This page provides examples for selected modules from Psana Module Catalog. Only the modules that are included in the standard analysis releases appear on this page.
Examples for Package ImgPixSpectra
See Psana Module Catalog.
Modules:
- ImgPixSpectra::CSPadPixSpectra
- ImgPixSpectra::MiniCSPadPixSpectra
- ImgPixSpectra::CameraPixSpectra
Auxiliary scripts
A few python scripts in ImgPixSpectra/data/
show how to process/plot the spectral array stored in the file.
PlotSpectralArrayFromFile.py
- allows to plot content of the spectral array as a 2-d plot. For example, the commandgenerates image for limited range of pixels for CSPad, MiniCSPad, or Camera, respectively:ImgPixSpectra/data/PlotSpectralArrayFromFile.py mini-cspad-pix-spectra.txt
SpectralArray.py
- provides access to the spectral array stored in the file. Theclass SpectralArray
defined in this script is used in thePlotSpectralArrayFromFile.py
.
MergeArrays.py
- sums the arrays from different files defined in the list and saves resulting array in a single file with the same shape. In this script the list of files is hardwired in theget_list_of_input_file_names()
method. The output file name,out_fname
, is also hardwired in the call tospectra_merging(out_fname)
.
A few auxiliary scripts for example are located in the directory ImgAlgos/data
:
psana.cfg
- set non-default parameters to runpsana
forImgAlgos::ImgPeakFinder
andImgAlgos::ImgPeakFilter
Thepsana
running this script saves images and peaks for event 115 in text files.PlotCameraImageFromFile.py
- Plots image and spectrum for image saved in file.PlotCameraImageAndPeaks.py
- Plots image with found peaks and spectrum.
Examples for Package ImgAlgos
See Psana Module Catalog.
Module ImgAlgos::ImgPeakFinder
See Psana Module Catalog.
- This algorithm consumes ~15 ms/event on psana0101 for full Opal1000 (1024x1024) camera image.
- Smearing algorithm use a "safety margin" which is currently set to 10 pixels (offset from each boarder of the full image size).
Image on different stages of this algorithm:
- raw image,
- image in the window with amplitudes above the
threshold_low
- few peaks at the edges were discarded by the window limits,
- image still contains many 1-photon pixels, which need to be eliminated,
- smeared image,
- raw image with found peaks (marked by the red circles)
- zoom of the previous plot.
Examples for Module ImgAlgos::CSPadArrAverage
Example of the configuration file for evaluation of pedestals:
[psana] modules = ImgAlgos.CSPadArrAverage files = <path-to-the-dark-run-file>.xtc [ImgAlgos.CSPadArrAverage] source = DetInfo(CxiDs1.0:Cspad.0) key = avefile = cspad-pedestals-ave.dat rmsfile = cspad-pedestals-rms.dat print_bits = 15 evts_stage1 = 100 evts_stage2 = 100 gate_width1 = 100 gate_width2 = 10
Example of the configuration file for evaluation of background:
[psana] modules = cspad_mod.CsPadCalib ImgAlgos.CSPadArrAverage files = <path-to-the-background-run-file>.xtc skip-events = 500 events = 1000000 [cspad_mod.CsPadCalib] inputKey = outputKey = calibrated doPedestals = yes doPixelStatus = no doCommonMode = no [ImgAlgos.CSPadArrAverage] source = DetInfo(CxiDs1.0:Cspad.0) key = calibrated avefile = cspad-background-ave.dat rmsfile = cspad-background-rms.dat print_bits = 15
Images of the CSPad arrays for averaged and rms values, respectively, in one of the CXI runs:
Examples for Module ImgAlgos::CSPadBkgdSubtract
See Psana Module Catalog.
Example of the module application
The file with the background array, bkgd_fname
, was obtained by averaging 1000 events using module CSPadArrAverage. Subtraction is done with normalization for norm_sector=0
.
Event image and pixel amplitude spectrum before and after the background subtraction are shown in plots:
Other event with better subtracted background:
Examples for Module ImgAlgos::ImgRadialCorrection
See Psana Module Catalog.
Example of the module application
Calibrated image and spectrum:
Calibrated and radial-corrected image, spectrum, and subtracted r-phi65 distribution for n_phi_bins
=65:
Calibrated and radial-corrected image, spectrum, and subtracted r-phi12 distribution for n_phi_bins
=12: