pybird.fake module

pybird.fake.get_cov_gauss(kk, dk, ipk_lin, b1, f1, Vs=3000000000.0, nbar=0.0003, n_mult=3)[source]

class pybird.fake.Fake(n_sky, zmin, zmax, zeff, Veff, degsq, P0, fiducial_cosmo, likelihood_config=None, likelihood_config_template_file='.h5', fiducial_nuisance=None, boltzmann='class', Omega_m_fid=0.31, kmin=0.005, kmax=0.4, dk=0.01, k_arr=None, cov=None, nbar=None, nbar_prior=None, fake_data_filename='fake_', path_to_data='./', fake_likelihood_config_filename='fake_', path_to_config='./')[source]

Bases: object

A class to generate fake data for testing PyBird calculations.

The Fake class creates synthetic power spectrum data with realistic covariance matrices for testing and validation purposes. It handles survey-specific parameters, cosmological models, and EFT nuisance parameters to generate realistic test cases.

n_sky

Number of sky patches.

Type:: int

cosmo

Cosmological parameters.

Type:: dict

boltzmann

Boltzmann solver to use (‘class’, ‘Symbolic’, etc.).

Type:: str

zmin

Minimum redshift for each sky patch.

Type:: list

zmax

Maximum redshift for each sky patch.

Type:: list

zeff

Effective redshift for each sky patch.

Type:: list

Veff

Effective volume for each sky patch.

Type:: list

degsq

Sky area in square degrees for each sky patch.

Type:: list

P0

Power spectrum normalization for each sky patch.

Type:: list

Omega_m_fid

Fiducial matter density parameter.

Type:: float

kmin

Minimum k value for power spectrum.

Type:: float

kmax

Maximum k value for power spectrum.

Type:: float

dk

k-bin width.

Type:: float

path_to_data

Path to save fake data files.

Type:: str

fake_data_filename

Base name for fake data files.

Type:: str

path_to_config

Path to save configuration files.

Type:: str

fake_likelihood_config_filename

Base name for configuration files.

Type:: str

fiducial_nuisance

Fiducial EFT nuisance parameters.

Type:: dict

c

Configuration dictionary for correlator.

Type:: dict

e

List of Correlator instances for each sky patch.

Type:: list

nbar

Number density for each sky patch.

Type:: list

H_fid

Fiducial Hubble parameter for each sky patch.

Type:: list

D_fid

Fiducial angular diameter distance for each sky patch.

Type:: list

kd

Array of k values for power spectrum.

Type:: ndarray

to_list()[source]: Convert input to list format matching n_sky.

set_survey_specific()[source]: Set survey-specific parameters.

set_correlator()[source]: Initialize correlator with configuration.

set_nuisance()[source]: Set EFT nuisance parameters.

set()[source]: Generate and save fake data.

test()[source]: Test the generated fake data with PyBird likelihood.

to_list(x, type=<class 'float'>, what='')[source]

set_survey_specific(zmin, zmax, zeff, Veff=10000000000.0, degsq=14000.0, P0=9000.0, Omega_m_fid=0.31, kmin=0.005, kmax=0.4, dk=0.01, k_arr=None, cov=None, nbar=None)[source]

set_correlator(likelihood_config, nbar=None)[source]

set_nuisance(fiducial_nuisance=None)[source]

set(prior_center_on_truth=True)[source]

test(run_config=None, plot=False)[source]