def splitPulses(frame):
'''
Count number of times a particular station is hit. HLC has two hits on a station and SLC has only one.
Form a dictionary with station number and number of time its hit.
If the count is 2 or more put that pulse in HLC, if the number of hit is only one then put that pulse in
SLC pulse.
'''
hlc_pulses = dataclasses.I3RecoPulseSeriesMap()
slc_pulses = dataclasses.I3RecoPulseSeriesMap()
seededRTpulses = dataclasses.I3RecoPulseSeriesMap.from_frame(
frame, 'IT_RT_180m_450ns')
stations = {}
keepomkeys = []
removeomkeys = []
for omkey, pulse in seededRTpulses:
if omkey.string not in stations:
stations[omkey.string] = 1
else:
stations[omkey.string] += 1
for omkey, pulse in seededRTpulses:
if stations[
omkey.string] >= 2: # HLC has hit on two tanks of a station.
hlc_pulses[omkey] = pulse
else:
slc_pulses[omkey] = pulse # SLC has hit on one tank of a station.
# Now save them in a container.
frame["SeededRTHLCPulses"] = hlc_pulses
frame["SeededRTSLCPulses"] = slc_pulses
def combine_pulse(frame):
if (HLCPulse in frame) and (SLCPulse in frame):
combined_pulse = dataclasses.I3RecoPulseSeriesMap()
removedSLCQcut = dataclasses.I3RecoPulseSeriesMap()
cleanhlcpulse = dataclasses.I3RecoPulseSeriesMap.from_frame(
frame, HLCPulse)
offlineslcpulse = frame[SLCPulse]
for omkey, pulse in cleanhlcpulse:
if omkey not in combined_pulse:
combined_pulse[omkey] = pulse
else:
pulselist = combined_pulse[omkey]
for pul in pulse:
pulselist.append(pul)
#for slcomkey, slcpulse in offlineslcpulse:
# if slcomkey not in combined_pulse:
# combined_pulse[slcomkey]=slcpulse
# else:
# pulselistslc = combined_pulse[slcomkey]
# for pulslc in slcpulse:
# pulselistslc.append(pulslc)
#frame['CombinedHLCSLCPulse'] = combined_pulse
for slcomkey, slcpulse in offlineslcpulse:
for pul in slcpulse:
if pul.charge > 0.8:
if slcomkey not in combined_pulse:
#combined_pulse[slcomkey]=slcpulse
combined_pulse[slcomkey] = [pul]
else:
pulselistslc = combined_pulse[slcomkey]
#for pulslc in slcpulse:
pulselistslc.append(pul)
frame['CombinedHLCSLCPulse'] = combined_pulse
def Process(self):
if not self.geometry:
self.geometry = True
geometry = dc.I3Geometry()
for string in self.strings:
for dom in self.doms:
omkey= icetray.OMKey(string,dom)
geometry.omgeo[omkey] = dc.I3OMGeo()
x=random.uniform(-500,500)
y=random.uniform(-500,500)
z=random.uniform(-300,300)
geometry.omgeo[omkey].position = dc.I3Position(x,y,z)
frame = icetray.I3Frame(icetray.I3Frame.Geometry);
frame.Put('I3Geometry',geometry)
self.PushFrame(frame)
pulsesmap= dc.I3RecoPulseSeriesMap()
for string in self.strings:
for dom in self.doms:
omkey= icetray.OMKey(string,dom)
pulse= dc.I3RecoPulse()
pulse.charge= random.uniform(0.3,6.)#pulses are not used in the algorithm of this module,
#just put a single pulse with any value of the charge
pulsesmap[omkey]= dc.I3RecoPulseSeries([pulse])
frame = icetray.I3Frame(icetray.I3Frame.Physics);
frame.Put("TestPulseSeriesMap",pulsesmap)
self.PushFrame(frame)
def setUp(self):
self.frame = icetray.I3Frame(icetray.I3Frame.Physics)
pulses = dataclasses.I3RecoPulseSeriesMap()
key1 = icetray.OMKey(42, 7)
