Content

Mask

Geometry center

ix_cent, iy_cent = det.point_indexes(runnum)

879, 871 (then x and y are swapped to Cartesian system).

Equatorial mask

Mask parameters

Wedge  871  879  454  387  148  196 1 k False False
Wedge  871  879  454  387  -27   21 1 k False False

Wedge parameters

t   = pars[0]              # figure type, ex. 'Wedge'
x   = float(pars[1])       # x coordinate of the wedge center
y   = float(pars[2])       # y coordinate of the wedge center
r   = float(pars[3])       # 1-st radius of the wedge 
w   = float(pars[4])       # radial width of the wedge 
t1  = float(pars[5])       # 1-st angle
t2  = float(pars[6])       # 2-nd angle
lw  = int(pars[7])         # line width
col = str(pars[8])         # color
s   = self.dicBool[pars[9].lower()]   # isSelected boolean parameter
rem = self.dicBool[pars[10].lower()]  # isRemoved - helper parameter

Involved sensors in adopted cxif5315 geometry: 0, 1, 9,15, 16,17, 25,31

Quads numeration in cxif5315 geometry

---------
| 1 | 0 |
----+----
| 2 | 3 |
---------

Arc mask

Wedge  871  879  454   26  -174  186 1 k False False

Involved sensors in the top part of the image in adopted cxif5315 geometry: 0, (1), 7, 8, (9), 15

Equatorial and arc combined mask

Radial background subtraction

For some reason polarization correction does not work well in this experiment for entire image.

Comparison of the 2-d interpolated radial background subtraction

nbins (rad:500, phi:1)

nbins (rad:500, phi:32)

SIngle angular bin still works fine in our ROI defined by both masks.

Comparison of the pfv2 with Cheetah list of peaks

Code for comparison: cxif5315/peak-list-comp-cheetah.py

Peak lists for comparison:

peakfinder: pfv2-cxif5315-r0169-2016-03-28T15:02:47.txt
cheetah: r0169-cheetah-peaks.txt - with unknown origin...

Comparison algorithm and conditions

Use pyimgalgos.TDFileContainer for both peakfinder and cheetah

    fc_ch = TDFileContainer(fncheet, indhdr='frameNumber', objtype=TDCheetahPeakRecord) # , pbits=256)
    fc_pf = TDFileContainer(fnpeaks, indhdr='Evnum', objtype=TDPeakRecord) #, pbits=256)

Loop over all groups (frames/events) in cheetah
- Find associated peak-finder group: gr_pf = fc_pf.group(evnum-1) # accounts for -1 offset in event numeration in Cheetah and pf.
- count cases when peak-finder group does not exist (peaks not found)
- discard frames if fidelity do not match
- discard frames with more than 5 peaks
- loop over cheetah peaks
  - discard cheetah peaks outside ROI mask
  - loop over pf-peaks and check that cheetah peak can be matched with one of them by location (s, r, c)
  - if not-matched - print peak main features