def test_for_matrix_smaller_than_block_size(self):
a = np.array([[20], [10]])
res = split_into_blocks(a, block_size=3)
expected = [[20, 20, 20], [10, 10, 10], [10, 10, 10]]
self.assertEqual(res.shape, (1, 1, 3, 3))
self.assertEqual(res[0, 0].tolist(), expected)
def blocks(self, a, block_size):
blocks = split_into_blocks(a, block_size)
h = a.shape[0] // block_size
w = a.shape[1] // block_size
for y in range(0, h):
for x in range(w):
yield blocks[y, x], y, x
def test_with_nice_matrix(self):
a = np.arange(16).reshape((4, 4))
blocks = split_into_blocks(a, block_size=2)
self.assertEqual(blocks.shape, (2, 2, 2, 2))
self.assertEqual(blocks[0, 0].ravel().tolist(), [0, 1, 4, 5])
self.assertEqual(blocks[0, 1].ravel().tolist(), [2, 3, 6, 7])
self.assertEqual(blocks[1, 0].ravel().tolist(), [8, 9, 12, 13])
self.assertEqual(blocks[1, 1].ravel().tolist(), [10, 11, 14, 15])
def f():
a = np.array([[]])
res = split_into_blocks(a, block_size=3)
def f():
split_into_blocks(np.array([[[32]]]), block_size=2)
def f():
split_into_blocks(np.array([32, 31]), block_size=2)
def test_with_complex_matrix(self):
a = np.array([[3 - 2j]])
blocks = split_into_blocks(a, block_size=1)
self.assertEqual(blocks[0, 0].ravel().tolist(), [3 - 2j])
def execute(self, array):
blocks_matrix = split_into_blocks(array, self._config.block_size)
return np.mean(blocks_matrix, axis=(2, 3))