#print ('Min RadolaN: ',np.nanmin(rwdata)) #rwdata = np.log10(rwdata) from satlib import read_rado #x1,y1,r1 = read_rado('201502270820') #rwdata = (rwdata+r1)/2 #from wradlib.trafo import idecibel #from wradlib.trafo import decibel #rwdata = idecibel(rwdata) ## Cut the GPM Swath ## ------------------ blon, blat, gprof_pp_b = cut_the_swath(gprof_lon,gprof_lat,gprof_pp, eu=0) blon1, blat1, gpm_h = cut_the_swath(gprof_lon,gprof_lat,gpm_h, eu=0)############################################################ proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) gpm_x, gpm_y = wradlib.georef.reproject(blon, blat, projection_target=proj_stereo , projection_source=proj_wgs) grid_xy = np.vstack((gpm_x.ravel(), gpm_y.ravel())).transpose() #rwdata = np.log10(rwdata) ## INTERLOLATION ## --------------
ax = fig.add_subplot(121, aspect='equal') for i in xx: pfad2 = ('/home/velibor/shkgpm/data/'+a[i]+'/dpr/*.HDF5') pfad_gpm = glob.glob(pfad2) pfad_gpm_g = pfad_gpm[0] gpmdpr = h5py.File(pfad_gpm_g, 'r') gprof_lat = np.array(gpmdpr['NS']['Latitude']) gprof_lon = np.array(gpmdpr['NS']['Longitude']) gprof_pp = np.array(gpmdpr['NS']['PRE']['binRealSurface'])#, dtype='float') gprof_pp = ((abs((gprof_pp-176.)))*125) from pcc import cut_the_swath blon, blat, bpp = cut_the_swath(gprof_lon, gprof_lat, gprof_pp, eu=0) proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) gpm_x, gpm_y = wradlib.georef.reproject(blon, blat, projection_target=proj_stereo , projection_source=proj_wgs) grid_xy = np.vstack((gpm_x.ravel(), gpm_y.ravel())).transpose() from pcc import plot_borders #ax = fig.add_subplot(int('33'+str(i+1)), aspect='equal') plt.pcolormesh(gpm_x,gpm_y, (bpp), cmap=plt.cm.gist_earth, norm=LogNorm(), vmin=1, vmax=3000)
### Threshold for DPR sensitivity R[R < TH] = np.nan # DPR Einlesen # ------------ gpmku = h5py.File(pfad_radar, 'r') gpmku_HS = gpmku['NS']['SLV'] dpr_lat = np.array(gpmku['NS']['Latitude']) dpr_lon = np.array(gpmku['NS']['Longitude']) dpr_pp = np.array(gpmku_HS['zFactorCorrectedNearSurface']) dpr_pp[dpr_pp < 0] = np.nan # Cut the Swath from pcc import cut_the_swath dpr_lon, dpr_lat, dpr_pp = cut_the_swath(dpr_lon, dpr_lat, dpr_pp, eu=2) # Koordinaten Projektion # ------------------ proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) dpr_lon, dpr_lat = wradlib.georef.reproject(dpr_lon, dpr_lat, projection_target=proj_stereo, projection_source=proj_wgs) blon, blat = wradlib.georef.reproject(blon0, blat0, projection_target=proj_stereo, projection_source=proj_wgs)
rn = rwdata.copy() rn[rn != -9999] = 1 rn[rn == -9999] = 0 radolan_grid_xy = wradlib.georef.get_radolan_grid(900,900) x = radolan_grid_xy[:,:,0] y = radolan_grid_xy[:,:,1] rwdata = np.ma.masked_equal(rwdata, -9999) / 2 - 32.5 #rwdata[rwdata < 0] = np.nan ## Cut the GPM Swath ## ------------------ blon, blat, gprof_pp_b = cut_the_swath(gprof_lon,gprof_lat,gprof_pp) proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) gpm_x, gpm_y = wradlib.georef.reproject(blon, blat, projection_target=proj_stereo , projection_source=proj_wgs) grid_xy = np.vstack((gpm_x.ravel(), gpm_y.ravel())).transpose() ## INTERLOLATION ## -------------- gk3 = wradlib.georef.epsg_to_osr(31467) grid_gpm_xy = np.vstack((gpm_x.ravel(), gpm_y.ravel())).transpose()
