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Plot postfit shapes #102

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merged 10 commits into from
Jan 24, 2025
Merged

Plot postfit shapes #102

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490fcc1
Changes in rebinning task, removed negative weights from training
Lara813 Dec 19, 2024
13970d5
Modified PostfitPlot task
Lara813 Jan 17, 2025
1ff9bb3
cleanup and fixes in postfit plotting
Jan 24, 2025
ed15666
Merge branch 'dev' into plot_postfit_shapes
Lara813 Jan 24, 2025
c38c458
Update hbw/ml/data_loader.py
Lara813 Jan 24, 2025
69460b1
Apply suggestions from code review
Lara813 Jan 24, 2025
9dba52e
Review changes
Lara813 Jan 24, 2025
caccecd
Apply suggestions from code review
Lara813 Jan 24, 2025
7641039
Update hbw/tasks/inference.py
Lara813 Jan 24, 2025
73e3a98
Merge branch 'dev' into plot_postfit_shapes
mafrahm Jan 24, 2025
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1 change: 1 addition & 0 deletions hbw/categorization/categories.py
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Original file line number Diff line number Diff line change
Expand Up @@ -274,6 +274,7 @@ def catid_2b(self: Categorizer, events: ak.Array, **kwargs) -> tuple[ak.Array, a
# TODO: not hard-coded -> use config?
ml_processes = [
"signal_ggf", "signal_ggf2", "signal_vbf", "signal_vbf2",
"signal_ggf4", "signal_ggf5", "signal_vbf4", "signal_vbf5",
"hh_ggf_hbb_hvv_kl1_kt1", "hh_vbf_hbb_hvv_kv1_k2v1_kl1",
"hh_ggf_hbb_hvvqqlnu_kl1_kt1", "hh_vbf_hbb_hvvqqlnu_kv1_k2v1_kl1",
"hh_ggf_hbb_hvv2l2nu_kl1_kt1", "hh_vbf_hbb_hvv2l2nu_kv1_k2v1_kl1",
Expand Down
44 changes: 40 additions & 4 deletions hbw/config/defaults_and_groups.py
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Original file line number Diff line number Diff line change
Expand Up @@ -133,6 +133,38 @@ def set_config_defaults_and_groups(config_inst):
# process groups for conveniently looping over certain processs
# (used in wrapper_factory and during plotting)
config_inst.x.process_groups = {
"ml_study": [
"hh_vbf_hbb_hww2l2nu_kv1p74_k2v1p37_kl14p4",
"hh_vbf_hbb_hww2l2nu_kvm0p758_k2v1p44_klm19p3",
"hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kvm2p12_k2v3p87_klm5p96",
"hh_vbf_hbb_hww2l2nu_kv1_k2v1_kl1",
"hh_vbf_hbb_hww2l2nu_kv1_k2v0_kl1",
"hh_vbf_hbb_hww2l2nu_kvm0p962_k2v0p959_klm1p43",
"hh_vbf_hbb_hww2l2nu_kvm1p21_k2v1p94_klm0p94",
"hh_vbf_hbb_hww2l2nu_kvm1p6_k2v2p72_klm1p36",
"hh_vbf_hbb_hww2l2nu_kvm1p83_k2v3p57_klm3p39",
