gwinferno.models.bsplines.separable.BSplinePrimaryBSplineRatio

class BSplinePrimaryBSplineRatio(n_splines_m, n_splines_q, m1, m1_inj, q, q_inj, mmax=100.0, m1min=3.0, m2min=3.0, kwargs_m={}, kwargs_q={}, **kwargs)

Bases: object

B-Spline models for the primary mass and mass ratio,

\[p(m_1, q \mid \mathbf{c}_m, \mathbf{c}_q) = p(m_1 \mid \mathbf{c}_m) p(q \mid \mathbf{c}_q),\]

where \(\mathbf{c}_m\) and \(\mathbf{c}_q\) are vectors of the n_splines_m and n_splines_q basis spline coefficients for the primary mass and mass ratio, respectively.

Parameters:

n_splines_m, n_splines_qint

Number of basis functions, i.e., the number of degrees of freedom, of the primary component mass and mass ratio spline models.

m1array_like

Primary component mass parameter estimation samples for basis evaluation.

m1_injarray_like

Primary component mass injection samples for basis evaluation.

qarray_like

Mass ratio parameter estimation samples for basis evaluation.

q_injarray_like

Mass ratio injection samples for basis evaluation.

mmaxfloat, default=100

Maximum component mass.

m1minfloat, default=3

Minimum primary component mass.

m2minfloat, default=3

Minimum secondary component mass, setting lower bound on the mass ratio (\(q>m_{2,\mathrm{min}}/m_\mathrm{max}\)).

kwargs_m, kwargs_qdict, optional

Additional keyword arguments to pass to the basis spline models for the primary component mass and mass ratio.

**kwargsdict, optional

Additional keyword arguments to pass to both basis spline models.

Methods

__call__(mcoefs, qcoefs, pe_samples=True)

Evaluate the joint probability density over the parameter estimation or injection samples. Use flag pe_samples to specify which samples are being evaluated (parameter estimation or injection).

Parameters:

mcoefs, qcoefsarray_like

Spline coefficients for the primary component mass and mass ratio.

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

Joint probability density for parameter estimation or injection samples.

__init__(n_splines_m, n_splines_q, m1, m1_inj, q, q_inj, mmax=100.0, m1min=3.0, m2min=3.0, kwargs_m={}, kwargs_q={}, **kwargs)