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Event display / xtc file browser
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.
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.
Note! This tool is under development... features are being added and new versions available often. This documentation might be slightly outdated, but the version mentioned here should work as advertised.
To run, you need to set up an offline release in your directory:
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{toc} h1. Event display / xtc file browser 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. 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{_}*. *Note\!* This tool is under development... features are being added and new versions available often. This documentation might be slightly outdated, but the version mentioned here should work as advertised. To run, you need to set up an offline release in your directory: {code} [user@psana0XXX ~] newrel ana-current myrelease [user@psana0XXX ~] cd myrelease {code} |
Add
...
the
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xtc
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browser
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package
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to
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your
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analysis
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release
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and
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"compile":
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} [user@psana0XXX myrelease] addpkg XtcEventBrowser V00-00-07 [user@psana0XXX myrelease] scons {code} |
Run
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the
...
program
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with
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the
...
command
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'xtcbrowser'
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and
...
optionally
...
give
...
the
...
input
...
xtc
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files
...
that
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you
...
want
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to
...
read
...
as
...
arguments.
...
You
...
can
...
also
...
browse
...
to
...
find
...
files
...
after
...
launching
...
the
...
browser.
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} [user@psana0XXX myrelease] xtcbrowser /reg/d/psdm/cxi/cxi80410/xtc/e55-r0581* {code} |
This
...
will
...
open
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a
...
Gui.
...
After
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opening
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file(s),
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click
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the
...
"Quick
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Scan"
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button
...
to
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scan
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the
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first
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1000
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events
...
in
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the
...
file.
...
After
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scanning,
...
a
...
new
...
window
...
will
...
pop
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up,
...
allowing
...
to
...
select
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detectors/devices
...
to
...
make
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plots
...
from.
...
The
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plots
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are
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made
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via
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pyana.
...
Configuration
...
file
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for
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pyana
...
will
...
be
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generated
...
automatically.
...
To
...
customize
...
your
...
analysis,
...
you
...
can
...
edit
...
the
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pyana
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config
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file
...
and
...
pyana
...
files
...
in
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XtcEventBrowser
...
package
...
to
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fit
...
your
...
need,
...
then
...
run
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pyana
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by
...
itself
...
(see
...
the
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pyana
...
section
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of
...
confluence).
A few things to note about the different detectors:
- CsPad: CsPad data is reconstructed in pyana_cspad.py.
...
- To
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- run
...
- this
...
- module
...
- by
...
- itself
...
- with
...
- pyana:
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Code Block
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pyana -m XtcEventBrowser/src/pyana_cspad.py <xtc files>
...
Options
...
- must
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- be
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- specified
...
- in
...
- a
...
- configuration
...
- file,
...
- or
...
- the
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- default
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- values
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- will
...
- be
...
- used:
...
.bq
image_source
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- =
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- CxiDs1-0
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- |Cspad-0
...
- #
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- specify
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- image
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- source
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draw_each_event
...
- =
...
- 0
...
- #
...
- if
...
- this
...
- is
...
- 1
...
- (True),
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- image
...
- is
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- drawn
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- for
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- each
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- event
...
dark_img_file
...
- =
...
- my_darks.npy
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- #
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- Name
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- of
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- dark-image
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- file
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- (binary
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- numpy
...
- array
...
- file)
...
- if
...
- you
...
- have
...
- one,
...
- or
...
- want
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- to
...
- make
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- one.
...
collect_darks
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- =
...
- 0
...
- #
...
- This
...
- must
...
- be
...
- set
...
- to
...
- 1
...
- if
...
- you
...
- want
...
- to
...
- create
...
- the
...
- dark-image
...
- file
...
.bq
XtcScanner
A rewrite of xtcsummary.py,
...
to
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be
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usable
...
as
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a
...
library
...
module
...
for
...
the
...
event
...
browser.
...
Can
...
be
...
run
...
just
...
like
...
the
...
script
...
above:
| Code Block |
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}XtcScanner.py <filename(s)>{code} h2. |
XtcBrowserMain.py
...
XtcBrowserMain
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is
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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
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- 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.
Main control widget. From here, select file(s) to browse, then select "Scan" or "Quick Scan" to provide a summary of the file.
Output of the Scan is currently text-only in the terminal or ipython window.
After the Scan, Checkboxes (will) allow you to select which sources you want to display data from. A button also allows you to run pyana. Here's an example output of beam energy by pyana.
Further analysis with pyana
Any serious data analysis will need more customized tools than we can provide in a GUI interface. This will require the user / analyst to program his/her own tools. Pyana is a complete framework for programming a user analysis in python. The Gui Event Browser can provide simple analysis code that can be expanded by the user. "Blank" analysis code can also be generated with Andy's codegen script (try codegen -h and codegen -p for options).
More information about pyana can be found on confluence.
Data visualization with NumPy (arrays) and MatPlotLib (plots).
Saving (and loading) a numpy array (e.g. image) to (from) a file
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*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. !app1_main.png|thumbnail,border=1! Main control widget. From here, select file(s) to browse, then select "Scan" or "Quick Scan" to provide a summary of the file. !app1_txt.png|thumbnail,border=1! Output of the Scan is currently text-only in the terminal or ipython window. !app1_beamE.png|thumbnail,border=1! After the Scan, Checkboxes (will) allow you to select which sources you want to display data from. A button also allows you to run pyana. Here's an example output of beam energy by pyana. h1. Further analysis with {{pyana}} Any serious data analysis will need more customized tools than we can provide in a GUI interface. This will require the user / analyst to program his/her own tools. Pyana is a complete framework for programming a user analysis in python. The Gui Event Browser can provide simple analysis code that can be expanded by the user. "Blank" analysis code can also be generated with Andy's {{codegen}} script (try {{codegen \-h}} and {{codegen \-p}} for options). More information about pyana can be found on confluence. h1. Data visualization with NumPy (arrays) and MatPlotLib (plots). h2. Saving (and loading) a numpy array (e.g. image) to (from) a file {code} import numpy as np # binary file .npy format np.save("filename.npy", array) array = np.load("filename.npy") # txt file np.savetxt("filename.dat", array) array = loadtxt("filename.dat") {code} h2. A comparison with MatLab. || MatLab || MatPlotLib || Comments || | {color:darkgreen}Loglog plot of one array vs. another{color} {code} |
A comparison with MatLab.
MatLab | MatPlotLib | Comments |
|---|---|---|
Loglog plot of one array vs. another
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Loglog plot of one array vs. another
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channels is a 4xN array of floats, where N is the number of events. Each column corresponds to one out of four Ipimb channels. |
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in |
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MatLab |
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and |
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0,1,2,3 |
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in |
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MatPlotLib/NumPy/Python. |
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| ]]></ac:plain-text-body></ac:structured-macro> | |
test | test | Test |
array of limits from graphical input | array of limits from graphical input |
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In MatLab, |
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|
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is |
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an |
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expandable |
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array |
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that |
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holds |
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limits |
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as |
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set |
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by |
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input |
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from |
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mouse |
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click |
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on |
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the |
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plot |
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(ginput). |
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|
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arrays |
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cannot |
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be |
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expanded, |
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so |
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I've |
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chosen |
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to |
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append |
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to |
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a |
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python |
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list |
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first, |
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then |
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fill |
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a |
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NumPy |
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array |
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for |
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the |
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usage |
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to |
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look |
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the |
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same. |
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filter | filter |
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Comment | ||
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