Synopsis
Return the model spectrum in the form required by the spectrumfile parameter of mkinstmap
Syntax
get_instmap_weights( [id=None, fluxtype="photon"] )
Description
The get_instmap_weights() command turns the current model values into the form used for the spectrumfile parameter of the CIAO mkinstmap tool. The return value is an object with the following fields:
| Field | Value |
|---|---|
| id | The dataset identifier. |
| modelexpr | A string containing the model expression. |
| xlo | The lower edge of each bin. |
| xhi | The upper edge of each bin. |
| xmid | The mid-point of each bin. |
| weight | The weight for each bin. |
| fluxtype | "photon" or "erg"; the instrument map is in units of cm^2 count / <fluxtype>. |
Please see the Calculating Spectral Weights thread for further information on how to use this routine.
Loading the routine
The routine can be loaded into Sherpa by saying:
from sherpa_contrib.utils import *
Arguments
| Name | Default value | Description |
|---|---|---|
| id | None (which means use the value of get_default_id) | Which dataset to use. |
| fluxtype | "photon" | The units for the instrument map are cm^2 count / <fluxtype>. The valid options for this argument are "photon" (the default) or "erg". |
Examples
Example 1
sherpa> w = get_instmap_weights() sherpa> print (w) id = 1 modelexpr = (xsphabs.gal * xsmekal.clus) xlo = Float32[47] xhi = Float32[47] xmid = Float32[47] weight = Float32[47] fluxtype = photon
Get the weights for the model values of the default dataset. The weights are appropriate for creating an instrument map in units of cm^2 count / photon and will sum to 1.
The weights can be plotted with Matplotlib, here as a curve:
sherpa> import matplotlib.pyplot as plt sherpa> plt.plot(w.xmid, w.weight)
Example 2
sherpa> w = get_instmap_weights(fluxtype="erg")
In this case the weights are intended to create an instrument map in units of cm^2 count / erg and so will not sum to 1 (the individual weights will be large in this case, with values somewhere around 1e8, depending on the binning and spectral model chosen).
Bugs
See the bugs pages on the Sherpa website for an up-to-date listing of known bugs.
See Also
- confidence
- get_conf, get_conf_results, get_covar, get_covar_opt, get_covar_results, get_covariance_results, get_int_proj, get_int_unc, get_proj, get_proj_opt, get_proj_results, get_projection_results, get_reg_proj, get_reg_unc
- contrib
- estimate_weighted_expmap, get_chart_spectrum, get_marx_spectrum, plot_instmap_weights, save_instmap_weights, sherpa_utils
- data
- get_areascal, get_arf, get_arf_plot, get_axes, get_backscal, get_bkg, get_bkg_arf, get_bkg_chisqr_plot, get_bkg_delchi_plot, get_bkg_fit_plot, get_bkg_model, get_bkg_model_plot, get_bkg_plot, get_bkg_ratio_plot, get_bkg_resid_plot, get_bkg_rmf, get_bkg_scale, get_bkg_source, get_bkg_source_plot, get_coord, get_counts, get_data, get_data_contour, get_data_contour_prefs, get_data_image, get_data_plot, get_data_plot_prefs, get_dep, get_dims, get_error, get_exposure, get_grouping, get_indep, get_quality, get_rmf, get_specresp, get_staterror, get_syserror
- filtering
- get_filter
- fitting
- calc_stat_info, get_stat_info
- info
- get_default_id, list_stats
- methods
- get_draws, get_iter_method_name, get_iter_method_opt, get_method, get_method_name, get_method_opt
- modeling
- get_model, get_model_component, get_model_component_image, get_model_component_plot, get_model_plot, get_num_par, get_num_par_frozen, get_num_par_thawed, get_order_plot, get_par, get_pileup_model, get_response, get_source, get_source_component_image, get_source_component_plot, get_source_contour, get_source_image, get_source_plot, image_source
- plotting
- get_split_plot
- psfs
- get_psf, get_psf_contour, get_psf_image, get_psf_plot
- statistics
- get_chisqr_plot, get_delchi_plot, get_prior, get_sampler, get_stat, get_stat_name
- utilities
- get_analysis, get_rate
- visualization
- image_getregion