def test_phases(self):
result = AReader.get_phase_all("msia", 0)
assert (len(result) == 2)
assert (result[0].shape[0] == 75 and result[1].shape == (80, 75))
for re in result[1]:
# print(re.sum())
assert (round(re.sum()) == 1)
def test_aeroextinct_profile(self):
aprofile = SReader.aerosol_profile(taua=0.1)
taua_scaled = integrate.cumtrapz(aprofile.values[:, 1],
aprofile.values[:, 0],
initial=0)[-1]
# print(taua_scaled)
assert (round(taua_scaled, 1) == 0.1)
referindex = 5
angstroms = AReader.get_angstroms(self.sensor, 10, referindex,
self.bands)
aprofile_s = ip.aersol(self.bands, angstroms, profile=aprofile)
assert (aprofile_s.columns.shape[0] == len(self.bands) + 2)
from utils import AhmadAerosolReader as AReader
from inputs import input
import numpy as np
sensor = 'msia'
bands = AReader.get_bands(sensor)
bands_int = np.asarray(bands,dtype=int)
print (bands)
rhs, fmfs =AReader.get_names(sensor)
for i,wl in enumerate(bands_int):
scatt, phases = AReader.get_phase_all(sensor, 0)
input.gen_aerosol_phase(sensor=sensor,band=wl, scatt=scatt,phases=phases,rhs=rhs,fmfs=fmfs)
def test_config(self):
bandindex = 8
confg = Config(self.sensor, bandindex)
confg.set_pixels(64, 64)
confg.set_geometry(30, 0, 0, 0)
confg.set_resoluztion(300.0, 300.0)
confg.set_surface("msf_%d" % self.bands_int[bandindex])
confg.set_aerosol_phases("mdlphs_%d" % self.bands_int[bandindex])
## get altitude grid from aerosol profile
aerosolp = SReader.aerosol_profile(taua=0.1)
z = aerosolp['z'].values #km
z = z * 1000 #convert it from km to m
# z_str = list(map(lambda x:"%.6E"%(x)),z) , z))
z_str = list(map(lambda x: "%.6E" % (x), z))
confg.set_altitude_grid(z_str)
## get aerosol extinction profile
referindex = 8 #set 865 as the reference
angstroms = AReader.get_angstroms(self.sensor, 10, referindex,
self.bands)
aprofile_s = ip.aersol(self.bands, angstroms, profile=aerosolp)
aerosol_extinct = aprofile_s['extinct_%d' %
self.bands_int[bandindex]].values
aerosol_extinct = aerosol_extinct * 0.001 #covert it from km^-1 into m^-1
taua_scaled = integrate.cumtrapz(aerosol_extinct, z, initial=0)[-1]
# print(taua_scaled)
assert (round(taua_scaled, 1) == 0.1)
confg.set_aerosol(map(lambda x: "%.6E" % (x), aerosol_extinct),
['0.9767' for i in range(aerosol_extinct.shape[0])],
38)
## get atmosphere profile
atm_profile = SReader.atm_profile()
ray_df, unit = ip.rayleight(atm_profile, self.bands)
ray_df.to_csv("../out/extinction_rayleigh_(%s).csv" % (unit))
z_ray = ray_df['z[km]'].values * 1e3 #convert from km to m
ray_extinct = ray_df['extinction_coe_%d' % self.bands_int[
bandindex]].values * 1e2 #convert from cm^-1 it into m^-1
f = inp.interp1d(z_ray, ray_extinct)
ray_extinct = f(z)
confg.set_rayleigh(map(lambda x: "%.6E" % (x), ray_extinct),
['1.000' for i in range(ray_extinct.shape[0])])
ray_scaled = integrate.cumtrapz(ray_extinct, z, initial=0)[-1]
# print(taua_scaled)
# assert (round(ray_scaled,1)==0.1)
print(ray_scaled)
## get temperature from atmosphere profile
temp_k = ray_df['t[K]'].values
f = inp.interp1d(z_ray, temp_k)
temp_k = f(z)
confg.set_tempprofile(map(lambda x: "%.6E" % (x), temp_k))
## get gas extinction profile
gas_profile = SReader.gas_profile()
no2_crosssect = SReader.no2_cross_section()
o3_crosssect = SReader.ozone_cross_section()
gas_abs, unit = ip.gas_absorption(bands=self.bands,
profile_df=gas_profile,
no2=no2_crosssect,
o3=o3_crosssect)
gas_abs.to_csv("../out/gas_abs_(%s).csv" % unit)
z_gas = gas_abs['Z'].values * 1e3 #convert from km to m
o3_extinct = gas_abs[
'abs_o3_%d' %
self.bands_int[bandindex]].values * 1e2 #convert it into m^-1
f = inp.interp1d(z_gas, o3_extinct)
o3_extinct = f(z)
no2_extinct = gas_abs[
'abs_no2_%d' %
self.bands_int[bandindex]].values * 1e2 #convert it into m^-1
f = inp.interp1d(z_gas, no2_extinct)
no2_extinct = f(z)
confg.set_gas([o3_extinct, no2_extinct])
confg.to_file("../out/config_%d" % (self.bands_int[bandindex]))
def setUp(self):
self.sensor = 'msia'
self.bands = AReader.get_bands(self.sensor)
self.bands_int = np.asarray(self.bands, dtype=int)
from utils import SciatranReader as SReader
from scipy import integrate
from inputs import input as ip
from inputs.config import Config
from scipy import interpolate as inp
taua_nirls = [0.005, 0.010, 0.050, 0.100, 0.500]
aero_phs = [0, 9, 20, 29, 50, 59, 70, 79]
resolutions = [30.0, 100.0, 500.0, 1500.0, 5000.0]
theta_s = [5, 10, 30, 50]
rho_diff = []
rho_diff_df = pd.read_csv("../database/s2_rho_diff.csv", index_col=0)
sensor = 'msia'
bands = AReader.get_bands(sensor)
bands_int = np.asarray(bands, dtype=int)
shape = "river"
columns = rows = 64
for bandindex, band in enumerate(rho_diff_df.columns[:-3]):
confg = Config(sensor, bandindex)
confg.set_pixels(rows, columns)
if not os.path.exists("../out/%d" % (bands_int[bandindex])):
os.mkdir("../out/%d" % (bands_int[bandindex]))
cur_dir = "../out/%d" % (bands_int[bandindex])
wavelenth = bands_int[bandindex]