def fill_validation_candidates(df_reco, tag=""):
"""
Create histograms for the validation on the event level as a function of the multiplicity
"""
_ = len(df_reco)
# Binning definition
binning_nsigma = buildbinning(1, -1000, -998)
binning_nsigma += buildbinning(2000, -100, 100)
binning_pt = buildbinning(100, 0, 100)
binning_eta = buildbinning(100, -1, 1)
binning_phi = buildbinning(100, 0, 7)
# Make and fill histograms
val = ValidationCollection(df_reco, tag=tag)
for i in ["TPC", "TOF"]:
for j in ["Pi", "K", "Pr"]:
for k in ["0", "1"]:
yaxis = [binning_nsigma, f"nsig{i}_{j}_{k}"]
val.make_and_fill(binning_pt, "p_prong0", *yaxis)
val.make_and_fill(binning_pt, "p_prong1", *yaxis)
val.make_and_fill(binning_pt, "pt_prong0", *yaxis)
val.make_and_fill(binning_pt, "pt_prong1", *yaxis)
val.make_and_fill(binning_pt, "pt_cand", *yaxis)
val.make_and_fill(binning_eta, "eta_cand", *yaxis)
val.make_and_fill(binning_phi, "phi_cand", *yaxis)
return val
def fill_validation_candidates(df_reco, tag=""):
"""
Create histograms for the validation on the event level as a function of the multiplicity
"""
_ = len(df_reco)
# Binning definition
binning_nsigma = buildbinning(1, -1000, -998)
binning_nsigma += buildbinning(2000, -100, 100)
binning_pt = buildbinning(400, 0, 100)
binning_pt = buildarray([1, 2, 4, 6, 8, 12, 24])
binning_eta = buildbinning(100, -1, 1)
binning_phi = buildbinning(100, 0, 7)
binning_inv_mass = buildbinning(100, 2, 2.5)
binning_v0m_perc = buildbinning(100, 0, 1)
binning_v0m_perc += buildbinning(89, 1.1, 10)
binning_v0m_perc += buildbinning(89, 11, 100)
binning_ntrklt = buildbinning(200, -0.5, 199.5)
# Make and fill histograms
val = ValidationCollection(df_reco, tag=tag)
# PID information
for i in ["TPC", "TOF"]:
for j in ["Pi", "K", "Pr"]:
for k in ["0", "1"]:
yaxis = [binning_nsigma, f"nsig{i}_{j}_{k}"]
val.make_and_fill(binning_pt, "p_prong0", *yaxis)
val.make_and_fill(binning_pt, "p_prong1", *yaxis)
val.make_and_fill(binning_pt, "pt_prong0", *yaxis)
val.make_and_fill(binning_pt, "pt_prong1", *yaxis)
val.make_and_fill(binning_pt, "pt_cand", *yaxis)
val.make_and_fill(binning_eta, "eta_cand", *yaxis)
val.make_and_fill(binning_phi, "phi_cand", *yaxis)
# Invariant mass
val.make_and_fill(binning_inv_mass, "inv_mass", binning_v0m_perc,
"perc_v0m")
val.make_and_fill(binning_inv_mass, "inv_mass", binning_ntrklt,
"n_tracklets_corr")
for i, j in enumerate(binning_pt[0:-1]):
# Defining pT interval
lower_pt = j
upper_pt = binning_pt[i + 1]
pt_interval = "_pt_cand_{:.1f}-{:.1f}".format(lower_pt, upper_pt)
# Cutting the DF in the pT interval
df_ptcut = df_reco[df_reco.pt_cand > lower_pt]
df_ptcut = df_ptcut[df_ptcut.pt_cand < upper_pt]
# Resetting validation collection to use the pT cut DF
val.reset_input(df_ptcut, tag=tag + pt_interval)
# Filling histograms with inv mass and multiplicity
val.make_and_fill(binning_inv_mass, "inv_mass", binning_v0m_perc,
"perc_v0m")
val.make_and_fill(binning_inv_mass, "inv_mass", binning_ntrklt,
"n_tracklets_corr")
return val
def fill_validation_candidates(df_reco, tag=""):
"""
Create histograms for the validation on the event level as a function of the multiplicity
"""
_ = len(df_reco)
# Binning definition
binning_nsigma = buildbinning(1, -1000, -998)
binning_nsigma += buildbinning(2000, -100, 100)
binning_pt = buildbinning(400, 0, 100)
binning_eta = buildbinning(100, -1, 1)
binning_phi = buildbinning(100, 0, 7)
binning_inv_mass = buildbinning(100, 2, 2.5)
binning_v0m_perc = buildbinning(100, 0, 1)
binning_v0m_perc += buildbinning(89, 1.1, 10)
binning_v0m_perc += buildbinning(89, 11, 100)
binning_ntrklt = buildbinning(200, -0.5, 199.5)
