def testFindBestSplit2(self):
minSplit = 1
X = numpy.zeros((20, 10))
y = numpy.ones(20)
X[0:10, 2] = numpy.arange(10)
X[10:, 2] = numpy.arange(10)+10
y[0:10] = -1
bestError, bestFeatureInd, bestThreshold, bestLeftInds, bestRightInds = findBestSplit2(minSplit, X, y)
self.assertEquals(bestError, 0.0)
self.assertEquals(bestFeatureInd, 2)
self.assertEquals(bestThreshold, 9.5)
self.assertTrue((bestLeftInds == numpy.arange(0, 10)).all())
self.assertTrue((bestRightInds == numpy.arange(10, 20)).all())
#Test case where all values are the same
X = numpy.zeros((20, 10))
bestError, bestFeatureInd, bestThreshold, bestLeftInds, bestRightInds = findBestSplit2(minSplit, X, y)
self.assertTrue(bestRightInds.shape[0]==0)
#Another simple example
X = numpy.random.rand(20, 1)
y = numpy.random.rand(20)
inds = [1, 3, 7, 12, 14, 15]
X[inds, 0] += 10
y[inds] += 1
bestError, bestFeatureInd, bestThreshold, bestLeftInds, bestRightInds = findBestSplit2(minSplit, X, y)
for i in range(10):
numExamples = numpy.random.randint(1, 200)
numFeatures = numpy.random.randint(1, 10)
X = numpy.random.rand(numExamples, numFeatures)
y = numpy.random.rand(numExamples)
bestError, bestFeatureInd, bestThreshold, bestLeftInds, bestRightInds = findBestSplit(minSplit, X, y)
bestError2, bestFeatureInd2, bestThreshold2, bestLeftInds2, bestRightInds2 = findBestSplit2(minSplit, X, y)
self.assertEquals(bestFeatureInd, bestFeatureInd2)
self.assertAlmostEquals(bestThreshold, bestThreshold2)
nptst.assert_array_equal(bestLeftInds, bestLeftInds2)
nptst.assert_array_equal(bestRightInds, bestRightInds2)
def testFindBestSplit(self):
minSplit = 1
X = numpy.zeros((20, 10))
y = numpy.ones(20)
X[0:10, 2] = numpy.arange(10)
X[10:, 2] = numpy.arange(10)+10
y[0:10] = -1
nodeInds = numpy.arange(X.shape[0])
argsortX = numpy.zeros(X.shape, numpy.int)
for i in range(X.shape[1]):
argsortX[:, i] = numpy.argsort(X[:, i])
argsortX[:, i] = numpy.argsort(argsortX[:, i])
bestError, bestFeatureInd, bestThreshold, bestLeftInds, bestRightInds = findBestSplit2(minSplit, X, y, nodeInds, argsortX)
self.assertEquals(bestError, 0.0)
self.assertEquals(bestFeatureInd, 2)
self.assertEquals(bestThreshold, 9.5)
self.assertTrue((bestLeftInds == numpy.arange(0, 10)).all())
self.assertTrue((bestRightInds == numpy.arange(10, 20)).all())
#Test case where all values are the same
X = numpy.zeros((20, 10))
argsortX = numpy.zeros(X.shape, numpy.int)
for i in range(X.shape[1]):
argsortX[:, i] = numpy.argsort(X[:, i])
argsortX[:, i] = numpy.argsort(argsortX[:, i])
bestError, bestFeatureInd, bestThreshold, bestLeftInds, bestRightInds = findBestSplit2(minSplit, X, y, nodeInds, argsortX)
self.assertTrue(bestLeftInds.shape[0]==0)
self.assertTrue(bestRightInds.shape[0]==X.shape[0])
#Another simple example
X = numpy.random.rand(20, 1)
y = numpy.random.rand(20)
inds = [1, 3, 7, 12, 14, 15]
X[inds, 0] += 10
y[inds] += 1
argsortX = numpy.zeros(X.shape, numpy.int)
for i in range(X.shape[1]):
argsortX[:, i] = numpy.argsort(X[:, i])
argsortX[:, i] = numpy.argsort(argsortX[:, i])
bestError, bestFeatureInd, bestThreshold, bestLeftInds, bestRightInds = findBestSplit2(minSplit, X, y, nodeInds, argsortX)
nptst.assert_array_equal(bestRightInds, numpy.array(inds))
#Test minSplit
minSplit = 10
bestError, bestFeatureInd, bestThreshold, bestLeftInds, bestRightInds = findBestSplit2(minSplit, X, y, nodeInds, argsortX)
self.assertTrue(bestLeftInds.shape[0] >= minSplit)
self.assertTrue(bestRightInds.shape[0] >= minSplit)
#Vary nodeInds
minSplit = 1
nodeInds = numpy.arange(16)
bestError, bestFeatureInd, bestThreshold, bestLeftInds, bestRightInds = findBestSplit2(minSplit, X, y, nodeInds, argsortX)
nptst.assert_array_equal(bestRightInds, numpy.array(inds))
nptst.assert_array_equal(bestLeftInds, numpy.setdiff1d(nodeInds, numpy.array(inds)))
nodeInds = numpy.arange(10)
bestError, bestFeatureInd, bestThreshold, bestLeftInds, bestRightInds = findBestSplit2(minSplit, X, y, nodeInds, argsortX)
nptst.assert_array_equal(bestRightInds, numpy.array([1,3,7]))
nptst.assert_array_equal(bestLeftInds, numpy.setdiff1d(nodeInds, numpy.array([1,3,7])))
