def interp_atm_lut(atm_lut_RHO, atm_lut_WVC, atm_lut_VZA, atm_lut_RAA, atm_lut,
rho, wvc, vza, raa):
""" Interpolate the atmospheric lookup table for visibility estimation.
Parameters
----------
atm_lut_RHO, atm_lut_WVC, atm_lut_VZA, atm_lut_RAA: list of floats
Atmospheric lookup table grids.
atm_lut: ndarray
Atmospheric lookup table, shape=(RHO, WVC, VIS, VZA, RAA).
Returns
-------
interp_rdn: 1D array
Interpolated radiance.
"""
from AtmLUT import get_interp_range, combos
# Get water vapor column interpolation range
rho_dict = get_interp_range(atm_lut_RHO, rho)
wvc_dict = get_interp_range(atm_lut_WVC, wvc)
vza_dict = get_interp_range(atm_lut_VZA, vza)
raa_dict = get_interp_range(atm_lut_RAA, raa)
# Update interpolated radiance
interp_rdn = np.zeros(atm_lut.shape[2])
index_combos = combos([
list(rho_dict.keys()),
list(wvc_dict.keys()),
list(vza_dict.keys()),
list(raa_dict.keys())
])
for index_combo in index_combos:
rho_index, wvc_index, vza_index, raa_index = index_combo
interp_rdn += atm_lut[
rho_index, wvc_index, :, vza_index,
raa_index] * rho_dict[rho_index] * wvc_dict[wvc_index] * vza_dict[
vza_index] * raa_dict[raa_index]
return interp_rdn
def interp_atm_lut(atm_lut_file, WVC, VIS, VZA, RAA):
""" Interpolate atmosphere look-up-table to different water vapor columns (WVC),
visibilities (VIS), view zenith angles (VZA) and relative azimuth angles (RAA).
Parameters
----------
atm_lut_file: str
Atmosphere look-up-table filename.
WVC, VIS, VZA, RAA: list of floats
Water vapor column, visibility, view zenith angles and relative azimuth angles.
Returns
-------
WAVE: array
Wavelengths of the atmosphere look-up-table radiance.
lut_rdn: 2D array
Interpolated path radiance (albedo=0.0, 0.5, 1.0).
"""
from AtmLUT import read_binary_metadata, get_interp_range, combos
# Read atmospheric lookup table grids
atm_lut_metadata = read_binary_metadata(atm_lut_file + '.meta')
atm_lut_metadata['shape'] = tuple(
[int(v) for v in atm_lut_metadata['shape']])
atm_lut_WVC = np.array([float(v) for v in atm_lut_metadata['WVC']])
atm_lut_VIS = np.array([float(v) for v in atm_lut_metadata['VIS']])
atm_lut_VZA = np.array([float(v) for v in atm_lut_metadata['VZA']])
atm_lut_RAA = np.array([float(v) for v in atm_lut_metadata['RAA']])
atm_lut_WAVE = np.array([float(v) for v in atm_lut_metadata['WAVE']])
# Read atmospheric lookup table data
atm_lut = np.memmap(atm_lut_file,
dtype=atm_lut_metadata['dtype'],
mode='r',
shape=atm_lut_metadata['shape']
) # shape=(RHO, WVC, VIS, VZA, RAA, WAVE)
# Initialize interpolated radiance
interp_rdn = np.zeros((len(WVC), len(atm_lut_WAVE)), dtype='float32')
# Do interpolation
for i in range(len(WVC)):
wvc, vis, vza, raa = WVC[i], VIS[i], VZA[i], RAA[i]
# Get interpolation ranges
wvc_dict = get_interp_range(atm_lut_WVC, wvc)
vis_dict = get_interp_range(atm_lut_VIS, vis)
vza_dict = get_interp_range(atm_lut_VZA, vza)
raa_dict = get_interp_range(atm_lut_RAA, raa)
# Get combos
index_combos = combos([
list(wvc_dict.keys()),
list(vis_dict.keys()),
list(vza_dict.keys()),
list(raa_dict.keys())
])
# Update interpolated radiance
for index_combo in index_combos:
wvc_index, vis_index, vza_index, raa_index = index_combo
interp_rdn[i, :] += atm_lut[
1, wvc_index, vis_index, vza_index,
raa_index, :] * wvc_dict[wvc_index] * vis_dict[
vis_index] * vza_dict[vza_index] * raa_dict[raa_index]
del index_combo, index_combos
# Clear atmosphere look-up table
atm_lut.flush()
del atm_lut
return atm_lut_WAVE, interp_rdn