Python Chain.best_fit Beispiele

Beispiel #1

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")

Beispiel #2

Datei: chain_point_to_CMBspectrum.py Projekt: JesusTorrado/cosmo_mini_toolbox

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")

Beispiel #3

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 = {

Beispiel #4

Datei: likelihood_compare_example.py Projekt: JesusTorrado/cosmo_mini_toolbox

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",
                   "A_s": best_fit_point[chain.index_of_param("custom2", chain=True)],
                   "n_s": best_fit_point[chain.index_of_param("custom3", chain=True)]}