for i in xx: pfad2 = ('/home/velibor/shkgpm/data/' + a[i] + '/dpr/*.HDF5') pfad_gpm = glob.glob(pfad2) pfad_gpm_g = pfad_gpm[0] gpmdpr = h5py.File(pfad_gpm_g, 'r') gprof_lat = np.array(gpmdpr['NS']['Latitude']) gprof_lon = np.array(gpmdpr['NS']['Longitude']) gprof_pp = np.array( gpmdpr['NS']['PRE']['binRealSurface']) #, dtype='float') gprof_pp = ((abs((gprof_pp - 176.))) * 125) from pcc import cut_the_swath blon, blat, bpp = cut_the_swath(gprof_lon, gprof_lat, gprof_pp, eu=0) proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) gpm_x, gpm_y = wradlib.georef.reproject(blon, blat, projection_target=proj_stereo, projection_source=proj_wgs) grid_xy = np.vstack((gpm_x.ravel(), gpm_y.ravel())).transpose() from pcc import plot_borders #ax = fig.add_subplot(int('33'+str(i+1)), aspect='equal') plt.pcolormesh(gpm_x,
dpr_pp[dpr_pp < 0] = np.nan dpr_pp_ms[dpr_pp_ms < 0] = np.nan dpr_pp_hs[dpr_pp_hs < 0] = np.nan from satlib import get_time_of_gpm_over_boxpol gpm_time = gpmku['NS']['ScanTime'] gt = get_time_of_gpm_over_boxpol(dpr_lon, dpr_lat, gpm_time) gz = gt[0:4] + '-' + gt[4:6] + '-' + gt[6:8] + 'T' + gt[8:10] + ':' + gt[ 10:12] + ':' + gt[12:14] + 'Z UTC' # Cut the Swath from pcc import cut_the_swath dpr_lon, dpr_lat, dpr_pp = cut_the_swath(dpr_lon, dpr_lat, dpr_pp, eu=0) dpr_lonms, dpr_latms, dpr_pp_ms = cut_the_swath(dpr_lonms, dpr_latms, dpr_pp_ms, eu=0) dpr_lonhs, dpr_laths, dpr_pp_hs = cut_the_swath(dpr_lonhs, dpr_laths, dpr_pp_hs, eu=0) # Koordinaten Projektion # ------------------ proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326)
radolan_grid_xy = wradlib.georef.get_radolan_grid(900,900) x = radolan_grid_xy[:,:,0] y = radolan_grid_xy[:,:,1] rwdata = np.ma.masked_equal(rwdata, -9999) / 2 - 32.5 ### Threshold for DPR sensitivity rwdata[rwdata<TH]=-9999 ######################################################## Cut the Swath for Bonn # ----------------------------------------------------------------------------- from pcc import cut_the_swath dpr_lon, dpr_lat, dpr_pp = cut_the_swath(dpr_lon,dpr_lat,dpr_pp, eu=0) ######################################################## Koordinaten Projektion # ----------------------------------------------------------------------------- proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) dpr_lon, dpr_lat = wradlib.georef.reproject(dpr_lon, dpr_lat, projection_target=proj_stereo , projection_source=proj_wgs) blon, blat = wradlib.georef.reproject(blon0, blat0,
