def addPythia8(
sequencer: acts.examples.Sequencer,
rnd: acts.examples.RandomNumbers,
nhard=1,
npileup=200,
beam0=acts.PdgParticle.eProton,
beam1=acts.PdgParticle.eProton,
cmsEnergy=14 * acts.UnitConstants.TeV,
vertexStddev: acts.Vector4 = acts.Vector4(0, 0, 0, 0),
vertexMean: acts.Vector4 = acts.Vector4(0, 0, 0, 0),
):
"""This function steers the particle generation using Pythia8
NB. this version is included here only for compatibility. Please use pythia8.addPythia8 instead.
"""
import pythia8
evGen = pythia8.addPythia8(
sequencer,
rnd=rnd,
nhard=nhard,
npileup=npileup,
beam=(beam0, beam1),
cmsEnergy=cmsEnergy,
vtxGen=acts.examples.GaussianVertexGenerator(stddev=vertexStddev,
mean=vertexMean),
returnEvGen=True,
)
return evGen
def _factory(s):
evGen = acts.examples.EventGenerator(
level=acts.logging.INFO,
generators=[
acts.examples.EventGenerator.Generator(
multiplicity=acts.examples.FixedMultiplicityGenerator(n=2),
vertex=acts.examples.GaussianVertexGenerator(
stddev=acts.Vector4(0, 0, 0, 0),
mean=acts.Vector4(0, 0, 0, 0)),
particles=acts.examples.ParametricParticleGenerator(
p=(1 * u.GeV, 10 * u.GeV),
eta=(-2, 2),
phi=(0, 360 * u.degree),
randomizeCharge=True,
numParticles=2,
),
)
],
outputParticles="particles_input",
randomNumbers=rng,
)
s.addReader(evGen)
return evGen
def runMaterialRecording(g4geo, outputDir, tracksPerEvent=10000, s=None):
global _material_recording_executed
if _material_recording_executed:
warnings.warn("Material recording already ran in this process. Expect crashes")
_material_recording_executed = True
rnd = RandomNumbers(seed=228)
s = s or acts.examples.Sequencer(events=2, numThreads=1)
evGen = EventGenerator(
level=acts.logging.INFO,
generators=[
EventGenerator.Generator(
multiplicity=FixedMultiplicityGenerator(n=1),
vertex=GaussianVertexGenerator(
stddev=acts.Vector4(0, 0, 0, 0),
mean=acts.Vector4(0, 0, 0, 0),
),
particles=ParametricParticleGenerator(
p=(1 * u.GeV, 10 * u.GeV), eta=(-4, 4), numParticles=tracksPerEvent
),
)
],
outputParticles="particles_initial",
randomNumbers=rnd,
)
s.addReader(evGen)
g4AlgCfg = acts.examples.geant4.materialRecordingConfig(
level=acts.logging.INFO,
detector=g4geo,
inputParticles=evGen.config.outputParticles,
outputMaterialTracks="material_tracks",
)
g4AlgCfg.detectorConstruction = g4geo
g4Alg = acts.examples.geant4.Geant4Simulation(
level=acts.logging.INFO, config=g4AlgCfg
)
s.addAlgorithm(g4Alg)
s.addWriter(
acts.examples.RootMaterialTrackWriter(
prePostStep=True,
recalculateTotals=True,
collection="material_tracks",
filePath=os.path.join(outputDir, "geant4_material_tracks.root"),
level=acts.logging.INFO,
)
)
return s
def addPythia8(
sequencer: acts.examples.Sequencer,
rnd: acts.examples.RandomNumbers,
nhard=1,
npileup=200,
beam0=acts.PdgParticle.eProton,
beam1=acts.PdgParticle.eProton,
cmsEnergy=14 * acts.UnitConstants.TeV,
vertexStddev: acts.Vector4 = acts.Vector4(0, 0, 0, 0),
vertexMean: acts.Vector4 = acts.Vector4(0, 0, 0, 0),
):
vertexGenerator = acts.examples.GaussianVertexGenerator(
stddev=vertexStddev, mean=vertexMean
)
generators = []
if nhard > 0:
generators.append(
acts.examples.EventGenerator.Generator(
multiplicity=acts.examples.FixedMultiplicityGenerator(n=nhard),
vertex=vertexGenerator,
particles=acts.examples.pythia8.Pythia8Generator(
level=acts.logging.INFO,
pdgBeam0=beam0,
pdgBeam1=beam1,
cmsEnergy=cmsEnergy,
settings=["HardQCD:all = on"],
),
)
)
if npileup > 0:
generators.append(
acts.examples.EventGenerator.Generator(
multiplicity=acts.examples.FixedMultiplicityGenerator(n=npileup),
vertex=vertexGenerator,
particles=acts.examples.pythia8.Pythia8Generator(
level=acts.logging.INFO,
pdgBeam0=beam0,
pdgBeam1=beam1,
cmsEnergy=cmsEnergy,
settings=["SoftQCD:all = on"],
),
)
)
# Input
evGen = acts.examples.EventGenerator(
level=acts.logging.INFO,
generators=generators,
outputParticles="particles_input",
randomNumbers=rnd,
)
sequencer.addReader(evGen)
return evGen
def runEventRecording(g4geo, outputDir, s=None):
hepmc_dir = os.path.join(outputDir, "hepmc3")
if not os.path.exists(hepmc_dir):
os.mkdir(hepmc_dir)
s = s or acts.examples.Sequencer(
events=int(os.environ.get("NEVENTS", 100)), numThreads=1)
rnd = acts.examples.RandomNumbers(seed=42)
evGen = acts.examples.EventGenerator(
level=acts.logging.INFO,
generators=[
acts.examples.EventGenerator.Generator(
multiplicity=acts.examples.FixedMultiplicityGenerator(n=2),
vertex=acts.examples.GaussianVertexGenerator(
stddev=acts.Vector4(0, 0, 0, 0),
mean=acts.Vector4(0, 0, 0, 0)),
