Content

Information from Philip

Test runs

3/6/2017 Philip: The data is in cxi11216. There is one tile. I appear to be using runs 9,
11, and 12 as pedestals for gain 0, 1, 2. Runs 18-22 have some data,
which is highly non-optimal; we have better stuff but in a painful format.

First look at 1-st event of exp=cxi11216:run=40

Philip's code in /reg/neh/home/philiph/psana/jungfrau/singleModule/makeTuple.py (copy on 2017-05-10)

Pedestal subtraction by Philip

    g0cut = 1<<14
    g1cut = 2<<14
    g2cut = 3<<14

         fG0 = frame<g0cut
         fG1 = (frame>=g0cut) & (frame<g1cut)
         fG2 = frame>=g2cut
         fGval = fG0*1 + fG1*2 + fG2*3

         frame = (frame&0x3fff).astype('int')
         frame[fG0] = frame[fG0] - ped0[fG0]
         frame[fG1] = ped1[fG1] - frame[fG1]
         frame[fG2] = ped2[fG2] - frame[fG2]

Pedestal subtracted events for runs 18, 22 from Philip:

Dark runs processing

Command to process dark runs: jungfrau_ndarr_dark_proc, e.g.

jungfrau_ndarr_dark_proc -h

jungfrau_ndarr_dark_proc -d exp=cxi11216:run=9,11,12:smd -s CxiEndstation.0:Jungfrau.0 -n 2000 -u

Help message after command: jungfrau_ndarr_dark_proc -h

> jungfrau_ndarr_dark_proc -h
Usage: 
jungfrau_ndarr_dark_proc -d <dataset> [-s <source>] [-f <file-name-template>]
       [-n <events-collect>] [-m <events-skip>] [-v <verbosity-bitword>] [-p <plot-bitword>] ...
       where -v, -S control bit-words stand for 1/2/4/8/16/32/... - ave/rms/status/mask/max/min/sta_int_lo/sta_int_hi
Ex.1:  jungfrau_ndarr_dark_proc -d exp=cxi11216:run=9,11,12:smd -s CxiEndstation.0:Jungfrau.0 -f nda-#exp-#run-#src-#evts-#type-#date-#time-#fid-#sec-#nsec.txt -n 100
Ex.2:  jungfrau_ndarr_dark_proc -d exp=cxi11216:run=9,11,12:smd -s CxiEndstation.0:Jungfrau.0 -f nda.expand -n 20 -m 0 -v 7 -p 1
Ex.3:  jungfrau_ndarr_dark_proc -d exp=cxi11216:run=9,11,12:smd -s CxiEndstation.0:Jungfrau.0 -f work/nda-#exp-#run-#src-#evts-#type.txt -n 5000 -u
Ex.4:  bsub -q psnehq -o log-%J.txt /reg/neh/home4/dubrovin/LCLS/con-jungfrau/arch/x86_64-rhel7-gcc48-opt/bin/jungfrau_ndarr_dark_proc -d exp=cxi11216:run=9,11,12:smd -s CxiEndstation.0:Jungfrau.0 -n 100 -u
Proceses jungfrau dark dataset.
Options:
  -h, --help            show this help message and exit
  -d DSNAME, --dsname=DSNAME
                        dataset name, default = exp=cxi11216:run=9,12,13:smd
  -s SOURCE, --source=SOURCE
                        input ndarray source name, default =
                        CxiEndstation.0:Jungfrau.0
  -f OFNAME, --ofname=OFNAME
                        output file name template, default =
                        nda-#exp-#run-#src-#evts-#type.txt
  -n EVENTS, --events=EVENTS
                        number of events to collect, default = 10000
  -m EVSKIP, --evskip=EVSKIP
                        number of events to skip, default = 0
  -b INTLOW, --intlow=INTLOW
                        intensity low limit, default = 1
  -t INTHIG, --inthig=INTHIG
                        intensity high limit, default = 16000
  -B RMSLOW, --rmslow=RMSLOW
                        rms low limit, default = 0.001
  -T RMSHIG, --rmshig=RMSHIG
                        rms high limit, default = 16000
  -F FRACLM, --fraclm=FRACLM
                        allowed fraction limit, default = 0.1
  -g NSIGMA, --nsigma=NSIGMA
                        number of sigma for gated average, default = 6.0
  -p PLOTIM, --plotim=PLOTIM
                        control bit-word to plot images, default = 0
  -v VERBOS, --verbos=VERBOS
                        control bit-word for verbosity, default = 255
  -S SAVEBW, --savebw=SAVEBW
                        control bit-word to save arrays, default = 255
  -D INTNLO, --intnlo=INTNLO
                        number of sigma from mean for low limit on INTENSITY,
                        default = 6.0
  -U INTNHI, --intnhi=INTNHI
                        number of sigma from mean for high limit on INTENSITY,
                        default = 6.0
  -L RMSNLO, --rmsnlo=RMSNLO
                        number of sigma from mean for low limit on RMS,
                        default = 6.0
  -H RMSNHI, --rmsnhi=RMSNHI
                        number of sigma from mean for high limit on RMS,
                        default = 6.0
  -c EVCODE, --evcode=EVCODE
                        comma separated event codes for selection as OR
                        combination, any negative code inverts selection,
                        default = None
  -C CLBDIR, --clbdir=CLBDIR
                        calib directory for deployment of calibration files,
                        default = None
  -u, --upload          upload files in calib directory, default = False

