Content

Accumulation of spectra for image

The Mini-CSPad image arrays (185, 388, 2) of the cxi49812 runs from 200 to 214 were processed as flattened arrays of amplitude vs pixel and stored in the 2d array: spectra (143560, 120), where

143560 = 185*388*2 is a total number of pixels,
120 is a number of bins in the image amplitude range from -20 to 100 ADC units.

Description of plots

For each run we present the set of plots:

Spectra: 120 amplitude bins * 143560 pixels (185*388*2 = 143560), amplitude range: [-20, 100] ADC units
Spectrum of all pixels
Spectrum of pixel 100000
Spectrum of pixel 10000

Plots

cxi49812-r0200, 42962 events

cxi49812-r0201, 15990 events

cxi49812-r0202, 40336 events

cxi49812-r0203, 10197 events

cxi49812-r0204, 66368 events

cxi49812-r0205, 32111 events

cxi49812-r0206, 73412 events

cxi49812-r0207, 29735 events

cxi49812-r0208, 35901 events

cxi49812-r0209, 27595 events

cxi49812-r0210, 34038 events

cxi49812-r0211, 15550 events

cxi49812-r0212, 47923 events

cxi49812-r0213, 22799 events

cxi49812-r0214, 25638 events

Sum of spectra for runs 202-207

To find the gain correction factors we sum together spectra of all runs with back-scattered photons
without fluorescense.

Additional plots

For each pixel spectrum the mean 0- and 1-photon amplitude is estimated as a weighted average over spectrum for amplitudes <20 and ? 20, respectively.
The gain is calculated as a difference between 1- and 0- photon mean amplitudes.

The gain correction factor is calculated for pixels with gain > 0 as

      gain_correction_factor(pixel) = Amplitude_mean / Amplitude(pixel)

The pixel-by-pixel product of the mean 1-photon amplitude and the gain correction factor is also shown for corss-check.

Array for gain correction

Numpy float32 array of the gain correction factors are saved in the file ~dubrovin/LCLS/PyApps/GainCalibration/cxi49812-r0203-r0207-gain-correction-factors.np
Should be shaped as (185*388*2 = 143560)