def I3CLSimTabulatePhotons(
tray,
name,
UseCPUs=True,
UseGPUs=False,
UseOnlyDeviceNumber=None,
MCTreeName="I3MCTree",
OutputMCTreeName=None,
FlasherInfoVectName=None,
FlasherPulseSeriesName=None,
MMCTrackListName="MMCTrackList",
ParallelEvents=1000,
RandomService=None,
MediumProperties=expandvars("$I3_SRC/clsim/resources/ice/spice_mie"),
UseGeant4=False,
CrossoverEnergyEM=None,
CrossoverEnergyHadron=None,
UseCascadeExtension=False,
DoNotParallelize=False,
Area=None,
WavelengthAcceptance=None,
AngularAcceptance=None,
UseHoleIceParameterization=True,
OverrideApproximateNumberOfWorkItems=None,
ExtraArgumentsToI3CLSimModule=dict(),
If=lambda f: True):
"""Do standard clsim processing up to the I3Photon level.
These photons still need to be converted to I3MCPEs to be usable
for further steps in the standard IceCube MC processing chain.
Reads its particles from an I3MCTree and writes an I3PhotonSeriesMap.
All available OpenCL GPUs (and optionally CPUs) will
be used. This will take over your entire machine,
so make sure to configure your batch jobs correctly
when using this on a cluster.
When using nVidia cards, you can set the
CUDA_VISIBLE_DEVICES environment variable to
limit GPU visibility. A setting of
CUDA_VISIBLE_DEVICES="0,3" would only use cards
#0 and #3 and ignore cards #1 and #2. In case you are
using a batch system, chances are this variable is already
set. Unfortunately, there is no corresponding setting
for the AMD driver.
This segment assumes that MMC has been applied to the
I3MCTree and that MMC was *NOT* run using the "-recc" option.
:param UseCPUs:
Turn this on to also use CPU-based devices.
(This may potentially slow down photon generation, which
is also done on the CPU in parallel.)
:param UseGPUs:
Turn this off to not use GPU-based devices.
This may be useful if your GPU is used for display
purposes and you don't want it to slow down.
:param UseOnlyDeviceNumber:
Use only a single device number, even if there is more than
one device found matching the required description. The numbering
starts at 0.
:param MCTreeName:
The name of the I3MCTree containing the particles to propagate.
:param OutputMCTreeName:
A copy of the (possibly sliced) MCTree will be stored as this name.
:param FlasherInfoVectName:
Set this to the name of I3FlasherInfoVect objects in the frame to
enable flasher simulation. The module will read I3FlasherInfoVect objects
and generate photons according to assumed parameterizations.
:param FlasherPulseSeriesName:
Set this to the name of an I3CLSimFlasherPulseSeries object in the frame to
enable flasher/Standard Candle simulation.
This cannot be used at the same time as FlasherInfoVectName.
(I3CLSimFlasherPulseSeries objects are clsim's internal flasher
representation, if "FlasherInfoVectName" is used, the I3FlasherInfoVect
objects are converted to I3CLSimFlasherPulseSeries objects.)
:param MMCTrackListName:
Only used if *ChopMuons* is active. Set it to the name
of the I3MMCTrackList object that contains additional
muon energy loss information.
:param ParallelEvents:
clsim will work on a couple of events in parallel in order
not to starve the GPU. Setting this too high will result
in excessive memory usage (all your frames have to be cached
in RAM). Setting it too low may impact simulation performance.
The optimal value depends on your energy distribution/particle type.
:param RandomService:
Set this to an instance of a I3RandomService. Alternatively,
you can specify the name of a configured I3RandomServiceFactory
added to I3Tray using tray.AddService(). If you don't configure
this, the default I3RandomServiceFactory will be used.
:param MediumProperties:
Set this either to a directory containing a PPC-compatible
ice description (icemodel.dat, icemodel.par and cfg.txt) or
to a photonics ice table file. PPC-compatible ice files should
generally lead to faster execution times on GPUs since it involves
less interpolation between table entries (the PPC ice-specification
is parametric w.r.t. wavelength, whereas the photonics specification
is not).
:param Area:
Geometric area of the sensor. If None, use the area of an IceCube DOM
:param WavelengthAcceptance:
Quantum efficiency of the sensor, relative to the geometric area. If
None, use the IceCube DOM (standard QE)
:param AngularAcceptance:
Efficiency as a function of polar angle, relative to the geometric area.
If None, use the IceCube angular efficiency, assuming hole ice.
:param UseGeant4:
Enabling this setting will disable all cascade and muon light yield
parameterizations. All particles will sent to Geant4 for a full
simulation. This does **not** apply to muons that do have a length
assigned. These are assumed to have been generated by MMC and
their light is generated according to the usual parameterization.
:param CrossoverEnergyEM:
If set it defines the crossover energy between full Geant4 simulations and
light yield parameterizations for electro magnetic cascades. This only works
when UseGeant4 is set to true. It works in conjunction with CrossoverEnergyHadron.
If one of both is set to a positiv value greater 0 (GeV), the hybrid simulation
is used.
If CrossoverEnergyEM is set to None while CrossoverEnergyHadron is set so
hybrid mode is working, GEANT4 is used for EM cascades.
If CrossoverEnergyEM is set to 0 (GeV) while CrossoverEnergyHadron is set
so hybrid mode is working, leptons and EM cascades will use parameterizations
for the whole energy range.
:param CrossoverEnergyHadron:
If set it defines the crossover energy between full Geant4 simulations and
light yield parameterizations for hadronic cascades. This only works when
UseGeant4 is set to true. It works in conjunction with CrossoverEnergyEM.
If one of both is set to a positiv value greater 0 (GeV), the hybrid simulation
is used.
If CrossoverEnergyHadron is set to None while CrossoverEnergyEM is set so
hybrid mode is working, GEANT4 is used for hadronic cascades.
If CrossoverEnergyHadron is set to 0 (GeV) while CrossoverEnergyHadron is
set so hybrid mode is working, hadronic cascades will use parameterizations
for the whole energy range.
:param UseCascadeExtension:
If True, simulate the longitudinal development of cascades. Otherwise,
simulate cascades as pointlike objects.
:param DoNotParallelize:
Try only using a single work item in parallel when running the
OpenCL simulation. This might be useful if you want to run jobs
in parallel on a batch system. This will only affect CPUs and
will be a no-op for GPUs.
:param OverrideApproximateNumberOfWorkItems:
Allows to override the auto-detection for the maximum number of parallel work items.
You should only change this if you know what you are doing.
:param If:
Python function to use as conditional execution test for segment modules.
