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Content
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Data
exp=cxif5315:run=169
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V2 News
V2 is done for test of peak finders after revision r1.
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Data processing and peak finding is done in cxif5315/proc-cxif5315-r0169-data-pfvn-2016-04-19.py
Peak selection parameters
- selection parameters were set with as minimal number of parameters as possible.
- selection parameters of different peak finders were adjusted to get about the same yield of peaks in the file.
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from ImgAlgos.PyAlgos import PyAlgos 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=500, son_min=6) # for pfv2r1 alg_arc.set_peak_selection_pars(npix_min=0, npix_max=1e6, amax_thr=0, atot_thr=0, son_min=6) # for pfv3r1, pfv4r1 alg_equ = ... # the same # in the event loop: # run peakfinders and get list of peak records for each region #peaks_arc = alg_arc.peak_finder_v2r1(nda, thr=30, r0=6, dr=0.5) peaks_arc = alg_arc.peak_finder_v3r1(nda, rank=5, r0=6, dr=0.5) #peaks_arc = alg_arc.peak_finder_v4r1(nda, thr_low=10, thr_high=150, rank=5, r0=6, dr=0.5) #peaks_equ = alg_equ.peak_finder_v2r1(...) # The same |
Summary of peak selection parameters
peak finder specific parameters for seed peak finding
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- common: son_min=6
- v2: atot_thr=500 # to keep the same number of peaks in the list as for v3,v4
Raw n-d array pre-processing before peak-finders
- get raw data
- subtract pedestals
- subtract radial background to polarization corrected data
- apply status mask
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For unknown reason it makes image visually worse...
Peak list
In revision 1 four parameters col_min, col_max, row_min, row_max were discarded.
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# Exp Run Date Time time(sec) time(nsec) fiduc Evnum Reg Seg Row Col Npix Amax Atot rcent ccent rsigma csigma bkgd rms son imrow imcol x[um] y[um] r[um] phi[deg] cxif5315 169 2015-02-22 02:20:47 1424600447 478050876 104418 0 ARC 7 135 366 109 121.5 2327.8 134.6 365.6 2.71 2.93 -13.24 19.66 11.34 152 638 7357 46871 47445 81.08 cxif5315 169 2015-02-22 02:20:47 1424600447 478050876 104418 0 ARC 8 21 170 91 133.1 1513.3 22.3 170.5 2.41 2.92 -9.00 20.34 7.80 149 434 -15104 47246 49601 107.73 cxif5315 169 2015-02-22 02:20:47 1424600447 478050876 104418 0 ARC 8 76 240 84 113.2 1167.8 74.3 240.6 2.25 2.87 -7.49 20.67 6.17 204 361 -23143 41219 47272 119.31 cxif5315 169 2015-02-22 02:20:47 1424600447 478050876 104418 0 EQU 1 162 30 88 247.7 1687.0 160.8 29.7 2.21 1.37 9.43 26.64 6.75 574 640 7582 550 7601 4.15 cxif5315 169 2015-02-22 02:20:47 1424600447 478050876 104418 0 EQU 17 93 16 121 69.1 906.7 93.1 16.0 2.77 2.70 -5.91 11.99 6.88 552 423 -16334 2911 16592 169.89 cxif5315 169 2015-02-22 02:20:47 1424600447 486382070 104421 1 ARC 8 6 65 121 123.2 1536.9 5.7 64.5 2.90 3.13 -7.68 22.41 6.23 134 539 -3559 48867 48996 94.17 cxif5315 169 2015-02-22 02:20:47 1424600447 486382070 104421 1 ARC 8 9 20 121 97.4 2003.4 8.7 19.7 2.75 2.93 -9.76 20.46 8.90 137 584 1387 48525 48545 88.36 cxif5315 169 2015-02-22 02:20:47 1424600447 486382070 104421 1 ARC 8 19 157 111 83.1 1616.3 19.1 156.5 2.89 2.93 -8.70 16.42 9.34 147 447 -13675 47462 49393 106.07 cxif5315 169 2015-02-22 02:20:47 1424600447 486382070 104421 1 EQU 16 103 235 121 88.7 1923.3 102.9 235.0 3.18 2.88 -13.77 10.90 16.04 774 228 -37664 -21466 43351 -150.32 cxif5315 169 2015-02-22 02:20:47 1424600447 503058551 104427 3 ARC 8 6 33 121 111.8 2222.4 5.3 32.7 3.19 3.05 -7.85 27.39 7.38 134 571 -41 48858 48858 90.05 cxif5315 169 2015-02-22 02:20:47 1424600447 503058551 104427 3 ARC 8 43 195 99 120.1 1640.6 43.7 195.0 2.86 3.36 -10.60 24.00 6.87 171 406 -18188 44835 48383 112.08 cxif5315 169 2015-02-22 02:20:47 1424600447 503058551 104427 3 EQU 17 64 130 121 88.0 1342.3 64.0 129.7 3.08 2.78 -5.90 14.02 8.71 666 393 -19542 -9614 21779 -153.80 ... |
Peak list processing
For peak list processing we use script:
cxif5315/proc-cxif5315-r0169-peaks-from-file-v6.py
Peak pre-selection for histogramms
ARC region
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def procPeakDataArc(pk) : """ Process peak for ARC region; accumulate peak statistics in histogram arrays. """ #=================== # discard from all histograms except its own sp.lst_arc_atot.append(pk.atot) if pk.atot<2000 : return #=================== sp.lst_arc_amax.append(pk.amax) sp.lst_arc_npix.append(pk.npix) sp.lst_arc_r .append(pk.r) ... |
EQU region
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def procPeakDataEqu(pk) : """ Process peak for EQU region; accumulate peak data """ #=================== # discard from all histograms except its own sp.lst_equ_atot.append(pk.atot) if pk.atot<2000 : return sp.lst_equ_r_raw.append(pk.r) if pk.r<100 : return #=================== sp.lst_equ_r .append(pk.r) sp.lst_equ_amax.append(pk.amax) sp.lst_equ_npix.append(pk.npix) ... |
Peak selection for fit
ARC region
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def peakIsSelectedArc(pk) : """Apply peak selection criteria to each peak from file """ if pk.son<9 : return False if pk.amax<150 : return False if pk.atot<2000 : return False if pk.npix>500 : return False if pk.r<435 : return False if pk.r>443 : return False if pk.rms>80 : return False if pk.bkgd<-20 : return False if pk.bkgd>50 : return False return True |
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To fit peaks we use funcy_l1_v0(x, phi_deg, bet_deg, DoR=433/sp.DETD, sgnrt=-1.)
EQU region
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def peakIsSelectedEqu(pk) : """Apply peak selection criteria to each peak from file """ if pk.son<9 : return False if pk.amax<150 : return False if pk.atot<2000 : return False if pk.npix>500 : return False if pk.r<100 : return False if pk.r>454 : return False if pk.rms>80 : return False if math.fabs(pk.bkgd)>20 : return False return True |
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To fit peaks we use funcy_l0
which aotomatically select solution depending on sign of parameter B.
References
- Hit/Peak Finding Details - description of algorithms
- ImgAlgos.PyAlgos - interface methods
- PSAS-147 - details about revision 1
- Radial Background Subtraction Algorithm
Overview
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