vec = dataclasses.I3RecoPulseSeries()
pulse = dataclasses.I3RecoPulse()
pulse.time = 1.0
pulse.charge = 2.3
vec.append(pulse)
pulse.time = 2.0
vec.append(pulse)
pulse.time = 15.0
vec.append(pulse)
pulses[key1] = vec
key2 = icetray.OMKey(7, 7)
vec = dataclasses.I3RecoPulseSeries()
pulse.time = 1.0
pulse.charge = 2.3
vec.append(pulse)
pulse.time = 2.0
vec.append(pulse)
pulse.time = 15.0
vec.append(pulse)
pulses[key2] = vec
self.frame['Pulses'] = pulses
mask1 = dataclasses.I3RecoPulseSeriesMapMask(self.frame, 'Pulses')
mask1.set(key1, 1, False)
self.frame['Mask1'] = mask1
mask2 = dataclasses.I3RecoPulseSeriesMapMask(self.frame, 'Pulses')
mask2.set(key2, 1, False)
self.frame['Mask2'] = mask2
def make_rpsmap():
rpsmap = dataclasses.I3RecoPulseSeriesMap()
for omkey in doms:
rpsmap[omkey] = dataclasses.I3RecoPulseSeries()
# time, width, and charge
rp_properties = [(1650, 100, 0), (1850, 100, 1), (0, 100, 2), (550, 0, 3),
(800, 0, 4), (3500, 100, 5), (3500, 100, 6),
(3500, 100, 7), (3500, 100, 8), (8000, 3000, 9),
(9000, 100, 10), (9500, 100, 11)]
rp_list = [dataclasses.I3RecoPulse() for i in range(len(rp_properties))]
for idx, prop in enumerate(rp_properties):
rp_list[idx].time = prop[0]
rp_list[idx].width = prop[1]
rp_list[idx].charge = prop[2]
rpsmap[doms[0]].append(rp_list[0])
rpsmap[doms[0]].append(rp_list[1])
rpsmap[doms[0]].append(rp_list[2])
rpsmap[doms[1]].append(rp_list[3])
rpsmap[doms[2]].append(rp_list[4])
rpsmap[doms[2]].append(rp_list[5])
rpsmap[doms[3]].append(rp_list[6])
rpsmap[doms[3]].append(rp_list[7])
rpsmap[doms[4]].append(rp_list[8])
rpsmap[doms[4]].append(rp_list[9])
rpsmap[doms[4]].append(rp_list[10])
rpsmap[doms[4]].append(rp_list[11])
return rpsmap
def discard_random_doms(self, pulses, discard_probability, *args, **kwargs):
"""Discard DOMs randomly based on the discard_probability.
Parameters
----------
pulses : I3RecoPulseSeriesMap
Pulses to modify.
discard_probability : float
The probabilty a DOM is discarded. Must be a value between 0 and 1.
*args
Variable length argument list.
**kwargs
Arbitrary keyword arguments.
Returns
-------
I3RecoPulseSeriesMap
The modified pulses.
"""
assert discard_probability >= 0 and discard_probability <= 1, \
'discard_probability {!r} not in [0, 1]'.format(discard_probability)
modified_pulses = {}
for key, dom_pulses in pulses.items():
# draw random variable and decide if DOM is discarded
discard_dom = self._random_generator.uniform() < discard_probability
# add DOM
if not discard_dom:
modified_pulses[key] = \
dataclasses.vector_I3RecoPulse(dom_pulses)
return dataclasses.I3RecoPulseSeriesMap(modified_pulses)
def _add_mc_pulses(self, frame, mcpe_series_map):
'''Create MC reco pulses from I3MCPESeriesMap
This is a dirty hack, so that other modules can be used without
changing them. However, this will use up unecessary space, because
I3RecoPulses have more data fields, which are not required by an
MC hit (width, ATWD, ...) .
Parameters
----------
frame : I3Frame
The I3Frame to which the MC Pulses will be added to.
mcpe_series_map : I3MCPESeriesMap
The I3MCPESeriesMap which will be converted.
'''
mc_pulse_map = dataclasses.I3RecoPulseSeriesMap()
for omkey, mcpe_series in mcpe_series_map.items():
mc_pulses = []
for mcpe in mcpe_series:
# create I3RecoPulse with corresponding time and 'charge'
# The charge is set to the number of photo electrons (npe)
mc_pulse = dataclasses.I3RecoPulse()
mc_pulse.time = mcpe.time
mc_pulse.charge = mcpe.npe
# append pulse
mc_pulses.append(mc_pulse)
mc_pulse_map[omkey] = dataclasses.vector_I3RecoPulse(mc_pulses)
# write to frame
frame[self._output_key] = mc_pulse_map
def gaussian_smear_pulse_times(self, pulses, scale, *args, **kwargs):
"""Smear the pulse times with a Gaussian centered at the original value.
Parameters
----------
pulses : I3RecoPulseSeriesMap
Pulses to modify.
scale : float
The scale parameter of the Gaussian that is used to smear the pulse
times.
*args
Variable length argument list.
**kwargs
Arbitrary keyword arguments.
Returns
-------
I3RecoPulseSeriesMap
The modified pulses.
"""
assert scale >= 0, 'scale {!r} must be >= zero'.format(scale)
modified_pulses = {}
for key, dom_pulses in pulses.items():
# smear times
times = self._random_generator.normal(loc=[p.time for p in dom_pulses],
scale=scale)
charges = np.array([p.charge for p in dom_pulses])
widths = np.array([p.width for p in dom_pulses])
flags = np.array([p.flags for p in dom_pulses])
# sort pulses in time
sorted_indices = np.argsort(times)
charges = charges[sorted_indices]
times = times[sorted_indices]
widths = widths[sorted_indices]
flags = flags[sorted_indices]
modified_dom_pulses = []
for charge, time, flag, width in zip(charges, times, flags, widths):
# create pulse
modified_pulse = dataclasses.I3RecoPulse()
modified_pulse.charge = charge
modified_pulse.time = time
modified_pulse.flags = int(flag)
modified_pulse.width = width
# append pulse
modified_dom_pulses.append(modified_pulse)
modified_pulses[key] = dataclasses.vector_I3RecoPulse(
fix_time_overlap(modified_dom_pulses))
return dataclasses.I3RecoPulseSeriesMap(modified_pulses)
def I3SuperDSTPacker(frame, Pulses='Pulses', Output='I3SuperDST'):
"""
Create a compressed representation of the reco pulses,
using I3SuperDST.
"""
if Pulses not in frame:
pulses_ = dataclasses.I3RecoPulseSeriesMap()
else:
pulses_ = dataclasses.I3RecoPulseSeriesMap.from_frame(
frame, Pulses)
frame[Output] = dataclasses.I3SuperDST(pulses_)
def Physics(self, frame):
rpsmap = dataclasses.I3RecoPulseSeriesMap()
doms = [icetray.OMKey(0, i) for i in range(4)]
for omkey, time in zip(doms, self.times):
rp = dataclasses.I3RecoPulse()
rp.time = time
rps = dataclasses.I3RecoPulseSeries()
rps.append(rp)
rpsmap[omkey] = rps
frame[self.output_map_name] = rpsmap
self.PushFrame(frame)
def I3MapKeyVectorDouble_to_I3RecoPulseSeriesMap(f):
i3MapKeyVectorDouble = f['splittedDOMMap']
i3RecoPulseSeriesMap = dataclasses.I3RecoPulseSeriesMap()
for (k, l) in i3MapKeyVectorDouble.items():
pulses = dataclasses.I3RecoPulseSeries()
for d in l:
p = dataclasses.I3RecoPulse()
p.time = d
pulses.append(p)
i3RecoPulseSeriesMap[k] = pulses
f['splittedDOMMap_pulses'] = i3RecoPulseSeriesMap
def FramePacket(self, frames):
mctree = dataclasses.I3MCTree()
mask = dataclasses.I3RecoPulseSeriesMapMask(
frames[0], self.pulseSourceName,
dataclasses.I3RecoPulseSeriesMap())
for frame in frames:
if (frame.Stop == icetray.I3Frame.Physics):
if (frame["I3EventHeader"].sub_event_stream == self.splitName):
smallmctree = dataclasses.I3MCTree()
