import matplotlib
matplotlib.use('Agg')
import numpy as np
import pylab as plt
from pspy import so_dict, so_map, so_mcm, sph_tools, so_spectra, pspy_utils, so_map_preprocessing
import os, sys
from pixell import enmap
import time, os
d = so_dict.so_dict()
d.read_from_file(sys.argv[1])
spectraDir = 'spectra'
try:
os.makedirs(spectraDir)
except:
pass
spectra = ['TT', 'TE', 'TB', 'ET', 'BT', 'EE', 'EB', 'BE', 'BB']
arrays = d['arrays']
niter = d['niter']
lmax = d['lmax']
type = d['type']
binning_file = d['binning_file']
theoryfile = d['theoryfile']
fsky = {}
fsky['pa1'] = 'fsky0.01081284'
fsky['pa2'] = 'fsky0.01071187'
apo = so_map.read_map(d['apo_path'])
def get_cl_array(cosmo_parameters, fg_parameters, ell_max, freq_list,
noise_list_matrix):
d = so_dict.so_dict()
d.read_from_file("global_healpix_example.dict")
fg_norm = d["fg_norm"]
components = {"tt": d["fg_components"], "ee": [], "te": []}
fg_model = {"normalisation": fg_norm, "components": components}
fg_params = {
'a_tSZ': fg_parameters[0],
'a_kSZ': fg_parameters[1],
'a_p': fg_parameters[2],
'beta_p': fg_parameters[3],
'a_c': fg_parameters[4],
'beta_c': fg_parameters[5],
'n_CIBC': 1.2,
'a_s': fg_parameters[6],
'T_d': 9.6
}
pars = camb.CAMBparams()
pars.set_cosmology(H0=cosmo_parameters[0],
ombh2=cosmo_parameters[1],
omch2=cosmo_parameters[2],
mnu=0.06,
omk=0,
tau=cosmo_parameters[5])
pars.InitPower.set_params(As=1e-10 * np.exp(cosmo_parameters[3]),
ns=cosmo_parameters[4],
r=0)
pars.set_for_lmax(ell_max - 1, lens_potential_accuracy=0)
results = camb.get_results(pars)
powers = results.get_cmb_power_spectra(pars, CMB_unit="muK")
totCL = powers['total']
TT = totCL[:, 0][2:]
ell_list = np.arange(len(TT) + 2)[2:]
power_spectrum_matrix = []
noise_list_matrix = [
element[:len(freq_list), :len(freq_list)]
for element in noise_list_matrix
]
fg_dict = mfl.get_foreground_model(fg_params, fg_model, freq_list,
ell_list)
n_ell = len(ell_list)
n_freqs = len(freq_list)
for ell in range(n_ell):
c_matrix = np.ones((n_freqs, n_freqs)) * TT[ell]
for i in range(n_freqs):
for j in range(n_freqs):
c_matrix[i, j] = c_matrix[i, j] + noise_list_matrix[ell][
i, j] + fg_dict['tt', 'all', freq_list[i],
freq_list[j]][ell]
power_spectrum_matrix.append(c_matrix)
return (np.array(power_spectrum_matrix))
