Beispiel #1
0
 def testLoadData(self):
     testPoints = [[0.307143, 0.130137, 0.050000],
                   [0.365584, 0.105479, 0.050000],
                   [0.178571, 0.201027, 0.050000],
                   [0.272078, 0.145548, 0.050000],
                   [0.318831, 0.065411, 0.050000],
                   [0.190260, 0.086986, 0.050000],
                   [0.190260, 0.062329, 0.072500],
                   [0.120130, 0.068493, 0.072500],
                   [0.225325, 0.056164, 0.072500],
                   [0.213636, 0.050000, 0.072500]]
     testValues = [
         -1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000,
         -1.000000, -1.000000, -1.000000, -1.000000
     ]
     filename = pathlocal + '/datasets/liver-disorders_normalized.arff.gz'
     adapter = ARFFAdapter(filename)
     container = adapter.loadData()
     points = container.getPoints()
     values = container.getValues()
     size = len(testPoints)
     dim = len(testPoints[0])
     testVector = DataVector(dim)
     for rowIdx in xrange(size):
         points.getRow(rowIdx, testVector)
         for colIdx in xrange(dim):
             if cvar.USING_DOUBLE_PRECISION:
                 self.assertEqual(testVector[colIdx],
                                  testPoints[rowIdx][colIdx])
             else:
                 self.assertAlmostEqual(testVector[colIdx],
                                        testPoints[rowIdx][colIdx])
         self.assertEqual(values[rowIdx], testValues[rowIdx])
 def testLoadData(self):
     testPoints = [[0.307143,0.130137,0.050000],
                   [0.365584,0.105479,0.050000],
                   [0.178571,0.201027,0.050000],
                   [0.272078,0.145548,0.050000],
                   [0.318831,0.065411,0.050000],
                   [0.190260,0.086986,0.050000],
                   [0.190260,0.062329,0.072500],
                   [0.120130,0.068493,0.072500],
                   [0.225325,0.056164,0.072500],
                   [0.213636,0.050000,0.072500]
                  ]
     testValues = [-1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, -1.000000, -1.000000, -1.000000, -1.000000]
     filename = pathlocal + '/datasets/liver-disorders_normalized.arff.gz'
     adapter = ARFFAdapter(filename)
     container = adapter.loadData()
     points = container.getPoints()
     values = container.getValues()
     size = len(testPoints)
     dim = len(testPoints[0])
     testVector = DataVector(dim)
     for rowIdx in xrange(size):
         points.getRow(rowIdx, testVector)
         for colIdx in xrange(dim):
             if cvar.USING_DOUBLE_PRECISION:
                 self.assertEqual(testVector[colIdx], testPoints[rowIdx][colIdx])
             else:
                 self.assertAlmostEqual(testVector[colIdx], testPoints[rowIdx][colIdx])
         self.assertEqual(values[rowIdx], testValues[rowIdx])
Beispiel #3
0
    def testSave(self):
        filename = pathlocal + '/datasets/saving.arff.gz'
        testPoints = [[0.307143, 0.130137, 0.050000],
                      [0.365584, 0.105479, 0.050000],
                      [0.178571, 0.201027, 0.050000],
                      [0.272078, 0.145548, 0.050000],
                      [0.318831, 0.065411, 0.050000],
                      [0.190260, 0.086986, 0.050000],
                      [0.190260, 0.062329, 0.072500],
                      [0.120130, 0.068493, 0.072500],
                      [0.225325, 0.056164, 0.072500],
                      [0.213636, 0.050000, 0.072500]]
        testValues = [
            -1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000,
            -1.000000, -1.000000, -1.000000, -1.000000
        ]
        attributes = {
            "x0": "NUMERIC",
            "x1": "NUMERIC",
            "x2": "NUMERIC",
            "class": "NUMERIC",
        }
        size = len(testPoints)
        dim = len(testPoints[0])
        point = DataVector(dim)
        points = DataMatrix(size, dim)

        for row in xrange(size):
            for col in xrange(dim):
                point[col] = testPoints[row][col]
            points.setRow(row, point)

        adapter = ARFFAdapter(filename)
        adapter.save(points, testValues, attributes)