"""
from icecube import icetray, dataclasses, phys_services, clsim
# make sure the geometry is updated to the new granular format (in case it is supported)
if hasattr(dataclasses, "I3ModuleGeo"):
tray.AddModule("I3GeometryDecomposer",
name + "_decomposeGeometry",
If=lambda frame: If(frame) and
("I3OMGeoMap" not in frame))
if UseGeant4:
if not clsim.I3CLSimLightSourceToStepConverterGeant4.can_use_geant4:
raise RuntimeError(
"You have requested to use Geant 4, but clsim was compiled without Geant 4 support"
)
# at the moment the Geant4 paths need to be set, even if it isn't used
# TODO: fix this
if clsim.I3CLSimLightSourceToStepConverterGeant4.can_use_geant4:
AutoSetGeant4Environment()
if MMCTrackListName is None or MMCTrackListName == "":
# the input does not seem to have been processed by MMC
ChopMuons = False
else:
ChopMuons = True
if MCTreeName is None or MCTreeName == "":
clSimMCTreeName = ""
if ChopMuons:
raise RuntimeError(
"You cannot have \"MMCTrackListName\" enabled with no MCTree!")
else:
clSimMCTreeName = MCTreeName
if FlasherInfoVectName is None or FlasherInfoVectName == "":
if (FlasherPulseSeriesName
is not None) and (FlasherPulseSeriesName != ""):
SimulateFlashers = True
clSimFlasherPulseSeriesName = FlasherPulseSeriesName
clSimOMKeyMaskName = ""
else:
SimulateFlashers = False
clSimFlasherPulseSeriesName = ""
clSimOMKeyMaskName = ""
else:
if (FlasherPulseSeriesName
is not None) and (FlasherPulseSeriesName != ""):
raise RuntimeError(
"You cannot use the FlasherPulseSeriesName and FlasherInfoVectName parameters at the same time!"
)
SimulateFlashers = True
clSimFlasherPulseSeriesName = FlasherInfoVectName + "_pulses"
clSimOMKeyMaskName = FlasherInfoVectName + "_OMKeys"
tray.AddModule(clsim.FlasherInfoVectToFlasherPulseSeriesConverter,
name + "_FlasherInfoVectToFlasherPulseSeriesConverter",
FlasherInfoVectName=FlasherInfoVectName,
FlasherPulseSeriesName=clSimFlasherPulseSeriesName,
FlasherOMKeyVectName=clSimOMKeyMaskName,
If=If)
# (optional) pre-processing
if ChopMuons:
if OutputMCTreeName is not None:
clSimMCTreeName_new = OutputMCTreeName
else:
clSimMCTreeName_new = clSimMCTreeName + "_sliced"
tray.AddModule("I3MuonSlicer",
name + "_chopMuons",
InputMCTreeName=clSimMCTreeName,
MMCTrackListName=MMCTrackListName,
OutputMCTreeName=clSimMCTreeName_new,
If=If)
clSimMCTreeName = clSimMCTreeName_new
else:
if (OutputMCTreeName is not None) and (OutputMCTreeName != ""):
# copy the MCTree to the requested output name
def copyMCTree(frame, inputName, outputName, If_=None):
if If_ is not None:
if not If_(frame): return
frame[outputName] = frame[inputName]
tray.AddModule(copyMCTree,
name + "_copyMCTree",
inputName=clSimMCTreeName,
outputName=OutputMCTreeName,
Streams=[icetray.I3Frame.DAQ],
If_=If)
clSimMCTreeName = OutputMCTreeName
else:
clSimMCTreeName = clSimMCTreeName
# some constants
DOMRadius = 0.16510 * icetray.I3Units.m # 13" diameter
if Area is None:
referenceArea = dataclasses.I3Constants.pi * DOMRadius**2
else:
referenceArea = Area
if WavelengthAcceptance is None:
domAcceptance = clsim.GetIceCubeDOMAcceptance(domRadius=DOMRadius)
else:
domAcceptance = WavelengthAcceptance
if AngularAcceptance is None:
angularAcceptance = clsim.GetIceCubeDOMAngularSensitivity(holeIce=True)
else:
angularAcceptance = AngularAcceptance
# muon&cascade parameterizations
ppcConverter = clsim.I3CLSimLightSourceToStepConverterPPC(
photonsPerStep=200)
ppcConverter.SetUseCascadeExtension(UseCascadeExtension)
if not UseGeant4:
particleParameterizations = GetDefaultParameterizationList(
ppcConverter, muonOnly=False)
else:
if CrossoverEnergyEM > 0 or CrossoverEnergyHadron > 0:
particleParameterizations = GetHybridParameterizationList(
ppcConverter,
CrossoverEnergyEM=CrossoverEnergyEM,
CrossoverEnergyHadron=CrossoverEnergyHadron)
elif MMCTrackListName is None or MMCTrackListName == "":
particleParameterizations = [
] # make sure absolutely **no** parameterizations are used
else:
# use no parameterizations except for muons with lengths assigned to them
# (those are assumed to have been generated by MMC)
particleParameterizations = GetDefaultParameterizationList(
ppcConverter, muonOnly=True)
# flasher parameterizations
if SimulateFlashers:
# this needs a spectrum table in order to pass spectra to OpenCL
spectrumTable = clsim.I3CLSimSpectrumTable()
particleParameterizations += GetFlasherParameterizationList(
spectrumTable)
icetray.logging.log_debug(
"number of spectra (1x Cherenkov + Nx flasher): %d" %
len(spectrumTable),
unit="clsim")
else:
# no spectrum table is necessary when only using the Cherenkov spectrum
spectrumTable = None
openCLDevices = configureOpenCLDevices(
UseGPUs=UseGPUs,
UseCPUs=UseCPUs,
OverrideApproximateNumberOfWorkItems=
OverrideApproximateNumberOfWorkItems,
DoNotParallelize=DoNotParallelize,
UseOnlyDeviceNumber=UseOnlyDeviceNumber)
tray.AddModule(
"I3CLSimTabulatorModule",
name + "_clsim",
MCTreeName=clSimMCTreeName,
RandomService=RandomService,
MediumProperties=MediumProperties,
SpectrumTable=spectrumTable,
FlasherPulseSeriesName=clSimFlasherPulseSeriesName,
Area=referenceArea,
WavelengthAcceptance=domAcceptance,
AngularAcceptance=angularAcceptance,
ParameterizationList=particleParameterizations,
# MaxNumParallelEvents=ParallelEvents,
OpenCLDeviceList=openCLDevices,
**ExtraArgumentsToI3CLSimModule)
unpin_threads()
def TabulatePhotonsFromSource(tray,
name,
PhotonSource="cascade",
Zenith=0. * I3Units.degree,
Azimuth=0. * I3Units.degree,
ZCoordinate=0. * I3Units.m,
Energy=1. * I3Units.GeV,
FlasherWidth=127,
FlasherBrightness=127,
Seed=12345,
NEvents=100,
IceModel='spice_mie',
DisableTilt=False,
Filename="",
TabulateImpactAngle=False,
PhotonPrescale=1,
Axes=None,
Directions=None,
Sensor='DOM',
RecordErrors=False):
"""
Tabulate the distribution of photoelectron yields on IceCube DOMs from various
light sources. The light profiles of the sources are computed from the same
parameterizations used in PPC, but like in the direct propagation mode can
be computed using GEANT4 instead.
The mode of tabulation is controlled primarily by the **PhotonSource** parameter.
- *'cascade'* will simulate an electromagnetic cascade of **Energy** GeV at
(0, 0, **ZCoordinate**), oriented according to **Zenith** and **Azimuth**.
