# get_proj¶

sherpa.astro.ui.get_proj()

Return the confidence-interval estimation object.

Note

The conf function should be used instead of proj.

Returns: proj object

conf()
Estimate parameter confidence intervals using the confidence method.
get_proj_opt()
Return one or all of the options for the confidence interval method.
proj()
Estimate confidence intervals for fit parameters.
set_proj_opt()
Set an option of the proj estimation object.

Notes

The attributes of the 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.
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 proj 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.

Examples

>>> print(get_proj())
name        = projection
numcores    = 8
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