Content
Introduction
In this note we describe the python
-based PyCSPadImage package which is intended to evaluate and provide access to the pixel coordinate arrays. In addition, it converts the CSPAD raw data from HDF5 file to the geometry-corrected 2-D image array. This package can be used in a stand-alone python
code.
Please note, that LCLS main-stream data analysis framework is based on C++/python package Psana. To work with CSPad images Psana has several modules which are collected in the CSPadPixCoords package. Two of these modules, CSPadImageProducer and CSPadInterpolImageProducer, are intended to produce the 2-D array with CSPAD image from raw XTC data. Precise CSPAD geometry is accounted in Psana using the calibration parameters supplied by the PSCalib package.
Package PyCSPadImage
Content
The python
-based PyCSPadImage package consists of modules:
Status |
Module |
For |
Description |
---|---|---|---|
|
|
2x1 |
defines the 2x1 section pixel coordinates |
|
|
CSPAD2x2 |
defines default CSPAD2x2 calibration parameters |
|
|
CSPAD2x2 |
provides access to the CSPAD2x2 calibration parameters |
|
|
CSPAD2x2 |
evaluates the CSPAD2x2 pixel coordinates |
|
|
CSPAD2x2 |
CSPAD2x2 examples |
|
|
CSPAD |
defines CSPAD configuration parameters |
|
|
CSPAD |
defines default calibration parameters |
|
|
CSPAD |
evaluates the center_global from other quad parametes |
|
|
CSPAD |
provides access to the CSPAD calibration parameters |
|
|
CSPAD |
evaluates the CSPAD pixel coordinates |
|
|
CSPAD |
CSPAD examples |
|
|
CSPAD |
Depricated |
|
|
Utils |
Graphical utils |
|
|
Utils |
Global methods |
|
|
Utils |
Common methods for operations with HDF5 files |
|
|
Internal |
It is used for alignment purpose |
How to get this package
Below we assume that all standard environment variable settings are done (otherwise see Analysis Workbook. Account Setup). In order to copy the PyCSPadImage package from SVN
repository and run a simple test one has to use commands:
log in to psana<XXXX> kinit cd <your-favorite-directory> newrel ana-current <your-release-directory-name> cd <your-release-directory-name> sit_setup addpkg PyCSPadImage HEAD python PyCSPadImage/src/Examples.py 1
External parameters
HDF5 data file:
fname = '/reg/d/psdm/xpp/xpptut13/hdf5/xpptut13-r0150.h5' # to test XPP data fname = '/reg/d/psdm/cxi/cxitut13/hdf5/cxitut13-r1150.h5' # to test CXI data
Path to the directory with calibration types:
path_calib = '/reg/d/psdm/CXI/cxi80410/calib/CsPad::CalibV1/CxiDs1.0:Cspad.0/' path_calib = '/reg/d/psdm/xpp/xpptut13/calib/CsPad::CalibV1/XppGon.0:Cspad.0/'
Known dataset names
dsname = '/Configure:0000/Run:0000/CalibCycle:0000/CsPad::ElementV2/CxiDs1.0:Cspad.0/data' dsname = '/Configure:0000/Run:0000/CalibCycle:0000/CsPad::ElementV2/CxiDsd.0:Cspad.0/data' dsname = '/Configure:0000/Run:0000/CalibCycle:0000/CsPad::ElementV2/XppGon.0:Cspad.0/data' dsname = '/Configure:0000/Run:0000/CalibCycle:0000/CsPad::ElementV2/XcsEndstation.0:Cspad.0/data'
Run and event number:
runnum = 628 event = 34
Import modules
import sys import os import numpy as np import PyCSPadImage.CalibPars as calp import PyCSPadImage.CSPadConfigPars as ccp import PyCSPadImage.CSPadImageProducer as cip import PyCSPadImage.CSPADPixCoords as pixcoor import PyCSPadImage.PixCoords2x1 as pixcoor2x1 import PyCSPadImage.GlobalGraphics as gg import PyCSPadImage.GlobalMethods as gm import PyCSPadImage.HDF5Methods as hm
Reconstruction of CSPAD image
CSPAD pixel coordinate arrays
Examples
Module Examples.py
contains a few examples of how to use the PyCSPadImage package.
Get and plot CSPAD image and spectrum
There are two equivalent examples defined by the methods main_example_xpp()
and main_example_cxi()
for XPP and CXI experimental data, respectively.
The essential part of these examples can be presented as:
import sys import os import CalibPars as calp import CSPadConfigPars as ccp import CSPadImageProducer as cip import GlobalGraphics as gg # For test purpose in main only import HDF5Methods as hm # For test purpose in main only #---------------------------------------------- def main_example_xpp() : print 'Start test in main_example_xpp()' path_calib = '/reg/d/psdm/xpp/xpp47712/calib/CsPad::CalibV1/XppGon.0:Cspad.0' fname, runnum = '/reg/d/psdm/xpp/xpp47712/hdf5/xpp47712-r0043.h5', 43 dsname = '/Configure:0000/Run:0000/CalibCycle:0000/CsPad::ElementV2/XppGon.0:Cspad.0/data' event = 0 print 'Load calibration parameters from', path_calib calp.calibpars.setCalibParsForPath ( run=runnum, path=path_calib ) print 'Get raw CSPad event %d from file %s \ndataset %s' % (event, fname, dsname) ds1ev = hm.getOneCSPadEventForTest( fname, dsname, event ) print 'ds1ev.shape = ',ds1ev.shape print 'Make the CSPad image from raw array' cspadimg = cip.CSPadImageProducer(rotation=0, tiltIsOn=True, mirror=False) arr = cspadimg.getCSPadImage( ds1ev ) print 'Plot CSPad image' gg.plotImage(arr,range=(0,2000),figsize=(11.6,10)) gg.move(200,100) gg.plotSpectrum(arr,range=(0,2000)) gg.move(50,50) print 'To EXIT the test click on "x" in the top-right corner of each plot window.' gg.show() #---------------------------------------------- if __name__ == "__main__" : main_example_xpp() sys.exit ( 'End of test.' )
This is working example, which can be copied, pasted in <file-name>.py file and executed.
