def get_effective_wavelength(self, bandname):
"""Get the effective wavelength with Rayleigh scattering in mind"""
try:
rsr = RelativeSpectralResponse(self.platform_name, self.sensor)
except(IOError, OSError):
LOG.exception(
"No spectral responses for this platform and sensor: %s %s", self.platform_name, self.sensor)
if isinstance(bandname, (float, integer_types)):
LOG.warning(
"Effective wavelength is set to the requested band wavelength = %f", bandname)
return bandname
msg = ("Can't get effective wavelength for band %s on platform %s and sensor %s" %
(str(bandname), self.platform_name, self.sensor))
raise KeyError(msg)
if isinstance(bandname, str):
bandname = BANDNAMES.get(self.sensor, BANDNAMES['generic']).get(bandname, bandname)
elif isinstance(bandname, (float, integer_types)):
if not(0.4 < bandname < 0.8):
raise BandFrequencyOutOfRange(
'Requested band frequency should be between 0.4 and 0.8 microns!')
bandname = get_bandname_from_wavelength(self.sensor, bandname, rsr.rsr)
wvl, resp = rsr.rsr[bandname][
'det-1']['wavelength'], rsr.rsr[bandname]['det-1']['response']
cwvl = get_central_wave(wvl, resp, weight=1. / wvl**4)
LOG.debug("Band name: %s Effective wavelength: %f", bandname, cwvl)
return cwvl
def convert2hdf5(platform_name):
"""Retrieve original RSR data and convert to internal hdf5 format"""
import h5py
ahi = AhiRSR(platform_name)
filename = os.path.join(ahi.output_dir,
"rsr_ahi_{platform}.h5".format(platform=platform_name))
with h5py.File(filename, "w") as h5f:
h5f.attrs['description'] = 'Relative Spectral Responses for AHI'
h5f.attrs['platform_name'] = platform_name
h5f.attrs['sensor'] = 'ahi'
h5f.attrs['band_names'] = AHI_BAND_NAMES.values()
for chname in AHI_BAND_NAMES.values():
grp = h5f.create_group(chname)
wvl = ahi.rsr[chname][
'wavelength'][~np.isnan(ahi.rsr[chname]['wavelength'])]
rsp = ahi.rsr[chname][
'response'][~np.isnan(ahi.rsr[chname]['wavelength'])]
grp.attrs['central_wavelength'] = get_central_wave(wvl, rsp)
arr = ahi.rsr[chname]['wavelength']
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
arr = ahi.rsr[chname]['response']
dset = grp.create_dataset('response', arr.shape, dtype='f')
dset[...] = arr
def convert2hdf5(platform_id, sat_number):
"""Retrieve original RSR data and convert to internal hdf5 format"""
import h5py
satellite_id = platform_id + str(sat_number)
ahi = AhiRSR('ch1', satellite_id)
filename = os.path.join(ahi.output_dir,
"rsr_ahi_%s%d.h5" % (platform_id, sat_number))
with h5py.File(filename, "w") as h5f:
h5f.attrs['description'] = 'Relative Spectral Responses for AHI'
h5f.attrs['platform'] = platform_id
h5f.attrs['sat_number'] = sat_number
h5f.attrs['band_names'] = AHI_BAND_NAMES
for chname in AHI_BAND_NAMES:
ahi = AhiRSR(chname, satellite_id)
grp = h5f.create_group(chname)
wvl = ahi.rsr[
'det-1']['wavelength'][~np.isnan(ahi.rsr['det-1']['wavelength'])]
rsp = ahi.rsr[
'det-1']['response'][~np.isnan(ahi.rsr['det-1']['wavelength'])]
grp.attrs['central_wavelength'] = get_central_wave(wvl, rsp)
arr = ahi.rsr['det-1']['wavelength']
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
arr = ahi.rsr['det-1']['response']
dset = grp.create_dataset('response', arr.shape, dtype='f')
dset[...] = arr
def get_effective_wavelength(self, bandname):
"""Get the effective wavelength with Rayleigh scattering in mind"""
try:
rsr = RelativeSpectralResponse(self.platform_name, self.sensor)
except(IOError, OSError):
LOG.exception(
"No spectral responses for this platform and sensor: %s %s", self.platform_name, self.sensor)
if isinstance(bandname, (float, integer_types)):
LOG.warning(
"Effective wavelength is set to the requested band wavelength = %f", bandname)
return bandname
return None
if isinstance(bandname, str):
bandname = BANDNAMES.get(self.sensor, BANDNAMES['generic']).get(bandname, bandname)
elif isinstance(bandname, (float, integer_types)):
if not(0.4 < bandname < 0.8):
raise BandFrequencyOutOfRange(
'Requested band frequency should be between 0.4 and 0.8 microns!')
