def Physics(self, frame):
q_tot = NaN
n_channels = 0
n_hits = 0
max_qfrac = NaN
pulse_map = dataclasses.I3RecoPulseSeriesMap.from_frame(
frame, self.pulses)
charge_list = []
for omkey, pulses in pulse_map:
# Throw out Deep Core strings (want homogenized total charge)
if (omkey.string < 79) and (omkey.om >= self.min_DOM) and (
omkey.om <= self.max_DOM):
n_channels += 1
for pulse in pulses:
charge_list += [pulse.charge]
# Check to see if DOMs with signal are in the min_DOM to
# max_DOM range
if n_channels == 0:
q_tot = NaN
max_qfrac = NaN
else:
q_tot = np.sum(charge_list)
n_hits = len(charge_list)
max_qfrac = np.max(charge_list) / q_tot
frame.Put('InIce_charge_{}_{}'.format(self.min_DOM, self.max_DOM),
dataclasses.I3Double(q_tot))
frame.Put('NChannels_{}_{}'.format(self.min_DOM, self.max_DOM),
icetray.I3Int(n_channels))
frame.Put('NHits_{}_{}'.format(self.min_DOM, self.max_DOM),
icetray.I3Int(n_hits))
frame.Put('max_qfrac_{}_{}'.format(self.min_DOM, self.max_DOM),
dataclasses.I3Double(max_qfrac))
self.PushFrame(frame)
def process_frame(frame, gcdfile='/cvmfs/icecube.opensciencegrid.org/data/GCD/GeoCalibDetectorStatus_2013.56429_V0.i3.gz', charge_scale=1.0, time_scale=1e-3):
""" Processes a frame to create an event graph and metadata out of it.
Parameters:
-----------
frame : I3Frame
The data frame to extract an event graph with features from.
gcd_file : str
Path to the gcd file.
charge_scale : float
The normalization constant for charge.
time_scale : float
The normalization constant for time.
"""
### Meta data of the event for analysis of the classifier and creation of ground truth
primary = dataclasses.get_most_energetic_neutrino(frame['I3MCTree'])
if primary is None:
get_weighted_primary(frame, MCPrimary='MCPrimary')
primary = frame['MCPrimary']
# Obtain the PDG Encoding for ground truth
#frame['PDGEncoding'] = dataclasses.I3Double(primary.pdg_encoding)
#frame['InteractionType'] = dataclasses.I3Double(frame['I3MCWeightDict']['InteractionType'])
frame['RunID'] = icetray.I3Int(frame['I3EventHeader'].run_id)
frame['EventID'] = icetray.I3Int(frame['I3EventHeader'].event_id)
frame['PrimaryEnergy'] = dataclasses.I3Double(primary.energy)
### Create features for each event
features, coordinates, _ = get_events_from_frame(frame, charge_scale=charge_scale, time_scale=time_scale)
for feature_name in vertex_features:
frame[feature_name] = dataclasses.I3VectorFloat(features[feature_name])
### Create offset lookups for the flattened feature arrays per event
frame['NumberVertices'] = icetray.I3Int(len(features[features.keys()[0]]))
### Create coordinates for each vertex
C = np.vstack(coordinates.values()).T
#C, C_mean, C_std = normalize_coordinates(C, weights=None, copy=True)
#C_cog, C_mean_cog, C_std_cog = normalize_coordinates(C, weights=features['TotalCharge'], copy=True)
frame['VertexX'] = dataclasses.I3VectorFloat(C[:, 0])
frame['VertexY'] = dataclasses.I3VectorFloat(C[:, 1])
frame['VertexZ'] = dataclasses.I3VectorFloat(C[:, 2])
### Output centering and true debug information
frame['PrimaryX'] = dataclasses.I3Double(primary.pos.x)
frame['PrimaryY'] = dataclasses.I3Double(primary.pos.y)
frame['PrimaryZ'] = dataclasses.I3Double(primary.pos.z)
frame['PrimaryAzimuth'] = dataclasses.I3Double(primary.dir.azimuth)
frame['PrimaryZenith'] = dataclasses.I3Double(primary.dir.zenith)
### Apply labeling
classify_wrapper(frame, None, gcdfile=gcdfile)
return True
def CreatePFrame(self, nside, pixel):
dec, ra = healpy.pix2ang(nside, pixel)
dec = dec - numpy.pi / 2.
