gwinferno.models.bsplines.single.BSplineRedshift#

class BSplineRedshift(n_splines, z, z_inj, dVdc, dVdc_inj, zmax=2.3, basis=<class 'gwinferno.interpolation.LogXBSpline'>, **kwargs)[source]#

Bases: Base1DBSplineModel

A B-Spline model for redshift. The B-Spline will define the volumetric rate density \(r\), which relates to the merger-rate per unit redshift in the detector-frame \(R\) by

\[R(z) = \frac{r(z)}{1+z} \frac{dV_c}{dz},\]

where \(dV_c/dz\) is the co-moving volume element and \(r(z)\) is the merger rate per unit co-moving volume.

Parameters:

n_splinesint: Number of basis functions, i.e., the number of degrees of freedom of the spline model.
zarray_like: Redshift parameter estimation samples for basis evaluation.
z_injarray_like: Redshift injection samples for basis evaluation.
dVdcarray_like: Differential co-moving volume for each parameter estimation sample.
dVdc_injarray_like: Differential co-moving volume for each injection sample.
zmaxfloat, default=2.3: Maximum redshift. Ignored if xrange is provided.
basisclass, default=LogXBSpline: 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.
`normalization`(cs)	Compute the normalization coefficient for the redshift basis spline; useful for computing the merger rate.
`pe_pdf`(coefs)	Project the coefficients `coefs` onto the design matrix evaluated at the parameter estimation samples.

__call__(coefs, pe_samples=True)[source]#

Evaluate the merger-rate per unit redshift in the detector-frame \(R\). 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: Merger-rate per unit redshift in the detector-frame \(R\).

__init__(n_splines, z, z_inj, dVdc, dVdc_inj, zmax=2.3, basis=<class 'gwinferno.interpolation.LogXBSpline'>, **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.

normalization(cs)[source]#

Compute the normalization coefficient for the redshift basis spline; useful for computing the merger rate.

Parameters:

coefsarray_like: Basis spline coefficients.

Returns:

float: The redshift normalization constant.

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.