        (points, values) = adapter.loadData().getPointsValues()
        size = len(testPoints)
        dim = len(testPoints[0])
        testVector = DataVector(dim)
        for rowIdx in xrange(size):
            points.getRow(rowIdx, testVector)
            for colIdx in xrange(dim):
                if cvar.USING_DOUBLE_PRECISION:
                    self.assertEqual(testVector[colIdx],
                                     testPoints[rowIdx][colIdx])
                else:
                    self.assertAlmostEqual(testVector[colIdx],
                                           testPoints[rowIdx][colIdx])
            self.assertEqual(values[rowIdx], testValues[rowIdx])

        os.remove(filename)
Beispiel #4
0
 def withTestingDataFromARFFFile(self, filename):
     """
     Signals to use data from ARFF file for testing dataset
     @param filename: Filename where to read the data from
     @return: LearnerBuilder object itself
     """
     adapter = ARFFAdapter(filename)
     dataContainer = adapter.loadData(DataContainer.TEST_CATEGORY)
     if self._learner.dataContainer is not None:
         dataContainer = self._learner.dataContainer.combine(dataContainer)
         self._learner.setDataContainer(dataContainer)
     else:
         self._learner.setDataContainer(dataContainer)
     return self
 def withTestingDataFromARFFFile(self, filename):
     """
     Signals to use data from ARFF file for testing dataset
     @param filename: Filename where to read the data from
     @return: LearnerBuilder object itself
     """
     adapter = ARFFAdapter(filename)
     dataContainer = adapter.loadData(DataContainer.TEST_CATEGORY)
     if self._learner.dataContainer is not None:
         dataContainer = self._learner.dataContainer.combine(dataContainer)
         self._learner.setDataContainer(dataContainer)
     else:
         self._learner.setDataContainer(dataContainer)
     return self
    def testSave(self):
        filename = pathlocal + '/datasets/saving.arff.gz'
        testPoints = [[0.307143,0.130137,0.050000],
                      [0.365584,0.105479,0.050000],
                      [0.178571,0.201027,0.050000],
                      [0.272078,0.145548,0.050000],
                      [0.318831,0.065411,0.050000],
                      [0.190260,0.086986,0.050000],
                      [0.190260,0.062329,0.072500],
                      [0.120130,0.068493,0.072500],
                      [0.225325,0.056164,0.072500],
                      [0.213636,0.050000,0.072500]
                     ]
        testValues = [-1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, -1.000000, -1.000000, -1.000000, -1.000000]
        attributes = {
                      "x0":"NUMERIC",
                      "x1":"NUMERIC",
                      "x2":"NUMERIC",
                      "class":"NUMERIC",
                      }
        size = len(testPoints)
        dim = len(testPoints[0])
        point = DataVector(dim)
        points = DataMatrix(size, dim)

        for row in xrange(size):
            for col in xrange(dim):
                point[col] = testPoints[row][col]
            points.setRow(row, point)

        adapter = ARFFAdapter(filename)
        adapter.save(points, testValues, attributes)

        (points, values) = adapter.loadData().getPointsValues()
        size = len(testPoints)
        dim = len(testPoints[0])
        testVector = DataVector(dim)
        for rowIdx in xrange(size):
            points.getRow(rowIdx, testVector)
            for colIdx in xrange(dim):
                if cvar.USING_DOUBLE_PRECISION:
                    self.assertEqual(testVector[colIdx], testPoints[rowIdx][colIdx])
                else:
                    self.assertAlmostEqual(testVector[colIdx], testPoints[rowIdx][colIdx])
            self.assertEqual(values[rowIdx], testValues[rowIdx])

        os.remove(filename)