def sz_lut(scheme, hydrom_type, list_frequencies, list_elevations,
list_temperatures, quad_pts):
"""
Computes and saves a scattering lookup table for a given
hydrometeor type (non melting) and various frequencies, elevations, etc.
Args:
scheme: microphysical scheme, '1mom' or '2mom'
hydrom_type: the hydrometeor type, either 'mS' (melt. snow)
or 'mG' (melt. graup)
list_frequencies: list of frequencies for which to obtain the
lookup tables, in GHz
list_elevations: list of incident elevation angles for which to
obtain the lookup tables, in degrees
list_temperatures: list of temperatures for which to obtain the
lookup tables, in K
quad_pts: the quadrature points computed with the
calculate_quadrature_points function (see below)
Returns:
No output but saves a lookup table
"""
if np.isscalar(list_frequencies):
list_frequencies = [list_frequencies]
hydrom = create_hydrometeor(hydrom_type, scheme)
if hydrom_type != 'R':
hydrom.radius_type = Scatterer.RADIUS_EQUAL_VOLUME
else:
hydrom.radius_type = Scatterer.RADIUS_MAXIMUM
list_D = np.linspace(hydrom.d_min, hydrom.d_max,
NUM_DIAMETERS).astype('float32')
num_cores = multiprocessing.cpu_count()
for f in list_frequencies:
global SCATTERER
wavelength = constants.C / (f * 1E09) * 1000 # in mm
SCATTERER = _create_scatterer(wavelength, hydrom.canting_angle_std)
SZ_matrices = np.zeros(
(len(list_elevations), len(list_temperatures), len(list_D), 12))
for i, e in enumerate(list_elevations):
print('Running elevation : ' + str(e))
results = (Parallel(n_jobs=num_cores)(
delayed(_compute_sz_with_quad)(hydrom, f, e, t, quad_pts[0],
quad_pts[1], list_D)
for t in list_temperatures))
arr_SZ = _flatten_matrices(results)
SZ_matrices[i, :, :, :] = arr_SZ
# Create lookup table for a given frequency
lut_SZ = Lookup_table()
lut_SZ.add_axis('e', list_elevations)
lut_SZ.add_axis('t', list_temperatures)
lut_SZ.add_axis('d', list_D)
lut_SZ.add_axis('sz', np.arange(12))
lut_SZ.set_value_table(SZ_matrices)
# The name of the lookup table is lut_SZ_<hydro_name>_<freq>_<scheme>.lut
filename = (FOLDER_LUT + "lut_SZ_" + hydrom_type + '_' +
str(f).replace('.', '_') + '_' + scheme + ".lut")
save_lut(lut_SZ, filename)
def sz_lut_melting(scheme, hydrom_type, list_frequencies, list_elevations,
list_wcontent, quad_pts):
"""
Computes and saves a scattering lookup table for a given melting
hydrometeortype and various frequencies, elevations, etc.
Args:
scheme: microphysical scheme, '1mom' or '2mom'
hydrom_type: the hydrometeor type, either 'mS' (melt. snow)
or 'mG' (melt. graup)
list_frequencies: list of frequencies for which to obtain the
lookup tables, in GHz
list_elevations: list of incident elevation angles for which to
obtain the lookup tables, in degrees
list_wcontent: list of water contents for which to obtain the
lookup tables, unitless, from 0 to 1
quad_pts: the quadrature points computed with the
calculate_quadrature_points function (see below)
Returns:
No output but saves a lookup table
"""
if np.isscalar(list_frequencies):
list_frequencies = [list_frequencies]
hydrom = create_hydrometeor(hydrom_type, scheme)
hydrom.radius_type = Scatterer.RADIUS_MAXIMUM
array_D = []
for wc in W_CONTENTS:
hydrom.f_wet = wc
list_D = np.linspace(hydrom.d_min, hydrom.d_max,
NUM_DIAMETERS).astype('float32')
array_D.append(list_D)
array_D = np.array(array_D)
num_cores = multiprocessing.cpu_count()
for f in list_frequencies:
global SCATTERER
wavelength = constants.C / (f * 1E09) * 1000 # in mm
# The 40 here is the orientation std, but it doesn't matter since
# we integrate "manually" over the distributions, we just have
# to set something to start
SCATTERER = _create_scatterer(wavelength, 40)
SZ_matrices = np.zeros(
(len(list_elevations), len(list_wcontent), len(list_D), 12))
for i, e in enumerate(list_elevations):
print('Running elevation : ' + str(e))
results = (Parallel(n_jobs=num_cores)(
delayed(_compute_sz_with_quad_melting)(
hydrom, f, e, wc, quad_pts[j][0], quad_pts[j][1])
for j, wc in enumerate(list_wcontent)))
arr_SZ = _flatten_matrices(results)
SZ_matrices[i, :, :, :] = arr_SZ
# Create lookup table for a given frequency
lut_SZ = Lookup_table()
lut_SZ.add_axis('e', list_elevations)
lut_SZ.add_axis('wc', list_wcontent)
lut_SZ.add_axis('d', array_D)
lut_SZ.add_axis('sz', np.arange(12))
lut_SZ.set_value_table(SZ_matrices)
# The name of the lookup table is lut_SZ_<hydro_name>_<freq>_<scheme>.lut
filename = (FOLDER_LUT + "lut_SZ_" + hydrom_type + '_' +
str(f).replace('.', '_') + '_' + scheme + ".lut")
save_lut(lut_SZ, filename)