Merge branch 'fasermc-dev' into 'master'

Digitization Updates

See merge request faser/calypso!266

Calorimeter/CaloDigiAlgs/python/CaloDigiAlgsConfig.py

@@ -33,13 +33,14 @@ def CaloWaveformDigiCfg(flags, name="CaloWaveformDigiAlg", **kwargs):
     kwargs.setdefault("CaloHitContainerKey", "EcalHits")
     kwargs.setdefault("WaveformContainerKey", "CaloWaveforms")
 
-    kwargs.setdefault("CB_alpha", -0.9)
-    kwargs.setdefault("CB_n", 10)
-    kwargs.setdefault("CB_sigma", 4)
+    kwargs.setdefault("CB_alpha", -0.32)
+    kwargs.setdefault("CB_n", 1000)
+    kwargs.setdefault("CB_sigma", 3.67)
     kwargs.setdefault("CB_mean", 820) # Time in ns
-    kwargs.setdefault("CB_norm", 4)  # Low gain default, use 20 for high gain
+    # This number is over-ridden in the digitization script, so change it there!
+    kwargs.setdefault("CB_norm", 5.0)  # Low gain default without filters, use x5? for high gain
 
-    kwargs.setdefault("base_mean", 15000)
+    kwargs.setdefault("base_mean", 15650)
     kwargs.setdefault("base_rms", 3)
 
     digiAlg = CompFactory.CaloWaveformDigiAlg(name, **kwargs)

Control/CalypsoExample/Digitization/scripts/faserMDC_digi.py

@@ -131,9 +131,9 @@ acc.merge(FaserSCT_DigitizationCfg(ConfigFlags))
 
 from CaloDigiAlgs.CaloDigiAlgsConfig import CaloWaveformDigitizationCfg
 if args.highCaloGain:
-    calo_norm = 20.
+    calo_norm = 25.
 else:
-    calo_norm = 4.
+    calo_norm =  5.
 acc.merge(CaloWaveformDigitizationCfg(ConfigFlags, CB_norm=calo_norm))
 
 from ScintDigiAlgs.ScintDigiAlgsConfig import ScintWaveformDigitizationCfg

Control/CalypsoExample/Digitization/scripts/faserMDC_digi_merge.py

@@ -193,9 +193,9 @@ acc.merge(FaserSCT_DigitizationCfg(ConfigFlags))
 
 from CaloDigiAlgs.CaloDigiAlgsConfig import CaloWaveformDigitizationCfg
 if args.highCaloGain:
-    calo_norm = 20.
+    calo_norm = 25.
 else:
-    calo_norm = 4.
+    calo_norm =  5.
 acc.merge(CaloWaveformDigitizationCfg(ConfigFlags, CB_norm=calo_norm))
 
 from ScintDigiAlgs.ScintDigiAlgsConfig import ScintWaveformDigitizationCfg

Control/CalypsoExample/Digitization/scripts/faser_digi.py

@@ -130,9 +130,9 @@ acc.merge(FaserSCT_DigitizationCfg(ConfigFlags))
 
 from CaloDigiAlgs.CaloDigiAlgsConfig import CaloWaveformDigitizationCfg
 if args.highCaloGain:
-    calo_norm = 20.
+    calo_norm = 25.
 else:
-    calo_norm = 4.
+    calo_norm = 5.
 acc.merge(CaloWaveformDigitizationCfg(ConfigFlags, CB_norm=calo_norm))
 
 from ScintDigiAlgs.ScintDigiAlgsConfig import ScintWaveformDigitizationCfg

Control/CalypsoExample/Generation/data/mdc/FaserMC-MDC_PG_muon_fasernu_higain_logE-101305.json

+{
+    "file_length": 2000,
+    "mass": 105.66,
+    "maxE": 5000.0,
+    "minE": 10.0,
+    "pid": [-13, 13],
+    "radius": -100.0,
+    "run": 101305,
+    "sampler": "log",
+    "segment": 0,
+    "short": "MDC_PG_muon_fasernu_higain_logE",
+    "zpos": -3990.0
+}

Scintillator/ScintDigiAlgs/python/ScintDigiAlgsConfig.py

@@ -14,19 +14,18 @@ from WaveformConditionsTools.WaveformCableMappingConfig import WaveformCableMapp
 # Updated aamplitudes (norm) to match testbeam response
 # Make everything except VetoNu look like the preshower
 dict_CB_param = {}
-dict_CB_param["VetoNu"]=dict(CB_alpha=-0.38, CB_n=25, CB_mean=815, CB_sigma=7.7, CB_norm = 13300) 
-
-dict_CB_param["Preshower"]=dict(CB_alpha=-0.32, CB_n=65, CB_mean=846, CB_sigma=5.3, CB_norm = 330)
-dict_CB_param["Trigger"]=dict(CB_alpha=-0.32, CB_n=65, CB_mean=815, CB_sigma=5.3, CB_norm = 330 )
-dict_CB_param["Timing"]=dict(CB_alpha=-0.32, CB_n=65, CB_mean=815, CB_sigma=5.3, CB_norm = 330)
-dict_CB_param["Veto"]=dict(CB_alpha=-0.32, CB_n=65, CB_mean=815, CB_sigma=5.3, CB_norm = 330) 
+dict_CB_param["Trigger"]=dict(CB_alpha=-0.424, CB_n=6.14, CB_mean=815, CB_sigma=3.21, CB_norm = 4240) 
+dict_CB_param["Timing"] =dict(CB_alpha=-0.424, CB_n=6.14, CB_mean=846, CB_sigma=3.21, CB_norm = 4240) 
+dict_CB_param["Veto"]   =dict(CB_alpha=-0.32,  CB_n=9.0,  CB_mean=815, CB_sigma=3.35, CB_norm = 6840) 
+dict_CB_param["VetoNu"] =dict(CB_alpha=-0.28,  CB_n=1000, CB_mean=815, CB_sigma=5.00, CB_norm = 7040) 
+dict_CB_param["Preshower"]=dict(CB_alpha=-0.32, CB_n=1000, CB_mean=846, CB_sigma=4.0, CB_norm =  400)
 
 dict_baseline_params = {
-    "Trigger"   : {"mean" : 15000, "rms" : 3},
-    "Timing"    : {"mean" : 15000, "rms" : 3},
-    "Veto"      : {"mean" : 15000, "rms" : 3},
-    "VetoNu"    : {"mean" : 15000, "rms" : 3},
-    "Preshower" : {"mean" : 15000, "rms" : 3},        
+    "Trigger"   : {"mean" : 15650, "rms" : 3},
+    "Timing"    : {"mean" : 15650, "rms" : 3},
+    "Veto"      : {"mean" : 15650, "rms" : 3},
+    "VetoNu"    : {"mean" : 15650, "rms" : 3},
+    "Preshower" : {"mean" : 15650, "rms" : 3},        
     }
 
 # One stop shopping for normal FASER data