Contents
2014-01-22 Meeting minutes
Hi everyone,
Here is a short summary of what I heard today for how we should start
with the pnCCD.
For pnCCD algorithms:
common-mode, pedestals, hot-pixels, quadrant rotations, hit-finders,
support in mikhail's calibManager
For pnCCD online displays: (using matplotlib for now)
shot by shot raw data
shot by shot calibrated data
projections of the above
region-of-interest
strip-charts of interesting quantities
(also display calibration values like noise-map,pedestal-map)
After this we will work on the acqiris as well (acqiris
constant-fraction algos already exist in psana).
Attached below is a 12 line python program that plots a real pnCCD
image and an x-projection (amoc0113 also has pnccd data we can look
at). You can run it on a psana node by saving it to pnccd.py and
doing "sit_setup" and then "ipython pnccd.py". This sort of code
should work online too (although we may have to change matplotlib
settings) as well as with calibrated images.
Display group (dan, mikhail, me) meets Thursday at 10:30. Analysis
group (sebastian, ankush(?), phil, mikhail, me) meets Friday at 1.
See you then...
chris
Script form Chris
Use interactive psana framework ~cpo/ipsana/shm.py
:
from psana import * events = DataSource('shmem=1_1_XCS.0').events() src = Source('DetInfo(XcsBeamline.1:Tm6740.5)') import matplotlib.pyplot as plt plt.ion() fig = plt.figure('pulnix') ax = fig.add_axes([0.1, 0.1, 0.8, 0.8]) # x0, y0, h, w for i in range(100): evt = events.next() frame = evt.get(Camera.FrameV1, src) ax.cla() ax.imshow(frame.data16()) fig.canvas.draw()
CASS Heritage
Online monitor
Data for tests
On 2014-01-27 Sebastian Carron kindly provide us with data files for pnCCD experiment amoa1214:
- Dark Run: 169, rear sensors gain 1/64, front 1/1, Imaging mode exp=amoa1214:run=169
- Run With Hits: 170 Low hit rate though, so you will have to use a hit finder of sorts exp=amoa1214:run=170
Calibration of pnCCD
New modules for "old-style" calibration:
- pdscalibdata/include/PnccdBaseV1.h - baseclass for pnCCD parameters, defines Segs, Rows, Cols, Size
- pdscalibdata/include/PnccdPedestalsV1.h - loads pedestals from file, returns ndarray of pedestals
- pdscalibdata/include/PnccdCommonModeV1.h - the same for common mode
- pdscalibdata/include/PnccdPixelGainV1.h - the same for pixel gain
- pdscalibdata/include/PnccdPixelStatusV1.h - the same for pixel status
- PSCalib::PnccdCalibPars - wrapper for all pnCCD types
Interface
Example can be found in PSCalib/test/ex_calib_file_finder.cpp:
// Assume that file is located in /reg/d/psdm/AMO/amotut13/calib/PNCCD::CalibV1/Camp.0:pnCCD.1/pedestals/1-end.data const std::string calibDir = "/reg/d/psdm/AMO/amotut13/calib"; const std::string groupName = "PNCCD::CalibV1"; const std::string source = "Camp.0:pnCCD.1"; unsigned long runNumber = 10; unsigned print_bits = 255; PSCalib::PnccdCalibPars *calibpars = new PSCalib::PnccdCalibPars(calibDir, groupName, source, runNumber, print_bits); calibpars->printCalibPars(); calibpars->printCalibParsStatus(); calibpars->printInputPars(); ndarray<pdscalibdata::PnccdPedestalsV1::pars_t, 3> peds = calibpars -> pedestals(); ndarray<pdscalibdata::PnccdCommonModeV1::pars_t, 1> cmod = calibpars -> common_mode(); ndarray<pdscalibdata::PnccdPixelStatusV1::pars_t, 3> stat = calibpars -> pixel_status(); ndarray<pdscalibdata::PnccdPixelGainV1::pars_t, 3> gain = calibpars -> pixel_gain();
Interface pros
Simple format for calibration files - just a text file with pre-defined number of values for each type:
973.941639 881.189675 1050.211 773.263749 899.241302 981.805836 1150.72615 993.084175 1121.15488 1029.76319 1220.14927 903.278339 1097.49944 1066.94949 1263.71044 1053.53872 1194.35915 935.320988 1317 ...
Interface drawback
Detector-dependent objects and parameters "knows" about parameters' array type and shape:
- PSCalib::PnccdCalibPars which depends on PnccdPedestalsV1, PnccdCommonModeV1, ..., PnccdBaseV1
pdscalibdata::PnccdPedestalsV1::pars_t = float
pdscalibdata::PnccdCommonModeV1::pars_t = uint16_t
pdscalibdata::PnccdPixelStatusV1::pars_t = uint16_t
pdscalibdata::PnccdPixelGainV1::pars_t = float
- const std::string groupName = "PNCCD::CalibV1"; - do we really need it ?
Other words, we need to define calibration array shape, type of parameters, and where to find it under calib directory: groupName="PNCCD::CalibV1", source="Camp.0:pnCCD.1";
How to improve interface for "new-style" calibration
- Use universal calibration object (for all detectors!):
PSCalib::CalibPars *calibpars = new PSCalib::CalibPars(calibDir, source, runNumber, print_bits);
wheresource d
efines the detector type, - Use universal (for all detectors!) modules for each calibration type:
pdscalibdata/include/DetPedestalsV1.h - loads pedestals from file, returns ndarray of pedestals
pdscalibdata/include/DetCommonModeV1.h - the same for common mode
pdscalibdata/include/DetPixelGainV1.h - the same for pixel gain
pdscalibdata/include/DetPixelStatusV1.h - the same for pixel status - Use universally (for all detectors!) pre-defined types of parameters :
pdscalibdata::DetPedestalsV1::pars_t = float
pdscalibdata::DetCommonModeV1::pars_t = uint16_t
pdscalibdata::DetPixelStatusV1::pars_t = uint16_t
pdscalibdata::DetPixelGainV1::pars_t = float
- Define the groupName="PNCCD::CalibV1" from dictionary for source="Camp.0:pnCCD.1" - this means that we will never change the groupName !
Save/retrieve ndarray type/shape from file header, for example:
# RULES: # Lines starting with # in the beginning of the file are considered as comments or pseudo-comments for metadata # Lines without # with space-separated values are used for input of parameters # Empty lines are ignored # Optional fields: # TITLE: This is a file with pedestals # DATE_TIME: 2014-01-30 10:21:23 # AUTHOR: someone # EXPERIMENT: amotut13 # DETECTOR: Camp.0:pnCCD.1 # CALIB_TYPE: pedestals # Mandatory fields to define the ndarray<TYPE,NDIMS> and its shape as unsigned shape[NDIMS] = {DIM1,DIM2,DIM3} # TYPE: float # NDIMS: 3 # DIM1: 4 # DIM2: 255 # DIM3: 255 973.941639 881.189675 1050.211 773.263749 899.241302 981.805836 1150.72615 993.084175 1121.15488 1029.76319 1220.14927 903.278339 1097.49944 1066.94949 1263.71044 1053.53872 1194.35915 935.320988 1317 ...