"hh_ggf_hbb_hww2l2nu_kl0_kt1",
"hh_ggf_hbb_hww2l2nu_kl1_kt1",
"hh_ggf_hbb_hww2l2nu_kl2p45_kt1",
"hh_ggf_hbb_hww2l2nu_kl5_kt1",
"st",
"tt",
"dy_m4to10", "dy_m10to50", "dy_m50toinf",
"w_lnu",
"vv",
"h_ggf", "h_vbf", "zh", "wh", "zh_gg", "tth",
],
"test_postfit": [
# "hh_vbf_hbb_hww2l2nu",
"hh_ggf_hbb_hww2l2nu",
"st",
"tt",
"dy",
"w_lnu",
"vv",
"h",
],
"all": ["*"],
"default": ["hh_ggf_hbb_hvv_kl1_kt1", "hh_vbf_hbb_hvv_kv1_k2v1_kl1", "tt", "dy", "st", "vv", "w_lnu", "h"], # noqa: E501
"sl": ["hh_ggf_hbb_hvv_kl1_kt1", "hh_vbf_hbb_hvv_kv1_k2v1_kl1", "tt", "qcd", "st", "dy", "vv", "w_lnu", "h"], # noqa: E501
Expand Down Expand Up @@ -282,10 +314,15 @@ def set_config_defaults_and_groups(config_inst):
),
# Dilepton
"SR_dl": (
"sr__1b__ml_signal_ggf", "sr__1b__ml_signal_ggf2", "sr__2b__ml_signal_ggf", "sr__2b__ml_signal_ggf2",
"sr__1b__ml_signal_vbf", "sr__1b__ml_signal_vbf2", "sr__2b__ml_signal_vbf", "sr__2b__ml_signal_vbf2",
"sr__1b__ml_signal_ggf4", "sr__1b__ml_signal_ggf5", "sr__2b__ml_signal_ggf4", "sr__2b__ml_signal_ggf5",
"sr__1b__ml_signal_vbf4", "sr__1b__ml_signal_vbf5", "sr__2b__ml_signal_vbf4", "sr__2b__ml_signal_vbf5",
"sr__1b__ml_hh_ggf_hbb_hvv2l2nu_kl1_kt1", "sr__2b__ml_hh_ggf_hbb_hvv2l2nu_kl1_kt1",
"sr__2mu__1b__ml_hh_ggf_hbb_hvv2l2nu_kl1_kt1", "sr__2mu__2b__ml_hh_ggf_hbb_hvv2l2nu_kl1_kt1",
"sr__2e__1b__ml_hh_ggf_hbb_hvv2l2nu_kl1_kt1", "sr__2e__2b__ml_hh_ggf_hbb_hvv2l2nu_kl1_kt1",
"sr__emu__1b__ml_hh_ggf_hbb_hvv2l2nu_kl1_kt1", "sr__emu__2b__ml_hh_ggf_hbb_hvv2l2nu_kl1_kt1",
"sr__1b", "sr__2b",
),
"vbfSR_dl": (
"sr__1b__ml_hh_vbf_hbb_hvv2l2nu_kv1_k2v1_kl1", "sr__2b__ml_hh_vbf_hbb_hvv2l2nu_kv1_k2v1_kl1",
Expand Down Expand Up @@ -372,10 +409,8 @@ def set_config_defaults_and_groups(config_inst):
for proc, _, _ in config_inst.walk_processes() if proc.has_tag("is_signal")
},
"dilep": {
"hh_ggf_hbb_hvv2l2nu_kl0_kt1": {"scale": 10000, "unstack": True},
"hh_ggf_hbb_hvv2l2nu_kl1_kt1": {"scale": 10000, "unstack": True},
"hh_ggf_hbb_hvv2l2nu_kl2p45_kt1": {"scale": 10000, "unstack": True},
"hh_ggf_hbb_hvv2l2nu_kl5_kt1": {"scale": 10000, "unstack": True},
"hh_vbf_hbb_hww2l2nu": {"scale": 90000, "unstack": True},
"hh_ggf_hbb_hww2l2nu": {"scale": 10000, "unstack": True},
},
"dileptest": {
"hh_ggf_hbb_hvv2l2nu_kl1_kt1": {"scale": 10000, "unstack": True},
Expand Down Expand Up @@ -478,4 +513,5 @@ def set_config_defaults_and_groups(config_inst):
"vbfSR_dl_resolved": is_signal_sm,
"vbfSR_dl_boosted": is_signal_sm,
"BR_dl": is_background,

