peak_position_refinement_com#

Diffraction2D.peak_position_refinement_com(peak_array, square_size=10, lazy_result=True, show_progressbar=True)[source]#

Refines the peak position using the center of mass.

Parameters:

peak_array (Numpy or Dask array) – Object with x and y coordinates of the peak positions. Must have the same dimensions as this signal’s navigation dimensions.
square_size (int) – Even integer, sub image from which the center of mass is calculated. Default 5.
lazy_result (bool, default True) – If True, will return a LazyDiffraction2D object. If False, will compute the result and return a Diffraction2D object.
show_progressbar (bool, default True)

Returns:

output_array – Same size as the two last dimensions in data, in the form [[y0, x0], [y1, x1], …]. The peak positions themselves are stored in 2D NumPy arrays inside each position in peak_array. This is done instead of making a 4D NumPy array, since the number of found peaks can vary in each position.

Return type:

dask 2D object array

Examples

>>> s = pxm.data.dummy_data.get_cbed_signal()
>>> peak_array = s.find_peaks_lazy()
>>> refined_peak_array = s.peak_position_refinement_com(peak_array, 20)
>>> refined_peak_array_com = refined_peak_array.compute(
...     show_progressbar=False)
>>> s.add_peak_array_as_markers(refined_peak_array_com)
>>> s.plot()