The sherpa.astro.ui module

Since some of these are re-exports of the sherpa.ui version, should we only document the new/different ones here? That would be a maintenance burden…

Functions

add_model(modelclass[, args, kwargs])	Create a user-defined model class.
add_user_pars(modelname, parnames[, …])	Add parameter information to a user model.
calc_chisqr([id])	Calculate the per-bin chi-squared statistic.
calc_data_sum([lo, hi, id, bkg_id])	Sum up the data values over a pass band.
calc_data_sum2d([reg, id])	Sum up the data values of a 2D data set.
calc_energy_flux([lo, hi, id, bkg_id])	Integrate the unconvolved source model over a pass band.
calc_kcorr(z, obslo, obshi[, restlo, …])	Calculate the K correction for a model.
calc_model_sum([lo, hi, id, bkg_id])	Sum up the fitted model over a pass band.
calc_model_sum2d([reg, id])	Sum up the convolved model for a 2D data set.
calc_photon_flux([lo, hi, id, bkg_id])	Integrate the unconvolved source model over a pass band.
calc_source_sum([lo, hi, id, bkg_id])	Sum up the source model over a pass band.
calc_source_sum2d([reg, id])	Sum up the unconvolved model for a 2D data set.
calc_stat([id])	Calculate the fit statistic for a data set.
calc_stat_info()	Display the statistic values for the current models.
clean()	Clear out the current Sherpa session.
conf(*args)	Estimate parameter confidence intervals using the confidence method.
confidence(*args)	Estimate parameter confidence intervals using the confidence method.
contour(*args)	Create a contour plot for an image data set.
contour_data([id])	Contour the values of an image data set.
contour_fit([id])	Contour the fit to a data set.
contour_fit_resid([id, replot, overcontour])	Contour the fit and the residuals to a data set.
contour_kernel([id])	Contour the kernel applied to the model of an image data set.
contour_model([id])	Create a contour plot of the model.
contour_psf([id])	Contour the PSF applied to the model of an image data set.
contour_ratio([id])	Contour the ratio of data to model.
contour_resid([id])	Contour the residuals of the fit.
contour_source([id])	Create a contour plot of the unconvolved spatial model.
copy_data(fromid, toid)	Copy a data set, creating a new identifier.
covar(*args)	Estimate parameter confidence intervals using the covariance method.
covariance(*args)	Estimate parameter confidence intervals using the covariance method.
create_arf(elo, ehi[, specresp, exposure, …])	Create an ARF.
create_model_component([typename, name])	Create a model component.
create_rmf(rmflo, rmfhi[, startchan, e_min, …])	Create an RMF.
dataspace1d(start, stop[, step, numbins, …])	Create the independent axis for a 1D data set.
dataspace2d(dims[, id, dstype])	Create the independent axis for a 2D data set.
delete_bkg_model([id, bkg_id])	Delete the background model expression for a data set.
delete_data([id])	Delete a data set by identifier.
delete_model([id])	Delete the model expression for a data set.
delete_model_component(name)	Delete a model component.
delete_psf([id])	Delete the PSF model for a data set.
eqwidth(src, combo[, id, lo, hi, bkg_id, …])	Calculate the equivalent width of an emission or absorption line.
fake([id, method])	Simulate a data set.
fake_pha(id, arf, rmf, exposure[, backscal, …])	Simulate a PHA data set from a model.
fit([id])	Fit a model to one or more data sets.
fit_bkg([id])	Fit a model to one or more background PHA data sets.
freeze(*args)	Fix model parameters so they are not changed by a fit.
get_analysis([id])	Return the units used when fitting spectral data.
get_areascal([id, bkg_id])	Return the fractional area factor of a PHA data set.
get_arf([id, resp_id, bkg_id])	Return the ARF associated with a PHA data set.
get_arf_plot([id, resp_id])	Return the data used by plot_arf.
get_axes([id, bkg_id])	Return information about the independent axes of a data set.
get_backscal([id, bkg_id])	Return the area scaling of a PHA data set.
get_bkg([id, bkg_id])	Return the background for a PHA data set.
get_bkg_arf([id])	Return the background ARF associated with a PHA data set.
get_bkg_chisqr_plot([id, bkg_id])	Return the data used by plot_bkg_chisqr.