The default coordinate system is spherical and centered the given vertex,
with 200 quadratically spaced bins in radius, 36 linear bins in azimuthal
angle (only from 0 to 180 degrees by default), 100 linear bins in the
cosine of the polar angle, and 105 quadratic bins in time residual w.r.t
the direct path from (0, 0, **ZCoordinate**).
- *'flasher'* will simulate a 405 nm LED flasher pulse with the given
**FlasherWidth** and **FlasherBrightness** settings. The source position
and coordinate system are the same as for the 'cascade' case.
- *'infinite-muon'* will simulate a "bare" muon of infinite length. The
coordinate system is cylindrical and centered on the axis of the muon.
Since the muon's position is degenerate with time, the usual parallel
distance is replaced by the z coordinate of the closest approach to the
detection position, and the starting positions of the simulated muons are
sampled randomly (**ZCoordinate** is ignored). There are 100 quadratic
bins in perpendicular distance to the source axis, 36 linear bins in
azimuthal angle (0 to :math:`\pi` radians), 100 linear bins in z
coordinate of closest approach, and 105 quadratic bins in time residual
w.r.t. the earliest possible Cherenkov photon.
:param PhotonSource: the type of photon source ('cascade', 'flasher', or 'infinite-muon').
:param Zenith: the orientation of the source
:param ZCoordinate: the depth of the source
:param Energy: the energy of the source (only for cascade tables)
:param FlasherWidth: the width of the flasher pulse (only for flasher tables)
:param FlasherBrightness: the brightness of the flasher pulse (only for flasher tables)
:param Seed: the seed for the random number service
:param NEvents: the number of events to simulate
:param RecordErrors: record the squares of weights as well (useful for error bars)
:param IceModel: the path to an ice model in $I3_SRC/clsim/resources/ice. Likely values include:
'spice_mie' ppc-style SPICE-Mie parametrization
'photonics_spice_1/Ice_table.spice.i3coords.cos080.10feb2010.txt' Photonics-style SPICE1 table
'photonics_wham/Ice_table.wham.i3coords.cos094.11jul2011.txt' Photonics-style WHAM! table
:param DisableTilt: if true, disable tilt in ice model
:param Filename: the name of the FITS file to write
:param TabulateImpactAngle: if True, tabulate the impact position of the
photon on the DOM instead of weighting by the DOM's angular acceptance
:param Axes: a subclass of :cpp:class:`clsim::tabulator::Axes` that defines the coordinate system.
If None, an appropriate default will be chosen based on **PhotonSource**.
:param Directions: a set of directions to allow table generation for multiple sources.
If None, only one direction given by **Zenith** and **Azimuth** is used.
"""
# check sanity of args
PhotonSource = PhotonSource.lower()
if PhotonSource not in ['cascade', 'flasher', 'infinite-muon']:
raise ValueError(
"photon source %s is unknown. Please specify either 'cascade', 'flasher', or 'infinite-muon'"
% PhotonSource)
from icecube import icetray, dataclasses, dataio, phys_services, sim_services, clsim
from os.path import expandvars
# a random number generator
randomService = phys_services.I3GSLRandomService(Seed)
tray.AddModule("I3InfiniteSource",
name + "streams",
Stream=icetray.I3Frame.DAQ)
tray.AddModule("I3MCEventHeaderGenerator",
name + "gen_header",
Year=2009,
DAQTime=158100000000000000,
RunNumber=1,
EventID=1,
IncrementEventID=True)
if Directions is None:
Directions = numpy.asarray([(Zenith, Azimuth)])
if PhotonSource in ('cascade', 'flasher', 'muon-segment'):
if PhotonSource == 'muon-segment':
ptype = I3Particle.ParticleType.MuMinus
else:
ptype = I3Particle.ParticleType.EMinus
def reference_source(zenith, azimuth, scale):
source = I3Particle()
source.type = ptype
source.energy = Energy * scale
source.pos = I3Position(0., 0., ZCoordinate)
source.dir = I3Direction(zenith, azimuth)
source.time = 0.
if PhotonSource == 'muon-segment':
source.length = 3.
else:
source.length = 0.
source.location_type = I3Particle.LocationType.InIce
return source
elif PhotonSource == 'infinite-muon':
from icecube import MuonGun
# pad depth to ensure that the track appears effectively infinite
surface = MuonGun.Cylinder(1800, 800)
# account for zenith-dependent distribution of track lengths
length_scale = surface.area(dataclasses.I3Direction(
0, 0)) / surface.area(dataclasses.I3Direction(Zenith, 0))
ptype = I3Particle.ParticleType.MuMinus
def reference_source(zenith, azimuth, scale):
source = I3Particle()
source.type = ptype
source.energy = Energy * scale
source.dir = I3Direction(zenith, azimuth)
source.pos = surface.sample_impact_position(
source.dir, randomService)
crossings = surface.intersection(source.pos, source.dir)
source.length = crossings.second - crossings.first
source.time = 0.
source.location_type = I3Particle.LocationType.InIce
return source
import copy
class MakeParticle(icetray.I3Module):
def __init__(self, ctx):
super(MakeParticle, self).__init__(ctx)
self.AddOutBox("OutBox")
self.AddParameter("SourceFunction", "", lambda: None)
self.AddParameter("NEvents", "", 100)
def Configure(self):
self.reference_source = self.GetParameter("SourceFunction")
self.nevents = self.GetParameter("NEvents")
self.emittedEvents = 0
def DAQ(self, frame):
if PhotonSource != "flasher":
primary = I3Particle()
mctree = I3MCTree()
mctree.add_primary(primary)
for zenith, azimuth in Directions:
source = self.reference_source(zenith, azimuth,
1. / len(Directions))
mctree.append_child(primary, source)
frame["I3MCTree"] = mctree
# use the emitting particle as a geometrical reference
frame["ReferenceParticle"] = source
else:
pulseseries = I3CLSimFlasherPulseSeries()
for zenith, azimuth in Directions:
pulse = makeFlasherPulse(0, 0, ZCoordinate, zenith,
azimuth, FlasherWidth,
FlasherBrightness,
1. / len(Directions))
pulseseries.append(pulse)
frame["I3FlasherPulseSeriesMap"] = pulseseries
frame["ReferenceParticle"] = self.reference_source(
Zenith, Azimuth, 1.)