particles=acts.examples.ParametricParticleGenerator(
p=(1 * u.GeV, 10 * u.GeV),
eta=(-2, 2),
phi=(0, 90 * u.degree),
randomizeCharge=True,
numParticles=4,
),
)
],
outputParticles="particles_input",
randomNumbers=rnd,
)
s.addReader(evGen)
erAlgCfg = acts.examples.geant4.hepmc3.EventRecording.Config(
inputParticles=evGen.config.outputParticles,
outputHepMcTracks="geant-event",
seed1=43,
seed2=44,
detectorConstruction=g4geo,
)
erAlg = acts.examples.geant4.hepmc3.EventRecording(config=erAlgCfg,
level=acts.logging.INFO)
s.addAlgorithm(erAlg)
s.addWriter(
acts.examples.hepmc3.HepMC3AsciiWriter(
level=acts.logging.INFO,
outputDir=hepmc_dir,
outputStem="events",
inputEvents=erAlg.config.outputHepMcTracks,
))
return s
def test_algebra():
v3 = acts.Vector3(1, 2, 3)
with pytest.raises(TypeError):
acts.Vector3(1, 2, 3, 4)
with pytest.raises(TypeError):
acts.Vector3(1, 2)
v3 = acts.Vector3([1, 2, 3])
with pytest.raises(TypeError):
acts.Vector3([1, 2, 3, 4])
with pytest.raises(TypeError):
acts.Vector3([1, 2])
with pytest.raises(TypeError):
acts.Vector3()
v4 = acts.Vector4(1, 2, 3, 4)
with pytest.raises(TypeError):
v4 = acts.Vector4(1, 2, 3)
v4 = acts.Vector4([1, 2, 3, 4])
with pytest.raises(TypeError):
acts.Vector4([1, 2, 3])
with pytest.raises(TypeError):
acts.Vector4()
def runTruthTracking(
trackingGeometry,
field,
outputDir: Path,
digiConfigFile: Path,
directNavigation=False,
s: acts.examples.Sequencer = None,
):
# Preliminaries
rnd = acts.examples.RandomNumbers()
# Sequencer
s = s or acts.examples.Sequencer(
events=10, numThreads=-1, logLevel=acts.logging.INFO)
# Input
vtxGen = acts.examples.GaussianVertexGenerator()
vtxGen.stddev = acts.Vector4(0, 0, 0, 0)
ptclGen = acts.examples.ParametricParticleGenerator(p=(1 * u.GeV,
10 * u.GeV),
eta=(-2, 2),
numParticles=2)
g = acts.examples.EventGenerator.Generator()
g.multiplicity = acts.examples.FixedMultiplicityGenerator()
g.vertex = vtxGen
g.particles = ptclGen
evGen = acts.examples.EventGenerator(
level=acts.logging.INFO,
generators=[g],
outputParticles="particles_input",
randomNumbers=rnd,
)
s.addReader(evGen)
s.addWriter(
acts.examples.RootParticleWriter(
level=acts.logging.INFO,
inputParticles=evGen.config.outputParticles,
filePath=str(outputDir / "particles.root"),
))
# Selector
selector = acts.examples.ParticleSelector(
level=acts.logging.INFO,
inputParticles=evGen.config.outputParticles,
outputParticles="particles_selected",
)
s.addAlgorithm(selector)
# Simulation
simAlg = acts.examples.FatrasSimulation(
level=acts.logging.INFO,
inputParticles=selector.config.outputParticles,
outputParticlesInitial="particles_initial",
outputParticlesFinal="particles_final",
outputSimHits="simhits",
randomNumbers=rnd,
trackingGeometry=trackingGeometry,
magneticField=field,
generateHitsOnSensitive=True,
)
s.addAlgorithm(simAlg)
# Digitization
digiCfg = acts.examples.DigitizationConfig(
acts.examples.readDigiConfigFromJson(str(digiConfigFile), ),
trackingGeometry=trackingGeometry,
randomNumbers=rnd,
inputSimHits=simAlg.config.outputSimHits,
)
digiAlg = acts.examples.DigitizationAlgorithm(digiCfg, acts.logging.INFO)
s.addAlgorithm(digiAlg)
selAlg = acts.examples.TruthSeedSelector(
level=acts.logging.INFO,
ptMin=500 * u.MeV,
nHitsMin=9,
inputParticles=simAlg.config.outputParticlesInitial,
inputMeasurementParticlesMap=digiCfg.outputMeasurementParticlesMap,
outputParticles="particles_seed_selected",
)
s.addAlgorithm(selAlg)
inputParticles = selAlg.config.outputParticles
smearAlg = acts.examples.ParticleSmearing(
level=acts.logging.INFO,
inputParticles=inputParticles,
outputTrackParameters="smearedparameters",
randomNumbers=rnd,
# Gaussian sigmas to smear particle parameters
# sigmaD0=20 * u.um,
# sigmaD0PtA=30 * u.um,
# sigmaD0PtB=0.3 / u.GeV,
# sigmaZ0=20 * u.um,
# sigmaZ0PtA=30 * u.um,
# sigmaZ0PtB=0.3 / u.GeV,
# sigmaPhi=1 * u.degree,
# sigmaTheta=1 * u.degree,
# sigmaPRel=0.01,
# sigmaT0=1 * u.ns,
# initialVarInflation=[1, 1, 1, 1, 1, 1],
)
s.addAlgorithm(smearAlg)
truthTrkFndAlg = acts.examples.TruthTrackFinder(
level=acts.logging.INFO,
inputParticles=inputParticles,
inputMeasurementParticlesMap=digiAlg.config.
outputMeasurementParticlesMap,
outputProtoTracks="prototracks",
)
s.addAlgorithm(truthTrkFndAlg)
if directNavigation:
srfSortAlg = acts.examples.SurfaceSortingAlgorithm(
level=acts.logging.INFO,
inputProtoTracks=truthTrkFndAlg.config.outputProtoTracks,
inputSimulatedHits=simAlg.config.outputSimHits,
inputMeasurementSimHitsMap=digiAlg.config.
