set_sampler_opt

sherpa.ui.set_sampler_opt(opt, value)

Set an option for the current MCMC sampler.

Parameters:
  • opt (str) – The option to change. Use get_sampler to view the available options for the current sampler.
  • value – The value for the option.

See also

get_sampler()
Return the current MCMC sampler options.
set_prior()
Set the prior function to use with a parameter.
set_sampler()
Set the MCMC sampler.

Notes

The options depend on the sampler. The options include:

defaultprior
Set to False when the default prior (flat, between the parameter’s soft limits) should not be used. Use set_prior to set the form of the prior for each parameter.
inv
A bool, or array of bools, to indicate which parameter is on the inverse scale.
log
A bool, or array of bools, to indicate which parameter is on the logarithm (natural log) scale.
original
A bool, or array of bools, to indicate which parameter is on the original scale.
p_M
The proportion of jumps generatd by the Metropolis jumping rule.
priorshape
An array of bools indicating which parameters have a user-defined prior functions set with set_prior.
scale
Multiply the output of covar by this factor and use the result as the scale of the t-distribution.

Examples

>>> set_sampler_opt('scale', 3)