maske = ~np.isnan(hhh) & ~np.isnan(ppp) fig = plt.figure(figsize=(14, 12)) #zzz = str(jahr)+'-'+str(monat)+'-'+str(tag)+'--'+str(stunde)+':'+str(minute)+' UTC' #fig.suptitle(zzz + ' UTC') ################### ax1 = fig.add_subplot(221, aspect='auto') #plt.subplot(2,2,1) plt.pcolormesh(dpr_lon, dpr_lat, np.ma.masked_invalid(dpr_pp_surf), vmin=np.nanmin(dpr_pp_surf), vmax=np.nanmax(dpr_pp_surf), cmap=get_miub_cmap()) cbar = plt.colorbar() cbar.set_label('Ref. in dbz') plot_borders(ax1) plot_radar(blon, blat, ax1, reproject=True, cband=False, col='black') plt.plot(dpr_lon[:, 0], dpr_lat[:, 0], color='black', lw=1) plt.plot(dpr_lon[:, -1], dpr_lat[:, -1], color='black', lw=1) plt.plot(dpr_lon[:, dpr_lon.shape[1] / 2], dpr_lat[:, dpr_lon.shape[1] / 2], color='black', lw=1, ls='--') ax1 = plt.scatter(bonnlon, bonnlat, c=50, s=50, color='red') plt.grid()
def plot_all(): ax1 = fig.add_subplot(231, aspect='equal') plt.pcolormesh(x, y, rwdata, cmap=get_miub_cmap(), vmin=0.1,vmax=50, zorder=2) cb = plt.colorbar(shrink=0.5) cb.set_label("Ref (dbz)",fontsize=ff) #cb.set_label("Rainrate (mm/h)",fontsize=ff) cb.ax.tick_params(labelsize=ff) plot_borders(ax1) plt.title('RADOLAN Ref: \n'+'20' + str(pfad_radolan[-20:-18])+'-'+str(pfad_radolan[-18:-16])+'-'+str(pfad_radolan[-16:-14])+ ' T: '+str(pfad_radolan[-14:-10]) + '00 UTC',fontsize=ff) #RW Product Polar Stereo plt.xlabel("x [km] ",fontsize=ff) plt.ylabel("y [km] ",fontsize=ff) plt.grid(color='r') plt.xlim(-420,390) plt.ylim(-4700, -3700) ax2 = fig.add_subplot(232, aspect='equal') pm2 = plt.pcolormesh(gprof_x, gprof_y,np.ma.masked_invalid(gprof_pp[latstart:latend]), cmap=my_cmap,vmin=0.1,vmax=10, zorder=2) cb = plt.colorbar(shrink=0.5) cb.set_label("Rainrate (mm/h)",fontsize=ff) cb.ax.tick_params(labelsize=ff) plt.xlabel("x [km] ",fontsize=ff) plt.ylabel("y [km] ",fontsize=ff) plt.title('GPM GPROF Rainrate: \n' + str(pfad_gprof_g[66:70]) + '-' +str(pfad_gprof_g[70:72])+ '-' + str(pfad_gprof_g[72:74]) + ' T: ' +str(pfad_gprof_g[76:82]) + '-' + str(pfad_gprof_g[84:90]) + ' UTC',fontsize=ff) plot_borders(ax2) plt.xticks(fontsize=ff) plt.yticks(fontsize=ff) plt.grid(color='r') plt.tight_layout() ax2.set_xlim(ax1.get_xlim()) ax2.set_ylim(ax1.get_ylim()) ax37 = fig.add_subplot(233, aspect='equal') plt.pcolormesh(dpr_x, dpr_y,np.ma.masked_invalid(dpr_pp[latstartd:latendd]), cmap=my_cmap,vmin=0.1,vmax=10, zorder=2) cb = plt.colorbar(shrink=0.5) cb.set_label("Rainrate (mm/h)",fontsize=ff) cb.ax.tick_params(labelsize=ff) plt.xlabel("x [km] ",fontsize=ff) plt.ylabel("y [km] ",fontsize=ff) plt.title('GPM DPR Rainrate: \n' + str(pfad_gprof_g[66:70]) + '-' +str(pfad_gprof_g[70:72])+ '-' + str(pfad_gprof_g[72:74]) + ' T: ' +str(pfad_gprof_g[76:82]) + '-' + str(pfad_gprof_g[84:90]) + ' UTC',fontsize=ff) plot_borders(ax37) plt.xticks(fontsize=ff) plt.yticks(fontsize=ff) plt.grid(color='r') ax37.set_xlim(ax1.get_xlim()) ax37.set_ylim(ax1.get_ylim()) ################################## ax29 = fig.add_subplot(234, aspect='equal') #pm2 = plt.pcolormesh(gprof_x, gprof_y,np.ma.masked_invalid(gprof_pp[latstart:latend]), # cmap=my_cmap,vmin=0.1,vmax=10, zorder=2) pm2 = plt.pcolormesh(gprof_x, gprof_y,np.ma.masked_invalid(gprof_snow[latstart:latend]), cmap=get_miub_cmap(),vmin=0,vmax=5, zorder=1) cb = plt.colorbar(shrink=0.5) cb.set_label("SnowCoverIndex ",fontsize=ff) cb.ax.tick_params(labelsize=ff) plt.xlabel("x [km] ",fontsize=ff) plt.ylabel("y [km] ",fontsize=ff) plt.title('GPM GPROF SnowCoverIndex: \n' + str(pfad_gprof_g[66:70]) + '-' +str(pfad_gprof_g[70:72])+ '-' + str(pfad_gprof_g[72:74]) + ' T: ' +str(pfad_gprof_g[76:82]) + '-' + str(pfad_gprof_g[84:90]) + ' UTC',fontsize=ff) plot_borders(ax29) plt.xticks(fontsize=ff) plt.yticks(fontsize=ff) plt.grid(color='r') #plt.tight_layout() ax29.set_xlim(ax1.get_xlim()) ax29.set_ylim(ax1.get_ylim()) from pcc import get_2_cmap ax28 = fig.add_subplot(235, aspect='equal') pm2 = plt.pcolormesh(gprof_x, gprof_y,np.ma.masked_invalid(gprof_l[latstart:latend]), cmap=get_2_cmap(),vmin=0,vmax=1, zorder=1) cb = plt.colorbar(shrink=0.5) cb.set_label("LiquidWaterFraction",fontsize=ff) cb.ax.tick_params(labelsize=ff) plt.xlabel("x [km] ",fontsize=ff) plt.ylabel("y [km] ",fontsize=ff) plt.title('GPM GPROF LiquidWaterFraction: \n' + str(pfad_gprof_g[66:70]) + '-' +str(pfad_gprof_g[70:72])+ '-' + str(pfad_gprof_g[72:74]) + ' T: ' +str(pfad_gprof_g[76:82]) + '-' + str(pfad_gprof_g[84:90]) + ' UTC',fontsize=ff) plot_borders(ax28) plt.xticks(fontsize=ff) plt.yticks(fontsize=ff) plt.grid(color='r') #plt.tight_layout() ax28.set_xlim(ax1.get_xlim()) ax28.set_ylim(ax1.get_ylim())
plt.ylim(-4700, -3700) plt.grid() plt.show() # Radarausschnitt dpr_pp_surf[np.where(r > radius)]=np.nan fig = plt.figure(figsize=(12,10)) zzz = str(jahr)+'-'+str(monat)+'-'+str(tag)+'--'+str(stunde)+':'+str(minute)+' UTC' fig.suptitle(zzz + ' UTC') ################### ax1 = fig.add_subplot(221, aspect='auto') #plt.subplot(2,2,1) plt.pcolormesh(dpr_lon, dpr_lat,np.ma.masked_invalid(dpr_pp_surf), vmin=np.nanmin(pp_surf), vmax=np.nanmax(pp_surf), cmap=get_miub_cmap()) cbar = plt.colorbar() cbar.set_label('Ref. in dbz') plot_borders(ax1) plot_radar(bonnlon, bonnlat, ax1, reproject=False, cband=False,col='black') #ax1 = plt.scatter(lon_ppi, lat_ppi, c=50 ,s=50, color='red') plt.scatter(k1,l1, c=50 ,s=50, color='red') plt.scatter(k2,l1, c=50 ,s=50, color='red') plt.scatter(k1,l2, c=50 ,s=50, color='red') plt.scatter(k2,l2, c=50 ,s=50, color='red') plt.grid() plt.xlim(-420,390) plt.ylim(-4700, -3700)