outputMeasurementSimHitsMap,
outputProtoTracks="sortedprototracks",
)
s.addAlgorithm(srfSortAlg)
inputProtoTracks = srfSortAlg.config.outputProtoTracks
else:
inputProtoTracks = truthTrkFndAlg.config.outputProtoTracks
fitAlg = acts.examples.TrackFittingAlgorithm(
level=acts.logging.INFO,
inputMeasurements=digiAlg.config.outputMeasurements,
inputSourceLinks=digiAlg.config.outputSourceLinks,
inputProtoTracks=inputProtoTracks,
inputInitialTrackParameters=smearAlg.config.outputTrackParameters,
outputTrajectories="trajectories",
directNavigation=directNavigation,
multipleScattering=True,
energyLoss=True,
pickTrack=-1,
trackingGeometry=trackingGeometry,
dFit=acts.examples.TrackFittingAlgorithm.makeTrackFitterFunction(
field),
fit=acts.examples.TrackFittingAlgorithm.makeTrackFitterFunction(
trackingGeometry, field),
)
s.addAlgorithm(fitAlg)
# Output
s.addWriter(
acts.examples.RootTrajectoryStatesWriter(
level=acts.logging.INFO,
inputTrajectories=fitAlg.config.outputTrajectories,
inputParticles=inputParticles,
inputSimHits=simAlg.config.outputSimHits,
inputMeasurementParticlesMap=digiAlg.config.
outputMeasurementParticlesMap,
inputMeasurementSimHitsMap=digiAlg.config.
outputMeasurementSimHitsMap,
filePath=str(outputDir / "trackstates_fitter.root"),
))
s.addWriter(
acts.examples.RootTrajectorySummaryWriter(
level=acts.logging.INFO,
inputTrajectories=fitAlg.config.outputTrajectories,
inputParticles=inputParticles,
inputMeasurementParticlesMap=digiAlg.config.
outputMeasurementParticlesMap,
filePath=str(outputDir / "tracksummary_fitter.root"),
))
s.addWriter(
acts.examples.TrackFinderPerformanceWriter(
level=acts.logging.INFO,
inputProtoTracks=truthTrkFndAlg.config.outputProtoTracks,
inputParticles=inputParticles,
inputMeasurementParticlesMap=digiAlg.config.
outputMeasurementParticlesMap,
filePath=str(outputDir / "performance_track_finder.root"),
))
s.addWriter(
acts.examples.TrackFitterPerformanceWriter(
level=acts.logging.INFO,
inputTrajectories=fitAlg.config.outputTrajectories,
inputParticles=inputParticles,
inputMeasurementParticlesMap=digiAlg.config.
outputMeasurementParticlesMap,
filePath=str(outputDir / "performance_track_fitter.root"),
))
return s
def runSeeding(trackingGeometry, field, outputDir, s=None):
srcdir = Path(__file__).resolve().parent.parent.parent.parent
csv_dir = os.path.join(outputDir, "csv")
if not os.path.exists(csv_dir):
os.mkdir(csv_dir)
# Input
rnd = acts.examples.RandomNumbers(seed=42)
evGen = acts.examples.EventGenerator(
level=acts.logging.INFO,
generators=[
acts.examples.EventGenerator.Generator(
multiplicity=acts.examples.FixedMultiplicityGenerator(n=2),
vertex=acts.examples.GaussianVertexGenerator(
stddev=acts.Vector4(0, 0, 0, 0),
mean=acts.Vector4(0, 0, 0, 0)),
particles=acts.examples.ParametricParticleGenerator(
p=(1 * u.GeV, 10 * u.GeV),
eta=(-2, 2),
phi=(0, 360 * u.degree),
randomizeCharge=True,
numParticles=4,
),
)
],
outputParticles="particles_input",
randomNumbers=rnd,
)
# Read input from input collection (e.g. Pythia8 output)
# evGen = acts.examples.RootParticleReader(
# level=acts.logging.INFO,
# particleCollection="particles_input",
# inputDir="output",
# inputFile="pythia8_particles.root",
# )
# Simulation
simAlg = acts.examples.FatrasSimulation(
level=acts.logging.INFO,
inputParticles=evGen.config.outputParticles,
# inputParticles=evGen.config.particleCollection,
outputParticlesInitial="particles_initial",
outputParticlesFinal="particles_final",
outputSimHits="simhits",
randomNumbers=rnd,
trackingGeometry=trackingGeometry,
magneticField=field,
generateHitsOnSensitive=True,
)
# Digitization
digiCfg = acts.examples.DigitizationConfig(
acts.examples.readDigiConfigFromJson(
str(srcdir /
"Examples/Algorithms/Digitization/share/default-smearing-config-generic.json"
)),
trackingGeometry=trackingGeometry,
randomNumbers=rnd,
inputSimHits=simAlg.config.outputSimHits,
)
digiAlg = acts.examples.DigitizationAlgorithm(digiCfg, acts.logging.INFO)
selAlg = acts.examples.TruthSeedSelector(
level=acts.logging.INFO,
ptMin=1 * u.GeV,
eta=(-2.5, 2.5),
nHitsMin=9,
inputParticles=simAlg.config.outputParticlesFinal,
inputMeasurementParticlesMap=digiCfg.outputMeasurementParticlesMap,
outputParticles="particles_selected",
)
inputParticles = selAlg.config.outputParticles
spAlg = acts.examples.SpacePointMaker(
level=acts.logging.INFO,
inputSourceLinks=digiCfg.outputSourceLinks,
inputMeasurements=digiCfg.outputMeasurements,
outputSpacePoints="spacepoints",
trackingGeometry=trackingGeometry,
geometrySelection=acts.examples.readJsonGeometryList(
str(srcdir /
"Examples/Algorithms/TrackFinding/share/geoSelection-genericDetector.json"
)),
)
gridConfig = acts.SpacePointGridConfig(
bFieldInZ=1.99724 * u.T,
minPt=500 * u.MeV,
rMax=200 * u.mm,
zMax=2000 * u.mm,
zMin=-2000 * u.mm,
deltaRMax=60 * u.mm,
cotThetaMax=7.40627, # 2.7 eta
)
