def event(self):
geoCache = Belle2.VXD.GeoCache.getInstance()
mcpart = Belle2.PyStoreArray('MCParticles')
for part in mcpart:
mctraj = part.getRelationsTo('MCParticleTrajectorys')
#if(len(mctraj) > 0):
#print(mc)
pxd_clusters = Belle2.PyStoreArray('PXDClusters')
#print("event=", Belle2.PyStoreObj('EventMetaData').obj().getEvent())
for cluster in pxd_clusters:
mcparticles = cluster.getRelationsTo('MCParticles')
#print(len(mcparticles))
# Event identification
self.data.exp = Belle2.PyStoreObj(
'EventMetaData').obj().getExperiment()
self.data.run = Belle2.PyStoreObj('EventMetaData').obj().getRun()
self.data.evt = Belle2.PyStoreObj('EventMetaData').obj().getEvent()
# Sensor identification
vxd_id = cluster.getSensorID()
self.data.vxd_id = vxd_id.getID()
self.data.layer = vxd_id.getLayerNumber()
self.data.ladder = vxd_id.getLadderNumber()
self.data.sensor = vxd_id.getSensorNumber()
#Find digits in cluster
digits = cluster.getRelationsTo('PXDDigits')
mc_part = cluster.getRelationsTo('MCParticles')
true_parts = cluster.getRelationsTo('PXDTrueHits')
sim_parts0 = cluster.getRelationsTo('PXDSimHits')
#print(len(digits))
info = geoCache.get(vxd_id)
r_local = ROOT.TVector3(cluster.getU(), cluster.getV(), 0)
r_global = info.pointToGlobal(r_local)
self.data.cls_u = r_local.X()
self.data.cls_v = r_local.Y()
self.data.cls_w = r_local.Z()
self.data.cls_x = r_global.X()
self.data.cls_y = r_global.Y()
self.data.cls_z = r_global.Z()
# Cluster size and charge
self.data.cls_uSize = cluster.getUSize()
self.data.cls_vSize = cluster.getVSize()
self.data.charge = cluster.getCharge()
self.data.seed_charge = cluster.getSeedCharge()
# Fill tree
self.file.cd()
self.tree.Fill()
def event(self):
""" Return True if event is fine, False otherwise """
someOK = False
EventMetaData = Belle2.PyStoreObj('EventMetaData')
event = EventMetaData.getEvent()
digits = Belle2.PyStoreArray('EKLMDigits')
hit2ds = Belle2.PyStoreArray('EKLMHit2ds')
self.hist_nDigit.Fill(len(digits))
self.hist_nHit2d.Fill(len(hit2ds))
super(EventInspectorEKLM, self).return_value(someOK)
def event(self):
"""Fill the histograms with the values of the MCParticle collection"""
T = Belle2.PCmsLabTransform()
mcParticles = Belle2.PyStoreArray('MCParticles')
nMCParticles = mcParticles.getEntries()
for i in range(nMCParticles):
mc = mcParticles[i]
if (mc.getPDG() == 15):
plab = mc.get4Vector()
pcms = T.rotateLabToCms() * plab
h_E.Fill(pcms.E())
h_px.Fill(pcms.Px())
h_py.Fill(pcms.Py())
h_pz.Fill(pcms.Pz())
# print (mc.getNDaughters())
vec_p4 = []
for idau in range(int(ndau)):
dau = mc.getDaughters()[idau]
p4lab = dau.get4Vector()
p4cms = T.rotateLabToCms() * p4lab
vec_p4.append(p4cms)
h_E_i[idau].Fill(p4cms.E())
# print (idau, dau.getPDG(), p4cms.E(), p4cms.M())
ij = 0
for idau in range(int(ndau)):
for jdau in range(idau):
mij = (vec_p4[idau] + vec_p4[jdau]).M()
h_m_ij[ij].Fill(mij)
# print(idau, jdau, ij, mij)
ij = ij + 1
def event(self):
rawFTSW = Belle2.PyStoreArray('RawFTSWs')
if not rawFTSW.isValid():
b2.B2ERROR('No RawFTSW available - event ignored')
self.return_value(0)
return
# unknown meaning of this number
unknownInt = 0
if rawFTSW[0].GetTRGType(unknownInt) != Belle2.TRGSummary.TTYP_RAND:
self.return_value(1)
else:
self.return_value(0)
def store_content(self):
"""
Store the current content of the store array into the internal list.
