def test_csv_multitrajectory_writer(tmp_path):
detector, trackingGeometry, decorators = GenericDetector.create()
field = acts.ConstantBField(acts.Vector3(0, 0, 2 * u.T))
from truth_tracking import runTruthTracking
s = Sequencer(numThreads=1, events=10)
runTruthTracking(
trackingGeometry,
field,
digiConfigFile=Path(
str(
Path(__file__).parent.parent.parent.parent /
"Examples/Algorithms/Digitization/share/default-smearing-config-generic.json"
)),
outputDir=tmp_path,
s=s,
)
csv_dir = tmp_path / "csv"
csv_dir.mkdir()
s.addWriter(
CsvMultiTrajectoryWriter(
level=acts.logging.INFO,
inputTrajectories="trajectories",
inputMeasurementParticlesMap="measurement_particles_map",
outputDir=str(csv_dir),
))
s.run()
del s
assert len([f for f in csv_dir.iterdir() if f.is_file()]) == 10
assert all(f.stat().st_size > 20 for f in csv_dir.iterdir())
def test_vertex_fitting_reading(
tmp_path, ptcl_gun, rng, finder, inputTracks, entries, assert_root_hash
):
ptcl_file = tmp_path / "particles.root"
detector, trackingGeometry, decorators = GenericDetector.create()
field = acts.ConstantBField(acts.Vector3(0, 0, 2 * u.T))
from vertex_fitting import runVertexFitting, VertexFinder
inputTrackSummary = None
if inputTracks:
from truth_tracking import runTruthTracking
s2 = Sequencer(numThreads=1, events=100)
runTruthTracking(
trackingGeometry,
field,
digiConfigFile=Path(
Path(__file__).parent.parent.parent.parent
/ "Examples/Algorithms/Digitization/share/default-smearing-config-generic.json"
),
outputDir=tmp_path,
s=s2,
)
s2.run()
del s2
inputTrackSummary = tmp_path / "tracksummary_fitter.root"
assert inputTrackSummary.exists()
assert ptcl_file.exists()
else:
s0 = Sequencer(events=100, numThreads=1)
evGen = ptcl_gun(s0)
s0.addWriter(
RootParticleWriter(
level=acts.logging.INFO,
inputParticles=evGen.config.outputParticles,
filePath=str(ptcl_file),
)
)
s0.run()
del s0
assert ptcl_file.exists()
finder = VertexFinder[finder]
s3 = Sequencer(numThreads=1)
runVertexFitting(
field,
inputParticlePath=ptcl_file,
inputTrackSummary=inputTrackSummary,
outputDir=tmp_path,
vertexFinder=finder,
s=s3,
)
alg = AssertCollectionExistsAlg(["fittedVertices"], name="check_alg")
s3.addAlgorithm(alg)
s3.run()
vertexing_file = tmp_path / "performance_vertexing.root"
assert vertexing_file.exists()
assert_entries(vertexing_file, "vertexing", entries)
assert_root_hash(vertexing_file.name, vertexing_file)
def test_ckf_tracks_example(
tmp_path, assert_root_hash, truthSmeared, truthEstimated, detector
):
csv = tmp_path / "csv"
assert not csv.exists()
srcdir = Path(__file__).resolve().parent.parent.parent.parent
if detector == "generic":
detector, trackingGeometry, decorators = GenericDetector.create()
geometrySelection = (
srcdir
/ "Examples/Algorithms/TrackFinding/share/geoSelection-genericDetector.json"
)
digiConfigFile = (
srcdir
/ "Examples/Algorithms/Digitization/share/default-smearing-config-generic.json"
)
elif detector == "odd":
matDeco = acts.IMaterialDecorator.fromFile(
srcdir / "thirdparty/OpenDataDetector/data/odd-material-maps.root",
level=acts.logging.INFO,
)
detector, trackingGeometry, decorators = getOpenDataDetector(matDeco)
digiConfigFile = (
srcdir / "thirdparty/OpenDataDetector/config/odd-digi-smearing-config.json"
)
geometrySelection = (
srcdir / "thirdparty/OpenDataDetector/config/odd-seeding-config.json"
)
else:
raise ValueError(f"Invalid detector {detector}")
field = acts.ConstantBField(acts.Vector3(0, 0, 2 * u.T))
events = 100
s = Sequencer(events=events, numThreads=1) # Digitization is not thread-safe
root_files = [
(
"performance_ckf.root",
None,
),
(
"trackstates_ckf.root",
"trackstates",
),
(
"tracksummary_ckf.root",
"tracksummary",
),
]
if not truthSmeared:
root_files += [
(
"performance_seeding_trees.root",
"track_finder_tracks",
),
]
for rf, _ in root_files:
assert not (tmp_path / rf).exists()
from ckf_tracks import runCKFTracks
runCKFTracks(
trackingGeometry,
decorators,
field=field,
outputCsv=True,
outputDir=tmp_path,
geometrySelection=geometrySelection,
digiConfigFile=digiConfigFile,
truthSmearedSeeded=truthSmeared,