#need to have the time range
if (not frame.Has(self.recoMapName + "TimeRange")):
time_pulses = []
pulses = dataclasses.I3RecoPulseSeriesMap.from_frame(
frame, self.recoMapName)
for item in pulses:
for pulse in item[1]:
time_pulses.append(pulse.time)
time_pulses = numpy.array(time_pulses)
frame.Put(
self.recoMapName + "TimeRange",
dataclasses.I3TimeWindow(time_pulses.min(),
time_pulses.max()))
#now do the composition work
tr = frame[self.recoMapName + "TimeRange"]
part = frame[self.fitName]
primary = deepcopy(frame[self.fitName])
inparticle = deepcopy(frame[self.fitName])
outparticle = deepcopy(frame[self.fitName])
#primary.pos = part.shift_along_track((tr.start-part.time)*part.speed)
primary.type = dataclasses.I3Particle.NuMuBar #NuMuBar
primary.shape = dataclasses.I3Particle.Primary #InfiniteTrack #ContainedTrack #StoppingTrack
#primary.time = tr.start
primary.energy = 1
#primary.length = part.speed*(tr.start-tr.stop)
mctree.add_primary(primary)
smallmctree.add_primary(primary)
inparticle.type = dataclasses.I3Particle.MuMinus
inparticle.shape = dataclasses.I3Particle.ContainedTrack
inparticle.energy = 1
inparticle.length = part.speed * (tr.start - tr.stop)
inparticle.time = tr.start
#inparticle.pos = part.shift_along_track((tr.start-part.time)*part.speed)
mctree.append_child(primary, inparticle)
smallmctree.append_child(primary, inparticle)
mask = mask | frame[self.recoMapName]
frame.Put("smallTree" + self.fitName, smallmctree)
frames[0].Put("coll" + self.recoMapName, mask)
frames[0].Put("coll" + self.fitName, mctree)
for frame in frames:
self.PushFrame(frame)
def shift_pulses(self, pulses, charge_shift=None, time_shift=None,
first_k_pulses=float('inf'), *args, **kwargs):
"""Shift the charges and times of the provided pulses.
There is an option to ony shift the first k number of pulses by providing
a value to first_k_pulses.
Parameters
----------
pulses : I3RecoPulseSeriesMap
Pulses to modify.
charge_shift : float, optional
The amount to shift the pulse charges.
time_shift : float, optional
The amount to shift the pulse times.
first_k_pulses : int, optional
If specified, only shift the first_k_pulses of a DOM.
*args
Variable length argument list.
**kwargs
Arbitrary keyword arguments.
Returns
-------
I3RecoPulseSeriesMap
The modified pulses.
"""
modified_pulses = {}
for key, dom_pulses in pulses.items():
modified_dom_pulses = []
pulse_counter = 0
for pulse in dom_pulses:
modified_pulse = dataclasses.I3RecoPulse(pulse)
pulse_counter += 1
# modify pulse
if pulse_counter <= first_k_pulses:
if time_shift is not None:
modified_pulse.time += time_shift
if charge_shift is not None:
modified_pulse.charge = np.clip(
modified_pulse.charge + charge_shift, 0., float('inf'))
# append pulse
modified_dom_pulses.append(modified_pulse)
modified_pulses[key] = \
dataclasses.vector_I3RecoPulse(modified_dom_pulses)
return dataclasses.I3RecoPulseSeriesMap(modified_pulses)
def fakeit(frame): header = dataclasses.I3EventHeader() frame['I3EventHeader'] = header pulsemap = dataclasses.I3RecoPulseSeriesMap() pulses = dataclasses.I3RecoPulseSeries() pulse = dataclasses.I3RecoPulse() pulses.append(pulse) pulsemap[icetray.OMKey(7,42)] = pulses pulsemap[icetray.OMKey(9,42)] = pulses frame['Pulses'] = pulsemap mask = dataclasses.I3RecoPulseSeriesMapMask(frame, 'Pulses') frame['PulseMask'] = mask
def _get_pulses(self, frame):
"""Get the I3RecoPulseSeriesMap from the frame.
