gwinferno.models.bsplines.single.BSplineMass#

class BSplineMass(n_splines, m, m_inj, mmin=2, mmax=100, basis=<class 'gwinferno.interpolation.LogXLogYBSpline'>, **kwargs)[source]#

Bases: Base1DBSplineModel

A B-Spline model for the mass of a single binary component.

Parameters:
n_splinesint

Number of basis functions, i.e., the number of degrees of freedom of the spline model.

marray_like

Component mass parameter estimation samples for basis evaluation.

m_injarray_like

Component mass injection samples for basis evaluation.

mminfloat, default=2

Minimum component mass. Ignored if xrange is provided.

mmaxfloat, default=100

Maximum component mass. Ignored if xrange is provided.

basisclass, default=LogXLogYBSpline

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, m, m_inj, mmin=2, mmax=100, basis=<class 'gwinferno.interpolation.LogXLogYBSpline'>, **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.