truthEstimatedSeeded=truthEstimated,
s=s,
)
s.run()
del s # files are closed in destructors, not great
assert csv.exists()
for rf, tn in root_files:
rp = tmp_path / rf
assert rp.exists()
if tn is not None:
assert_root_hash(rf, rp)
assert len([f for f in csv.iterdir() if f.name.endswith("CKFtracks.csv")]) == events
assert all([f.stat().st_size > 300 for f in csv.iterdir()])
ptMin=500 * u.MeV,
))
logger.info("Using vertex finder: %s", vertexFinder.name)
return addVertexFitting(
s,
field,
outputDirRoot=outputDir if outputRoot else None,
associatedParticles=associatedParticles,
vertexFinder=vertexFinder,
)
if "__main__" == __name__:
detector, trackingGeometry, decorators = GenericDetector.create()
field = acts.ConstantBField(acts.Vector3(0, 0, 2 * u.T))
inputParticlePath = Path("particles.root")
if not inputParticlePath.exists():
inputParticlePath = None
inputTrackSummary = None
for p in ("tracksummary_fitter.root", "tracksummary_ckf.root"):
p = Path(p)
if p.exists():
inputTrackSummary = p
break
runVertexFitting(
))
return s
if "__main__" == __name__:
matDeco = None
# matDeco = acts.IMaterialDecorator.fromFile("material.json")
# matDeco = acts.IMaterialDecorator.fromFile("material.root")
## Generic detector: Default
(
detector,
trackingGeometry,
contextDecorators,
) = GenericDetector.create(mdecorator=matDeco)
## Alternative: Aligned detector in a couple of modes
# detector, trackingGeometry, contextDecorators = AlignedDetector.create(
# decoratorLogLevel=acts.logging.INFO,
# # These parameters need to be tuned so that GC doesn't break
# # with multiple threads
# iovSize=10,
# flushSize=10,
# # External alignment store
# mode=AlignedDetector.Config.Mode.External,
# # OR: Internal alignment storage
# # mode=AlignedDetector.Config.Mode.Internal,
# )
## Alternative: DD4hep detector
def test_ckf_tracks_example_truth_smeared(tmp_path, assert_root_hash):
# the example as written is only compatible with the generic detector
detector, trackingGeometry, decorators = GenericDetector.create()
field = acts.ConstantBField(acts.Vector3(0, 0, 2 * u.T))
events = 10
s = Sequencer(events=events, numThreads=1) # Digitization is not thread-safe
root_files = [
("performance_ckf.root", None, None),
(
"trackstates_ckf.root",
"trackstates",
80,
),
(
"tracksummary_ckf.root",
"tracksummary",
10,
),
]
csv = tmp_path / "csv"
assert not csv.exists()
for rf, _, _ in root_files:
assert not (tmp_path / rf).exists()
from ckf_tracks import runCKFTracks
runCKFTracks(
trackingGeometry,
decorators,
field=field,
geometrySelection=Path(
Path(__file__).parent.parent.parent.parent
/ "Examples/Algorithms/TrackFinding/share/geoSelection-genericDetector.json"
),
digiConfigFile=Path(
Path(__file__).parent.parent.parent.parent
/ "Examples/Algorithms/Digitization/share/default-smearing-config-generic.json"
),
outputCsv=True,
outputDir=tmp_path,
truthSmearedSeeded=True,
truthEstimatedSeeded=False,
s=s,
)
s.run()
del s # files are closed in destructors, not great
assert csv.exists()
for rf, tn, nume in root_files:
rp = tmp_path / rf
assert rp.exists()
if tn is not None and nume is not None:
assert_entries(rp, tn, nume)
assert_root_hash(rf, rp)
assert len([f for f in csv.iterdir() if f.name.endswith("CKFtracks.csv")]) == events
assert all([f.stat().st_size > 300 for f in csv.iterdir()])
def runDigitizationConfig(
trackingGeometry,
input: Path,
output: Path,
):
inputConfig = readDigiConfigFromJson(str(input))
digiConfigurator = DigitizationConfigurator()
digiConfigurator.compactify = True
digiConfigurator.inputDigiComponents = inputConfig
trackingGeometry.visitSurfaces(digiConfigurator)
outputConfig = GeometryHierarchyMap_DigiComponentsConfig(
digiConfigurator.outputDigiComponents)
writeDigiConfigToJson(outputConfig, str(output))
if "__main__" == __name__:
detector, trackingGeometry, _ = GenericDetector.create()
runDigitizationConfig(
trackingGeometry=trackingGeometry,
input=Path(__file__).parent /
"../../Algorithms/Digitization/share/default-smearing-config-generic.json",
output=Path.cwd() / "digi-config-out.json",
)