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peaks : dict -  dictionary ofarrays/lists - most natural order to work with a single value for many peaks

dict keywords:

• • seg : array of int - segment index, e.g. in CSPAD consisting of 32 segments this index should be in the range from 0 to 31
  • row : array of int - row of the central pixel with maximal intensity in the square region defined by rank
  • col : array of int - column of the central pixel with maximal intensity in the square region defined by rank
  • seg : array of int - segment index for data.ndim>2, e.g. in CSPAD consisting of 32 segments this index should be in the range from 0 to 31
  • npix : array of int - number of pixels accounted in the peak
  • amp_max : array of float - maximal intensity among peak pixels
  • amp_total : array of float - total intensity of pixels accounted in the peak
  • row_cgmean : array of float - "center of gravity" row coordinate evaluated for pixels accounted in the peak using their intensities as weights
  • col_cgmean : array of float - "center of gravity" column coordinate evaluated for pixels accounted in the peak using their intensities as weights
  • raw_cgrms : array of float - "center of gravity" row coordinate rms
  • col_cgrms : array of float - "center of gravity" column coordinate rms
  • base : array of float - per pixel base level mean estimated for pixels in the ring region (parameters base_r, base_dr)  around peak center
  • noise : array of float - per pixel base level rms estimated for pixels in the ring region (parameters base_r, base_dr) around peak center
  • son : array of float - signal over noise ratio estimated as amp_total / (noise * sqrt(npix))
  • peakinds : list of peak objects
peak attributes:
pixinds : array of (int,int) - ( of numpy.array(ndim=2) - list of the peak-pixel row,col) indexes for pixels accounted in the peak indexes. Shape of the array for each peak is (npix,2).
  • pixrow : array of int - row index for pixels accounted in the peak
  • pixcol : array of int - column index for pixels accounted in the peak
  peakmap : array shaped as data of int - map with pixels marked by peak numberspeak methods:

• • • row_min() : int - minimal row of the pixels accounted in the peak
    • row_max() : int - maximal row of the pixels accounted in the peak
    • col_min() : int - minimal column of the pixels accounted in the peak
    • col_max() : int - maximal column of the pixels accounted in the peak
    • other methods of data processing involving pixrow, pixcol, etc.


Peak-finding algorithms

Each peak-finding algorithm works in a few stages. First stage is a search for peak candidates or "seed" peaks and this is a most distinctive part between algorithms:

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• returned values of  amp_max and amp_total are base level corrected by subtracting base and base*npix, respectively, if do_base_sub=True.
• signal over noise son is evaluated as amp_total / (noise * sqrt(npix)),
• output dictionary of peak parameters is generated from the list of seed peaks complying with selection parameters npix_min, npix_max, amax_thr, atot_thr, son_min.

References

• Peak Finding Details
• Hit and Peak Finding Algorithms
• ImgAlgos auto-doc

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