...
Cloak |
---|
|
- Fetching the ControlPV information:
ControlPV is available from the env object, and since it only changes at the beginning of each calibration cycle, the begincalibcycle function is the appropriate place to get it: none The ControlConfig object may contain several pvControl and pvMonitor objects. In this case there's only one, but make sure the name matches anyway: none
- Fetching the IPIMB and PhaseCavity information:
All the other information that we need, is available through the evt object, and event member function is the place to get it: none Use "XppSb3Ipm-1|Ipimb-0" (a.k.a. IPM3) sum of all channels for normalization and filtering none Use "XppSb3Pim-1|Ipimb-0" (a.k.a. PIM3) channel 1 as signal none Get the phase cavity: none Compute delay time and fill histograms none
|
Image peak finding
Here are a collection of useful algorithms for image analysis: http://docs.scipy.org/doc/scipy/reference/ndimage.html![](/images/icons/linkext7.gif)
...
Panel |
---|
Edit pyana.cfg to include configuration for xppt_image_analysis, and comment out the delay_scan module: Code Block |
---|
|
[pyana]
modules = pyana_examples.xppt_image_analysis
#modules = pyana_examples.xppt_delayscan
[pyana_examples.xppt_image_analysis]
source = XppGon-0|Cspad-0
region = 127.3, 188.4, 95.1, 126.9
[pyana_examples.xppt_delayscan]
controlpv = fs2:ramp_angsft_target
ipimb_norm = XppSb3Ipm-1|Ipimb-0
ipimb_sig = XppSb3Pim-1|Ipimb-0
threshold = 0.1
outputfile = point_scan_delay.npy
|
Then run the xppt_image_analysis pyana module on xppi0112 run 55: Code Block |
---|
|
pyana -n 10 /reg/d/psdm/XPP/xppi0112/xtc/e162-r0055-s00-c00.xtc
|
*Edit pyana.cfg again and comment out the region parameter (add a semicolon ";" to the beginning of the line). Run again a single event and try to select a region by mouse clicks instead:* Code Block |
---|
|
pyana -n 1 /reg/d/psdm/XPP/xppi0112/xtc/e162-r0055-s00-c00.xtc
|
- Hit the "Zoom to rectangle" button in the matplotlib toolbar.
- Zoom in on a rectangle around the bright spot in the "Region of interest" plot to the right.
- You should now see the region marked out in the left window.
- Hit the "Zoom" button once more, to go back to normal mode.
- Click on the red rectangle in the left plot to print the region parameters and new Center of mass to screen.
|
Here are some code snippet highlights from the xppt_image_analysis.py module:
...