From ee869da58b7cacd77523c32ae5b7f129679f133d Mon Sep 17 00:00:00 2001 From: Jonas Gunz Date: Sat, 14 Oct 2023 00:44:11 +0200 Subject: custom colormap WIP --- test/cross.py | 29 +++++++++++++++++++++++++++-- 1 file changed, 27 insertions(+), 2 deletions(-) (limited to 'test') diff --git a/test/cross.py b/test/cross.py index de6b9be..6194630 100755 --- a/test/cross.py +++ b/test/cross.py @@ -1,10 +1,32 @@ #!/usr/bin/env python3 import matplotlib.pyplot as plt +import matplotlib as mpl +from matplotlib.colors import LinearSegmentedColormap import xarray as xr from metpy.interpolate import cross_section +clcov_cmap = { + 'red': ( + (0.0, 0.0, 0.0), + (0.1, 1.0, 1.0), + (1.0, 0.2, 0.2), + ), + 'green': ( + (0.0, 0.0, 0.0), + (0.1, 1.0, 1.0), + (1.0, 0.2, 0.2), + ), + 'blue': ( + (0.0, 1.0, 1.0), + (0.1, 1.0, 1.0), + (1.0, 0.2, 0.2), + ), +} + +mpl.colormaps.register(LinearSegmentedColormap('clcov', clcov_cmap)) + data = xr.load_dataset('dwd_icon-eu/combined.grib2', engine='cfgrib') lat, lon = (47.96, 11.99) data = data.sel(latitude=lat, longitude = lon, method='nearest') @@ -14,13 +36,16 @@ print(data) # start figure and set axis fig, ax = plt.subplots(figsize=(5, 5)) +ax.set_ylabel('Pressure level [hPa]') + #clc = ax.plot(data.step.values.astype('float64'), data.isobaricInhPa, data.ccl.transpose()) #clc = ax.imshow(data.ccl.transpose(), extent=(data.step.values.astype(float).min(), data.step.values.astype(float).max(), data.isobaricInhPa.min(), data.isobaricInhPa.max()), aspect='auto', cmap='Blues_r', vmin=0, vmax=100) #plt.colorbar(clc, label='clcov') -clc = ax.contourf(data.step.values.astype('float64'), data.isobaricInhPa, data.ccl.transpose(), cmap='Blues_r', vmin=0, vmax=100, levels=9) +# Blues_r +clc = ax.contourf(data.step.values.astype('float64'), data.isobaricInhPa, data.ccl.transpose(), cmap='clcov', vmin=0, vmax=100, levels=9) # use Format parameter for n/8 -plt.colorbar(clc, label='clcov', extendfrac=None, ticks=[100*n/8 for n in range(9)], format=lambda x,_: f'{int(x/12.5)}/8') +plt.colorbar(clc, label='cloudcov', extendfrac=None, ticks=[100*n/8 for n in range(9)], format=lambda x,_: f'{int(x/12.5)}/8') cf = ax.contour(data.step.values.astype('float64'), data.isobaricInhPa, data.t.metpy.convert_units('degC').transpose()) -- cgit v1.2.3