import os import sys sys.path.append("../src") from Chain import Chain from Likelihood_Planck import Likelihood_Planck # Prepare the likelihoods likelihoods = ["commander", "CAMspec", "lowlike"] clik_dir = "/home/torradocacho/codes/stable/planck_likelihood_1303" lik = Likelihood_Planck(base_folder=clik_dir, likelihoods=likelihoods) # Prepare the spectra CHAINS = "/data/misc/torradocacho/chains" 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,
import os import sys sys.path.append("../src") from CMBspectrum import CMBspectrum from Likelihood_Planck import Likelihood_Planck # Prepare the likelihoods likelihoods = ["commander", "CAMspec", "lowlike"] clik_dir = "/home/torradocacho/cosmo/data/planck/likelihood" lik = Likelihood_Planck(base_folder=clik_dir, likelihoods=likelihoods) # Prepare the spectrum base_folder = "./CMB_spectra" spectrum_name = "planck_WP" spectrum = CMBspectrum(os.path.join(base_folder, spectrum_name)) # Prepare the nuisance parameters base_folder = "./nuisance" nuisance_name = "nuisance_planck_WP.dat" lik.set_nuisance(n_file=os.path.join(base_folder, nuisance_name)) # Get the likelihood loglik = lik.get_loglik(spectrum, verbose=True)
import os import sys sys.path.append("../src") from Chain import Chain from Likelihood_Planck import Likelihood_Planck # Prepare the likelihoods likelihoods = ["commander", "CAMspec", "lowlike"] clik_dir = "/home/torradocacho/codes/stable/planck_likelihood_1303" lik = Likelihood_Planck(base_folder=clik_dir, likelihoods=likelihoods) # Prepare the spectra CHAINS = "/data/misc/torradocacho/chains" 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",