zenith, azimuth = astro.equa_to_dir(ra, dec, self.event_mjd)
zenith = float(zenith)
azimuth = float(azimuth)
direction = dataclasses.I3Direction(zenith, azimuth)
position = self.seed_position
time = self.seed_time
energy = self.seed_energy
variationDistance = 20. * I3Units.m
posVariations = [
dataclasses.I3Position(0., 0., 0.),
dataclasses.I3Position(-variationDistance, 0., 0.),
dataclasses.I3Position(variationDistance, 0., 0.),
dataclasses.I3Position(0., -variationDistance, 0.),
dataclasses.I3Position(0., variationDistance, 0.),
dataclasses.I3Position(0., 0., -variationDistance),
dataclasses.I3Position(0., 0., variationDistance)
]
for i in range(0, len(posVariations)):
posVariation = posVariations[i]
p_frame = icetray.I3Frame(icetray.I3Frame.Physics)
thisPosition = dataclasses.I3Position(position.x + posVariation.x,
position.y + posVariation.y,
position.z + posVariation.z)
# generate the particle from scratch
particle = dataclasses.I3Particle()
particle.shape = dataclasses.I3Particle.ParticleShape.InfiniteTrack
particle.fit_status = dataclasses.I3Particle.FitStatus.OK
particle.pos = thisPosition
particle.dir = direction
particle.time = time
particle.energy = energy
p_frame[self.output_particle_name] = particle
# generate a new event header
eventHeader = dataclasses.I3EventHeader(self.event_header)
eventHeader.sub_event_stream = "SCAN_nside%04u_pixel%04u_posvar%04u" % (
nside, pixel, i)
eventHeader.sub_event_id = pixel
p_frame["I3EventHeader"] = eventHeader
p_frame["SCAN_HealpixPixel"] = icetray.I3Int(int(pixel))
p_frame["SCAN_HealpixNSide"] = icetray.I3Int(int(nside))
p_frame["SCAN_PositionVariationIndex"] = icetray.I3Int(int(i))
for frame in self.GCDQpFrames[0:-1]:
self.PushFrame(frame)
self.PushFrame(p_frame)
def RFrame(self, frame):
position = frame[self.input_pos_name]
time = frame[self.input_time_name].value
energy = float('NaN')
self.PushFrame(frame)
for pixel in self.pixels:
p_frame = icetray.I3Frame(icetray.I3Frame.Physics)
zenith, azimuth = healpy.pix2ang(self.nside, pixel)
direction = dataclasses.I3Direction(zenith,azimuth)
#print "reconstructing with fixed direction", direction, "(npixels=", self.npix, ", pixel=", pixel, ")"
variationDistance = 20.*I3Units.m
posVariations = [dataclasses.I3Position(0.,0.,0.),
dataclasses.I3Position(-variationDistance,0.,0.),
dataclasses.I3Position( variationDistance,0.,0.),
dataclasses.I3Position(0.,-variationDistance,0.),
dataclasses.I3Position(0., variationDistance,0.),
dataclasses.I3Position(0.,0.,-variationDistance),
dataclasses.I3Position(0.,0., variationDistance)]
for i in range(len(posVariations)):
thisPosition = dataclasses.I3Position(position.x + posVariations[i].x,position.y + posVariations[i].y,position.z + posVariations[i].z)
# generate the particle from scratch
particle = dataclasses.I3Particle()
particle.shape = dataclasses.I3Particle.ParticleShape.Cascade
particle.fit_status = dataclasses.I3Particle.FitStatus.OK
particle.pos = thisPosition
particle.dir = direction
particle.time = time
particle.energy = energy
thisParticleName = self.output_particle_name
if i>0: thisParticleName = thisParticleName+"_%i"%i
p_frame[thisParticleName] = particle
p_frame["HealpixPixel"] = icetray.I3Int(int(pixel))
p_frame["HealpixNSide"] = icetray.I3Int(int(self.nside))
# generate a new event header
eventHeader = dataclasses.I3EventHeader(frame["I3EventHeader"])
eventHeader.sub_event_stream = "millipede_scan_nside%04u" % self.nside
