clmm.utils.boost module

General utility functions that are used in multiple modules

clmm.utils.boost.compute_nfw_boost(rvals, rscale=1000, boost0=0.1)[source]

Given a list of rvals, and optional rscale and boost0, return the corresponding boost factor at each rval

Parameters:

rvals (array_like) -- Radii
rscale (float, optional) -- scale radius for NFW in same units as rvals (default 2000 kpc)
boost0 (float, optional) -- Boost factor at each value of rvals

Returns:

Boost factor

Return type:

array

clmm.utils.boost.compute_powerlaw_boost(rvals, rscale=1000, boost0=0.1, alpha=-1.0)[source]

Given a list of rvals, and optional rscale and boost0, and alpha, return the corresponding boost factor at each rval

Parameters:

rvals (array_like) -- Radii
rscale (float, optional) -- Scale radius for NFW in same units as rvals (default 2000 kpc)
boost0 (float, optional) -- Boost factor at each value of rvals
alpha (float, optional) -- Exponent from Melchior+16. Default: -1.0

Returns:

Boost factor

Return type:

array

clmm.utils.boost.correct_sigma_with_boost_model(rvals, sigma_vals, boost_model='nfw_boost', **boost_model_kw)[source]

Given a boost model and sigma profile, compute corrected sigma

Parameters:

rvals (array_like) -- radii
sigma_vals (array_like) -- uncorrected sigma with cluster member dilution
boost_model (str, optional) --
Boost model to use for correcting sigma
- 'nfw_boost' - NFW profile model (Default)
- 'powerlaw_boost' - Powerlaw profile

Returns:

sigma_corrected -- correted radial profile

Return type:

numpy.ndarray

clmm.utils.boost.correct_sigma_with_boost_values(sigma_vals, boost_factors)[source]

Given a list of boost values and sigma profile, compute corrected sigma

Parameters:

Returns:

sigma_corrected -- correted radial profile

Return type:

numpy.ndarray