seedFilterConfig = acts.SeedFilterConfig(maxSeedsPerSpM=1,
deltaRMin=1 * u.mm)
seedFinderConfig = acts.SeedfinderConfig(
rMax=gridConfig.rMax,
deltaRMin=seedFilterConfig.deltaRMin,
deltaRMax=gridConfig.deltaRMax,
collisionRegionMin=-250 * u.mm,
collisionRegionMax=250 * u.mm,
zMin=gridConfig.zMin,
zMax=gridConfig.zMax,
maxSeedsPerSpM=seedFilterConfig.maxSeedsPerSpM,
cotThetaMax=gridConfig.cotThetaMax,
sigmaScattering=50,
radLengthPerSeed=0.1,
minPt=gridConfig.minPt,
bFieldInZ=gridConfig.bFieldInZ,
beamPos=acts.Vector2(0 * u.mm, 0 * u.mm),
impactMax=3 * u.mm,
)
seedingAlg = acts.examples.SeedingAlgorithm(
level=acts.logging.VERBOSE,
inputSpacePoints=[spAlg.config.outputSpacePoints],
outputSeeds="seeds",
outputProtoTracks="prototracks",
gridConfig=gridConfig,
seedFilterConfig=seedFilterConfig,
seedFinderConfig=seedFinderConfig,
)
parEstimateAlg = acts.examples.TrackParamsEstimationAlgorithm(
level=acts.logging.VERBOSE,
inputProtoTracks=seedingAlg.config.outputProtoTracks,
inputSpacePoints=[spAlg.config.outputSpacePoints],
inputSourceLinks=digiCfg.outputSourceLinks,
outputTrackParameters="estimatedparameters",
outputProtoTracks="prototracks_estimated",
trackingGeometry=trackingGeometry,
magneticField=field,
)
s = s or acts.examples.Sequencer(
events=100, numThreads=-1, logLevel=acts.logging.INFO)
s.addReader(evGen)
s.addAlgorithm(simAlg)
s.addAlgorithm(digiAlg)
s.addAlgorithm(selAlg)
s.addAlgorithm(spAlg)
s.addAlgorithm(seedingAlg)
s.addAlgorithm(parEstimateAlg)
s.addWriter(
acts.examples.RootParticleWriter(
level=acts.logging.INFO,
inputParticles=evGen.config.outputParticles,
filePath=outputDir + "/evgen_particles.root",
))
s.addWriter(
acts.examples.CsvParticleWriter(
level=acts.logging.INFO,
inputParticles=evGen.config.outputParticles,
outputStem="evgen_particles",
outputDir=outputDir + "/csv",
))
s.addWriter(
acts.examples.RootParticleWriter(
level=acts.logging.INFO,
inputParticles=simAlg.config.outputParticlesFinal,
filePath=outputDir + "/fatras_particles_final.root",
))
s.addWriter(
acts.examples.CsvParticleWriter(
level=acts.logging.INFO,
inputParticles=simAlg.config.outputParticlesFinal,
outputStem="fatras_particles_final",
outputDir=outputDir + "/csv",
))
s.addWriter(
acts.examples.RootParticleWriter(
level=acts.logging.INFO,
inputParticles=simAlg.config.outputParticlesInitial,
filePath=outputDir + "/fatras_particles_initial.root",
))
s.addWriter(
acts.examples.CsvParticleWriter(
level=acts.logging.INFO,
inputParticles=simAlg.config.outputParticlesInitial,
outputStem="fatras_particles_initial",
outputDir=outputDir + "/csv",
))
s.addWriter(
acts.examples.TrackFinderPerformanceWriter(
level=acts.logging.INFO,
inputProtoTracks=seedingAlg.config.outputProtoTracks,
inputParticles=inputParticles,
inputMeasurementParticlesMap=digiCfg.outputMeasurementParticlesMap,
filePath=outputDir + "/performance_seeding_trees.root",
))
s.addWriter(
acts.examples.SeedingPerformanceWriter(
level=acts.logging.DEBUG,
inputProtoTracks=seedingAlg.config.outputProtoTracks,
inputParticles=inputParticles,
inputMeasurementParticlesMap=digiCfg.outputMeasurementParticlesMap,
filePath=outputDir + "/performance_seeding_hists.root",
))
s.addWriter(
acts.examples.RootTrackParameterWriter(
level=acts.logging.VERBOSE,
inputTrackParameters=parEstimateAlg.config.outputTrackParameters,
inputProtoTracks=parEstimateAlg.config.outputProtoTracks,
inputParticles=simAlg.config.outputParticlesFinal,
inputSimHits=simAlg.config.outputSimHits,
inputMeasurementParticlesMap=digiCfg.outputMeasurementParticlesMap,
inputMeasurementSimHitsMap=digiCfg.outputMeasurementSimHitsMap,
filePath=outputDir + "/estimatedparams.root",
treeName="estimatedparams",
))
return s
def runCKFTracks(
trackingGeometry,
decorators,
geometrySelection: Path,
digiConfigFile: Path,
field,
outputDir: Path,
truthSmearedSeeded=False,
truthEstimatedSeeded=False,
outputCsv=True,
inputParticlePath: Optional[Path] = None,
s=None,
):
s = s or Sequencer(events=100, numThreads=-1)
logger = acts.logging.getLogger("CKFExample")
for d in decorators:
s.addContextDecorator(d)
rnd = acts.examples.RandomNumbers(seed=42)
if inputParticlePath is None:
logger.info("Generating particles using particle gun")
evGen = acts.examples.EventGenerator(
level=acts.logging.INFO,
generators=[
acts.examples.EventGenerator.Generator(
multiplicity=acts.examples.FixedMultiplicityGenerator(n=2),
vertex=acts.examples.GaussianVertexGenerator(
stddev=acts.Vector4(0, 0, 0, 0),
mean=acts.Vector4(0, 0, 0, 0)),
particles=acts.examples.ParametricParticleGenerator(
p=(1 * u.GeV, 10 * u.GeV),
eta=(-2, 2),
phi=(0, 360 * u.degree),
randomizeCharge=True,
numParticles=4,
),
)
],
outputParticles="particles_input",
randomNumbers=rnd,
)
s.addReader(evGen)
inputParticles = evGen.config.outputParticles
else:
logger.info("Reading particles from %s", inputParticlePath.resolve())
