe auf die ersten {output_limit} Variablen gekürzt)\")  \n",
    "        break  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Exportieren der NetCDF4-Dateien im CSV-Format"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.1 Definieren eine Funktion zum Konvertieren von NetCDF-Daten in DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "\n",
    "# Funktion zur Konvertierung von NetCDF-Daten in ein Pandas DataFrame\n",
    "def netcdf_to_dataframe(\n",
    "    nc_file,\n",
    "    bounding_box=None):\n",
    "\n",
    "    # Öffne das NetCDF-Dataset im Lesemodus\n",
    "    with xr.open_dataset(nc_file['path']) as nc_dataset:\n",
    "        # Zugriff auf die Variablendaten aus dem Datensatz\n",
    "        variable_data = nc_dataset[nc_file['variable_name']]\n",
    "\n",
    "        # Sicherstellen, dass die Namen für Breiten- und Längengrad korrekt sind\n",
    "        latitude_name = 'latitude' if 'latitude' in nc_dataset.coords else 'lat'\n",
    "        longitude_name = 'longitude' if 'longitude' in nc_dataset.coords else 'lon'\n",
    "        \n",
    "        # Falls eine Begrenzungsbox angegeben ist, die Daten filtern\n",
    "        if bounding_box:\n",
    "            filtered_data = variable_data.where(\n",
    "                (nc_dataset[latitude_name] >= bounding_box[1]) & (nc_dataset[latitude_name] <= bounding_box[3]) &\n",
    "                (nc_dataset[longitude_name] >= bounding_box[0]) & (nc_dataset[longitude_name] <= bounding_box[2]),\n",
    "                drop=True\n",
    "            )\n",
    "        else:\n",
    "            filtered_data = variable_data\n",
    "\n",
    "        # Umwandlung des xarray-Datensatzes in ein Pandas DataFrame\n",
    "        df = filtered_data.to_dataframe().reset_index().set_index(['time', latitude_name, longitude_name])\n",
    "\n",
    "        variable_column_name = f\"{nc_file['variable_name']}_{nc_file['rcp']}_{nc_file['rcp_statistic']}\"\n",
    "        df.rename(columns={nc_file['variable_name']: variable_column_name}, inplace=True)\n",
    "\n",
    "        # Entfernen nicht benötigter Spalten (variiert je nach Datensatz)\n",
    "        if 'height' in df.columns:\n",
    "            df = df.drop(columns=['height'])\n",
    "        if 'quantile' in df.columns:\n",
    "            df = df.drop(columns=['quantile'])\n",
    "\n",
    "        return df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2 DataFrame erstellen und als zusammengeführte CSV-Datei exportieren"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Datei existiert bereits unter .\\data\\sis-heat-and-cold-spells\\csv\\HWD_EU_climate\\HWD_EU_climate_climatological_related.csv.\n",
      "Überspringen den Export.\n",
      "Lesen bestehende CSV-Datei ein...\n"
     ]
    },
    {
     "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></th>\n",
       "      <th></th>\n",
       "      <th>HWD_EU_climate _rcp45_mean</th>\n",
       "      <th>HWD_EU_climate _rcp45_stdev</th>\n",
       "      <th>HWD_EU_climate _rcp85_mean</th>\n",
       "      <th>HWD_EU_climate _rcp85_stdev</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1986-01-01</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">47.10</th>\n",
       "      <th>5.70</th>\n",
       "      <td>0.77</td>\n",
       "      <td>1.33</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.80</th>\n",
       "      <td>0.76</td>\n",
       "      <td>1.31</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.90</th>\n",
       "      <td>0.77</td>\n",
       "      <td>1.18</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6.00</th>\n",
       "      <td>0.74</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6.10</th>\n",
       "      <td>0.72</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2085-01-01</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">55.20</th>\n",
       "      <th>14.70</th>\n",
       "      <td>3.60</td>\n",
       "      <td>2.06</td>\n",
       "      <td>6.99</td>\n",
       "      <td>2.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.80</th>\n",
       "      <td>2.84</td>\n",
       "      <td>1.80</td>\n",
       "      <td>5.61</td>\n",
       "      <td>2.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.90</th>\n",
       "      <td>2.58</td>\n",
       "      <td>1.48</td>\n",
       "      <td>5.11</td>\n",
       "      <td>2.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15.00</th>\n",
       "      <td>3.00</td>\n",
       "      <td>1.58</td>\n",
       "      <td>5.66</td>\n",
       "      <td>1.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15.10</th>\n",
       "      <td>3.43</td>\n",
       "      <td>2.30</td>\n",
       "      <td>6.42</td>\n",
       "      <td>2.68</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>779000 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        HWD_EU_climate _rcp45_mean  \\\n",
       "time       lat   lon                                 \n",
       "1986-01-01 47.10 5.70                      0.77      \n",
       "                 5.80                      0.76      \n",
       "                 5.90                      0.77      \n",
