def preprocess(self, dst_file):
chain = r.TChain("HPS_Event")
chain.Add(dst_file)
tree = chain.GetTree()
from ROOT import HpsEvent
hps_event = HpsEvent()
branch = chain.SetBranchAddress("Event", r.AddressOf(hps_event))
# Create the file name for the preprocessed ROOT file
#output_file_name = root_file.GetName()[str(root_file.GetName()).rindex("/") + 1:-5]
output_file_name = "beam_tri_preprocessed_signal.root"
# Add variables to the ntuple
ft_maker = ft.FlatTupleMaker(output_file_name)
ft_maker.add_variable("cluster_0_energy")
ft_maker.add_variable("cluster_1_energy")
ft_maker.add_variable("cluster_0_x")
ft_maker.add_variable("cluster_1_x")
ft_maker.add_variable("cluster_0_y")
ft_maker.add_variable("cluster_1_y")
ft_maker.add_variable("track_0_p")
ft_maker.add_variable("track_0_px")
ft_maker.add_variable("track_0_py")
ft_maker.add_variable("track_0_pz")
ft_maker.add_variable("track_0_tanlambda")
ft_maker.add_variable("track_0_phi0")
ft_maker.add_variable("track_0_omega")
ft_maker.add_variable("track_0_d0")
ft_maker.add_variable("track_0_z0")
ft_maker.add_variable("track_0_charge")
ft_maker.add_variable("track_1_p")
ft_maker.add_variable("track_1_px")
ft_maker.add_variable("track_1_py")
ft_maker.add_variable("track_1_pz")
ft_maker.add_variable("track_1_tanlambda")
ft_maker.add_variable("track_1_phi0")
ft_maker.add_variable("track_1_omega")
ft_maker.add_variable("track_1_d0")
ft_maker.add_variable("track_1_z0")
ft_maker.add_variable("track_1_charge")
matcher = tcm.TrackClusterMatcher()
for entry in xrange(0, chain.GetEntries()):
if (entry + 1) % 1000 == 0: print "Event " + str(entry + 1)
chain.GetEntry(entry)
#if not au.is_good_data_event(hps_event) : continue
# Loop through all clusters in the event and find a 'good' pair.
# For now, a 'good' pair is defined as two clusters whose cluster
# time difference is less than 1.7 ns and greater than -1.6 ns
cluster_pair = au.get_good_cluster_pair(hps_event)
if not self.is_good_cluster_pair(cluster_pair): continue
matcher.find_all_matches(hps_event)
tracks = [
matcher.get_track(cluster_pair[0]),
matcher.get_track(cluster_pair[1])
]
if (tracks[0] is None) or (tracks[1] is None): continue
ft_maker.set_variable_value("cluster_0_energy",
cluster_pair[0].getEnergy())
ft_maker.set_variable_value("cluster_1_energy",
cluster_pair[1].getEnergy())
ft_maker.set_variable_value("cluster_0_x",
cluster_pair[0].getPosition()[0])
ft_maker.set_variable_value("cluster_1_x",
cluster_pair[1].getPosition()[0])
ft_maker.set_variable_value("cluster_0_y",
cluster_pair[0].getPosition()[1])
ft_maker.set_variable_value("cluster_1_y",
cluster_pair[1].getPosition()[1])
ft_maker.set_variable_value(
"track_0_p",
np.linalg.norm(np.asarray(tracks[0].getMomentum())))
