class testClassBalancingDatasetSplitter(unittest.TestCase):
def setUp(self):
self.target = ClassBalancingDatasetSplitter()
def testSplitUnionIsEqualToTotal(self):
items = self.createImages(15, label=0)
result = self.target.split(items, [.6, .2, .2])
aggregated_result = result[0] + result[1] + result[2]
self.assertEqual(sorted(aggregated_result), sorted(items))
def testSplitIntersectionIsEmpy(self):
items = self.createImages(15, label=0)
result = self.target.split(items, [.6, .2, .2])
self.assertEqual(0, len(numpy.intersect1d(result[0], result[1])))
self.assertEqual(0, len(numpy.intersect1d(result[1], result[2])))
self.assertEqual(0, len(numpy.intersect1d(result[0], result[2])))
def testClassAreBalanced(self):
items0 = self.createImages(10, label=0)
items1 = self.createImages(5, label=1)
items2 = self.createImages(100, label=2)
items3 = self.createImages(200, label=3)
items = items0 + items1 + items2 + items3
result = self.target.split(items, [.6, .2, .2])
self.assertNumberOfItemsInResultWithLabel([6, 2, 2], result, label=0)
self.assertNumberOfItemsInResultWithLabel([3, 1, 1], result, label=1)
self.assertNumberOfItemsInResultWithLabel([60, 20, 20],
result,
label=2)
self.assertNumberOfItemsInResultWithLabel([120, 40, 40],
result,
label=3)
def assertNumberOfItemsInResultWithLabel(self, n, result, label):
for i in range(3):
self.assertEquals(n[i],
self.NumberOfItemsWithLabel(result[i], label))
def NumberOfItemsWithLabel(self, array, label):
return sum(1 if item.getLabel() == label else 0 for item in array)
def createImage(self, label):
image = Mock()
image.getLabel.return_value = label
return image
def createImages(self, quantity, label):
return [self.createImage(label) for i in range(quantity)]
class testClassBalancingDatasetSplitter(unittest.TestCase):
def setUp(self):
self.target = ClassBalancingDatasetSplitter()
def testSplitUnionIsEqualToTotal(self):
items = self.createImages(15, label = 0)
result = self.target.split(items, [.6,.2,.2])
aggregated_result = result[0] + result[1] + result[2]
self.assertEqual(sorted(aggregated_result), sorted(items))
def testSplitIntersectionIsEmpy(self):
items = self.createImages(15, label = 0)
result = self.target.split(items, [.6,.2,.2])
self.assertEqual(0, len(numpy.intersect1d(result[0], result[1])))
self.assertEqual(0, len(numpy.intersect1d(result[1], result[2])))
self.assertEqual(0, len(numpy.intersect1d(result[0], result[2])))
def testClassAreBalanced(self):
items0 = self.createImages(10, label = 0)
items1 = self.createImages(5, label = 1)
items2 = self.createImages(100, label = 2)
items3 = self.createImages(200, label = 3)
items = items0 + items1 + items2 + items3
result = self.target.split(items, [.6, .2, .2])
self.assertNumberOfItemsInResultWithLabel([6, 2, 2], result, label = 0)
self.assertNumberOfItemsInResultWithLabel([3, 1, 1], result, label = 1)
self.assertNumberOfItemsInResultWithLabel([60, 20, 20], result, label = 2)
self.assertNumberOfItemsInResultWithLabel([120, 40, 40], result, label = 3)
def assertNumberOfItemsInResultWithLabel(self, n, result, label):
for i in range(3):
self.assertEquals(n[i], self.NumberOfItemsWithLabel(result[i], label))
def NumberOfItemsWithLabel(self, array, label):
return sum(1 if item.getLabel() == label else 0 for item in array)
def createImage(self, label):
image = Mock()
image.getLabel.return_value = label
return image
def createImages(self, quantity, label):
return [self.createImage(label) for i in range(quantity)]
def ClassBalancingSplit():
return ClassBalancingDatasetSplitter()
def Create(imageSource, preprocessor = None):
return DatasetCreator(imageSource = imageSource,
datasetSplitter = ClassBalancingDatasetSplitter(),
preprocessor = preprocessor)
def setUp(self):
self.target = ClassBalancingDatasetSplitter()
def setUp(self):
self.target = ClassBalancingDatasetSplitter()