       "                 6.00                      0.74      \n",
       "                 6.10                      0.72      \n",
       "...                                         ...      \n",
       "2085-01-01 55.20 14.70                     3.60      \n",
       "                 14.80                     2.84      \n",
       "                 14.90                     2.58      \n",
       "                 15.00                     3.00      \n",
       "                 15.10                     3.43      \n",
       "\n",
       "                        HWD_EU_climate _rcp45_stdev  \\\n",
       "time       lat   lon                                  \n",
       "1986-01-01 47.10 5.70                      1.33       \n",
       "                 5.80                      1.31       \n",
       "                 5.90                      1.18       \n",
       "                 6.00                      0.96       \n",
       "                 6.10                      0.80       \n",
       "...                                         ...       \n",
       "2085-01-01 55.20 14.70                     2.06       \n",
       "                 14.80                     1.80       \n",
       "                 14.90                     1.48       \n",
       "                 15.00                     1.58       \n",
       "                 15.10                     2.30       \n",
       "\n",
       "                        HWD_EU_climate _rcp85_mean  \\\n",
       "time       lat   lon                                 \n",
       "1986-01-01 47.10 5.70                      0.77      \n",
       "                 5.80                      0.76      \n",
       "                 5.90                      0.77      \n",
       "                 6.00                      0.74      \n",
       "                 6.10                      0.72      \n",
       "...                                         ...      \n",
       "2085-01-01 55.20 14.70                     6.99      \n",
       "                 14.80                     5.61      \n",
       "                 14.90                     5.11      \n",
       "                 15.00                     5.66      \n",
       "                 15.10                     6.42      \n",
       "\n",
       "                        HWD_EU_climate _rcp85_stdev  \n",
       "time       lat   lon                                 \n",
       "1986-01-01 47.10 5.70                      0.95      \n",
       "                 5.80                      0.96      \n",
       "                 5.90                      0.89      \n",
       "                 6.00                      0.72      \n",
       "                 6.10                      0.63      \n",
       "...                                         ...      \n",
       "2085-01-01 55.20 14.70                     2.59      \n",
       "                 14.80                     2.45      \n",
       "                 14.90                     2.09      \n",
       "                 15.00                     1.98      \n",
       "                 15.10                     2.68      \n",
       "\n",
       "[779000 rows x 4 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tqdm.notebook import tqdm\n",
    "import textwrap\n",
    "\n",
    "# Definieren Sie den Variablennamen für die Filterung von NetCDF-Dateien.\n",
    "variable_name = 'HWD_EU_climate'  # Andere Optionen: HWD_EU_climate, HWD_EU_health, HWD_merged (für HWD_national), oder CDS_national\n",
    "\n",
    "# Erstellen Sie einen Ordner für die Speicherung von CSV-Teilsatzdateien.\n",
    "subset_csv_folder = os.path.join(csv_folder, f\"{variable_name}\")\n",
    "os.makedirs(subset_csv_folder, exist_ok=True)  # Ensure the folder exists\n",
    "\n",
    "# Definieren Sie den Namen der CSV-Ausgabedatei anhand des Variablennamens und der ausgewählten Definition\n",
    "csv_filename = f\"{variable_name}_{selected_definition}.csv\"\n",
    "csv_filepath = os.path.join(subset_csv_folder, csv_filename)\n",
    "\n",
    "# Filtern Sie die Liste der NetCDF-Dateien so, dass nur diejenigen enthalten sind, die dem Variablennamen entsprechen\n",
    "nc_files_subset = list(filter(lambda nc_file: nc_file['variable_name'] == variable_name, nc_files))\n",
    "\n",
    "# Exportieren Sie die NetCDF-Dateien als zusammengeführte CSV-Datei\n",
    "if not os.path.isfile(csv_filepath):\n",
    "    dataframes = [netcdf_to_dataframe(nc_file) for nc_file in tqdm(nc_files_subset)]\n",
    "    df_merged = pd.concat(dataframes, axis=1)\n",
    "    df_merged.to_csv(csv_filepath, sep=',', encoding='utf8')\n",
    "else:\n",
    "    print(f\"Datei existiert bereits unter {csv_filepath}.\\nÜberspringen den Export.\")\n",
    "    print(\"Lesen bestehende CSV-Datei ein...\")\n",
    "    df_merged = pd.read_csv(csv_filepath).set_index(['time', 'lat', 'lon'])\n",
    "\n",
    "# Funktion zum Umbruch der Spaltennamen für bessere Lesbarkeit\n",
    "def wrap_column_names(df, width):\n",
    "    wrapped_columns = {col: \" \".join(textwrap.wrap(col, width)) for col in df.columns}\n",
    "    return df.rename(columns=wrapped_columns)\n",
    "    \n",
    "# Ändere die Pandas-Anzeigeoptionen\n",