self.PushFrame(frame)
self.emittedEvents += 1
if self.emittedEvents >= self.nevents:
self.RequestSuspension()
tray.AddModule(MakeParticle,
SourceFunction=reference_source,
NEvents=NEvents)
if PhotonSource == "flasher":
flasherpulse = "I3FlasherPulseSeriesMap"
mctree = None
else:
flasherpulse = None
mctree = "I3MCTree"
header = dict(FITSTable.empty_header)
header['zenith'] = Zenith / I3Units.degree
header['azimuth'] = Azimuth / I3Units.degree
header['z'] = ZCoordinate
header['energy'] = Energy
header['type'] = int(ptype)
header['efficiency'] = Efficiency.RECEIVER | Efficiency.WAVELENGTH
if PhotonSource == 'infinite-muon':
header['n_events'] = length_scale * NEvents / float(PhotonPrescale)
if Axes is None:
if PhotonSource != "infinite-muon":
dims = [
clsim.tabulator.PowerAxis(0, 580, 200, 2),
clsim.tabulator.LinearAxis(0, 180, 36),
clsim.tabulator.LinearAxis(-1, 1, 100),
clsim.tabulator.PowerAxis(0, 7e3, 105, 2),
]
geo = clsim.tabulator.SphericalAxes
else:
dims = [
clsim.tabulator.PowerAxis(0, 580, 100, 2),
clsim.tabulator.LinearAxis(0, numpy.pi, 36),
clsim.tabulator.LinearAxis(-8e2, 8e2, 80),
clsim.tabulator.PowerAxis(0, 7e3, 105, 2),
]
geo = clsim.tabulator.CylindricalAxes
# Add a dimension for the impact angle
if TabulateImpactAngle:
dims.append(clsim.tabulator.LinearAxis(-1, 1, 20))
Axes = geo(dims)
if PhotonSource == "flasher":
header['flasherwidth'] = FlasherWidth
header['flasherbrightness'] = FlasherBrightness
# some constants
DOMRadius = 0.16510 * icetray.I3Units.m # 13" diameter
referenceArea = dataclasses.I3Constants.pi * DOMRadius**2
# NB: GetIceCubeDOMAcceptance() calculates the quantum efficiency by
# dividing the geometric area (a circle of radius domRadius) by the
# tabulated effective area. Scaling that radius by *sqrt(prescale)*
# _reduces_ the effective quantum efficiency by a factor *prescale*.
# Since we draw photons directly from the QE-weighted Cherenkov
# spectrum, this causes *prescale* fewer photons to be progagated per
# light source. We compensate by dividing the number of events by
# *prescale* in the header above.
# to be propagated per light source.
domAcceptance = clsim.GetIceCubeDOMAcceptance(
domRadius=math.sqrt(PhotonPrescale) * DOMRadius)
if Sensor.lower() == 'dom':
angularAcceptance = clsim.GetIceCubeDOMAngularSensitivity(holeIce=True)
elif Sensor.lower() == 'degg':
referenceArea = dataclasses.I3Constants.pi * (300. * I3Units.mm / 2)**2
angularAcceptance = Gen2Sensors.GetDEggAngularSensitivity(pmt='both')
domAcceptance = Gen2Sensors.GetDEggAcceptance(active_fraction=1. /
PhotonPrescale)
elif Sensor.lower() == 'wom':
# outer diameter of the pressure vessel is 11.4 cm, walls are 9 mm thick
referenceArea = (11 - 2 * 0.9) * 90 * icetray.I3Units.cm2
angularAcceptance = Gen2Sensors.GetWOMAngularSensitivity()
domAcceptance = Gen2Sensors.GetWOMAcceptance(active_fraction=1. /
PhotonPrescale)
else:
raise ValueError("Don't know how to simulate %ds yet" % (sensor))
tray.AddSegment(
I3CLSimTabulatePhotons,
name + "makeCLSimPhotons",
MCTreeName=
mctree, # if source is a cascade this will point to the I3MCTree
FlasherPulseSeriesName=
flasherpulse, # if source is a flasher this will point to the I3CLSimFlasherPulseSeries
MMCTrackListName=None, # do NOT use MMC
ParallelEvents=
1, # only work at one event at a time (it'll take long enough)
RandomService=randomService,
# UnWeightedPhotons=True,
UseGPUs=
False, # table-making is not a workload particularly suited to GPUs
UseCPUs=True, # it should work fine on CPUs, though
Area=referenceArea,
WavelengthAcceptance=domAcceptance,
AngularAcceptance=angularAcceptance,
DoNotParallelize=True, # no multithreading
UseGeant4=False,
OverrideApproximateNumberOfWorkItems=
1, # if you *would* use multi-threading, this would be the maximum number of jobs to run in parallel (OpenCL is free to split them)
ExtraArgumentsToI3CLSimModule=dict(Filename=Filename,
TableHeader=header,
Axes=Axes,
PhotonsPerBunch=200,
EntriesPerPhoton=5000,
RecordErrors=RecordErrors),
MediumProperties=parseIceModel(
expandvars("$I3_SRC/clsim/resources/ice/" + IceModel),
disableTilt=DisableTilt),
)
#print "maxWorkgroupSizeForKernel:", tester.maxWorkgroupSize
# the function currently only accepts I3VectorFloat as its input type
vector = dataclasses.I3VectorFloat(numpy.array(xValues))
if useReferenceFunction:
yValues = numpy.array(tester.EvaluateReferenceFunction(vector))
else:
yValues = numpy.array(tester.EvaluateFunction(vector))
return yValues
domAngularAcceptance_holeIce = clsim.GetIceCubeDOMAngularSensitivity(
holeIce=expandvars(
"$I3_SRC/ice-models/resources/models/angsens/as.h2-50cm"))
domAngularAcceptance = clsim.GetIceCubeDOMAngularSensitivity(
holeIce=expandvars(
"$I3_SRC/ice-models/resources/models/angsens/as.nominal"))
####
fig = pylab.figure(3)
fig.subplots_adjust(left=0.09, bottom=0.05, top=0.95, right=0.98)
ax = fig.add_subplot(3, 1, 1)
bx = fig.add_subplot(3, 1, 2)
cx = fig.add_subplot(3, 1, 3)
cosines = numpy.linspace(-1., 1., num=10000)
def I3CLSimMakeHitsFromPhotons(tray,
name,
MCTreeName="I3MCTree_sliced",
PhotonSeriesName="PhotonSeriesMap",
MCPESeriesName="MCPESeriesMap",
RandomService=None,
DOMOversizeFactor=5.,
UnshadowedFraction=0.9,
UseHoleIceParameterization=True,
If=lambda f: True):
"""
Convert I3Photons into I3MCPEs. This applies the DOM
angular acceptance (and wavenelgth acceptance in case
you are using the unbiased photon propagation mode.)
:param MCTreeName:
The name of the I3MCTree containing the particles to propagate.
:param PhotonSeriesName:
Name of the input I3PhotonSeriesMap to be converted.
:param MCPESeriesName:
Name of the output I3MCPESeriesMap written by the module.
Set this to None to prevent generating MCPEs from
Photons.
:param RandomService:
Set this to an instance of a I3RandomService. Alternatively,
you can specify the name of a configured I3RandomServiceFactory
added to I3Tray using tray.AddService(). If you don't configure
this, the default I3RandomServiceFactory will be used.
:param DOMOversizeFactor:
Set the DOM oversize factor. To disable oversizing, set this to 1.
:param UnshadowedFraction:
Fraction of photocathode available to receive light (e.g. unshadowed by the cable)
:param UseHoleIceParameterization:
Use an angular acceptance correction for hole ice scattering.
:param If:
Python function to use as conditional execution test for segment modules.
