Content

Table of Contents

Data

exp=cxif5315:run=169

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V2 News

V2 is done for test of peak finders after revision r1.

See for detaildetails

Hit/Peak Finding Details - description of algorithms
ImgAlgos.PyAlgos - interface methodspeak finders API
PSAS-147 - details about revision 1

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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.

Code Block

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

Raw n-d array pre-processing before peak-finders

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Summary of peak selection parameters

peak finder specific parameters for seed peak finding

v2: thr=30
v3: rank=5
v4: thr_low=10, thr_high=150, rank=5

use the same parameters for S/N calculation

r0=6, dr=0.5

peak selection in the list

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

Code Block

from pyimgalgos.RadialBkgd  import RadialBkgd, polarization_factor

nda_bkgd  = det.bkgd(runnum) # pre-defined n-d array with averaged background from calib/.../pixel_bkgd/...
nda_smask = det.mask(runnum, calib=False, status=True, edges=True, central=True, unbond=True, unbondnbrs=True)

 
mask_bkgd = nda_smask # * mask_winds_tot
rb = RadialBkgd(Xarr, Yarr, mask=mask_bkgd, radedges=(5200, 80000), nradbins=200, nphibins=1)
pf = polarization_factor(rb.pixel_rad(), rb.pixel_phi(), DIST_STOD)

    # in the event loop:
    nda_data = det.raw(evt)
    if nda_data is not None :

...

Code Block

from pyimgalgos.RadialBkgd  import RadialBkgd, polarization_factor


nda_smask = det.mask(runnum, calib=False, status=True, edges=True, central=True, unbond=True, unbondnbrs=True)

mask_bkgd = nda_smask # * mask_winds_tot
rb = RadialBkgd(Xarr, Yarr, mask=mask_bkgd, radedges=(5200, 80000), nradbins=200, nphibins=1)
pf = polarization_factor(rb.pixel_rad(), rb.pixel_phi(), DIST_STOD)

    # in the event loop:
    nda_data = det.raw(evt)
    if nda_data is not None :
        nda =  np.array(nda_data, dtype=np.float32, copy=True)
        nda -= nda_peds

        #det.common_mode_apply(evt, nda, cmpars=(1,50,50,100))
        #ndanda = subtract_bkgd  np.array(nda_data, nda_bkgd, mask=nda_smask, winds=winds_bkgd, pbits=0)

dtype=np.float32, copy=True)
        nda -= rb.subtract_bkgd(nda.flatten() * pf)
nda_peds

          nda.shape = shape_cspad#det.common_mode_apply(evt, nda, cmpars=(1,50,50,100))
        #nda = subtract_bkgd(nda, nda_bkgd, mask=nda_smask, winds=winds_bkgd, pbits=0)

        nda *= nda_smaskrb.subtract_bkgd(nda.flatten() * pf)
        nda.shape = shape_cspad

        nda *= nda_smask

Common mode correction was tested before and after background subtraction.

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.

For each peak finder we created list of peak parameters, For each peak finder we created list of peak parameters, beginning as

Code Block

collapse	true

# 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

 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

Code Block

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)
...

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EQU region

Code Block

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)
  ...

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Peak selection for fit

ARC region

Code Block

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.)

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EQU region

Code Block

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

To fit peaks we use funcy_l0 which aotomatically select solution depending on sign of parameter B.

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