eventHeader.sub_event_id = pixel
p_frame["I3EventHeader"] = eventHeader
self.PushFrame(p_frame)
def coincidenceLabel_poly(p_frame):
if is_data(p_frame):
return True
if 'I3MCWeightDict' not in p_frame.keys():
return
poly = p_frame['PolyplopiaCount']
#print('Poly? {}'.format(poly.value))
if poly == icetray.I3Int(0):
coincidence = 0
else:
coincidence = 1
p_frame.Put("multiplicity", icetray.I3Int(coincidence))
return
def FramePacket(self, frames):
n_reduced = 0
oframes = []
for frame in frames:
if (frame.Has("I3EventHeader") and
frame["I3EventHeader"].sub_event_stream == self.splitName):
r = dataclasses.I3RecoPulseSeriesMap.from_frame(
frame, self.pulsesName)
keep = True
if (len(r) == 0):
keep = False
else:
for item in r:
keep = False
if (len(item[1])):
keep = True
break
if (keep):
oframes.append(frame)
else:
n_reduced += 1
else:
oframes.append(frame)
for frame in oframes:
if (frame.Stop == icetray.I3Frame.DAQ):
red_value = frame[self.splitName + "ReducedCount"].value
frame.Delete(self.splitName + "ReducedCount")
frame.Put(self.splitName + "ReducedCount",
icetray.I3Int((red_value + n_reduced)))
self.PushFrame(frame)
def fix_pixel_num(frame):
nside = frame["SCAN_HealpixNSide"].value
pixel = frame["SCAN_HealpixPixel"].value
posvar = frame["SCAN_PositionVariationIndex"].value
header = frame["I3EventHeader"]
# we used to do this to go from pixel to dec/ra:
dec, ra = healpy.pix2ang(nside, pixel)
dec = dec - numpy.pi / 2.
# this is what we *should* have done:
# dec = numpy.pi/2. - dec
new_pixel = healpy.ang2pix(nside, numpy.pi / 2. - dec, ra)
# --- sanity check
# (this is how we *want* this to be converted. Make sure the above did the right thing)
new_dec, new_ra = healpy.pix2ang(nside, new_pixel)
new_dec = numpy.pi / 2. - new_dec
if abs(new_dec - dec) > 1e-7:
raise RuntimeError(
"Logic error in pixel conversion. new_dec={}, dec={}".format(
new_dec, dec))
# --- end sanity check
new_header = copy.copy(header)
new_header.sub_event_id = new_pixel
new_header.sub_event_stream = "SCAN_nside%04u_pixel%04u_posvar%04u" % (
nside, new_pixel, posvar)
del frame["SCAN_HealpixPixel"]
frame["SCAN_HealpixPixel"] = icetray.I3Int(new_pixel)
del frame["I3EventHeader"]
frame["I3EventHeader"] = new_header
def MicroCount(frame):
MicroValuesHits = dataclasses.I3MapStringInt()
MicroValuesPE = dataclasses.I3MapStringDouble()
DTWs = ["DTW175","DTW200", "DTW250", "DTW300"]
for DTW in DTWs:
totalCharge = 0
if not frame.Has("DCFidPulses_" + DTW):
MicroValuesHits["STW9000_" + DTW] = icetray.I3Int(0)
MicroValuesPE["STW9000_" + DTW] = dataclasses.I3Double( totalCharge)
continue
# end if()
for omkey in frame["DCFidPulses_" + DTW].apply(frame):
for pulse in omkey[1]:
totalCharge += pulse.charge
# end for()
# end for()
MicroValuesHits["STW9000_" + DTW] = len(frame["DCFidPulses_" + DTW].apply(frame))
MicroValuesPE["STW9000_" + DTW] = totalCharge
# end for()
frame["MicroCountHits"] = MicroValuesHits
frame["MicroCountPE"] = MicroValuesPE
return
def DAQ(self, frame):
print('DAQ Frame')
self.PushFrame(frame)
for i in range(0, max_phys_frames):
subframe = self.get_next_sub_event(frame)
subframe['TriggerID'] = icetray.I3Int(i)
self.PushFrame(subframe)
return True
def make_and_push_P(self, pspec):
newPframe = I3Frame('P')
for i in range(pspec['nP']):
newPframe = I3Frame('P')
ehP = self.make_header(i, pspec['name'])
newPframe.Put('I3EventHeader', ehP)
newPframe.Put('NCh', icetray.I3Int(
12 + 5 * i)) # note: unphysical nonsense! just for this test.
