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Commit 5ef09113 authored by Loïc Le Guyader's avatar Loïc Le Guyader
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Merge branch 'noPPinfo' into 'master' 

No pulse pattern info case

See merge request !24
parents 838bcd6e aa19e723
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1 merge request!24No pulse pattern info case
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xgm.py
+ 62
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......@@ -114,7 +114,7 @@ def repRate(data, sase='sase3'):
return f
def selectSASEinXGM(data, sase='sase3', xgm='SCS_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
with fresh bunch, dedicated trains to one SASE, pulse on demand),
......@@ -125,6 +125,8 @@ def selectSASEinXGM(data, sase='sase3', xgm='SCS_XGM'):
data: xarray Dataset containing xgm data
sase: key of sase to select: {'sase1', 'sase3'}
xgm: key of xgm to select: {'SA3_XGM', 'SCS_XGM'}
sase3First: bool, optional. Used in case no bunch pattern was recorded
npulses: int, optional. Required in case no bunch pattern was recorded.
Output:
DataArray that has all trainIds that contain a lasing
......@@ -132,6 +134,25 @@ def selectSASEinXGM(data, sase='sase3', xgm='SCS_XGM'):
that sase in the run. The missing values, in case of change of number of pulses,
are filled with NaNs.
'''
if sase not in data:
print('Missing bunch pattern info!')
if npulses is None:
raise TypeError('npulses argument is required when bunch pattern ' +
'info is missing.')
print('Retrieving {} SASE {} pulses assuming that '.format(npulses, sase[4])
+'SASE {} pulses come first.'.format('3' if sase3First else '1'))
#in older version of DAQ, non-data numbers were filled with 0.0.
xgmData = data[xgm].where(data[xgm]!=0.0, drop=True)
xgmData = xgmData.fillna(0.0).where(xgmData!=1.0, drop=True)
if (sase3First and sase=='sase3') or (not sase3First and sase=='sase1'):
return xgmData[:,:npulses]
else:
if xr.ufuncs.isnan(xgmData).any():
raise Exception('The number of pulses changed during the run. '
'This is not supported yet.')
else:
start=xgmData.shape[1]-npulses
return xgmData[:,start:start+npulses]
result = None
npulses_sa3 = data['npulses_sase3']
npulses_sa1 = data['npulses_sase1']
......@@ -374,8 +395,9 @@ def mcpPeaks(data, intstart, intstop, bkgstart, bkgstop, mcp=1, t_offset=None, n
bkgstart: trace index of background start
bkgstop: trace index of background stop
mcp: MCP channel number
t_offset: index separation between two pulses. If None, checks the
pulse pattern and determine the t_offset assuming mininum pulse
t_offset: index separation between two pulses. Needed if bunch
pattern info is not available. If None, checks the pulse
pattern and determine the t_offset assuming mininum pulse
separation of 220 ns and digitizer resolution of 2 GHz.
npulses: number of pulses. If None, takes the maximum number of
pulses according to the bunch patter (field 'npulses_sase3')
......@@ -389,8 +411,8 @@ def mcpPeaks(data, intstart, intstop, bkgstart, bkgstop, mcp=1, t_offset=None, n
raise ValueError("Source not found: {}!".format(keyraw))
if npulses is None:
npulses = int(data['npulses_sase3'].max().values)
sa3 = data['sase3'].where(data['sase3']>1)
if t_offset 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
......@@ -399,7 +421,7 @@ def mcpPeaks(data, intstart, intstop, bkgstart, bkgstop, mcp=1, t_offset=None, n
t_offset = 440 * step
else:
t_offset = 1
results = xr.DataArray(np.empty((sa3.shape[0], npulses)), coords=sa3.coords,
results = xr.DataArray(np.empty((data.trainId.shape[0], npulses)), coords=data[keyraw].coords,
dims=['trainId', 'MCP{}fromRaw'.format(mcp)])
for i in range(npulses):
a = intstart + t_offset*i
......@@ -412,11 +434,15 @@ def mcpPeaks(data, intstart, intstop, bkgstart, bkgstop, mcp=1, t_offset=None, n
def getTIMapd(data, mcp=1, use_apd=True, intstart=None, intstop=None,
bkgstart=None, bkgstop=None, t_offset=None, npulses=None):
bkgstart=None, bkgstop=None, t_offset=None, npulses=None,
stride=1):
''' Extract peak-integrated data from TIM where pulses are from SASE3 only.