def plot_all(): ax1 = fig.add_subplot(231, aspect='equal') plt.pcolormesh(x, y, rwdata, cmap=get_miub_cmap(), vmin=0.1, vmax=50, zorder=2) cb = plt.colorbar(shrink=0.5) cb.set_label("Ref (dbz)", fontsize=ff) #cb.set_label("Rainrate (mm/h)",fontsize=ff) cb.ax.tick_params(labelsize=ff) plot_borders(ax1) plt.title('RADOLAN Ref: \n' + '20' + str(pfad_radolan[-20:-18]) + '-' + str(pfad_radolan[-18:-16]) + '-' + str(pfad_radolan[-16:-14]) + ' T: ' + str(pfad_radolan[-14:-10]) + '00 UTC', fontsize=ff) #RW Product Polar Stereo plt.xlabel("x [km] ", fontsize=ff) plt.ylabel("y [km] ", fontsize=ff) plt.grid(color='r') plt.xlim(-420, 390) plt.ylim(-4700, -3700) ax2 = fig.add_subplot(232, aspect='equal') pm2 = plt.pcolormesh(gprof_x, gprof_y, np.ma.masked_invalid(gprof_pp[latstart:latend]), cmap=my_cmap, vmin=0.1, vmax=10, zorder=2) cb = plt.colorbar(shrink=0.5) cb.set_label("Rainrate (mm/h)", fontsize=ff) cb.ax.tick_params(labelsize=ff) plt.xlabel("x [km] ", fontsize=ff) plt.ylabel("y [km] ", fontsize=ff) plt.title('GPM GPROF Rainrate: \n' + str(pfad_gprof_g[66:70]) + '-' + str(pfad_gprof_g[70:72]) + '-' + str(pfad_gprof_g[72:74]) + ' T: ' + str(pfad_gprof_g[76:82]) + '-' + str(pfad_gprof_g[84:90]) + ' UTC', fontsize=ff) plot_borders(ax2) plt.xticks(fontsize=ff) plt.yticks(fontsize=ff) plt.grid(color='r') plt.tight_layout() ax2.set_xlim(ax1.get_xlim()) ax2.set_ylim(ax1.get_ylim()) ax37 = fig.add_subplot(233, aspect='equal') plt.pcolormesh(dpr_x, dpr_y, np.ma.masked_invalid(dpr_pp[latstartd:latendd]), cmap=my_cmap, vmin=0.1, vmax=10, zorder=2) cb = plt.colorbar(shrink=0.5) cb.set_label("Rainrate (mm/h)", fontsize=ff) cb.ax.tick_params(labelsize=ff) plt.xlabel("x [km] ", fontsize=ff) plt.ylabel("y [km] ", fontsize=ff) plt.title('GPM DPR Rainrate: \n' + str(pfad_gprof_g[66:70]) + '-' + str(pfad_gprof_g[70:72]) + '-' + str(pfad_gprof_g[72:74]) + ' T: ' + str(pfad_gprof_g[76:82]) + '-' + str(pfad_gprof_g[84:90]) + ' UTC', fontsize=ff) plot_borders(ax37) plt.xticks(fontsize=ff) plt.yticks(fontsize=ff) plt.grid(color='r') ax37.set_xlim(ax1.get_xlim()) ax37.set_ylim(ax1.get_ylim()) ################################## ax29 = fig.add_subplot(234, aspect='equal') #pm2 = plt.pcolormesh(gprof_x, gprof_y,np.ma.masked_invalid(gprof_pp[latstart:latend]), # cmap=my_cmap,vmin=0.1,vmax=10, zorder=2) pm2 = plt.pcolormesh(gprof_x, gprof_y, np.ma.masked_invalid(gprof_snow[latstart:latend]), cmap=get_miub_cmap(), vmin=0, vmax=5, zorder=1) cb = plt.colorbar(shrink=0.5) cb.set_label("SnowCoverIndex ", fontsize=ff) cb.ax.tick_params(labelsize=ff) plt.xlabel("x [km] ", fontsize=ff) plt.ylabel("y [km] ", fontsize=ff) plt.title('GPM GPROF SnowCoverIndex: \n' + str(pfad_gprof_g[66:70]) + '-' + str(pfad_gprof_g[70:72]) + '-' + str(pfad_gprof_g[72:74]) + ' T: ' + str(pfad_gprof_g[76:82]) + '-' + str(pfad_gprof_g[84:90]) + ' UTC', fontsize=ff) plot_borders(ax29) plt.xticks(fontsize=ff) plt.yticks(fontsize=ff) plt.grid(color='r') #plt.tight_layout() ax29.set_xlim(ax1.get_xlim()) ax29.set_ylim(ax1.get_ylim()) from pcc import get_2_cmap ax28 = fig.add_subplot(235, aspect='equal') pm2 = plt.pcolormesh(gprof_x, gprof_y, np.ma.masked_invalid(gprof_l[latstart:latend]), cmap=get_2_cmap(), vmin=0, vmax=1, zorder=1) cb = plt.colorbar(shrink=0.5) cb.set_label("LiquidWaterFraction", fontsize=ff) cb.ax.tick_params(labelsize=ff) plt.xlabel("x [km] ", fontsize=ff) plt.ylabel("y [km] ", fontsize=ff) plt.title('GPM GPROF LiquidWaterFraction: \n' + str(pfad_gprof_g[66:70]) + '-' + str(pfad_gprof_g[70:72]) + '-' + str(pfad_gprof_g[72:74]) + ' T: ' + str(pfad_gprof_g[76:82]) + '-' + str(pfad_gprof_g[84:90]) + ' UTC', fontsize=ff) plot_borders(ax28) plt.xticks(fontsize=ff) plt.yticks(fontsize=ff) plt.grid(color='r') #plt.tight_layout() ax28.set_xlim(ax1.get_xlim()) ax28.set_ylim(ax1.get_ylim())
result = np.ma.masked_invalid(result) rrr = result.reshape(gpm_x.shape) Z = wradlib.trafo.idecibel(rwdata) rwdata = wradlib.zr.z2r(Z, a=200., b=1.6) Zr = wradlib.trafo.idecibel(rrr) rrr = wradlib.zr.z2r(Zr, a=200., b=1.6) #rrr[rrr<=TH_ka]=np.NaN #rrr[rrr==-9999.0]=np.nan from pcc import plot_radar from pcc import get_miub_cmap my_cmap2 = get_miub_cmap() ######################################################################### PLOT ###########################################################################---- m = 176 #176 mm = 0.125 #0.125 h = np.arange(m, 0, -1) * mm # Bei 88 500m und bei 176 ist es 250m cut = 22 #22 bei bon201410 NS node[:, cut] nn = (m - node[:, cut]) * mm fig = plt.figure(figsize=(12, 12)) fft = 15.0 #figtextpositionen
