def photomet_rolo(img_name, rolo_angle_dict):
""" Compute and return photometric properties of a projected rolo image
Args: LROC NAC frame
Returns:
clat, clon, emission, incidence
"""
#rolo_band = rolodir + '/footprints/' + no_ext + '.' + rolo_base + '.band0001.cub'
# get clat and clon for next calculation (just from the NAC map file)
# needs to be updated for new pysis
mapping = parse_file_header(img_name + '.map')['Mapping']
lat = mapping['CenterLatitude']
lon = mapping['CenterLongitude']
subearthlat = rolo_angle_dict[rolo_base]['selat']
subearthlon = rolo_angle_dict[rolo_base]['selon']
subsolarlat = rolo_angle_dict[rolo_base]['sslat']
subsolarlon = rolo_angle_dict[rolo_base]['sslon']
emission = rolotools.compute_emission(subearthlat, subearthlon, lat, lon)
incidence = rolotoos.compute_incidence(subsolarlat, subsolarlon, lat, lon)
return lat, lon, emission, incidence
def main():
# read in lat and lon from the ROLO data file
# Filename,Sample,Line,PlanetocentricLatitude,PositiveEast180Longitude
dtype = {
'names': ['filename','sample','line','lat','lon'],
'formats': ['S64', 'f8','f8', 'f8', 'f8']
}
# rolo_pix_data: numpy array of image data
rolo_pix_data = np.loadtxt('rolo_s_l_lat_lon.csv', dtype=dtype, delimiter=',')
dtype = {
'names': ['imagename', 'phase', 'selat', 'selon', 'sslat', 'sslon', 'lsratioatSE'],
'formats': ['S64', 'f8', 'f8', 'f8', 'f8', 'f8', 'f8']
}
angle = np.loadtxt('rolo_angle_info.csv', dtype=dtype, delimiter=',')
# rolo_angle_dict: dictionary of angles for images
rolo_angle_dict = dict(zip(angle['imagename'], angle))
subearthlat = rolo_angle_dict[image_name]['selat']
subearthlon = rolo_angle_dict[image_name]['selon']
subsolarlat = rolo_angle_dict[image_name]['sslat']
subsolarlon = rolo_angle_dict[image_name]['sslon']
lat, lon = rolo_pix_data['lat'], rolo_pix_data['lon']
emission = rolotools.compute_emission(subearthlat, subearthlon, lat, lon)
incidence = rolotoos.compute_incidence(subsolarlat, subsolarlon, lat, lon)
# calculate Lommel-Seeliger factor for each point
# L-S = cos(i) / ( cos(e) + cos(i) )
LommelSeeliger = np.cos(np.radians(incidence))/(np.cos(np.radians(emission))+np.cos(np.radians(incidence)))
# LS value at Sub Earth point
LSsubearth = 0.4590 # I think I need to compute this for each image.
# compute LS ratio for each point in image
LSratio = LSsubearth / LommelSeeliger
# write a function for generic ascii image writing
# eventually this should be direct to isis (no ascii)
write_image(emission, 'test_out_ema.ascii')
write_image(incidence, 'test_out_inc.ascii')
write_image(LSratio, 'test_out_LS_ratio.ascii')
