fake

Context: data

Synopsis

Simulate a data set.

Syntax

fake(id: int | str | None = None, method=poisson_noise)

No return value.

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	Type information	Definition
id	int, str, or None, optional	The identifier for the data set to use. If not given then the default identifier is used, as returned by `get_default_id` .
method	callable or None, optional	If None (the default) then the data is simulated using the `poisson_noise` routine. If set, it must be a callable that takes an ndarray of the predicted values and an optional rng argument that takes a NumPy random generator, and returns an ndarray of the same size with the simulated data.

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.