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Main window (top) after the file scan. In this case the file contain several "calibration cycles" (motor scan steps), and the GUI lists number of calibration cycles and number of events. Some more information is printed to the terminal window from which the xtcbrowser was launched.

Another window, pyana control center (bottom), also pops up, showing the contents of the file in terms of detectors / devices. You can set general parameters for pyana processing and plotting in this GuiGUI, among them how often to update plots (default is every 100 events). As

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Once you checkmark the detectors you want to display information from, another tab will pop up showing the current pyana configuration , as it will be written to file. text.

If a ControlPV is present and checked off, only a pyana_scan module will be used. All the other devices you check will be added to the input of the scan.
If no ControlPV is used, other pyana modules will be configured as appropriate to display a variety of information from the events.

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Once you start selecting devices, the pyana configuration text shows up in the GUI. If "Epics Process Variables" are checked off, another Gui appears that lists all the epics variables. Select the ones you want to display.

Press the "Write configuration to file" button once you're done. You can further edit the file by hand if you want. Once a file is written, the a "Run pyana" button appears.
If "Epics Process Variables" are checked off, another Gui appears that lists all the epics variables. Select the ones you want to displaywill appear.

Loglog plot of one array vs. another

%
%
%
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')

Loglog plot of one array vs. another

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')

channels is a 4xN array of floats, where N is the number of events. Each column corresponds to one out of four Ipimb channels.

Note that the arrays are indexed with 1,2,3,4 in MatLab and 0,1,2,3 in MatPlotLib/NumPy/Python.

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test

test

Test

array of limits from graphical input

array of limits from graphical input

In MatLab, lims is an expandable array that holds limits as set by input from mouse click on the plot (ginput).
NumPy arrays cannot be expanded, so I've declared a 4x2 array of zeros to start with, then fill it with ginput().

filter

filter

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