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. #========================================================================================