Content

pnCCD overview

Large area pnCCD DAQ and Elictronics, Lothar Struder & Robert Hartmann

Development of calibration of pnCCD

2014-01-22 Meeting minutes

Hi everyone,

Here is a short summary of what I heard today for how we should start
with the pnCCD.

For pnCCD algorithms:
common-mode, pedestals, hot-pixels, quadrant rotations, hit-finders,
support in mikhail's calibManager

For pnCCD online displays: (using matplotlib for now)
shot by shot raw data
shot by shot calibrated data
projections of the above
region-of-interest
strip-charts of interesting quantities
(also display calibration values like noise-map,pedestal-map)

After this we will work on the acqiris as well (acqiris
constant-fraction algos already exist in psana).

Attached below is a 12 line python program that plots a real pnCCD
image and an x-projection (amoc0113 also has pnccd data we can look
at).  You can run it on a psana node by saving it to pnccd.py and
doing "sit_setup" and then "ipython pnccd.py".  This sort of code
should work online too (although we may have to change matplotlib
settings) as well as with calibrated images.

Display group (dan, mikhail, me) meets Thursday at 10:30.  Analysis
group (sebastian, ankush(?), phil, mikhail, me) meets Friday at 1.

See you then...

chris 

pnCCD overview

Large area pnCCD DAQ and Elictronics, Lothar Struder & Robert Hartmann

Script form Chris

Use interactive psana framework ~cpo/ipsana/shm.py:

from psana import *

events = DataSource('shmem=1_1_XCS.0').events()
src = Source('DetInfo(XcsBeamline.1:Tm6740.5)')
import matplotlib.pyplot as plt

plt.ion()
fig = plt.figure('pulnix')
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])  # x0, y0, h, w

for i in range(100):

    evt = events.next()
    frame = evt.get(Camera.FrameV1, src)

    ax.cla()
    ax.imshow(frame.data16())
    fig.canvas.draw()

Walking and talking about unlimited pipeline (processing)

CASS Heritage

Online monitor

Data for tests

On 2014-01-27 Sebastian Carron kindly provide us with data files for pnCCD experiment amoa1214:

• Dark Run: 169, rear sensors gain 1/64, front 1/1, Imaging mode                                  exp=amoa1214:run=169
• Run With Hits:  170  Low hit rate though, so you will have to use a hit finder of sorts   exp=amoa1214:run=170

...

New modules for "old-style" calibration:

...

#include "PSCalib/CalibPars.h"
#include "PSCalib/CalibParsStore.h"

// Instatiation
//Here we assume that code is working inside psana module where evt and env variables are defined through input parameters of call-back methods.
//Code below instateates calibpars object using factory static method PSCalib::CalibParsStore::Create:

std::string calib_dir = env.calibDir(); // or "/reg/d/psdm/<INS>/<experiment>/calib"
std::string  group = std::string(); // or something like "PNCCD::CalibV1";
const std::string source = "Camp.0:pnCCD.1";
const std::string key = ""; // key for raw data
Pds::Src src; env.get(source, key, &src);
PSCalib::CalibPars* calibpars = PSCalib::CalibParsStore::Create(calib_dir, group, src, PSCalib::getRunNumber(evt));

// Access methods
calibpars->printCalibPars();
const PSCalib::CalibPars::pedestals_t*    peds_data = calibpars->pedestals();
const PSCalib::CalibPars::pixel_gain_t*   gain_data = calibpars->pixel_gain();
const PSCalib::CalibPars::pixel_rms_t*    rms_data  = calibpars->pixel_rms();
const PSCalib::CalibPars::pixel_status_t* stat_data = calibpars->pixel_status();
const PSCalib::CalibPars::common_mode_t*  cmod_data = calibpars->common_mode();

Implementation of CalibParsStore

Doxy doc for CalibParsStore

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