bandname = get_bandname_from_wavelength(self.sensor, bandname, rsr.rsr)
wvl, resp = rsr.rsr[bandname][
'det-1']['wavelength'], rsr.rsr[bandname]['det-1']['response']
cwvl = get_central_wave(wvl, resp, weight=1. / wvl**4)
LOG.debug("Band name: %s Effective wavelength: %f", bandname, cwvl)
return cwvl
def convert2hdf5(platform_name):
"""Retrieve original RSR data and convert to internal hdf5 format"""
import h5py
avhrr = AvhrrRSR('ch1', platform_name)
filename = os.path.join(avhrr.output_dir,
"rsr_avhrr_%s.h5" % platform_name)
with h5py.File(filename, "w") as h5f:
h5f.attrs['description'] = 'Relative Spectral Responses for AVHRR'
h5f.attrs['platform_name'] = platform_name
h5f.attrs['band_names'] = AVHRR_BAND_NAMES
for chname in AVHRR_BAND_NAMES:
avhrr = AvhrrRSR(chname, satellite_id)
grp = h5f.create_group(chname)
wvl = avhrr.rsr['wavelength'][~np.isnan(avhrr.rsr['wavelength'])]
rsp = avhrr.rsr['response'][~np.isnan(avhrr.rsr['wavelength'])]
grp.attrs['central_wavelength'] = get_central_wave(wvl, rsp)
arr = avhrr.rsr['wavelength']
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
arr = avhrr.rsr['response']
dset = grp.create_dataset('response', arr.shape, dtype='f')
dset[...] = arr
def convert2hdf5(platform_id, sat_number):
"""Retrieve original RSR data and convert to internal hdf5 format"""
import h5py
satellite_id = platform_id + str(sat_number)
avhrr = AvhrrRSR('ch1', satellite_id)
filename = os.path.join(avhrr.output_dir,
"rsr_avhrr_%s%d.h5" % (platform_id, sat_number))
with h5py.File(filename, "w") as h5f:
h5f.attrs['description'] = 'Relative Spectral Responses for AVHRR'
h5f.attrs['platform'] = platform_id
h5f.attrs['sat_number'] = sat_number
h5f.attrs['band_names'] = AVHRR_BAND_NAMES
for chname in AVHRR_BAND_NAMES:
avhrr = AvhrrRSR(chname, 'noaa18')
grp = h5f.create_group(chname)
wvl = avhrr.rsr['wavelength'][~np.isnan(avhrr.rsr['wavelength'])]
rsp = avhrr.rsr['response'][~np.isnan(avhrr.rsr['wavelength'])]
grp.attrs['central_wavelength'] = get_central_wave(wvl, rsp)
arr = avhrr.rsr['wavelength']
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
arr = avhrr.rsr['response']
dset = grp.create_dataset('response', arr.shape, dtype='f')
dset[...] = arr
def convert2hdf5(platform_name):
"""Retrieve original RSR data and convert to internal hdf5 format"""
import h5py
ahi = AhiRSR(platform_name)
filename = os.path.join(
ahi.output_dir, "rsr_ahi_{platform}.h5".format(platform=platform_name))
with h5py.File(filename, "w") as h5f:
h5f.attrs['description'] = 'Relative Spectral Responses for AHI'
h5f.attrs['platform_name'] = platform_name
h5f.attrs['sensor'] = 'ahi'
h5f.attrs['band_names'] = AHI_BAND_NAMES.values()
for chname in AHI_BAND_NAMES.values():
grp = h5f.create_group(chname)
wvl = ahi.rsr[chname]['wavelength'][
~np.isnan(ahi.rsr[chname]['wavelength'])]
rsp = ahi.rsr[chname]['response'][
~np.isnan(ahi.rsr[chname]['wavelength'])]
grp.attrs['central_wavelength'] = get_central_wave(wvl, rsp)
arr = ahi.rsr[chname]['wavelength']
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
arr = ahi.rsr[chname]['response']
dset = grp.create_dataset('response', arr.shape, dtype='f')
dset[...] = arr
def convert2hdf5(platform_name):
"""Retrieve original RSR data and convert to internal hdf5 format"""
