mrpy.extra.likelihoods.CurveLike

class mrpy.extra.likelihoods.CurveLike(logm, data_dndm, logHs, alpha, beta, lnA, sig_data=1, sig_rhomean=inf, rhom=83265000000.0)

A subclass of mrpy.core.MRP_PO_Likelihood which adds the likelihood (and derivatives) of a model given data in the form of a curve.

See Murray, Robotham, Power (2017), Appendix C.1 for a description.

Parameters:

logm : array_like

Vector of log10 masses.

data_dndm : array_like

Array of the same length as logm, giving the value of the differential mass function.

hs, alpha, beta, lnA : float

The parameters of the MRP.

sig_data : array_like, optional

The uncertainty of the data (standard deviation). This is used in the likelihood to weight different mass scales. If scalar, all mass scales are weighted evenly.

sig_rhomean,: float, optional

This controls how much influence the total mean density of the universe has on the likelihood. The default value of inf means it is completely ignored. If it is 0, it becomes an absolute constraint, so that the total mass density of the universe is perfectly matched (setting the normalisation). In between, it acts as an uncertainty on this value.

rhom : float, optional

Mass density of the Universe. Only used if ‘sig_rhomean` not infinite.

Methods

__init__(logm, data_dndm, logHs, alpha, …)
dndlog10m([log]) Return the MRP in log10 space at `m’.
dndm([log]) Return the MRP at m.
ngtm([log]) The number density greater than mmin.
rho_gtm([log]) The mass-weighted integral of the MRP, in reverse (ie.