Delete plot_ambs_forecast.py

video_prediction_tools/utils/plot_ambs_forecast.py

-#!/usr/bin/env python
-# coding: utf-8
-
-"""
-Script to plot video frame prediction forecasts of 2m temperature as well as the difference w.r.t. the ground truth.
-Data is expected to be saved in netCDF-files produced by main_visualize_postprocess.py (= the postprocessing step of
-the AMBS-workflow)
-"""
-
-import xarray as xr
-import numpy as np
-import pandas as pd
-
-import matplotlib
-
-matplotlib.use('Agg')
-import matplotlib.pyplot as plt
-import cartopy
-from mpl_toolkits.basemap import Basemap
-
-
-# The plot function
-
-def create_plot(data: xr.DataArray, data_ref: xr.DataArray, varname: str, fcst_hour: int, plt_fname: str):
-    """
-    Creates filled contour plot of the forecast data as well as the difference between forecast and analysis (ground
-    truth).
-    ML: So far, only plotting of the 2m temperature is supported (with 12 predicted hours/frames)
-    :param data: the forecasted data array to be plotted
-    :param data_ref: the reference data ('ground truth')
-    :param varname: the name of the variable
-    :param plt_fname: the filename to the store the plot
-    :return: -
-    """
-    method = create_plot.__name__
-
-    try:
-        coords = data.coords
-        # handle coordinates and forecast times
-        lat, lon = coords["lat"], coords["lon"]
-        dates_fcst = pd.to_datetime(coords["time_forecast"].data)
-    except Exception as err:
-        print("%{0}: Could not retrieve expected coordinates lat, lon and time_forecast from data.".format(method))
-        raise err
-
-    lons, lats = np.meshgrid(lon, lat)
-
-    date0 = dates_fcst[0] - (dates_fcst[1] - dates_fcst[0])
-    date0_str = date0.strftime("%Y-%m-%d %H:%M UTC")
-
-    fhhs = ((dates_fcst - date0) / pd.Timedelta('1 hour')).values
-
-    # check data to be plotted since programme is not generic so far
-    if np.shape(dates_fcst)[0] != 12:
-        raise ValueError("%{0}: Currently, only 12 hour forecast can be handled properly.".format(method))
-
-    if varname != "2t":
-        raise ValueError("%{0}: Currently, only 2m temperature is plotted nicely properly.".format(method))
-
-    # define levels
-    clevs = np.arange(-10., 40., 1.)
-    clevs_diff = np.arange(-10.5, 10.6, 1.)
-
-    # create fig and subplot axes
-    fig, axes = plt.subplots(2, 1, sharex=True, sharey=True, figsize=(6,12))
-    axes = axes.flatten()
-    cbar_labs = ["°C", "K"]
-    
-    for t in np.arange(2):
-        m = Basemap(projection='cyl', llcrnrlat=np.min(lat), urcrnrlat=np.max(lat),
-                    llcrnrlon=np.min(lon), urcrnrlon=np.max(lon), resolution='l', ax=axes[t])
-        m.drawcoastlines()
-        x, y = m(lons, lats)
-    
-        lat_lab = [1, 0, 0, 0]
-        axes[t].set_ylabel(u'Latitude', labelpad=32)
-        lon_lab = list(np.zeros(4))
-        if t == 1:
-            lon_lab = [0, 0, 0, 1]
-            axes[t].set_xlabel(u'Longitude', labelpad=17)
-    
-        m.drawmapboundary()
-        m.drawparallels(np.arange(0, 90, 5),labels=lat_lab, xoffset=0.5)
-        m.drawmeridians(np.arange(5, 355, 10),labels=lon_lab, yoffset=0.5)
-        if t == 0:
-            cs = m.contourf(x, y, data.isel(time_forecast=fcst_hour)-273.15, clevs, cmap=plt.get_cmap("jet"), ax=axes[t])
-            cbar_ticks = None
-        elif t == 1:
-            cs = m.contourf(x, y, data.isel(time_forecast=fcst_hour)-data_ref.isel(time_forecast=fcst_hour),
-                            clevs_diff, cmap=plt.get_cmap("PuOr"), ax=axes[t])
-            cbar_ticks = list(np.arange(-10.5, -2., 2.)) + [-0.5, 0.5] + list(np.arange(2.5, 10.6, 2.))
-            print(cbar_ticks)
-        # add colorbar.
-        pos = axes[t].get_position()
-
-        cbar_ax = fig.add_axes([0.95, pos.y0+0.08*(t*2-1), 0.02, pos.y1 - pos.y0])
-        cbar = fig.colorbar(cs, cax=cbar_ax, orientation="vertical",  ticks=cbar_ticks)
-        cbar.set_label(cbar_labs[t])
-    # save to disk
-    #plt.show()
-    #plt.subplots_adjust(top=0.92, bottom=0.08, left=0.10, right=0.95, hspace=-0.5, wspace=0.05)
-    plt.subplots_adjust(hspace=-0.5)
-    #plt.tight_layout()
-
-    plt.savefig(plt_fname, bbox_inches="tight")
-    plt.close()
-
-
-def main(args):
-
-    parser = ArgumentParser()
-
-    # add optional arguments which may be passed
-    parser.add_argument("-fname", "--filename", dest="filename", type=str,
-                        help="The path to the netCDF-file from which the plot data is retrieved.")
-    parser.add_argument("-fhour", "--forecast_hour", dest="forecast_hour", type=int,
-                        help="The forecast hour/lead time for which the plot should be created")
-
-    args = parser.parse_args()
-
-    filename = args.filename
-    fhh = args.forecast_hour
-
-    if os.path.isfile(filename):
-        raise FileNotFoundError("Could not find the indictaed netCDF-file '{0}'".format(filename))
-
-    with xr.open_dataset(filename) as dfile:
-        t2m_fcst, t2m_ref = dfile["2t_fcst"], dfile["2t_ref"]
-
-    create_plot(t2m_fcst, t2m_ref, "2t", fhh, "{0}_fhh{1:d}.png".format(filename[0:-3], fhh))
-
-
-if __name__ == "__main__":
-    main(sys.argv[1:])