ParameterScale¶
- class sherpa.sim.sample.ParameterScale[source] [edit on github]¶
Bases:
sherpa.utils.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.
- Parameters
fit (sherpa.fit.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.
- Returns
scales – The scales array (npar elements, matching the free parameters in fit). It may be multi-dimensional.
- Return type
numpy array