self.PushFrame(newPframe)
def GetStations(frame, InputITpulses, output):
nstation = 0
if InputITpulses in frame:
vemPulses = frame[InputITpulses]
if vemPulses.__class__ == dc.I3RecoPulseSeriesMapMask:
vemPulses = vemPulses.apply(frame)
stationList = set([pulse.key().string for pulse in vemPulses])
nstation = len(stationList)
frame[output] = icetray.I3Int(nstation)
def CreatePFrame(self, nside, pixel, pixel_index):
dec, ra = healpy.pix2ang(nside, pixel)
dec = numpy.pi/2. - dec
zenith, azimuth = astro.equa_to_dir(ra, dec, self.event_mjd)
zenith = float(zenith)
azimuth = float(azimuth)
direction = dataclasses.I3Direction(zenith,azimuth)
position = self.seed_position
time = self.seed_time
energy = self.seed_energy
for i in range(0,len(self.posVariations)):
posVariation = self.posVariations[i]
p_frame = icetray.I3Frame(icetray.I3Frame.Physics)
thisPosition = dataclasses.I3Position(position.x + posVariation.x, position.y + posVariation.y, position.z + posVariation.z)
# generate the particle from scratch
particle = dataclasses.I3Particle()
particle.shape = dataclasses.I3Particle.ParticleShape.InfiniteTrack
particle.fit_status = dataclasses.I3Particle.FitStatus.OK
particle.pos = thisPosition
particle.dir = direction
particle.time = time
particle.energy = energy
p_frame[self.output_particle_name] = particle
# generate a new event header
eventHeader = dataclasses.I3EventHeader(self.event_header)
eventHeader.sub_event_stream = "SCAN_nside%04u_pixel%04u_posvar%04u" % (nside, pixel, i)
eventHeader.sub_event_id = pixel
p_frame["I3EventHeader"] = eventHeader
p_frame["SCAN_HealpixPixel"] = icetray.I3Int(int(pixel))
p_frame["SCAN_HealpixNSide"] = icetray.I3Int(int(nside))
p_frame["SCAN_PositionVariationIndex"] = icetray.I3Int(int(i))
# an overall sequence index, 0-based, in case we need to re-start
p_frame["SCAN_EventOverallIndex"] = icetray.I3Int( int(i) + pixel_index*len(self.posVariations))
if self.inject_event_name is not None:
p_frame["SCAN_EventName"] = dataclasses.I3String(self.inject_event_name)
self.PushFrame(p_frame)
def coincidenceLabel_poly(physics_frame, gcdfile):
poly = physics_frame['PolyplopiaCount']
#print "Poly {}".format(poly)
if poly == icetray.I3Int(0):
coincidence = 0
#elif poly == icetray.I3Int(0):
# coincidence = 0
else:
coincidence = 1
return coincidence
def set_signature(frame, gcdfile=None, surface=None):
if is_data(frame):
return True
if surface is None:
if gcdfile is None:
surface = icecube.MuonGun.ExtrudedPolygon.from_I3Geometry(
frame['I3Geometry'])
else:
surface = icecube.MuonGun.ExtrudedPolygon.from_file(gcdfile,
padding=0)
if "visible_track" in frame.keys():
p = frame["visible_track"]
intersections = surface.intersection(p.pos, p.dir)
elif "visible_nu" in frame.keys():
p = frame["visible_nu"]
intersections = surface.intersection(p.pos + p.length * p.dir, p.dir)
else:
val = -1
frame.Put("signature", icetray.I3Int(val))
return
if not np.isfinite(intersections.first):
val = -1
elif p.is_neutrino:
if intersections.first <= 0 and intersections.second > 0:
val = 0 # starting event
else:
val = -1 # vertex outside detector
elif p.is_track:
if intersections.first <= 0 and intersections.second > 0:
val = 0 # starting event