ft_maker.set_variable_value("track_0_px",
tracks[0].getMomentum()[0])
ft_maker.set_variable_value("track_0_py",
tracks[0].getMomentum()[1])
ft_maker.set_variable_value("track_0_pz",
tracks[0].getMomentum()[2])
ft_maker.set_variable_value("track_0_tanlambda",
tracks[0].getTanLambda())
ft_maker.set_variable_value("track_0_phi0", tracks[0].getPhi0())
ft_maker.set_variable_value("track_0_omega", tracks[0].getOmega())
ft_maker.set_variable_value("track_0_d0", tracks[0].getD0())
ft_maker.set_variable_value("track_0_z0", tracks[0].getZ0())
ft_maker.set_variable_value("track_0_charge",
tracks[0].getCharge())
ft_maker.set_variable_value(
"track_1_p",
np.linalg.norm(np.asarray(tracks[1].getMomentum())))
ft_maker.set_variable_value("track_1_px",
tracks[1].getMomentum()[0])
ft_maker.set_variable_value("track_1_py",
tracks[1].getMomentum()[1])
ft_maker.set_variable_value("track_1_pz",
tracks[1].getMomentum()[2])
ft_maker.set_variable_value("track_1_tanlambda",
tracks[1].getTanLambda())
ft_maker.set_variable_value("track_1_phi0", tracks[1].getPhi0())
ft_maker.set_variable_value("track_1_omega", tracks[1].getOmega())
ft_maker.set_variable_value("track_1_d0", tracks[1].getD0())
ft_maker.set_variable_value("track_1_z0", tracks[1].getZ0())
ft_maker.set_variable_value("track_1_charge",
tracks[1].getCharge())
ft_maker.fill()
ft_maker.close()
def preprocess(self, dst_file):
chain = r.TChain("HPS_Event")
chain.Add(dst_file)
tree = chain.GetTree()
from ROOT import HpsEvent
hps_event = HpsEvent()
branch = chain.SetBranchAddress("Event", r.AddressOf(hps_event))
# Add variables to the ntuple
ft_maker = ft.FlatTupleMaker(self.output_file_name)
ft_maker.add_variable("cluster_0_energy")
ft_maker.add_variable("cluster_1_energy")
ft_maker.add_variable("cluster_0_x")
ft_maker.add_variable("cluster_1_x")
ft_maker.add_variable("cluster_0_y")
ft_maker.add_variable("cluster_1_y")
ft_maker.add_variable("track_0_p")
ft_maker.add_variable("track_0_px")
ft_maker.add_variable("track_0_py")
ft_maker.add_variable("track_0_pz")
ft_maker.add_variable("track_0_theta")
ft_maker.add_variable("track_0_phi0")
ft_maker.add_variable("track_0_omega")
ft_maker.add_variable("track_0_d0")
ft_maker.add_variable("track_0_z0")
ft_maker.add_variable("track_1_p")
ft_maker.add_variable("track_1_px")
ft_maker.add_variable("track_1_py")
ft_maker.add_variable("track_1_pz")
ft_maker.add_variable("track_1_theta")
ft_maker.add_variable("track_1_phi0")
ft_maker.add_variable("track_1_omega")
ft_maker.add_variable("track_1_d0")
ft_maker.add_variable("track_1_z0")
ft_maker.add_variable("track_pair_p_sum")
matcher = tcm.TrackClusterMatcher()
for entry in xrange(0, chain.GetEntries()):
if (entry+1)%1000 == 0 : print "Event " + str(entry+1)
chain.GetEntry(entry)