import h5py
modis = ModisRSR('20', platform_name)
mfile = os.path.join(
modis.output_dir,
"rsr_modis_{platform}.h5".format(platform=platform_name))
with h5py.File(mfile, "w") as h5f:
h5f.attrs['description'] = 'Relative Spectral Responses for MODIS'
h5f.attrs['platform_name'] = platform_name
h5f.attrs['band_names'] = MODIS_BAND_NAMES
for chname in MODIS_BAND_NAMES:
modis = ModisRSR(chname, platform_name)
grp = h5f.create_group(chname)
grp.attrs['number_of_detectors'] = len(modis.rsr.keys())
# Loop over each detector to check if the sampling wavelengths are
# identical:
det_names = [detector_name for detector_name in modis.rsr.keys()]
wvl = modis.rsr[det_names[0]]['wavelength']
wvl_is_constant = True
for det in det_names[1:]:
if wvl.shape != modis.rsr[det]['wavelength'].shape:
wvl_is_constant = False
break
elif not np.allclose(wvl, modis.rsr[det]['wavelength']):
wvl_is_constant = False
break
if wvl_is_constant:
arr = modis.rsr[det_names[0]]['wavelength']
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
# Loop over each detector:
for det in modis.rsr:
det_grp = grp.create_group(det)
wvl = modis.rsr[det]['wavelength'][
~np.isnan(modis.rsr[det]['wavelength'])]
rsp = modis.rsr[det]['response'][
~np.isnan(modis.rsr[det]['wavelength'])]
det_grp.attrs['central_wavelength'] = get_central_wave(
wvl, rsp)
if not wvl_is_constant:
arr = modis.rsr[det]['wavelength']
dset = det_grp.create_dataset('wavelength',
arr.shape,
dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
arr = modis.rsr[det]['response']
dset = det_grp.create_dataset('response', arr.shape, dtype='f')
dset[...] = arr
def convert2hdf5(platform_name):
"""Retrieve original RSR data and convert to internal hdf5 format"""
import h5py
modis = ModisRSR('20', platform_name)
mfile = os.path.join(modis.output_dir,
"rsr_modis_{platform}.h5".format(platform=platform_name))
with h5py.File(mfile, "w") as h5f:
h5f.attrs['description'] = 'Relative Spectral Responses for MODIS'
h5f.attrs['platform_name'] = platform_name
h5f.attrs['band_names'] = MODIS_BAND_NAMES
for chname in MODIS_BAND_NAMES:
modis = ModisRSR(chname, platform_name)
grp = h5f.create_group(chname)
grp.attrs['number_of_detectors'] = len(modis.rsr.keys())
# Loop over each detector to check if the sampling wavelengths are
# identical:
det_names = modis.rsr.keys()
wvl = modis.rsr[det_names[0]]['wavelength']
wvl_is_constant = True
for det in det_names[1:]:
if not np.alltrue(wvl == modis.rsr[det]['wavelength']):
wvl_is_constant = False
break
if wvl_is_constant:
arr = modis.rsr[det_names[0]]['wavelength']
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
# Loop over each detector:
for det in modis.rsr:
det_grp = grp.create_group(det)
wvl = modis.rsr[det]['wavelength'][
~np.isnan(modis.rsr[det]['wavelength'])]
rsp = modis.rsr[det]['response'][
~np.isnan(modis.rsr[det]['wavelength'])]
det_grp.attrs[
'central_wavelength'] = get_central_wave(wvl, rsp)
if not wvl_is_constant:
arr = modis.rsr[det]['wavelength']
dset = det_grp.create_dataset(
'wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
arr = modis.rsr[det]['response']
dset = det_grp.create_dataset('response', arr.shape, dtype='f')
dset[...] = arr
def convert(self):
"""Convert spectral response functions from wavelength to wavenumber."""
