get_conf

sherpa.ui.get_conf()

Return the confidence-interval estimation object.

Returns:conf
Return type:object

See also

conf()
Estimate confidence intervals using the confidence method.
get_conf_opt()
Return one or all of the options for the confidence interval method.
set_conf_opt()
Set an option of the conf estimation object.

Notes

The attributes of the confidence-interval object include:

eps
The precision of the calculated limits. The default is 0.01.
fast
If True then the fit optimization used may be changed from the current setting (only for the error analysis) to use a faster optimization method. The default is False.
max_rstat
If the reduced chi square is larger than this value, do not use (only used with chi-square statistics). The default is 3.
maxfits
The maximum number of re-fits allowed (that is, when the remin filter is met). The default is 5.
maxiters
The maximum number of iterations allowed when bracketing limits, before stopping for that parameter. The default is 200.
numcores
The number of computer cores to use when evaluating results in parallel. This is only used if parallel is True. The default is to use all cores.
openinterval
How the conf method should cope with intervals that do not converge (that is, when the maxiters limit has been reached). The default is False.
parallel
If there is more than one free parameter then the results can be evaluated in parallel, to reduce the time required. The default is True.
remin
The minimum difference in statistic value for a new fit location to be considered better than the current best fit (which starts out as the starting location of the fit at the time conf is called). The default is 0.01.
sigma
What is the error limit being calculated. The default is 1.
soft_limits
Should the search be restricted to the soft limits of the parameters (True), or can parameter values go out all the way to the hard limits if necessary (False). The default is False
tol
The tolerance for the fit. The default is 0.2.
verbose
Should extra information be displayed during fitting? The default is False.

Examples

>>> print(get_conf())
name         = confidence
numcores     = 8
verbose      = False
openinterval = False
max_rstat    = 3
maxiters     = 200
soft_limits  = False
eps          = 0.01
fast         = False
maxfits      = 5
remin        = 0.01
tol          = 0.2
sigma        = 1
parallel     = True

Change the remin field to 0.05.

>>> cf = get_conf()
>>> cf.remin = 0.05