get_reg_proj
- sherpa.astro.ui.get_reg_proj(par0=None, par1=None, id: IdType | None = None, otherids: Sequence[IdType] | None = None, recalc=False, fast=True, min=None, max=None, nloop=(10, 10), delv=None, fac=4, log=(False, False), sigma=(1, 2, 3), levels=None, numcores=None)
Return the region-projection object.
This returns (and optionally calculates) the data used to display the
reg_proj
contour plot. Note that if the therecalc
parameter isFalse
(the default value) then all other parameters are ignored and the results of the lastreg_proj
call are returned.Changed in version 4.16.1: The log parameter can now be set to
True
for one or both parameters.- Parameters:
par0 – The parameters to plot on the X and Y axes, respectively. These arguments are only used if recalc is set to
True
.par1 – The parameters to plot on the X and Y axes, respectively. These arguments are 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 toreg_proj
(orget_reg_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 isFalse
.min (pair of numbers, optional) – The minimum parameter value for the calculation. The default value of
None
means that the limit is calculated from the covariance, using thefac
value.max (pair of number, optional) – The maximum parameter value for the calculation. The default value of
None
means that the limit is calculated from the covariance, using thefac
value.nloop (pair of int, optional) – The number of steps to use. This is used when
delv
is set toNone
.delv (pair of number, optional) – The step size for the parameter. Setting this overrides the
nloop
parameter. The default isNone
.fac (number, optional) – When
min
ormax
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 (pair of bool, optional) – Should the step size be logarithmically spaced? The default (
False
) is to use a linear grid.sigma (sequence of number, optional) – The levels at which to draw the contours. The units are the change in significance relative to the starting value, in units of sigma.
levels (sequence of number, optional) – The numeric values at which to draw the contours. This overrides the
sigma
parameter, if set (the default isNone
).numcores (optional) – The number of CPU cores to use. The default is to use all the cores on the machine.
- Returns:
rproj – The fields of this object can be used to re-create the plot created by
reg_proj
.- Return type:
a
sherpa.plot.RegionProjection
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.
reg_unc
Plot the statistic value as two parameters are varied.
Examples
Return the results for the
reg_proj
run for thexpos
andypos
parameters of thesrc
component, for the default data set:>>> reg_proj(src.xpos, src.ypos) >>> rproj = get_reg_proj()
Since the
recalc
parameter has not been changed toTrue
, the following will return the results for the last call toreg_proj
, which may not have been for the r0 and alpha parameters:>>> rprog = get_reg_proj(src.r0, src.alpha)
Create the data without creating a plot:
>>> rproj = get_reg_proj(pl.gamma, gal.nh, recalc=True)
Specify the range and step size for both the parameters, in this case pl.gamma should vary between 0.5 and 2.5, with gal.nh between 0.01 and 1, both with 51 values and the nH range done over a log scale:
>>> rproj = get_reg_proj(pl.gamma, gal.nh, id="src", ... min=(0.5, 0.01), max=(2.5, 1), ... nloop=(51, 51), log=(False, True), ... recalc=True)