}
2 changes: 1 addition & 1 deletion hbw/inference/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,7 +89,7 @@ def config_variable(self: InferenceModel, config_cat_inst: od.Config):
dnn_proc = dnn_cat.replace("ml_", "")
return f"mlscore.{dnn_proc}"
else:
return "mli_mbb"
return "mli_lep_pt"

def customize_category(self: InferenceModel, cat_inst: DotDict, config_cat_inst: od.Config):
""" Function to allow customizing the inference category """
Expand Down
233 changes: 211 additions & 22 deletions hbw/inference/dl.py
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Original file line number Diff line number Diff line change
Expand Up @@ -153,8 +153,94 @@
# "hh_ggf_hbb_hvv2l2nu_kl2p45_kt1",
# "hh_ggf_hbb_hvv2l2nu_kl5_kt1",

dl.derive("dl_ml_study_5", cls_dict={
"ml_model_name": "dl_22post_ml_study_5",
"config_categories": [
"sr__1b__ml_signal_ggf5",
"sr__1b__ml_signal_vbf5",
"sr__1b__ml_tt",
"sr__1b__ml_st",
"sr__1b__ml_dy",
"sr__1b__ml_h",
"sr__2b__ml_signal_ggf5",
"sr__2b__ml_signal_vbf5",
"sr__2b__ml_tt",
"sr__2b__ml_st",
"sr__2b__ml_dy",
"sr__2b__ml_h",
],
"processes": [
# qqHH_CV_m0p012_C2V_0p03_kl_10p2
# "hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kv1p74_k2v1p37_kl14p4",
"hh_vbf_hbb_hww2l2nu_kvm0p758_k2v1p44_klm19p3",
"hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kvm2p12_k2v3p87_klm5p96",
"hh_vbf_hbb_hww2l2nu_kv1_k2v1_kl1",
"hh_vbf_hbb_hww2l2nu_kv1_k2v0_kl1",
"hh_vbf_hbb_hww2l2nu_kvm0p962_k2v0p959_klm1p43",
"hh_vbf_hbb_hww2l2nu_kvm1p21_k2v1p94_klm0p94",
"hh_vbf_hbb_hww2l2nu_kvm1p6_k2v2p72_klm1p36",
"hh_vbf_hbb_hww2l2nu_kvm1p83_k2v3p57_klm3p39",
"hh_ggf_hbb_hww2l2nu_kl0_kt1",
"hh_ggf_hbb_hww2l2nu_kl1_kt1",
"hh_ggf_hbb_hww2l2nu_kl2p45_kt1",
"hh_ggf_hbb_hww2l2nu_kl5_kt1",
"st",
"tt",
"dy",
"w_lnu",
"vv",
"h_ggf", "h_vbf", "zh", "wh", "zh_gg", "tth",
],
"systematics": rate_systematics,
})

dl.derive("dl_ml_study_1", cls_dict={
dl.derive("dl_ml_study_4", cls_dict={
"ml_model_name": "dl_22post_ml_study_4",
"config_categories": [
"sr__1b__ml_signal_ggf4",
"sr__1b__ml_signal_vbf4",
"sr__1b__ml_tt",
"sr__1b__ml_st",
"sr__1b__ml_dy",
"sr__1b__ml_h",
"sr__2b__ml_signal_ggf4",
"sr__2b__ml_signal_vbf4",
"sr__2b__ml_tt",
"sr__2b__ml_st",
"sr__2b__ml_dy",
"sr__2b__ml_h",
],
"processes": [
# qqHH_CV_m0p012_C2V_0p03_kl_10p2
# "hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kv1p74_k2v1p37_kl14p4",
"hh_vbf_hbb_hww2l2nu_kvm0p758_k2v1p44_klm19p3",
"hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kvm2p12_k2v3p87_klm5p96",
"hh_vbf_hbb_hww2l2nu_kv1_k2v1_kl1",
"hh_vbf_hbb_hww2l2nu_kv1_k2v0_kl1",
"hh_vbf_hbb_hww2l2nu_kvm0p962_k2v0p959_klm1p43",
"hh_vbf_hbb_hww2l2nu_kvm1p21_k2v1p94_klm0p94",
"hh_vbf_hbb_hww2l2nu_kvm1p6_k2v2p72_klm1p36",
"hh_vbf_hbb_hww2l2nu_kvm1p83_k2v3p57_klm3p39",
"hh_ggf_hbb_hww2l2nu_kl0_kt1",
"hh_ggf_hbb_hww2l2nu_kl1_kt1",
"hh_ggf_hbb_hww2l2nu_kl2p45_kt1",
"hh_ggf_hbb_hww2l2nu_kl5_kt1",
"st",
"tt",
"dy",
"w_lnu",
"vv",
"h_ggf", "h_vbf", "zh", "wh", "zh_gg", "tth",
],
"systematics": rate_systematics,
})