get_bkg_delchi_plot([id, bkg_id])	Return the data used by plot_bkg_delchi.
get_bkg_fit_plot([id, bkg_id])	Return the data used by plot_bkg_fit.
get_bkg_model([id, bkg_id])	Return the model expression for the background of a PHA data set.
get_bkg_model_plot([id, bkg_id])	Return the data used by plot_bkg_model.
get_bkg_plot([id, bkg_id])	Return the data used by plot_bkg.
get_bkg_ratio_plot([id, bkg_id])	Return the data used by plot_bkg_ratio.
get_bkg_resid_plot([id, bkg_id])	Return the data used by plot_bkg_resid.
get_bkg_rmf([id])	Return the background RMF associated with a PHA data set.
get_bkg_scale([id])	Return the background scaling factor for a PHA data set.
get_bkg_source([id, bkg_id])	Return the model expression for the background of a PHA data set.
get_bkg_source_plot([id, lo, hi, bkg_id])	Return the data used by plot_bkg_source.
get_cdf_plot()	Return the data used to plot the last CDF.
get_chisqr_plot([id])	Return the data used by plot_chisqr.
get_conf()	Return the confidence-interval estimation object.
get_conf_opt([name])	Return one or all of the options for the confidence interval method.
get_conf_results()	Return the results of the last conf run.
get_confidence_results()	Return the results of the last conf run.
get_coord([id])	Get the coordinate system used for image analysis.
get_counts([id, filter, bkg_id])	Return the dependent axis of a data set.
get_covar()	Return the covariance estimation object.
get_covar_opt([name])	Return one or all of the options for the covariance method.
get_covar_results()	Return the results of the last covar run.
get_covariance_results()	Return the results of the last covar run.
get_data([id])	Return the data set by identifier.
get_data_contour([id])	Return the data used by contour_data.
get_data_contour_prefs()	Return the preferences for contour_data.
get_data_image([id])	Return the data used by image_data.
get_data_plot([id])	Return the data used by plot_data.
get_data_plot_prefs()	Return the preferences for plot_data.
get_default_id()	Return the default data set identifier.
get_delchi_plot([id])	Return the data used by plot_delchi.
get_dep([id, filter, bkg_id])	Return the dependent axis of a data set.
get_dims([id, filter])	Return the dimensions of the data set.
get_draws([id, otherids, niter, covar_matrix])	Run the pyBLoCXS MCMC algorithm.
get_energy_flux_hist([lo, hi, id, num, …])	Return the data displayed by plot_energy_flux.
get_error([id, filter, bkg_id])	Return the errors on the dependent axis of a data set.
get_exposure([id, bkg_id])	Return the exposure time of a PHA data set.
get_filter([id])	Return the filter expression for a data set.
get_fit_contour([id])	Return the data used by contour_fit.
get_fit_plot([id])	Return the data used to create the fit plot.
get_fit_results()	Return the results of the last fit.
get_functions()	Return the functions provided by Sherpa.
get_grouping([id, bkg_id])	Return the grouping array for a PHA data set.
get_indep([id, filter, bkg_id])	Return the independent axes of a data set.
get_int_proj([par, id, otherids, recalc, …])	Return the interval-projection object.
get_int_unc([par, id, otherids, recalc, …])	Return the interval-uncertainty object.
get_iter_method_name()	Return the name of the iterative fitting scheme.
get_iter_method_opt([optname])	Return one or all options for the iterative-fitting scheme.
get_kernel_contour([id])	Return the data used by contour_kernel.
get_kernel_image([id])	Return the data used by image_kernel.
get_kernel_plot([id])	Return the data used by plot_kernel.
get_method([name])	Return an optimization method.
get_method_name()	Return the name of current Sherpa optimization method.
get_method_opt([optname])	Return one or all of the options for the current optimization method.
get_model([id])	Return the model expression for a data set.
get_model_autoassign_func()	Return the method used to create model component identifiers.
get_model_component(name)	Returns a model component given its name.
get_model_component_image(id[, model])	Return the data used by image_model_component.
get_model_component_plot(id[, model])	Return the data used to create the model-component plot.
get_model_contour([id])	Return the data used by contour_model.
get_model_contour_prefs()	Return the preferences for contour_model.
