def setup_converter(useGeant4=False):
# make a converter
if useGeant4:
ppcConverter = clsim.I3CLSimLightSourceToStepConverterGeant4()
else:
ppcConverter = clsim.I3CLSimLightSourceToStepConverterPPC(
photonsPerStep=200)
# initialize it
randomGen = phys_services.I3SPRNGRandomService(seed=123456,
nstreams=10000,
streamnum=1)
mediumProperties = clsim.MakeIceCubeMediumProperties()
#DOMRadius = 0.16510*icetray.I3Units.m # 13" diameter
#RadiusOverSizeFactor = 5.
#domAcceptance = clsim.GetIceCubeDOMAcceptance(domRadius = DOMRadius*RadiusOverSizeFactor)
domAcceptance = clsim.I3CLSimFunctionConstant(1.)
# lets set it up
ppcConverter.SetMediumProperties(mediumProperties)
ppcConverter.SetRandomService(randomGen)
ppcConverter.SetWlenBias(domAcceptance)
ppcConverter.SetMaxBunchSize(10240)
ppcConverter.SetBunchSizeGranularity(1)
ppcConverter.Initialize()
return ppcConverter
num = []
for number in num_orig:
num.append(
float(number) / float(samples) /
float(range_width / float(numBins)))
num = numpy.array(num)
bins = numpy.array(bins[:-1]) + (bins[1] - bins[0]) / 2.
return dict(num=num, bins=bins)
beta = 1.
mediumProps = clsim.MakeIceCubeMediumProperties()
domAcceptance = clsim.GetIceCubeDOMAcceptance()
flatAcceptance = clsim.I3CLSimFunctionConstant(1.)
phaseRefIndex = mediumProps.GetPhaseRefractiveIndex(0)
wlen_range = (mediumProps.GetMinWavelength() / I3Units.nanometer,
mediumProps.GetMaxWavelength() / I3Units.nanometer)
genWavelength = clsim.makeCherenkovWavelengthGenerator(domAcceptance, False,
mediumProps)
histGenWavelength = genMCHistogramsOpenCL(genWavelength, hist_range=wlen_range)
histGenWavelengthHost = genMCHistogramsHost(genWavelength,
hist_range=wlen_range)
numberOfPhotonsPerMeter = clsim.NumberOfPhotonsPerMeter(
phaseRefIndex, domAcceptance, wlen_range[0] * I3Units.nanometer,
wlen_range[1] * I3Units.nanometer)
genWavelengthFlat = clsim.makeCherenkovWavelengthGenerator(
def I3CLSimMakePhotons(
tray,
name,
UseCPUs=False,
UseGPUs=True,
UseOnlyDeviceNumber=None,
MCTreeName="I3MCTree",
OutputMCTreeName=None,
FlasherInfoVectName=None,
FlasherPulseSeriesName=None,
MMCTrackListName="MMCTrackList",
PhotonSeriesName="PhotonSeriesMap",
ParallelEvents=1000,
TotalEnergyToProcess=0.,
RandomService=None,
IceModelLocation=expandvars("$I3_SRC/clsim/resources/ice/spice_mie"),
DisableTilt=False,
UnWeightedPhotons=False,
UnWeightedPhotonsScalingFactor=None,
UseGeant4=False,
CrossoverEnergyEM=None,
CrossoverEnergyHadron=None,
UseCascadeExtension=True,
StopDetectedPhotons=True,
PhotonHistoryEntries=0,
DoNotParallelize=False,
DOMOversizeFactor=5.,
UnshadowedFraction=0.9,
HoleIceParameterization=expandvars(
"$I3_SRC/ice-models/resources/models/angsens/as.h2-50cm"),
WavelengthAcceptance=None,
DOMRadius=0.16510 * icetray.I3Units.m, # 13" diameter
OverrideApproximateNumberOfWorkItems=None,
IgnoreSubdetectors=['IceTop'],
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 PhotonSeriesName:
Configure this to enable writing an I3PhotonSeriesMap containing
all photons that reached the DOM surface.
: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 TotalEnergyToProcess:
clsim will work on a couple of events in parallel in order
not to starve the GPU. With this setting clsim will figure out
how many frames to accumulate as to not starve the GPU based on
the energy of the light sources that are producing the photons
in the detector. 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.
This cannot be used in flasher mode, since we cannot measure
the energy of the light sources.
: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 IceModelLocation:
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 DisableTilt:
Do not simulate ice tilt, even if the ice model directory
provides tilt information. (Photonics-based models will never
have tilt.)
