class Radiance(dict, _V):
"""
The Radiance class
Radiance object is Read-Only and contains minimum information
"""
def __init__(self):
dict.__init__(self)
for key in radiance_list:
self[key] = None
self[key + '_ATTRIBUTE'] = {'COMMENT': 'none', 'UNITS': 'n/a'}
self.misc = None
def loadh5(self, h5):
self.loadh5liste(h5, radiance_list)
def read(self, filename):
f = h5py.File(filename, 'r')
# get the Dataset
h5 = f['/RADIANCE/']
self.loadh5(h5)
# Load
self.loadh5(h5)
h5 = f['/MISC/']
self.misc = Misc()
self.misc.loadh5(h5)
f.close()
class Kmatrix(object):
"""
The Kmatrix class
This class contains all K Matrix related information
Its members are
- profile: the profile considered for the K calculation
- option: calculation options
- kmatrix: a profile class containing the K results
- chanprof: input channels/profiles
- emissivity: K result for emissivity
- reflectance: K result for reflectance
- misc: important coef file names, list of wavenumbers...
"""
def __init__(self):
self.profile = Profile()
self.option = Option()
self.kmatrix = Profile()
self.chanprof = Chanprof()
self.emissivity = Emissivity()
self.reflectance = Reflectance()
self.misc = Misc()
self.scaled = False
self.scalecoef = 1.0
self.scaledfirst = True
def display(self):
self.profile.display()
self.option.display()
self.kmatrix.display()
self.chanprof.display()
self.emissivity.display()
self.reflectance.display()
self.misc.display()
def loadh5(self, h5):
h5p = h5['PROFILES/0001']
self.profile.loadh5(h5p)
h5o = h5['OPTIONS']
self.option.loadh5(h5o)
if 'KMATRIX' in h5.keys():
h5k = h5['KMATRIX']
self.kmatrix.loadh5(h5k)
h5c = h5['CHANPROF']
self.chanprof.loadh5(h5c)
if 'EMISSIVITY_K' in h5.keys():
h5e = h5['EMISSIVITY_K']
self.emissivity.loadh5(h5e)
if 'REFLECTANCE_K' in h5.keys():
h5r = h5['REFLECTANCE_K']
self.reflectance.loadh5(h5r)
h5m = h5['MISC']
self.misc.loadh5(h5m)
def saveh5(self, h5, path):
self.profile.saveh5(h5, path + '/PROFILES/0001')
self.option.saveh5(h5, path + '/OPTIONS/')
self.kmatrix.saveh5(h5, path + '/KMATRIX/')
self.chanprof.saveh5(h5, path + '/CHANPROF/')
self.emissivity.saveh5(h5, path + '/EMISSIVITY_K/')
self.reflectance.saveh5(h5, path + '/REFLECTANCE_K/')
self.misc.saveh5(h5, path + '/MISC/')
def getchanprof(self, ip):
"Extracts a jacobian for a given channel"
"A jacobian for a channel is a profile structure"
"Channel should start from 0"
# take care dimension order is opposite as Fortran"
chanprof = Profile()
# a cause des predicteurs on peut avoir nchannel different
nchan = self.kmatrix['T'].shape[1]
if (ip < 0 or ip >= nchan):
print("ERROR Invalid channel index", ip, " allowed is [0,",
nchan - 1, "]")
chanprof.__init__
return chanprof
for key in (self.kmatrix.profile_list + self.kmatrix.aerosol_list +
self.kmatrix.cloud_list):
if (self.kmatrix[key] is not None):
if (key == "DATE" or key == "TIME" or key == "ID"):
chanprof[key] = self.kmatrix[key]
else:
if np.isscalar(self.kmatrix[key]):
chanprof[key] = self.kmatrix[key]
elif (self.kmatrix[key].ndim == 0):
chanprof[key] = self.kmatrix[key]
elif (self.kmatrix[key].ndim == 1):
chanprof[key] = self.kmatrix[key][ip]
elif (self.kmatrix[key].ndim == 2):
chanprof[key] = self.kmatrix[key][:, ip]
elif (self.kmatrix[key].ndim == 3):
chanprof[key] = self.kmatrix[key][:, :, ip]
else:
print "ERROR kmatrix getchanprof"
chanprof[key + '_ATTRIBUTE'] = self.kmatrix[key + '_ATTRIBUTE']
if ('LBOUND' in chanprof[key + '_ATTRIBUTE'].keys()):
del chanprof[key + '_ATTRIBUTE']['LBOUND']
del chanprof[key + '_ATTRIBUTE']['UBOUND']
for key in self.kmatrix.s2m_list:
if (self.kmatrix['S2M'][key] is not None):
if (self.kmatrix['S2M'][key].ndim == 0):
chanprof['S2M'][key] = self.kmatrix['S2M'][key]
elif (self.kmatrix['S2M'][key].ndim == 1):
chanprof['S2M'][key] = self.kmatrix['S2M'][key][ip]
else:
print "ERROR kmatrix getchanprof"
chanprof['S2M'][key + '_ATTRIBUTE'] = self.kmatrix['S2M'][
key + '_ATTRIBUTE']
if ('LBOUND' in chanprof['S2M'][key + '_ATTRIBUTE'].keys()):
del chanprof['S2M'][key + '_ATTRIBUTE']['LBOUND']
del chanprof['S2M'][key + '_ATTRIBUTE']['UBOUND']
for key in self.kmatrix.sskin_list:
if (self.kmatrix['SKIN'][key] is not None):
if (key == "FASTEM"):