Parameters
----------
frame : I3Frame
The current I3Frame.
"""
pulses = frame[self.pulse_key]
if isinstance(pulses, dataclasses.I3RecoPulseSeriesMapMask) or \
isinstance(pulses, dataclasses.I3RecoPulseSeriesMapUnion):
pulses = pulses.apply(frame)
return dataclasses.I3RecoPulseSeriesMap(pulses)
def fixDST(fr, pulseMaskName, newPulseMapName):
if pulseMaskName in fr:
pulsemap = fr[pulseMaskName].apply(fr)
newMap = dataclasses.I3RecoPulseSeriesMap()
for (omkey, pulses) in pulsemap:
series = dataclasses.I3RecoPulseSeries()
for p in pulses:
if p.width <= 0.:
p.time -= 0.51 * I3Units.ns
p.width = 0.5 * I3Units.ns
series.append(p)
newMap[omkey] = series
fr[newPulseMapName] = newMap
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 Physics(self, frame):
pulse_map = dataclasses.I3RecoPulseSeriesMap()
for string in range(1, n_strings + 1):
for om in range(1, n_doms + 1):
om_key = icetray.OMKey(string, om)
n_hits = np.random.poisson(lam=self.lambda_poisson)
times = (np.random.random(n_hits) * self.event_length).round(1)
pulse_series = dataclasses.I3RecoPulseSeries()
for time in sorted(times):
pulse = dataclasses.I3RecoPulse()
pulse.time = time
pulse.charge = 1.0
pulse_series.append(pulse)
pulse_map[om_key] = pulse_series
frame["SLOPPOZELA_Pulses"] = pulse_map
self.PushFrame(frame)
def setUp(self):
super(I3RecoPulseSeriesMapMaskTest2, self).setUp()
# create a pulse series map with a known bad
# 0 width case. only two pulses.
self.pulses = dataclasses.I3RecoPulseSeriesMap()
key1 = icetray.OMKey(42, 7)
vec = dataclasses.I3RecoPulseSeries()
pulse = dataclasses.I3RecoPulse()
pulse.time = 10226.6
pulse.charge = 28.1466
pulse.width = 0.833585
vec.append(pulse)
pulse.time = 10227.4
pulse.charge = 18.5683
pulse.width = 0.833585
vec.append(pulse)
self.pulses[key1] = vec
def Physics(self, frame):
"""Modifies pulses as specified in modification.
Parameters
----------
frame : I3Frame
Current i3 frame.
"""
# get pulses
pulses = frame[self._pulse_key]
if isinstance(pulses, dataclasses.I3RecoPulseSeriesMapMask) or \
isinstance(pulses, dataclasses.I3RecoPulseSeriesMapUnion):
pulses = pulses.apply(frame)
# make copy of pulses
pulses = copy.copy(dataclasses.I3RecoPulseSeriesMap(pulses))
# get modification function
modification_func = getattr(pulse_modification_functions,
self._modification)
# apply modification to pulses
modified_pulses = modification_func(
self,
pulses,
dom_noise_rate_dict=self._dom_noise_rate,
frame=frame,
**self._modification_settings)
# write to frame
if self._out_key is None:
frame[self._pulse_key + '_mod'] = modified_pulses
frame[self._pulse_key +
'_modTimeRange'] = dataclasses.I3TimeWindow(
frame[self._pulse_key + 'TimeRange'])
else:
frame[self._out_key] = copy.copy(modified_pulses)
if self._pulse_key + 'TimeRange' in frame.keys():
frame[self._out_key +
'_modTimeRange'] = dataclasses.I3TimeWindow(
frame[self._pulse_key + 'TimeRange'])
# push frame
self.PushFrame(frame)
def mcpulse_to_recopulse(frame, mapname = "I3MCPulseSeriesMap", outputmap = "I3RecoPulseSeriesMap"):
'''
A module that does a direct conversion of I3MCPulses to I3RecoPulses.
It is intended to be used with PMTResponseSimulator output when one
wants to avoid the DOM simulation for some reason (no DOM electronic simulation. ie no launches but
PMT effects such as saturation is present).