from scipy import stats, linspace import wradlib as wrl from osgeo import osr from pcc import get_time_of_gpm from pcc import cut_the_swath ## Landgrenzenfunktion ## ------------------- from pcc import boxpol_pos bonn_pos = boxpol_pos() bx, by = bonn_pos['gkx_ppi'], bonn_pos['gky_ppi'] bonnlat, bonnlon = bonn_pos['lat_ppi'], bonn_pos['lon_ppi'] from pcc import plot_borders from pcc import plot_radar from pcc import get_miub_cmap my_cmap = get_miub_cmap() from pcc import get_my_cmap my_cmap2 = get_my_cmap() GGG = [] RRR = [] # Ref.Threshold nach RADOLAN_Goudenhoofdt_2016 TH_ref = 12#18#7 ''' zz = np.array([20140609, 20140610, 20140629, 20140826, 20140921, 20141007, 20141016, 20150128, 20150227, 20150402, 20150427, 20160405, 20160607, 20160805, 20160904, 20160917, 20161001, 20161024, 20170113, 20170203,20170223])
hhh = np.array(pp.shape[0]*pp.shape[1]*list(hdpr)) ppp = pp.reshape(pp.shape[0]*pp.shape[1]*pp.shape[2]) maske = ~np.isnan(hhh) & ~np.isnan(ppp) #cut1, cut2 = 24, 3254 fig = plt.figure(figsize=(14,12)) #zzz = str(jahr)+'-'+str(monat)+'-'+str(tag)+'--'+str(stunde)+':'+str(minute)+' UTC' #fig.suptitle(zzz + ' UTC') ################### ax1 = fig.add_subplot(221, aspect='auto') #plt.subplot(2,2,1) plt.pcolormesh(dpr_lon, dpr_lat,np.ma.masked_invalid(dpr_pp_surf), vmin=0, vmax=50, cmap=get_miub_cmap()) cbar = plt.colorbar() cbar.set_label('Ref. in dbz') plot_borders(ax1) plot_radar(blon, blat, ax1, reproject=True, cband=False,col='black') plt.plot(dpr_lon[:,0],dpr_lat[:,0], color='black',lw=1) plt.plot(dpr_lon[:,-1],dpr_lat[:,-1], color='black',lw=1) plt.plot(dpr_lon[:,dpr_lon.shape[1]/2],dpr_lat[:,dpr_lon.shape[1]/2], color='black',lw=1, ls='--') plt.plot(dpr_lon[:,cut1],dpr_lat[:,cut1], color='red',lw=2,ls='--') plt.plot(dpr_lon[cut2,:],dpr_lat[cut2,:], color='green',lw=2,ls='--') ax1 = plt.scatter(bonnlon, bonnlat, c=50 ,s=50, color='red') plt.grid()
lon_ppi = attrs['VOL']['Longitude'] lat_ppi = attrs['VOL']['Latitude'] alt_ppi = attrs['VOL']['Height'] from mpl_toolkits.axisartist.grid_finder import FixedLocator, DictFormatter # reading in GAMIC hdf5 file mask_ind = np.where(data <= np.nanmin(zh)) zh[mask_ind] = np.nan ma = np.ma.array(zh, mask=np.isnan(zh)) fft = 15 import pcc as pcc cmap2 = pcc.get_miub_cmap() sb = [231,232,233,234,235,236] radpar = [zh, zv, zdr,phidp, rhohv, kdp] vmini = [0, 0, -1, -100, .7,-0.75] vmaxi = [50, 50, 3, 50, .99, 2] name = ['Zh (dBZ)','Zv (dBZ)','Zdr (db)','PhiDP','RhoHV (/)', r"kdp ( $^\circ$ $km^{-1}$)"] #cc = [cmap2, cmap2, cmap2, 'jet', 'jet', 'jet'] fig = plt.figure(figsize=(16,12)) for iii in range(len(radpar)): cgax, caax, paax, pm, xxx, yyy = pcc.pcc_plot_cg_rhi(radpar[iii], r=r, th=th, rf=1e3, subplot=sb[iii],
