import os
import sys
sys.path.append("../src")
from Chain import Chain
from plot_Cl_CMB import plot_Cl_CMB
base_folder = "./chains"
name = "planck_WP"
chain = Chain(os.path.join(base_folder, name))
class_folder = "/home/torradocacho/cosmo/code/class_v1.7.2"
spectrum = chain.CMBspectrum_from_point(chain.best_fit(),
class_folder=class_folder,
verbose=True)
plot_Cl_CMB([spectrum], title="Best fit CMB spectrum")
base_folder = os.path.join(CHAINS, "historicas/aaot/gaussN/07_final")
chain = Chain(os.path.join(base_folder, "gaussN_var_c"))
# 2 best fits
best_fit_points = chain.best_fit(how_many=2)
class_folder = "/home/torradocacho/cosmo/code/class_v1.7.2_external_Pk"
# Overall best fit
best_fit_point = best_fit_points[1]
override_params = {
"command":
"python " +
os.path.join(class_folder, "external_Pk/generate_Pk_from_u_gaussN.py")
}
spectrum_bf1 = chain.CMBspectrum_from_point(best_fit_point,
class_folder=class_folder,
override_params=override_params,
verbose=True)
override_params = {
"P_k_ini type": "analytic_Pk",
"A_s": best_fit_point[chain.index_of_param("custom2", chain=True)],
"n_s": best_fit_point[chain.index_of_param("custom3", chain=True)]
}
spectrum_bf1_0 = chain.CMBspectrum_from_point(best_fit_point,
class_folder=class_folder,
override_params=override_params,
verbose=True)
nuisance_bf1 = chain.nuisance_file_from_point(best_fit_point, None)
lik.set_nuisance(n_dict=nuisance_bf1)
print "The original -loglik was: ", best_fit_point[5]
# Get the respective likelihoods
