Merge branch 'mwaterla_large_seeding_window' into 'master'

Mwaterla large seeding window

See merge request !2311

VPHitEfficiencies/info.yaml

+defaults:
+  application: "Moore/v55r17"
+  inform:
+    - mark.waterlaat@cern.ch
+  wg: Calib
+
+{%- set samples = [
+    "95100000/TURCAL_RAWBANKS.DST", 
+    "95100000/TURCAL_PERSISTRECORAWBANKS.DST",
+    "96000000/NOBIAS.DST",
+] %}
+
+# Split the jobs into batches of 42 sensors to reduce the memory usage
+{%- set sensor_step = 42 %}
+{%- set n_sensors = 208 %}
+
+{%- for filetype in samples %}
+{%- for begin_sensor in range(0, n_sensors, sensor_step) %}
+
+{%- set stream = filetype.split("/")[1].rsplit(".", 1)[0] %}
+{#- Subtract one as the sensors are zero indexed #}
+{%- set end_sensor = [begin_sensor + sensor_step, n_sensors] | min - 1 %}
+
+MagUp_Collision24_{{ stream }}_{{ begin_sensor }}-{{ end_sensor }}:
+  input:
+    bk_query: "/LHCb/Collision24/Beam6800GeV-VeloClosed-MagUp/RealData/Sprucing24c2/{{ filetype }}"
+    keep_running: false
+    runs: 
+      - 303092:304604
+    dq_flags:
+      - OK
+  output: VPHITEFFICIENCIES.ROOT
+  options: 
+    entrypoint: VPHitEfficiencies.moore_data:main
+    extra_args:
+      - {{ stream | lower }}
+      - {{ begin_sensor }}
+      - {{ end_sensor }}
+    extra_options:
+      input_type: ROOT
+      input_raw_format: 0.5
+      evt_max: -1
+      output_type: "ROOT"
+      simulation: False
+      data_type: "Upgrade"
+      geometry_version: "run3/2024.Q1.2-v00.00"
+      conditions_version: "master"
+{%- endfor %}
+{%- endfor %}