dl_ml_study_1 = dl.derive("dl_ml_study_1", cls_dict={
"ml_model_name": "dl_22post_ml_study_1",
"config_categories": [
"sr__1b__ml_signal_ggf",
Expand All @@ -171,16 +257,69 @@
"sr__2b__ml_h",
],
"processes": [
"hh_vbf_hbb_hvv2l2nu_kv1_k2v1_kl1",
"hh_vbf_hbb_hvv2l2nu_kv1_k2v0_kl1",
"hh_vbf_hbb_hvv2l2nu_kvm0p962_k2v0p959_klm1p43",
"hh_vbf_hbb_hvv2l2nu_kvm1p21_k2v1p94_klm0p94",
"hh_vbf_hbb_hvv2l2nu_kvm1p6_k2v2p72_klm1p36",
"hh_vbf_hbb_hvv2l2nu_kvm1p83_k2v3p57_klm3p39",
"hh_ggf_hbb_hvv2l2nu_kl0_kt1",
"hh_ggf_hbb_hvv2l2nu_kl1_kt1",
"hh_ggf_hbb_hvv2l2nu_kl2p45_kt1",
"hh_ggf_hbb_hvv2l2nu_kl5_kt1",
# qqHH_CV_m0p012_C2V_0p03_kl_10p2
# "hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kv1p74_k2v1p37_kl14p4",
"hh_vbf_hbb_hww2l2nu_kvm0p758_k2v1p44_klm19p3",
"hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kvm2p12_k2v3p87_klm5p96",
"hh_vbf_hbb_hww2l2nu_kv1_k2v1_kl1",
"hh_vbf_hbb_hww2l2nu_kv1_k2v0_kl1",
"hh_vbf_hbb_hww2l2nu_kvm0p962_k2v0p959_klm1p43",
"hh_vbf_hbb_hww2l2nu_kvm1p21_k2v1p94_klm0p94",
"hh_vbf_hbb_hww2l2nu_kvm1p6_k2v2p72_klm1p36",
"hh_vbf_hbb_hww2l2nu_kvm1p83_k2v3p57_klm3p39",
"hh_ggf_hbb_hww2l2nu_kl0_kt1",
"hh_ggf_hbb_hww2l2nu_kl1_kt1",
"hh_ggf_hbb_hww2l2nu_kl2p45_kt1",
"hh_ggf_hbb_hww2l2nu_kl5_kt1",
"st",
"tt",
"dy",
"w_lnu",
"vv",
"h_ggf", "h_vbf", "zh", "wh", "zh_gg", "tth",
],
"systematics": rate_systematics,
})

dl_ml_study_1.derive("dl_ml_study_1_handle", cls_dict={
"ml_model_name": "dl_22post_ml_study_1_handle",
})

dl_ml_study_3 = dl.derive("dl_ml_study_3", cls_dict={
"ml_model_name": "dl_22_procs1_w0",
"config_categories": [
"sr__1b__ml_hh_ggf_hbb_hvv2l2nu_kl1_kt1",
"sr__1b__ml_hh_vbf_hbb_hvv2l2nu_kv1_k2v1_kl1",
"sr__1b__ml_tt",
"sr__1b__ml_st",
"sr__1b__ml_dy",
"sr__1b__ml_h",
"sr__2b__ml_hh_ggf_hbb_hvv2l2nu_kl1_kt1",
"sr__2b__ml_hh_vbf_hbb_hvv2l2nu_kv1_k2v1_kl1",
"sr__2b__ml_tt",
"sr__2b__ml_st",
"sr__2b__ml_dy",
"sr__2b__ml_h",
],
"processes": [
# "hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kv1p74_k2v1p37_kl14p4",
"hh_vbf_hbb_hww2l2nu_kvm0p758_k2v1p44_klm19p3",
"hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kvm2p12_k2v3p87_klm5p96",
"hh_vbf_hbb_hww2l2nu_kv1_k2v1_kl1",
"hh_vbf_hbb_hww2l2nu_kv1_k2v0_kl1",
"hh_vbf_hbb_hww2l2nu_kvm0p962_k2v0p959_klm1p43",
"hh_vbf_hbb_hww2l2nu_kvm1p21_k2v1p94_klm0p94",
"hh_vbf_hbb_hww2l2nu_kvm1p6_k2v2p72_klm1p36",
"hh_vbf_hbb_hww2l2nu_kvm1p83_k2v3p57_klm3p39",
"hh_ggf_hbb_hww2l2nu_kl0_kt1",
"hh_ggf_hbb_hww2l2nu_kl1_kt1",
"hh_ggf_hbb_hww2l2nu_kl2p45_kt1",
"hh_ggf_hbb_hww2l2nu_kl5_kt1",
"st",
"tt",
"dy",
"w_lnu",
Expand All @@ -190,7 +329,11 @@
"systematics": rate_systematics,
})

dl.derive("dl_ml_study_2", cls_dict={
dl_ml_study_3.derive("dl_ml_study_3_handle", cls_dict={
"ml_model_name": "dl_22_procs1_w0_handle",
})