if self._wavespace == WAVE_LENGTH:
rsr, info = convert2wavenumber(self.rsr)
for band in rsr.keys():
for det in rsr[band].keys():
self.rsr[band][det][WAVE_NUMBER] = rsr[
band][det][WAVE_NUMBER]
self.rsr[band][det]['response'] = rsr[
band][det]['response']
self.unit = info['unit']
self.si_scale = info['si_scale']
self._wavespace = WAVE_NUMBER
for band in rsr.keys():
for det in rsr[band].keys():
self.rsr[band][det]['central_wavenumber'] = \
get_central_wave(self.rsr[band][det][WAVE_NUMBER], self.rsr[band][det]['response'])
del self.rsr[band][det][WAVE_LENGTH]
else:
errmsg = "Conversion from {wn} to {wl} not supported yet".format(wn=WAVE_NUMBER, wl=WAVE_LENGTH)
raise NotImplementedError(errmsg)
def convert(self):
"""Convert spectral response functions from wavelength to wavenumber"""
from pyspectral.utils import (convert2wavenumber, get_central_wave)
if self._wavespace == WAVE_LENGTH:
rsr, info = convert2wavenumber(self.rsr)
for band in rsr.keys():
for det in rsr[band].keys():
self.rsr[band][det][WAVE_NUMBER] = rsr[
band][det][WAVE_NUMBER]
self.rsr[band][det]['response'] = rsr[
band][det]['response']
self.unit = info['unit']
self.si_scale = info['si_scale']
self._wavespace = WAVE_NUMBER
for band in rsr.keys():
for det in rsr[band].keys():
self.rsr[band][det]['central_wavenumber'] = \
get_central_wave(self.rsr[band][det][WAVE_NUMBER], self.rsr[band][det]['response'])
del self.rsr[band][det][WAVE_LENGTH]
else:
errmsg = "Conversion from {wn} to {wl} not supported yet".format(wn=WAVE_NUMBER, wl=WAVE_LENGTH)
raise NotImplementedError(errmsg)
3.7065142, 3.716509, 3.7264658, 3.7364102, 3.7463682,
3.7563652, 3.7664226, 3.7763396, 3.7863384, 3.7964207,
3.8063589, 3.8163606, 3.8264089, 3.8364836, 3.8463381,
3.8563975, 3.8664163, 3.8763755, 3.8864797, 3.8964978,
3.9064275, 3.9164873, 3.9264729, 3.9364026, 3.9465107,
3.9535347], dtype='double')
TEST_RSR['20']['det-1']['response'] = np.array([
0.01, 0.0118, 0.01987, 0.03226, 0.05028, 0.0849,
0.16645, 0.33792, 0.59106, 0.81815, 0.96077, 0.92855,
0.86008, 0.8661, 0.87697, 0.85412, 0.88922, 0.9541,
0.95687, 0.91037, 0.91058, 0.94256, 0.94719, 0.94808,
1., 0.92676, 0.67429, 0.44715, 0.27762, 0.14852,
0.07141, 0.04151, 0.02925, 0.02085, 0.01414, 0.01], dtype='double')
TEST_RSR['20']['det-1']['central_wavelength'] = get_central_wave(TEST_RSR['20']['det-1']['wavelength'],
TEST_RSR['20']['det-1']['response'])
SEV_RSR = {'IR3.9': {}}
SEV_RSR['IR3.9']['det-1'] = {}
WAVN = np.array([2083.33325195, 2091.00048828, 2098.72387695, 2106.50488281,
2114.34375, 2122.24121094, 2130.19775391, 2138.21435547,
2146.29101562, 2154.42944336, 2162.62963867, 2170.89257812,
2179.21899414, 2187.609375, 2196.06494141, 2204.58569336,
2213.17285156, 2221.82714844, 2230.54956055, 2239.34082031,
2248.20141602, 2257.13256836, 2266.13500977, 2275.20947266,
2284.35668945, 2293.57788086, 2302.87402344, 2312.24584961,
2321.6940918, 2331.21972656, 2340.82421875, 2350.5078125,
2360.27197266, 2370.11743164, 2380.0456543, 2390.05737305,
2400.15356445, 2410.33544922, 2420.60449219, 2430.9609375,
2441.40625, 2451.94189453, 2462.5690918, 2473.28857422,
def main():
"""Main"""
import sys