#cut1, cut2 = 24, 3254 fig = plt.figure(figsize=(14, 12)) #zzz = str(jahr)+'-'+str(monat)+'-'+str(tag)+'--'+str(stunde)+':'+str(minute)+' UTC' #fig.suptitle(zzz + ' UTC') ################### ax1 = fig.add_subplot(221, aspect='auto') #plt.subplot(2,2,1) plt.pcolormesh(dpr_lon, dpr_lat, np.ma.masked_invalid(dpr_pp_surf), vmin=0, vmax=50, cmap=get_miub_cmap()) cbar = plt.colorbar() cbar.set_label('Ref. in dbz') plot_borders(ax1) plot_radar(blon, blat, ax1, reproject=True, cband=False, col='black') plt.plot(dpr_lon[:, 0], dpr_lat[:, 0], color='black', lw=1) plt.plot(dpr_lon[:, -1], dpr_lat[:, -1], color='black', lw=1) plt.plot(dpr_lon[:, dpr_lon.shape[1] / 2], dpr_lat[:, dpr_lon.shape[1] / 2], color='black', lw=1, ls='--') plt.plot(dpr_lon[:, cut1], dpr_lat[:, cut1], color='red', lw=2, ls='--') plt.plot(dpr_lon[cut2, :], dpr_lat[cut2, :], color='green', lw=2, ls='--') ax1 = plt.scatter(bonnlon, bonnlat, c=50, s=50, color='red')
fft=15 lll = np.arange(-30,60,1) cbname = 'Rainrate (mm/h)' cbname2 = 'Reflectivity (dBZ)' from pcc import boxpol_pos bonn_pos = boxpol_pos() bx, by = bonn_pos['gkx_ppi'], bonn_pos['gky_ppi'] boxlat, boxlon = bonn_pos['lat_ppi'], bonn_pos['lon_ppi'] from pcc import plot_borders from pcc import plot_radar from pcc import get_my_cmap from pcc import get_miub_cmap my_cmap = get_my_cmap() my_cmap2 = get_miub_cmap() ax1 = fig.add_subplot(2,3,1, aspect='equal') pm1 = plt.pcolormesh(sf_ku_x, sf_ku_y,np.ma.masked_invalid(sf_ku_z), cmap=my_cmap2, vmin=0, vmax=50 ) plt.plot(ka_x[:,0],ka_y[:,0], color='gray',lw=1) plt.plot(ka_x[:,-1],ka_y[:,-1], color='gray',lw=1) plt.plot(ku_x[:,0],ku_y[:,0], color='gray',lw=1) plt.plot(ku_x[:,-1],ku_y[:,-1], color='gray',lw=1) cb = plt.colorbar(shrink=0.5,extend='max') cb.set_label(cbname,fontsize=fft) cb.ax.tick_params(labelsize=fft)
from pcc import get_miub_cmap from pcc import plot_radar gridded[np.where(x>-150)]=np.nan gridded[np.where(x<-300)]=np.nan gridded[np.where(y<-4325)]=np.nan gridded[np.where(y>-4150)]=np.nan rwdata[np.where(x>-150)]=np.nan rwdata[np.where(x<-300)]=np.nan rwdata[np.where(y<-4325)]=np.nan rwdata[np.where(y>-4150)]=np.nan plt.subplot(2,2,3) #wradlib.vis.plot_ppi(zh,r,az, vmin=0, vmax=50) plt.pcolormesh(bx, by,zh, cmap=get_miub_cmap(), vmin=0, vmax=50) plt.scatter(gkx, gky, s=25, color='black') plt.grid(color='black') plt.title('BoXPol') plt.subplot(2,2,2) plt.pcolormesh(x,y,rwdata, vmin=0, vmax=50, cmap=get_miub_cmap()) plt.scatter(gkx, gky, s=25, color='black') plt.grid(color='black') plt.title('Radolan') plt.xlim(-350, -100) plt.ylim(-4400, -4100) plt.subplot(2,2,1) plt.pcolormesh(x,y,gridded, vmin=0, vmax=50, cmap=get_miub_cmap())
