Last modified: December 2020

URL: https://cxc.cfa.harvard.edu/sherpa/ahelp/fake.html
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AHELP for CIAO 4.13 Sherpa v1

fake

Context: data

Synopsis

Simulate a data set.

Syntax

fake(id=None, method=poisson_noise)

id - int or str, optional
method - func

Description

Take a data set, evaluate the model for each bin, and then use this value to create a data value from each bin. The default behavior is to use a Poisson distribution, with the model value as the expectation value of the distribution.


Examples

Example 1

Create a random realisation of the model - a constant plus gaussian line - for the range x=-5 to 5.

>>> dataspace1d(-5, 5, 0.5, dstype=Data1D)
>>> set_source(gauss1d.gline + const1d.bgnd)
>>> bgnd.c0 = 2
>>> gline.fwhm = 4
>>> gline.ampl = 5
>>> gline.pos = 1
>>> fake()
>>> plot_data()
>>> plot_model(overplot=True)

Example 2

For a 2D data set, display the simulated data, model, and residuals:

>>> dataspace2d([150, 80], id='fakeimg')
>>> set_source('fakeimg', beta2d.src + polynom2d.bg)
>>> src.xpos, src.ypos = 75, 40
>>> src.r0, src.alpha = 15, 2.3
>>> src.ellip, src.theta = 0.4, 1.32
>>> src.ampl = 100
>>> bg.c, bg.cx1, bg.cy1 = 3, 0.4, 0.3
>>> fake('fakeimg')
>>> image_fit('fakeimg')

PARAMETERS

The parameters for this function are:

Parameter Definition
id The identifier for the data set to use. If not given then the default identifier is used, as returned by `get_default_id` .
method The function used to create a random realisation of a data set.

Notes

The function for the method argument accepts a single argument, the data values, and should return an array of the same shape as the input, with the data values to use.

The function can be called on any data set, it does not need to have been created with `dataspace1d` or `dataspace2d` .

Specific data set types may have their own, specialized, version of this function.


Bugs

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

See Also

data
copy_data, dataspace1d, dataspace2d, datastack, delete_data, fake_pha, get_axes, 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, 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_quality, get_specresp, get_staterror, get_syserror, group, group_adapt, group_adapt_snr, group_bins, group_counts, group_snr, group_width, 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, set_data, set_quality, ungroup, unpack_arf, unpack_arrays, unpack_ascii, unpack_bkg, unpack_data, unpack_image, unpack_pha, unpack_rmf, unpack_table
filtering
get_filter, load_filter, set_filter
info
get_default_id, list_bkg_ids, list_data_ids, list_response_ids
modeling
add_model, add_user_pars, clean, load_table_model, load_template_interpolator, load_template_model, load_user_model, save_model, save_source
plotting
plot_data, set_xlinear, set_xlog, set_ylinear, set_ylog
saving
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
statistics
load_user_stat
utilities
calc_data_sum, calc_data_sum2d, calc_ftest, calc_kcorr, calc_mlr, calc_model_sum2d, calc_source_sum2d, get_rate
visualization
contour, contour_data, contour_ratio, histogram1d, histogram2d, image_data, rebin