elif intersections.first > 0 and intersections.second > 0:
if p.length <= intersections.first:
val = -1 # no hit
elif p.length > intersections.second:
val = 1 # through-going event
else:
val = 2 # stopping event
else:
val = -1 # vertex behind detector
frame.Put("signature", icetray.I3Int(val))
return
def FramePacket(self, frames):
count = 0
for frame in frames:
if (frame.Stop == icetray.I3Frame.Physics):
if (frame.Has("I3EventHeader")):
if (frame["I3EventHeader"].sub_event_stream ==
self.splitname):
count += 1
frames[0].Put(self.splitname + "SplitCount", icetray.I3Int(count))
for frame in frames:
self.PushFrame(frame)
return
def selectFinalFit(frame):
fits = [
"SplineMPE_split", "MPEFit_split", "SPEFit4_split",
"SPEFitSingle_split", "ImprovedLineFit_split"
]
resultName = "TrackFit"
result = None
params = None
for fitName in fits:
if (not frame.Has(fitName)):
continue
fit = frame.Get(fitName)
if (fit.fit_status == dataclasses.I3Particle.OK):
frame.Put(resultName, fit)
frame.Put(resultName + "Fallback",
icetray.I3Int(fits.index(fitName)))
if (frame.Has(fitName + "FitParams")):
frame.Put(resultName + "FitParams",
frame.Get(fitName + "FitParams"))
break
if (not frame.Has(resultName + "Fallback")):
frame.Put(resultName + "Fallback", icetray.I3Int(len(fits)))
def setUpModule():
"""
Generate .i3 file (borrowed from dataio test_randomaccess_file)
"""
i3f = dataio.I3File(test_filename, dataio.I3File.Mode.Writing)
frames = test_frames
for pr in frames:
frame = icetray.I3Frame(icetray.I3Frame.Stream(pr[0]))
frame[pr[0]] = icetray.I3Int(pr[1])
i3f.push(frame)
i3f.close()
def classify_corsika(p_frame, gcdfile=None, surface=None):
if is_data(p_frame):
return True
if surface is None:
if gcdfile is None:
surface = icecube.MuonGun.ExtrudedPolygon.from_I3Geometry(
p_frame['I3Geometry'])
else:
surface = icecube.MuonGun.ExtrudedPolygon.from_file(gcdfile,
padding=0)
mu_list = []
I3Tree = p_frame['I3MCTree']
primaries = I3Tree.get_primaries()
for p in primaries:
tlist = []
find_muons(p, I3Tree, surface, plist=tlist)
mu_list.append(tlist[-1])
if len(np.concatenate(mu_list)) == 0:
pclass = 11 # Passing Track
elif len(mu_list) > 1:
pclass = 21 # several events
clist = np.concatenate(mu_list)
energies = np.array(
[calc_depositedE_single_p(p, I3Tree, surface) for p in clist])
inds = np.argsort(energies)
p_frame.Put("visible_track", clist[inds[-1]])
else:
if len(mu_list[0]) > 1:
energies = np.array([
calc_depositedE_single_p(p, I3Tree, surface)
for p in mu_list[0]
])
mu_signatures = np.array(
[has_signature(p, surface) for p in mu_list[0]])
if np.any(mu_signatures == 1):
pclass = 22 # Through Going Bundle
else:
pclass = 23 # Stopping Muon Bundle
inds = np.argsort(energies)
p_frame.Put("visible_track", mu_list[0][inds[-1]])
else:
if has_signature(mu_list[0][0], surface) == 2:
pclass = 4 # Stopping Track
else:
pclass = 2 # Through Going Track
p_frame.Put("visible_track", mu_list[0][0])
p_frame.Put("classification", icetray.I3Int(pclass))
return
def test_default(self):
h = PhysicsHistogram(0,
10,
10,
"DerivedHistogram",
expression="frame['integer'].value")
for i in range(10):
frame = icetray.I3Frame()
frame["integer"] = icetray.I3Int(i)
h.Physics(frame)
for bin_value in h.bin_values:
self.assertEqual(bin_value, 1)