Appropriate permission is required to access particular experimental data.
In addition to the description above, the statements
gg.plotImage(arr,range=(0,2000),figsize=(11.6,10)) gg.move(200,100) gg.plotSpectrum(arr,range=(0,2000)) gg.move(50,50) gg.show()
allow to plot the CSPAD 2-d array as image and spectrum, move graphical windows to specified position and show all graphics.
Get CSPAD pixel coordinate arrays
Here we reproduce the test method
example_of_image_built_from_pix_coordinate_array_shaped_as_data()
from the module Examples.py
.
This example shows how to get the CSPAD pixel coordinate arrays. In addition, it uses the getTestImageShapedAsData(ds1ev)
(slow) method to produce image from the pixel coordinate arrays and data and plots this image.
import sys import CalibPars as calp import CalibParsEvaluated as cpe import GlobalGraphics as gg # For test purpose in main only import HDF5Methods as hm # For test purpose in main only #---------------------------------------------- def example_of_image_built_from_pix_coordinate_array_shaped_as_data() : """Some CSPAD segments may be missing in the dataset """ fname, runnum = '/reg/d/psdm/CXI/cxi80410/hdf5/cxi80410-r0628.h5', 628 dsname = '/Configure:0000/Run:0000/CalibCycle:0000/CsPad::ElementV2/CxiDs1.0:Cspad.0/data' path_calib = '/reg/d/psdm/CXI/cxi80410/calib/CsPad::CalibV1/CxiDs1.0:Cspad.0' Range = (1000,3500) calp.calibpars.setCalibParsForPath (run=runnum, path=path_calib) #cpe.cpeval.printCalibParsEvaluated('center_global') cpe.cpeval.evaluateCSPadPixCoordinatesShapedAsData(fname,dsname,rotation=0) # At this point pixel coordinates are available and can be extracted: xpix, ypix = cpe.cpeval.getCSPadPixCoordinatesShapedAsData_pix() print 'xpix =\n', xpix # Test image from pixel coordinate and data arrays can be produced and plotted: ds1ev = hm.getOneCSPadEventForTest( fname, dsname, event=0 ) # returns array with shape=(29, 185, 388) arr = cpe.cpeval.getTestImageShapedAsData(ds1ev) gg.plotImage(arr,range=Range,figsize=(11.6,10)) gg.move(200,100) gg.show() #---------------------------------------------- if __name__ == "__main__" : example_of_image_built_from_pix_coordinate_array_shaped_as_data() sys.exit ( 'End of test.' )
Get CSPAD pixel coordinate arrays without data base.
Use class CSPadPixCoordsWODB.py
Essentialy user has to provide 4 arrays for 2x1 alignment. For example see
def main_test_cspad()
:
xc_um = 109.92 * np.array( [[ 473.38, 685.26, 155.01, 154.08, 266.81, 53.95, 583.04, 582.15], [ 989.30, 987.12, 1096.93, 884.11, 1413.16, 1414.94, 1500.83, 1288.02], [1142.59, 930.23, 1459.44, 1460.67, 1347.57, 1559.93, 1032.27, 1033.44], [ 626.78, 627.42, 516.03, 729.15, 198.28, 198.01, 115.31, 327.66]]) yc_um = 109.92 * np.array( [[1028.07, 1026.28, 1139.46, 926.91, 1456.78, 1457.35, 1539.71, 1327.89], [1180.51, 967.36, 1497.74, 1498.54, 1385.08, 1598.19, 1069.65, 1069.93], [ 664.89, 666.83, 553.60, 765.91, 237.53, 236.06, 152.17, 365.47], [ 510.38, 722.95, 193.33, 193.41, 308.04, 95.25, 625.28, 624.14]]) orient_deg = np.array( [[ 90., 90., 0., 0., 270., 270., 0., 0.], [ 0., 0., 270., 270., 180., 180., 270., 270.], [ 90., 90., 0., 0., 270., 270., 0., 0.], [ 0., 0., 270., 270., 180., 180., 270., 270.]]) tilt_deg = np.array( [[0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.]])
ALL arrays are shown here FOR TEST PURPOSE ONLY !!! and they are not consistent with any real detector. The orient_deg
is not consistent with real orientation as well...
These arrays of alignment parameters are used for initialization of the CSPadPixCoordsWODB
class object, which can be used to get X,Y-coordinate arrays as shown below:
w = CSPadPixCoordsWODB(xc_um, yc_um, orient_deg, tilt_deg) X,Y = w.get_cspad_pix_coordinate_arrays_pix ()
where X.shape = Y.shape = (4, 8, 185, 388) and obviously can be re-shaped to (32, 185, 388). Then, it is easy to produce image of coordinate arrays using numpy
2D histogramming method:
xsize = X.max() + 1 ysize = Y.max() + 1 Img, Xedges, Yedges = np.histogram2d(X.flatten(), Y.flatten(), bins=[xsize,ysize], range=[[0,xsize],[0,ysize]], normed=False, weights=None)
In order to get an image of intensity the weights array needs to be provided.
References
- CSPad image producer in Python - earlier version description.
- CSPad Alignment
- Psana CSPad Geometry
- Package CSPadPixCoords for Psana