VPHitEfficiencies/moore_data.py

+###############################################################################
+# (c) Copyright 2023 CERN for the benefit of the LHCb Collaboration           #
+#                                                                             #
+# This software is distributed under the terms of the GNU General Public      #
+# Licence version 3 (GPL Version 3), copied verbatim in the file "COPYING".   #
+#                                                                             #
+# In applying this licence, CERN does not waive the privileges and immunities #
+# granted to it by virtue of its status as an Intergovernmental Organization  #
+# or submit itself to any jurisdiction.                                       #
+###############################################################################
+import argparse
+
+from Moore import run_reconstruction, Options
+from Moore.config import Reconstruction
+from PyConf.Algorithms import (
+    fromPrVeloTracksV1TracksMerger,  
+    VPHitEfficiencyMonitor,
+    VeloRetinaClusterTrackingSIMDFull,
+    TrackEventFitter,
+    TrackListRefiner,
+    TrackSelectionToContainer,
+    DeterministicPrescaler, 
+)
+from PyConf.Tools import (
+    TrackMasterFitter,
+    TrackInterpolator,
+    TrackLinearExtrapolator,
+)
+from PyConf.application import( 
+    default_raw_banks, 
+    make_odin, 
+    default_raw_event, 
+)
+from RecoConf.legacy_rec_hlt1_tracking import (
+    make_reco_pvs,
+    make_PatPV3DFuture_pvs,
+    make_RetinaClusters,
+    get_default_ut_clusters, 
+    get_global_clusters_on_track_tool_only_velo, 
+)
+from RecoConf.hlt2_tracking import (
+    TrackBestTrackCreator,
+    make_PrStoreUTHit_empty_hits,
+    get_global_measurement_provider,
+    get_track_master_fitter, 
+)
+from RecoConf.decoders import default_VeloCluster_source
+from PyConf import configurable
+import Functors as F 
+
+make_reco_pvs.global_bind(make_pvs_from_velo_tracks=make_PatPV3DFuture_pvs)
+
+velo_clusters_algorithm_light = make_RetinaClusters
+velo_tracking_algorithm = VeloRetinaClusterTrackingSIMDFull
+bankType = "VPRetinaCluster"
+default_VeloCluster_source.global_bind(bank_type="VPRetinaCluster")
+
+# get TMF
+def get_my_track_master_fitter():
+    with TrackMasterFitter.bind(
+            MaxNumberOutliers=2,
+            NumberFitIterations=10,
+            FastMaterialApproximation=True):
+        return get_track_master_fitter(
+            clusters_on_track_tool=get_global_clusters_on_track_tool_only_velo)
+
+@configurable
+def make_my_sequence(
+    *, 
+    beginSensor = 0, 
+    endSensor = 1, 
+    ):  
+    data = []
+
+    filterList = []
+    
+    prescaler = DeterministicPrescaler(
+            name="MyEventPrescaler",
+            AcceptFraction=float(
+                0.1, 
+            ),  # make sure prescale is not interpreted as 'int' because it changes the hash computation...
+            SeedName="KSPrescaler",
+            ODINLocation=make_odin()) 
+    
+    filterList += [prescaler]
+   
+    with get_default_ut_clusters.bind(disable_ut=True),\
+         get_global_measurement_provider.bind(
+            ignoreUT=True,
+            velo_hits=velo_clusters_algorithm_light,
+            ignoreFT=True,
+            ignoreMuon=True,
+            ut_hits=make_PrStoreUTHit_empty_hits):
+            
+        for sensor_under_study in range(beginSensor, endSensor + 1):
+            
+            my_mask = [sensor in [sensor_under_study]
+                    for sensor in range(208)] 
+            
+            vpClustering = velo_tracking_algorithm(
+                RawBanks=default_raw_banks(bankType),
+                SensorMasks=tuple(my_mask),
+                MaxScatterSeeding=0.1,
+                MaxScatterForwarding=0.1,
+                MaxScatter3hits=0.02,
+                SeedingWindow=10, 
+                SkipForward=8)
+            
+            clusters = vpClustering.HitsLocation
+            vpTracks = vpClustering.TracksLocation
+            vpTracks_backwards = vpClustering.TracksBackwardLocation
+
+            vpTracks_v1 = fromPrVeloTracksV1TracksMerger(  # converts Pr -> v1 tracks and merges forward/backward
+                InputTracksLocation1=vpTracks,
+                InputTracksLocation2=vpTracks_backwards, 
+                TrackAddClusterTool=get_global_clusters_on_track_tool_only_velo(),
+                ).OutputTracksLocation
+
+            my_TrackMasterFitter = get_my_track_master_fitter()
+
+            fittedTracks = TrackEventFitter(
+                TracksInContainer=vpTracks_v1,
+                Fitter=(my_TrackMasterFitter),
+                MaxChi2DoF=2.8,
+                name="TrackEventFitter_{hash}").TracksOutContainer
+
+            bestTracks = TrackBestTrackCreator(
+                name="TrackBestTrackCreator_{hash}",
+                TracksInContainers=[fittedTracks],
+                DoNotRefit=True,
+                AddGhostProb=False,
+                FitTracks=False,
+                MaxChi2DoF=2.8,
+            ).TracksOutContainer
+
+            tracks_selection = TrackListRefiner(
+            inputLocation=bestTracks,
+            Code=F.require_all(
+                F.NVPHITS >= 3,
+                F.ETA >= 1.3, 
+                F.P >= 0,  # Here to make it explicit
+                F.PT >= 0)).outputLocation
+            
+            filtered_tracks = TrackSelectionToContainer(
+                name="TrackSelectionToContainer_{hash}",
+                InputLocation=tracks_selection).OutputLocation
+            
+            trackExtrapolator = TrackLinearExtrapolator()
+            trackInterpolator = TrackInterpolator(Extrapolator=trackExtrapolator)
+            
+            my_vp_efficiency_alg = VPHitEfficiencyMonitor(
+                name="VPHitEfficiencyMonitorSensor_{0}".format(
+                    sensor_under_study),
+                TrackLocation=filtered_tracks,
+                PrVPHitsLocation=clusters,
+                UseAandCSide=False, 
+                MaxTrackCov=100.0,
+                SensorUnderStudy=sensor_under_study,
+                Interpolator=trackInterpolator,
+                Extrapolator=trackExtrapolator,
+                ExpertMode=False, 
+                ResidualTolerance=0.4,  
+            )
+            data += [my_vp_efficiency_alg]
+
+    return Reconstruction('hlt2_hit_eff_reco', data, filters = filterList)
+
+from PyConf.application import default_raw_event
+
+
+def main(options: Options, *args):
+    parser = argparse.ArgumentParser(description="Moore HLT2 Hit Efficiency")
+    parser.add_argument("stream", choices=["turcal_rawbanks", "turcal_persistrecorawbanks", "nobias"])
+    parser.add_argument("begin_sensor", type=int)
+    parser.add_argument("end_sensor", type=int)
+    args = parser.parse_args(args)
+
+    # DO NOT COPY THIS THIS WITHOUT CONSULTING DPA-WP2 FIRST
+    # This is a horrible hack to make it so the histograms are written to the
+    # file that is expected by Analysis Productions. Ideally we should have a
+    # better way of managing output/ntuples/histograms but it's currently an
+    # extremely niche use case.
+    
+    raw_options = options.dict()
+    raw_options["histo_file"] = raw_options["ntuple_file"]
+    raw_options["ntuple_file"] = None
+    options = Options(**raw_options)
+    # DO NOT COPY THIS THIS WITHOUT CONSULTING DPA-WP2 FIRST
+
+    default_raw_event.global_bind(stream=args.stream)
+    make_my_sequence.global_bind(beginSensor=args.begin_sensor, endSensor=args.end_sensor)
+    config = run_reconstruction(options, make_my_sequence)
+    return config