ParameterScale

class sherpa.sim.sample.ParameterScale[source] [edit on github]

Bases: NoNewAttributesAfterInit

Create the scaling used to generate parameters.

The scaling generally refers to an error value (defaulting to one sigma) for each parameter.

Methods

get_scales(fit[, myscales])

Return the samples.

Attributes Summary

sigma

Methods Summary

get_scales(fit[, myscales])

Return the samples.

Attributes Documentation

sigma: float = 1

Methods Documentation

get_scales(fit: Fit, myscales: ndarray | None = None) → ndarray[source] [edit on github]

Return the samples.

Parameters:
fitsherpa.fit.Fit instance

This defines the thawed parameters that are used to generate the samples, along with any possible error analysis.

myscalesnumpy array or None, optional

The scales to use. If None then they are calculated from the fit.

Returns:
scalesnumpy array

The scales array (npar elements, matching the free parameters in fit). It may be multi-dimensional.