def Split_Recombine(tray, name, Params=RunParameters()):
#tray.AddModule("Keep","HouseCleaning",
#Keys = ["I3Geometry",
#"I3Calibration",
#"I3DetectorStatus",
#"I3DetectorConfiguration",
#"I3EventHeader",
#"OfflinePulses",
#"I3MCTree"])
# NOTE Define the name of the unultered Pulses in the Q-frame
OrgPulses = "OfflinePulses"
# NOTE Define the name of the subevent stream that you like to create
SplitName = "org"
# NOTE Define how the split Pulses should be named
SplitPulses = "org"
from icecube import CoincSuite
# NOTE Create a complement object <I3Int>(SplitName+"ReducedName") in the Q frame keeping trace of the number of frames which have been recombined
tray.AddModule(
lambda f: f.Put(SplitName + "ReducedCount", icetray.I3Int(0)),
"ReducedCountMaker",
Streams=[icetray.I3Frame.DAQ])
# NOTE Discard frames that you do not want to concider for recombinations early on.
# NOTE every discarded frame should be accounted for by increasing the 'ReducedCount'
tray.AddModule(
"AfterpulseDiscard",
"AfterpulseDiscard",
SplitName=
SplitName, #NOTE Run on the splitframes; this paramater should be set for all modules
RecoMapName=
SplitPulses, #NOTE use the SplitPulses; this paramater should be set for all modules
QTotFraction=.1,
TimeOffset=3.E3 * I3Units.ns,
OverlapFraction=0.75)
# NOTE remove the frames the you do not want to use
# tray.AddModule(lambda f: which_split(f,split_name=SplitName) and f.Has("Afterpulse"), "KillAfterpulseFrame")
# NOTE create the HypoFrames from all remaining SplitFrames
tray.AddModule(
"HypoFrameCreator",
"ForceHypoFrames",
SplitName=SplitName,
HypoName="hypoframe", # NOTE give the stream of Hypoframes a unique name
RecoMapName=SplitPulses,
MaxTimeSeparation=3000. * I3Units.ns
) # NOTE specify that frames timely spaced too far apart should not be recombined
def test_fill(self):
h = DerivedHistogram(0, 10, 10, "DerivedHistogram")
for i in range(10):
frame = icetray.I3Frame()
frame["integer"] = icetray.I3Int(i)
h.DAQ(frame)
frame = icetray.I3Frame()
frame["integer"] = icetray.I3Int(-1)
h.DAQ(frame)
frame = icetray.I3Frame()
frame["integer"] = icetray.I3Int(10)
h.DAQ(frame)
self.assertEqual(len(h.bin_values), 10)
self.assertEqual(h.name, "DerivedHistogram")
for bin_value in h.bin_values:
self.assertEqual(bin_value, 1)
self.assertEqual(h.overflow, 1)
self.assertEqual(h.underflow, 1)
def classify_muongun(p_frame,
gcdfile=None,
surface=None,
primary_key='MCPrimary'):
p = p_frame[primary_key]
if has_signature(p, surface) == 1:
pclass = 2 # Through Going Track
elif has_signature(p, surface) == 2:
pclass = 4 # Stopping Track
else:
pclass = 0
p_frame.Put("classification_truth_id", icetray.I3Int(pclass))
p_frame.Put("classification_truth", dataclasses.I3String(decode[pclass]))
p_frame.Put("visible_track", p)
return
def classify_muongun(p_frame, gcdfile=None, surface=None, primary_key='MCPrimary'):
if is_data(p_frame):
return True
if surface is None:
if gcdfile is None:
surface = icecube.MuonGun.ExtrudedPolygon.from_I3Geometry(p_frame['I3Geometry'])
else:
surface = icecube.MuonGun.ExtrudedPolygon.from_file(gcdfile, padding=0)
p = p_frame[primary_key]
if has_signature(p, surface) == 1:
pclass = 2 # Through Going Track
elif has_signature(p, surface) == 2:
