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Last modified: December 2013

URL: http://cxc.harvard.edu/sherpa/ahelp/fake.html
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AHELP for CIAO 4.6 Sherpa v1

fake

Context: data

Synopsis

Simulate a generic data set with a chosen model and add noise

Syntax

fake(id=None)

Description

The fake command simulates a generic data set by evaluating a chosen source model over a blank data set created with the dataspace1d command; Poisson noise is added to the modeled data values. The dataspace1d command creates an empty data array with a user-defined grid; the user specifies the grid 'start' and 'stop' points, and optionally the grid 'step' size or 'numbins' and data set type ('dstype', default is Data1dInt).

Example 1

sherpa> dataspace1d(0.1, 10, 0.01)
sherpa> set_source(gauss1d.g1)
sherpa> fake()

The fake command evaluates a 1D Gaussian model function over an empty 1D data array created with the dataspace1d command. The modeled values are simulated with Poisson noise and stored to data set id=1. Since the 'dstype' argument was not explicitly set in the dataspace1d command, the empty array has the default data set type Data1DInt.

sherpa> show_data()
Data Set: 1
Filter: 0.1050-10.0050 x
name      = dataspace1d
xlo       = Float64[991]
xhi       = Float64[991]
y         = Float64[991]
staterror = None
syserror  = None

sherpa> show_source()
Model: 1
gauss1d.g1
   Param        Type          Value          Min          Max      Units
   -----        ----          -----          ---          ---      -----
   g1.fwhm      thawed           10  1.17549e-38  3.40282e+38           
   g1.pos       thawed            0 -3.40282e+38  3.40282e+38           
   g1.ampl      thawed            1 -3.40282e+38  3.40282e+38      

Example 2

sherpa> dataspace1d(1, 10, id=2, dstype=DataPHA)
sherpa> set_source(2, xspowerlaw.p1)
sherpa> fake(2)

Here, the fake command is used to generate a generic 1D PHA data set using a powerlaw model function. Since the 'step' argument was not explicitly set in the dataspace1d command, the empty data array is created using the default grid step size of 1. The modeled values are simulated with Poisson noise and stored to data set id=2.

Example 3

sherpa> dataspace2d([256, 300])
sherpa> set_source(beta2d.bb + const2d.cc)
sherpa> bb.xpos = 128
sherpa> bb.ypos = 128
sherpa> fake()
sherpa> image_model()

The fake command is used to generate a 2D dataset - with 256 X pixels and 300 Y pixels - using a beta2d model combined with a 2D constant (const2d).

See Also

data
copy_data, dataspace1d, dataspace2d, delete_data, fake_pha, get_axes, get_bkg_plot, get_counts, get_data, get_data_plot, get_dep, get_dims, get_error, get_quality, get_specresp, get_staterror, get_syserror, group, 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_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, get_ratio, get_resid, histogram1d, histogram2d, image_data, rebin

Last modified: December 2013
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