get_int_proj

sherpa.ui.get_int_proj(par=None, id: IdType | None = None, otherids: Sequence[IdType] | None = None, recalc=False, fast=True, min=None, max=None, nloop=20, delv=None, fac=1, log=False, numcores=None)

Return the interval-projection object.

This returns (and optionally calculates) the data used to display the int_proj plot. Note that if the the recalc parameter is False (the default value) then all other parameters are ignored and the results of the last int_proj call are returned.

Changed in version 4.16.1: The log parameter can now be set to True.

Parameters:

  • par – The parameter to plot. This argument is only used if recalc is set to True.

  • id (str, int, or None, optional) – The data set that provides the data. If not given then all data sets with an associated model are used simultaneously.

  • otherids (list of str or int, or None, optional) – Other data sets to use in the calculation.

  • recalc (bool, optional) – The default value (False) means that the results from the last call to int_proj (or get_int_proj) are returned, ignoring all other parameter values. Otherwise, the statistic curve is re-calculated, but not plotted.

  • fast (bool, optional) – 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.

  • min (number, optional) – The minimum parameter value for the calculation. The default value of None means that the limit is calculated from the covariance, using the fac value.

  • max (number, optional) – The maximum parameter value for the calculation. The default value of None means that the limit is calculated from the covariance, using the fac value.

  • nloop (int, optional) – The number of steps to use. This is used when delv is set to None.

  • delv (number, optional) – The step size for the parameter. Setting this overrides the nloop parameter. The default is None.

  • fac (number, optional) – When min or max is not given, multiply the covariance of the parameter by this value to calculate the limit (which is then added or subtracted to the parameter value, as required).

  • log (bool, optional) – Should the step size be logarithmically spaced? The default (False) is to use a linear grid.

  • numcores (optional) – The number of CPU cores to use. The default is to use all the cores on the machine.

Returns:

iproj – The fields of this object can be used to re-create the plot created by int_proj.

Return type:

a sherpa.plot.IntervalProjection instance

See also

conf

Estimate parameter confidence intervals using the confidence method.

covar

Estimate the confidence intervals using the covariance method.

int_proj

Calculate and plot the fit statistic versus fit parameter value.

int_unc

Calculate and plot the fit statistic versus fit parameter value.

reg_proj

Plot the statistic value as two parameters are varied.

Examples

Return the results of the int_proj run:

>>> int_proj(src.xpos)
>>> iproj = get_int_proj()
>>> min(iproj.y)
119.55942437129544

Since the recalc parameter has not been changed to True, the following will return the results for the last call to int_proj, which may not have been for the src.ypos parameter:

>>> iproj = get_int_proj(src.ypos)

Create the data without creating a plot:

>>> iproj = get_int_proj(pl.gamma, recalc=True)

Specify the range and step size for the parameter, in this case varying linearly between 12 and 14 with 51 values:

>>> iproj = get_int_proj(src.r0, id="src", min=12, max=14,
...                      nloop=51, recalc=True)