'''
recopulsemap = dataclasses.I3RecoPulseSeriesMap()
mcpulsemap = frame[mapname]
for omkey, pulses in mcpulsemap:
recopulsemap[omkey] = dataclasses.I3RecoPulseSeries()
for pulse in pulses:
rpulse = dataclasses.I3RecoPulse()
rpulse.time = pulse.time
rpulse.charge = pulse.charge
rpulse.flags = dataclasses.I3RecoPulse.PulseFlags.LC
recopulsemap[omkey].append(rpulse)
frame[outputmap] = recopulsemap
def discard_k_highest_charge_doms(self, pulses, k, *args, **kwargs):
"""Discard the top k DOMs that have the most charge.
Parameters
----------
pulses : I3RecoPulseSeriesMap
Pulses to modify.
k : int
The number of DOMs to discard.
*args
Variable length argument list.
**kwargs
Arbitrary keyword arguments.
Returns
-------
I3RecoPulseSeriesMap
The modified pulses.
"""
assert k >= 0, 'k {!r} must be >= zero'.format(k)
# calculate total charge for each DOM
dom_charges = []
keys = []
for key, dom_pulses in pulses.items():
dom_charge = np.sum([p.charge for p in dom_pulses])
dom_charges.append(dom_charge)
keys.append(key)
sorted_indices = np.argsort(dom_charges)
sorted_keys = [keys[i] for i in sorted_indices]
top_k = np.clip(k, 0, len(keys))
modified_pulses = {}
for key in sorted_keys[:-top_k]:
# add DOM
modified_pulses[key] = \
dataclasses.vector_I3RecoPulse(pulses[key])
return dataclasses.I3RecoPulseSeriesMap(modified_pulses)
def Create_PulseSeriesMap(frame):
pulsesmap = dc.I3RecoPulseSeriesMap()
p1 = dc.I3RecoPulse()
p1.charge = 2.3
p1.time = 5.1
p2 = dc.I3RecoPulse()
p2.charge = 1.5
p2.time = 9.1
pulsesmap[icetray.OMKey(10, 4)] = dc.I3RecoPulseSeries([p1, p2])
p1 = dc.I3RecoPulse()
p1.charge = 4.5
p1.time = 43.1
p2 = dc.I3RecoPulse()
p2.charge = 0.9
p2.time = 1.2
pulsesmap[icetray.OMKey(25, 13)] = dc.I3RecoPulseSeries([p1, p2])
frame.Put("TestRecoPulseSeriesMap", pulsesmap)
def Physics(self, frame):
pulse_map = dataclasses.I3RecoPulseSeriesMap()
for string in range(51, 60):
track_time = self.event_length / 9 * (string - 50)
for om in range(40, 45):
om_key = icetray.OMKey(string, om)
n_hits = np.random.poisson(lam=3)
times = (np.random.random(n_hits) * 50000 - 25000 +
track_time).round(1)
pulse_series = dataclasses.I3RecoPulseSeries()
for time in sorted(times):
pulse = dataclasses.I3RecoPulse()
pulse.time = time
pulse.charge = 1.0
pulse.flags = 7
pulse_series.append(pulse)
pulse_map[om_key] = pulse_series
frame["SLOPPORATOR_Pulses"] = pulse_map
self.PushFrame(frame)
def scramble_charges(self, pulses, *args, **kwargs):
"""Scramble the charges of the pulses.
Parameters
----------
pulses : I3RecoPulseSeriesMap
Pulses to modify.
*args
Variable length argument list.
**kwargs
Arbitrary keyword arguments.
Returns
-------
I3RecoPulseSeriesMap
The modified pulses.