get_model_image([id])	Return the data used by image_model.
get_model_pars(model)	Return the names of the parameters of a model.
get_model_plot([id])	Return the data used to create the model plot.
get_model_plot_prefs()	Return the preferences for plot_model.
get_model_type(model)	Describe a model expression.
get_num_par([id])	Return the number of parameters in a model expression.
get_num_par_frozen([id])	Return the number of frozen parameters in a model expression.
get_num_par_thawed([id])	Return the number of thawed parameters in a model expression.
get_order_plot([id, orders])	Return the data used by plot_order.
get_par(par)	Return a parameter of a model component.
get_pdf_plot()	Return the data used to plot the last PDF.
get_photon_flux_hist([lo, hi, id, num, …])	Return the data displayed by plot_photon_flux.
get_pileup_model([id])	Return the pile up model for a data set.
get_prior(par)	Return the prior function for a parameter (MCMC).
get_proj()	Return the confidence-interval estimation object.
get_proj_opt([name])	Return one or all of the options for the confidence interval method.
get_proj_results()	Return the results of the last proj run.
get_projection_results()	Return the results of the last proj run.
get_psf([id])	Return the PSF model defined for a data set.
get_psf_contour([id])	Return the data used by contour_psf.
get_psf_image([id])	Return the data used by image_psf.
get_psf_plot([id])	Return the data used by plot_psf.
get_pvalue_plot([null_model, alt_model, …])	Return the data used by plot_pvalue.
get_pvalue_results()	Return the data calculated by the last plot_pvalue call.
get_quality([id, bkg_id])	Return the quality flags for a PHA data set.
get_rate([id, filter, bkg_id])	Return the count rate of a PHA data set.
get_ratio_contour([id])	Return the data used by contour_ratio.
get_ratio_image([id])	Return the data used by image_ratio.
get_ratio_plot([id])	Return the data used by plot_ratio.
get_reg_proj([par0, par1, id, otherids, …])	Return the region-projection object.
get_reg_unc([par0, par1, id, otherids, …])	Return the region-uncertainty object.
get_resid_contour([id])	Return the data used by contour_resid.
get_resid_image([id])	Return the data used by image_resid.
get_resid_plot([id])	Return the data used by plot_resid.
get_response([id, bkg_id])	Return the response information applied to a PHA data set.
get_rmf([id, resp_id, bkg_id])	Return the RMF associated with a PHA data set.
get_sampler()	Return the current MCMC sampler options.
get_sampler_name()	Return the name of the current MCMC sampler.
get_sampler_opt(opt)	Return an option of the current MCMC sampler.
get_scatter_plot()	Return the data used to plot the last scatter plot.
get_source([id])	Return the source model expression for a data set.
get_source_component_image(id[, model])	Return the data used by image_source_component.
get_source_component_plot(id[, model])	Return the data used by plot_source_component.
get_source_contour([id])	Return the data used by contour_source.
get_source_image([id])	Return the data used by image_source.
get_source_plot([id, lo, hi])	Return the data used by plot_source.
get_specresp([id, filter, bkg_id])	Return the effective area values for a PHA data set.
get_split_plot()	Return the plot attributes for displays with multiple plots.
get_stat([name])	Return the fit statisic.
get_stat_info()	Return the statistic values for the current models.
get_stat_name()	Return the name of the current fit statistic.
get_staterror([id, filter, bkg_id])	Return the statistical error on the dependent axis of a data set.
get_syserror([id, filter, bkg_id])	Return the systematic error on the dependent axis of a data set.
get_trace_plot()	Return the data used to plot the last trace.
group([id, bkg_id])	Turn on the grouping for a PHA data set.
group_adapt(id[, min, bkg_id, maxLength, …])	Adaptively group to a minimum number of counts.
group_adapt_snr(id[, min, bkg_id, …])	Adaptively group to a minimum signal-to-noise ratio.
group_bins(id[, num, bkg_id, tabStops])	Group into a fixed number of bins.
group_counts(id[, num, bkg_id, maxLength, …])	Group into a minimum number of counts per bin.
group_snr(id[, snr, bkg_id, maxLength, …])	Group into a minimum signal-to-noise ratio.