"""
from icecube import icetray, dataclasses, clsim
# some constants
DOMRadius = 0.16510 * icetray.I3Units.m # 13" diameter
Jitter = 2. * icetray.I3Units.ns
# detector properties
domAcceptance = clsim.GetIceCubeDOMAcceptance(
domRadius=DOMRadius * DOMOversizeFactor, efficiency=UnshadowedFraction)
domAngularSensitivity = clsim.GetIceCubeDOMAngularSensitivity(
holeIce=UseHoleIceParameterization)
tray.AddModule(
"I3PhotonToMCPEConverter",
name + "_clsim_make_hits",
RandomService=RandomService,
MCTreeName=MCTreeName,
InputPhotonSeriesMapName=PhotonSeriesName,
OutputMCPESeriesMapName=MCPESeriesName,
DOMRadiusWithoutOversize=DOMRadius,
DOMOversizeFactor=DOMOversizeFactor,
DOMPancakeFactor=DOMOversizeFactor,
WavelengthAcceptance=domAcceptance,
AngularAcceptance=domAngularSensitivity,
IgnoreDOMsWithoutDetectorStatusEntry=
False, # in icesim4 it is the job of the DOM simulation tools to cut out these DOMs
If=If)
def setupDetector(GCDFile,
SimulateFlashers=False,
IceModelLocation=expandvars("$I3_SRC/clsim/resources/ice/spice_mie"),
DisableTilt=False,
UnWeightedPhotons=False,
UnWeightedPhotonsScalingFactor=None,
UseI3PropagatorService=True,
UseGeant4=False,
CrossoverEnergyEM=None,
CrossoverEnergyHadron=None,
UseCascadeExtension=True,
StopDetectedPhotons=True,
DOMOversizeFactor=5.,
UnshadowedFraction=0.9,
HoleIceParameterization=expandvars("$I3_SRC/ice-models/resources/models/angsens/as.h2-50cm"),
WavelengthAcceptance=None,
DOMRadius=0.16510*icetray.I3Units.m, # 13" diameter
CableOrientation=None,
IgnoreSubdetectors=['IceTop']):
"""
Set up data structures used in N different places in clsim
:param GCDFile: either a filename or a tuple of (Geometry, Calibration) frames
"""
from icecube import clsim, dataclasses
from icecube.icetray import logging
from icecube.clsim import GetDefaultParameterizationList
from icecube.clsim import GetFlasherParameterizationList
from icecube.clsim import GetHybridParameterizationList
from icecube.clsim.GetIceCubeCableShadow import GetIceCubeCableShadow
import numpy
def harvest_detector_parameters(GCDFile):
from icecube import dataio, dataclasses
from I3Tray import I3Tray
tray = I3Tray()
tray.Add(dataio.I3Reader, Filenamelist=[GCDFile])
# make sure the geometry is updated to the new granular format
tray.AddModule("I3GeometryDecomposer",
If=lambda frame: ("I3OMGeoMap" not in frame) and ("I3ModuleGeoMap" not in frame))
def pluck_geo(frame):
pluck_geo.frame = frame
pluck_geo.frame = None
tray.Add(pluck_geo, Streams=[icetray.I3Frame.Geometry])
def pluck_calib(frame):
pluck_calib.frame = frame
pluck_calib.frame = None
tray.Add(pluck_calib, Streams=[icetray.I3Frame.Calibration])
tray.Execute()
if CableOrientation:
icetray.logging.log_warn("Explicitly simulating cable shadow. This will reduce overall DOM efficiency by ~10%.", unit="clsim")
pluck_geo.frame['CableShadow'] = GetIceCubeCableShadow(CableOrientation) if isinstance(CableOrientation, str) else CableOrientation
geometry = clsim.I3CLSimSimpleGeometryFromI3Geometry(
DOMRadius, DOMOversizeFactor, pluck_geo.frame,
ignoreSubdetectors=dataclasses.ListString(IgnoreSubdetectors),
# NB: we trust advanced users to properly label subdetectors, and disable any
# min/max string/om numbers and strings/oms to ignore
ignoreStrings=dataclasses.ListInt(), ignoreDomIDs=dataclasses.ListUInt(),
ignoreStringIDsSmallerThan=1, ignoreStringIDsLargerThan=numpy.iinfo(numpy.int32).max,
ignoreDomIDsSmallerThan=1, ignoreDomIDsLargerThan=numpy.iinfo(numpy.uint32).max,
splitIntoPartsAccordingToPosition=False, useHardcodedDeepCoreSubdetector=False
)
rde = dict()
spe_compensation_factor = dict()
for k, domcal in pluck_calib.frame['I3Calibration'].dom_cal.iteritems():
rde[k] = domcal.relative_dom_eff
comp = domcal.combined_spe_charge_distribution.compensation_factor
spe_compensation_factor[k] = comp if not math.isnan(comp) else 1.
return geometry, rde, spe_compensation_factor
geometry, rde, spe_compensation_factor = harvest_detector_parameters(GCDFile)
# ice properties
if isinstance(IceModelLocation, str):
mediumProperties = parseIceModel(IceModelLocation, disableTilt=DisableTilt)
else:
# get ice model directly if not a string
mediumProperties = IceModelLocation
icemodel_efficiency_factor = mediumProperties.efficiency
# detector properties
if WavelengthAcceptance is None:
# Combine all global factors that enter only the wavelength acceptance
domEfficiencyCorrection = UnshadowedFraction*icemodel_efficiency_factor
assert domEfficiencyCorrection > 0
# The hole ice acceptance curve peaks at a value different than 1. Use
# this in the wavelength generation
maxAngularAcceptance = numpy.loadtxt(HoleIceParameterization)[0]
assert maxAngularAcceptance > 0
@memoize
def getWavelengthAcceptance(rde, spe_comp, efficiency_scale):
"""
Construct a wavelength acceptance
This is memoized to create only one instance per combination of
parameters, e.g. one for IceCube and one for DeepCore.
"""
kwargs = {}
if round(rde, 6) == 1.35:
kwargs['highQE'] = True
# reset RDE to 1; highQE curve is already scaled
rde = 1
elif rde != 1:
raise ValueError("Relative DOM efficiency {} is neither 1 nor 1.35. You probably need to add support for individual DOM efficiencies".format(rde))
try:
if not math.isfinite(spe_comp):
raise ValueError("SPE compensation factor is {}. Fix your GCD file.".format(spe_comp))
except AttributeError:
# likely Python2 isfinite is python3.
if math.isnan(spe_comp) or math.isinf(spe_comp):
raise ValueError("SPE compensation factor is {}. Fix your GCD file.".format(spe_comp))
return clsim.GetIceCubeDOMAcceptance(domRadius = DOMRadius*DOMOversizeFactor, efficiency=rde*spe_comp*efficiency_scale, **kwargs)
def getEnvelope(functions, scale=1):
"""Construct the supremum of a set of I3CLSimFunctionFromTable"""
first = functions[0]
return clsim.I3CLSimFunctionFromTable(
first.GetMinWlen(),
first.GetWavelengthStepping(),
[scale*max((f.GetEntryValue(i) for f in functions)) for i in range(first.GetNumEntries())]
)
# Wavelength acceptance of individual DOMs
domAcceptance = clsim.I3CLSimFunctionMap()
for string_id,dom_id in zip(geometry.stringIDs,geometry.domIDs):
k = icetray.OMKey(string_id,dom_id,0)
if math.isnan(rde.get(k,float('nan'))):
continue
try:
domAcceptance[k] = getWavelengthAcceptance(rde.get(k,float('nan')), spe_compensation_factor.get(k,float('nan')), domEfficiencyCorrection)
except ValueError as e:
raise ValueError(str(k)+' '+e.args[0])
# The wavelength generation bias is the maximum possible value of
# the product of wavelength acceptance (wvl) and angular acceptance
# (ang), such that the PE conversion probability, given by
# wvl*ang/bias, is never > 1
domAcceptanceEnvelope = getEnvelope(list(set(domAcceptance.values())), maxAngularAcceptance)
else:
domAcceptance = WavelengthAcceptance
domAcceptanceEnvelope = WavelengthAcceptance
angularAcceptance = clsim.GetIceCubeDOMAngularSensitivity(holeIce=HoleIceParameterization)
# photon generation wavelength bias
if not UnWeightedPhotons:
wavelengthGenerationBias = domAcceptanceEnvelope
if UnWeightedPhotonsScalingFactor is not None:
raise RuntimeError("UnWeightedPhotonsScalingFactor should not be set when UnWeightedPhotons is not set")
else:
logging.log_info("***** running unweighted simulation with a photon pre-scaling of {}".format(UnWeightedPhotonsScalingFactor), unit="clsim")
wavelengthGenerationBias = clsim.I3CLSimFunctionConstant(1. if UnWeightedPhotonsScalingFactor is None else UnWeightedPhotonsScalingFactor)
# create wavelength generators
wavelengthGenerators = [clsim.makeCherenkovWavelengthGenerator(wavelengthGenerationBias, UnWeightedPhotons, mediumProperties)]
# muon&cascade parameterizations
ppcConverter = clsim.I3CLSimLightSourceToStepConverterPPC(photonsPerStep=200)
ppcConverter.SetUseCascadeExtension(UseCascadeExtension)
if not UseGeant4:
particleParameterizations = GetDefaultParameterizationList(ppcConverter, muonOnly=False)
else:
if CrossoverEnergyEM>0 or CrossoverEnergyHadron>0:
particleParameterizations = GetHybridParameterizationList(ppcConverter, CrossoverEnergyEM=CrossoverEnergyEM, CrossoverEnergyHadron=CrossoverEnergyHadron)
else:
# use no parameterizations except for muons with lengths assigned to them
# (those are assumed to have been generated by PROPOSAL)
particleParameterizations = GetDefaultParameterizationList(ppcConverter, muonOnly=True)
# flasher parameterizations
if SimulateFlashers:
# this needs a spectrum table in order to pass spectra to OpenCL
spectrumTable = clsim.I3CLSimSpectrumTable()
particleParameterizations += clsim.GetFlasherParameterizationList(spectrumTable)
for spectrum in spectrumTable:
if spectrum:
wavelengthGenerators.append(clsim.makeWavelengthGenerator(spectrum, wavelengthGenerationBias, mediumProperties))
logging.log_info("number of spectra (1x Cherenkov + Nx flasher): {}".format(len(spectrumTable)), unit="clsim")
else:
# no spectrum table is necessary when only using the Cherenkov spectrum
spectrumTable = None
return dict(Geometry=geometry,
MediumProperties=mediumProperties,
IceModelLocation=IceModelLocation,
WavelengthGenerationBias=wavelengthGenerationBias,
SpectrumTable=spectrumTable,
GenerateCherenkovPhotonsWithoutDispersion=UnWeightedPhotons,
WavelengthGenerators=wavelengthGenerators,
DOMRadius=DOMRadius,
DOMOversizeFactor=DOMOversizeFactor,
DOMPancakeFactor=DOMOversizeFactor,
UnshadowedFraction=UnshadowedFraction,
AngularAcceptance=angularAcceptance,
WavelengthAcceptance=domAcceptance,
ParameterizationList=particleParameterizations,
UseGeant4=UseGeant4,
UseI3PropagatorService=UseI3PropagatorService,
IgnoreSubdetectors=IgnoreSubdetectors,)
def I3CLSimMakeHitsFromPhotons(
tray,
name,
PhotonSeriesName="PhotonSeriesMap",
MCPESeriesName="MCPESeriesMap",
RandomService=None,
DOMOversizeFactor=5.,
UnshadowedFraction=1.0,
IceModelLocation=None, #Needed for icemodel-dependent efficiency
HoleIceParameterization=expandvars(
"$I3_BUILD/ice-models/resources/models/angsens/as.h2-50cm"),
MergeHits=False,
GCDFile=None,
If=lambda f: True):
"""
Convert I3Photons into I3MCPEs. This applies the DOM
angular acceptance (and wavenelgth acceptance in case
you are using the unbiased photon propagation mode.)
:param PhotonSeriesName:
Name of the input I3PhotonSeriesMap to be converted.
:param MCPESeriesName:
Name of the output I3MCPESeriesMap written by the module.
Set this to None to prevent generating MCPEs from
Photons.
:param RandomService:
Set this to an instance of a I3RandomService. Alternatively,
you can specify the name of a configured I3RandomServiceFactory
added to I3Tray using tray.AddService(). If you don't configure
this, the default I3RandomServiceFactory will be used.
:param DOMOversizeFactor:
Set the DOM oversize factor. To disable oversizing, set this to 1.
:param UnshadowedFraction:
Fraction of photocathode available to receive light (e.g. unshadowed by the cable)
:param HoleIceParameterization:
Set this to a hole ice parameterization file. The default file contains the
coefficients for nominal angular acceptance correction due to hole ice (ice-models
project is required). Use file $I3_BUILD/ice-models/resources/models/angsens/as.nominal
for no hole ice parameterization.
:param MergeHits:
Set to true to perform time merging on the MCPE as they are produced. This is useful for
reducing the memory and disk space used by high energy (bright) events, and can allow
detector simulation to run much more quickly. This causes parent particle information to be
stored in an additional frame object.
:param If:
Python function to use as conditional execution test for segment modules.