    "pd.options.display.float_format = '{:,.2f}'.format\n",
    "    \n",
    "# Zeige das DataFrame an\n",
    "df_wrapped = wrap_column_names(df_merged, width=14)\n",
    "df_wrapped"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Exportieren der NetCDF4-Datei nach GeoTIFF"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1 Definieren eine Funktion zum Exportieren der NetCDF4-Datei als GeoTIFF-Datei(en)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from rasterio.transform import from_origin\n",
    "import rasterio\n",
    "\n",
    "from tqdm.notebook import tqdm\n",
    "\n",
    "def main_export_geotiff(\n",
    "    nc_file,\n",
    "    bounding_box=None,\n",
    "    start_year=None,\n",
    "    end_year=None,\n",
    "    merged=None,\n",
    "    output_directory=None):\n",
    "    \n",
    "    \"\"\"\n",
    "    Parameter:\n",
    "        nc_file (dict): Ein Wörterbuch mit den Schlüsseln 'path' (Dateipfad), 'variable', 'rcp' und 'statistic'.\n",
    "        bounding_box (list): [lon_min, lat_min, lon_max, lat_max] (optional).\n",
    "        start_year (int): Startjahr für den Datensatz (optional).\n",
    "        end_year (int): Endjahr für den Datensatz (optional).\n",
    "        merged (bool): Ob ein zusammengeführtes GeoTIFF oder einzelne GeoTIFFs erstellt werden sollen (optional).\n",
    "        output_directory (str): Verzeichnis zum Speichern der Ausgabe-GeoTIFF-Dateien (optional).\n",
    "    \"\"\"\n",
    "     \n",
    "    # Öffnet die NetCDF-Datei\n",
    "    with nc.Dataset(nc_file['path'], 'r') as nc_dataset:\n",
    "        nc_dataset = nc.Dataset(nc_file['path'], 'r')\n",
    "        lon = nc_dataset['lon'][:]\n",
    "        lat = nc_dataset['lat'][:]\n",
    "                    \n",
    "        # Falls eine Begrenzungsbox angegeben wurde, filtere die Daten entsprechend\n",
    "        if bounding_box:\n",
    "            lon_min, lat_min, lon_max, lat_max = bounding_box\n",
    "            \n",
    "            indices_lat = np.where((lat >= lat_min) & (lat <= lat_max))[0]\n",
    "            indices_lon = np.where((lon >= lon_min) & (lon <= lon_max))[0]\n",
    "            start_lat, end_lat = indices_lat[0], indices_lat[-1] + 1\n",
    "            start_lon, end_lon = indices_lon[0], indices_lon[-1] + 1\n",
    "        else:\n",
    "            start_lat, end_lat = 0, len(lat)\n",
    "            start_lon, end_lon = 0, len(lon)\n",
    "        \n",
    "        lat = lat[start_lat:end_lat]\n",
    "        lon = lon[start_lon:end_lon]\n",
    "            \n",
    "        # Extrahiere die Zeitvariable und konvertiere sie in lesbare Datumsangaben\n",
    "        time_var = nc_dataset.variables['time']\n",
    "        time_units = time_var.units\n",
    "        time_calendar = getattr(time_var, \"calendar\", \"standard\")\n",
    "        cftime = nc.num2date(time_var[:], units=time_units, calendar=time_calendar)\n",
    "        \n",
    "        # Berechnet die räumliche Auflösung und die Rastertransformation\n",
    "        dx = abs(lon[1] - lon[0])\n",
    "        dy = abs(lat[1] - lat[0])\n",
    "        transform = from_origin(lon.min() - dx / 2, lat.min() - dy / 2, dx, -dy)\n",
    "            \n",
    "        # Bestimmt den verfügbaren Zeitraum\n",
    "        min_year = cftime[0].year\n",
    "        max_year = cftime[-1].year\n",
    "\n",
    "        if start_year and end_year:\n",
    "            # Passen Sie start_year und end_year basierend auf dem verfügbaren Zeitraum an\n",
    "            if start_year < min_year:\n",
    "                print(f\"Das angegebene Startjahr {start_year} liegt vor dem Datensatzbereich.\")\n",
    "                print(f\"Das Startjahr wird auf {min_year} angepasst.\")\n",
    "            if end_year > max_year:\n",
    "                print(f\"Das angegebene Endjahr {end_year} liegt nach dem Datensatzbereich.\")\n",
    "                print(f\"Das Endjahr wird auf {max_year} angepasst.\")\n",
    "\n",
    "            start_year = max(start_year, min_year)\n",
    "            end_year = min(end_year, max_year)\n",
    "        else:\n",
    "            # Standardmäßig wird der gesamte Datensatz verwendet\n",
    "            start_year = min_year\n",
    "            end_year = max_year\n",
    "            \n",
    "        # Findet die Indizes, die dem angegebenen Jahresbereich entsprechen\n",
    "        start_index = next(i for i, dt in enumerate(cftime) if dt.year == start_year)\n",
    "        end_index = next(i for i, dt in enumerate(cftime) if dt.year == end_year) + 1  # Full year (monthly data)\n",
    "        \n",
    "        # Extrahiere Variablen-Daten\n",
    "        variable_data = nc_dataset.variables[nc_file['variable_name']]\n",
    "        variable_data_subset = variable_data[start_index:end_index, start_lat:end_lat, start_lon:end_lon]\n",
    "        \n",
    "        if merged:\n",
    "            # Erstellt ein zusammengeführtes GeoTIFF mit allen Zeitscheiben als separate Bänder\n",
    "            if output_directory:\n",
    "                subset_directory_path = output_directory\n",
    "            else:\n",