group_width(id[, num, bkg_id, tabStops])	Group into a fixed bin width.
guess([id, model, limits, values])	Estimate the parameter values and ranges given the loaded data.
ignore([lo, hi])	Exclude data from the fit.
ignore2d([val])	Exclude a spatial region from all data sets.
ignore2d_id(ids[, val])	Exclude a spatial region from a data set.
ignore2d_image([ids])	Exclude pixels using the region defined in the image viewer.
ignore_bad([id, bkg_id])	Exclude channels marked as bad in a PHA data set.
ignore_id(ids[, lo, hi])	Exclude data from the fit for a data set.
image_close()	Close the image viewer.
image_data([id, newframe, tile])	Display a data set in the image viewer.
image_deleteframes()	Delete all the frames open in the image viewer.
image_fit([id, newframe, tile, deleteframes])	Display the data, model, and residuals for a data set in the image viewer.
image_getregion([coord])	Return the region defined in the image viewer.
image_kernel([id, newframe, tile])	Display the 2D kernel for a data set in the image viewer.
image_model([id, newframe, tile])	Display the model for a data set in the image viewer.
image_model_component(id[, model, newframe, …])	Display a component of the model in the image viewer.
image_open()	Start the image viewer.
image_psf([id, newframe, tile])	Display the 2D PSF model for a data set in the image viewer.
image_ratio([id, newframe, tile])	Display the ratio (data/model) for a data set in the image viewer.
image_resid([id, newframe, tile])	Display the residuals (data - model) for a data set in the image viewer.
image_setregion(reg[, coord])	Set the region to display in the image viewer.
image_source([id, newframe, tile])	Display the source expression for a data set in the image viewer.
image_source_component(id[, model, …])	Display a component of the source expression in the image viewer.
image_xpaget(arg)	Return the result of an XPA call to the image viewer.
image_xpaset(arg[, data])	Return the result of an XPA call to the image viewer.
int_proj(par[, id, otherids, replot, fast, …])	Calculate and plot the fit statistic versus fit parameter value.
int_unc(par[, id, otherids, replot, min, …])	Calculate and plot the fit statistic versus fit parameter value.
link(par, val)	Link a parameter to a value.
list_bkg_ids([id])	List all the background identifiers for a data set.
list_data_ids()	List the identifiers for the loaded data sets.
list_functions([outfile, clobber])	Display the functions provided by Sherpa.
list_iter_methods()	List the iterative fitting schemes.
list_methods()	List the optimization methods.
list_model_components()	List the names of all the model components.
list_model_ids()	List of all the data sets with a source expression.
list_models([show])	List the available model types.
list_priors()	Return the priors set for model parameters, if any.
list_response_ids([id, bkg_id])	List all the response identifiers of a data set.
list_samplers()	List the MCMC samplers.
list_stats()	List the fit statistics.
load_arf(id[, arg, resp_id, bkg_id])	Load an ARF from a file and add it to a PHA data set.
load_arrays(id, *args)	Create a data set from array values.
load_ascii(id[, filename, ncols, colkeys, …])	Load an ASCII file as a data set.
load_ascii_with_errors(id[, filename, …])	Load an ASCII file with asymmetric errors as a data set.
load_bkg(id[, arg, use_errors, bkg_id])	Load the background from a file and add it to a PHA data set.
load_bkg_arf(id[, arg])	Load an ARF from a file and add it to the background of a PHA data set.
load_bkg_rmf(id[, arg])	Load a RMF from a file and add it to the background of a PHA data set.
load_conv(modelname, filename_or_model, …)	Load a 1D convolution model.
load_data(id[, filename])	Load a data set from a file.
load_filter(id[, filename, bkg_id, ignore, …])	Load the filter array from a file and add to a data set.
load_grouping(id[, filename, bkg_id])	Load the grouping scheme from a file and add to a PHA data set.
load_image(id[, arg, coord, dstype])	Load an image as a data set.
load_multi_arfs(id, filenames[, resp_ids])	Load multiple ARFs for a PHA data set.
load_multi_rmfs(id, filenames[, resp_ids])	Load multiple RMFs for a PHA data set.
load_pha(id[, arg, use_errors])	Load a PHA data set.
load_psf(modelname, filename_or_model, …)	Create a PSF model.