assert inputParticlePath.exists()
inputParticles = "particles_read"
s.addReader(
RootParticleReader(
level=acts.logging.INFO,
filePath=str(inputParticlePath.resolve()),
particleCollection=inputParticles,
orderedEvents=False,
))
# Selector
selector = acts.examples.ParticleSelector(
level=acts.logging.INFO,
inputParticles=inputParticles,
outputParticles="particles_selected",
)
s.addAlgorithm(selector)
# Simulation
simAlg = acts.examples.FatrasSimulation(
level=acts.logging.INFO,
inputParticles=selector.config.outputParticles,
outputParticlesInitial="particles_initial",
outputParticlesFinal="particles_final",
outputSimHits="simhits",
randomNumbers=rnd,
trackingGeometry=trackingGeometry,
magneticField=field,
generateHitsOnSensitive=True,
)
s.addAlgorithm(simAlg)
# Run the sim hits smearing
digiCfg = acts.examples.DigitizationConfig(
acts.examples.readDigiConfigFromJson(str(digiConfigFile)),
trackingGeometry=trackingGeometry,
randomNumbers=rnd,
inputSimHits=simAlg.config.outputSimHits,
)
digiAlg = acts.examples.DigitizationAlgorithm(digiCfg, acts.logging.INFO)
s.addAlgorithm(digiAlg)
# Run the particle selection
# The pre-selection will select truth particles satisfying provided criteria
# from all particles read in by particle reader for further processing. It
# has no impact on the truth hits themselves
selAlg = acts.examples.TruthSeedSelector(
level=acts.logging.INFO,
ptMin=500 * u.MeV,
nHitsMin=9,
inputParticles=simAlg.config.outputParticlesInitial,
inputMeasurementParticlesMap=digiCfg.outputMeasurementParticlesMap,
outputParticles="particles_seed_selected",
)
s.addAlgorithm(selAlg)
inputParticles = selAlg.config.outputParticles
# Create starting parameters from either particle smearing or combined seed
# finding and track parameters estimation
if truthSmearedSeeded:
logger.info("Using smeared truth particles for seeding")
# Run particle smearing
ptclSmear = acts.examples.ParticleSmearing(
level=acts.logging.INFO,
inputParticles=inputParticles,
outputTrackParameters="smearedparameters",
randomNumbers=rnd,
# gaussian sigmas to smear particle parameters
sigmaD0=20 * u.um,
sigmaD0PtA=30 * u.um,
sigmaD0PtB=0.3 / 1 * u.GeV,
sigmaZ0=20 * u.um,
sigmaZ0PtA=30 * u.um,
sigmaZ0PtB=0.3 / 1 * u.GeV,
sigmaPhi=1 * u.degree,
sigmaTheta=1 * u.degree,
sigmaPRel=0.01,
sigmaT0=1 * u.ns,
initialVarInflation=[1, 1, 1, 1, 1, 1],
)
outputTrackParameters = ptclSmear.config.outputTrackParameters
s.addAlgorithm(ptclSmear)
else:
# Create space points
spAlg = acts.examples.SpacePointMaker(
level=acts.logging.INFO,
inputSourceLinks=digiAlg.config.outputSourceLinks,
inputMeasurements=digiAlg.config.outputMeasurements,
outputSpacePoints="spacepoints",
trackingGeometry=trackingGeometry,
geometrySelection=acts.examples.readJsonGeometryList(
str(geometrySelection)),
)
s.addAlgorithm(spAlg)
# Run either: truth track finding or seeding
if truthEstimatedSeeded:
logger.info(
"Using truth track finding from space points for seeding")
# Use truth tracking
truthTrackFinder = acts.examples.TruthTrackFinder(
level=acts.logging.INFO,
inputParticles=inputParticles,
inputMeasurementParticlesMap=digiAlg.config.
outputMeasurementParticlesMap,
outputProtoTracks="prototracks",
)
s.addAlgorithm(truthTrackFinder)
inputProtoTracks = truthTrackFinder.config.outputProtoTracks
inputSeeds = ""
else:
logger.info("Using seeding")
# Use seeding
gridConfig = acts.SpacePointGridConfig(
bFieldInZ=1.99724 * u.T,
minPt=500 * u.MeV,
rMax=200 * u.mm,
zMax=2000 * u.mm,
zMin=-2000 * u.mm,
deltaRMax=60 * u.mm,
cotThetaMax=7.40627, # 2.7 eta
)
seedFilterConfig = acts.SeedFilterConfig(maxSeedsPerSpM=1,
deltaRMin=1 * u.mm)
seedFinderConfig = acts.SeedfinderConfig(
rMax=gridConfig.rMax,
deltaRMin=seedFilterConfig.deltaRMin,
deltaRMax=gridConfig.deltaRMax,
collisionRegionMin=-250 * u.mm,
collisionRegionMax=250 * u.mm,
zMin=gridConfig.zMin,
zMax=gridConfig.zMax,
maxSeedsPerSpM=seedFilterConfig.maxSeedsPerSpM,
cotThetaMax=gridConfig.cotThetaMax,
sigmaScattering=50,
radLengthPerSeed=0.1,
minPt=gridConfig.minPt,
bFieldInZ=gridConfig.bFieldInZ,
beamPos=acts.Vector2(0 * u.mm, 0 * u.mm),
impactMax=3 * u.mm,
)
seeding = acts.examples.SeedingAlgorithm(
level=acts.logging.INFO,
inputSpacePoints=[spAlg.config.outputSpacePoints],
outputSeeds="seeds",
outputProtoTracks="prototracks",
gridConfig=gridConfig,
seedFilterConfig=seedFilterConfig,
seedFinderConfig=seedFinderConfig,
)
s.addAlgorithm(seeding)
inputProtoTracks = seeding.config.outputProtoTracks
inputSeeds = seeding.config.outputSeeds
# Write truth track finding / seeding performance
trackFinderPerformanceWriter = acts.examples.TrackFinderPerformanceWriter(
level=acts.logging.INFO,
inputProtoTracks=inputProtoTracks,
inputParticles=
inputParticles, # the original selected particles after digitization
inputMeasurementParticlesMap=digiAlg.config.