import h5py
handler = logging.StreamHandler(sys.stderr)
formatter = logging.Formatter(fmt=_DEFAULT_LOG_FORMAT,
datefmt=_DEFAULT_TIME_FORMAT)
handler.setFormatter(formatter)
handler.setLevel(logging.DEBUG)
LOG.setLevel(logging.DEBUG)
LOG.addHandler(handler)
platform_name = "NOAA-20"
#platform_name = "Suomi-NPP"
viirs = ViirsRSR('M1', platform_name)
filename = os.path.join(viirs.output_dir,
"rsr_viirs_{0}.h5".format(platform_name))
with h5py.File(filename, "w") as h5f:
h5f.attrs['description'] = 'Relative Spectral Responses for VIIRS'
h5f.attrs['platform_name'] = platform_name
h5f.attrs['sensor'] = 'viirs'
h5f.attrs['band_names'] = VIIRS_BAND_NAMES
for chname in VIIRS_BAND_NAMES:
viirs = ViirsRSR(chname, platform_name)
grp = h5f.create_group(chname)
grp.attrs['number_of_detectors'] = len(viirs.rsr.keys())
# Loop over each detector to check if the sampling wavelengths are
# identical:
det_names = viirs.rsr.keys()
wvl = viirs.rsr[det_names[0]]['wavelength']
wvl, idx = np.unique(wvl, return_index=True)
wvl_is_constant = True
for det in det_names[1:]:
det_wvl = np.unique(viirs.rsr[det]['wavelength'])
if not np.alltrue(wvl == det_wvl):
LOG.warning(
"Wavelngth arrays are not the same among detectors!")
wvl_is_constant = False
if wvl_is_constant:
arr = wvl
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
# Loop over each detector:
for det in viirs.rsr:
det_grp = grp.create_group(det)
wvl = viirs.rsr[det]['wavelength'][
~np.isnan(viirs.rsr[det]['wavelength'])]
rsp = viirs.rsr[det]['response'][
~np.isnan(viirs.rsr[det]['wavelength'])]
wvl, idx = np.unique(wvl, return_index=True)
rsp = np.take(rsp, idx)
LOG.debug("wvl.shape: %s", str(wvl.shape))
det_grp.attrs['central_wavelength'] = get_central_wave(
wvl, rsp)
if not wvl_is_constant:
arr = wvl
dset = det_grp.create_dataset('wavelength',
arr.shape,
dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
dset = det_grp.create_dataset('response', rsp.shape, dtype='f')
dset[...] = rsp
def main():
"""Main"""
import sys
import h5py
handler = logging.StreamHandler(sys.stderr)
formatter = logging.Formatter(fmt=_DEFAULT_LOG_FORMAT,
datefmt=_DEFAULT_TIME_FORMAT)
handler.setFormatter(formatter)
handler.setLevel(logging.DEBUG)
LOG.setLevel(logging.DEBUG)
LOG.addHandler(handler)
platform_name = "Suomi-NPP"
viirs = ViirsRSR('M1', 'Suomi-NPP')
filename = os.path.join(viirs.output_dir,
"rsr_viirs_%s.h5" % platform_name)
with h5py.File(filename, "w") as h5f:
h5f.attrs['description'] = 'Relative Spectral Responses for VIIRS'
h5f.attrs['platform_name'] = platform_name
h5f.attrs['band_names'] = VIIRS_BAND_NAMES
for chname in VIIRS_BAND_NAMES:
viirs = ViirsRSR(chname)
grp = h5f.create_group(chname)
grp.attrs['number_of_detectors'] = len(viirs.rsr.keys())
# Loop over each detector to check if the sampling wavelengths are
# identical:
det_names = viirs.rsr.keys()
wvl = viirs.rsr[det_names[0]]['wavelength']
wvl, idx = np.unique(wvl, return_index=True)
wvl_is_constant = True
for det in det_names[1:]:
det_wvl = np.unique(viirs.rsr[det]['wavelength'])
if not np.alltrue(wvl == det_wvl):
LOG.warning(
"Wavelngth arrays are not the same among detectors!")
