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Analysis of cxif5315
New peakfinder
New peakfinder peak_finder_v2 from class ImgAlgos.PyAlgos is used in this analysis with functionality as follows
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# initialization winds_arc = [ (s, 0, 185, 0, 388) for s in (0,1,7,8,9,15,16,17,23,24,25,31)] alg_arc = PyAlgos(windows=winds_arc, mask=mask_arc, pbits=0) alg_arc.set_peak_selection_pars(npix_min=5, npix_max=500, amax_thr=0, atot_thr=1000, son_min=6) ... # in the event loop: peaks_arc = alg_arc.peak_finder_v2(nda, thr=20, r0=5, dr=0.05) #similar for EQUatorial region: peaks_equ = alg_equ.peak_finder_v2(nda, thr=20, r0=5, dr=0.05) |
Background subtraction algorithm
Averaged n-d array for (data) cxif5315-r0169 is used as a background. Normalization between data and background is done in four rectangular windows, highlighted in the plot:
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from pyimgalgos.GlobalUtils import subtract_bkgd
# use part of segments 4 and 20 to subtr bkgd
winds_bkgd = [ (s, 10, 100, 270, 370) for s in (4,12,20,28)]
#calibration of raw data
nda = np.array(nda_raw, dtype=np.float32, copy=True)
nda -= nda_peds
nda = subtract_bkgd(nda, nda_bkgd, mask=nda_smask, winds=winds_bkgd, pbits=0)
nda *= nda_smask
det.common_mode_apply(evt, nda) |
Scripts
Data processing script uses direct access to data. Example is available since release ana-0.16.1 in
ImgAlgos/examples/ex_peakfinder_cspad.py
Results
Peak data processing script is under development. Results for ARC region:
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New peakfinder more than doubles the number of signal events in the distance distribution.
References
- class ImgAlgos.PyAlgos - collection of n-d array processing algorithms
- class Detector.PyDetector - direct access to detector data and calibration n-d arrays
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