outputMeasurementParticlesMap,
filePath=str(outputDir / "performance_seeding_trees.root"),
)
s.addWriter(trackFinderPerformanceWriter)
# Estimate track parameters from seeds
paramEstimation = acts.examples.TrackParamsEstimationAlgorithm(
level=acts.logging.INFO,
inputSeeds=inputSeeds,
inputProtoTracks=inputProtoTracks,
inputSpacePoints=[spAlg.config.outputSpacePoints],
inputSourceLinks=digiCfg.outputSourceLinks,
outputTrackParameters="estimatedparameters",
outputProtoTracks="prototracks_estimated",
trackingGeometry=trackingGeometry,
magneticField=field,
bFieldMin=0.1 * u.T,
deltaRMax=100.0 * u.mm,
deltaRMin=10.0 * u.mm,
sigmaLoc0=25.0 * u.um,
sigmaLoc1=100.0 * u.um,
sigmaPhi=0.02 * u.degree,
sigmaTheta=0.02 * u.degree,
sigmaQOverP=0.1 / 1.0 * u.GeV,
sigmaT0=1400.0 * u.s,
initialVarInflation=[1, 1, 1, 1, 1, 1],
)
s.addAlgorithm(paramEstimation)
outputTrackParameters = paramEstimation.config.outputTrackParameters
# Setup the track finding algorithm with CKF
# It takes all the source links created from truth hit smearing, seeds from
# truth particle smearing and source link selection config
trackFinder = acts.examples.TrackFindingAlgorithm(
level=acts.logging.INFO,
measurementSelectorCfg=acts.MeasurementSelector.Config([
(acts.GeometryIdentifier(), ([], [15.0], [10]))
]),
inputMeasurements=digiAlg.config.outputMeasurements,
inputSourceLinks=digiAlg.config.outputSourceLinks,
inputInitialTrackParameters=outputTrackParameters,
outputTrajectories="trajectories",
findTracks=acts.examples.TrackFindingAlgorithm.makeTrackFinderFunction(
trackingGeometry, field),
)
s.addAlgorithm(trackFinder)
# write track states from CKF
trackStatesWriter = acts.examples.RootTrajectoryStatesWriter(
level=acts.logging.INFO,
inputTrajectories=trackFinder.config.outputTrajectories,
# @note The full particles collection is used here to avoid lots of warnings
# since the unselected CKF track might have a majority particle not in the
# filtered particle collection. This could be avoided when a seperate track
# selection algorithm is used.
inputParticles=selector.config.outputParticles,
inputSimHits=simAlg.config.outputSimHits,
inputMeasurementParticlesMap=digiAlg.config.
outputMeasurementParticlesMap,
inputMeasurementSimHitsMap=digiAlg.config.outputMeasurementSimHitsMap,
filePath=str(outputDir / "trackstates_ckf.root"),
treeName="trackstates",
)
s.addWriter(trackStatesWriter)
# write track summary from CKF
trackSummaryWriter = acts.examples.RootTrajectorySummaryWriter(
level=acts.logging.INFO,
inputTrajectories=trackFinder.config.outputTrajectories,
# @note The full particles collection is used here to avoid lots of warnings
# since the unselected CKF track might have a majority particle not in the
# filtered particle collection. This could be avoided when a seperate track
# selection algorithm is used.
inputParticles=selector.config.outputParticles,
inputMeasurementParticlesMap=digiAlg.config.
outputMeasurementParticlesMap,
filePath=str(outputDir / "tracksummary_ckf.root"),
treeName="tracksummary",
)
s.addWriter(trackSummaryWriter)
# Write CKF performance data
ckfPerfWriter = acts.examples.CKFPerformanceWriter(
level=acts.logging.INFO,
inputParticles=inputParticles,
inputTrajectories=trackFinder.config.outputTrajectories,
inputMeasurementParticlesMap=digiAlg.config.
outputMeasurementParticlesMap,
# The bottom seed could be the first, second or third hits on the truth track
nMeasurementsMin=selAlg.config.nHitsMin - 3,
ptMin=0.4 * u.GeV,
filePath=str(outputDir / "performance_ckf.root"),
)
s.addWriter(ckfPerfWriter)
if outputCsv:
csv_dir = outputDir / "csv"
csv_dir.mkdir(parents=True, exist_ok=True)
logger.info("Writing CSV files")
csvMTJWriter = acts.examples.CsvMultiTrajectoryWriter(
level=acts.logging.INFO,
inputTrajectories=trackFinder.config.outputTrajectories,
inputMeasurementParticlesMap=digiAlg.config.
outputMeasurementParticlesMap,
outputDir=str(csv_dir),
)
s.addWriter(csvMTJWriter)
return s
def addPythia8(
s: acts.examples.Sequencer,
rnd: Optional[acts.examples.RandomNumbers] = None,
nhard: int = 1,
npileup: int = 200,
beam: Optional[
Union[acts.PdgParticle,
Iterable]] = None, # default: acts.PdgParticle.eProton
cmsEnergy: Optional[float] = None, # default: 14 * acts.UnitConstants.TeV
hardProcess: Optional[Iterable] = None, # default: ["HardQCD:all = on"]
pileupProcess: Iterable = ["SoftQCD:all = on"],
vtxGen: Optional[acts.examples.EventGenerator.VertexGenerator] = None,
outputDirCsv: Optional[Union[Path, str]] = None,
outputDirRoot: Optional[Union[Path, str]] = None,
printParticles: bool = False,
returnEvGen: bool = False,
) -> Union[acts.examples.Sequencer, acts.examples.EventGenerator]:
"""This function steers the particle generation using Pythia8
NB. this is a reimplementation of common.addPythia8, which is maintained for now for compatibility.
Parameters
----------
s: Sequencer
the sequencer module to which we add the particle gun steps (returned from addParticleGun)
rnd : RandomNumbers, None
random number generator
nhard, npileup : int, 1, 200
Number of hard-scatter and pileup vertices
beam : PdgParticle|[PdgParticle,PdgParticle], eProton
beam particle(s)
cmsEnergy : float, 14 TeV
CMS energy
hardProcess, pileupProcess : [str], ["HardQCD:all = on"], ["SoftQCD:all = on"]
hard and pileup processes
vtxGen : VertexGenerator, None
vertex generator module
outputDirCsv : Path|str, path, None
the output folder for the Csv output, None triggers no output
outputDirRoot : Path|str, path, None
the output folder for the Root output, None triggers no output
printParticles : bool, False
print generated particles
returnEvGen: bool, False
returns EventGenerator instead of Sequencer.
This option is included for compatibility and will be removed when common.addPythia8 is removed.