"""
registered_store_arrays = Belle2.PyStoreArray.list()
registered_store_objects = Belle2.PyStoreObj.list()
event_store_content_list = []
for store_array_name in registered_store_arrays:
store_array = Belle2.PyStoreArray(store_array_name)
event_store_content_list.append(
StoreContent(store_array_name, len(store_array)))
for store_array_name in registered_store_objects:
event_store_content_list.append(StoreContent(store_array_name, 0))
event_store_content = StoreContentList(
content=event_store_content_list, event_number=self.event_number)
self.store_content_list.append(event_store_content)
def event(self):
"""Fill the histograms with the values of the MCParticle collection"""
mcParticles = Belle2.PyStoreArray('MCParticles')
nMCParticles = mcParticles.getEntries()
h_nMCParticles.Fill(nMCParticles)
for i in range(nMCParticles):
mc = mcParticles[i]
if mc.hasStatus(Belle2.MCParticle.c_PrimaryParticle):
p = mc.getMomentum()
t = mc.get4Vector()
h_momentum.Fill(p.Mag())
h_px.Fill(p.Px())
h_py.Fill(p.Py())
h_pz.Fill(p.Pz())
h_E.Fill(t.E())
h_pt.Fill(p.Perp())
h_phi.Fill(p.Phi() / math.pi * 180)
h_theta.Fill(p.Theta() / math.pi * 180)
h_costheta.Fill(math.cos(p.Theta()))
h_pdg.Fill(mc.getPDG())
h_vertex.Fill(mc.getProductionVertex().X(),
mc.getProductionVertex().Y())
def event(self):
'''Return match of event number to input list'''
mcplist = Belle2.PyStoreArray("MCParticles")
# Get event number, need for DF index
evtNum = self.eventinfo.getEvent()
# parentLFN = self.eventinfo.getParentLFN() # for pd series
# Get training label, need for DF index
useful = True
# If we already have list of event numbers then only keep requested events
if not self.create_evtNum_file:
useful = evtNum in self.evtNum_arr
if self.keep_only != -1 and self.keep_only != useful:
return
else:
self.evtNum_arr.append(evtNum)
event_dict = {}
# Create particle vars
for mcp in mcplist:
if mcp.isPrimaryParticle() and self._check_status_bit(
mcp.getStatus()):
# Load particle's data
arrayIndex = mcp.getArrayIndex()
four_vec = mcp.get4Vector()
prod_vec = mcp.getProductionVertex()
mother = mcp.getMother()
motherPDG = 0
motherArrayIndex = 0
if mother:
motherPDG = mother.getPDG()
motherArrayIndex = mother.getArrayIndex()
# Append to dict for making dataframe later
event_dict[(useful, evtNum, arrayIndex)] = {
'PDG': mcp.getPDG(),
'mass': mcp.getMass(),
'charge': mcp.getCharge(),
'energy': mcp.getEnergy(),
'prodTime': mcp.getProductionTime(),
'x': prod_vec.x(),
'y': prod_vec.y(),
'z': prod_vec.z(),
'px': four_vec.Px(),
'py': four_vec.Py(),
'pz': four_vec.Pz(),
'nDaughters': mcp.getNDaughters(),
'status': mcp.getStatus(),
'motherPDG': motherPDG,
'motherIndex': motherArrayIndex,
}
# Create event wide feedforward vars
# First particle is always the top of the decay chain
if len(event_dict) > 0:
MCdecay_string = self._build_decay_string(mcplist[0])
# data_dict['decay_input'] = self.cap.preproc_single_decay_string(MCdecay_string, self.LSTM_flag)
decay_str_df = pd.DataFrame(
data=[{
'label': useful,
'decay_str': MCdecay_string
}],
index=[evtNum],
)
self.decay_str_list.append(decay_str_df)
# If I tokenize the decay string here then root_pandas should work
event_df = pd.DataFrame.from_dict(event_dict, orient='index')
event_df.index.names = self.index_names
self.events_list.append(event_df)
def event(self):
""" Return True if event is fine, False otherwise """
someOK = False
EventMetaData = Belle2.PyStoreObj('EventMetaData')
event = EventMetaData.getEvent()
rawklms = Belle2.PyStoreArray('RawKLMs')