# Loop through all clusters in the event and find a 'good' pair.
# For now, a 'good' pair is defined as two clusters whose cluster
# time difference is less than 1.6 ns and greater than -1.6 ns
cluster_pair = au.get_good_cluster_pair(hps_event)
if len(cluster_pair) != 2 : continue
matcher.find_all_matches(hps_event)
tracks = [matcher.get_track(cluster_pair[0]), matcher.get_track(cluster_pair[1])]
if (tracks[0] is None) or (tracks[1] is None) : continue
ft_maker.set_variable_value("cluster_0_energy", cluster_pair[0].getEnergy())
ft_maker.set_variable_value("cluster_1_energy", cluster_pair[1].getEnergy())
ft_maker.set_variable_value("cluster_0_x", cluster_pair[0].getPosition()[0])
ft_maker.set_variable_value("cluster_1_x", cluster_pair[1].getPosition()[0])
ft_maker.set_variable_value("cluster_0_y", cluster_pair[0].getPosition()[1])
ft_maker.set_variable_value("cluster_1_y", cluster_pair[1].getPosition()[1])
ft_maker.set_variable_value("track_0_p", np.linalg.norm(np.asarray(tracks[0].getMomentum())))
ft_maker.set_variable_value("track_0_px", tracks[0].getMomentum()[0])
ft_maker.set_variable_value("track_0_py", tracks[0].getMomentum()[1])
ft_maker.set_variable_value("track_0_pz", tracks[0].getMomentum()[2])
track_0_theta = math.fabs(math.pi/2 - math.acos(te.get_cos_theta(tracks[0])))
ft_maker.set_variable_value("track_0_theta", track_0_theta)
ft_maker.set_variable_value("track_0_phi0", tracks[0].getPhi0())
ft_maker.set_variable_value("track_0_omega", tracks[0].getOmega())
ft_maker.set_variable_value("track_0_d0", tracks[0].getD0())
ft_maker.set_variable_value("track_0_z0", tracks[0].getZ0())
ft_maker.set_variable_value("track_1_p", np.linalg.norm(np.asarray(tracks[1].getMomentum())))
ft_maker.set_variable_value("track_1_px", tracks[1].getMomentum()[0])
ft_maker.set_variable_value("track_1_py", tracks[1].getMomentum()[1])
ft_maker.set_variable_value("track_1_pz", tracks[1].getMomentum()[2])
track_1_theta = math.fabs(math.pi/2 - math.acos(te.get_cos_theta(tracks[1])))
ft_maker.set_variable_value("track_1_theta", track_1_theta)
ft_maker.set_variable_value("track_1_phi0", tracks[1].getPhi0())
ft_maker.set_variable_value("track_1_omega", tracks[1].getOmega())
ft_maker.set_variable_value("track_1_d0", tracks[1].getD0())
ft_maker.set_variable_value("track_1_z0", tracks[1].getZ0())
p_sum = np.linalg.norm(np.asarray(tracks[0].getMomentum())) + np.linalg.norm(np.asarray(tracks[1].getMomentum()))
ft_maker.set_variable_value("track_pair_p_sum", p_sum)
ft_maker.fill()
ft_maker.close()
def preprocess(self, dst_file):
chain = r.TChain("HPS_Event")
chain.Add(dst_file)
tree = chain.GetTree()
from ROOT import HpsEvent
hps_event = HpsEvent()
branch = chain.SetBranchAddress("Event", r.AddressOf(hps_event))
# Create the file name for the preprocessed ROOT file
#output_file_name = root_file.GetName()[str(root_file.GetName()).rindex("/") + 1:-5]
output_file_name = "beam_tri_preprocessed_signal.root"
# Add variables to the ntuple
ft_maker = ft.FlatTupleMaker(output_file_name)
ft_maker.add_variable("cluster_0_energy")
ft_maker.add_variable("cluster_1_energy")
ft_maker.add_variable("cluster_0_x")
ft_maker.add_variable("cluster_1_x")
ft_maker.add_variable("cluster_0_y")
ft_maker.add_variable("cluster_1_y")
ft_maker.add_variable("track_0_p")
ft_maker.add_variable("track_0_px")
ft_maker.add_variable("track_0_py")
ft_maker.add_variable("track_0_pz")
ft_maker.add_variable("track_0_tanlambda")
ft_maker.add_variable("track_0_phi0")
ft_maker.add_variable("track_0_omega")
ft_maker.add_variable("track_0_d0")
ft_maker.add_variable("track_0_z0")
ft_maker.add_variable("track_0_charge")
ft_maker.add_variable("track_1_p")
ft_maker.add_variable("track_1_px")
ft_maker.add_variable("track_1_py")
ft_maker.add_variable("track_1_pz")
ft_maker.add_variable("track_1_tanlambda")
ft_maker.add_variable("track_1_phi0")
ft_maker.add_variable("track_1_omega")
ft_maker.add_variable("track_1_d0")
ft_maker.add_variable("track_1_z0")
ft_maker.add_variable("track_1_charge")
matcher = tcm.TrackClusterMatcher()
for entry in xrange(0, chain.GetEntries()):
if (entry+1)%1000 == 0 : print "Event " + str(entry+1)
chain.GetEntry(entry)