load_quality(id[, filename, bkg_id])	Load the quality array from a file and add to a PHA data set.
load_rmf(id[, arg, resp_id, bkg_id])	Load a RMF from a file and add it to a PHA data set.
load_staterror(id[, filename, bkg_id])	Load the statistical errors from a file.
load_syserror(id[, filename, bkg_id])	Load the systematic errors from a file.
load_table(id[, filename, ncols, colkeys, …])	Load a FITS binary file as a data set.
load_table_model(modelname, filename[, method])	Load tabular or image data and use it as a model component.
load_template_interpolator(name, …)	Set the template interpolation scheme.
load_template_model(modelname, templatefile)	Load a set of templates and use it as a model component.
load_user_model(func, modelname[, filename])	Create a user-defined model.
load_user_stat(statname, calc_stat_func[, …])	Create a user-defined statistic.
load_xstable_model(modelname, filename)	Load a XSPEC table model.
normal_sample([num, sigma, correlate, id, …])	Sample the fit statistic by taking the parameter values from a normal distribution.
notice([lo, hi])	Include data in the fit.
notice2d([val])	Include a spatial region of all data sets.
notice2d_id(ids[, val])	Include a spatial region of a data set.
notice2d_image([ids])	Include pixels using the region defined in the image viewer.
notice_id(ids[, lo, hi])	Include data from the fit for a data set.
pack_image([id])	Convert a data set into an image structure.
pack_pha([id])	Convert a PHA data set into a file structure.
pack_table([id])	Convert a data set into a table structure.
paramprompt([val])	Should the user be asked for the parameter values when creating a model?
plot(*args)	Create one or more plot types.
plot_arf([id, resp_id])	Plot the ARF associated with a data set.
plot_bkg([id, bkg_id])	Plot the background values for a PHA data set.
plot_bkg_chisqr([id, bkg_id])	Plot the chi-squared value for each point of the background of a PHA data set.
plot_bkg_delchi([id, bkg_id])	Plot the ratio of residuals to error for the background of a PHA data set.
plot_bkg_fit([id, bkg_id])	Plot the fit results (data, model) for the background of a PHA data set.
plot_bkg_fit_delchi([id, bkg_id, replot, …])	Plot the fit results, and the residuals, for the background of a PHA data set.
plot_bkg_fit_resid([id, bkg_id, replot, …])	Plot the fit results, and the residuals, for the background of a PHA data set.
plot_bkg_model([id, bkg_id])	Plot the model for the background of a PHA data set.
plot_bkg_ratio([id, bkg_id])	Plot the ratio of data to model values for the background of a PHA data set.
plot_bkg_resid([id, bkg_id])	Plot the residual (data-model) values for the background of a PHA data set.
plot_bkg_source([id, lo, hi, bkg_id])	Plot the model expression for the background of a PHA data set.
plot_cdf(points[, name, xlabel, replot, …])	Plot the cumulative density function of an array of values.
plot_chisqr([id])	Plot the chi-squared value for each point in a data set.
plot_data([id])	Plot the data values.
plot_delchi([id])	Plot the ratio of residuals to error for a data set.
plot_energy_flux([lo, hi, id, num, bins, …])	Display the energy flux distribution.
plot_fit([id])	Plot the fit results (data, model) for a data set.
plot_fit_delchi([id, replot, overplot, …])	Plot the fit results, and the residuals, for a data set.
plot_fit_resid([id, replot, overplot, …])	Plot the fit results, and the residuals, for a data set.
plot_kernel([id])	Plot the 1D kernel applied to a data set.
plot_model([id])	Plot the model for a data set.
plot_model_component(id[, model])	Plot a component of the model for a data set.
plot_order([id, orders])	Plot the model for a data set convolved by the given response.
plot_pdf(points[, name, xlabel, bins, …])	Plot the probability density function of an array of values.
plot_photon_flux([lo, hi, id, num, bins, …])	Display the photon flux distribution.
plot_psf([id])	Plot the 1D PSF model applied to a data set.
plot_pvalue(null_model, alt_model[, …])	Compute and plot a histogram of likelihood ratios by simulating data.
plot_ratio([id])	Plot the ratio of data to model for a data set.
plot_resid([id])	Plot the residuals (data - model) for a data set.