"""
if int(s.config.logLevel) <= int(acts.logging.DEBUG):
acts.examples.dump_args_calls(locals())
# Preliminaries
rnd = rnd or acts.examples.RandomNumbers()
vtxGen = vtxGen or acts.examples.GaussianVertexGenerator(
stddev=acts.Vector4(0, 0, 0, 0), mean=acts.Vector4(0, 0, 0, 0))
if not isinstance(beam, Iterable):
beam = (beam, beam)
generators = []
if nhard is not None and nhard > 0:
generators.append(
acts.examples.EventGenerator.Generator(
multiplicity=acts.examples.FixedMultiplicityGenerator(n=nhard),
vertex=vtxGen,
particles=acts.examples.pythia8.Pythia8Generator(
level=s.config.logLevel,
**acts.examples.defaultKWArgs(
pdgBeam0=beam[0],
pdgBeam1=beam[1],
cmsEnergy=cmsEnergy,
settings=hardProcess,
),
),
))
if npileup > 0:
generators.append(
acts.examples.EventGenerator.Generator(
multiplicity=acts.examples.FixedMultiplicityGenerator(
n=npileup),
vertex=vtxGen,
particles=acts.examples.pythia8.Pythia8Generator(
level=s.config.logLevel,
**acts.examples.defaultKWArgs(
pdgBeam0=beam[0],
pdgBeam1=beam[1],
cmsEnergy=cmsEnergy,
settings=pileupProcess,
),
),
))
# Input
evGen = acts.examples.EventGenerator(
level=s.config.logLevel,
generators=generators,
outputParticles="particles_input",
randomNumbers=rnd,
)
s.addReader(evGen)
if printParticles:
s.addAlgorithm(
acts.examples.ParticlesPrinter(
level=s.config.logLevel,
inputParticles=evGen.config.outputParticles))
if outputDirCsv is not None:
outputDirCsv = Path(outputDirCsv)
if not outputDirCsv.exists():
outputDirCsv.mkdir()
s.addWriter(
acts.examples.CsvParticleWriter(
level=s.config.logLevel,
inputParticles=evGen.config.outputParticles,
outputDir=str(outputDirCsv),
outputStem="particles",
))
if outputDirRoot is not None:
outputDirRoot = Path(outputDirRoot)
if not outputDirRoot.exists():
outputDirRoot.mkdir()
s.addWriter(
acts.examples.RootParticleWriter(
level=s.config.logLevel,
inputParticles=evGen.config.outputParticles,
filePath=str(outputDirRoot / "pythia8_particles.root"),
))
return evGen if returnEvGen else s
def addParticleGun(
s: Sequencer,
outputDirCsv: Optional[Union[Path, str]] = None,
outputDirRoot: Optional[Union[Path, str]] = None,
momentumConfig: MomentumConfig = MomentumConfig(),
etaConfig: EtaConfig = EtaConfig(),
phiConfig: PhiConfig = PhiConfig(),
particleConfig: ParticleConfig = ParticleConfig(),
multiplicity: int = 1,
vtxGen: Optional[EventGenerator.VertexGenerator] = None,
printParticles: bool = False,
rnd: Optional[RandomNumbers] = None,
) -> Sequencer:
"""This function steers the particle generation using the particle gun
Parameters
----------
s: Sequencer
the sequencer module to which we add the particle gun steps (returned from addParticleGun)
outputDirCsv : Path|str, path, None
the output folder for the Csv output, None triggers no output
outputDirRoot : Path|str, path, None
the output folder for the Root output, None triggers no output
momentumConfig : MomentumConfig(min, max, transverse)
momentum configuration: minimum momentum, maximum momentum, transverse
etaConfig : EtaConfig(min, max, uniform)
pseudorapidity configuration: eta min, eta max, uniform
phiConfig : PhiConfig(min, max)
azimuthal angle configuration: phi min, phi max
particleConfig : ParticleConfig(num, pdg, randomizeCharge)
partilce configuration: number of particles, particle type, charge flip
multiplicity : int, 1
number of generated vertices
vtxGen : VertexGenerator, None
vertex generator module
printParticles : bool, False
print generated particles
rnd : RandomNumbers, None
random number generator
"""
if int(s.config.logLevel) <= int(acts.logging.DEBUG):
acts.examples.dump_args_calls(locals())
# Preliminaries
rnd = rnd or RandomNumbers(seed=228)
# Input
evGen = EventGenerator(
level=s.config.logLevel,
generators=[
EventGenerator.Generator(
multiplicity=FixedMultiplicityGenerator(n=multiplicity),
vertex=vtxGen
or acts.examples.GaussianVertexGenerator(
stddev=acts.Vector4(0, 0, 0, 0), mean=acts.Vector4(0, 0, 0, 0)
),
particles=acts.examples.ParametricParticleGenerator(
**acts.examples.defaultKWArgs(
p=(momentumConfig.min, momentumConfig.max),
pTransverse=momentumConfig.transverse,
eta=(etaConfig.min, etaConfig.max),
phi=(phiConfig.min, phiConfig.max),
etaUniform=etaConfig.uniform,
numParticles=particleConfig.num,
pdg=particleConfig.pdg,
randomizeCharge=particleConfig.randomizeCharge,
)
),
)
],
outputParticles="particles_input",
randomNumbers=rnd,
)
s.addReader(evGen)
if printParticles:
s.addAlgorithm(
ParticlesPrinter(
level=s.config.logLevel, inputParticles=evGen.config.outputParticles
)
)
if outputDirCsv is not None:
outputDirCsv = Path(outputDirCsv)
if not outputDirCsv.exists():
outputDirCsv.mkdir()
s.addWriter(
CsvParticleWriter(
level=s.config.logLevel,
inputParticles=evGen.config.outputParticles,
outputDir=str(outputDirCsv),
outputStem="particles",
)
)
if outputDirRoot is not None:
outputDirRoot = Path(outputDirRoot)
if not outputDirRoot.exists():
outputDirRoot.mkdir()
s.addWriter(
RootParticleWriter(
level=s.config.logLevel,
inputParticles=evGen.config.outputParticles,
filePath=str(outputDirRoot / "particles.root"),
)
)
return s
def runFatras(trackingGeometry,
field,
outputDir,
s: acts.examples.Sequencer = None):
