tracking-parametrisation-tuner/moore_options/get_resolution_and_eff_data.py

# flake8: noqa


"""
This set of options is used for reconstruction development purposes,
and assumes that the input contains MCHits (i.e. is of `Exended`
DST/digi type).
author:     Furkan Cetin
date:       10/2023
Moore/run gaudirun.py /work/cetin/LHCb/reco_tuner/moore_options/get_resolution_and_eff_data.py
"""

from Moore import options, run_reconstruction

from Moore.config import Reconstruction
from PyConf.Algorithms import PrKalmanFilter
from PyConf.Tools import TrackMasterExtrapolator
import glob

from RecoConf.mc_checking import (
    check_track_resolution,
    check_tracking_efficiency,
    get_mc_categories,
    get_hit_type_mask,
    make_links_lhcbids_mcparticles_tracking_system,
    make_links_tracks_mcparticles,
    get_track_checkers,
)
from RecoConf.core_algorithms import make_unique_id_generator
from RecoConf.hlt2_tracking import make_hlt2_tracks
from RecoConf.hlt1_tracking import (
    make_VeloClusterTrackingSIMD_hits,
    make_PrStorePrUTHits_hits,
    make_PrStoreSciFiHits_hits,
    get_global_materiallocator,
)

decay = "test"

options.evt_max = -1

options.ntuple_file = f"data/resolutions_and_effs_{decay}_thesis.root"
options.input_type = "ROOT"


if decay == "B":
    options.input_files = glob.glob("/auto/data/guenther/Bd_Kstee/*.xdigi")
elif decay == "BJpsi":
    options.input_files = glob.glob("/auto/data/guenther/Bd_JpsiKst_ee/*.xdigi")
elif decay == "D":
    options.input_files = glob.glob("/auto/data/guenther/Dst_D0ee/*.xdigi")
elif decay == "test2":
    options.input_files = [
        "/auto/data/guenther/Bd_JpsiKst_ee/00143565_00000009_1.xdigi"
    ]
elif decay == "test":
    options.input_files = ["/auto/data/guenther/Bd_Kstee/00151673_00000002_1.xdigi"]

options.dddb_tag = "dddb-20210617"
options.conddb_tag = "sim-20210617-vc-md100"
options.simulation = True
options.output_level = 3


def run_tracking_resolution():
    tracks = make_hlt2_tracks(light_reco=True, fast_reco=False, use_pr_kf=True)
    fitted_forward_tracks = PrKalmanFilter(
        Input=tracks["Forward"]["Pr"],
        MaxChi2=2.8,
        MaxChi2PreOutlierRemoval=20,
        HitsVP=make_VeloClusterTrackingSIMD_hits(),
        HitsUT=make_PrStorePrUTHits_hits(),
        HitsFT=make_PrStoreSciFiHits_hits(),
        ReferenceExtrapolator=TrackMasterExtrapolator(
            MaterialLocator=get_global_materiallocator(),
        ),
        InputUniqueIDGenerator=make_unique_id_generator(),
    ).OutputTracks

    links_to_lhcbids = make_links_lhcbids_mcparticles_tracking_system()
    links_to_forward = make_links_tracks_mcparticles(
        InputTracks=tracks["Forward"],
        LinksToLHCbIDs=links_to_lhcbids,
    )
    links_to_match = make_links_tracks_mcparticles(
        InputTracks=tracks["Match"],
        LinksToLHCbIDs=links_to_lhcbids,
    )
    links_to_best = make_links_tracks_mcparticles(
        InputTracks=tracks["BestLong"],
        LinksToLHCbIDs=links_to_lhcbids,
    )
    links_to_seed = make_links_tracks_mcparticles(
        InputTracks=tracks["Seed"],
        LinksToLHCbIDs=links_to_lhcbids,
    )

    res_checker_forward = check_track_resolution(tracks["Forward"], suffix="Forward")
    res_checker_best_long = check_track_resolution(
        tracks["BestLong"],
        suffix="BestLong",
    )
    res_checker_best_forward = check_track_resolution(
        dict(v1=fitted_forward_tracks),
        suffix="BestForward",
    )
    res_checker_seed = check_track_resolution(
        tracks["Seed"],
        suffix="Seed",
    )

    eff_checker_forward = check_tracking_efficiency(
        "Forward",
        tracks["Forward"],
        links_to_forward,
        links_to_lhcbids,
        get_mc_categories("Forward"),
        get_hit_type_mask("Forward"),
    )
    eff_checker_match = check_tracking_efficiency(
        "Match",
        tracks["Match"],
        links_to_match,
        links_to_lhcbids,
        get_mc_categories("Match"),
        get_hit_type_mask("Match"),
    )
    eff_checker_best_long = check_tracking_efficiency(
        "BestLong",
        tracks["BestLong"],
        links_to_best,
        links_to_lhcbids,
        get_mc_categories("BestLong"),
        get_hit_type_mask("BestLong"),
    )
    eff_checker_seed = check_tracking_efficiency(
        "Seed",
        tracks["Seed"],
        links_to_seed,
        links_to_lhcbids,
        get_mc_categories("Seed"),
        get_hit_type_mask("Seed"),
    )

    # types_and_locations_for_checkers = {
    #     "Forward": tracks["Forward"],
    #     "Seed": tracks["Seed"],
    #     "Match": tracks["Match"],
    # }

    # data = []
    # data += get_track_checkers(types_and_locations_for_checkers)

    data = [
        res_checker_forward,
        res_checker_best_long,
        res_checker_best_forward,
        res_checker_seed,
        eff_checker_forward,
        eff_checker_match,
        eff_checker_best_long,
        eff_checker_seed,
    ]

    return Reconstruction("run_tracking_debug", data)


run_reconstruction(options, run_tracking_resolution)