plot_scatter(x, y[, name, xlabel, ylabel, …])	Create a scatter plot.
plot_source([id, lo, hi])	Plot the source expression for a data set.
plot_source_component(id[, model])	Plot a component of the source expression for a data set.
plot_trace(points[, name, xlabel, replot, …])	Create a trace plot of row number versus value.
proj(*args)	Estimate parameter confidence intervals using the projection method.
projection(*args)	Estimate parameter confidence intervals using the projection method.
reg_proj(par0, par1[, id, otherids, replot, …])	Plot the statistic value as two parameters are varied.
reg_unc(par0, par1[, id, otherids, replot, …])	Plot the statistic value as two parameters are varied.
resample_data([id, niter, seed])	Resample data with asymmetric error bars.
reset([model, id])	Reset the model parameters to their default settings.
restore([filename])	Load in a Sherpa session from a file.
sample_energy_flux([lo, hi, id, num, …])	Return the energy flux distribution of a model.
sample_flux([modelcomponent, lo, hi, id, …])	Return the flux distribution of a model.
sample_photon_flux([lo, hi, id, num, …])	Return the photon flux distribution of a model.
save([filename, clobber])	Save the current Sherpa session to a file.
save_all([outfile, clobber])	Save the information about the current session to a text file.
save_arrays(filename, args[, fields, ascii, …])	Write a list of arrays to a file.
save_data(id[, filename, bkg_id, ascii, clobber])	Save the data to a file.
save_delchi(id[, filename, bkg_id, ascii, …])	Save the ratio of residuals (data-model) to error to a file.
save_error(id[, filename, bkg_id, ascii, …])	Save the errors to a file.
save_filter(id[, filename, bkg_id, ascii, …])	Save the filter array to a file.
save_grouping(id[, filename, bkg_id, ascii, …])	Save the grouping scheme to a file.
save_image(id[, filename, ascii, clobber])	Save the pixel values of a 2D data set to a file.
save_model(id[, filename, bkg_id, ascii, …])	Save the model values to a file.
save_pha(id[, filename, bkg_id, ascii, clobber])	Save a PHA data set to a file.
save_quality(id[, filename, bkg_id, ascii, …])	Save the quality array to a file.
save_resid(id[, filename, bkg_id, ascii, …])	Save the residuals (data-model) to a file.
save_source(id[, filename, bkg_id, ascii, …])	Save the model values to a file.
save_staterror(id[, filename, bkg_id, …])	Save the statistical errors to a file.
save_syserror(id[, filename, bkg_id, ascii, …])	Save the systematic errors to a file.
save_table(id[, filename, ascii, clobber])	Save a data set to a file as a table.
set_analysis(id[, quantity, type, factor])	Set the units used when fitting and displaying spectral data.
set_areascal(id[, area, bkg_id])	Change the fractional area factor of a PHA data set.
set_arf(id[, arf, resp_id, bkg_id])	Set the ARF for use by a PHA data set.
set_backscal(id[, backscale, bkg_id])	Change the area scaling of a PHA data set.
set_bkg(id[, bkg, bkg_id])	Set the background for a PHA data set.
set_bkg_full_model(id[, model, bkg_id])	Define the convolved background model expression for a PHA data set.
set_bkg_model(id[, model, bkg_id])	Set the background model expression for a PHA data set.
set_bkg_source(id[, model, bkg_id])	Set the background model expression for a PHA data set.
set_conf_opt(name, val)	Set an option for the confidence interval method.
set_coord(id[, coord])	Set the coordinate system to use for image analysis.
set_counts(id[, val, bkg_id])	Set the dependent axis of a data set.
set_covar_opt(name, val)	Set an option for the covariance method.
set_data(id[, data])	Set a data set.
set_default_id(id)	Set the default data set identifier.
set_dep(id[, val, bkg_id])	Set the dependent axis of a data set.
set_exposure(id[, exptime, bkg_id])	Change the exposure time of a PHA data set.
set_filter(id[, val, bkg_id, ignore])	Set the filter array of a data set.
set_full_model(id[, model])	Define the convolved model expression for a data set.
set_grouping(id[, val, bkg_id])	Apply a set of grouping flags to a PHA data set.
