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Median filter

  • input imaging n-d array is treated per event as a set of 2-d frames for two lowest indexes. For each pixel of the 2-d frame median intensity is evaluated using a group of nearest pixels located in the circular region defined by the radial parameter rank (r≤rank). If input array has a number of dimensions exceeding 2 the numpy.shape of output array is reduced to 3-d.
  • Docs: self-doc, method median_filter_ndarr, code examples example01-03

Normalized fixed-shape background

  • averaged background array (evaluated in advance and retrieved once from file or from .../calib/pixel_bkgd/ by det.bkgd(run)) is subtracted from imaging array. Normalization factor is evaluated using pixel intensity in windows (parameter winds). It is assumed that windows specifies regions with dominating background and small amount of signal.
  • Docs: self-doc, method subtract_bkgdexample, code example test_01

References