data = data['SCAN0']['ZH']['data'] r = metadata['SCAN0']['r'] th = metadata['SCAN0']['el'] mask_ind = np.where(data <= np.nanmin(data)) data[mask_ind] = np.nan ma = np.ma.array(data, mask=np.isnan(data)) ############################################################Parameter bestimmen ip = 0 PV_vmin = [0.1, -15] PV_vmax = [10, 40] PV_name = ['Rainrate (mm/h)', 'Z (dBZ)'] # Swath ueber Deutschland from pcc import cut_the_swath blon, blat, gprof_pp_b = cut_the_swath(gprof_lon, gprof_lat, gprof_pp) ablon, ablat, dpr3 = cut_the_swath(gprof_lon, gprof_lat, dpr) nblon, nblat, node = cut_the_swath(gprof_lon, gprof_lat, Node) node = node[:, :, 1:4:2] dpr4 = np.copy(dpr3) print('Shape: ', dpr3.shape) #dpr3 = gprof_pp_b #gprof_pp_b = gprof_pp_b[:,:,80] #gprof_pp_b[gprof_pp_b==-9999.9]=np.nan print 'gprof min max:' + str(np.nanmin(gprof_pp_b)), str( np.nanmax(gprof_pp_b)), gprof_pp_b.shape
rwdata[rwdata <= 0.5] = -9999 #print ('Min RadolaN: ',np.nanmin(rwdata)) #rwdata = np.log10(rwdata) from satlib import read_rado #x1,y1,r1 = read_rado('201502270820') #rwdata = (rwdata+r1)/2 #from wradlib.trafo import idecibel #from wradlib.trafo import decibel #rwdata = idecibel(rwdata) ## Cut the GPM Swath ## ------------------ blon, blat, gprof_pp_b = cut_the_swath(gprof_lon, gprof_lat, gprof_pp, eu=0) blon1, blat1, gpm_h = cut_the_swath( gprof_lon, gprof_lat, gpm_h, eu=0) ############################################################ proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) gpm_x, gpm_y = wradlib.georef.reproject(blon, blat, projection_target=proj_stereo, projection_source=proj_wgs) grid_xy = np.vstack((gpm_x.ravel(), gpm_y.ravel())).transpose()
print pfad2 pfad_gprof = glob.glob(pfad2) print pfad_gprof pfad_gprof_g = pfad_gprof[0] gpmdprs = h5py.File(pfad_gprof_g, 'r') gprof_lat = np.array(gpmdprs['S1']['Latitude']) gprof_lon = np.array(gpmdprs['S1']['Longitude']) gprof_pp = np.array(gpmdprs['S1']['surfacePrecipitation']) gprof_pp[gprof_pp == -9999.9] = np.nan ## Cut the GPM Swath ## ------------------ from pcc import cut_the_swath glon, glat, gpp = cut_the_swath(gprof_lon, gprof_lat, gprof_pp, eu=True) dlon, dlat, dpp = cut_the_swath(dpr_lon, dpr_lat, dpr_pp, eu=True) proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) g_x, g_y = wradlib.georef.reproject(glon, glat, projection_target=proj_stereo, projection_source=proj_wgs) g_xy = np.vstack((g_x.ravel(), g_y.ravel())).transpose() d_x, d_y = wradlib.georef.reproject(dlon, dlat, projection_target=proj_stereo,
#rwdata[rwdata <= 15] = -9999 #print ('Min RadolaN: ',np.nanmin(rwdata)) #rwdata = np.log10(rwdata) from satlib import read_rado #x1,y1,r1 = read_rado('201502270820') #rwdata = (rwdata+r1)/2 #from wradlib.trafo import idecibel #from wradlib.trafo import decibel #rwdata = idecibel(rwdata) ## Cut the GPM Swath ## ------------------ blon, blat, gprof_pp_b = cut_the_swath(gprof_lon, gprof_lat, gprof_pp, eu=0) blon, blat, gprof_bbh_b = cut_the_swath(gprof_lon, gprof_lat, dpr_bbh, eu=0) print('2. ', gprof_pp_b.shape, blat.shape, blon.shape, gprof_bbh_b.shape) proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) gpm_x, gpm_y = wradlib.georef.reproject(blon, blat,