set_iter_method(meth)	Set the iterative-fitting scheme used in the fit.
set_iter_method_opt(optname, val)	Set an option for the iterative-fitting scheme.
set_method(meth)	Set the optimization method.
set_method_opt(optname, val)	Set an option for the current optimization method.
set_model(id[, model])	Set the source model expression for a data set.
set_model_autoassign_func([func])	Set the method used to create model component identifiers.
set_par(par[, val, min, max, frozen])	Set the value, limits, or behavior of a model parameter.
set_pileup_model(id[, model])	Include a model of the Chandra ACIS pile up when fitting PHA data.
set_prior(par, prior)	Set the prior function to use with a parameter.
set_proj_opt(name, val)	Set an option for the projection method.
set_psf(id[, psf])	Add a PSF model to a data set.
set_quality(id[, val, bkg_id])	Apply a set of quality flags to a PHA data set.
set_rmf(id[, rmf, resp_id, bkg_id])	Set the RMF for use by a PHA data set.
set_sampler(sampler)	Set the MCMC sampler.
set_sampler_opt(opt, value)	Set an option for the current MCMC sampler.
set_source(id[, model])	Set the source model expression for a data set.
set_stat(stat)	Set the statistical method.
set_staterror(id[, val, fractional, bkg_id])	Set the statistical errors on the dependent axis of a data set.
set_syserror(id[, val, fractional, bkg_id])	Set the systematic errors on the dependent axis of a data set.
set_xlinear([plottype])	New plots will display a linear X axis.
set_xlog([plottype])	New plots will display a logarithmically-scaled X axis.
set_ylinear([plottype])	New plots will display a linear Y axis.
set_ylog([plottype])	New plots will display a logarithmically-scaled Y axis.
show_all([id, outfile, clobber])	Report the current state of the Sherpa session.
show_bkg([id, bkg_id, outfile, clobber])	Show the details of the PHA background data sets.
show_bkg_model([id, bkg_id, outfile, clobber])	Display the background model expression used to fit a data set.
show_bkg_source([id, bkg_id, outfile, clobber])	Display the background model expression for a data set.
show_conf([outfile, clobber])	Display the results of the last conf evaluation.
show_covar([outfile, clobber])	Display the results of the last covar evaluation.
show_data([id, outfile, clobber])	Summarize the available data sets.
show_filter([id, outfile, clobber])	Show any filters applied to a data set.
show_fit([outfile, clobber])	Summarize the fit results.
show_kernel([id, outfile, clobber])	Display any kernel applied to a data set.
show_method([outfile, clobber])	Display the current optimization method and options.
show_model([id, outfile, clobber])	Display the model expression used to fit a data set.
show_proj([outfile, clobber])	Display the results of the last proj evaluation.
show_psf([id, outfile, clobber])	Display any PSF model applied to a data set.
show_source([id, outfile, clobber])	Display the source model expression for a data set.
show_stat([outfile, clobber])	Display the current fit statistic.
simulfit([id])	Fit a model to one or more data sets.
subtract([id])	Subtract the background estimate from a data set.
t_sample([num, dof, id, otherids, numcores])	Sample the fit statistic by taking the parameter values from a Student’s t-distribution.
thaw(*args)	Allow model parameters to be varied during a fit.
ungroup([id, bkg_id])	Turn off the grouping for a PHA data set.
uniform_sample([num, factor, id, otherids, …])	Sample the fit statistic by taking the parameter values from an uniform distribution.
unlink(par)	Unlink a parameter value.
unpack_arf(arg)	Create an ARF data structure.
unpack_arrays(*args)	Create a sherpa data object from arrays of data.
unpack_ascii(filename[, ncols, colkeys, …])	Unpack an ASCII file into a data structure.
unpack_bkg(arg[, use_errors])	Create a PHA data structure for a background data set.
unpack_data(filename, *args, **kwargs)	Create a sherpa data object from a file.
unpack_image(arg[, coord, dstype])	Create an image data structure.
unpack_pha(arg[, use_errors])	Create a PHA data structure.
unpack_rmf(arg)	Create a RMF data structure.
unpack_table(filename[, ncols, colkeys, dstype])	Unpack a FITS binary file into a data structure.
unsubtract([id])	Undo any background subtraction for the data set.