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 coefficientscoefs
, 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 coefficientscoefs
, 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.