Fix QCD Shape unc, calulated at hist merge step, not event wise Unc, so added data-driven flag so that it do not crash before hist-Merge

Analysis/AnalysisCacheProducer.py

@@ -159,7 +159,10 @@ def createAnalysisCache(
     Utilities.InitializeCorrections(setup, dataset_name, stage="AnalysisCache")
     scale_uncertainties = set()
     if setup.global_params["compute_unc_variations"]:
-        scale_uncertainties.update(unc_cfg_dict["shape"].keys())
+        for unc_name, unc_params in unc_cfg_dict["shape"].items():
+            if isinstance(unc_params, dict) and unc_params.get("data_driven", False):
+                continue
+            scale_uncertainties.add(unc_name)
     print("Scale uncertainties to consider:", scale_uncertainties)
 
     producer_config = setup.global_params["payload_producers"][producer_to_run]

Analysis/HistMergerFromHists.py

@@ -45,17 +45,18 @@ def fill_hists(
     unc_source="Central",
     data_type="data",
 ):
+    load_source = "Central" if unc_source == "QCDScale" else unc_source
     var_check = f"{var_input}"
     for key_tuple, hist_map in items_dict.items():
         for var, var_hist in hist_map.items():
-            scales = ["Up", "Down"] if unc_source != "Central" else ["Central"]
+            scales = ["Up", "Down"] if load_source != "Central" else ["Central"]
             for scale in scales:
-                if unc_source != "Central" and dataset_type != data_type:
-                    var_check = f"{var_input}_{unc_source}_{scale}"
+                if load_source != "Central" and dataset_type != data_type:
+                    var_check = f"{var_input}_{load_source}_{scale}"
                 if var != var_check:
                     continue
 
-                final_key = (key_tuple, (unc_source, scale))
+                final_key = (key_tuple, (load_source, scale))
                 if dataset_type not in all_hist_dict.keys():
                     all_hist_dict[dataset_type] = {}
                 if final_key not in all_hist_dict[dataset_type]:

Analysis/HistProducerFromNTuple.py

@@ -250,7 +250,10 @@ def BuildAllHistActions(
             uncs_to_compute.update(
                 {
                     key: setup.global_params["scales"]
-                    for key in unc_cfg_dict["shape"].keys()
+                    for key, params in unc_cfg_dict["shape"].items()
+                    if not (
+                        isinstance(params, dict) and params.get("data_driven", False)
+                    )
                 }
             )
     print(uncs_to_compute)

Analysis/HistTupleProducer.py

@@ -92,7 +92,10 @@ def createHistTuple(
     print("Norm uncertainties to consider:", norm_uncertainties)
     scale_uncertainties = set()
     if setup.global_params["compute_unc_variations"]:
-        scale_uncertainties.update(unc_cfg_dict["shape"].keys())
+        for unc_name, unc_params in unc_cfg_dict["shape"].items():
+            if isinstance(unc_params, dict) and unc_params.get("data_driven", False):
+                continue
+            scale_uncertainties.add(unc_name)
     print("Scale uncertainties to consider:", scale_uncertainties)
 
     print("Defining binnings for variables")