def brdfModel(s, vza, sza, raa):
'''
Run the full BRDF model for parameters in s
'''
try:
brdf = []
for i in xrange(len(s['n'])):
brdf.append(run_prosail(s['n'][i],s['cab'][i],s['car'][i],s['cbrown'][i],s['cw'][i],s['cm'][i],\
s['lai'][i],s['ala'][i],0.0,s['bsoil'][i],s['psoil'][i],s['hspot'][i],\
vza[i],sza[i],raa[i],2))
except:
brdf = []
for i in xrange(len(s['n'])):
brdf.append(run_prosail(s['n'][i],s['cab'][i],s['car'][i],s['cbrown'][i],s['cw'][i],s['cm'][i],\
s['lai'][i],s['ala'][i],0.0,s['bsoil'][i],s['psoil'][i],s['hspot'][i],\
vza,sza,raa,2))
return (vza, sza, raa), transform(s), fixnan(np.array(brdf))
def brdfModel(s,vza,sza,raa):
'''
Run the full BRDF model for parameters in s
'''
try:
brdf = []
for i in xrange(len(s['n'])):
brdf.append(run_prosail(s['n'][i],s['cab'][i],s['car'][i],s['cbrown'][i],s['cw'][i],s['cm'][i],\
s['lai'][i],s['ala'][i],0.0,s['bsoil'][i],s['psoil'][i],s['hspot'][i],\
vza[i],sza[i],raa[i],2))
except:
brdf = []
for i in xrange(len(s['n'])):
brdf.append(run_prosail(s['n'][i],s['cab'][i],s['car'][i],s['cbrown'][i],s['cw'][i],s['cm'][i],\
s['lai'][i],s['ala'][i],0.0,s['bsoil'][i],s['psoil'][i],s['hspot'][i],\
vza,sza,raa,2))
return (vza,sza,raa),transform(s),fixnan(np.array(brdf))
def brdfModel(s, vza, sza, raa, bandpass=None):
'''
Run the full BRDF model for parameters in s
Parameters:
s : dictionary of model parameters (state)
vza : view zenith angle (degrees)
float or float array of the same size as the number of
entries in each dictionary item
sza : solar zenith angle (degrees)
float or float array of the same size as the number of
entries in each dictionary item
raa : relative azimuth angle (degrees)
float or float array of the same size as the number of
entries in each dictionary item
Options:
bandpass : set of bandpass functions
'''
from prosail_fortran import run_prosail
brdf = []
wavelength = np.arange(400, 2501).astype(float)
for i in xrange(len(s['n'])):
try:
brf = run_prosail(s['n'][i],s['cab'][i],s['car'][i],s['cbrown'][i],s['cw'][i],s['cm'][i],\
s['lai'][i],s['ala'][i],0.0,s['bsoil'][i],s['psoil'][i],s['hspot'][i],\
vza[i],sza[i],raa[i],2)
except:
brf = run_prosail(s['n'][i],s['cab'][i],s['car'][i],s['cbrown'][i],s['cw'][i],s['cm'][i],\
s['lai'][i],s['ala'][i],0.0,s['bsoil'][i],s['psoil'][i],s['hspot'][i],\
vza,sza,raa,2)
if bandpass:
brf = bandpass * brf
brdf.append(brf)
if bandpass:
wavelength = bandpass * wavelength
return (vza, sza, raa), transform(s), fixnan(np.array(brdf)), wavelength
def brdfModel(s,vza,sza,raa,bandpass=None):
'''
Run the full BRDF model for parameters in s
Parameters:
s : dictionary of model parameters (state)
vza : view zenith angle (degrees)
float or float array of the same size as the number of
entries in each dictionary item
sza : solar zenith angle (degrees)
float or float array of the same size as the number of
entries in each dictionary item
raa : relative azimuth angle (degrees)
float or float array of the same size as the number of
entries in each dictionary item
Options:
bandpass : set of bandpass functions
'''
from prosail_fortran import run_prosail
brdf = []
wavelength = np.arange(400,2501).astype(float)
for i in xrange(len(s['n'])):
try:
brf = run_prosail(s['n'][i],s['cab'][i],s['car'][i],s['cbrown'][i],s['cw'][i],s['cm'][i],\
s['lai'][i],s['ala'][i],0.0,s['bsoil'][i],s['psoil'][i],s['hspot'][i],\
vza[i],sza[i],raa[i],2)
except:
brf = run_prosail(s['n'][i],s['cab'][i],s['car'][i],s['cbrown'][i],s['cw'][i],s['cm'][i],\
s['lai'][i],s['ala'][i],0.0,s['bsoil'][i],s['psoil'][i],s['hspot'][i],\
vza,sza,raa,2)
if bandpass:
brf = bandpass * brf
brdf.append(brf)
if bandpass:
wavelength = bandpass * wavelength
return (vza,sza,raa),transform(s),fixnan(np.array(brdf)),wavelength
def trans_prosail ( N, cab, car, cbrown, cw, cm, lai, lidfa, lidfb, rsoil, psoil, \
hspot, tts, tto, psi, typelidf):
"""A version of PROSAIL that uses transformed parameters to quasi-linearise
the model. See http://dx.doi.org/10.1016/j.rse.2011.12.027"""
# Define the constants
slai = -2.0
skab = -100.0
skar = -100.0
skw = -1./50.
skm = -1./100.
# Transform the parameters to real units
xlai = slai * np.log ( lai )
xkab = skab * np.log ( cab )
xkar = skar * np.log ( car )
xkw = skw * np.log ( cw )
xdm = skm * np.log ( cm )
# Run the PROSAIL model
retval = run_prosail ( N, xkab, xkar, cbrown, xkw, xdm, xlai, \
lidfa, lidfb, rsoil, psoil, hspot, tts, tto, psi, typelidf )
return retval
def trans_prosail ( N, cab, car, cbrown, cw, cm, lai, lidfa, lidfb, rsoil, psoil, \
hspot, tts, tto, psi, typelidf):
"""A version of PROSAIL that uses transformed parameters to quasi-linearise
the model. See http://dx.doi.org/10.1016/j.rse.2011.12.027"""
# Define the constants
slai = -2.0
skab = -100.0
skar = -100.0
skw = -1./50.
skm = -1./100.
# Transform the parameters to real units
xlai = slai * np.log ( lai )
xkab = skab * np.log ( cab )
xkar = skar * np.log ( car )
xkw = skw * np.log ( cw )
xdm = skm * np.log ( cm )
# Run the PROSAIL model
retval = run_prosail ( N, xkab, xkar, cbrown, xkw, xdm, xlai, \
lidfa, lidfb, rsoil, psoil, hspot, tts, tto, psi, typelidf )
return retval