rdkit.ML.DecTree.QuantTree

Package rdkit :: Package ML :: Package DecTree :: Module QuantTree |
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# Source Code for Module rdkit.ML.DecTree.QuantTree

     1  # $Id$
     2  #
     3  #  Copyright (C) 2001, 2003  greg Landrum and Rational Discovery LLC
     4  #   All Rights Reserved
     5  #
     6  """ Defines the class _QuantTreeNode_, used to represent decision trees with automatic
     7   quantization bounds
     8
     9    _QuantTreeNode_ is derived from _DecTree.DecTreeNode_
    10
    11  """
    12  from rdkit.ML.DecTree import DecTree,Tree
    13  from rdkit.six import cmp
    14
    15 -class QuantTreeNode(DecTree.DecTreeNode):
    16    """
    17
    18    """
    19 -  def __init__(self,*args,**kwargs):
    20      DecTree.DecTreeNode.__init__(self,*args,**kwargs)
    21      self.qBounds = []
    22      self.nBounds = 0
    23 -  def ClassifyExample(self,example,appendExamples=0):
    24      """ Recursively classify an example by running it through the tree
    25
    26        **Arguments**
    27
    28          - example: the example to be classified
    29
    30          - appendExamples: if this is nonzero then this node (and all children)
    31            will store the example
    32
    33        **Returns**
    34
    35          the classification of _example_
    36
    37        **NOTE:**
    38          In the interest of speed, I don't use accessor functions
    39          here.  So if you subclass DecTreeNode for your own trees, you'll
    40          have to either include ClassifyExample or avoid changing the names
    41          of the instance variables this needs.
    42
    43      """
    44      if appendExamples:
    45        self.examples.append(example)
    46      if self.terminalNode:
    47        return self.label
    48      else:
    49        val = example[self.label]
    50        if not hasattr(self,'nBounds'): self.nBounds = len(self.qBounds)
    51        if self.nBounds:
    52          for i,bound in enumerate(self.qBounds):
    53            if val < bound:
    54              val = i
    55              break
    56          else:
    57            val = i+1
    58        else:
    59          val = int(val)
    60        return self.children[val].ClassifyExample(example,appendExamples=appendExamples)
    61
    62 -  def SetQuantBounds(self,qBounds):
    63      self.qBounds = qBounds[:]
    64      self.nBounds = len(self.qBounds)
    65 -  def GetQuantBounds(self):
    66      return self.qBounds
    67
    68 -  def __cmp__(self,other):
    69      return (self<other)*-1 or (other<self)*1
    70
    71 -  def __lt__(self,other):
    72      if str(type(self)) < str(type(other)): return True
    73      if self.qBounds<other.qBounds: return True
    74      if Tree.TreeNode.__lt__(self,other): return True
    75      return False
    76 -  def __eq__(self,other):
    77      return not self<other and not other<self
    78
    79 -  def __str__(self):
    80      """ returns a string representation of the tree
    81
    82        **Note**
    83
    84          this works recursively
    85
    86      """
    87      here = '%s%s %s\n'%('  '*self.level,self.name,str(self.qBounds))
    88      for child in self.children:
    89        here = here + str(child)
    90      return here
    91