def sensor_wave(satsen, wave_range=(0.39, 2.4), wave_step=0.001):
from numpy import linspace
from acolite import config, rsr_convolute_dict, rsr_read
pp_path = config['pp_data_dir']
rsr_file = pp_path + '/RSR/' + satsen + '.txt'
rsr, rsr_bands = rsr_read(file=rsr_file)
wave_hyper = linspace(wave_range[0], wave_range[1],
((wave_range[1] - wave_range[0]) / wave_step) + 2)
rsr_wave = rsr_convolute_dict(wave_hyper, wave_hyper, rsr)
waves = {
rband: '{:.0f}'.format(round(rsr_wave[rband] * 1000.))
for rband in rsr_wave
}
return (waves)
def fixed_model(metadata,
tau550,
rsr_file=None,
lutdir=None,
lut='PONDER-LUT-201607-MOD2-1013mb',
pressure=None):
import acolite as pp
import os
## get scene geometry and default bands from metadata
try:
if 'SE_DISTANCE' in metadata.keys():
se_distance = metadata['SE_DISTANCE']
else:
se_distance = pp.distance_se(metadata['DOY'])
ths = metadata['THS']
thv = metadata['THV']
azi = metadata['AZI']
if 'SATELLITE_SENSOR' in metadata.keys():
sensor = metadata['SATELLITE_SENSOR']
else:
sensor = metadata['SENSOR']
#rednir_bands = metadata['BANDS_REDNIR']
#vis_bands = metadata['BANDS_VIS']
#nir_bands = metadata['BANDS_NIR']
#bestfit_bands_defaults = metadata['BANDS_BESTFIT']
bands_sorted = metadata['BANDS_ALL']
except:
print(
'Could not get appropriate metadata for model selection for satellite {}'
.format(metadata['SATELLITE']))
print(metadata.keys())
return (1)
# ## get scene geometry
# if metadata['SATELLITE']=='Pléiades':
# se_distance = pp.distance_se(metadata['DOY'])
# ths = 90. - metadata['GEOMETRY'][1]['SUN_ELEVATION']
# thv = metadata['GEOMETRY'][1]['VIEWING_ANGLE']
# azi = abs(metadata['GEOMETRY'][1]['SUN_AZIMUTH'] - metadata['GEOMETRY'][1]['AZIMUTH_ANGLE'])
# if azi > 180: azi -= 180
# sensor = metadata['INSTRUMENT']+metadata['MISSION_INDEX']
# rednir_bands = ['Red','NIR']
# vis_bands = ['Blue','Green','Red']
# if metadata['SATELLITE']=='WorldView2':
# se_distance = pp.distance_se(metadata['DOY'])
# ths = metadata['THS']
# thv = metadata['THV']
# azi = metadata['AZI']
# sensor = 'WorldView2'
# rednir_bands = ['RED','NIR1','NIR2']
# vis_bands = ['COASTAL','BLUE','GREEN','YELLOW','RED']
## set LUT dir and rsr_file
#pypath='/storage/Python/' ## to improve!
#pp_path = os.path.dirname(pp.__file__)
#if lutdir is None:
# lutdir=pp_path+'/data/LUT/'
#if rsr_file is None:
# rsr_file = pp_path+'/data/RSR/'+sensor+'.txt'
## set LUT dir and rsr_file
from acolite import config
pp_path = config['pp_data_dir']
if lutdir is None:
lutdir = pp_path + '/LUT/'
if rsr_file is None:
rsr_file = pp_path + '/RSR/' + sensor + '.txt'
rsr, rsr_bands = pp.rsr_read(file=rsr_file)
## get sensor LUT
#lut_sensor, meta_sensor = pp.aerlut.get_sensor_lut(sensor, rsr_file, lutdir=lutdir, lutid=lut, override=0)
#(ratm, rorayl, dtotr, utotr, dtott, utott, astot) = pp.aerlut.lut_get_ac_parameters_fixed_tau_sensor(lut_sensor,meta_sensor,azi,thv,ths,tau550)
## get sensor LUT
lut_sensor, meta_sensor = pp.aerlut.get_sensor_lut(sensor,
rsr_file,
lutdir=lutdir,
lutid=lut,
override=0)
## read luts at other pressures if needed
if pressure is not None:
lut_data_dict = {}
lut_data_dict[lut] = {'lut': lut_sensor, 'meta': meta_sensor}
lut_split = lut.split('-')
lut0 = '-'.join(lut_split[0:-1] + ['0500mb'])
lut_sensor, meta_sensor = pp.aerlut.get_sensor_lut(sensor,
rsr_file,
lutdir=lutdir,
lutid=lut0,
override=0)
lut_data_dict[lut0] = {'lut': lut_sensor, 'meta': meta_sensor}
lut1 = '-'.join(lut_split[0:-1] + ['1100mb'])
lut_sensor, meta_sensor = pp.aerlut.get_sensor_lut(sensor,
rsr_file,
lutdir=lutdir,
lutid=lut1,
override=0)
lut_data_dict[lut1] = {'lut': lut_sensor, 'meta': meta_sensor}
lut_sensor, meta_sensor = pp.aerlut.aerlut_pressure(
lut,
lutdir,
pressure,
sensor,
rsr_file,
lut_data_dict=lut_data_dict)
(ratm, rorayl, dtotr, utotr, dtott, utott,
astot) = pp.aerlut.lut_get_ac_parameters_fixed_tau_sensor(
