[RelVal] Add specific QC objects to compare

RelVal/config/QC/async/ITS_include_patterns_default.txt

@@ -0,0 +1,15 @@
+# for data and MC
+ITS_Tracks_PhiDistribution$
+ITS_Tracks_NClusters$
+ITS_Tracks_VertexZ$
+ITS_Tracks_VertexRvsZ$
+ITS_Tracks_VertexCoordinates$
+ITS_Clusters_Layer0_AverageClusterSizeSummary$
+ITS_Clusters_Layer3_AverageClusterSizeSummary$
+# only MC
+ITS_TracksMc_efficiency_eta_ratioFromTEfficiency$
+ITS_TracksMc_efficiency_phi_ratioFromTEfficiency$
+ITS_TracksMc_efficiency_pt_ratioFromTEfficiency$
+ITS_TracksMc_faketrack_eta_ratioFromTEfficiency$
+ITS_TracksMc_faketrack_phi_ratioFromTEfficiency$
+ITS_TracksMc_faketrack_pt_ratioFromTEfficiency$

RelVal/config/QC/async/TOF_include_patterns_defautl.txt

@@ -0,0 +1,11 @@
+# note that all "/" have to be replaced by "_"
+TOF_Digits_DecodingErrors$
+TOF_Digits_Multiplicity_Integrated$
+TOF_MatchTrAll_mTOFChi2ITSTPC-ITSTPCTRD$
+TOF_MatchTrAll_mTOFChi2TPC$
+TOF_MatchTrAll_mTOFChi2TPCTRD$
+TOF_MatchTrAll_mEffPt_ITSTPC-ITSTPCTRD_ratioFromTEfficiency$
+TOF_PID_EvTimeTOF$
+TOF_PID_DeltaBCTOFFT0$
+TOF_PID_DeltatPi_Pt_ITSTPC_t0TOF$
+TOF_PID_DeltatPi_Pt_ITSTPCTRD_t0TOF$

RelVal/config/QC/async/TPC_include_patterns_default.txt

@@ -0,0 +1,13 @@
+# note that all "/" have to be replaced by "_"
+TPC_Tracks_hPhiAside$
+TPC_Tracks_hPhiCside$
+TPC_Tracks_hEta$
+TPC_Tracks_hNClustersAfterCuts$
+TPC_Tracks_hQOverPt$
+TPC_Tracks_hDCAr_A_Pos$
+TPC_Tracks_hDCAr_C_Pos$
+TPC_Tracks_hDCArVsEtaPos$
+TPC_Tracks_h2DNClustersPhiAside$
+TPC_Tracks_h2DNClustersPhiCside$
+TPC_PID_hdEdxTotMIP_TPC$
+TPC_PID_hdEdxTotVsP_TPC$

RelVal/utils/o2dpg_release_validation_utils.py

@@ -282,9 +282,15 @@ def load_this_patterns(patterns):
                 return patterns
 
             patterns_from_file = []
-            with open(patterns[0][1:], "r") as f:
+            filename = patterns[0][1:]
+            if not exists(filename):
+                print(f"WARNING: Pattern file {filename} does not exist, not extracting any patterns!")
+                return
+            with open(filename, "r") as f:
                 for line in f:
                     line = line.strip()
+                    # remove all comments; allows for inline comments or entire comment lines), then take the first token
+                    line = line.split("#")[0].strip()
                     if not line:
                         continue
                     patterns_from_file.append(line)