Source Code for Module ML.ModelPackage.Packager

 1  ## Automatically adapted for numpy.oldnumeric Jun 27, 2008 by -c 
 2   
 3  # 
 4  # Copyright (C) 2002-2008 Greg Landrum and Rational Discovery LLC 
 5  # All rights are reserved. 
 6  # 
 7   
 8   
 9  import exceptions 
10 -class DescriptorCalculationError(exceptions.Exception): 
11    """ used to signal problems generating descriptor values """ 
12    pass 
13 -class ClassificationError(exceptions.Exception): 
14    """ used to signal problems generating predictions """ 
15    pass 
16   
17 -class ModelPackage(object): 
18    """ a container class to package a composite model with a descriptor 
19    calculator so that objects needing predictions (compounds, molecules, etc.) 
20    can be passed directly in without worrying about generating descriptors 
21   
22    """ 
23 -  def __init__(self,descCalc=None,model=None,dataSet=None,notes=''): 
24      self._descCalc = descCalc 
25      self._model = model 
26      self._notes = notes 
27      self._dataSet = dataSet 
28      self._initialized = 0 
29      self._supplementalData = [] 
30       
31 -  def SetCalculator(self,calc): 
32      self._descCalc = calc 
33 -  def GetCalculator(self): 
34      return self._descCalc 
35   
36 -  def SetModel(self,model): 
37      self._model = model 
38 -  def GetModel(self): 
39      return self._model 
40   
41 -  def SetDataset(self,data): 
42      self._dataSet = data 
43 -  def GetDataset(self): 
44      return self._dataSet 
45   
46 -  def SetNotes(self,notes): 
47      self._notes = notes 
48 -  def GetNotes(self): 
49      return self._notes 
50   
51 -  def SetSupplementalData(self,suppD): 
52      self._supplementalData = suppD 
53 -  def GetSupplementalData(self): 
54      if not hasattr(self,'_supplementalData'): 
55        self._supplementalData = [] 
56      return self._supplementalData 
57 -  def AddSupplementalData(self,data): 
58      if not hasattr(self,'_supplementalData'): 
59        self._supplementalData = [] 
60      self._supplementalData.append(data) 
61     
62 -  def Classify(self,obj,label='',threshold=0): 
63      if not self._initialized: 
64        self.Init() 
65      try: 
66        descs = self._descCalc.CalcDescriptors(obj) 
67      except: 
68        raise DescriptorCalculationError,'problems encountered generating descriptors' 
69   
70      argVect = [label]+list(descs)+[0] 
71      try: 
72        res = self._model.ClassifyExample(argVect,threshold=threshold,appendExample=0) 
73      except: 
74        import traceback 
75        traceback.print_exc() 
76        raise ClassificationError,'problems encountered generating prediction' 
77   
78      return res 
79   
80 -  def Init(self): 
81      if self._model is None or self._descCalc is None: 
82        return 
83       
84      nms = self._model.GetDescriptorNames() 
85      lbl = nms[0] 
86      act = nms[-1] 
87      descs = self._descCalc.GetDescriptorNames() 
88      order = [lbl] + list(descs) + [act] 
89      self._model.SetInputOrder(order) 
90       
91      self._initialized = 1 
92