def read_cci_ctth(cci_nc):
"""Read cloud top: temperature, height and pressure from filename
"""
ctth = CtthObj()
cth = cci_nc.variables['cth'][::]
if hasattr(cth, 'mask'):
cth_data = np.where(cth.mask, ATRAIN_MATCH_NODATA, cth.data)
else:
cth_data = cth.data # already scaled!
logger.info("Setting ctth for non cloudy pixels do nodata ...")
cth_data[cci_nc.variables['cc_total'][::] < 0.5] = ATRAIN_MATCH_NODATA
cth_corr = cci_nc.variables['cth_corrected'][::]
if hasattr(cth_corr, 'mask'):
cth_data_corr = np.where(cth_corr.mask, ATRAIN_MATCH_NODATA, cth_corr.data)
else:
cth_data_corr = cth_corr.data # already scaled!
logger.debug("Setting ctth for non cloudy pixels do nodata ...")
cth_data_corr[cci_nc.variables['cc_total'][::] < 0.5] = ATRAIN_MATCH_NODATA
ctth.h_gain = 1.0
ctth.h_intercept = 0.0
ctth.h_nodata = ATRAIN_MATCH_NODATA
ctth.height = 1000*cth_data
ctth.height_corr = 1000*cth_data_corr
ctt = cci_nc.variables['ctt'][::]
if hasattr(ctt, 'mask'):
ctt_data = np.where(ctt.mask, ATRAIN_MATCH_NODATA, ctt.data)
else:
ctt_data = ctt.data
logger.debug("Setting ctth for non cloudy pixels do nodata ...")
ctt_data[cci_nc.variables['cc_total'][::] < 0.5] = ATRAIN_MATCH_NODATA
ctth.t_gain = 1.0
ctth.t_intercept = 0.0
ctth.t_nodata = ATRAIN_MATCH_NODATA
ctth.temperature = ctt_data
ctp = cci_nc.variables['ctp'][::]
if hasattr(ctp, 'mask'):
ctp_data = np.where(ctp.mask, ATRAIN_MATCH_NODATA, ctp.data) # Upscaled
else:
ctp_data = ctp.data
ctth.p_gain = 1.0
ctth.p_intercept = 0.0
ctth.p_nodata = ATRAIN_MATCH_NODATA
logger.debug("Setting ctth for non cloudy pixels do nodata ...")
ctp_data[cci_nc.variables['cc_total'][::] < 0.5] = ATRAIN_MATCH_NODATA
ctth.pressure = ctp_data
return ctth
def read_patmosx_ctype_cmask_ctth(patmosx_nc):
"""Read cloudtype and flag info from filename."""
ctth = CtthObj()
ctype = CtypeObj()
cma = CmaObj()
ctth.height = patmosx_nc.variables['cld_height_acha'][0, :, :].astype(np.float)
ctth.h_nodata = patmosx_nc.variables['cld_height_acha']._FillValue
if np.ma.is_masked(ctth.height):
ctth.height.data[ctth.height.mask] = ATRAIN_MATCH_NODATA
ctth.height = ctth.height.data
ctth.height = 1000*ctth.height
cf = patmosx_nc.variables['cloud_fraction'][0, :, :].astype(np.float)
cma.cma_ext = np.where(cf >= 0.5, 1, 0)
if np.ma.is_masked(cf):
cma.cma_ext[cf.mask] = 255
ctype.phaseflag = None
ctype.ct_conditions = None
return ctype, cma, ctth
def read_patmosx_ctype_cmask_ctth_hdf(patmosx_hdf):
"""Read cloudtype and flag info from filename."""
ctth = CtthObj()
ctype = CtypeObj()
cma = CmaObj()
name = 'cld_height_acha'
height_unscaled = np.array(patmosx_hdf.select(name).get())
offset = patmosx_hdf.select(name).attributes()['add_offset']
gain = patmosx_hdf.select(name).attributes()['scale_factor']
ctth.height = height_unscaled * gain + offset
ctth.h_nodata = patmosx_hdf.select(name)._FillValue
# ctth.height = 1000*ctth.height
ctth.height[height_unscaled == ctth.h_nodata] = ATRAIN_MATCH_NODATA
name = 'cloud_fraction'
cf_unscaled = np.array(patmosx_hdf.select(name).get())
offset = patmosx_hdf.select(name).attributes()['add_offset']
gain = patmosx_hdf.select(name).attributes()['scale_factor']
cf = cf_unscaled * gain + offset
cf[cf_unscaled == patmosx_hdf.select(name)._FillValue] = ATRAIN_MATCH_NODATA
cma.cma_ext = np.where(cf >= 0.5, 1, 0)
ctype.phaseflag = None
ctype.ct_conditions = None
return ctype, cma, ctth