"""
modified_pulses = {}
for key, dom_pulses in pulses.items():
charges = [p.charge for p in dom_pulses]
# scramble pulse charges
self._random_generator.shuffle(charges)
modified_dom_pulses = []
for pulse, charge in zip(dom_pulses, charges):
modified_pulse = dataclasses.I3RecoPulse(pulse)
# modify pulse
modified_pulse.charge = charge
# append pulse
modified_dom_pulses.append(modified_pulse)
modified_pulses[key] = \
dataclasses.vector_I3RecoPulse(modified_dom_pulses)
return dataclasses.I3RecoPulseSeriesMap(modified_pulses)
def effective_domsim(frame, mapname = "I3MCPulseSeriesMap", outputmap = "I3RecoPulseSeriesMap"):
'''
A module similar to mcpulse_to_recopulse above. It does an effective DOM
electronics simulation by adding jitter to the time and charge to the pulse
while converting the MCPulse to a reco pulse. The values for the spread of the gaussian
jitter were found by studying the spread of 1PE extracted pulses.
The module is intended to be use with the PMTResponseSimulator output in situations
when one wants to avoid the actual DOM simulation for some reason.
'''
from icecube.icetray import I3Units
recopulsemap = dataclasses.I3RecoPulseSeriesMap()
mcpulsemap = frame[mapname]
for omkey, pulses in mcpulsemap:
recopulsemap[omkey] = dataclasses.I3RecoPulseSeries()
for pulse in pulses:
rpulse = dataclasses.I3RecoPulse()
rpulse.time = random_service.gaus(pulse.time,2.0*I3Units.ns)
rpulse.charge = random_service.gaus(pulse.charge,0.012)#PE
rpulse.flags = dataclasses.I3RecoPulse.PulseFlags.LC
recopulsemap[omkey].append(rpulse)
frame[outputmap] = recopulsemap
def FramePacket(self, frames):
partvec = dataclasses.I3VectorI3Particle()
mask = dataclasses.I3RecoPulseSeriesMapMask(
frames[0], self.pulseSourceName,
dataclasses.I3RecoPulseSeriesMap())
for frame in frames:
if (frame.Stop == icetray.I3Frame.Physics):
if (frame["I3EventHeader"].sub_event_stream == self.splitName):
primary = deepcopy(frame[self.fitName])
primary.type = dataclasses.I3Particle.MuMinus
primary.shape = dataclasses.I3Particle.ContainedTrack
primary.length = 500 #part.speed*(tr.start-tr.stop)
partvec.append(frame[self.fitName])
mask = mask | frame[self.recoMapName]
frame.Put("Primary", primary)
frames[0].Put(self.outputPrefix + self.recoMapName, mask)
frames[0].Put(self.outputPrefix + self.fitName, partvec)
for frame in frames:
self.PushFrame(frame)
def Create_PulseSeriesMap(frame):
pulsesmap= dc.I3RecoPulseSeriesMap()
p1=dc.I3RecoPulse()
p1.charge=2.3
p1.time=1.0*icetray.I3Units.ns
p1.width=.0*icetray.I3Units.ns
p2=dc.I3RecoPulse()
p2.charge=1.5
p2.time=2.*icetray.I3Units.ns
p2.width=.0*icetray.I3Units.ns
pulsesmap[icetray.OMKey(10,4)]= dc.I3RecoPulseSeries([p1,p2])
p1=dc.I3RecoPulse()
p1.charge=4.5
p1.time=3.0*icetray.I3Units.ns
p1.width=.0*icetray.I3Units.ns
p2=dc.I3RecoPulse()
p2.charge=0.9
p2.time=802.*icetray.I3Units.ns #will find two pulses (in OMKey(10,4)) that are not in the window of 800 ns
p2.width=.0*icetray.I3Units.ns
pulsesmap[icetray.OMKey(10,5)]= dc.I3RecoPulseSeries([p1,p2])
frame.Put("TestRecoPulseSeriesMap",pulsesmap)
def Physics(self, frame):
source = frame[self.pulses]
if type(source) != dataclasses.I3RecoPulseSeriesMap:
source = dataclasses.I3RecoPulseSeriesMap.from_frame(
frame, self.pulses)
vetopulses = dataclasses.I3RecoPulseSeriesMap()
for key, pulses in source.iteritems():
if key.string > 86 and key.om <= self.nRows: #key.om starts in 1
if self.omgeomap[key].omtype == 120: #degg
if key.pmt == 0:
vetopulses[key] = pulses
elif self.omgeomap[key].omtype == 130: #mdom
if key.pmt < 12: # from 0 to 11
vetopulses[key] = pulses
nvetohits = 0
chargevetohits = 0.