dpr_pp_ms = np.array(gpmka_MS['zFactorCorrectedNearSurface']) dpr_pp_hs = np.array(gpmka_HS['zFactorCorrectedNearSurface']) dpr_pp[dpr_pp < 0] = np.nan dpr_pp_ms[dpr_pp_ms < 0] = np.nan dpr_pp_hs[dpr_pp_hs < 0] = np.nan from satlib import get_time_of_gpm_over_boxpol gpm_time = gpmku['NS']['ScanTime'] gt = get_time_of_gpm_over_boxpol(dpr_lon, dpr_lat, gpm_time) gz = gt[0:4]+'-'+gt[4:6]+'-'+gt[6:8]+'T'+gt[8:10]+':'+gt[10:12]+':'+gt[12:14]+'Z UTC' # Cut the Swath from pcc import cut_the_swath dpr_lon, dpr_lat, dpr_pp = cut_the_swath(dpr_lon,dpr_lat,dpr_pp, eu=0) dpr_lonms, dpr_latms, dpr_pp_ms = cut_the_swath(dpr_lonms,dpr_latms,dpr_pp_ms, eu=0) dpr_lonhs, dpr_laths, dpr_pp_hs = cut_the_swath(dpr_lonhs,dpr_laths,dpr_pp_hs, eu=0) # Koordinaten Projektion # ------------------ proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) dpr_lon, dpr_lat = wradlib.georef.reproject(dpr_lon, dpr_lat, projection_target=proj_stereo , projection_source=proj_wgs) dpr_lonms, dpr_latms = wradlib.georef.reproject(dpr_lonms, dpr_latms, projection_target=proj_stereo , projection_source=proj_wgs) dpr_lonhs, dpr_laths = wradlib.georef.reproject(dpr_lonhs, dpr_laths, projection_target=proj_stereo , projection_source=proj_wgs)
rn = rwdata.copy() rn[rn != -9999] = 1 rn[rn == -9999] = 0 radolan_grid_xy = wradlib.georef.get_radolan_grid(900,900) x = radolan_grid_xy[:,:,0] y = radolan_grid_xy[:,:,1] #################################### RADOLAN RX und RY Einlesen rwdata2 = np.ma.masked_equal(rwdata2, -9999) / 2 - 32.5 rwdata = np.ma.masked_equal(rwdata, -9999) * 8 #rwdata[rwdata < 0] = np.nan ############################################# Cut the GPM Swath blon, blat, gpmdpr_z_b = cut_the_swath(gprof_lon,gprof_lat,gpmdpr_z,eu=0) blon, blat, gpmdpr_pp_b = cut_the_swath(gprof_lon,gprof_lat,gpmdpr_pp,eu=0) blon, blat, dpr_pp_b = cut_the_swath(gprof_lon,gprof_lat,dpr_pp,eu=0) blon, blat, dpr_bbh_b = cut_the_swath(gprof_lon,gprof_lat,dpr_bbh,eu=0) blon, blat, dpr_bbw_b = cut_the_swath(gprof_lon,gprof_lat,dpr_bbw,eu=0) blon, blat, dpr_phase_b = cut_the_swath(gprof_lon,gprof_lat,dpr_phase,eu=0) blon, blat, dpr_typ_b = cut_the_swath(gprof_lon,gprof_lat,dpr_typ,eu=0) blon, blat, dpr_top_b = cut_the_swath(gprof_lon,gprof_lat,dpr_top,eu=0) proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) gpm_x, gpm_y = wradlib.georef.reproject(blon, blat, projection_target=proj_stereo , projection_source=proj_wgs) grid_xy = np.vstack((gpm_x.ravel(), gpm_y.ravel())).transpose()
radolan_zeit = rwattrs['datetime'].strftime("%Y.%m.%d -- %H:%M:%S") radolan_grid_xy = wradlib.georef.get_radolan_grid(900,900) x = radolan_grid_xy[:,:,0] y = radolan_grid_xy[:,:,1] rwdata = np.ma.masked_equal(rwdata, -9999) / 2 - 32.5 ### Threshold for DPR sensitivity rwdata[rwdata<TH]=np.nan Z_radolan = rwdata ######################################################## Cut the Swath for Bonn # ----------------------------------------------------------------------------- dpr_lon, dpr_lat, Z_dpr = cut_the_swath(dpr_lon_1,dpr_lat_1,Z_dpr, eu=0) dpr_lon, dpr_lat, dpr_raintype = cut_the_swath(dpr_lon_1,dpr_lat_1,dpr_raintype, eu=0) dpr_lon, dpr_lat, dpr_phase = cut_the_swath(dpr_lon_1,dpr_lat_1,dpr_phase, eu=0) ######################################################## Koordinaten Projektion # ----------------------------------------------------------------------------- proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) dpr_lon, dpr_lat = wradlib.georef.reproject(dpr_lon, dpr_lat, projection_target=proj_stereo , projection_source=proj_wgs) blon, blat = wradlib.georef.reproject(blon0, blat0,
#dpr = dpr[:,:,:,1] #dpr[dpr<-9998]=np.nan #####################################Parameter bestimmen ip = 0 PV_vmin = [0.1,-15] PV_vmax = [10,40] PV_name = ['Rainrate (mm/h)','Z (dBZ)'] # Swath ueber Deutschland from pcc import cut_the_swath blon, blat, gprof_pp_b = cut_the_swath(gprof_lon,gprof_lat,gprof_pp, eu=0) ablon, ablat, dpr3 = cut_the_swath(gprof_lon,gprof_lat,dpr, eu=0) dpr4 = np.copy(dpr3) dpr4[dpr4<100]=dpr4[dpr4<100]-100 dpr4[dpr4>=200]=dpr4[dpr4>=200]-200 dpr4[dpr4==125]=0 dpr4[dpr4==175]=0 dpr4[dpr4==100]=0 dpr4[dpr4==150]=0 print('Shape: ', dpr3.shape) #dpr3 = gprof_pp_b #gprof_pp_b = gprof_pp_b[:,:,80] #gprof_pp_b[gprof_pp_b==-9999.9]=np.nan
rn = rwdata.copy() rn[rn != -9999] = 1 rn[rn == -9999] = 0 radolan_grid_xy = wradlib.georef.get_radolan_grid(900, 900) x = radolan_grid_xy[:, :, 0] y = radolan_grid_xy[:, :, 1] #################################### RADOLAN RX und RY Einlesen rwdata2 = np.ma.masked_equal(rwdata2, -9999) / 2 - 32.5 rwdata = np.ma.masked_equal(rwdata, -9999) * 8 #rwdata[rwdata < 0] = np.nan ############################################# Cut the GPM Swath blon, blat, gpmdpr_z_b = cut_the_swath(gprof_lon, gprof_lat, gpmdpr_z, eu=0) blon, blat, gpmdpr_pp_b = cut_the_swath(gprof_lon, gprof_lat, gpmdpr_pp, eu=0) blon, blat, dpr_pp_b = cut_the_swath(gprof_lon, gprof_lat, dpr_pp, eu=0) blon, blat, dpr_bbh_b = cut_the_swath(gprof_lon, gprof_lat, dpr_bbh, eu=0) blon, blat, dpr_bbw_b = cut_the_swath(gprof_lon, gprof_lat,
######################################## Bei Dropsize #parameter2 = gpmdprs['NS']['SLV']['paramDSD'] #dpr = np.array(parameter2, dtype=float) #dpr = dpr[:,:,:,1] #dpr[dpr<-9998]=np.nan #####################################Parameter bestimmen ip = 0 PV_vmin = [0.1, -15] PV_vmax = [10, 40] PV_name = ['Rainrate (mm/h)', 'Z (dBZ)'] # Swath ueber Deutschland from pcc import cut_the_swath blon, blat, gprof_pp_b = cut_the_swath(gprof_lon, gprof_lat, gprof_pp, eu=0) ablon, ablat, dpr3 = cut_the_swath(gprof_lon, gprof_lat, dpr, eu=0) dpr4 = np.copy(dpr3) dpr4[dpr4 < 100] = dpr4[dpr4 < 100] - 100 dpr4[dpr4 >= 200] = dpr4[dpr4 >= 200] - 200 dpr4[dpr4 == 125] = 0 dpr4[dpr4 == 175] = 0 dpr4[dpr4 == 100] = 0 dpr4[dpr4 == 150] = 0 print('Shape: ', dpr3.shape) #dpr3 = gprof_pp_b #gprof_pp_b = gprof_pp_b[:,:,80] #gprof_pp_b[gprof_pp_b==-9999.9]=np.nan