#if not au.is_good_data_event(hps_event) : continue
# Loop through all clusters in the event and find a 'good' pair.
# For now, a 'good' pair is defined as two clusters whose cluster
# time difference is less than 1.7 ns and greater than -1.6 ns
cluster_pair = au.get_good_cluster_pair(hps_event)
if not self.is_good_cluster_pair(cluster_pair) : continue
matcher.find_all_matches(hps_event)
tracks = [matcher.get_track(cluster_pair[0]), matcher.get_track(cluster_pair[1])]
if (tracks[0] is None) or (tracks[1] is None) : continue
ft_maker.set_variable_value("cluster_0_energy", cluster_pair[0].getEnergy())
ft_maker.set_variable_value("cluster_1_energy", cluster_pair[1].getEnergy())
ft_maker.set_variable_value("cluster_0_x", cluster_pair[0].getPosition()[0])
ft_maker.set_variable_value("cluster_1_x", cluster_pair[1].getPosition()[0])
ft_maker.set_variable_value("cluster_0_y", cluster_pair[0].getPosition()[1])
ft_maker.set_variable_value("cluster_1_y", cluster_pair[1].getPosition()[1])
ft_maker.set_variable_value("track_0_p", np.linalg.norm(np.asarray(tracks[0].getMomentum())))
ft_maker.set_variable_value("track_0_px", tracks[0].getMomentum()[0])
ft_maker.set_variable_value("track_0_py", tracks[0].getMomentum()[1])
ft_maker.set_variable_value("track_0_pz", tracks[0].getMomentum()[2])
ft_maker.set_variable_value("track_0_tanlambda", tracks[0].getTanLambda())
ft_maker.set_variable_value("track_0_phi0", tracks[0].getPhi0())
ft_maker.set_variable_value("track_0_omega", tracks[0].getOmega())
ft_maker.set_variable_value("track_0_d0", tracks[0].getD0())
ft_maker.set_variable_value("track_0_z0", tracks[0].getZ0())
ft_maker.set_variable_value("track_0_charge", tracks[0].getCharge())
ft_maker.set_variable_value("track_1_p", np.linalg.norm(np.asarray(tracks[1].getMomentum())))
ft_maker.set_variable_value("track_1_px", tracks[1].getMomentum()[0])
ft_maker.set_variable_value("track_1_py", tracks[1].getMomentum()[1])
ft_maker.set_variable_value("track_1_pz", tracks[1].getMomentum()[2])
ft_maker.set_variable_value("track_1_tanlambda", tracks[1].getTanLambda())
ft_maker.set_variable_value("track_1_phi0", tracks[1].getPhi0())
ft_maker.set_variable_value("track_1_omega", tracks[1].getOmega())
ft_maker.set_variable_value("track_1_d0", tracks[1].getD0())
ft_maker.set_variable_value("track_1_z0", tracks[1].getZ0())
ft_maker.set_variable_value("track_1_charge", tracks[1].getCharge())
ft_maker.fill()
ft_maker.close()
def preprocess(self, dst_file):
chain = r.TChain("HPS_Event")
chain.Add(dst_file)
tree = chain.GetTree()
from ROOT import HpsEvent
hps_event = HpsEvent()
branch = chain.SetBranchAddress("Event", r.AddressOf(hps_event))
# Add variables to the ntuple
ft_maker = ft.FlatTupleMaker(self.output_file_name)
ft_maker.add_variable("cluster_0_energy")
ft_maker.add_variable("cluster_1_energy")
ft_maker.add_variable("cluster_0_x")
ft_maker.add_variable("cluster_1_x")
ft_maker.add_variable("cluster_0_y")
ft_maker.add_variable("cluster_1_y")
ft_maker.add_variable("track_0_p")
ft_maker.add_variable("track_0_px")
ft_maker.add_variable("track_0_py")
ft_maker.add_variable("track_0_pz")
ft_maker.add_variable("track_0_theta")
ft_maker.add_variable("track_0_phi0")
ft_maker.add_variable("track_0_omega")
ft_maker.add_variable("track_0_d0")
ft_maker.add_variable("track_0_z0")
ft_maker.add_variable("track_1_p")
ft_maker.add_variable("track_1_px")
ft_maker.add_variable("track_1_py")
ft_maker.add_variable("track_1_pz")
ft_maker.add_variable("track_1_theta")
ft_maker.add_variable("track_1_phi0")
ft_maker.add_variable("track_1_omega")
ft_maker.add_variable("track_1_d0")
ft_maker.add_variable("track_1_z0")
ft_maker.add_variable("track_pair_p_sum")
matcher = tcm.TrackClusterMatcher()
for entry in xrange(0, chain.GetEntries()):
if (entry + 1) % 1000 == 0: print "Event " + str(entry + 1)
chain.GetEntry(entry)
