MultiFilterASTs

class beast.observationmodel.noisemodel.toothpick.MultiFilterASTs(astfile, filters, vega_fname=None, *args, **kwargs)[source]

Bases: beast.observationmodel.noisemodel.noisemodel.NoiseModel

A noise model for based Artificial Star Tests (ASTs) that are provided as one single table.

The noise model is computed in equally spaced bins in log flux space to avoid injecting noise when the ASTs grossly oversample the model space. This is the case for single band ASTs - this is always the case for the BEAST toothpick noise model.

Attributes
astfilestr

file containing the ASTs

filterslist

sequence of filter names

filter_aliasesdict

alias of filter names between internal and external names

Parameters
astfilestr

file containing the ASTs

filterslist

filters using the internal namings (obs_inst_band)

vega_fnamestr, optional

filename of the vega database

Methods Summary

__call__(sedgrid, **kwargs)

Call self as a function.

fit([nbins, completeness_mag_cut, progress])

Alias of fit_bins

fit_bins([nbins, completeness_mag_cut, progress])

Compute the necessary statistics before evaluating the noise model

interpolate(sedgrid[, progress])

Interpolate the results of the ASTs on a model grid

setFilters(filters[, vega_fname])

Set the filters and update the vega reference for the conversions

set_data_mappings([in_pair, out_pair, upcase])

Specify the mapping directly with the interface to PHAT-like ASTs

Methods Documentation

__call__(sedgrid, **kwargs)[source]

Call self as a function.

fit(nbins=50, completeness_mag_cut=80, progress=True)[source]

Alias of fit_bins

fit_bins(nbins=50, completeness_mag_cut=80, progress=True)[source]

Compute the necessary statistics before evaluating the noise model

Parameters
completeness_mag_cutfloat

magnitude at which consider a star not recovered

progressbool, optional

if set, display a progress bar

.. see also: :func:`_compute_stddev`
interpolate(sedgrid, progress=True)[source]

Interpolate the results of the ASTs on a model grid

Parameters
sedgridbeast.core.grid type

model grid to interpolate AST results on

progressbool, optional

if set, display a progress bar

Returns
biasndarray

bias table of the models

sigmandarray

dispersion table of the models

compndarray

completeness table per model

setFilters(filters, vega_fname=None)[source]

Set the filters and update the vega reference for the conversions

Parameters
filterslist

filters using the internally normalized namings

vega_fnamestr, optional

filename of the vega database

set_data_mappings(in_pair='in', 'in', out_pair='out', 'vega', upcase=False)[source]

Specify the mapping directly with the interface to PHAT-like ASTs

Parameters
in_pair, out_pairtuple, optional

(in, out) strings giving the ending string mappings defaults: (in, in) aliases internal HST_WFC3_F275W_in to exernal f275w_in and (out, vega) aliases internal HST_WFC3_F275W_out to external f275w_vega

upcasebool, optional

set to make the external name all uppercase