Last modified: December 2023

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AHELP for CIAO 4.16 Sherpa


Context: modeling


Create a user-defined model.


load_user_model(func, modelname, filename=None, *args, **kwargs)

func - func
modelname - str
filename - str, optional


Assign a name to a function; this name can then be used as any other name of a model component, either in a source expression - such as with `set_model` - or to change a parameter value. The `add_user_pars` function should be called after `load_user_model` to set up the parameter names and defaults.


Create a two-parameter model of the form "y = mx + c", where the intercept is the first parameter and the slope the second, set the parameter names and default values, then use it in a source expression:

>>> def func1d(pars, x, xhi=None):
...     if xhi is not None:
...         x = (x + xhi)/2
...     return x * pars[1] + pars[0]
>>> load_user_model(func1d, "myfunc")
>>> add_user_pars(myfunc, ["c", "m"], [0, 1])
>>> set_source(myfunc + gauss1d.gline)


The parameters for this function are:

Parameter Definition
func The function that evaluates the model.
modelname The name to use to refer to the model component.
filename Set this to include data from this file in the model. The file should contain two columns, and the second column is stored in the _y attribute of the model.
args Arguments for reading in the data from `filename` , if set. See `load_table` and `load_image` for more information.
kwargs Keyword arguments for reading in the data from `filename` , if set. See `load_table` and `load_image` for more information.


The `load_user_model` function is designed to make it easy to add a model, but the interface is not the same as the existing models (such as having to call both `load_user_model` and `add_user_pars` for each new instance). The `add_model` function is used to add a model as a Python class, which is more work to set up, but then acts the same way as the existing models.

The function used for the model depends on the dimensions of the data. For a 1D model, the signature is:

def func1d(pars, x, xhi=None):

where, if xhi is not None, then the dataset is binned and the x argument is the low edge of each bin. The pars argument is the parameter array - the names, defaults, and limits can be set with `add_user_pars` - and should not be changed. The return value is an array the same size as x.

For 2D models, the signature is:

def func2d(pars, x0, x1, x0hi=None, x1hi=None):

There is no way using this interface to indicate that the model is for 1D or 2D data.


See the bugs pages on the Sherpa website for an up-to-date listing of known bugs.

See Also

dataspace1d, dataspace2d, datastack, fake, get_bkg_chisqr_plot, get_bkg_delchi_plot, get_bkg_fit_plot, get_bkg_model_plot, get_bkg_plot, get_bkg_ratio_plot, get_bkg_resid_plot, get_bkg_source_plot, load_arf, load_arrays, load_ascii, load_bkg, load_bkg_arf, load_bkg_rmf, load_data, load_grouping, load_image, load_multi_arfs, load_multi_rmfs, load_pha, load_quality, load_rmf, load_staterror, load_syserror, load_table, pack_image, pack_pha, pack_table, unpack_arf, unpack_arrays, unpack_ascii, unpack_bkg, unpack_data, unpack_image, unpack_pha, unpack_rmf, unpack_table
get_default_id, list_bkg_ids, list_data_ids, list_model_ids, show_bkg_model, show_bkg_source
add_model, add_user_pars, clean, create_model_component, delete_bkg_model, delete_model, delete_model_component, get_model, get_model_autoassign_func, 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_source, get_source_component_image, get_source_component_plot, get_source_contour, get_source_image, get_source_plot, get_xsabund, get_xscosmo, get_xsxsect, get_xsxset, image_model, image_model_component, image_source, image_source_component, integrate, link, load_table_model, load_template_interpolator, load_template_model, normal_sample, reset, save_model, save_source, set_bkg_model, set_bkg_source, set_full_model, set_model, set_model_autoassign_func, set_pileup_model, set_source, set_xsabund, set_xscosmo, set_xsxsect, set_xsxset, t_sample, uniform_sample
get_cdf_plot, get_pdf_plot, get_pvalue_plot, get_pvalue_results, plot_cdf, plot_model, plot_model_component, plot_pdf, plot_pvalue, plot_scatter, plot_source, plot_source_component, plot_trace
delete_psf, load_conv
save_arrays, save_data, save_delchi, save_error, save_filter, save_grouping, save_image, save_pha, save_quality, save_resid, save_staterror, save_syserror, save_table
calc_chisqr, calc_energy_flux, calc_model_sum, calc_photon_flux, calc_source_sum, calc_stat, eqwidth
contour_model, contour_ratio, contour_resid