Correction

det.calib method is used to get Jungfrau calibrated data. Implementation in Detector/UtilsJungfrau.py

Apply pedestals' correction to the same data which were used for calibration of cxi11216, run 9,11,12, use "working" part of the segment:

img.shape = (512,1024)

img = img[:512,:]

Run 9, gain 0

raw:
calib:
common mode corrections in half-rows and columns for gain0 pixel as mask:

Run 11, gain 2

raw:
calib:

Run 12, gain 1

raw:
calib:

Geometry

Basic segment geometry is implemented in PSCalib.SegGeometryJungfrauV1.py

mask of edges:

Calibration constants

Example of geometry constants for 1-segment detector is in

/reg/g/psdm/detector/alignment/jungfrau/

calib/Jungfrau::CalibV1/CxiEndstation.0:Jungfrau.0/geometry/1-end.data

Detector interface

Calibration constant types

Detector interface expects to find constant in calib directory of few types:

pedestals - from dark runs processing
pixel_status - from dark runs processing
pixel_gain - supplied by Philip
pixel_offset - supplied by Philip
pixel_mask - user defined ROI mask
geometry - in /reg/g/psdm/detector/alignment/jungfrau/

Examples

Detector/examples/ex_jungfrau_det.py
Detector/examples/ex_jungfrau_raw_plot.py
Detector/examples/ex_jungfrau_ipython.py
PSCalib/src/SegGeometryStore.py 5
PSCalib/src/SegGeometryJungfrauV1.py [0,...6]

Data type and shape

raw data: shape:(1, 512, 1024) size:524288 dtype:uint16
calib data: shape:(1, 512, 1024) size:524288 dtype:float32
mask: shape:(1, 512, 1024) size:524288 dtype:uint8
status_as_mask: shape:(1, 512, 1024) size:524288 dtype:uint8
mask_geo: shape:(1, 512, 1024) size:524288 dtype:uint8
mask_calib: shape:(1, 512, 1024) size:524288 dtype:uint8

pedestals: shape:(3, 1, 512, 1024) size:1572864 dtype:float32
rms: shape:(3, 1, 512, 1024) size:1572864 dtype:float32
gain: shape:(3, 1, 512, 1024) size:1572864 dtype:float32
offset: shape:(3, 1, 512, 1024) size:1572864 dtype:float32
datast: shape:(3, 1, 512, 1024) size:1572864 dtype:uint16
status: shape:(3, 1, 512, 1024) size:1572864 dtype:uint16
coords_x: shape:(1, 512, 1024) size:524288 dtype:float64
coords_y: shape:(1, 512, 1024) size:524288 dtype:float64
area: shape:(1, 512, 1024) size:524288 dtype:float64
image (calibrated data or raw): shape:(514, 1030) size:529420 dtype:float32
image_xaxis: shape:(514,) size:514 dtype:float64
image_yaxis: shape:(1030,) size:1030 dtype:float64
common_mod: shape:(16,) size:16 dtype:float64 [ 7. 1. 100. 0. 0.]

1M Jungfrau test

Code fix

Add V2 of data and configuration objects

Dark run processing

Philip wrote:

xcsx22015 run 513.  I see gain 0 and 1.
508, 509, 510: normal, forced gain1, forced gain2 dark runs
516, 517, 518: ditto

jungfrau_ndarr_dark_proc -d exp=xcsx22015:run=503,504,505:smd -s XcsEndstation.0:Jungfrau.0 -u 
jungfrau_ndarr_dark_proc -d exp=xcsx22015:run=508,509,510:smd -s XcsEndstation.0:Jungfrau.0 -u
jungfrau_ndarr_dark_proc -d exp=xcsx22015:run=516,517,518:smd -s XcsEndstation.0:Jungfrau.0 -u

Constants of types

geometry
pedestals
pixel_max
pixel_min
pixel_rms
pixel_status

are deployed in

/reg/d/psdm/xcs/xcsx22015/calib/Jungfrau::CalibV1/XcsEndstation.0:Jungfrau.0/

Geometry is also deployed for two segments. IT NEEDS TO BE TUNED FOR SENSORS' POSITION AND ORIENTATION

Need in constants of

pixel_gain
pixel_offset

Image

python Detector/examples/ex_jungfrau_det.py 3

References

Detector interface