    "                subset_directory_path = os.path.join(geotiff_folder, f\"{selected_variable}_{selected_definition}-merged\")\n",
    "                os.makedirs(subset_directory_path, exist_ok=True)\n",
    "\n",
    "            # Pfad der Ausgabedatei festlegen\n",
    "            output_filename = f\"{nc_file['variable_name']}_{nc_file['rcp']}_{nc_file['rcp_statistic']}_{start_year}-{end_year}.tif\"\n",
    "            output_filepath = os.path.join(subset_directory_path, output_filename)\n",
    "\n",
    "            # Erstellt eine GeoTIFF-Datei mit mehreren Bändern für jede Zeitscheibe\n",
    "            with rasterio.open(\n",
    "                output_filepath,\n",
    "                \"w\",\n",
    "                driver = \"GTiff\",\n",
    "                dtype = str(variable_data_subset.dtype),\n",
    "                width = variable_data_subset.shape[2],\n",
    "                height = variable_data_subset.shape[1],\n",
    "                count = variable_data_subset.shape[0],\n",
    "                crs = \"EPSG:4326\",\n",
    "                nodata = -9999,\n",
    "                transform=transform,        \n",
    "            ) as dst:\n",
    "                for year_index in tqdm(range(variable_data_subset.shape[0]),\n",
    "                                    desc=f\"Exportiere zusammengeführte GeoTIFF-Datei von {start_year} bis {end_year}\"):\n",
    "                    band_data = variable_data_subset[year_index,:,:]\n",
    "                    dt = cftime[start_index + year_index]\n",
    "                    band_desc = f\"{dt.year:04d}-{dt.month:02d}-{dt.day:02d}\"\n",
    "                    \n",
    "                    # Schreibe jede Jahresscheibe als Band\n",
    "                    dst.write(band_data, year_index + 1)\n",
    "                    dst.set_band_description(year_index + 1, band_desc)\n",
    "                    \n",
    "        else:\n",
    "            # Export als einzelne GeoTIFF-Dateien\n",
    "            if output_directory:\n",
    "                subset_directory_path = output_directory\n",
    "            else:\n",
    "                subset_directory_path = os.path.join(geotiff_folder, f\"{selected_variable}_{selected_definition}-individual\")\n",
    "                os.makedirs(subset_directory_path, exist_ok=True)\n",
    "            \n",
    "            for year_index in tqdm(range(variable_data_subset.shape[0]),\n",
    "                                   desc=\"Exportieren einzelner GeoTIFF-Dateien\"):\n",
    "                # Bestimmt das Datum für die aktuelle Zeitscheibe\n",
    "                dt = cftime[start_index + year_index]\n",
    "                dt_full = f\"{dt.year:04d}-{dt.month:02d}-{dt.day:02d}\"\n",
    "\n",
    "                # Definiert den Speicherort der Ausgabe-GeoTIFF-Datei            \n",
    "                output_filename = f\"{nc_file['variable_name']}_{nc_file['rcp']}_{nc_file['rcp_statistic']}_{dt_full}.tif\"\n",
    "                output_filepath = os.path.join(subset_directory_path, output_filename)\n",
    "\n",
    "                # Exportiert die aktuelle Zeitscheibe als GeoTIFF\n",
    "                with rasterio.open(\n",
    "                    output_filepath,\n",
    "                    \"w\",\n",
    "                    driver=\"GTiff\",\n",
    "                    dtype=str(variable_data_subset.dtype),\n",
    "                    width=variable_data_subset.shape[2],\n",
    "                    height=variable_data_subset.shape[1],\n",
    "                    count=1,\n",
    "                    crs=\"EPSG:4326\",\n",
    "                    nodata=-9999,\n",
    "                    transform=transform,\n",
    "                ) as dst:\n",
    "                    year_precipitation_data = variable_data_subset[year_index, :, :]\n",
    "                    dst.write(year_precipitation_data, 1)\n",
    "                    dst.set_band_description(1, f\"{dt.year:04d}-{dt.month:02d}-{dt.day:02d}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2 Ausgewählte NetCDF4-Datei(en) in GeoTIFF-Datei(en) exportieren"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0729c6574572481eb33af9ae2dbcc108",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Exportiere zusammengeführte GeoTIFF-Datei von 1986 bis 2085:   0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "18fcf6acba2c4918b01c31b1952b1a47",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Exportiere zusammengeführte GeoTIFF-Datei von 1986 bis 2085:   0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "17d7b9d0f9b649219f60119142f48bcb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Exportiere zusammengeführte GeoTIFF-Datei von 1986 bis 2085:   0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "42ea2174dbfa43299fa94ebf80816030",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Exportiere zusammengeführte GeoTIFF-Datei von 1986 bis 2085:   0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1c4e7559195e489c96b03172bce1a854",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Exportieren einzelner GeoTIFF-Dateien:   0%|          | 0/6 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2b8ab97fd51548a9bb560ea131e4d368",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Exportieren einzelner GeoTIFF-Dateien:   0%|          | 0/6 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a4d4f4bb10bf4c008dbe8f6c8b8358f9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Exportieren einzelner GeoTIFF-Dateien:   0%|          | 0/6 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ca4fbf973a1c46be8fd6a52256db2517",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Exportieren einzelner GeoTIFF-Dateien:   0%|          | 0/6 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if __name__ == \"__main__\":\n",
