{
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   "id": "d157bce7-ea0e-45ad-9c4e-7ee254b54d92",
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   "source": [
    "# ICON Training - Hands-on Session -  Basic plot script using Matplotlib and Cartopy\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82416258-d6c8-4e5f-ab72-f32245cd9da7",
   "metadata": {
    "tags": []
   },
   "source": [
    "This is a Python 3 Jupyter notebook. We start by loading the necessary modules."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1a1867c-bd4a-4a3c-bfc5-8e43ec7e53fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "import getpass\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import cartopy\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bae0f2f2-86ff-45b5-88ae-67d13caa3a63",
   "metadata": {},
   "source": [
    "Define the directory and filenames."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "56c07887-ca1f-4bd7-8c1c-bc1e7751c68d",
   "metadata": {},
   "outputs": [],
   "source": [
    "user   = getpass.getuser()\n",
    "EXPDIR = f\"/scratch/{user[0]}/{user}/exercise_lam/\"\n",
    "\n",
    "# file name\n",
    "filename_ll = f\"{EXPDIR}/ilfff01000000ML.nc\"\n",
    "\n",
    "# output file\n",
    "output_filename1 = \"./TQV_regular.png\"\n",
    "output_filename2 = \"./TQC_regular.png\"\n",
    "\n",
    "# colorbar and label\n",
    "plot_color    = \"gist_rainbow\"\n",
    "plot_label    = \"kg m-2\"\n",
    "\n",
    "#select the timestep to be plotted (note that we have only 1 timestep per file)\n",
    "timestep = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6ab0b55-cca8-4ac7-a671-f5654f156960",
   "metadata": {},
   "source": [
    "Then open the **regular (lat/lon)** datafile and preload coordinate arrays:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13beebb9-6952-455c-bdb3-5394248bae16",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_ll = xr.open_dataset(filename_ll)\n",
    "lon   = ds_ll[\"tqv_dia\"].lon\n",
    "lat   = ds_ll[\"tqv_dia\"].lat"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1aa04af-f4d1-4064-957a-8d13b26e8d0d",
   "metadata": {},
   "source": [
    "Create 2 plots. One for tqv and one for tqc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12ba7619-d13c-4102-8160-306c24822748",
   "metadata": {},
   "outputs": [],
   "source": [
    "# process tqv_dia\n",
    "#\n",
    "fig1 = plt.figure(figsize=(9, 9))\n",
    "tqv = ds_ll[\"tqv_dia\"][timestep,:,:]\n",
    "\n",
    "plot_min = np.round(np.amin(tqv))\n",
    "plot_max = np.round(np.amax(tqv))\n",
    "\n",
    "ax = plt.axes(projection=cartopy.crs.PlateCarree())\n",
    "ax.add_feature(cartopy.feature.BORDERS,edgecolor='gray')\n",
    "ax.contourf(lon, lat, tqv, 60, cmap = plot_color, transform = cartopy.crs.PlateCarree())\n",
    "ax.gridlines(draw_labels=True, dms=True, x_inline=False, y_inline=False)\n",
    "plt.colorbar(plt.cm.ScalarMappable(cmap=plot_color,norm=plt.Normalize(plot_min,plot_max)),ax=ax, orientation='horizontal', label=plot_label)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "# process tqc_dia\n",
    "#\n",
    "fig2 = plt.figure(figsize=(9, 9))\n",
    "\n",
    "tqc           = ds_ll[\"tqc_dia\"][timestep,:,:]\n",
    "\n",
    "plot_min = np.round(np.amin(tqc))\n",
    "plot_max = np.round(np.amax(tqc))\n",
    "\n",
    "ax = plt.axes(projection=cartopy.crs.PlateCarree())\n",
    "ax.add_feature(cartopy.feature.BORDERS,edgecolor='gray')\n",
    "ax.contourf(lon, lat, tqc, 60, cmap = plot_color, transform = cartopy.crs.PlateCarree())\n",
    "ax.gridlines(draw_labels=True, dms=True, x_inline=False, y_inline=False)\n",
    "plt.colorbar(plt.cm.ScalarMappable(cmap=plot_color,norm=plt.Normalize(plot_min,plot_max)),ax=ax, orientation='horizontal', label=plot_label)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "fig1.savefig(output_filename1, dpi=200)\n",
    "fig2.savefig(output_filename2, dpi=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57398f8f-f9b9-4241-9afc-313dd4c24b55",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "*Author info: Deutscher Wetterdienst (DWD) 2025 ::  icon@dwd.de. For a full list of contributors, see CONTRIBUTING in the root directory. License info: see LICENSE file.*"
   ]
  }
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