gwinferno.models.bsplines.single.BSplineChiPrecess#

class BSplineChiPrecess(n_splines, chip, chip_inj, basis=<class 'gwinferno.interpolation.BSpline'>, **kwargs)[source]#

Bases: Base1DBSplineModel

A B-Spline model for the binary effective precession \(\chi_\mathrm{p}\).

Parameters:

n_splinesint: Number of basis functions, i.e., the number of degrees of freedom of the spline model.
chiparray_like: Effective precession parameter estimation samples for basis evaluation.
chip_injarray_like: Effective precession injection samples for basis evaluation.
basisclass, default=BSpline: Type of basis to use.

Methods

`eval_spline`(bases, coefs)	Given design matrix `bases` and coefficients `coefs`, project coefficients onto the basis.
`inj_pdf`(coefs)	Project the coefficients `coefs` onto the design matrix evaluated at the injection samples.
`pe_pdf`(coefs)	Project the coefficients `coefs` onto the design matrix evaluated at the parameter estimation samples.

__call__(coefs, pe_samples=True)#

Evaluate the projection of the coefficients along the design matrix over the parameter estimation or injection samples. Use flag pe_samples to specify which samples are being evaluated (parameter estimation or injection).

Parameters:

coefsarray_like: Basis spline coefficients.
pe_samplesbool, default=True: If True, design matrix is evaluated across parameter estimation samples. If False, design matrix is evaluated across injection samples.

Returns:

array_like: The linear combination of the basis components evaluated at the parameter estimation or injection samples given the coefficients.

__init__(n_splines, chip, chip_inj, basis=<class 'gwinferno.interpolation.BSpline'>, **kwargs)[source]#

eval_spline(bases, coefs)#

Given design matrix bases and coefficients coefs, project coefficients onto the basis.

Parameters:

basesarray_like: Design matrix of the spline, i.e., basis functions evaluated at samples.
coefsarray_like: Basis spline coefficients.

Returns:

array_like: The linear combination of the basis components given the coefficients.

inj_pdf(coefs)#

Project the coefficients coefs onto the design matrix evaluated at the injection samples.

Parameters:

coefsarray_like: Basis spline coefficients.

Returns:

array_like: The linear combination of the basis components evaluated at the injection samples given the coefficients.

pe_pdf(coefs)#

Project the coefficients coefs onto the design matrix evaluated at the parameter estimation samples.

Parameters:

coefsarray_like: Basis spline coefficients.

Returns:

array_like: The linear combination of the basis components evaluated at the parameter estimation samples given the coefficients.