def gpm_bb(dates, pn=0): zt = dates pfad = ('/automount/ags/velibor/gpmdata/dpr/2A.GPM.DPR.V6-20160118.' + zt + '*.HDF5') dpr_pfad = sorted(glob.glob(pfad))[pn] print dpr_pfad scan = 'NS' #or MS # Einlesen dpr = h5py.File(dpr_pfad, 'r') dpr_lat = np.array(dpr[scan]['Latitude']) dpr_lon = np.array(dpr[scan]['Longitude']) dpr_pp = np.array(dpr[scan]['SLV']['zFactorCorrected']) dpr_pp[dpr_pp < 0] = np.nan dpr_pp_surf = np.array(dpr[scan]['SLV']['zFactorCorrectedNearSurface']) dpr_pp_surf[dpr_pp_surf < 0] = np.nan dpr_bbh = np.array(dpr[scan]['CSF']['heightBB'], dtype=float) dpr_bbh[dpr_bbh < 0] = np.nan dpr_bbw = np.array(dpr[scan]['CSF']['widthBB'], dtype=float) dpr_bbw[dpr_bbw < 0] = np.nan dpr_time = dpr['NS']['ScanTime'] proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) from pcc import boxpol_pos bonn_pos = boxpol_pos() bx, by = bonn_pos['gkx_ppi'], bonn_pos['gky_ppi'] bonnlat, bonnlon = bonn_pos['lat_ppi'], bonn_pos['lon_ppi'] blat, blon = bonn_pos['lat_ppi'], bonn_pos['lon_ppi'] dpr_lon, dpr_lat = wradlib.georef.reproject(dpr_lon, dpr_lat, projection_target=proj_stereo, projection_source=proj_wgs) bonnlon, bonnlat = wradlib.georef.reproject(bonnlon, bonnlat, projection_target=proj_stereo, projection_source=proj_wgs) print '-------->', bonnlon, bonnlat lon0, lat0, radius = bonnlon, bonnlat, 100 r = np.sqrt((dpr_lat - lat0)**2 + (dpr_lon - lon0)**2) position = r < radius lat = dpr_lat[position] lon = dpr_lon[position] dpr_pp[np.where(r > radius)] = np.nan pp = dpr_pp dpr_pp_surf[np.where(r > radius)] = np.nan dpr_bbw[np.where(r > radius)] = np.nan dpr_bbh[np.where(r > radius)] = np.nan # Zeitstempel erstellen l2, l1 = -190, -250 k2, k1 = -4210, -4270 # BoxPol #l2, l1 = -110, -320 #k2, k1 = -4130, -4340 # pos = np.where((dpr_lat < k2) & (dpr_lat > k1) & (dpr_lon < l2) & (dpr_lon > l1)) stunde = np.array(dpr_time['Hour'])[pos[0]][0] minute = np.array(dpr_time['Minute'])[pos[0]][0] sekunde = np.array(dpr_time['Second'])[pos[0]][0] jahr = np.array(dpr_time['Year'])[pos[0]][0] monat = np.array(dpr_time['Month'])[pos[0]][0] tag = np.array(dpr_time['DayOfMonth'])[pos[0]][0] zeit = (str(jahr) + '.' + str(monat) + '.' + str(tag) + ' -- ' + str(stunde) + ':' + str(minute) + ':' + str(sekunde)) print zeit h = np.arange(150, 4800, 150) if scan == 'HS': hdpr = 1000 * (np.arange(88, 0, -1) * 0.250) else: hdpr = 1000 * (np.arange(176, 0, -1) * 0.125) hhh = np.array(pp.shape[0] * pp.shape[1] * list(hdpr)) ppp = pp.reshape(pp.shape[0] * pp.shape[1] * pp.shape[2]) maske = ~np.isnan(hhh) & ~np.isnan(ppp) fig = plt.figure(figsize=(14, 12)) zzz = str(jahr) + '-' + str(monat) + '-' + str(tag) + '--' + str( stunde) + ':' + str(minute) + ' UTC' fig.suptitle(zzz + ' UTC') ################### ax1 = fig.add_subplot(221, aspect='auto') #plt.subplot(2,2,1) plt.pcolormesh(dpr_lon, dpr_lat, np.ma.masked_invalid(dpr_pp_surf), vmin=np.nanmin(dpr_pp_surf), vmax=np.nanmax(dpr_pp_surf), cmap=get_miub_cmap()) cbar = plt.colorbar() cbar.set_label('Ref. in dbz') plot_borders(ax1) plot_radar(blon, blat, ax1, reproject=True, cband=False, col='black') plt.plot(dpr_lon[:, 0], dpr_lat[:, 0], color='black', lw=1) plt.plot(dpr_lon[:, -1], dpr_lat[:, -1], color='black', lw=1) plt.plot(dpr_lon[:, dpr_lon.shape[1] / 2], dpr_lat[:, dpr_lon.shape[1] / 2], color='black', lw=1, ls='--') ax1 = plt.scatter(bonnlon, bonnlat, c=50, s=50, color='red') plt.grid() plt.xlim(-420, 390) plt.ylim(-4700, -3700) ################## ax2 = fig.add_subplot(222, aspect='auto') plt.hist2d(ppp[maske], hhh[maske], bins=30, cmap=get_my_cmap(), vmin=0.1) print pp.shape #plt.plot(np.nanmax(pp[:,:],axis=0),hdpr, color='red', lw=2) plt.plot(np.nanmean(pp[:, :, :], axis=(0, 1)), hdpr, color='red', lw=2) plt.plot(np.nanmedian(pp[:, :, :], axis=(0, 1)), hdpr, color='green', lw=2) cbar = plt.colorbar() cbar.set_label('#') plt.title('DPR Ref. in Box') plt.xlabel('Reflectivity in dBZ') plt.grid() plt.xticks() plt.yticks() #plt.ylim(0,6000) #plt.xlim(0,50) ################## #print np.uniforn(bbh) #mini = np.nanmin(bbh[bbh>0]) ax3 = fig.add_subplot(223, aspect='auto') plt.pcolormesh(dpr_lon, dpr_lat, np.ma.masked_invalid(dpr_bbh), vmin=np.nanmin(dpr_bbh[dpr_bbh > 0]), vmax=np.nanmax(dpr_bbh), cmap='jet') cbar = plt.colorbar() cbar.set_label('BB Hight in m') plot_borders(ax3) plot_radar(blon, blat, ax3, reproject=True, cband=False, col='black') plt.plot(dpr_lon[:, 0], dpr_lat[:, 0], color='black', lw=1) plt.plot(dpr_lon[:, -1], dpr_lat[:, -1], color='black', lw=1) plt.plot(dpr_lon[:, dpr_lon.shape[1] / 2], dpr_lat[:, dpr_lon.shape[1] / 2], color='black', lw=1, ls='--') ax1 = plt.scatter(bonnlon, bonnlat, c=50, s=50, color='red') plt.grid() #plt.title('BB Hight') plt.xlim(-420, 390) plt.ylim(-4700, -3700) ################## ax4 = fig.add_subplot(224, aspect='auto') plt.pcolormesh(dpr_lon, dpr_lat, np.ma.masked_invalid(dpr_bbw), vmin=np.nanmin(dpr_bbw[dpr_bbh > 0]), vmax=np.nanmax(dpr_bbw), cmap='jet') cbar = plt.colorbar() cbar.set_label('BB Width in m') plot_borders(ax4) plot_radar(blon, blat, ax4, reproject=True, cband=False, col='black') plt.plot(dpr_lon[:, 0], dpr_lat[:, 0], color='black', lw=1) plt.plot(dpr_lon[:, -1], dpr_lat[:, -1], color='black', lw=1) plt.plot(dpr_lon[:, dpr_lon.shape[1] / 2], dpr_lat[:, dpr_lon.shape[1] / 2], color='black', lw=1, ls='--') ax1 = plt.scatter(bonnlon, bonnlat, c=50, s=50, color='red') plt.grid() #plt.title('BB Width') plt.xlim(-420, 390) plt.ylim(-4700, -3700) plt.tight_layout() plt.show()