The sherpa.astro.ui moduleΒΆ

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 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 fitted model for a 2D data set.
calc_photon_flux([lo, hi, id, bkg_id]) Integrate the 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 fitted 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 the confidence intervals for parameters using the confidence method.
confidence(\*args) Estimate the confidence intervals for parameters 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]) Contour the values of the model, including any PSF.
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]) Contour the values of the model, without any PSF.
copy_data(fromid, toid) Copy a data set to a new identifier.
covar(\*args) Estimate the confidence intervals for parameters using the covariance method.
covariance(\*args) Estimate the confidence intervals for parameters using the covariance method.
create_model_component([typename, name]) Create a model component.
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 by plot_fit.
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 by plot_model_component.
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 by plot_model.
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.
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 respone 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 a 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_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 the confidence intervals for parameters using the projection method.
projection(\*args) Estimate the confidence intervals for parameters 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.
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.