ndiffmodules_vetohits_set = set()
for key, pulses in vetopulses.iteritems():
for pulse in pulses:
nvetohits += 1
chargevetohits += pulse.charge
ndiffmodules_vetohits_set.add("" + str(key.string) + "," +
str(key.om))
ndiffmodules_vetohits = len(ndiffmodules_vetohits_set)
ndiffpmts_vetohits = len(vetopulses)
#now we write the stuff
frame.Put("MyVetoHits_" + str(self.nRows) + "rows_" + self.pulses,
vetopulses)
i3map = dataclasses.I3MapStringDouble()
i3map["nVetoHits"] = nvetohits
i3map["chargeVetoHits"] = chargevetohits
i3map["nModules_VetoHits"] = ndiffmodules_vetohits
i3map["nPMTs_VetoHits"] = ndiffpmts_vetohits
frame.Put("InfoMyVetoHits_" + str(self.nRows) + "rows_" + self.pulses,
i3map)
self.PushFrame(frame)
def test_PulseChargeShifting(self):
frame = icetray.I3Frame()
omkey = icetray.OMKey(1, 1)
# create a calibration object
calibration = dataclasses.I3Calibration()
calibration.dom_cal[omkey] = dataclasses.I3DOMCalibration()
calibration.dom_cal[omkey].mean_atwd_charge = 1.2
calibration.dom_cal[omkey].mean_fadc_charge = 1.8
frame["I3Calibration"] = calibration
# create some pulses on our fake DOM
pulse1 = dataclasses.I3RecoPulse()
pulse1.flags = dataclasses.I3RecoPulse.PulseFlags.ATWD
pulse1.time = 1. * I3Units.nanosecond
pulse1.charge = 10.
pulse1.width = 1.
pulse2 = dataclasses.I3RecoPulse()
pulse2.flags = dataclasses.I3RecoPulse.PulseFlags.FADC
pulse2.time = 10. * I3Units.nanosecond
pulse2.charge = 5.
pulse2.width = 1.
pulse_series = dataclasses.I3RecoPulseSeriesMap()
pulse_series[omkey] = dataclasses.I3RecoPulseSeries()
pulse_series[omkey].append(pulse1)
pulse_series[omkey].append(pulse2)
# add these pulses to our new frame
frame["UnshiftedPulses"] = pulse_series
# create a shifter object
frame[
"ShiftedPulses"] = dataclasses.I3RecoPulseSeriesMapApplySPECorrection(
pulses_key="UnshiftedPulses", calibration_key="I3Calibration")
# retrieve the shifted pulses
shifted_pulses = dataclasses.I3RecoPulseSeriesMap.from_frame(
frame, "ShiftedPulses")
# make sure everything is as expected
self.assertEqual(pulse_series[omkey][0].time,
shifted_pulses[omkey][0].time,
"these should be the same.")
self.assertEqual(pulse_series[omkey][0].width,
shifted_pulses[omkey][0].width,
"these should be the same.")
self.assertEqual(pulse_series[omkey][0].flags,
shifted_pulses[omkey][0].flags,
"these should be the same.")
self.assertAlmostEqual(pulse_series[omkey][0].charge /
calibration.dom_cal[omkey].mean_atwd_charge,
shifted_pulses[omkey][0].charge,
places=4,
msg="these should be the same.")
self.assertEqual(pulse_series[omkey][1].time,
shifted_pulses[omkey][1].time,
"these should be the same.")
self.assertEqual(pulse_series[omkey][1].width,
shifted_pulses[omkey][1].width,
"these should be the same.")
self.assertEqual(pulse_series[omkey][1].flags,
shifted_pulses[omkey][1].flags,
"these should be the same.")
self.assertAlmostEqual(pulse_series[omkey][1].charge /
calibration.dom_cal[omkey].mean_fadc_charge,
shifted_pulses[omkey][1].charge,
places=4,
msg="these should be the same.")