"""
from icecube import icetray, dataclasses, clsim
from icecube.clsim.traysegments.common import parseIceModel
icemodel_efficiency_factor = 1.0
# ice properties
if isinstance(IceModelLocation, str):
mediumProperties = parseIceModel(IceModelLocation)
else:
# get ice model directly if not a string
mediumProperties = IceModelLocation
if mediumProperties is not None:
# IceModel-dependent efficiency
icemodel_efficiency_factor = mediumProperties.efficiency
else:
icetray.logging.log_warn(
"No IceModel configured. Using DOMefficiency of %f" %
icemodel_efficiency_factor)
if UnshadowedFraction <= 0:
raise RuntimeError("UnshadowedFraction must be a positive number")
# some constants
DOMRadius = 0.16510 * icetray.I3Units.m # 13" diameter
Jitter = 2. * icetray.I3Units.ns
# detector properties
max_compensation_factor = 1.0
if GCDFile is None:
icetray.logging.log_warn(
"No GCD file given. Setting compensation factor to 1.0!!!!")
else:
max_compensation_factor = get_compensation_factor(
dataio.I3File(GCDFile))
icetray.logging.log_info(
"Net DOM efficiency (with compensation factor): %s" %
(UnshadowedFraction * icemodel_efficiency_factor *
max_compensation_factor))
domAcceptance = clsim.GetIceCubeDOMAcceptance(
domRadius=DOMRadius * DOMOversizeFactor,
efficiency=icemodel_efficiency_factor * UnshadowedFraction)
domAngularSensitivity = clsim.GetIceCubeDOMAngularSensitivity(
holeIce=HoleIceParameterization)
tray.AddModule(
"I3PhotonToMCPEConverter",
name + "_clsim_make_hits",
RandomService=RandomService,
InputPhotonSeriesMapName=PhotonSeriesName,
OutputMCPESeriesMapName=MCPESeriesName,
DOMRadiusWithoutOversize=DOMRadius,
DOMOversizeFactor=DOMOversizeFactor,
DOMPancakeFactor=DOMOversizeFactor,
WavelengthAcceptance=domAcceptance,
AngularAcceptance=domAngularSensitivity,
IgnoreDOMsWithoutDetectorStatusEntry=
False, # in icesim4 it is the job of the DOM simulation tools to cut out these DOMs
MergeHits=MergeHits,
If=If)
wlenDependentValue=functionOpenCL)
#print "maxWorkgroupSizeForKernel:", tester.maxWorkgroupSize
# the function currently only accepts I3VectorFloat as its input type
vector = dataclasses.I3VectorFloat(numpy.array(xValues))
if useReferenceFunction:
yValues = numpy.array(tester.EvaluateReferenceFunction(vector))
else:
yValues = numpy.array(tester.EvaluateFunction(vector))
return yValues
domAngularAcceptance_holeIce = clsim.GetIceCubeDOMAngularSensitivity(holeIce=True)
domAngularAcceptance = clsim.GetIceCubeDOMAngularSensitivity(holeIce=False)
####
fig = pylab.figure(3)
fig.subplots_adjust(left=0.09, bottom=0.05, top=0.95, right=0.98)
ax = fig.add_subplot(3, 1, 1)
bx = fig.add_subplot(3, 1, 2)
cx = fig.add_subplot(3, 1, 3)
cosines=numpy.linspace(-1.,1.,num=10000)
def setupDetector(
GCDFile,
SimulateFlashers=False,
IceModelLocation=expandvars("$I3_SRC/clsim/resources/ice/spice_mie"),
DisableTilt=False,
UnWeightedPhotons=False,
UnWeightedPhotonsScalingFactor=None,
MMCTrackListName="MMCTrackList",
UseGeant4=False,
CrossoverEnergyEM=None,
CrossoverEnergyHadron=None,
UseCascadeExtension=True,
StopDetectedPhotons=True,
DOMOversizeFactor=5.,
UnshadowedFraction=0.9,
HoleIceParameterization=expandvars(
"$I3_SRC/ice-models/resources/models/angsens/as.h2-50cm"),
WavelengthAcceptance=None,
DOMRadius=0.16510 * icetray.I3Units.m, # 13" diameter
IgnoreSubdetectors=['IceTop']):
"""
Set up data structures used in N different places in clsim
"""
from icecube import clsim
from icecube.clsim import GetDefaultParameterizationList
from icecube.clsim import GetFlasherParameterizationList
from icecube.clsim import GetHybridParameterizationList
import numpy
def harvest_detector_parameters(GCDFile):
from icecube import dataio, dataclasses
from I3Tray import I3Tray
tray = I3Tray()
tray.Add(dataio.I3Reader, Filenamelist=[GCDFile])
# make sure the geometry is updated to the new granular format
tray.AddModule("I3GeometryDecomposer",
If=lambda frame: ("I3OMGeoMap" not in frame) and
("I3ModuleGeoMap" not in frame))
def pluck_geo(frame):
pluck_geo.frame = frame
pluck_geo.frame = None
tray.Add(pluck_geo, Streams=[icetray.I3Frame.Geometry])
def pluck_calib(frame):
pluck_calib.frame = frame
pluck_calib.frame = None
tray.Add(pluck_calib, Streams=[icetray.I3Frame.Calibration])
tray.Execute()
geometry = clsim.I3CLSimSimpleGeometryFromI3Geometry(
DOMRadius,
DOMOversizeFactor,
pluck_geo.frame,
ignoreSubdetectors=dataclasses.ListString(IgnoreSubdetectors),
# NB: we trust advanced users to properly label subdetectors, and disable any
# min/max string/om numbers and strings/oms to ignore
ignoreStrings=dataclasses.ListInt(),
ignoreDomIDs=dataclasses.ListUInt(),
ignoreStringIDsSmallerThan=1,
ignoreStringIDsLargerThan=numpy.iinfo(numpy.int32).max,
ignoreDomIDsSmallerThan=1,
ignoreDomIDsLargerThan=numpy.iinfo(numpy.uint32).max,
splitIntoPartsAccordingToPosition=False,
useHardcodedDeepCoreSubdetector=False)
rde = dict()
for k, domcal in pluck_calib.frame['I3Calibration'].dom_cal.iteritems(
):
rde[k] = domcal.relative_dom_eff
return geometry, rde
geometry, rde = harvest_detector_parameters(GCDFile)
# ice properties
if isinstance(IceModelLocation, str):
mediumProperties = parseIceModel(IceModelLocation,
disableTilt=DisableTilt)
else:
# get ice model directly if not a string
mediumProperties = IceModelLocation
# detector properties
if WavelengthAcceptance is None:
# the hole ice acceptance curve peaks at a value different than 1
peak = numpy.loadtxt(HoleIceParameterization)[
0] # The value at which the hole ice acceptance curve peaks
domEfficiencyCorrection = UnshadowedFraction * peak
acceptance = {
'IceCube':
clsim.GetIceCubeDOMAcceptance(domRadius=DOMRadius *
DOMOversizeFactor,
efficiency=domEfficiencyCorrection),
'DeepCore':
clsim.GetIceCubeDOMAcceptance(domRadius=DOMRadius *
DOMOversizeFactor,
efficiency=domEfficiencyCorrection,
highQE=True),
}
domAcceptanceEnvelope = clsim.I3CLSimFunctionFromTable(
acceptance['IceCube'].GetMinWlen(),
acceptance['IceCube'].GetWavelengthStepping(), [
max((f.GetEntryValue(i) for f in acceptance.values()))
for i in range(acceptance['IceCube'].GetNumEntries())
])
domAcceptance = clsim.I3CLSimFunctionMap()
#loop over every event in the geometry and determine what type of DOM it is
