imporoved the plot style

rdstar/offline_analysis/selection/selection_info_containers.py

@@ -156,7 +156,7 @@ class CutInfo:
             return [str(float(f))]
 
     def scale_cut(self, percentage: float = 0.1) -> "CutInfo":
-        assert 0. <= percentage < 1., percentage
+        assert 0. <= percentage <= 1., percentage
         if self.cut_type == "==":
             cut_str = ""
             cut_type = ""

rdstar/studies/low_level_cut_study/low_level_cut_defintions.py

@@ -8,7 +8,7 @@ from rdstar.online_analysis.final_state_particles import fsp_cut_sets
 from rdstar.studies.low_level_cut_study.decay_channels_cut_study import D_decay_label_to_cut_info_list as D_loose_dict, \
     Dstar_decay_label_to_cut_info_list as Dstar_loose_dict
 from rdstar.online_analysis.decay_channels import D_decay_label_to_cut_info_list, Dstar_decay_label_to_cut_info_list, \
-    D_decay_label_to_decay_id, Dstar_decay_label_to_decay_id
+    D_decay_label_to_decay_id, Dstar_decay_label_to_decay_id, Dstar_decay_channels, D_decay_channels
 
 
 
@@ -77,6 +77,11 @@ combined_decay_mode_id_dict = {}
 combined_decay_mode_id_dict.update(D_decay_label_to_decay_id)
 combined_decay_mode_id_dict.update(Dstar_decay_label_to_decay_id)
 
+combined_channel_dict = {}
+combined_channel_dict.update(D_decay_channels)
+combined_channel_dict.update(Dstar_decay_channels)
+combined_channel_dict.update({"":""})
+
 if __name__ == '__main__':
     for channel, item in Dstar_decay_label_to_cut_info_list.items():
         for c in item:

rdstar/studies/low_level_cut_study/plotting.py

@@ -9,7 +9,8 @@ from rdstar.offline_analysis.selection.selection_info_containers import CutInfo
 
 from templatefitter.plotter.plot_style import set_matplotlibrc_params, KITColors
 
-from rdstar.studies.low_level_cut_study.low_level_cut_defintions import fsp_cut_dict, D_cut_dict, combined_decay_mode_id_dict
+from rdstar.studies.low_level_cut_study.low_level_cut_defintions import fsp_cut_dict, D_cut_dict, \
+    combined_decay_mode_id_dict, combined_channel_dict
 
 
 class LowLevelCutPlotter:
@@ -65,7 +66,7 @@ class LowLevelCutPlotter:
                     plt.cla()
                     plt.title(cut_info.cut_str, loc="center")
                     plt.title(channel, loc="right")
-                    plt.savefig(save_path)
+                    #plt.savefig(save_path)
                     continue
 
                 fig, ax = plt.subplots()
@@ -88,20 +89,21 @@ class LowLevelCutPlotter:
                 )
 
                 plt.grid(False)
-                plt.title(cut_info.cut_str, loc="center")
-                plt.title(channel, loc="right")
+                plt.xlabel(cut_info.cut_label)
+                plt.ylabel("Entries")
+                plt.title(combined_channel_dict[channel], loc="right")
                 plt.legend(loc="best")
                 save_path = os.path.join(self.target_path, f"{key}_{new_cut_info.cut_name}_evaluation.pdf")
                 output.update({f"{key}_{new_cut_info.cut_name}_evaluation": save_path})
-                plt.savefig(save_path)
-                #plt.show()
+                #plt.savefig(save_path)
+                plt.show()
 
         return output
 
 if __name__ == '__main__':
-    #df = pd.read_hdf("/ceph/pecker/rdstar/low_level_cut_study/CombinedNTuples/e_ntuple_total.h5")
-    df = pd.read_hdf("/ceph/pecker/rdstar/low_level_cut_study/CombinedNTuples/dcharged_ntuple_total.h5")
-    llcp = LowLevelCutPlotter(n_tuple="dcharged_ntuple", target_path="")
+    df = pd.read_hdf("/ceph/pecker/rdstar/low_level_cut_study/prod_4thAug/CombinedNTuples/e_ntuple_total.h5")
+    #df = pd.read_hdf("/ceph/pecker/rdstar/low_level_cut_study/CombinedNTuples/dcharged_ntuple_total.h5")
+    llcp = LowLevelCutPlotter(n_tuple="e_ntuple", target_path="")
     print(llcp.generate_output_dict())
     llcp.get_df(df=df)
     #llcp.apply_cuts(pivot=fsp_cut_dict["e_ntuple"]["cuts"][0], cut_infos=fsp_cut_dict["e_ntuple"]["cuts"])