wvl_is_constant = False
if wvl_is_constant:
arr = wvl
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
# Loop over each detector:
for det in viirs.rsr:
det_grp = grp.create_group(det)
wvl = viirs.rsr[det]['wavelength'][
~np.isnan(viirs.rsr[det]['wavelength'])]
rsp = viirs.rsr[det]['response'][
~np.isnan(viirs.rsr[det]['wavelength'])]
wvl, idx = np.unique(wvl, return_index=True)
rsp = np.take(rsp, idx)
LOG.debug("wvl.shape: %s", str(wvl.shape))
det_grp.attrs[
'central_wavelength'] = get_central_wave(wvl, rsp)
if not wvl_is_constant:
arr = wvl
dset = det_grp.create_dataset(
'wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
dset = det_grp.create_dataset('response', rsp.shape, dtype='f')
dset[...] = rsp
def generate_metimage_file(platform_name):
"""Retrieve original RSR data and convert to internal hdf5 format.
"""
import h5py
bandnames = METIMAGE_BAND_NAMES
instr = MetImageRSR(bandnames[0], platform_name)
instr_name = instr.instrument.replace('/', '')
filename = os.path.join(instr.output_dir,
"rsr_{0}_{1}.h5".format(instr_name,
platform_name))
with h5py.File(filename, "w") as h5f:
h5f.attrs['description'] = ('Relative Spectral Responses for ' +
instr.instrument.upper())
h5f.attrs['platform_name'] = platform_name
h5f.attrs['band_names'] = bandnames
for chname in bandnames:
metimage = MetImageRSR(chname, platform_name)
grp = h5f.create_group(chname)
grp.attrs['number_of_detectors'] = len(metimage.rsr.keys())
# Loop over each detector to check if the sampling wavelengths are
# identical:
det_names = list(metimage.rsr.keys())
wvl = metimage.rsr[det_names[0]]['wavelength']
wvl, idx = np.unique(wvl, return_index=True)
wvl_is_constant = True
for det in det_names[1:]:
det_wvl = np.unique(metimage.rsr[det]['wavelength'])
if not np.alltrue(wvl == det_wvl):
LOG.warning(
"Wavelngth arrays are not the same among detectors!")
wvl_is_constant = False
if wvl_is_constant:
arr = wvl
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
# Loop over each detector:
for det in metimage.rsr:
det_grp = grp.create_group(det)
wvl = metimage.rsr[det]['wavelength'][
~np.isnan(metimage.rsr[det]['wavelength'])]
rsp = metimage.rsr[det]['response'][
~np.isnan(metimage.rsr[det]['wavelength'])]
wvl, idx = np.unique(wvl, return_index=True)
rsp = np.take(rsp, idx)
LOG.debug("wvl.shape: %s", str(wvl.shape))
det_grp.attrs[
'central_wavelength'] = get_central_wave(wvl, rsp)
if not wvl_is_constant:
arr = wvl
dset = det_grp.create_dataset(
'wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
dset = det_grp.create_dataset('response', rsp.shape, dtype='f')
dset[...] = rsp
def generate_metimage_file(platform_name):
"""Retrieve original RSR data and convert to internal hdf5 format.
"""
import h5py
bandnames = METIMAGE_BAND_NAMES
instr = MetImageRSR(bandnames[0], platform_name)
instr_name = instr.instrument.replace('/', '')
filename = os.path.join(instr.output_dir,
"rsr_{0}_{1}.h5".format(instr_name, platform_name))
with h5py.File(filename, "w") as h5f:
h5f.attrs['description'] = ('Relative Spectral Responses for ' +
instr.instrument.upper())
h5f.attrs['platform_name'] = platform_name
h5f.attrs['band_names'] = bandnames
for chname in bandnames:
metimage = MetImageRSR(chname, platform_name)
grp = h5f.create_group(chname)
grp.attrs['number_of_detectors'] = len(metimage.rsr.keys())
# Loop over each detector to check if the sampling wavelengths are
# identical:
det_names = list(metimage.rsr.keys())
wvl = metimage.rsr[det_names[0]]['wavelength']
wvl, idx = np.unique(wvl, return_index=True)
wvl_is_constant = True
for det in det_names[1:]:
det_wvl = np.unique(metimage.rsr[det]['wavelength'])
if not np.alltrue(wvl == det_wvl):
LOG.warning(
"Wavelngth arrays are not the same among detectors!")
