Add missing file.

hbt/inference/default.py

@@ -0,0 +1,167 @@
+# coding: utf-8
+
+"""
+Default inference model.
+"""
+
+from columnflow.inference import inference_model, ParameterType
+
+
+@inference_model
+def default(self):
+
+    #
+    # categories
+    #
+
+    self.add_category(
+        "incl",
+        config_category="incl__os__iso",
+        config_variable="res_dnn_hh",
+        config_data_datasets=["data_*"],
+        mc_stats=8.0,
+    )
+
+    #
+    # processes
+    #
+
+    for kl in ["0", "1", "2p45", "5"]:
+        self.add_process(
+            f"ggHH_kl_{kl}_kt_1_13p6TeV_hbbhtt",
+            is_signal=True,
+            config_process=f"hh_ggf_hbb_htt_kl{kl}_kt1",
+            config_mc_datasets=[f"hh_ggf_hbb_htt_kl{kl}_kt1_powheg"],
+        )
+    self.add_process(
+        "TT",
+        config_process="tt",
+        config_mc_datasets=["^tt_(sl|dl|fh)_powheg$"],
+    )
+    self.add_process(
+        "DY",
+        config_process="dy",
+        config_mc_datasets=["dy_*_amcatnlo"],
+    )
+
+    #
+    # parameters
+    #
+
+    # general groups
+    self.add_parameter_group("experiment")
+    self.add_parameter_group("theory")
+
+    # groups that contain parameters that solely affect the signal cross section and/or br
+    self.add_parameter_group("signal_norm_xs")
+    self.add_parameter_group("signal_norm_xsbr")
+
+    # parameter that is added by the HH physics model, representing kl-dependent QCDscale + mtop
+    # uncertainties on the ggHH cross section
+    self.add_parameter_to_group("THU_HH", "theory")
+    self.add_parameter_to_group("THU_HH", "signal_norm_xs")
+    self.add_parameter_to_group("THU_HH", "signal_norm_xsbr")
+
+    # theory uncertainties
+    self.add_parameter(
+        "BR_hbb",
+        type=ParameterType.rate_gauss,
+        process=["*_hbb", "*_hbbhtt"],
+        effect=(0.9874, 1.0124),
+        group=["theory", "signal_norm_xsbr"],
+    )
+    self.add_parameter(
+        "BR_htt",
+        type=ParameterType.rate_gauss,
+        process=["*_htt", "*_hbbhtt"],
+        effect=(0.9837, 1.0165),
+        group=["theory", "signal_norm_xsbr"],
+    )
+    self.add_parameter(
+        "pdf_gg",  # contains alpha_s
+        type=ParameterType.rate_gauss,
+        process="TT",
+        effect=1.042,
+        group=["theory"],
+    )
+    self.add_parameter(
+        "pdf_Higgs_ggHH",  # contains alpha_s
+        type=ParameterType.rate_gauss,
+        process="ggHH_*",
+        effect=1.023,
+        group=["theory", "signal_norm_xs", "signal_norm_xsbr"],
+    )
+    self.add_parameter(
+        "pdf_Higgs_qqHH",  # contains alpha_s
+        type=ParameterType.rate_gauss,
+        process="qqHH_*",
+        effect=1.027,
+        group=["theory", "signal_norm_xs", "signal_norm_xsbr"],
+    )
+    self.add_parameter(
+        "QCDscale_ttbar",
+        type=ParameterType.rate_gauss,
+        process="TT",
+        effect=(0.965, 1.024),
+        group=["theory"],
+    )
+    self.add_parameter(
+        "QCDscale_qqHH",
+        type=ParameterType.rate_gauss,
+        process="qqHH_*",
+        effect=(0.9997, 1.0005),
+        group=["theory", "signal_norm_xs", "signal_norm_xsbr"],
+    )
+
+    # lumi
+    lumi = self.config_inst.x.luminosity
+    for unc_name in lumi.uncertainties:
+        self.add_parameter(
+            unc_name,
+            type=ParameterType.rate_gauss,
+            effect=lumi.get(names=unc_name, direction=("down", "up"), factor=True),
+            group="experiment",
+        )
+
+    # btag
+    for name in self.config_inst.x.btag_unc_names:
+        self.add_parameter(
+            f"CMS_btag_{name}",
+            type=ParameterType.shape,
+            config_shift_source=f"btag_{name}",
+            group="experiment",
+        )
+
+    # pileup
+    self.add_parameter(
+        "CMS_pileup_2022",
+        type=ParameterType.shape,
+        config_shift_source="minbias_xs",
+        group="experiment",
+    )
+
+    #
+    # cleanup
+    #
+
+    self.cleanup(keep_parameters="THU_HH")
+
+
+@inference_model
+def default_no_shifts(self):
+    # same initialization as "default" above
+    default.init_func.__get__(self, self.__class__)()
+
+    #
+    # remove all parameters that require a shift source other than nominal
+    #
+
+    for category_name, process_name, parameter in self.iter_parameters():
+        if parameter.type.is_shape or any(trafo.from_shape for trafo in parameter.transformations):
+            self.remove_parameter(parameter.name, process=process_name, category=category_name)
+
+    #
+    # cleanup
+    #
+
+    self.cleanup(keep_parameters="THU_HH")