    "    # Exportieren Sie alle NetCDF-Dateien als zusammengeführte GeoTIFF-Dateien.\n",
    "    for nc_file in nc_files_subset:\n",
    "        main_export_geotiff(\n",
    "            nc_file=nc_file,\n",
    "            bounding_box=None,\n",
    "            merged=True\n",
    "            )\n",
    "\n",
    "    # Exportieren Sie alle NetCDF-Dateien als einzelne GeoTIFF-Dateien.\n",
    "    for nc_file in nc_files_subset:\n",
    "        main_export_geotiff(\n",
    "            nc_file=nc_file,\n",
    "            bounding_box=None,\n",
    "            start_year = 1995,\n",
    "            end_year = 2000,\n",
    "            merged = False,\n",
    "            )\n",
    "            \n",
    "    # Zusätzlicher Fall (Erweiterte Filterung)\n",
    "    # temp_folder = os.path.join(geotiff_folder, \"_temp_folder\")\n",
    "    # os.makedirs(temp_folder, exist_ok=True)\n",
    "    \n",
    "    # main_export_geotiff(\n",
    "    #     nc_file=nc_files[0],\n",
    "    #     bounding_box=bbox_wgs84_konstanz_standard,\n",
    "    #     start_year=1995,\n",
    "    #     end_year=2000,\n",
    "    #     merged=True,\n",
    "    #     output_directory=temp_folder)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Analyse und Visualisierung Optionen"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.1 Vorbereitung der Daten für die Visualisierung"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>HWD_EU_clim ate_rcp45_m ean</th>\n",
       "      <th>HWD_EU_clim ate_rcp45_s tdev</th>\n",
       "      <th>HWD_EU_clim ate_rcp85_m ean</th>\n",
       "      <th>HWD_EU_clim ate_rcp85_s tdev</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</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>1986-01-01</th>\n",
       "      <td>47.60</td>\n",
       "      <td>9.00</td>\n",
       "      <td>0.69</td>\n",
       "      <td>1.18</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986-01-01</th>\n",
       "      <td>47.60</td>\n",
       "      <td>9.10</td>\n",
       "      <td>0.68</td>\n",
       "      <td>1.17</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986-01-01</th>\n",
       "      <td>47.60</td>\n",
       "      <td>9.20</td>\n",
       "      <td>0.66</td>\n",
       "      <td>1.13</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986-01-01</th>\n",
       "      <td>47.70</td>\n",
       "      <td>9.00</td>\n",
       "      <td>0.67</td>\n",
       "      <td>1.16</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986-01-01</th>\n",
       "      <td>47.70</td>\n",
       "      <td>9.10</td>\n",
       "      <td>0.67</td>\n",
       "      <td>1.23</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.81</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             lat  lon  HWD_EU_clim ate_rcp45_m ean  \\\n",
       "time                                                 \n",
       "1986-01-01 47.60 9.00                     0.69       \n",
       "1986-01-01 47.60 9.10                     0.68       \n",
       "1986-01-01 47.60 9.20                     0.66       \n",
       "1986-01-01 47.70 9.00                     0.67       \n",
       "1986-01-01 47.70 9.10                     0.67       \n",
       "\n",
       "            HWD_EU_clim ate_rcp45_s tdev  HWD_EU_clim ate_rcp85_m ean  \\\n",
       "time                                                                    \n",
       "1986-01-01                     1.18                          0.69       \n",
       "1986-01-01                     1.17                          0.68       \n",
       "1986-01-01                     1.13                          0.66       \n",
       "1986-01-01                     1.16                          0.67       \n",
       "1986-01-01                     1.23                          0.67       \n",
       "\n",
       "            HWD_EU_clim ate_rcp85_s tdev  \n",
       "time                                      \n",
       "1986-01-01                     0.74       \n",
       "1986-01-01                     0.76       \n",
       "1986-01-01                     0.74       \n",
       "1986-01-01                     0.71       \n",
       "1986-01-01                     0.81       "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Daten für die Region Konstanz filtern (WGS84-Format)\n",
    "lon_min, lat_min, lon_max, lat_max = bbox_wgs84_konstanz_standard\n",
    "\n",
    "# DataFrame mit einer Abfrage filtern\n",
    "filtered_df = (\n",
    "    df_merged.query(\n",
    "        \"@lat_min <= lat <= @lat_max and @lon_min <= lon <= @lon_max\"\n",
