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.

Attributes Summary


Methods Summary

get_scales(fit[, myscales])

Return the samples.

Attributes Documentation

sigma = 1

Methods Documentation

get_scales(fit, myscales=None)[source] [edit on github]

Return the samples.

  • fit ( instance) – This defines the thawed parameters that are used to generate the samples, along with any possible error analysis.

  • myscales (numpy array or None, optional) – The scales to use. If None then they are calculated from the fit.


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

Return type

numpy array