pclass = 4 # Stopping Track
else:
pclass = 0
p_frame.Put("classification", icetray.I3Int(pclass))
p_frame.Put("visible_track", p)
return
def test_daq(self):
'''
This tests that nothing happens when the DAQ
method is called.
'''
h = PhysicsHistogram(0,
10,
10,
"DerivedHistogram",
expression="frame['integer'].value")
for i in range(10):
frame = icetray.I3Frame()
frame["integer"] = icetray.I3Int(i)
h.DAQ(frame)
# all the bins should still be empty
for bin_value in h.bin_values:
self.assertEqual(bin_value, 0)
def classify_corsika(p_frame, gcdfile=None, surface=None):
mu_list = []
I3Tree = p_frame['I3MCTree']
primaries = I3Tree.get_primaries()
for p in primaries:
tlist = []
find_muons(p, I3Tree, surface, plist=tlist)
mu_list.append(tlist[-1])
if len(np.concatenate(mu_list)) == 0:
pclass = 11 # Passing Track
elif len(mu_list) > 1:
pclass = 21 # several events
clist = np.concatenate(mu_list)
energies = np.array(
[calc_depositedE_single_p(p, I3Tree, surface) for p in clist])
inds = np.argsort(energies)
p_frame.Put("visible_track", clist[inds[-1]])
else:
if len(mu_list[0]) > 1:
energies = np.array([
calc_depositedE_single_p(p, I3Tree, surface)
for p in mu_list[0]
])
mu_signatures = np.array(
[has_signature(p, surface) for p in mu_list[0]])
if np.any(mu_signatures == 1):
pclass = 22 # Through Going Bundle
else:
pclass = 23 # Stopping Muon Bundle
inds = np.argsort(energies)
p_frame.Put("visible_track", mu_list[0][inds[-1]])
else:
if has_signature(mu_list[0][0], surface) == 2:
pclass = 4 # Stopping Track
else:
pclass = 2 # Through Going Track
p_frame.Put("visible_track", mu_list[0][0])
p_frame.Put("classification_truth_id", icetray.I3Int(pclass))
p_frame.Put("classification_truth", dataclasses.I3String(decode[pclass]))
return
def FramePacket(self, frames):
reducedValue = 0
qframe = frames[0]
if (qframe.Has(self.splitName + "SplitCount")):
splits = qframe[self.splitName + "SplitCount"].value
nsplitframes = 0
for frame in frames:
if (frame.Has("I3EventHeader")):
if (frame["I3EventHeader"].sub_event_stream ==
self.splitName):
nsplitframes += 1
reducedValue = splits - nsplitframes
if (reducedValue < 0):
icetray.logging.log_fatal(
"Something is wrong with your SplitCount-variable")
qframe.Put(self.splitName + "ReducedCount",
icetray.I3Int(reducedValue))
for frame in frames:
self.PushFrame(frame)
return
def Physics(self, frame):
q_tot = -1.0
n_channels = -1
max_charge_frac = -1.0
if self.inice_pulses in frame:
VEMpulses = frame[self.inice_pulses]
if VEMpulses.__class__ == dc.I3RecoPulseSeriesMapMask:
VEMpulses = VEMpulses.apply(frame)
charge_list = []
n_channels = 0
for om, pulses in VEMpulses:
n_channels += 1
for pulse in pulses:
charge_list += [pulse.charge]
q_tot = sum(charge_list)
max_charge_frac = max(charge_list)/q_tot
frame.Put('InIce_charge', dc.I3Double(q_tot))
frame.Put('NChannels', icetray.I3Int(n_channels))
frame.Put('max_charge_frac', dc.I3Double(max_charge_frac))
self.PushFrame(frame)
def CalculateNAbove200( frame, PulseSeries, ConfigID):
# Loop over all the triggers looking
# for the times of all the selected triggers
triggerTimes = []
for trigger in frame[ "I3TriggerHierarchy"]:
if trigger.key.config_id == ConfigID:
triggerTimes.append( trigger.time)