    "    )\n",
    "    .reset_index()\n",
    "    .set_index(\"time\")\n",
    ")\n",
    "\n",
    "# DataFrame anzeigen\n",
    "df_wrapped = wrap_column_names(filtered_df, width=11)\n",
    "df_wrapped.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.2 Daten filtern und Monatsdurchschnitt berechnen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>HWD_EU_clim ate_rcp45_m ean</th>\n",
       "      <th>HWD_EU_clim ate_rcp45_s tdev</th>\n",
       "      <th>HWD_EU_clim ate_rcp85_m ean</th>\n",
       "      <th>HWD_EU_clim ate_rcp85_s tdev</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1986-01-01</th>\n",
       "      <td>0.67</td>\n",
       "      <td>1.14</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987-01-01</th>\n",
       "      <td>0.79</td>\n",
       "      <td>1.14</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988-01-01</th>\n",
       "      <td>0.92</td>\n",
       "      <td>1.14</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989-01-01</th>\n",
       "      <td>0.93</td>\n",
       "      <td>1.14</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-01-01</th>\n",
       "      <td>0.95</td>\n",
       "      <td>1.14</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.73</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            HWD_EU_clim ate_rcp45_m ean  HWD_EU_clim ate_rcp45_s tdev  \\\n",
       "time                                                                    \n",
       "1986-01-01                     0.67                         1.14        \n",
       "1987-01-01                     0.79                         1.14        \n",
       "1988-01-01                     0.92                         1.14        \n",
       "1989-01-01                     0.93                         1.14        \n",
       "1990-01-01                     0.95                         1.14        \n",
       "\n",
       "            HWD_EU_clim ate_rcp85_m ean  HWD_EU_clim ate_rcp85_s tdev  \n",
       "time                                                                   \n",
       "1986-01-01                     0.67                         0.73       \n",
       "1987-01-01                     0.79                         0.73       \n",
       "1988-01-01                     0.92                         0.73       \n",
       "1989-01-01                     0.93                         0.73       \n",
       "1990-01-01                     0.95                         0.73       "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Gruppierung nach dem 'time'-Index und Berechnung des Durchschnitts für jede Gruppe\n",
    "filtered_df_average = filtered_df.groupby(level='time').mean()\n",
    "filtered_df_average = filtered_df_average.drop(columns=['lat', 'lon'])\n",
    "\n",
    "# DataFrame anzeigen\n",
    "df_wrapped = wrap_column_names(filtered_df_average, width=11)\n",
    "df_wrapped.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.3 Definieren einer Funktion zur Erstellung eines Liniendiagramms mit Fehler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "\n",
    "def plot_with_shaded_area(ax, x, y_mean, y_stdev, line_color, fill_color, line_label, fill_label, marker_style):\n",
    "    \"\"\"Hilfsfunktion zum Plotten von Mittelwertlinien mit schattiertem Fehlerbereich.\"\"\"\n",
    "    ax.plot(x, y_mean, color=line_color, label=line_label, marker=marker_style, markevery=5, linestyle='--')\n",
    "    ax.fill_between(x, y_mean - y_stdev, y_mean + y_stdev, color=fill_color, alpha=0.3, label=fill_label)\n",
    "\n",
    "def plot_line_and_shade(filtered_df_average, variable_name_list):\n",
    "    # Diagramm erstellen\n",
    "    fig, ax = plt.subplots(figsize=(13, 7), facecolor='#f1f1f1', edgecolor='k')\n",
    "\n",
    "    y_max_list = []\n",
    "    y_min_list = []\n",
    "    for variable_name in variable_name_list:\n",
    "        # Daten für RCP4.5 plotten\n",
    "        plot_with_shaded_area(\n",
    "            ax=ax,\n",
    "            x=filtered_df_average.index,\n",
    "            y_mean=filtered_df_average[f\"{variable_name}_rcp45_mean\"],\n",
    "            y_stdev=filtered_df_average[f\"{variable_name}_rcp45_stdev\"],\n",
    "            line_color='#1f77b4',\n",
    "            fill_color='#aec7e8',\n",
    "            line_label=f\"{variable_name}_rcp45_mean\",\n",
    "            fill_label=f\"{variable_name}_rcp45_stdev\",\n",
    "            marker_style=None\n",
    "        )\n",
    "\n",
    "        # Daten für RCP8.5 plotten\n",
    "        plot_with_shaded_area(\n",
    "            ax=ax,\n",
    "            x=filtered_df_average.index,\n",
    "            y_mean=filtered_df_average[f\"{variable_name}_rcp85_mean\"],\n",
    "            y_stdev=filtered_df_average[f\"{variable_name}_rcp85_stdev\"],\n",
    "            line_color='#ff7f0e',\n",
    "            fill_color='#ffbb78',\n",
    "            line_label=f\"{variable_name}_rcp85_mean\",\n",
    "            fill_label=f\"{variable_name}_rcp85_stdev\",\n",
    "            marker_style=None\n",
    "        )\n",
    "        \n",
    "        # Dynamische Anpassung der Y-Achse\n",