#based on the relative efficiency in the detector status
for string_id, dom_id in zip(geometry.stringIDs, geometry.domIDs):
k = icetray.OMKey(string_id, dom_id, 0)
releff = rde.get(k, float('nan'))
if releff == 1:
domAcceptance[k] = acceptance['IceCube']
elif round(releff, 6) == 1.35:
domAcceptance[k] = acceptance['DeepCore']
elif math.isnan(releff):
#DOMs where rde is nan are bad DOMs which are unplugged
#call them IceCube for now, hits generated by them will be
#removed later by detector simulation
domAcceptance[k] = acceptance['IceCube']
else:
raise ValueError(
"Relative DOM efficiency is neither 1 nor 1.35. You probably need to add support for individual DOM efficiencies"
)
else:
domAcceptance = WavelengthAcceptance
domAcceptanceEnvelope = WavelengthAcceptance
angularAcceptance = clsim.GetIceCubeDOMAngularSensitivity(
holeIce=HoleIceParameterization)
# photon generation wavelength bias
if not UnWeightedPhotons:
wavelengthGenerationBias = domAcceptanceEnvelope
if UnWeightedPhotonsScalingFactor is not None:
raise RuntimeError(
"UnWeightedPhotonsScalingFactor should not be set when UnWeightedPhotons is not set"
)
else:
if UnWeightedPhotonsScalingFactor is not None:
print(
"***** running unweighted simulation with a photon pre-scaling of",
UnWeightedPhotonsScalingFactor)
wavelengthGenerationBias = clsim.I3CLSimFunctionConstant(
UnWeightedPhotonsScalingFactor)
else:
wavelengthGenerationBias = None
# create wavelength generators
wavelengthGenerators = [
clsim.makeCherenkovWavelengthGenerator(wavelengthGenerationBias,
UnWeightedPhotons,
mediumProperties)
]
# flasher parameterizations
if SimulateFlashers:
# this needs a spectrum table in order to pass spectra to OpenCL
spectrumTable = clsim.I3CLSimSpectrumTable()
for spectrum in spectrumTable:
wavelengthGenerators.append(
makeWavelengthGenerator(spectrum, wavelengthGenerationBias,
mediumProperties))
print("number of spectra (1x Cherenkov + Nx flasher):",
len(spectrumTable))
else:
# no spectrum table is necessary when only using the Cherenkov spectrum
spectrumTable = None
# muon&cascade parameterizations
ppcConverter = clsim.I3CLSimLightSourceToStepConverterPPC(
photonsPerStep=200)
ppcConverter.SetUseCascadeExtension(UseCascadeExtension)
if not UseGeant4:
particleParameterizations = GetDefaultParameterizationList(
ppcConverter, muonOnly=False)
else:
if CrossoverEnergyEM > 0 or CrossoverEnergyHadron > 0:
particleParameterizations = GetHybridParameterizationList(
ppcConverter,
CrossoverEnergyEM=CrossoverEnergyEM,
CrossoverEnergyHadron=CrossoverEnergyHadron)
elif MMCTrackListName is None or MMCTrackListName == "":
particleParameterizations = [
] # make sure absolutely **no** parameterizations are used
else:
# use no parameterizations except for muons with lengths assigned to them
# (those are assumed to have been generated by MMC)
particleParameterizations = GetDefaultParameterizationList(
ppcConverter, muonOnly=True)
return dict(Geometry=geometry,
MediumProperties=mediumProperties,
IceModelLocation=IceModelLocation,
WavelengthGenerationBias=wavelengthGenerationBias,
SpectrumTable=spectrumTable,
GenerateCherenkovPhotonsWithoutDispersion=UnWeightedPhotons,
WavelengthGenerators=wavelengthGenerators,
DOMRadius=DOMRadius,
DOMOversizeFactor=DOMOversizeFactor,
DOMPancakeFactor=DOMOversizeFactor,
UnshadowedFraction=UnshadowedFraction,
AngularAcceptance=angularAcceptance,
WavelengthAcceptance=domAcceptance,
ParameterizationList=particleParameterizations,
IgnoreSubdetectors=IgnoreSubdetectors)
def getDetectorParameters(
IceModel="spice_lea",
DisableTilt=False,
UnshadowedFraction=0.95, #1.,match the clsim setting
UseHoleIceParameterization=True,
DOMOversizeFactor=5.,
UnWeightedPhotons=False):
DOMRadius = 0.16510 * icetray.I3Units.m # 13" diameter
# ice properties
if isinstance(IceModel, str):
mediumProperties = parseIceModel(os.path.expandvars(
'$I3_BUILD/clsim/resources/ice/%s' % IceModel),
disableTilt=DisableTilt)
else:
# get ice model directly if not a string
mediumProperties = IceModel
# detector properties
if UseHoleIceParameterization:
print "calculating DOM efficiency correction using hole ice"
# the hole ice acceptance curve peaks at 0.75 instead of 1
domEfficiencyCorrection = UnshadowedFraction * 0.75 * 1.35 * 1.01 # DeepCore DOMs have a relative efficiency of 1.35 plus security margin of +1%
else:
domEfficiencyCorrection = UnshadowedFraction * 1.35 * 1.01 # security margin of +1%
print "from tray segment: domEfficiencyCorrection is ", domEfficiencyCorrection
domAcceptance = clsim.GetIceCubeDOMAcceptance(
domRadius=DOMRadius * DOMOversizeFactor,
efficiency=domEfficiencyCorrection)
print "from tray segment: domAcceptance NumEntries is ", domAcceptance.GetNumEntries(
)
print "from tray segment: domAcceptance MinWlen is ", domAcceptance.GetMinWlen(
)
print "from tray segment: domAcceptance MaxWlen is ", domAcceptance.GetMaxWlen(
)
print "from tray segment: domAcceptance FirstWlen is ", domAcceptance.GetFirstWavelength(
)
print "from tray segment: domAcceptance WlenStepping is ", domAcceptance.GetWavelengthStepping(
)
print "from tray segment: domAcceptance 4th entry value is ", domAcceptance.GetEntryValue(
4)
print "from tray segment: domAcceptance 4th entry wlen is ", domAcceptance.GetEntryWavelength(
4)
domAngularSensitivity = clsim.GetIceCubeDOMAngularSensitivity(
holeIce=UseHoleIceParameterization)
print "from tray segment: domAngularSensitivity coefficients are ", domAngularSensitivity.GetCoefficients(
)
print "from tray segment: with hole ice ", UseHoleIceParameterization
if not UnWeightedPhotons:
wavelengthGenerationBias = domAcceptance
else:
wavelengthGenerationBias = None
print "from tray segment: wavelengthGenerationBias is ", wavelengthGenerationBias
wavelengthGenerators = clsim.I3CLSimRandomValuePtrSeries()
wavelengthGenerators.append(
clsim.makeCherenkovWavelengthGenerator(wavelengthGenerationBias,
False, mediumProperties))
print "from tray segment: wavelengthGenerators is ", wavelengthGenerators #[0].NumberOfParameters() #no pybindings?
return mediumProperties, wavelengthGenerationBias, wavelengthGenerators, domAcceptance, domAngularSensitivity, DOMOversizeFactor