:param UnWeightedPhotons:
Enabling this setting will disable all optimizations. These
are currently a DOM oversize factor of 5 (with the appropriate
timing correction) and a biased initial photon spectrum that
includes the DOM spectral acceptance. Enabling this setting
essentially means that all photons that would be generated
in the real detector *will* actually be generated. This will siginificatly
slow down the simulation, but the optional ``PhotonSeries``
will contain an unweighted sample of photons that arrive
at your DOMs. This can be useful for DOM acceptance studies.
:param UnWeightedPhotonsScalingFactor:
If UnWeightedPhotons is turned on, this can be used to scale
down the overall number of photons generated. This should normally
not be touched (it can be used when generating photon paths
for animation). Valid range is a float >0. and <=1.
:param StopDetectedPhotons:
Configures behaviour for photons that hit a DOM. If this is true (the default)
photons will be stopped once they hit a DOM. If this is false, they continue to
propagate.
:param PhotonHistoryEntries:
The maximum number of scatterings points to be saved for every photon hitting a DOM.
Only the most recent positions are saved, older positions are overwritten if
the maximum size is reached.
: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 set, the cascade light emission parameterizations will include
longitudinal extension. Otherwise, parameterized cascades will be
treated as point-like.
: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 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_SRC/ice-models/resources/models/angsens/as.nominal
for no hole ice parameterization.
:param WavelengthAcceptance:
If specified, use this wavelength acceptance to scale the generated
Cherenkov spectrum rather than using the DOM acceptance modified for
oversizing and angular acceptance.
:param DOMRadius:
Allow the DOMRadius to be set externally, for things like mDOMs.
: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) and
("I3ModuleGeoMap" 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()
# warn the user in case they might have done something they probably don't want
if UnWeightedPhotons and (DOMOversizeFactor != 1.):
print("********************")
print(
"Enabling the clsim.I3CLSimMakeHits() \"UnWeightedPhotons=True\" option without setting"
)
print(
"\"DOMOversizeFactor=1.\" will still apply a constant weighting factor of DOMOversizeFactor**2."
)
print("If this is what you want, you can safely ignore this warning.")
print("********************")
# a constant
Jitter = 2. * icetray.I3Units.ns
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
# 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 * 1.35 * 1.01 # DeepCore DOMs have a relative efficiency of 1.35 plus security margin of +1%
domAcceptance = clsim.GetIceCubeDOMAcceptance(
domRadius=DOMRadius * DOMOversizeFactor,
efficiency=domEfficiencyCorrection)
else:
domAcceptance = WavelengthAcceptance
# photon generation wavelength bias
if not UnWeightedPhotons:
wavelengthGenerationBias = domAcceptance
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
# 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)
print("number of spectra (1x Cherenkov + Nx flasher):",
len(spectrumTable))
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)
if PhotonHistoryEntries == 0:
module = 'I3CLSimModule<I3CompressedPhotonSeriesMap>'
else:
module = 'I3CLSimModule<I3PhotonSeriesMap>'
tray.AddModule(
module,
name + "_clsim",
MCTreeName=clSimMCTreeName,
PhotonSeriesMapName=PhotonSeriesName,
DOMRadius=DOMRadius,
DOMOversizeFactor=DOMOversizeFactor,
DOMPancakeFactor=
DOMOversizeFactor, # you will probably want this to be the same as DOMOversizeFactor
RandomService=RandomService,
MediumProperties=mediumProperties,
SpectrumTable=spectrumTable,
FlasherPulseSeriesName=clSimFlasherPulseSeriesName,
OMKeyMaskName=clSimOMKeyMaskName,
#IgnoreNonIceCubeOMNumbers=False,
GenerateCherenkovPhotonsWithoutDispersion=False,
WavelengthGenerationBias=wavelengthGenerationBias,
ParameterizationList=particleParameterizations,
MaxNumParallelEvents=ParallelEvents,
TotalEnergyToProcess=TotalEnergyToProcess,
OpenCLDeviceList=openCLDevices,
#UseHardcodedDeepCoreSubdetector=False, # setting this to true saves GPU constant memory but will reduce performance
StopDetectedPhotons=StopDetectedPhotons,
PhotonHistoryEntries=PhotonHistoryEntries,
IgnoreSubdetectors=IgnoreSubdetectors,
If=If,
**ExtraArgumentsToI3CLSimModule)
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 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)