    "        interval = 1\n",
    "        rcp45_min = filtered_df_average[f\"{variable_name}_rcp45_mean\"].min() - \\\n",
    "                    filtered_df_average[f\"{variable_name}_rcp45_stdev\"].max()\n",
    "        rcp85_min = filtered_df_average[f\"{variable_name}_rcp85_mean\"].min() - \\\n",
    "                    filtered_df_average[f\"{variable_name}_rcp85_stdev\"].max()\n",
    "        y_min = min(rcp45_min, rcp85_min) - 0.5\n",
    "        y_min = y_min // interval * interval\n",
    "\n",
    "        rcp45_max = filtered_df_average[f\"{variable_name}_rcp45_mean\"].max() + \\\n",
    "                    filtered_df_average[f\"{variable_name}_rcp45_stdev\"].max()\n",
    "        rcp85_max = filtered_df_average[f\"{variable_name}_rcp85_mean\"].max() + \\\n",
    "                    filtered_df_average[f\"{variable_name}_rcp85_stdev\"].max()\n",
    "        y_max = max(rcp45_max, rcp85_max) + 0.5\n",
    "        y_max = (y_max + interval) // interval * interval\n",
    "        \n",
    "        y_max_list.append(y_max)\n",
    "        y_min_list.append(y_min)\n",
    "\n",
    "    ax.set_ylim(min(y_min_list), max(y_max_list))\n",
    "    \n",
    "    # X-Achse für bessere Lesbarkeit anpassen\n",
    "    ax.set_xlim(filtered_df_average.index.min(), filtered_df_average.index.max())\n",
    "    ax.set_xticks(filtered_df_average.index[::5])\n",
    "    tick_positions = filtered_df_average.index[::5]\n",
    "    tick_labels = [str(pd.to_datetime(date).year) for date in tick_positions]\n",
    "    ax.set_xticks(ticks=tick_positions, labels=tick_labels, rotation=0)\n",
    "    \n",
    "    # Gitterlinien hinzufügen\n",
    "    ax.grid(visible=True, color='#b0b0b0', linestyle='--', linewidth=0.8, alpha=0.6)\n",
    "    ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%0.2f'))\n",
    "\n",
    "    # Achsenbeschriftungen und Titel anpassen\n",
    "    ax.set_xlabel('Jahr', fontsize=14)\n",
    "    ax.set_ylabel('Temperatur (°C)', fontsize=14, labelpad=10)\n",
    "    ax.set_title(\n",
    "        f\"{variable_name}\\n(Vergleich der Szenarien RCP 4.5 und RCP 8.5)\",\n",
    "        fontsize=14,\n",
    "        fontweight='bold'\n",
    "    )\n",
    "    \n",
    "    # Beschreibung und Quelle hinzufügen\n",
    "    plt.figtext(\n",
    "        0.65,\n",
    "        -0.04,\n",
    "        (\n",
    "            'Beschreibung: Gesamtzahl der Hitzewellentage und Kältetage.\\n'\n",
    "            'Temperaturstatistik für Europa, abgeleitet aus Klimaprojektionen.\\n'\n",
    "            'Copernicus Climate Change Service (C3S) Klimadatenspeicher (CDS).\\n'\n",
    "            'DOI: 10.24381/cds.8be2c014 (Zugriff am 14-10-2024)'\n",
    "        ),\n",
    "        ha='left',\n",
    "        va='center',\n",
    "        fontsize=9,\n",
    "        wrap=True,\n",
    "        backgroundcolor='w',\n",
    "    )\n",
    "    \n",
    "    # Legende Anpassungen\n",
    "    ax.legend(loc='upper left', fontsize=10, frameon=True, title='Scenario', title_fontsize=11)\n",
    "    \n",
    "    # Layout anpassen und Diagramm anzeigen\n",
    "    fig.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.4 Visualisierung des Liniendiagramms mit Fehler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1300x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if __name__ == \"__main__\":\n",
    "    # Variable des Einzeldatensatzes\n",
    "    # Dieser Code schlägt für Cold Spell Days fehl, weil die Daten für Konstanz leer sind\n",
    "    plot_line_and_shade(filtered_df_average=filtered_df_average,\n",
    "                        variable_name_list=[f\"{nc_files[0]['variable_name']}\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.5 Definieren eine Funktion zur Erstellung einer Heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.crs as ccrs\n",
    "import numpy as np\n",
    "\n",
    "def main_plt_plot(\n",
    "        nc_file=nc_file,\n",
    "        selected_year=None,\n",
    "        bounding_box=None):\n",
    "    \n",
    "    # Öffnet die NetCDF-Datei\n",
    "    nc_dataset = nc.Dataset(nc_file['path'], mode='r')\n",
    "    lat = nc_dataset.variables['lat'][:]\n",
    "    lon = nc_dataset.variables['lon'][:]\n",
    "\n",
    "    # Falls eine Begrenzungsbox angegeben wurde, filtere die Daten entsprechend\n",
    "    if bounding_box:\n",
    "        lat_indices = np.where((lat >= bounding_box[1]) & (lat <= bounding_box[3]))[0]\n",
    "        lon_indices = np.where((lon >= bounding_box[0]) & (lon <= bounding_box[2]))[0]\n",
    "\n",
    "        lat_subset = lat[lat_indices]\n",
    "        lon_subset = lon[lon_indices]\n",
    "    else:\n",
    "        lat_indices = slice(None)\n",
    "        lon_indices = slice(None)\n",
    "\n",
    "        lat_subset = lat\n",
    "        lon_subset = lon\n",
    "\n",
    "    # Extrahiere Variablen-Daten\n",
    "    variable_name = nc_file['variable_name']\n",
    "    variable_data = nc_dataset.variables[variable_name][..., lat_indices, lon_indices]\n",
    "    var_units = getattr(nc_dataset.variables[variable_name], \"units\", \"N/A\")\n",
    "\n",
    "    # Bestimmen Sie den Jahresindex auf der Grundlage von selected_year.\n",