wvl_is_constant = False
if wvl_is_constant:
arr = wvl
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
# Loop over each detector:
for det in metimage.rsr:
det_grp = grp.create_group(det)
wvl = metimage.rsr[det]['wavelength'][
~np.isnan(metimage.rsr[det]['wavelength'])]
rsp = metimage.rsr[det]['response'][
~np.isnan(metimage.rsr[det]['wavelength'])]
wvl, idx = np.unique(wvl, return_index=True)
rsp = np.take(rsp, idx)
LOG.debug("wvl.shape: %s", str(wvl.shape))
det_grp.attrs['central_wavelength'] = get_central_wave(
wvl, rsp)
if not wvl_is_constant:
arr = wvl
dset = det_grp.create_dataset('wavelength',
arr.shape,
dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
dset = det_grp.create_dataset('response', rsp.shape, dtype='f')
dset[...] = rsp
3.8063589, 3.8163606, 3.8264089, 3.8364836, 3.8463381, 3.8563975,
3.8664163, 3.8763755, 3.8864797, 3.8964978, 3.9064275, 3.9164873,
3.9264729, 3.9364026, 3.9465107, 3.9535347
],
dtype='double')
TEST_RSR['20']['det-1']['response'] = np.array([
0.01, 0.0118, 0.01987, 0.03226, 0.05028, 0.0849, 0.16645, 0.33792, 0.59106,
0.81815, 0.96077, 0.92855, 0.86008, 0.8661, 0.87697, 0.85412, 0.88922,
0.9541, 0.95687, 0.91037, 0.91058, 0.94256, 0.94719, 0.94808, 1., 0.92676,
0.67429, 0.44715, 0.27762, 0.14852, 0.07141, 0.04151, 0.02925, 0.02085,
0.01414, 0.01
],
dtype='double')
TEST_RSR['20']['det-1']['central_wavelength'] = get_central_wave(
TEST_RSR['20']['det-1']['wavelength'], TEST_RSR['20']['det-1']['response'])
SEV_RSR = {'IR3.9': {}}
SEV_RSR['IR3.9']['det-1'] = {}
WAVN = np.array([
2083.33325195, 2091.00048828, 2098.72387695, 2106.50488281, 2114.34375,
2122.24121094, 2130.19775391, 2138.21435547, 2146.29101562, 2154.42944336,
2162.62963867, 2170.89257812, 2179.21899414, 2187.609375, 2196.06494141,
2204.58569336, 2213.17285156, 2221.82714844, 2230.54956055, 2239.34082031,
2248.20141602, 2257.13256836, 2266.13500977, 2275.20947266, 2284.35668945,
2293.57788086, 2302.87402344, 2312.24584961, 2321.6940918, 2331.21972656,
2340.82421875, 2350.5078125, 2360.27197266, 2370.11743164, 2380.0456543,
2390.05737305, 2400.15356445, 2410.33544922, 2420.60449219, 2430.9609375,
2441.40625, 2451.94189453, 2462.5690918, 2473.28857422, 2484.10180664,
2495.01025391, 2506.01416016, 2517.11645508, 2528.31713867, 2539.61816406,
2551.02050781, 2562.52587891, 2574.13525391, 2585.8503418, 2597.67236328,
if not np.alltrue(wvl == viirs.rsr[det_names[0]]['wavelength']):
wvl_is_constant = False
if wvl_is_constant:
arr = viirs.rsr[det_names[0]]['wavelength']
dset = grp.create_dataset('wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
# Loop over each detector:
for det in viirs.rsr:
det_grp = grp.create_group(det)
wvl = viirs.rsr[det]['wavelength'][
~np.isnan(viirs.rsr[det]['wavelength'])]
rsp = viirs.rsr[det]['response'][
~np.isnan(viirs.rsr[det]['wavelength'])]
det_grp.attrs[
'central_wavelength'] = get_central_wave(wvl, rsp)
if not wvl_is_constant:
arr = viirs.rsr[det]['wavelength']
dset = det_grp.create_dataset(
'wavelength', arr.shape, dtype='f')
dset.attrs['unit'] = 'm'
dset.attrs['scale'] = 1e-06
dset[...] = arr
arr = viirs.rsr[det]['response']
dset = det_grp.create_dataset('response', arr.shape, dtype='f')
dset[...] = arr