dl_ml_study_2 = dl.derive("dl_ml_study_2", cls_dict={
"ml_model_name": "dl_22post_ml_study_2",
"config_categories": [
"sr__1b__ml_signal_ggf2",
Expand All @@ -207,16 +350,22 @@
"sr__2b__ml_h",
],
"processes": [
"hh_vbf_hbb_hvv2l2nu_kv1_k2v1_kl1",
"hh_vbf_hbb_hvv2l2nu_kv1_k2v0_kl1",
"hh_vbf_hbb_hvv2l2nu_kvm0p962_k2v0p959_klm1p43",
"hh_vbf_hbb_hvv2l2nu_kvm1p21_k2v1p94_klm0p94",
"hh_vbf_hbb_hvv2l2nu_kvm1p6_k2v2p72_klm1p36",
"hh_vbf_hbb_hvv2l2nu_kvm1p83_k2v3p57_klm3p39",
"hh_ggf_hbb_hvv2l2nu_kl0_kt1",
"hh_ggf_hbb_hvv2l2nu_kl1_kt1",
"hh_ggf_hbb_hvv2l2nu_kl2p45_kt1",
"hh_ggf_hbb_hvv2l2nu_kl5_kt1",
# "hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kv1p74_k2v1p37_kl14p4",
"hh_vbf_hbb_hww2l2nu_kvm0p758_k2v1p44_klm19p3",
"hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kvm2p12_k2v3p87_klm5p96",
"hh_vbf_hbb_hww2l2nu_kv1_k2v1_kl1",
"hh_vbf_hbb_hww2l2nu_kv1_k2v0_kl1",
"hh_vbf_hbb_hww2l2nu_kvm0p962_k2v0p959_klm1p43",
"hh_vbf_hbb_hww2l2nu_kvm1p21_k2v1p94_klm0p94",
"hh_vbf_hbb_hww2l2nu_kvm1p6_k2v2p72_klm1p36",
"hh_vbf_hbb_hww2l2nu_kvm1p83_k2v3p57_klm3p39",
"hh_ggf_hbb_hww2l2nu_kl0_kt1",
"hh_ggf_hbb_hww2l2nu_kl1_kt1",
"hh_ggf_hbb_hww2l2nu_kl2p45_kt1",
"hh_ggf_hbb_hww2l2nu_kl5_kt1",
"st",
"tt",
"dy",
"w_lnu",
Expand All @@ -226,6 +375,14 @@
"systematics": rate_systematics,
})

dl_ml_study_2.derive("dl_ml_study_2_handle", cls_dict={
"ml_model_name": "dl_22post_ml_study_2_handle",
})

dl_ml_study_2.derive("dl_ml_study_2_ignore", cls_dict={
"ml_model_name": "dl_22post_ml_study_2",
})

dl.derive("dl_hww_and_hzz", cls_dict={
"processes": [
"hh_ggf_hbb_hww_kl0_kt1",
Expand Down Expand Up @@ -390,3 +547,35 @@
"systematics": rate_systematics},
)
dl.derive("dl_rates_only", cls_dict={"systematics": rate_systematics})

dl.derive("dl_postfit_test", cls_dict={
"ml_model_name": None,
"config_categories": [
"sr__1b",
"sr__2b",
],
"processes": [
# "hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kv1p74_k2v1p37_kl14p4",
"hh_vbf_hbb_hww2l2nu_kvm0p758_k2v1p44_klm19p3",
"hh_vbf_hbb_hww2l2nu_kvm0p012_k2v0p03_kl10p2",
"hh_vbf_hbb_hww2l2nu_kvm2p12_k2v3p87_klm5p96",
"hh_vbf_hbb_hww2l2nu_kv1_k2v1_kl1",
"hh_vbf_hbb_hww2l2nu_kv1_k2v0_kl1",
"hh_vbf_hbb_hww2l2nu_kvm0p962_k2v0p959_klm1p43",
"hh_vbf_hbb_hww2l2nu_kvm1p21_k2v1p94_klm0p94",
"hh_vbf_hbb_hww2l2nu_kvm1p6_k2v2p72_klm1p36",
"hh_vbf_hbb_hww2l2nu_kvm1p83_k2v3p57_klm3p39",
"hh_ggf_hbb_hww2l2nu_kl0_kt1",
"hh_ggf_hbb_hww2l2nu_kl1_kt1",
"hh_ggf_hbb_hww2l2nu_kl2p45_kt1",
"hh_ggf_hbb_hww2l2nu_kl5_kt1",
"st",
"tt",
"dy",
"w_lnu",
"vv",
"h_ggf", "h_vbf", "zh", "wh", "zh_gg", "tth",
],
"systematics": rate_systematics,
})
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