If use_apd is False it calculates integration from raw traces.
The missing values, in case of change of number of pulses, are filled
with NaNs.
If no bunch pattern info is available, the function assumes that
SASE 3 comes first and that the number of pulses is fixed in both
SASE 1 and 3.
Inputs:
data: xarray Dataset containing MCP raw traces (e.g. 'MCP1raw')
......@@ -426,12 +452,28 @@ def getTIMapd(data, mcp=1, use_apd=True, intstart=None, intstop=None,
bkgstop: trace index of background stop
t_offset: index separation between two pulses
mcp: MCP channel number
npulses: number of pulses to compute
npulses: int, optional. Number of pulses to compute. Required if
no bunch pattern info is available.
stride: int, optional. Used to select pulses in the APD array if
no bunch pattern info is available.
Output:
tim: DataArray of shape trainId only for SASE3 pulses x N
with N=max(number of pulses per train)
'''
if 'sase3' not in data:
print('Missing bunch pattern info!\n')
if npulses is None:
raise TypeError('npulses argument is required when bunch pattern ' +
'info is missing.')
print('Retrieving {} SASE 3 pulses assuming that '.format(npulses) +
'SASE 3 pulses come first.')
if use_apd:
tim = data['MCP{}apd'.format(mcp)][:,:npulses:stride]
else:
tim = mcpPeaks(data, intstart, intstop, bkgstart, bkgstop, mcp=mcp,
t_offset=t_offset, npulses=npulses)
return tim
sa3 = data['sase3'].where(data['sase3']>1, drop=True)
npulses_sa3 = data['npulses_sase3']
maxpulses = int(npulses_sa3.max().values)
......@@ -752,7 +794,7 @@ def checkTimApdWindow(data, mcp=1, use_apd=True, intstart=None, intstop=None):
def matchXgmTimPulseId(data, use_apd=True, intstart=None, intstop=None,
bkgstart=None, bkgstop=None, t_offset=None,
npulses=None):
npulses=None, sase3First=True, stride=1):
''' Function to match XGM pulse Id with TIM pulse Id.
Inputs:
data: xarray Dataset containing XGM and TIM data
......@@ -764,18 +806,24 @@ def matchXgmTimPulseId(data, use_apd=True, intstart=None, intstop=None,
bkgstart: trace index of background start
bkgstop: trace index of background stop
t_offset: index separation between two pulses
npulses: number of pulses to compute
npulses: number of pulses to compute. Required if no bunch
pattern info is available
sase3First: bool, needed if bunch pattern is missing.
stride: int, used to select pulses in the TIM APD array if
no bunch pattern info is available.
Output:
xr DataSet containing XGM and TIM signals with the share
dimension 'pId'. Raw traces, raw XGM and raw APD are dropped.
'''
res = selectSASEinXGM(data, xgm='SCS_XGM').rename({'XGMbunchId':'pId'}).rename('SCS_XGM')
res = selectSASEinXGM(data, xgm='SCS_XGM', npulses=npulses,
sase3First=sase3First).rename({'XGMbunchId':'pId'}).rename('SCS_XGM')
dropList = ['SCS_XGM']
mergeList = [res]
if 'SA3_XGM' in data:
res2 = selectSASEinXGM(data, xgm='SA3_XGM').rename({'XGMbunchId':'pId'}).rename('SA3_XGM')
res2 = selectSASEinXGM(data, xgm='SA3_XGM', npulses=npulses,
sase3First=sase3First).rename({'XGMbunchId':'pId'}).rename('SA3_XGM')
dropList.append('SA3_XGM')
mergeList.append(res2)
......@@ -783,8 +831,8 @@ def matchXgmTimPulseId(data, use_apd=True, intstart=None, intstop=None,
if 'MCP{}apd'.format(mcp) in data or 'MCP{}raw'.format(mcp) in data:
MCPapd = getTIMapd(data, mcp=mcp, use_apd=use_apd, intstart=intstart,
intstop=intstop,bkgstart=bkgstart, bkgstop=bkgstop,
t_offset=t_offset,
npulses=npulses).rename('MCP{}apd'.format(mcp))
t_offset=t_offset, npulses=npulses,
stride=stride).rename('MCP{}apd'.format(mcp))
if use_apd:
MCPapd = MCPapd.rename({'apdId':'pId'})
else:
......
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