digits = Belle2.PyStoreArray('EKLMDigits')
hit2ds = Belle2.PyStoreArray('EKLMHit2ds')
#klmdigi = Belle2.PyStoreArray('KLMDigitEventInfo')
#eklmids = Belle2.PyStoreArray('EKLMHitBases')
self.hist_nDigit.Fill(len(digits))
self.hist_nHit2d.Fill(len(hit2ds))
for copper in range(0, len(rawklms)):
rawklm = rawklms[copper]
if rawklm.GetNumEntries() != 1:
print('##0 Event', event, 'copper', copper, ' getNumEntries=',
rawklm.GetNumEntries())
continue
nodeID = rawklm.GetNodeID(0) - self.BKLM_ID
if nodeID >= self.EKLM_ID - self.BKLM_ID:
nodeID = nodeID - (self.EKLM_ID - self.BKLM_ID) + 4
self.hist_rawKLMnodeID.Fill(nodeID, copper)
if (nodeID < 0) or (nodeID > 4): # skip EKLM nodes
continue
for digit in digits:
sector = digit.getSector()
endcap = digit.getEndcap()
time = digit.getTime()
ctime = digit.getCTime()
tdc = digit.getTDC()
#klmdigi = digit.getRelatedTo('KLMDigitEventInfo')
#triggtime = digit.getRelativeCTime()
#print (ctime, tdc)#, triggtime)
#print(time)
self.hist_time.Fill(time)
self.hist_ctime.Fill(ctime)
self.hist_tdc.Fill(tdc)
if (endcap == 1):
self.hist_BackwardSectorOccupancy.Fill(sector)
self.hist_BackwardSectorbyctime.Fill(sector, ctime)
else:
self.hist_ForwardSectorOccupancy.Fill(sector)
self.hist_ForwardSectorbyctime.Fill(sector, ctime)
self.hist_EndcapOccupancy.Fill(endcap)
for hit2d in hit2ds:
sector = hit2d.getSector()
endcap = hit2d.getEndcap()
layer = hit2d.getLayer()
gx = hit2d.getPositionX()
gy = hit2d.getPositionY()
gz = hit2d.getPositionZ()
if (endcap == 1):
self.hist_occupancyBackwardXY.Fill(gx, gy)
self.hist_LayeroccupancyBackwardRZ.Fill(layer, gz)
self.hist_LayeroccupancyBackward.Fill(layer)
self.hist_occupancyBackwardXYPerLayer[layer - 1].Fill(gx, gy)
else:
self.hist_occupancyForwardXY.Fill(gx, gy)
self.hist_LayeroccupancyForwardRZ.Fill(layer, gz)
self.hist_LayeroccupancyForward.Fill(layer)
self.hist_occupancyForwardXYPerLayer[layer - 1].Fill(gx, gy)
super(EventInspectorEKLM, self).return_value(someOK)
def event(self):
"""Return match of event number to input list"""
if self.model is None:
from keras.models import load_model
self.model = load_model(self.model_file)
# Required to be initialised before multithreading
self.model._make_predict_function()
# And if needed infer the name of the extra info var
if self.extra_info_var is None:
self.extra_info_var = self.model.name
b2.B2INFO('EventExtraInfo variable set to: {}'.format(
self.extra_info_var))
b2.B2INFO('Initialised model')
# Need to create the eventExtraInfo entry for each event
if self.extra_info_var:
self.e_e_info.create()
mcplist = Belle2.PyStoreArray("MCParticles")
# Can get away with list because we don't use arrayIndex
event_list = []
data_dict = {}
if self.model_type in [
'combined-LSTM', 'combined-wideCNN', 'particles'
]:
# Create particle vars
for mcp in mcplist:
if mcp.isPrimaryParticle():
# Check mc particle is useable
if not self.cap.check_status_bit(mcp.getStatus()):
continue
four_vec = mcp.get4Vector()
prod_vec = mcp.getProductionVertex()
mother = mcp.getMother()
motherPDG = 0
if mother:
motherPDG = mother.getPDG()
event_list.append({
'PDG': mcp.getPDG(),
# 'mass': mcp.getMass(),
'charge': mcp.getCharge(),
'energy': mcp.getEnergy(),
'prodTime': mcp.getProductionTime(),
'x': prod_vec.x(),
'y': prod_vec.y(),
'z': prod_vec.z(),
'px': four_vec.Px(),
'py': four_vec.Py(),
'pz': four_vec.Pz(),
'motherPDG': motherPDG,
})
# Convert to a dataframe for preprocessing
event_df = pd.DataFrame(event_list)
# Perform event preprocessing and get back the numpy array of particles
data_dict['particle_input'], data_dict['pdg_input'], data_dict[
