#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
