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, model])

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, model])

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, replot, overplot, …])

Plot the ARF associated with a data set.

plot_bkg([id, bkg_id, replot, overplot, …])

Plot the background values for a PHA data set.

plot_bkg_chisqr([id, bkg_id, replot, …])

Plot the chi-squared value for each point of the background of a PHA data set.

plot_bkg_delchi([id, bkg_id, replot, …])

Plot the ratio of residuals to error for the background of a PHA data set.

plot_bkg_fit([id, bkg_id, replot, overplot, …])

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_ratio([id, bkg_id, replot, …])

Plot the fit results, and the data/model ratio, 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, replot, …])

Plot the model for the background of a PHA data set.

plot_bkg_ratio([id, bkg_id, replot, …])

Plot the ratio of data to model values for the background of a PHA data set.

plot_bkg_resid([id, bkg_id, replot, …])

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, replot, overplot, clearwindow])

Plot the chi-squared value for each point in a data set.

plot_data([id, replot, overplot, clearwindow])

Plot the data values.

plot_delchi([id, replot, overplot, clearwindow])

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, replot, overplot, clearwindow])

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_ratio([id, replot, overplot, …])

Plot the fit results, and the ratio of data to model, for a data set.

plot_fit_resid([id, replot, overplot, …])

Plot the fit results, and the residuals, for a data set.

plot_kernel([id, replot, overplot, clearwindow])

Plot the 1D kernel applied to a data set.

plot_model([id, replot, overplot, clearwindow])

Plot the model for a data set.

plot_model_component(id[, model, replot, …])

Plot a component of the model for a data set.

plot_order([id, orders, replot, overplot, …])

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, replot, overplot, clearwindow])

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, replot, overplot, clearwindow])

Plot the ratio of data to model for a data set.

plot_resid([id, replot, overplot, clearwindow])

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, replot, overplot, …])

Plot the source expression for a data set.

plot_source_component(id[, model, replot, …])

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.