'mother_pdg_input'] = self.cap.preproc_single_whole_decay(
event_df)
# Need to do reshaping here I think
# x_arr = np.reshape(x_arr, (1, x_arr.shape[0], x_arr.shape[1]))
# pdg_arr = np.reshape(pdg_arr, (1, pdg_arr.shape[0]))
# mother_pdg_arr = np.reshape(mother_pdg_arr, (1, mother_pdg_arr.shape[0]))
# Build decay string
if self.model_type in [
'combined-LSTM', 'combined-wideCNN', 'decstr-LSTM',
'decstr-wideCNN'
]:
# First particle is always the top of the decay chain
if len(mcplist) > 0:
MCdecay_string = self.cap.build_decay_string(mcplist[0])
data_dict['decay_input'] = self.cap.preproc_single_decay_string(
MCdecay_string, self.LSTM_flag)
# Outputs pass probability
pred = self.model.predict(data_dict)
# Need to set this to some debug mode
# b2.B2INFO('Pass probability:\t{}'.format(pred[0][0]))
# b2.B2INFO('Passes threshold:\t{}'.format(int(pred[0][0] >= self.threshold)))
# Save the pass probability to EventExtraInfo
if self.extra_info_var:
self.e_e_info.addExtraInfo(self.extra_info_var, pred[0][0])
# Module returns bool of whether prediciton passes threshold for use in basf2 path flow control
self.return_value(int(pred[0][0] >= self.threshold))
def event(self):
geoCache = Belle2.VXD.GeoCache.getInstance()
trg = Belle2.PyStoreArray('TRGSummary')
gdl_25 = ((trgSum.getPsnmBits(0) & 0x6000000) > 25);
gdl_26 = ((trgSum.getPsnmBits(0) & 0x4000000) > 26);
if gdl_25 != 0 or gld_26 != 0:
pxd_clusters = Belle2.PyStoreArray('PXDClusters')
#print("event=", Belle2.PyStoreObj('EventMetaData').obj().getEvent())
for cluster in pxd_clusters:
# Event identification
self.data.exp = Belle2.PyStoreObj('EventMetaData').obj().getExperiment()
self.data.run = Belle2.PyStoreObj('EventMetaData').obj().getRun()
self.data.evt = Belle2.PyStoreObj('EventMetaData').obj().getEvent()
# Sensor identification
vxd_id = cluster.getSensorID()
self.data.vxd_id = vxd_id.getID()
self.data.layer = vxd_id.getLayerNumber()
self.data.ladder = vxd_id.getLadderNumber()
self.data.sensor = vxd_id.getSensorNumber()
#Find digits in cluster
digits = cluster.getRelationsTo('PXDDigits')
mc_part = cluster.getRelationsTo('MCParticles')
true_parts = cluster.getRelationsTo('PXDTrueHits')
sim_parts0 = cluster.getRelationsTo('PXDSimHits')
#for sim_part in sim_parts0:
#print("sim_part0")
#for true_part in true_parts:
#print("true_part")
#sim_parts = cluster.getRelationsTo('PXDSimHits')
#for sim_part in sim_parts:
#print("sim_part")
#print(sim_part.getBackgroundTag())
#for particle in mc_part:
#sim_parts = particle.getRelationsTo('PXDSimHits')
#for sim_part in sim_parts:
#print("sim_part")
#print(sim_part.getBackgroundTag())
# if particle.isPrimaryParticle() == True:
# i = i + 1
# print(i)
#Get u,v coordinates of each digit
#print ("new cluster")
#for digit in digits:
# print(digit.getSensorID())
#static VXD::GeoCache& geo = VXD::GeoCache::getInstance();
#const VXD::SensorInfoBase& info = geo.get(sensorID);
#abs_pos = info.pointToGlobal(local_pos)
info = geoCache.get(vxd_id)
r_local = ROOT.TVector3(cluster.getU(), cluster.getV(), 0)
r_global = info.pointToGlobal(r_local)
self.data.cls_u = r_local.X()
self.data.cls_v = r_local.Y()
self.data.cls_w = r_local.Z()
self.data.cls_x = r_global.X()
self.data.cls_y = r_global.Y()
self.data.cls_z = r_global.Z()
# Cluster size and charge
self.data.cls_uSize = cluster.getUSize()
self.data.cls_vSize = cluster.getVSize()
self.data.charge = cluster.getCharge()
self.data.seed_charge = cluster.getSeedCharge()
# Fill tree
self.file.cd()
self.tree.Fill()