def test_resize_to_shape(self):
data = np.random.rand(3, 4, 5)
new_shape = [5, 6, 6]
data_out = ima.resize_to_shape(data, new_shape)
self.assertEquals(new_shape[0], data_out.shape[0])
self.assertEquals(new_shape[1], data_out.shape[1])
self.assertEquals(new_shape[2], data_out.shape[2])
def test_resize_to_shape(self):
data = np.random.rand(3, 4, 5)
new_shape = [5, 6, 6]
data_out = ima.resize_to_shape(data, new_shape)
# self.assertCountEqual(new_shape, data_out.shape)
self.assertEqual(new_shape[0], data_out.shape[0])
self.assertEqual(new_shape[1], data_out.shape[1])
self.assertEqual(new_shape[2], data_out.shape[2])
def test_resize_to_shape_with_dtype_orig(self):
data = 10 * np.random.rand(3, 4, 5).astype(dtype=np.uint8)
new_shape = [5, 6, 6]
data_out = ima.resize_to_shape(data, new_shape, dtype="orig")
self.assertEquals(new_shape[0], data_out.shape[0])
self.assertEquals(new_shape[1], data_out.shape[1])
self.assertEquals(new_shape[2], data_out.shape[2])
assert data_out.dtype == np.uint8
assert np.array_equal(np.unique(data), np.unique(data_out))
def test_resize_to_shape_with_small_number_of_seeds(self):
data = np.zeros([50, 51, 52])
data[10:15, 10:30, 10:30] = 1
data[30:36, 20:30, 20:30] = 2
new_shape = [10, 10, 10]
data_out = ima.resize_to_shape(data, new_shape, order=0, dtype=None)
assert np.array_equal(np.unique(data), np.unique(data_out))
self.assertEquals(new_shape[0], data_out.shape[0])
self.assertEquals(new_shape[1], data_out.shape[1])
self.assertEquals(new_shape[2], data_out.shape[2])
def test_resize_to_shape_no_new_unique_values(self):
data = np.zeros([10, 15, 12])
value1 = 1
value2 = 2
data[:5, :7, :6] = value1
data[-5:, :7, :6] = value2
expected_shape = [15, 15, 15]
resized = ima.resize_to_shape(data, expected_shape)
unique = np.unique(resized)
self.assertEqual(resized.shape[0], expected_shape[0])
self.assertEqual(resized.shape[1], expected_shape[1])
self.assertEqual(resized.shape[2], expected_shape[2])
self.assertEqual(resized[1, 1, 1], value1)
self.assertEqual(resized[-2, 1, 1], value2)
self.assertEqual(len(unique), 3)
self.assertEqual(unique[0], 0)
self.assertEqual(unique[1], 1)
self.assertEqual(unique[2], 2)
def test_resize_to_shape_no_new_unique_values(self):
data = np.zeros([10, 15, 12])
value1 = 1
value2 = 2
data[:5, :7, :6] = value1
data[-5:, :7, :6] = value2
expected_shape = [15, 15, 15]
resized = ima.resize_to_shape(data, expected_shape)
unique = np.unique(resized)
self.assertEqual(resized.shape[0], expected_shape[0])
self.assertEqual(resized.shape[1], expected_shape[1])
self.assertEqual(resized.shape[2], expected_shape[2])
self.assertEqual(resized[1, 1, 1], value1)
self.assertEqual(resized[-2, 1, 1], value2)
self.assertEqual(len(unique), 3)
self.assertEqual(unique[0], 0)
self.assertEqual(unique[1], 1)
self.assertEqual(unique[2], 2)