# Make and fill histograms
val = ValidationCollection(df_reco, tag=tag)
# PID information
for i in ["TPC", "TOF"]:
for j in ["Pi", "K", "Pr"]:
for k in ["0", "1"]:
yaxis = [binning_nsigma, f"nsig{i}_{j}_{k}"]
val.make_and_fill(binning_pt, "p_prong0", *yaxis)
val.make_and_fill(binning_pt, "p_prong1", *yaxis)
val.make_and_fill(binning_pt, "pt_prong0", *yaxis)
val.make_and_fill(binning_pt, "pt_prong1", *yaxis)
val.make_and_fill(binning_pt, "pt_cand", *yaxis)
val.make_and_fill(binning_eta, "eta_cand", *yaxis)
val.make_and_fill(binning_phi, "phi_cand", *yaxis)
# Invariant mass
val.make_and_fill(binning_inv_mass, "inv_mass", binning_v0m_perc, "perc_v0m")
val.make_and_fill(binning_inv_mass, "inv_mass", binning_ntrklt, "n_tracklets_corr")
return val
def fill_validation_vertex(dfevt, dfevtevtsel, df_reco):
"""
Create histograms for the validation on the event level as a function of the multiplicity
"""
_ = len(df_reco)
__ = len(dfevtevtsel)
# Binning definition
# binning_xyvtx = buildbinning(100, -1.0, 1)
binning_zvtx = buildbinning(100, -15.0, 15)
# Make and fill histograms
val = ValidationCollection(dfevt[dfevt.is_ev_rej_INT7 == 0])
# val.make_and_fill(binning_xyvtx, "x_vtx_reco")
# val.make_and_fill(binning_xyvtx, "y_vtx_reco")
val.make_and_fill(binning_zvtx, "z_vtx_reco")
return val
def fill_validation_multiplicity(dfevt, dfevtevtsel, df_reco):
"""
Create histograms for the validation on the event level as a function of the multiplicity
"""
_ = len(df_reco)
# Binning definition
binning_ntrklt = buildbinning(200, -0.5, 199.5)
binning_ntrklt_diff = buildbinning(10, -0.5, 9.5)
binning_v0m = buildbinning(1500, -0.5, 1499.5)
binning_zvtx = buildbinning(100, -15.0, 15)
binning_v0m_perc = buildbinning(100, 0, 1)
binning_v0m_perc += buildbinning(89, 1.1, 10)
binning_v0m_perc += buildbinning(89, 11, 100)
# Make and fill histograms
val = ValidationCollection(dfevt[dfevt.is_ev_rej_INT7 == 0])
# val = ValidationCollection(dfevt[dfevtevtsel])
# val = ValidationCollection(dfevt[dfevt])
for i in ["v0m", "v0m_eq", "v0m_corr", "v0m_eq_corr"]:
val.make_and_fill(binning_ntrklt, "n_tracklets", binning_v0m, i)
val.make_and_fill(binning_v0m, i, binning_v0m_perc, "perc_v0m")
for i in ["n_tracklets", "n_tracklets_corr", "n_tracklets_corr_shm"]:
val.make_and_fill(binning_ntrklt, i, binning_v0m_perc, "perc_v0m")
val.make_and_fill(binning_v0m_perc, "perc_v0m", binning_ntrklt, i)
val.reset_input(dfevtevtsel, "")
val.make_and_fill(binning_ntrklt, "n_tracklets",
binning_ntrklt, "n_tracklets_corr")
val.make_and_fill(binning_zvtx, "z_vtx_reco",
binning_ntrklt, "n_tracklets_corr")
val.make_and_fill(binning_zvtx, "z_vtx_reco",
binning_ntrklt, "n_tracklets")
val.make_and_fill(binning_ntrklt, "n_tracklets_corr")
val.make_and_fill(binning_ntrklt, "n_tracklets_corr_shm")
val.reset_input(filter_bit_df(dfevt, "is_ev_rej", [[4], []]), "pileup")
val.make_and_fill(binning_ntrklt, "n_tracklets_corr")
# val.reset_input(dfevtevtsel.query("is_ev_sel_shm == 1"), "spd")
# val.make_and_fill(binning_ntrklt, "n_tracklets_corr")
df_reco["n_tracklets_corr-n_tracklets_corr_sub"] = (
df_reco["n_tracklets_corr"] - df_reco["n_tracklets_corr_sub"]
)
for i in [[df_reco, ""],
[df_reco[df_reco.is_ev_rej_INT7 == 0], "MB"],
[df_reco.query("is_ev_sel_shm == 1"), "HMSPD"],
]:
val.reset_input(*i)
val.make_and_fill(
binning_ntrklt,
"n_tracklets_corr",
binning_ntrklt_diff,
"n_tracklets_corr-n_tracklets_corr_sub",
)
val.make_and_fill(
binning_ntrklt, "n_tracklets_corr_sub", binning_ntrklt, "n_tracklets_corr"
)
val.make_and_fill(
binning_ntrklt, "n_tracklets_corr", binning_ntrklt, "n_tracklets_corr_sub"
)
return val