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This page is about n-d array processing algorithms coded in ImgAlgos.PyAlgos. Algorithms are implemented on C++ and also have python callable interface using  boost/python wrapper. All examples are shown for python level interface.

Common hood

Make object and set parameters

import psana
from ImgAlgos.PyAlgos import PyAlgos 

# create object:
alg = PyAlgos(windows=winds, mask=mask, pbits=0)
# where pbits - is a print info control bit-word:
# pbits = 0   - print nothing
#       + 1   - main results, list of peaks
#       + 2   - input parameters, index matrix of pixels for S/N algorithm
#       + 128 - tracking and all details in class PyAlgos.py
#       + 256 - tracking and all details in class AlgArrProc
#       + 512 - tracking and all details in class AlgImgProc

# set peak-selector parameters:
alg.set_peak_selection_pars(npix_min=5, npix_max=5000, amax_thr=0, atot_thr=0, son_min=10)

Define ROI using windows and/or mask

# List of windows
winds = None # entire size of all segments will be used for peak finding
winds = (( 0, 0, 185, 0, 388),              ( 1, 20,160, 30,300),              ( 7, 0, 185, 0, 388))

# Mask
mask = None                   # (default) all pixels in windows will be used for peak finding
mask = det.mask()             # see class Detector.PyDetector
mask = np.loadtxt(fname_mask) # 
mask.shape = <should be the same as shape of data n-d array>

Evaluation of the background level, rms, and S/N ratio

Matrices of pixels for r0=3 and 4 and different dr values

r0=3  dr=0.1 (4 pixels)   r0=3  dr=0.5 (12 pixels)   r0=3  dr=1 (24 pixels) 
0 0 0 0 0 0 0 0 0         0 0 0 0 0 0 0 0 0          0 0 0 0 1 0 0 0 0       
0 0 0 0 1 0 0 0 0         0 0 0 1 1 1 0 0 0          0 0 1 1 1 1 1 0 0       
0 0 0 0 0 0 0 0 0         0 0 0 0 0 0 0 0 0          0 1 0 0 0 0 0 1 0       
0 0 0 0 0 0 0 0 0         0 1 0 0 0 0 0 1 0          0 1 0 0 0 0 0 1 0       
0 1 0 0 + 0 0 1 0         0 1 0 0 + 0 0 1 0          1 1 0 0 + 0 0 1 1       
0 0 0 0 0 0 0 0 0         0 1 0 0 0 0 0 1 0          0 1 0 0 0 0 0 1 0       
0 0 0 0 0 0 0 0 0         0 0 0 0 0 0 0 0 0          0 1 0 0 0 0 0 1 0       
0 0 0 0 1 0 0 0 0         0 0 0 1 1 1 0 0 0          0 0 1 1 1 1 1 0 0       
0 0 0 0 0 0 0 0 0         0 0 0 0 0 0 0 0 0          0 0 0 0 1 0 0 0 0

r0=4  dr=0.2 (12 pixels)   r0=4  dr=0.3 (16 pixels)    r0=4  dr=0.5 (24 pixels)
0 0 0 0 0 0 0 0 0 0 0      0 0 0 0 0 0 0 0 0 0 0       0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 1 1 1 0 0 0 0      0 0 0 0 1 1 1 0 0 0 0       0 0 0 1 1 1 1 1 0 0 0
0 0 0 0 0 0 0 0 0 0 0      0 0 1 0 0 0 0 0 1 0 0       0 0 1 0 0 0 0 0 1 0 0
0 0 0 0 0 0 0 0 0 0 0      0 0 0 0 0 0 0 0 0 0 0       0 1 0 0 0 0 0 0 0 1 0
0 1 0 0 0 0 0 0 0 1 0      0 1 0 0 0 0 0 0 0 1 0       0 1 0 0 0 0 0 0 0 1 0
0 1 0 0 0 + 0 0 0 1 0      0 1 0 0 0 + 0 0 0 1 0       0 1 0 0 0 + 0 0 0 1 0
0 1 0 0 0 0 0 0 0 1 0      0 1 0 0 0 0 0 0 0 1 0       0 1 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 0      0 0 0 0 0 0 0 0 0 0 0       0 1 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 0      0 0 1 0 0 0 0 0 1 0 0       0 0 1 0 0 0 0 0 1 0 0
0 0 0 0 1 1 1 0 0 0 0      0 0 0 0 1 1 1 0 0 0 0       0 0 0 1 1 1 1 1 0 0 0
0 0 0 0 0 0 0 0 0 0 0      0 0 0 0 0 0 0 0 0 0 0       0 0 0 0 0 0 0 0 0 0 0 

 

