Convolution operator

class qef.operators.convolve.Convolve(resolution, model, **kws)

Bases: lmfit.model.CompositeModel

Convolution between model and resolution.

It is assumed that the resolution FWHM is energy independent. Non-symmetric energy ranges are allowed (when the range of negative values is different than that of positive values).

The convolution requires multiplication by the X-spacing to preserve normalization

eval(params=None, **kwargs)

TODO: docstring in public method.

qef.operators.convolve.convolve(model, resolution)

Convolution of resolution with model data.

It is assumed that the resolution FWHM is energy independent. We multiply by spacing \(dx\) of independent variable \(x\).

\[(model \otimes resolution)[n] = dx * \sum_m model[m] * resolution[m-n]\]

Parameters:

• model (numpy.ndarray) – model data
• resolution (numpy.ndarray) – resolution data

Returns:

Return type:

numpy.ndarray