diff --git a/Load.py b/Load.py
index 094c280b91a836c6c200e753ac57fb7b761fc624..a618b94d729626fc545af340f7000cc50181712d 100644
--- a/Load.py
+++ b/Load.py
@@ -10,6 +10,7 @@ from karabo_data import by_index, RunDirectory
from karabo_data.read_machinery import find_proposal
import xarray as xr
import os
+import euxfel_bunch_pattern as bp
mnemonics = {
# Machine
@@ -28,6 +29,9 @@ mnemonics = {
"bunchpattern": {'source':'SCS_RR_UTC/TSYS/TIMESERVER',
'key':'readBunchPatternTable.value',
'dim':None},
+ "bunchPatternTable": {'source':'SCS_RR_UTC/TSYS/TIMESERVER',
+ 'key':'bunchPatternTable.value',
+ 'dim':['pulse_slot']},
"npulses_sase3": {'source':'SCS_RR_UTC/MDL/BUNCH_DECODER',
'key':'sase3.nPulses.value',
'dim':None},
@@ -209,6 +213,10 @@ mnemonics = {
"PP800_TeleLens": {'source':'SCS_ILH_LAS/MOTOR/LT7',
'key':'actualPosition.value',
'dim':None},
+ "ILH_8CAM1": {'source':'SCS_ILH_LAS/CAM/8CAM1:daqOutput',
+ 'key':'data.image.pixels',
+ 'dim':['8cam1_y', '8cam1_x']},
+
# FFT
"scannerX": {'source':'SCS_CDIFFT_SAM/LMOTOR/SCANNERX',
@@ -229,6 +237,10 @@ mnemonics = {
"magnet_old": {'source':'SCS_CDIFFT_MAG/SUPPLY/CURRENT',
'key':'actualCurrent.value',
'dim':None},
+
+ "Vertical_FDM": {'source':'SCS_CDIFFT_LDM/CAM/CAMERA1A:daqOutput',
+ 'key':'data.image.pixels',
+ 'dim':['vfdm_y', 'vfdm_x']},
# FastCCD, if in raw folder, raw images
# if in proc folder, dark substracted and relative gain corrected
@@ -364,8 +376,51 @@ mnemonics = {
'dim': ['gott_pId','pixelId']}
}
+def extractSaseBunchPattern(runDir, sase=3):
+ ''' generate the "saseX" and "npulse_saseX" arrays directly from the bunch pattern table and not using the
+ MDL device BUNCH_DECODER.
+ Inputs:
+ runDir: run directory obtained by karabo_data.runDirectory()
+ sase: int, sase number between 1 and 3
+
+ Outputs:
+ sase: DataArray containing indices of the sase pulses for each train
+ npulses_sase: DataArray containing the number of pulses for each train
+
+ '''
+ if not (1 <= sase <= 3):
+ raise ValueError("Invalid SASE value {!r}, expected 1-3")
+ bp_mnemo = mnemonics['bunchPatternTable']
+ bp_table = runDir.get_array(bp_mnemo['source'],bp_mnemo['key'],
+ extra_dims=bp_mnemo['dim'])
+ destination = bp.DESTINATION_T5D if (sase == 2) else bp.DESTINATION_T4D
+ matched = (bp_table & bp.DESTINATION_MASK) == destination
+
+ if sase == 1:
+ # Pulses to SASE 1 when soft kick is off
+ matched &= (bp_table & bp.PHOTON_LINE_DEFLECTION) == 0
+ elif sase == 3:
+ # Pulses to SASE 3 when soft kick is on
+ matched &= (bp_table & bp.PHOTON_LINE_DEFLECTION) != 0
+
+ nz = np.nonzero(matched.values)
+ dim_pId = matched.shape[1]
+ sase_array = np.ones(matched.shape, dtype=np.uint64)*dim_pId
+ sase_array[nz] = nz[1]
+ sase_array = np.sort(sase_array)
+ sase_array[sase_array == dim_pId] = 0
+
+ sase_da = xr.DataArray(sase_array[:,:1000], dims=['trainId', 'bunchId'],
+ coords={'trainId':matched.trainId},
+ name=f'sase{sase}')
+ npulses_sase = xr.DataArray(np.count_nonzero(sase_da, axis=1), dims=['trainId'],
+ coords={'trainId':matched.trainId},
+ name=f'npulses_sase{sase}')
+ return sase_da, npulses_sase
+
+
def load(fields, runNB, proposalNB, subFolder='raw', display=False, validate=False,
- subset=by_index[:], rois={}):
+ subset=by_index[:], rois={}, useBPTable=True):
""" Load a run and extract the data. Output is an xarray with aligned trainIds
Inputs:
@@ -384,6 +439,9 @@ def load(fields, runNB, proposalNB, subFolder='raw', display=False, validate=Fal
names, for example {'fastccd':{'ref':{'roi':by_index[730:890, 535:720],
'dim': ['ref_x', 'ref_y']}, 'sam':{'roi':by_index[1050:1210, 535:720],
'dim': ['sam_x', 'sam_y']}}}
+ useBPTable: If True, uses the raw bunch pattern table to extract sase pulse
+ number and indices in the trains. If false, load the data from BUNCH_DECODER
+ middle layer device.
Outputs:
res: an xarray DataSet with aligned trainIds
@@ -405,8 +463,18 @@ def load(fields, runNB, proposalNB, subFolder='raw', display=False, validate=Fal
keys = []
vals = []
- # always load pulse pattern infos
- fields += ["sase1", "sase3", "npulses_sase3", "npulses_sase1"]
+ # load pulse pattern infos
+ if useBPTable:
+ if mnemonics['bunchPatternTable']['source'] not in run.all_sources:
+ print('Source {} not found in run. Skipping!'.format(
+ mnemonics['bunchPatternTable']['source']))
+ else:
+ sase1, npulses_sase1 = extractSaseBunchPattern(run, 1)
+ sase3, npulses_sase3 = extractSaseBunchPattern(run, 3)
+ keys += ["sase1", "npulses_sase1", "sase3", "npulses_sase3"]
+ vals += [sase1, npulses_sase1, sase3, npulses_sase3]
+ else:
+ fields += ["sase1", "sase3", "npulses_sase3", "npulses_sase1"]
for f in fields:
@@ -444,7 +512,7 @@ def load(fields, runNB, proposalNB, subFolder='raw', display=False, validate=Fal
for nk,nv in rois[k].items():
vals.append(run.get_array(v['source'], v['key'], extra_dims=nv['dim'], roi=nv['roi']))
keys.append(nk)
-
+
aligned_vals = xr.align(*vals, join='inner')
result = dict(zip(keys, aligned_vals))
result = xr.Dataset(result)
@@ -474,3 +542,4 @@ def concatenateRuns(runs):
result.attrs['run'] = [run.attrs['run'] for run in orderedRuns]
result.attrs['runFolder'] = [run.attrs['runFolder'] for run in orderedRuns]
return result
+