    "    if selected_year < 1986:\n",
    "        year_index = 0\n",
    "        year = 1985\n",
    "    elif selected_year > 2085:\n",
    "        year_index = -1\n",
    "        year = 2085\n",
    "    else:\n",
    "        year_index = selected_year-1986\n",
    "        year = selected_year\n",
    "\n",
    "    # Extrahieren Sie die Daten für das ausgewählte Jahr.\n",
    "    band_data = variable_data[year_index]\n",
    "\n",
    "    # NaN-Werte für Perzentilberechnungen entfernen\n",
    "    band_data_nonan = band_data[~np.isnan(band_data)]\n",
    "    vmin = np.nanpercentile(band_data_nonan, 1)\n",
    "    vmax = np.nanpercentile(band_data_nonan, 99)\n",
    "\n",
    "    def dynamic_round(value):\n",
    "        # Bestimmen Sie die Größe des Wertes.\n",
    "        order_of_magnitude = np.floor(np.log10(abs(value)))\n",
    "        \n",
    "        # Verwenden Sie diese Größe, um die Genauigkeit dynamisch zu wählen.\n",
    "        if order_of_magnitude < -2:  # Werte kleiner als 0,01\n",
    "            return round(value, 3)\n",
    "        elif order_of_magnitude < -1:  # Werte zwischen 0,01 und 1\n",
    "            return round(value, 2)\n",
    "        elif order_of_magnitude < 0:  # Werte zwischen 1 und 10\n",
    "            return round(value, 1)\n",
    "        else:  # Werte 10 oder größer\n",
    "            return round(value)\n",
    "    \n",
    "    # Dynamische Rundung auf vmin und vmax anwenden\n",
    "    vmin = dynamic_round(vmin)\n",
    "    vmax = dynamic_round(vmax)\n",
    "\n",
    "    bins = 10\n",
    "    interval = (vmax - vmin) / bins\n",
    "    \n",
    "    # Erstellen Sie ein 2D-Netzgitter für die grafische Darstellung.\n",
    "    lon_grid, lat_grid = np.meshgrid(lon_subset, lat_subset)\n",
    "\n",
    "    # Erstelle die Figur\n",
    "    fig, ax = plt.subplots(\n",
    "        figsize=(12, 8),\n",
    "        facecolor='#f1f1f1',\n",
    "        edgecolor='k',\n",
    "        subplot_kw={'projection': ccrs.PlateCarree()}\n",
    "    )\n",
    "\n",
    "    # Kartenmerkmale hinzufügen\n",
    "    ax.coastlines(edgecolor='black', linewidth=1.5)\n",
    "    ax.add_feature(cfeature.BORDERS, edgecolor='black', linewidth=1.5)\n",
    "\n",
    "    # Erstellen Sie ein Farbnetzdiagramm mit der angegebenen Farbkarte und den Grenzen.\n",
    "    cmap = plt.get_cmap(\"viridis\", bins)\n",
    "    pcm = ax.pcolormesh(\n",
    "        lon_grid,\n",
    "        lat_grid,\n",
    "        band_data,\n",
    "        transform=ccrs.PlateCarree(),\n",
    "        cmap=cmap,\n",
    "        shading='auto',\n",
    "        vmin=vmin,\n",
    "        vmax=vmax,\n",
    "        )\n",
    "    \n",
    "    # Einen Farbbalken hinzufügen\n",
    "    ticks = np.linspace(vmin, vmax, num=bins + 1)\n",
    "    cbar = plt.colorbar(pcm, ax=ax, orientation='vertical', pad=0.02, ticks=ticks)\n",
    "    cbar.set_label(f\"{variable_name}\", fontsize=12)\n",
    "    cbar.ax.tick_params(labelsize=12)\n",
    "    \n",
    "    # Gitterlinien hinzufügen\n",
    "    gl = ax.gridlines(draw_labels=True,\n",
    "                      crs=ccrs.PlateCarree(),\n",
    "                      linewidth=0.8,\n",
    "                      color='gray',\n",
    "                      alpha=0.7,\n",
    "                      linestyle='--')\n",
    "    gl.top_labels = False \n",
    "    gl.right_labels = False\n",
    "    gl.xlabel_style = {'size': 10, 'color': 'black'}\n",
    "    gl.ylabel_style = {'size': 10, 'color': 'black'}\n",
    "    \n",
    "    # Titel und Beschriftungen hinzufügen\n",
    "    fig.text(0.5, 0.0, 'Longitude', ha='center', fontsize=14)\n",
    "    fig.text(0.06, 0.5, 'Latitude', va='center', rotation='vertical', fontsize=14)\n",
    "    ax.set_aspect(\"equal\")\n",
    "\n",
    "    # Einen Titel hinzufügen\n",
    "    ax.set_title(f\"{variable_name}, {year}\", fontsize=14)\n",
    "\n",
    "    # Layout anpassen und das Diagramm anzeigen\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.6 Visualisierung mit Heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\ShaileshShrestha\\anaconda3\\envs\\cds_env\\lib\\site-packages\\numpy\\lib\\_function_base_impl.py:4842: UserWarning: Warning: 'partition' will ignore the 'mask' of the MaskedArray.\n",
      "  arr.partition(\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\ShaileshShrestha\\anaconda3\\envs\\cds_env\\lib\\site-packages\\numpy\\lib\\_function_base_impl.py:4842: UserWarning: Warning: 'partition' will ignore the 'mask' of the MaskedArray.\n",
      "  arr.partition(\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if __name__ == \"__main__\":\n",
    "    # Beispiel für einen Anwendungsfall\n",
    "    main_plt_plot(nc_file=nc_files[0],\n",
    "                  selected_year=1990,\n",
    "                  )\n",
    "\n",
    "    main_plt_plot(nc_file=nc_files[0],\n",
    "                  selected_year=2010,\n",
    "                  )"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "cds_env",
   "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": "3.10.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}