cpf.figconf['axessize'] = [0.1, 0.1, 0.8, 0.8]
cpf.figconf['axesrange'] = [134.97, 136.09, 34.36, 35.30]
cpf.figconf['contour'] = True
cpf.figconf['contourlevels'] = max_dbz_levels
cpf.figconf['contourcolor'] = 'k'
cpf.figconf['gridline'] = True
cpf.figconf['ylabel'] = 'Lat'
cpf.figconf['xlabel'] = 'Lon'
cpf.figconf['xtick'] = [134.5, 135, 135.5, 136, 136.5, 137]
cpf.figconf['ytick'] = [34, 34.5, 35, 35.5]
cpf.figconf[
'title'] = 'Max BIMODALITY for variable ' + var + ' at ' + date
cpf.figconf[
'figname'] = '/Figure_BIMODALITY_vertmax_' + var + '_' + date
cpf.figconf['close'] = False
cpf.plot_x_y_cartopy(lon, lat, my_bimodality[:, :],
max_dbz[:, :], my_bimodality[:, :])
cpf.figconf['close'] = True
cpf.figconf['show'] = True
cpf.figconf['colorbar'] = False
cpf.figconf['shadedcolormap'] = 'Greys'
cpf.figconf['shadedmin'] = 0.0
cpf.figconf['shadedmax'] = 1.0
color_mask = 0.4 * np.ones(np.shape(radar_mask))
color_mask[radar_mask] = np.nan
cpf.plot_x_y_cartopy(lon, lat, color_mask, max_dbz[:, :],
color_mask)
#========================================================================================
#Generate regional averages of the moment.
#========================================================================================
cpf.figconf['ytick'] = [34, 34.5, 35, 35.5]
#cpf.figconf['show']=True
if my_kldgr.shape[2] > 1:
for il in plotlevels:
cpf.figconf[
'title'] = 'KLD G.R. for variable ' + var + ' at level ' + str(
int(ctl_dict['vlevels'][np.asscalar(
il)])) + ' at ' + date
cpf.figconf[
'figname'] = '/Figure_KLDGR_' + var + '_' + date + '_' + str(
int(ctl_dict['vlevels'][np.asscalar(il)]))
cpf.plot_x_y_cartopy(lon, lat, my_kldgr[:, :, il],
max_dbz[:, :, il], my_kldgr[:, :,
il])
else:
cpf.figconf[
'title'] = 'KLD G.R. for variable ' + var + ' at ' + date
cpf.figconf[
'figname'] = '/Figure_KLDGR_' + var + '_' + date
cpf.plot_x_y_cartopy(lon, lat, my_kldgr[:, :],
max_dbz[:, :, 0], my_kldgr[:, :])
#========================================================================================
#Generate regional averages of the moment.
#========================================================================================
cpf.figconf['ytick'] = [34, 34.5, 35, 35.5]
#cpf.figconf['show']=True
if my_grf.shape[2] > 1:
for il in plotlevels:
cpf.figconf[
'title'] = 'Sprd. G.R. for variable ' + var + ' at level ' + str(
int(ctl_dict['vlevels'][np.asscalar(
il)])) + ' at ' + date
cpf.figconf[
'figname'] = '/Figure_GRF_' + var + '_' + date + '_' + str(
int(ctl_dict['vlevels'][np.asscalar(il)]))
cpf.plot_x_y_cartopy(lon, lat, my_grf[:, :, il],
max_dbz[:, :, il], my_grf[:, :,
il])
else:
cpf.figconf[
'title'] = 'Sprd. G.R. for variable ' + var + ' at ' + date
cpf.figconf['figname'] = '/Figure_GRF_' + var + '_' + date
cpf.plot_x_y_cartopy(lon, lat, my_grf[:, :],
max_dbz[:, :, 0], my_grf[:, :])
#========================================================================================
#Generate regional averages of the moment.
#========================================================================================
grf_regional_mean[var][it, :], grf_regional_max[var][
cpf.figconf['ytick'] = [34, 34.5, 35, 35.5]
#cpf.figconf['show']=True
if my_skew.shape[2] > 1:
for il in plotlevels:
cpf.figconf[
'title'] = 'SKEW for variable ' + var + ' at level ' + str(
int(ctl_dict['vlevels'][np.asscalar(
il)])) + ' at ' + date
cpf.figconf[
'figname'] = '/Figure_SKEW_' + var + '_' + date + '_' + str(
int(ctl_dict['vlevels'][np.asscalar(il)]))
cpf.plot_x_y_cartopy(lon, lat, my_skew[:, :, il],
max_dbz[:, :, il], my_skew[:, :,
il])
else:
cpf.figconf[
'title'] = 'SKEW for variable ' + var + ' at ' + date
cpf.figconf['figname'] = '/Figure_SKEW_' + var + '_' + date
cpf.plot_x_y_cartopy(lon, lat, my_skew[:, :],
max_dbz[:, :, 0], my_skew[:, :])
#========================================================================================
#Generate regional averages of the moment.
#========================================================================================
skew_regional_mean[var][it, :], skew_regional_max[var][
]
#cpf.figconf['show']=True
if my_kld.shape[2] > 1:
for il in plotlevels:
cpf.figconf[
'title'] = 'KLD for variable ' + var + ' at level ' + str(
int(ctl_dict['vlevels'][np.asscalar(
il)])) + ' at ' + date
cpf.figconf[
'figname'] = '/Figure_KLD_' + my_reg + '_' + var + '_' + date + '_' + str(
int(ctl_dict['vlevels'][np.asscalar(il)]))
cpf.plot_x_y_cartopy(lon, lat, my_kld[:, :, il],
max_dbz[:, :,
il], my_kld[:, :, il])
else:
cpf.figconf[
'title'] = 'KLD for variable ' + var + ' at ' + date
cpf.figconf[
'figname'] = '/Figure_KLD_' + var + '_' + date
cpf.plot_x_y_cartopy(lon, lat, my_kld[:, :],
max_dbz[:, :, 0], my_kld[:, :])
#=========================================================================================
#Advance time
#=========================================================================================
cpf.figconf['axessize'] = [0.1, 0.1, 0.8, 0.8]
cpf.figconf['axesrange'] = [134.97, 136.09, 34.36, 35.30]
cpf.figconf['contour'] = True
cpf.figconf['contourlevels'] = max_dbz_levels
cpf.figconf['contourcolor'] = 'k'
cpf.figconf['gridline'] = True
cpf.figconf['ylabel'] = 'Lat'
cpf.figconf['xlabel'] = 'Lon'
cpf.figconf['xtick'] = [134.5, 135, 135.5, 136, 136.5, 137]
cpf.figconf['ytick'] = [34, 34.5, 35, 35.5]
cpf.figconf[
'title'] = 'Max KLD for variable ' + var + ' at ' + date
cpf.figconf[
'figname'] = '/Figure_KLD_vertmax_' + var + '_' + date
cpf.figconf['close'] = False
cpf.plot_x_y_cartopy(lon, lat, my_kld[:, :], max_dbz[:, :],
my_kld[:, :])
cpf.figconf['close'] = True
cpf.figconf['show'] = False
cpf.figconf['colorbar'] = False
cpf.figconf['shadedcolormap'] = 'Greys'
cpf.figconf['shadedmin'] = 0.0
cpf.figconf['shadedmax'] = 1.0
color_mask = 0.4 * np.ones(np.shape(radar_mask))
color_mask[radar_mask] = np.nan
cpf.plot_x_y_cartopy(lon, lat, color_mask, max_dbz[:, :],
color_mask)
#========================================================================================
#Generate regional averages of the moment.
#========================================================================================
