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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

(tick)

PixCoords2x1.py

2x1

defines the 2x1 section pixel coordinates

(tick)

CSPAD2x2CalibParsDefault.py

CSPAD2x2

defines default CSPAD2x2 calibration parameters

(tick)

CSPAD2x2CalibPars.py

CSPAD2x2

provides access to the CSPAD2x2 calibration parameters

(tick)

CSPAD2x2PixCoords.py

CSPAD2x2

evaluates the CSPAD2x2 pixel coordinates

(tick)

CSPAD2x2Examples.py

CSPAD2x2

CSPAD2x2 examples

(tick)

CSPadConfigPars.py

CSPAD

defines CSPAD configuration parameters

(tick)

CalibParsDefault.py

CSPAD

defines default calibration parameters

(tick)

CSPADCalibParsEvaluated.py

CSPAD

evaluates the center_global from other quad parametes

(tick)

CalibPars.py

CSPAD

provides access to the CSPAD calibration parameters

(tick)

CSPADPixCoords.py

CSPAD

evaluates the CSPAD pixel coordinates

(tick)

Examples.py

CSPAD

CSPAD examples

(plus)

CSPadImageProducer.py

CSPAD

Depricated

(tick)

GlobalGraphics.py

Utils

Graphical utils

(tick)

GlobalMethods.py

Utils

Global methods

(tick)

HDF5Methods.py

Utils

Common methods for operations with HDF5 files

(plus)

Alignment.py

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

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