From 54c101515c158ff730e813365deb8e6bba8aba71 Mon Sep 17 00:00:00 2001
From: Laurent Mercadier <laurent.mercadier@xfel.eu>
Date: Tue, 10 Mar 2020 22:48:50 +0100
Subject: [PATCH] Re-add option to integrate over or take extremum of peak
---
xgm.py | 23 ++++++++++++++++++-----
1 file changed, 18 insertions(+), 5 deletions(-)
diff --git a/xgm.py b/xgm.py
index 24f2250..7289fc7 100644
--- a/xgm.py
+++ b/xgm.py
@@ -814,7 +814,8 @@ def matchXgmTimPulseId(data, use_apd=True, intstart=None, intstop=None,
# Fast ADC
-def fastAdcPeaks(data, channel, intstart, intstop, bkgstart, bkgstop, period=None, npulses=None):
+def fastAdcPeaks(data, channel, intstart, intstop, bkgstart, bkgstop,
+ period=None, npulses=None, usePeakValue=False, peakType='pos'):
''' Computes peak integration from raw FastADC traces.
Inputs:
@@ -831,6 +832,8 @@ def fastAdcPeaks(data, channel, intstart, intstop, bkgstart, bkgstop, period=Non
two bunches @ 4.5 MHz.
npulses: number of pulses. If None, takes the maximum number of
pulses according to the bunch patter (field 'npulses_sase3')
+ usePeakValue: bool, if True takes the peak value of the signal,
+ otherwise integrates over integration region.
Output:
results: DataArray with dims trainId x max(sase3 pulses)
@@ -859,11 +862,18 @@ def fastAdcPeaks(data, channel, intstart, intstop, bkgstart, bkgstop, period=Non
bkga = bkgstart + period*i
bkgb = bkgstop + period*i
bg = np.outer(np.median(data[keyraw][:,bkga:bkgb], axis=1), np.ones(b-a))
- integ = np.trapz(data[keyraw][:,a:b] - bg, axis=1)
- results[:,i] = integ
+ if usePeakValue:
+ if peakType=='pos':
+ val = np.max(data[keyraw][:,a:b] - bg, axis=1)
+ if peakType=='neg':
+ val = np.min(data[keyraw][:,a:b] - bg, axis=1)
+ else:
+ val = np.trapz(data[keyraw][:,a:b] - bg, axis=1)
+ results[:,i] = val
return results
-def autoFindFastAdcPeaks(data, channel=5, window='small', display=False, plot=False):
+def autoFindFastAdcPeaks(data, channel=5, window='small', usePeakValue=False,
+ display=False, plot=False):
''' Automatically finds peaks in channel of Fast ADC trace, a minimum width of 4
samples. The find_peaks function and determination of the peak integration
region and baseline subtraction is optimized for typical photodiode signals
@@ -873,6 +883,8 @@ def autoFindFastAdcPeaks(data, channel=5, window='small', display=False, plot=Fa
key: data key of the array of traces
window: 'small' or 'large': defines the width of the integration region
centered on the peak.
+ usePeakValue: bool, if True takes the peak value of the signal,
+ otherwise integrates over integration region.
display: bool, displays info on the pulses found
plot: bool, plots regions of integration of the first pulse in the trace
Output:
@@ -916,7 +928,8 @@ def autoFindFastAdcPeaks(data, channel=5, window='small', display=False, plot=Fa
print(f'Found {npulses} {posNeg} pulses, avg. width={w}, period={period} samples, ' +
f'rep. rate={1e6/(9.230769*period):.3f} kHz')
fAdcPeaks = fastAdcPeaks(data, channel=channel, intstart=intstart, intstop=intstop,
- bkgstart=bkgstart, bkgstop=bkgstop, period=period, npulses=npulses)
+ bkgstart=bkgstart, bkgstop=bkgstop, period=period, npulses=npulses,
+ usePeakValue=usePeakValue, peakType=posNeg[:3])
if plot:
plt.figure()
plt.plot(trace_plot, 'o-', ms=3)
--
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