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Peakfinder

A set of peak-finding algorithms developed for analysis of data from LCLS pixel array detectors.

Interface

from ... import peakfinder

peaks = peakfinder(*args, **kwargs)
peaks = peakfinder(mode, data, mask=mask, **kwargs)

Input

arguments:

mode : str - selects the algorithm of the "seed" peak definition:

'Droplet' - uses keyword arguments thr, thr_high, rank, r0, dr, and peak selection parameters

'Ranker' - uses keyword arguments rank, r0, dr, nsigm, and peak selection parameters

data :

2-d numpy.array - data for processing

n-d numpy.array - (n>2) a set of 2-d arrays of data for processing. Last two indexes are used as 2-d row and column

[2-d numpy.array] - list of 2-d arrays of data for processing

keyword arguments for peak finding:

mask : numpy.array(shape,dtype=np.uint16) | None - the same structure as data - pixel mask with 0/1 for bad/good pixel

rank : int -  radial size of the region (2*rank+1 rows and columns) around pixel for peak finding.

thr : float -   threshold on pixel intensity

thr_high : float - high threshold on pixel intensity for 'Droplet' finder

 r0 : float - internal radius of the ring for evaluation of background and noise rms

dr : float - width of the ring for evaluation of background and noise rms

nsigm : float -  threshold in number of noise rms

keyword arguments for peak selection:   
 

npix_min : int- minimal number of pixels in the peak  

npix_max : int -   maximal number of pixels in the peak 

amax_thr : float -  threshold on pixel with maximal intensity   

atot_thr : float - threshold on total peak intensity  

son_min  : float   - threshold on S/N value

Output

peaks

list of peak objects, where peak is a container of attributes.

peak attributes:

    • seg - segment index beginning from 0, e.g. in CSPAD this index should be in the range (0,32)
    • row - index of row beginning from 0
    • col - index of column beginning from 0
    • npix - number of pixels accounted in the peak
    • amp_max - pixel with maximal intensity
    • amp_total - total intensity of all pixels accounted in the peak
    • row_cgrav - row coordinate of the peak evaluated as a "center of gravity" over pixels accounted in the peak using their intensities as weights
    • col_cgrav - column coordinate of the peak evaluated as a "center of gravity" over pixels accounted in the peak using their intensities as weights
    • raw_sigma - row sigma evaluated in the "center of gravity" algorithm
    • col_sigma - column sigma evaluated in the "center of gravity" algorithm
    • row_min - minimal row of the pixel group accounted in the peak
    • row_max - maximal row of the pixel group accounted in the peak
    • col_min - minimal column of the pixel group accounted in the peak
    • col_max - maximal column of the pixel group accounted in the peak
    • bkgd - background level estimated as explained in section below
    • noise - r.m.s. of the background estimated  as explained in  section below
    • son - signal over noise ratio estimated  as explained in  section below
    • pix_inds - list of peak index tuples (seg, row, col)

Peak-finding algorithms

Method peakfinder is a wrapper around a few algorithms described in this section. First argument mode switches between different peak-finding algorithms. Each 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:

  • Droplet - two-threshold peak-finding algorithm in restricted by rank region around pixel with maximal intensity. It is assumed that only pixels with intensity above thr_high are pretending to be peak candidate centers. Candidate is considered as a peak if their intensity is maximal in the (square) region of radius around them. Low threshold in the same region is used to account for contributing to peak pixels.
    Two neighbor pixels are assumed connected if have common side.
  • Ranker - define peaks in local maximums of specified rank (radius), for example rank=2 means 5x5 pixel region around central pixel. Group of connected pixels above nsigm threshold in the rank restricted region is used to form the peak.

Other stages for all algorithms are about the same.

  • background mean value and rms are estimated using pixels in the ring with internal radius r0 and width dr,
  • peak parameters are updated with background information; intensity is corrected, signal over noise (S/N) is evaluated,
  • output list of peaks is generated from the list of seed peaks using selection parameters.

References


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