diff --git a/video_prediction_tools/utils/plot_ambs_forecast.py b/video_prediction_tools/utils/plot_ambs_forecast.py
deleted file mode 100644
index e26f5a2b662f196fc3fe7ad7dec0134636891794..0000000000000000000000000000000000000000
--- a/video_prediction_tools/utils/plot_ambs_forecast.py
+++ /dev/null
@@ -1,134 +0,0 @@
-#!/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:])