# end if()
# end for()
# Check that there is at least one of the
# selected triggers.
if len(triggerTimes) == 0:
frame[ "NAbove200"] = icetray.I3Int( 0)
return
# end if()
triggerTimes.sort()
earliestTriggerTime = triggerTimes[0]
chargeCounter = 0
geometry = frame[ "I3Geometry"]
for omkey in frame[ PulseSeries]:
if not geometry.omgeo[ omkey[0]].position.z > -200 * I3Units.m:
continue
# end if()
for pulse in omkey[1]:
if (pulse.time - earliestTriggerTime) < 0 and (pulse.time - earliestTriggerTime) > -2000:
chargeCounter += pulse.charge
# end if()
# end for()
# end for()
frame[ "NAbove200"] = dataclasses.I3Double( chargeCounter)
return
def Process(self):
""" deliver frames QP with only a bit of rudamentary information """
#make a Q-frame
Qframe = icetray.I3Frame(icetray.I3Frame.DAQ)
Qeh = dataclasses.I3EventHeader()
Qeh.start_time = (dataclasses.I3Time(2011, 0))
Qeh.end_time = (dataclasses.I3Time(2011, 2))
Qeh.run_id = 1
Qeh.event_id = 1
Qframe.Put("I3EventHeader", Qeh)
Qrecomap = dataclasses.I3RecoPulseSeriesMap()
recopulse1 = dataclasses.I3RecoPulse()
recopulse1.time = 0
recopulse1.charge = 1
recopulse2 = dataclasses.I3RecoPulse()
recopulse2.time = 1
recopulse2.charge = 2
Qrecomap[icetray.OMKey(1,1)] = [recopulse1]
Qrecomap[icetray.OMKey(2,2)] = [recopulse2]
Qframe.Put(OrgPulses, Qrecomap)
Qframe.Put(SplitName+"SplitCount", icetray.I3Int(1))
self.PushFrame(Qframe)
#now make the first p-frame containing one I3RecoPulse
P1frame = icetray.I3Frame(icetray.I3Frame.Physics)
P1eh = dataclasses.I3EventHeader()
P1eh.start_time = (dataclasses.I3Time(2011, 0))
P1eh.end_time = (dataclasses.I3Time(2011, 1))
P1eh.run_id = 1
P1eh.event_id = 1
P1eh.sub_event_stream = "split"
P1eh.sub_event_id = 0
P1frame.Put("I3EventHeader", P1eh)
P1recomap = dataclasses.I3RecoPulseSeriesMap()
P1recomap[icetray.OMKey(1,1)] = [recopulse1]
P1recomask = dataclasses.I3RecoPulseSeriesMapMask(Qframe, OrgPulses, Qrecomap)
P1frame.Put(SplitPulses, P1recomask)
self.PushFrame(P1frame)
self.RequestSuspension()
def putints(frame, where, value):
frame[where] = icetray.I3Int(value)
print('put value %s at %s' % (value, where))
