rdkit/Python/ML/DecTree/UnitTestID3.py

#
#  Copyright (C) 2000  greg Landrum
#

""" unit tests for the ID3 implementation """
import RDConfig
import unittest
from ML.DecTree import ID3,DecTree
import cPickle
from ML.Data import MLData

class ID3TestCase(unittest.TestCase):
  def setUp(self):
    print '\n%s: '%self.shortDescription(),
    self.basicTreeName=RDConfig.RDCodeDir+'/ML/DecTree/regress/BasicTree.pkl'
    self.multiTreeName=RDConfig.RDCodeDir+'/ML/DecTree/regress/MultiTree.pkl'
  def _setupBasicTree(self):
    examples = [[0,0,0,0,0],
                [0,0,0,1,0],
                [1,0,0,0,1],
                [2,1,0,0,1],
                [2,2,1,0,1],
                [2,2,1,1,0],
                [1,2,1,1,1],
                [0,1,0,0,0],
                [0,2,1,0,1],
                [2,1,1,0,1],
                [0,1,1,1,1],
                [1,1,0,1,1],
                [1,0,1,0,1],
                [2,1,0,1,0]
                ]

    data = MLData.MLQuantDataSet(examples)
    attrs = range(0,data.GetNVars())
    t1 = ID3.ID3Boot(data.GetAllData(),attrs,data.GetNPossibleVals())
    self.t1 = t1
    self.examples = examples

  def testBasicTree(self):
    " testing basic tree growth "
    self._setupBasicTree()
    inFile = open(self.basicTreeName,'r')
    t2 = cPickle.load(inFile)
    assert self.t1 == t2, 'Incorrect tree generated.'

  def _setupMultiTree(self):
    examples = [[0,1,0,0],
                [0,0,0,1],
                [0,0,1,2],
                [0,1,1,2],
                [1,0,0,2],
                [1,0,1,2],
                [1,1,0,2],
                [1,1,1,0]
                ]

    data = MLData.MLQuantDataSet(examples)
    attrs = range(0,data.GetNVars())
    t1 = ID3.ID3Boot(data.GetAllData(),attrs,data.GetNPossibleVals())
    self.t1 = t1
    self.examples = examples

  def testMultiTree(self):
    " testing multivalued tree growth "
    self._setupMultiTree()
    inFile = open(self.multiTreeName,'r')
    t2 = cPickle.load(inFile)
    assert self.t1 == t2, 'Incorrect tree generated.'
    
  def testClassify(self):
    " testing basic tree classification "
    self._setupBasicTree()
    assert self.t1.ClassifyExample(self.examples[0])==self.examples[0][-1],\
           'BasicExample 0 misclassified'
    assert self.t1.ClassifyExample(self.examples[1])==self.examples[1][-1],\
           'BasicExample 1 misclassified'
    assert self.t1.ClassifyExample(self.examples[6])==self.examples[6][-1],\
           'BasicExample 6 misclassified'
    self._setupMultiTree()
    assert self.t1.ClassifyExample(self.examples[0])==self.examples[0][-1],\
           'MultiExample 0 misclassified'
    assert self.t1.ClassifyExample(self.examples[1])==self.examples[1][-1],\
           'MultiExample 1 misclassified'
    assert self.t1.ClassifyExample(self.examples[6])==self.examples[6][-1],\
           'MultiExample 6 misclassified'

  # ------------- force python in the ID3 code   
  def _setupPyBasicTree(self):
    from ML.InfoTheory import entropy
    ID3.entropy.InfoEntropy = entropy.PyInfoEntropy
    ID3.entropy.InfoGain = entropy.PyInfoGain
    
    examples = [[0,0,0,0,0],
                [0,0,0,1,0],
                [1,0,0,0,1],
                [2,1,0,0,1],
                [2,2,1,0,1],
                [2,2,1,1,0],
                [1,2,1,1,1],
                [0,1,0,0,0],
                [0,2,1,0,1],
                [2,1,1,0,1],
                [0,1,1,1,1],
                [1,1,0,1,1],
                [1,0,1,0,1],
                [2,1,0,1,0]
                ]

    data = MLData.MLQuantDataSet(examples)
    attrs = range(0,data.GetNVars())
    t1 = ID3.ID3Boot(data.GetAllData(),attrs,data.GetNPossibleVals())
    self.t1 = t1
    self.examples = examples

  def testPyBasicTree(self):
    " testing basic tree growth (python entropy code) "
    self._setupPyBasicTree()
    inFile = open(self.basicTreeName,'r')
    t2 = cPickle.load(inFile)
    assert self.t1 == t2, 'Incorrect tree generated.'

  def _setupPyMultiTree(self):
    from ML.InfoTheory import entropy
    ID3.entropy.InfoEntropy = entropy.PyInfoEntropy
    ID3.entropy.InfoGain = entropy.PyInfoGain

    examples = [[0,1,0,0],
                [0,0,0,1],
                [0,0,1,2],
                [0,1,1,2],
                [1,0,0,2],
                [1,0,1,2],
                [1,1,0,2],
                [1,1,1,0]
                ]

    data = MLData.MLQuantDataSet(examples)
    attrs = range(0,data.GetNVars())
    t1 = ID3.ID3Boot(data.GetAllData(),attrs,data.GetNPossibleVals())
    self.t1 = t1
    self.examples = examples

  def testPyMultiTree(self):
    " testing multivalued tree growth (python entropy code) "
    self._setupPyMultiTree()
    inFile = open(self.multiTreeName,'r')
    t2 = cPickle.load(inFile)
    assert self.t1 == t2, 'Incorrect tree generated.'
    
  def testPyClassify(self):
    " testing tree classification (python entropy code) "
    self._setupPyBasicTree()
    assert self.t1.ClassifyExample(self.examples[0])==self.examples[0][-1],\
           'BasicExample 0 misclassified'
    assert self.t1.ClassifyExample(self.examples[1])==self.examples[1][-1],\
           'BasicExample 1 misclassified'
    assert self.t1.ClassifyExample(self.examples[6])==self.examples[6][-1],\
           'BasicExample 6 misclassified'
    self._setupMultiTree()
    assert self.t1.ClassifyExample(self.examples[0])==self.examples[0][-1],\
           'MultiExample 0 misclassified'
    assert self.t1.ClassifyExample(self.examples[1])==self.examples[1][-1],\
           'MultiExample 1 misclassified'
    assert self.t1.ClassifyExample(self.examples[6])==self.examples[6][-1],\
           'MultiExample 6 misclassified'
    
if __name__ == '__main__':
  unittest.main()