# Loop through all clusters in the event and find a 'good' pair.
# For now, a 'good' pair is defined as two clusters whose cluster
# time difference is less than 1.6 ns and greater than -1.6 ns
cluster_pair = au.get_good_cluster_pair(hps_event)
if len(cluster_pair) != 2: continue
matcher.find_all_matches(hps_event)
tracks = [
matcher.get_track(cluster_pair[0]),
matcher.get_track(cluster_pair[1])
]
if (tracks[0] is None) or (tracks[1] is None): continue
ft_maker.set_variable_value("cluster_0_energy",
cluster_pair[0].getEnergy())
ft_maker.set_variable_value("cluster_1_energy",
cluster_pair[1].getEnergy())
ft_maker.set_variable_value("cluster_0_x",
cluster_pair[0].getPosition()[0])
ft_maker.set_variable_value("cluster_1_x",
cluster_pair[1].getPosition()[0])
ft_maker.set_variable_value("cluster_0_y",
cluster_pair[0].getPosition()[1])
ft_maker.set_variable_value("cluster_1_y",
cluster_pair[1].getPosition()[1])
ft_maker.set_variable_value(
"track_0_p",
np.linalg.norm(np.asarray(tracks[0].getMomentum())))
ft_maker.set_variable_value("track_0_px",
tracks[0].getMomentum()[0])
ft_maker.set_variable_value("track_0_py",
tracks[0].getMomentum()[1])
ft_maker.set_variable_value("track_0_pz",
tracks[0].getMomentum()[2])
track_0_theta = math.fabs(math.pi / 2 -
math.acos(te.get_cos_theta(tracks[0])))
ft_maker.set_variable_value("track_0_theta", track_0_theta)
ft_maker.set_variable_value("track_0_phi0", tracks[0].getPhi0())
ft_maker.set_variable_value("track_0_omega", tracks[0].getOmega())
ft_maker.set_variable_value("track_0_d0", tracks[0].getD0())
ft_maker.set_variable_value("track_0_z0", tracks[0].getZ0())
ft_maker.set_variable_value(
"track_1_p",
np.linalg.norm(np.asarray(tracks[1].getMomentum())))
ft_maker.set_variable_value("track_1_px",
tracks[1].getMomentum()[0])
ft_maker.set_variable_value("track_1_py",
tracks[1].getMomentum()[1])
ft_maker.set_variable_value("track_1_pz",
tracks[1].getMomentum()[2])
track_1_theta = math.fabs(math.pi / 2 -
math.acos(te.get_cos_theta(tracks[1])))
ft_maker.set_variable_value("track_1_theta", track_1_theta)
ft_maker.set_variable_value("track_1_phi0", tracks[1].getPhi0())
ft_maker.set_variable_value("track_1_omega", tracks[1].getOmega())
ft_maker.set_variable_value("track_1_d0", tracks[1].getD0())
ft_maker.set_variable_value("track_1_z0", tracks[1].getZ0())
p_sum = np.linalg.norm(np.asarray(
tracks[0].getMomentum())) + np.linalg.norm(
np.asarray(tracks[1].getMomentum()))
ft_maker.set_variable_value("track_pair_p_sum", p_sum)
ft_maker.fill()
ft_maker.close()
