diff --git a/Load.py b/Load.py
index d539553c5606c979143a0025ae32ccc0b486c2f6..d05679c50cd3b914174b5e870500e1e30f0e3427 100644
--- a/Load.py
+++ b/Load.py
@@ -116,6 +116,14 @@ mnemonics = {
"VFM_BENDERF": {'source':'SCS_KBS_VFM/MOTOR/BENDERF',
'key':'encoderPosition.value',
'dim':None},
+
+ # LASER TIMING
+ "AFS_PhaseShifter": {'source':'SCS_ILH_LAS/PHASESHIFTER/DOOCS',
+ 'key':'actualPosition.value',
+ 'dim':None},
+ "AFS_DelayLine": {'source':'SCS_ILH_LAS/MOTOR/LT3',
+ 'key':'AActualPosition.value',
+ 'dim':None},
# FFT
"scannerX": {'source':'SCS_CDIFFT_SAM/LMOTOR/SCANNERX',
@@ -192,6 +200,68 @@ mnemonics = {
'key':'digitizers.channel_1_A.raw.samples',
'dim': ['samplesId']},
+ # FastADC
+ "FastADC0peaks": {'source':'SCS_UTC1_MCP/ADC/1:channel_0.output',
+ 'key':'data.peaks',
+ 'dim':['peakId']},
+ "FastADC0raw": {'source':'SCS_UTC1_MCP/ADC/1:channel_0.output',
+ 'key':'data.rawData',
+ 'dim':['samplesId']},
+ "FastADC1peaks": {'source':'SCS_UTC1_MCP/ADC/1:channel_1.output',
+ 'key':'data.peaks',
+ 'dim':['peakId']},
+ "FastADC1raw": {'source':'SCS_UTC1_MCP/ADC/1:channel_1.output',
+ 'key':'data.rawData',
+ 'dim':['samplesId']},
+ "FastADC2peaks": {'source':'SCS_UTC1_MCP/ADC/1:channel_2.output',
+ 'key':'data.peaks',
+ 'dim':['peakId']},
+ "FastADC2raw": {'source':'SCS_UTC1_MCP/ADC/1:channel_2.output',
+ 'key':'data.rawData',
+ 'dim':['samplesId']},
+ "FastADC3peaks": {'source':'SCS_UTC1_MCP/ADC/1:channel_3.output',
+ 'key':'data.peaks',
+ 'dim':['peakId']},
+ "FastADC3raw": {'source':'SCS_UTC1_MCP/ADC/1:channel_3.output',
+ 'key':'data.rawData',
+ 'dim':['samplesId']},
+ "FastADC4peaks": {'source':'SCS_UTC1_MCP/ADC/1:channel_4.output',
+ 'key':'data.peaks',
+ 'dim':['peakId']},
+ "FastADC4raw": {'source':'SCS_UTC1_MCP/ADC/1:channel_4.output',
+ 'key':'data.rawData',
+ 'dim':['samplesId']},
+ "FastADC5peaks": {'source':'SCS_UTC1_MCP/ADC/1:channel_5.output',
+ 'key':'data.peaks',
+ 'dim':['peakId']},
+ "FastADC5raw": {'source':'SCS_UTC1_MCP/ADC/1:channel_5.output',
+ 'key':'data.rawData',
+ 'dim':['samplesId']},
+ "FastADC6peaks": {'source':'SCS_UTC1_MCP/ADC/1:channel_6.output',
+ 'key':'data.peaks',
+ 'dim':['peakId']},
+ "FastADC6raw": {'source':'SCS_UTC1_MCP/ADC/1:channel_6.output',
+ 'key':'data.rawData',
+ 'dim':['samplesId']},
+ "FastADC7peaks": {'source':'SCS_UTC1_MCP/ADC/1:channel_7.output',
+ 'key':'data.peaks',
+ 'dim':['peakId']},
+ "FastADC7raw": {'source':'SCS_UTC1_MCP/ADC/1:channel_7.output',
+ 'key':'data.rawData',
+ 'dim':['samplesId']},
+ "FastADC8peaks": {'source':'SCS_UTC1_MCP/ADC/1:channel_8.output',
+ 'key':'data.peaks',
+ 'dim':['peakId']},
+ "FastADC8raw": {'source':'SCS_UTC1_MCP/ADC/1:channel_8.output',
+ 'key':'data.rawData',
+ 'dim':['samplesId']},
+ "FastADC9peaks": {'source':'SCS_UTC1_MCP/ADC/1:channel_9.output',
+ 'key':'data.peaks',
+ 'dim':['peakId']},
+ "FastADC9raw": {'source':'SCS_UTC1_MCP/ADC/1:channel_9.output',
+ 'key':'data.rawData',
+ 'dim':['samplesId']},
+
# KARABACON
"KARABACON": {'source':'SCS_DAQ_SCAN/MDL/KARABACON',
'key': 'actualStep.value',
diff --git a/xgm.py b/xgm.py
index 5b292f64a1a03c9d5f861cf6c53fd5f12729b74c..9b62b14a332b21be5e3a4daf3388657f7c0fd935 100644
--- a/xgm.py
+++ b/xgm.py
@@ -10,6 +10,7 @@ import numpy as np
import xarray as xr
+# Machine
def pulsePatternInfo(data, plot=False):
''' display general information on the pulse patterns operated by SASE1 and SASE3.
