plot_kld_5min[np.logical_not(radar_mask)] = np.nan
plot_kld_diff[np.logical_not(radar_mask)] = np.nan
#Axes limits
#my_axes = [icoldelta*(icol-1)+hmargin+hoffset,irowdelta*(irow-1)+vmargin+voffset,irowdelta-2*hmargin,icoldelta-2*vmargin]
ax = axs[
irow,
icol] #plt.axes( my_axes , facecolor=None , projection=ccrs.PlateCarree() )
#The pcolor
ncolors = 12
smin = -60
smax = 60
delta = (smax - smin) / ncolors
#p=ax.pcolor(lon , lat , np.transpose( np.squeeze( plot_kld_5min ) ) ,
# transform=ccrs.PlateCarree(),vmin=smin , vmax=smax ,cmap=cpf.cmap_discretize('YlGn',21) )
my_map = cpf.cmap_discretize('coolwarm', 11)
p = ax.contourf(lon,
lat,
np.transpose(np.squeeze(plot_kld_diff)),
transform=ccrs.PlateCarree(),
vmin=smin,
vmax=smax,
cmap=my_map)
#m = plt.cm.ScalarMappable(cmap=my_map)
#m.set_array(np.transpose(plot_kld_diff))
#m.set_clim(smin,smax)
#cb=plt.colorbar(m,ax=ax,shrink=0.9,boundaries=np.arange(smin,smax+delta,delta))
ax.set_extent(axesrange, ccrs.PlateCarree())
gl = ax.gridlines(crs=ccrs.PlateCarree(),
draw_labels=True,
fig = plt.figure(1, figsize=[6.5, 5])
ax = fig.add_subplot(111, projection=ccrs.PlateCarree())
#The pcolor
smin = np.nanmin(my_data['topo'])
smax = np.nanmax(my_data['topo'])
p = ax.pcolor(lon,
lat,
topo,
transform=ccrs.PlateCarree(),
vmin=smin,
vmax=smax,
cmap=cpf.cmap_discretize('copper_r', 41))
ax.set_extent(axesrange, ccrs.PlateCarree())
topo[topo > 1.2] = np.nan
#Colorbar
cb = plt.colorbar(p, ax=ax, orientation='vertical', shrink=0.9)
cb.ax.tick_params(labelsize=10)
p = ax.pcolor(lon,
lat,
topo,
transform=ccrs.PlateCarree(),
vmin=-1.0,
vmax=10.0,
cmap=cpf.cmap_discretize('Blues_r', 10))
ax.set_extent(axesrange, ccrs.PlateCarree())
# for key in skew :
for var in plot_variables :
if var in ctl_dict['var_list'] :
#Plot moments.
my_skew=skew[var]
#my_skew[ my_skew > 100 ] = np.nan #There are som inf values in the reflectivity field.
my_skew[ my_skew == undef ] = np.nan
print('Skew for Var ',var,' ',(np.nanmin(my_skew)),np.nanmax(my_skew))
date=ctime.strftime("%Y%m%d%H%M%S")
cpf.set_default() #Restore defaults
my_map=cpf.cmap_discretize('RdBu_r',10)
cpf.figconf['figpath']=plotbasedir
cpf.figconf['figsize']=(12,10)
cpf.figconf['titlefontsize']=20
cpf.figconf['labelfontsize']=12
cpf.figconf['pcolor']=True
cpf.figconf['shadedmin']=-1.5
if var == 'w' :
cpf.figconf['shadedmax']=1.5
else :
cpf.figconf['shadedmax']=1.5
cpf.figconf['shadedcolormap']=my_map
cpf.figconf['colorbar']=False
cpf.figconf['colorbarfontsize']=15
cpf.figconf['axessize']=[0.1,0.1,0.8,0.8]
cpf.figconf['contour']=True
ctl=ctl_dict,
records=np.array([0, 1]))
lat = np.squeeze(tmp[:, :, 1])
lon = np.squeeze(tmp[:, :, 0])
#=========================================================
# READ'N PLOT
#=========================================================
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
from matplotlib import patches
ncolors = 10
my_map = cpf.cmap_discretize('Blues', ncolors)
tmp_lon = lon[90, :]
levels = ctl_dict['vlevels']
tick_levels = [1000, 850, 700, 500, 300]
levels_str = list()
levels = np.delete(levels, 4, axis=0)
levels[3] = 850.0
titles = ['(a)', '(b)', '(c)', '(d)', '(e)', '(f)', '(g)', '(h)', '(i)']
#Get the level string list.
levels_str = []
for ilev in tick_levels:
levels_str.append(str(int(ilev)))
#ax=plt.subplot(121,projection=ccrs.PlateCarree())
ax1 = axs[0,
0] #plt.axes([0.05, 0.075, 0.44, 1.0],projection=ccrs.PlateCarree())
#ax = fig.add_subplot(111, projection=ccrs.PlateCarree())
#The pcolor
smin = np.nanmin(my_data['topo'])
smax = np.nanmax(my_data['topo'])
p = ax1.pcolor(lon,
lat,
topo,
transform=ccrs.PlateCarree(),
vmin=smin,
vmax=smax,
cmap=cpf.cmap_discretize('copper_r', 41))
topo[topo > 1.2] = np.nan
#Colorbar
p = ax1.pcolor(lon,
lat,
topo,
transform=ccrs.PlateCarree(),
vmin=-1.0,
vmax=10.0,
cmap=cpf.cmap_discretize('Blues_r', 10))
gl = ax1.gridlines(crs=ccrs.PlateCarree(),
draw_labels=True,
linewidth=1.0,
color='k',
alpha=0.5,
xtick = [134.5, 135, 135.5, 136, 136.5, 137]
ytick = [34, 34.5, 35, 35.5]
axesrange = [134.97, 136.09, 34.36, 35.30]
titles = [
'(a) - 5MIN ', '(b) - 2MIN ', '(c) - 1MIN ', '(d) - 30SEC ',
'(e) - 5MIN-4D ', '(f) - 1MIN-4D '
]
for iexp, my_exp in enumerate(exps):
varsh = plot_kld_mean[:, :, iexp]
varc = plot_dbz_mean[:, :, iexp]
if iexp == 0:
my_map = cpf.cmap_discretize('Blues', 10)
smin = 0
smax = 5.0
else:
my_map = cpf.cmap_discretize('Spectral', 10)
smin = -50.0
smax = 50.0
ax = axs[irow, icol]
#Axes limits
#my_axes = [icoldelta*(icol-1)+hmargin+hoffset,irowdelta*(irow-1)+vmargin+voffset,irowdelta-2*hmargin,icoldelta-2*vmargin]
#ax = plt.axes( my_axes , facecolor=None , projection=ccrs.PlateCarree() )
#The pcolor