chanprof['SKIN'][key] = self.kmatrix['SKIN'][key]
else:
if (self.kmatrix['SKIN'][key].ndim == 0):
chanprof['SKIN'][key] = self.kmatrix['SKIN'][key]
elif (self.kmatrix['SKIN'][key].ndim == 1):
chanprof['SKIN'][key] = self.kmatrix['SKIN'][key][ip]
else:
print "ERROR kmatrix getchanprof"
chanprof['SKIN'][key + '_ATTRIBUTE'] = self.kmatrix['SKIN'][
key + '_ATTRIBUTE']
if ('LBOUND' in chanprof['SKIN'][key + '_ATTRIBUTE'].keys()):
del chanprof['SKIN'][key + '_ATTRIBUTE']['LBOUND']
del chanprof['SKIN'][key + '_ATTRIBUTE']['UBOUND']
return chanprof
def kreset(self):
self.kscale(1.0)
def kscale(self, coef):
"""Scale KMatrix by input profile * coef
Temperature arrays are not modified
This method could be called several times, scaling coefficient is
always considered relative to the original matrix
Could be called with coef = 1.0 even for the first call
in that case the kMatrix is reset to the original values and units"""
if (self.scaled):
old = self.scalecoef
val = coef / old
else:
val = coef
if (coef == 1.0):
print "KMatrix reset"
reset = True
else:
print "KMatrix scaling by coef ", coef
reset = False
coefstr = '{}'.format(coef)
try:
nchan = len(self.chanprof['CHANNELS'])
except:
nchan = 1
for key in (self.kmatrix.profile_list + self.kmatrix.aerosol_list +
self.kmatrix.cloud_list):
if (self.kmatrix[key] is not None):
if (key == "DATE" or key == "TIME" or key == "ID"
or key == "T"):
pass
else:
if (self.kmatrix[key].ndim == 0):
pass
if (self.kmatrix[key].ndim == 1):
self.kmatrix[key][:] = self.kmatrix[
key][:] * self.profile[key][None] * val
elif (self.kmatrix[key].ndim == 2):
self.kmatrix[key][:, :] = self.kmatrix[
key][:, :] * self.profile[key][:, None] * val
elif (self.kmatrix[key].ndim == 3):
print self.kmatrix[key].shape
self.profile[key] = self.kmatrix[key][:, :, ip]
self.kmatrix[key][:, :, :] = self.kmatrix[
key][:, :, :] * self.profile[key][:, :, None] * val
if (self.scaledfirst):
self.kmatrix[key + '_ATTRIBUTE_SAVED'] = {
'UNITS': 'n/a'
}
self.kmatrix[
key + '_ATTRIBUTE_SAVED']['UNITS'] = self.kmatrix[
key + '_ATTRIBUTE']['UNITS']
if (reset):
self.kmatrix[key +
'_ATTRIBUTE']['UNITS'] = self.kmatrix[
key + '_ATTRIBUTE_SAVED']['UNITS']
else:
self.kmatrix[key + '_ATTRIBUTE']['UNITS'] = (
self.kmatrix[key + '_ATTRIBUTE_SAVED']['UNITS'] +
" scaled by " + coefstr + " input profile")
for key in self.kmatrix.s2m_list:
if (self.kmatrix['S2M'][key] is not None):
if (self.kmatrix['S2M'][key].ndim == 0):
pass
elif (key == "T"):
pass
elif (self.kmatrix['S2M'][key].ndim == 1):
for i in range(nchan):
self.kmatrix['S2M'][key][i] = self.kmatrix['S2M'][key][
i] * self.profile['S2M'][key] * val
if (self.scaledfirst):
self.kmatrix['S2M'][key + '_ATTRIBUTE_SAVED'] = {
'UNITS': 'n/a'
}
self.kmatrix['S2M'][
key +
'_ATTRIBUTE_SAVED']['UNITS'] = self.kmatrix['S2M'][
key + '_ATTRIBUTE']['UNITS']
if (reset):
self.kmatrix['S2M'][
key + '_ATTRIBUTE']['UNITS'] = self.kmatrix['S2M'][
key + '_ATTRIBUTE_SAVED']['UNITS']
else:
self.kmatrix['S2M'][key + '_ATTRIBUTE']['UNITS'] = (
self.kmatrix['S2M'][key +
'_ATTRIBUTE_SAVED']['UNITS'] +
" scaled by " + coefstr + " input profile")
for key in self.kmatrix.sskin_list:
if (self.kmatrix['SKIN'][key] is not None):
if (key == "FASTEM" or key == "T"):
pass
else:
if (self.kmatrix['SKIN'][key].ndim == 0):
pass
elif (self.kmatrix['SKIN'][key].ndim == 1):
for i in range(nchan):
self.kmatrix['SKIN'][key][
i] = self.kmatrix['SKIN'][key][
i] * self.profile['SKIN'][key] * val
if (self.scaledfirst):
self.kmatrix['SKIN'][key + '_ATTRIBUTE_SAVED'] = {
'UNITS': 'n/a'
}
self.kmatrix['SKIN'][key + '_ATTRIBUTE_SAVED'][
'UNITS'] = self.kmatrix['SKIN'][
key + '_ATTRIBUTE']['UNITS']
if (reset):
self.kmatrix['SKIN'][
key +
'_ATTRIBUTE']['UNITS'] = self.kmatrix['SKIN'][
key + '_ATTRIBUTE_SAVED']['UNITS']
else:
self.kmatrix['SKIN'][
key +
'_ATTRIBUTE']['UNITS'] = (self.kmatrix['SKIN'][
key + '_ATTRIBUTE_SAVED']['UNITS'] +
" scaled by " +
coefstr +
" input profile")
if (reset):
self.scaled = False
else:
self.scaled = True
self.scalecoef = coef
self.scaledfirst = False
def read(self, filename):
f = h5py.File(filename, 'r')
# get the Dataset
h5 = f['/']
# Load kmatrix
self.loadh5(h5)
print 'loaded'
# Close HDF file
f.close()