This is useful to track changes of number of pulses or mode of operation of
@@ -114,6 +115,7 @@ def repRate(data, sase='sase3'):
return f
+# XGM
def selectSASEinXGM(data, sase='sase3', xgm='SCS_XGM', sase3First=True, npulses=None):
''' Extract SASE1- or SASE3-only XGM data.
There are various cases depending on i) the mode of operation (10 Hz
@@ -385,6 +387,7 @@ def calibrateXGMs(data, rollingWindow=200, plot=False):
return np.array([sa3_calib_factor, scs_calib_factor])
+# TIM
def mcpPeaks(data, intstart, intstop, bkgstart, bkgstop, mcp=1, t_offset=None, npulses=None):
''' Computes peak integration from raw MCP traces.
@@ -844,4 +847,93 @@ def matchXgmTimPulseId(data, use_apd=True, intstart=None, intstop=None,
dropList.append('MCP{}apd'.format(mcp))
mergeList.append(data.drop(dropList))
subset = xr.merge(mergeList, join='inner')
+ subset.attrs['run'] = data.attrs['run']
return subset
+
+# Fast ADC
+def fastAdcPeaks(data, channel, intstart, intstop, bkgstart, bkgstop, period=None, npulses=None):
+ ''' Computes peak integration from raw FastADC traces.
+
+ Inputs:
+ data: xarray Dataset containing FastADC raw traces (e.g. 'FastADC1raw')
+ channel: FastADC channel number
+ intstart: trace index of integration start
+ intstop: trace index of integration stop
+ bkgstart: trace index of background start
+ bkgstop: trace index of background stop
+ period: number of samples between two pulses. Needed if bunch
+ pattern info is not available. If None, checks the pulse
+ pattern and determine the period assuming a resolution of
+ 9.23 ns per sample which leads to 24 samples between
+ 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')
+
+ Output:
+ results: DataArray with dims trainId x max(sase3 pulses)
+
+ '''
+ keyraw = 'FastADC{}raw'.format(channel)
+ if keyraw not in data:
+ raise ValueError("Source not found: {}!".format(keyraw))
+ if npulses is None:
+ npulses = int(data['npulses_sase3'].max().values)
+ if period is None:
+ sa3 = data['sase3'].where(data['sase3']>1)
+ if npulses > 1:
+ #Calculate the number of pulses between two lasing pulses (step)
+ step = sa3.where(data['npulses_sase3']>1, drop=True)[0,:2].values
+ step = int(step[1] - step[0])
+ #multiply by elementary pulse length (221.5 ns / 9.23 ns = 24 samples)
+ period = 24 * step
+ else:
+ period = 1
+ results = xr.DataArray(np.empty((data.trainId.shape[0], npulses)), coords=data[keyraw].coords,
+ dims=['trainId', 'peakId'.format(channel)])
+ for i in range(npulses):
+ a = intstart + period*i
+ b = intstop + period*i
+ 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
+ return results
+
+
+def mergeFastAdcPeaks(data, channel, intstart, intstop, bkgstart, bkgstop,
+ period=None, npulses=None, dim='lasPulseId'):
+ ''' Calculates the peaks from Fast ADC raw traces with fastAdcPeaks()
+ and merges the results in Dataset.
+ Inputs:
+ data: xr Dataset with 'FastADC[channel]raw' traces
+ channel: Fast ADC channel
+ intstart: trace index of integration start
+ intstop: trace index of integration stop
+ bkgstart: trace index of background start
+ bkgstop: trace index of background stop
+ period: Number of samples separation between two pulses. Needed
+ if bunch pattern info is not available. If None, checks the
+ pulse pattern and determine the period assuming a resolution
+ of 9.23 ns per sample which leads to 24 samples between
+ 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')
+ dim: name of the xr dataset dimension along the peaks
+
+ '''
+ peaks = fastAdcPeaks(data, channel=channel, intstart=intstart, intstop=intstop,
+ bkgstart=bkgstart, bkgstop=bkgstop, period=period,
+ npulses=npulses)
+
+ key = 'FastADC{}peaks'.format(channel)
+ if key in data:
+ s = data.drop(key)
+ else:
+ s = data
+ peaks = peaks.rename(key).rename({'peakId':dim})
+ subset = xr.merge([s, peaks], join='inner')
+ subset.attrs['run'] = data.attrs['run']
+ return subset
+
+