# Get the filterid filter.
f.read(filter_file, path='/%s/%s' % (filterid, ccd))
# For each defined redshift, eval the photometry and store on the database.
db_m = db.get('/%s/%s/%s' % (filterid, ccd, 'library'))
i_z = 0
for z in np.arange(z_from, z_to, z_step):
if z == 0:
d_L = 3.08567758e19 # 10 parsec in cm
else:
d_L = cosmocalc.cosmocalc(z)['DL_cm']
k_cosmo = L_sun / ( 4 * np.pi * np.power(d_L,2) )
O = zcor(obs_spec, z)
O['flux'] = O['flux'] * k_cosmo
x = spec2filterset(f.filterset, O, dlambda_eff = 3.0)
# print 'z', z
# print aux0[i_base]
#
# plt.figure(1)
# plt.clf()
# plt.plot(O['wl'][kk], O['flux'][kk])
# plt.figure(2)
# plt.clf()
# plt.plot(f.filteravgwls, x, '.')
# Get the filterid filter.
f.read(filter_file, path='/%s/%s' % (filterid, ccd))
# For each defined redshift, eval the photometry and store on the database.
db_m = db.get('/%s/%s/%s' % (filterid, ccd, 'library'))
i_z = 0
for z in np.arange(z_from, z_to, z_step):
if z == 0:
d_L = 3.08567758e19 # 10 parsec in cm
else:
d_L = cosmocalc.cosmocalc(z)['DL_cm']
k_cosmo = L_sun / ( 4 * np.pi * np.power(d_L,2) )
O = zcor(obs_spec, z)
O['flux'] = O['flux'] * k_cosmo
O['error'] = O['error'] * k_cosmo
M = zcor(model_spec, z)
M['flux'] = M['flux'] * k_cosmo
x = spec2filterset(f.filterset, O, M, dlambda_eff = 3.0)
db_m[i_z, i_file] = x
i_z = i_z + 1
db.close()
log.debug('Took %3.2f seconds.' % (time.time() - t_start))