radolan_grid_xy = wradlib.georef.get_radolan_grid(900,900) x = radolan_grid_xy[:,:,0] y = radolan_grid_xy[:,:,1] if r_pro=='rz': rwdata = np.ma.masked_equal(rwdata, -9999) *8 # Einheit 1/100mm pro 5min if r_pro=='rx': rwdata = np.ma.masked_equal(rwdata, -9999) / 2 - 32.5 #rwdata[rwdata < 0] = np.nan ## Cut the GPM Swath ## ------------------ from pcc import cut_the_swath blon, blat, gprof_pp_b = cut_the_swath(gprof_lon,gprof_lat,gprof_pp, eu=True) proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) gpm_x, gpm_y = wradlib.georef.reproject(blon, blat, projection_target=proj_stereo , projection_source=proj_wgs) grid_xy = np.vstack((gpm_x.ravel(), gpm_y.ravel())).transpose() ## INTERLOLATION ## -------------- gk3 = wradlib.georef.epsg_to_osr(31467) grid_gpm_xy = np.vstack((gpm_x.ravel(), gpm_y.ravel())).transpose()
x = radolan_grid_xy[:, :, 0] y = radolan_grid_xy[:, :, 1] if r_pro == 'rz': rwdata = np.ma.masked_equal(rwdata, -9999) * 8 # Einheit 1/100mm pro 5min if r_pro == 'rx': rwdata = np.ma.masked_equal(rwdata, -9999) / 2 - 32.5 #rwdata[rwdata < 0] = np.nan ## Cut the GPM Swath ## ------------------ from pcc import cut_the_swath blon, blat, gprof_pp_b = cut_the_swath(gprof_lon, gprof_lat, gprof_pp, eu=True) proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) gpm_x, gpm_y = wradlib.georef.reproject(blon, blat, projection_target=proj_stereo, projection_source=proj_wgs) grid_xy = np.vstack((gpm_x.ravel(), gpm_y.ravel())).transpose() ## INTERLOLATION ## --------------
# ----------------------------------------------------------------------------- fig = plt.figure(figsize=(12, 12)) #GPM Parameter gpm_para = [ 'zFactorCorrectedNearSurface', 'zFactorCorrectedESurface', 'precipRateNearSurface', 'piaFinal' ] gl = len(gpm_para) for iii in range(gl): gprof_pp = np.array(gpmdpr['NS']['SLV'][gpm_para[iii]]) gprof_pp[gprof_pp == -9999.9] = np.nan ## Cut the GPM Swath ## ------------------ blon, blat, gprof_pp_b = cut_the_swath(gprof_lon, gprof_lat, gprof_pp) proj_stereo = wrl.georef.create_osr("dwd-radolan") proj_wgs = osr.SpatialReference() proj_wgs.ImportFromEPSG(4326) gpm_x, gpm_y = wradlib.georef.reproject(blon, blat, projection_target=proj_stereo, projection_source=proj_wgs) grid_xy = np.vstack((gpm_x.ravel(), gpm_y.ravel())).transpose() ax2 = fig.add_subplot( int('1' + str(gl) + str(iii + 1)), aspect='equal') #------------------------------------ pm2 = plt.pcolormesh(gpm_x, gpm_y,
#dpr = dpr[:,:,:,1] #dpr[dpr<-9998]=np.nan #####################################Parameter bestimmen ip = 0 PV_vmin = [0.1,-15] PV_vmax = [10,40] PV_name = ['Rainrate (mm/h)','Z (dBZ)'] # Swath ueber Deutschland from pcc import cut_the_swath blon, blat, gprof_pp_b = cut_the_swath(gprof_lon,gprof_lat,gprof_pp) ablon, ablat, dpr3 = cut_the_swath(gprof_lon,gprof_lat,dpr) nblon, nblat, node = cut_the_swath(gprof_lon,gprof_lat, Node) node = node[:,:,3] dpr4 = np.copy(dpr3) print('Shape: ', dpr3.shape) #dpr3 = gprof_pp_b #gprof_pp_b = gprof_pp_b[:,:,80] #gprof_pp_b[gprof_pp_b==-9999.9]=np.nan print 'gprof min max:' + str(np.nanmin(gprof_pp_b)), str(np.nanmax(gprof_pp_b)), gprof_pp_b.shape