# Preliminaries
rnd = acts.examples.RandomNumbers()
# Input
vtxGen = acts.examples.GaussianVertexGenerator()
vtxGen.stddev = acts.Vector4(0, 0, 0, 0)
ptclGen = acts.examples.ParametricParticleGenerator(p=(1 * u.GeV,
10 * u.GeV),
eta=(-2, 2))
g = acts.examples.EventGenerator.Generator()
g.multiplicity = acts.examples.FixedMultiplicityGenerator()
g.vertex = vtxGen
g.particles = ptclGen
evGen = acts.examples.EventGenerator(
level=acts.logging.INFO,
generators=[g],
outputParticles="particles_input",
randomNumbers=rnd,
)
# Selector
selector = acts.examples.ParticleSelector(
level=acts.logging.INFO,
inputParticles=evGen.config.outputParticles,
outputParticles="particles_selected",
)
# Simulation
alg = acts.examples.FatrasSimulation(
level=acts.logging.INFO,
inputParticles=selector.config.outputParticles,
outputParticlesInitial="particles_initial",
outputParticlesFinal="particles_final",
outputSimHits="simhits",
randomNumbers=rnd,
trackingGeometry=trackingGeometry,
magneticField=field,
generateHitsOnSensitive=True,
)
# Sequencer
s = s or acts.examples.Sequencer(
events=100, numThreads=-1, logLevel=acts.logging.INFO)
s.addReader(evGen)
s.addAlgorithm(selector)
s.addAlgorithm(alg)
# Output
s.addWriter(
acts.examples.CsvParticleWriter(
level=acts.logging.INFO,
outputDir=outputDir + "/csv",
inputParticles="particles_final",
outputStem="particles_final",
))
s.addWriter(
acts.examples.RootParticleWriter(
level=acts.logging.INFO,
inputParticles="particles_final",
filePath=outputDir + "/fatras_particles_final.root",
))
s.addWriter(
acts.examples.CsvParticleWriter(
level=acts.logging.INFO,
outputDir=outputDir + "/csv",
inputParticles="particles_initial",
outputStem="particles_initial",
))
s.addWriter(
acts.examples.RootParticleWriter(
level=acts.logging.INFO,
inputParticles="particles_initial",
filePath=outputDir + "/fatras_particles_initial.root",
))
s.addWriter(
acts.examples.CsvSimHitWriter(
level=acts.logging.INFO,
inputSimHits=alg.config.outputSimHits,
outputDir=outputDir + "/csv",
outputStem="hits",
))
s.addWriter(
acts.examples.RootSimHitWriter(
level=acts.logging.INFO,
inputSimHits=alg.config.outputSimHits,
filePath=outputDir + "/hits.root",
))
return s
def configureDigitization(
trackingGeometry,
field,
outputDir: Path,
particlesInput: Optional[Path] = None,
outputRoot=True,
outputCsv=True,
s=None,
):
srcdir = Path(__file__).resolve().parent.parent.parent.parent
csv_dir = os.path.join(outputDir, "csv")
if not os.path.exists(csv_dir):
os.mkdir(csv_dir)
# Input
rnd = acts.examples.RandomNumbers(seed=42)
particleCollection = "particles_input"
if particlesInput is None:
evGen = acts.examples.EventGenerator(
level=acts.logging.INFO,
generators=[
acts.examples.EventGenerator.Generator(
multiplicity=acts.examples.FixedMultiplicityGenerator(n=2),
vertex=acts.examples.GaussianVertexGenerator(
stddev=acts.Vector4(0, 0, 0, 0), mean=acts.Vector4(0, 0, 0, 0)
),
particles=acts.examples.ParametricParticleGenerator(
p=(1 * u.GeV, 10 * u.GeV),
eta=(-2, 2),
phi=(0, 360 * u.degree),
randomizeCharge=True,
numParticles=4,
),
)
],
outputParticles=particleCollection,
randomNumbers=rnd,
)
else:
# Read input from input collection (e.g. Pythia8 output)
evGen = acts.examples.RootParticleReader(
level=acts.logging.INFO,
particleCollection=particleCollection,
filePath=str(particlesInput),
orderedEvents=False,
)
# Simulation
simAlg = acts.examples.FatrasSimulation(
level=acts.logging.INFO,
inputParticles=particleCollection,
outputParticlesInitial="particles_initial",
outputParticlesFinal="particles_final",
outputSimHits="simhits",
randomNumbers=rnd,
trackingGeometry=trackingGeometry,
magneticField=field,
generateHitsOnSensitive=True,
)
# Digitization
digiCfg = acts.examples.DigitizationConfig(
acts.examples.readDigiConfigFromJson(
str(
srcdir
/ "Examples/Algorithms/Digitization/share/default-smearing-config-generic.json"
)
),
trackingGeometry=trackingGeometry,
randomNumbers=rnd,
inputSimHits=simAlg.config.outputSimHits,
)
digiAlg = acts.examples.DigitizationAlgorithm(digiCfg, acts.logging.INFO)
s = s or acts.examples.Sequencer(
events=100, numThreads=-1, logLevel=acts.logging.INFO
)
s.addReader(evGen)
s.addAlgorithm(simAlg)
s.addAlgorithm(digiAlg)
if outputRoot:
rmwConfig = acts.examples.RootMeasurementWriter.Config(
inputMeasurements=digiAlg.config.outputMeasurements,
inputClusters=digiAlg.config.outputClusters,
inputSimHits=simAlg.config.outputSimHits,
inputMeasurementSimHitsMap=digiAlg.config.outputMeasurementSimHitsMap,
filePath=str(outputDir / f"{digiAlg.config.outputMeasurements}.root"),
trackingGeometry=trackingGeometry,
)
rmwConfig.addBoundIndicesFromDigiConfig(digiAlg.config)
s.addWriter(acts.examples.RootMeasurementWriter(rmwConfig, acts.logging.INFO))
if outputCsv:
csv_dir = outputDir / "csv"
csv_dir.mkdir(parents=True, exist_ok=True)
s.addWriter(
acts.examples.CsvMeasurementWriter(
level=acts.logging.VERBOSE,
inputMeasurements=digiAlg.config.outputMeasurements,
inputClusters=digiAlg.config.outputClusters,
inputSimHits=simAlg.config.outputSimHits,
inputMeasurementSimHitsMap=digiAlg.config.outputMeasurementSimHitsMap,
outputDir=str(csv_dir),
)
)
return s
