LArHVGainsPredictor.GainPredictor Class Reference

Collaboration diagram for LArHVGainsPredictor.GainPredictor:

Public Member Functions
	__init__ (self, mapping)
	GetGain (self, receiver, orig_gain, layer_corr_ref, layer_corr_new, layer_names)

Public Attributes
	geometry_convertor = mapping
dict	layer_weights_em = {}
dict	layer_weights_had = {}

Detailed Description

Definition at line 74 of file LArHVGainsPredictor.py.

Constructor & Destructor Documentation

__init__()

LArHVGainsPredictor.GainPredictor.__init__	(		self,
			mapping )

Definition at line 76 of file LArHVGainsPredictor.py.

  def __init__(self, mapping):
    
    self.geometry_convertor = mapping
 
    self.layer_weights_em  = {} # per eta bin
    self.layer_weights_had = {} # per eta bin
 
    file_name= ROOT.PathResolver.find_calib_file("TrigT1Calo/HVcorrPhysicsWeights_v1.txt")
 
    
    
    try:
      
      file = open(file_name)
      
    except IOError:
 
      print ("\ncould not find file: %s ....exiting\n" % file_name)
 
      sys.exit()
 
    for line in file.readlines():
 
      parts = line.split()
 
      self.layer_weights_em [int(parts[0])] = [float(parts[1]),float(parts[2]),float(parts[3]),float(parts[4]),float(parts[5])]
      self.layer_weights_had[int(parts[0])] = [float(parts[6]),float(parts[7]),float(parts[8]),float(parts[9])]
 
    file.close()
    
 

Member Function Documentation

GetGain()

LArHVGainsPredictor.GainPredictor.GetGain	(		self,
			receiver,
			orig_gain,
			layer_corr_ref,
			layer_corr_new,
			layer_names )

Definition at line 107 of file LArHVGainsPredictor.py.

  def GetGain(self, receiver, orig_gain, layer_corr_ref, layer_corr_new, layer_names):
 
    coolid = self.geometry_convertor.getPPMfromReceiver(receiver)
    
    eta_bin = self.geometry_convertor.getEtaBin(coolid)
 
    hv_coef_ref = 0. # ref hv coefficient
    hv_coef_new = 0. # new hv coefficient
 
    
 
    if self.geometry_convertor.isCoolEm (coolid):
 
      is_overlap = self.geometry_convertor.isPPMOverlap(coolid)
 
      
 
      for n in range(len(layer_names)):
 
        layer = layer_names[n]
        
        if PlotCalibrationHV.isEmPresampler(layer):
 
          hv_coef_ref += layer_corr_ref[n] * self.layer_weights_em [eta_bin][0]
          hv_coef_new += layer_corr_new[n] * self.layer_weights_em [eta_bin][0]
 
        if PlotCalibrationHV.isEmFront(layer,is_overlap):
 
          hv_coef_ref += layer_corr_ref[n] * self.layer_weights_em [eta_bin][1]
          hv_coef_new += layer_corr_new[n] * self.layer_weights_em [eta_bin][1]
 
        if PlotCalibrationHV.isEmMiddle(layer,is_overlap):
 
          hv_coef_ref += layer_corr_ref[n] * self.layer_weights_em [eta_bin][2]
          hv_coef_new += layer_corr_new[n] * self.layer_weights_em [eta_bin][2]
 
        if PlotCalibrationHV.isEmBack(layer,is_overlap):
 
          hv_coef_ref += layer_corr_ref[n] * self.layer_weights_em [eta_bin][3]
          hv_coef_new += layer_corr_new[n] * self.layer_weights_em [eta_bin][3]
 
        if PlotCalibrationHV.isEmOverlapBack(layer,is_overlap):
 
          hv_coef_ref += layer_corr_ref[n] * self.layer_weights_em [eta_bin][4]
          hv_coef_new += layer_corr_new[n] * self.layer_weights_em [eta_bin][4]          
 
    
   
    if self.geometry_convertor.isCoolHad(coolid):
 
      regions = "EmbFcalHighEta" # (?)
 
      
 
      for n in range(len(layer_names)):
 
        layer = layer_names[n]
 
        if PlotCalibrationHV.isHadFirstLayer(layer,regions):
        
          hv_coef_ref += layer_corr_ref[n] * self.layer_weights_had[eta_bin][0]
          hv_coef_new += layer_corr_new[n] * self.layer_weights_had[eta_bin][0]
 
        if PlotCalibrationHV.isHadSecondLayer(layer,regions):
            
          hv_coef_ref += layer_corr_ref[n] * self.layer_weights_had[eta_bin][1]
          hv_coef_new += layer_corr_new[n] * self.layer_weights_had[eta_bin][1]
          
        if PlotCalibrationHV.isHadThirdLayer(layer,regions):
 
          hv_coef_ref += layer_corr_ref[n] * self.layer_weights_had[eta_bin][2]
          hv_coef_new += layer_corr_new[n] * self.layer_weights_had[eta_bin][2]
          
        if PlotCalibrationHV.isHadFourthLayer(layer,regions):
 
          hv_coef_ref += layer_corr_ref[n] * self.layer_weights_had[eta_bin][3]
          hv_coef_new += layer_corr_new[n] * self.layer_weights_had[eta_bin][3]
 
    pred_gain = orig_gain * (hv_coef_new/hv_coef_ref) # predicted gain
 
    return pred_gain
 
 

Member Data Documentation

geometry_convertor

LArHVGainsPredictor.GainPredictor.geometry_convertor = mapping

Definition at line 78 of file LArHVGainsPredictor.py.

layer_weights_em

dict LArHVGainsPredictor.GainPredictor.layer_weights_em = {}

Definition at line 80 of file LArHVGainsPredictor.py.

layer_weights_had

dict LArHVGainsPredictor.GainPredictor.layer_weights_had = {}

Definition at line 81 of file LArHVGainsPredictor.py.

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The documentation for this class was generated from the following file:

• LArHVGainsPredictor.py