Matrices of pixels for r0=5 and 6 and different dr values

r0=5  dr=0.05 (12 pixels)      r0=5  dr=0.5  (28 pixels)            
0 0 0 0 0 0 0 0 0 0 0 0 0      0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 1 0 0 0 0 0 0      0 0 0 0 1 1 1 1 1 0 0 0 0
0 0 0 1 0 0 0 0 0 1 0 0 0      0 0 0 1 0 0 0 0 0 1 0 0 0
0 0 1 0 0 0 0 0 0 0 1 0 0      0 0 1 0 0 0 0 0 0 0 1 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0      0 1 0 0 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 0 0 0      0 1 0 0 0 0 0 0 0 0 0 1 0
0 1 0 0 0 0 + 0 0 0 0 1 0      0 1 0 0 0 0 + 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 0 0 0      0 1 0 0 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 0 0 0      0 1 0 0 0 0 0 0 0 0 0 1 0
0 0 1 0 0 0 0 0 0 0 1 0 0      0 0 1 0 0 0 0 0 0 0 1 0 0
0 0 0 1 0 0 0 0 0 1 0 0 0      0 0 0 1 0 0 0 0 0 1 0 0 0
0 0 0 0 0 0 1 0 0 0 0 0 0      0 0 0 0 1 1 1 1 1 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0      0 0 0 0 0 0 0 0 0 0 0 0 0

r0=6  dr=0.2 (12 pixels)        r0=6  dr=0.5 (28 pixels)      
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0     0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 1 1 1 0 0 0 0 0 0     0 0 0 0 0 1 1 1 1 1 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0     0 0 0 1 0 0 0 0 0 0 0 1 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0     0 0 1 0 0 0 0 0 0 0 0 0 1 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0     0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0     0 1 0 0 0 0 0 0 0 0 0 0 0 1 0
0 1 0 0 0 0 0 0 0 0 0 0 0 1 0     0 1 0 0 0 0 0 0 0 0 0 0 0 1 0
0 1 0 0 0 0 0 + 0 0 0 0 0 1 0     0 1 0 0 0 0 0 + 0 0 0 0 0 1 0
0 1 0 0 0 0 0 0 0 0 0 0 0 1 0     0 1 0 0 0 0 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0     0 1 0 0 0 0 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0     0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0     0 0 1 0 0 0 0 0 0 0 0 0 1 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0     0 0 0 1 0 0 0 0 0 0 0 1 0 0 0
0 0 0 0 0 0 1 1 1 0 0 0 0 0 0     0 0 0 0 0 1 1 1 1 1 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0     0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 

 

Hit finders

Number of pixels above threshold

Total intensity above threshold

Peak finders

Two threshold "Droplet finder"

two-threshold peak-finding algorithm in restricted region around pixel with maximal intensity.

peak_finder_v1

peaks = alg.peak_finder_v1(nda, thr_low=10, thr_high=150, radius=5, dr=0.05)

 

 

Flood filling algorithm

define peaks for regoins of connected pixels above threshold

peak_finder_v2

peaks = alg.peak_finder_v2(nda, thr=10, r0=5, dr=0.05)

 

Local maximums search algorithm

define peaks in local maximums of specified rank (radius), for example rank=2 means 5x5 pixel region around central pixel.

peak_finder_v3

peaks = alg.peak_finder_v3(nda, rank=2, r0=5, dr=0.05)

 

  • makes a map of pixels with local maximums of requested rank for data ndarray and mask, pixel code in the map may have bits 0/1/2/4 standing for not-a-maximum / maximum-in-row / maximum-in-column / maximum-in-rectangular-region of radius=rank.
  • for each pixel with local maximal intensity in the region defined by the rank radius counts a number of pixels with intensity above zero, total positive intensity, center of gravity coordinates and rms,
  • using parameters r0(ex.=5.0), dr(ex.=0.05) evaluates background level, rms of noise, and S/N for the pixel with maximal intensity.
  • makes list of peaks which pass selector with parameters set in set_peak_selection_pars, for example
alg.set_peak_selection_pars(npix_min=5, npix_max=500, amax_thr=0, atot_thr=1000, son_min=6)

 

Demonstration for local maximum map

Test for 100x100 image with random normal distribution of intensities

Example of the map of local maximums found for rank from 1 to 5:

color coding of pixels:

  • blue=0 - not a local maximum
  • green=1 - local maximum in row
  • yellow=1+2 - local maximum in row and column
  • red=1+2+4 - local maximum in rectangular region of radius=rank.

Table for rank, associated 2-d region size, fraction of pixels recognized as local maximums for rank, and time consumption for this algorithm.

rank2-d regionfractiontime, ms
13x30.10625.4
25x50.03725.2
37x70.01795.1
49x90.01045.2
511x110.00665.2

 

References

 

 

 

 

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