lut_sensor, meta_sensor, azi, thv, ths, tau550)
return (ratm, rorayl, dtotr, utotr, dtott, utott, astot,
tau550), lut_sensor, meta_sensor
def get_sensor_lut(sensor,
rsr_file,
override=0,
lutdir=None,
lutid='PONDER-LUT-201605-MOD2-1013mb'):
import os, sys
if True:
import acolite as pp
from acolite import rsr_convolute, rsr_read, aerlut
## get sensor RSR
pp_path = pp.config['pp_data_dir']
if lutdir is None:
lutdir = pp_path + '/LUT/'
if rsr_file is None:
rsr_file = pp_path + '/RSR/' + sensor + '.txt'
rsr, rsr_bands = rsr_read(file=rsr_file)
## sensor LUT NetCDF is stored here
lutnc = lutdir + '/' + lutid + '/' + lutid + '_' + sensor + '.nc'
if (os.path.isfile(lutnc)) & (override == 1): os.remove(lutnc)
## generate sensor LUT NetCDF if needed
if (os.path.isfile(lutnc) == 0):
from numpy import linspace, interp, nan, zeros
## read LUT
lut, meta = aerlut.import_lut(lutid, lutdir, override=0)
lut_dims = lut.shape
## set up wavelength space
wave_range = [0.2, 2.4]
wave_step = 0.001
wave_hyper = linspace(wave_range[0], wave_range[1],
((wave_range[1] - wave_range[0]) / wave_step) +
2)
## interpolate RSR to same dimensions
rsr_hyper = dict()
for band in rsr:
band_wave_hyper = wave_hyper
band_response_hyper = interp(wave_hyper,
rsr[band]['wave'],
rsr[band]['response'],
left=0,
right=0)
band_response_sum = sum(band_response_hyper)
rsr_hyper[band] = {
'wave': band_wave_hyper,
'response': band_response_hyper,
'sum': band_response_sum
}
## interpolate lut to hyperspectral, and convolute to sensor bands
### set up empty sensor LUT
lut_sensor = dict()
for band in rsr:
lut_sensor[band] = zeros([
len(meta['par']),
len(meta['azi']),
len(meta['thv']),
len(meta['ths']), 1,
len(meta['tau'])
])
### only one wind setting, hard coded here
i4 = 0
v4 = meta['wnd']
### run through all simulations
data_wave = meta['wave']
for i0, v0 in enumerate(meta['par']):
for i1, v1 in enumerate(meta['azi']):
for i2, v2 in enumerate(meta['thv']):
for i3, v3 in enumerate(meta['ths']):
#for i4, v4 in enumerate(meta['wnd']):
for i5, v5 in enumerate(meta['tau']):
data_hyper = interp(wave_hyper,
data_wave,
lut[i0, :, i1, i2, i3, i4, i5],
left=0,
right=0)
for band in rsr:
lut_sensor[band][i0, i1, i2, i3, i4, i5] = (
sum(data_hyper *
rsr_hyper[band]['response']) /
rsr_hyper[band]['sum'])
## write nc file
try:
if os.path.isfile(lutnc) == 0:
from netCDF4 import Dataset
nc = Dataset(lutnc, 'w', format='NETCDF4_CLASSIC')
## write metadata
for i in meta:
attdata = meta[i]
if isinstance(attdata, list):
if isinstance(attdata[0], str):
attdata = ','.join(attdata)
setattr(nc, i, attdata)
## set up LUT dimension
nc.createDimension('par', lut_dims[0])
#nc.createDimension('wave', lut_dims[1]) # not used here
nc.createDimension('azi', lut_dims[2])
nc.createDimension('thv', lut_dims[3])
nc.createDimension('ths', lut_dims[4])
nc.createDimension('wnd', lut_dims[5])
nc.createDimension('tau', lut_dims[6])
## write LUT
for band in lut_sensor.keys():
var = nc.createVariable(
band, float,
('par', 'azi', 'thv', 'ths', 'wnd', 'tau'))
nc.variables[band][:] = lut_sensor[band]
nc.close()
arr = None
meta = None
except:
if os.path.isfile(lutnc): os.remove(lutnc)
print(sys.exc_info()[0])
print('Failed to write LUT data to NetCDF (id=' + lutid + ')')
## read dataset from NetCDF
if (os.path.isfile(lutnc) == 1):
try:
if os.path.isfile(lutnc):
from netCDF4 import Dataset
nc = Dataset(lutnc)
## read in metadata
meta = dict()
for attr in nc.ncattrs():
attdata = getattr(nc, attr)
if isinstance(attdata, str): attdata = attdata.split(',')
meta[attr] = attdata
## read in LUT
lut_sensor = dict()
datasets = list(nc.variables.keys())
for dataset in datasets:
lut_sensor[dataset] = nc.variables[dataset][:]
nc.close()
except:
print(sys.exc_info()[0])
print('Failed to open LUT data from NetCDF (id=' + lutid + ')')
return lut_sensor, meta