...

Xtc files contain the raw data streamed from the DAQ online system, therefore they are not indexed and the events don't always line up in the "right" order. Therefore it's not straight-forward to browse (back and fourth) through an xtc file. This tool is also not a real browser, but allows a simple-to-run interface to the xtc files.

xtcbrowser

This tool is written in python, relying on PyQt4 for graphical user interface. The data processing is done via the pyana framework and visualization provided by matplotlib.

...

• CsPad: CsPad data is reconstructed in pyana_cspad.py. To run this module by itself with pyana:

  Code Block
  pyana -m XtcEventBrowser/src/pyana_cspad.py <xtc files>

  Options must be specified in a configuration file, or the default values will be used:

  Code Block
  image_source = CxiDs1-0|Cspad-0 # specify image source draw_each_event = 0 # if this is 1 (True), image is drawn for each event dark_img_file = my_darks.npy # Name of dark-image file (binary numpy array file) if you have one, or want to make one. collect_darks = 0 # This must be set to 1 if you want to create the dark-image file

XtcScanner

A rewrite of xtcsummary.py, to be usable as a library module for the event browser. Can be run just like the script above:

XtcScanner.py <filename(s)>

XtcBrowserMain.py

XtcBrowserMain is a class in the XtcEventBrowser package. It opens a GUI:

• Input xtc file name(s) via:
  • file browser
  • text input line
• Options to scan the files for contents (making use of XtcExplorer)
  • Quick scan reads only the first 1000 events (sufficient to see what detectors were in use)
  • Full scan of all files (needed to know how many events and calibration cycles were in the given run(s).
• Output from scan can be used to configure pyana. Checkboxes for each detector found.
• Run simple pyana analysis via a button
• Can be run from interactive ipython session
• (Should be able to) Return prompt to ipython to continue working on plots / redraw.
• Write pyana script for the simple analysis done by the Gui, which the user can modify to have more control and options for further analysis.

...

xtcscanner

This is a command-line interface to the XtcScanner class that makes a summary of the xtc file.

usage: xtcscanner [options] xtc-files ...

options:
  -h, --help            show this help message and exit
  -n NDATAGRAMS, --ndatagrams=NDATAGRAMS
  -v, --verbose
  -l L1_OFFSET, --l1-offset=L1_OFFSET

Further analysis with pyana

...

%
%
%
a1 = subplot(121);
loglog(channels(:,1),channels(:,2),'o')
xlabel('CH0')
ylabel('CH1')
a2 = subplot(122);
loglog(channels(:,3),channels(:,4),'o')
xlabel('CH2')
ylabel('CH3')

import matplotlib.pyplot as plt
import numpy as np

a1 = plt.subplot(221)
plt.loglog(channels[:,0],channels[:,1], 'o' )
plt.xlabel('CH0')
plt.ylabel('CH1')
a2 = plt.subplot(222)
plt.loglog(channels[:,2],channels[:,3], 'o' )
plt.xlabel('CH2')
plt.ylabel('CH3')

axes(a1)
hold on
lims(1:2,:) = ginput(2);

axes(a2)
hold on
lims(3:4,:) = ginput(2);

plt.axes(a1)
plt.hold(True)
limslista = plt.ginput(2)

plt.axes(a2)
plt.hold(True)

limslistb = plt.ginput(2)
limsa = np.array(limslista)
limsb = np.array(limslistb)

lims = np.hstack( [limsa, limsb] )

fbool1 = (channels(:,1)>min(lims(1:2,1)))&(channels(:,1)<max(lims(1:2,1)))
fbool2 = (channels(:,2)>min(lims(1:2,2)))&(channels(:,2)<max(lims(1:2,2)));
fbool = fbool1&fbool2
loglog(channels(fbool,1),channels(fbool,2),'or')

fbool3 = (channels(:,3)>min(lims(3:4,3)))&(channels(:,3)<max(lims(3:4,3)))
fbool4 = (channels(:,4)>min(lims(3:4,4)))&(channels(:,4)<max(lims(3:4,4)));
fbool = fbool3&fbool4
loglog(channels(fbool,3),channels(fbool,4),'or') 

fbools0 = (channels[:,0]>lims[:,0].min())&(channels[:,0]<lims[:,0].max())
fbools1 = (channels[:,1]>lims[:,1].min())&(channels[:,1]<lims[:,1].max())
fbools = fbools0 & fbools1

fbools2 = (channels[:,2]>lims[:,2].min())&(channels[:,2]<lims[:,2].max())
fbools3 = (channels[:,3]>lims[:,3].min())&(channels[:,3]<lims[:,3].max())
fbools = fbools2&fbools3