pspec_likelihood.likelihood.GaussianLinearSystematics

class pspec_likelihood.likelihood.GaussianLinearSystematics(*, model: DataModelInterface, set_negative_to_zero=False, linear_systematics_basis_function: Callable, linear_systematics_mean: ndarray, linear_systematics_cov: ndarray)

A Gaussian likelihood where some systematics are assumed to be linear.

Parameters:

• linear_systematics_basis_function (Callable) – A function that, given a set of non-linear systematics parameters (potentially an empty set), will compute the basis set corresponding to the known linear parameters of the model, at the kperp/kpar of either the observation or theory.

• linear_systematics_mean (numpy.ndarray) – The prior mean of the linear systematics.

• linear_systematics_cov (numpy.ndarray) – The prior covariance of the linear systematics.

Methods

__init__(*, model[, set_negative_to_zero])	Method generated by attrs for class GaussianLinearSystematics.
get_mu_linear(basis)	Compute the posterior mean of linear parameters.
get_sigma_linear(basis)	Compute the posterior covariance of the linear parameters.
loglike(theory_params, sys_params)	Compute the log likelihood.
validate()	Validation of a particular likelihood.

Attributes

data_mask	A mask where data is properly defined and usable.
power_spectrum	Return power_spectrum respecting set_negative_to_zero.
variance	Compute the variance of the likelihood.
linear_systematics_basis_function
linear_systematics_mean
linear_systematics_cov
model
set_negative_to_zero