MultiFilterASTs¶
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class
beast.observationmodel.noisemodel.toothpick.
MultiFilterASTs
(astfile, filters, vega_fname=None, *args, **kwargs)[source]¶ Bases:
beast.observationmodel.noisemodel.noisemodel.NoiseModel
Implement a noise model for which input information of ASTs are provided as one single table
Attributes
astfile: str file containing the ASTs filters: sequence(str) sequence of filter names Methods Summary
__call__
(…) <==> x(…)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
()hard code mapping directly with the interface to PHAT-like ASTs Methods Documentation
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fit_bins
(nbins=30, completeness_mag_cut=80, progress=True)[source]¶ Compute the necessary statistics before evaluating the noise model
Parameters: completeness_mag_cut: float
magnitude at which consider a star not recovered
progress: bool, optional
if set, display a progress bar
.. see also: :func:`_compute_stddev`
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interpolate
(sedgrid, progress=True)[source]¶ Interpolate the results of the ASTs on a model grid
Parameters: sedgrid: beast.core.grid type
model grid to interpolate AST results on
progress: bool, optional
if set, display a progress bar
Returns: bias: ndarray
bias table of the models
sigma: ndarray
dispersion table of the models
comp: ndarray
completeness table per model
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