V3 Specifics
- background shape is evaluated in run 162 WITHOUT common mode correction
- pfv3r1 - is upgraded
- S/N statistical significance is improved by increasing number of pixels
Data processing
exp=cxif5315:run=169
nda_data = det.raw(evt) if nda_data is not None : nda = np.array(nda_data, 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
Peak finder parameters
alg_arc = PyAlgos(windows=winds_arc, mask=mask_arc, pbits=2) alg_arc.set_peak_selection_pars(npix_min=0, npix_max=1e6, amax_thr=0, atot_thr=0, son_min=6) #alg_arc.set_peak_selection_pars(npix_min=0, npix_max=1e6, amax_thr=0, atot_thr=500, son_min=6) # for v2r1 alg_equ = ... the same # in the event loop #peaks_arc = alg_arc.peak_finder_v2r1(nda, thr=30, r0=7, dr=2) #peaks_arc = alg_arc.peak_finder_v3r1(nda, rank=5, r0=7, dr=2) peaks_arc = alg_arc.peak_finder_v4r1(nda, thr_low=10, thr_high=150, rank=5, r0=7, dr=2)
Results
ARC
pfv2
pfv3
pfv4
EQU
Overview
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