def test_get_chunk_sizes(self):
chunks = get_chunk_sizes((100, 100, 40), (30, 25, 50))
self.assertEqual([(30, 30, 30, 10), (25, 25, 25, 25), (40, )],
list(chunks))
chunks = get_chunk_sizes((100, 100, 40), (100, 100, 40))
self.assertEqual([(100, ), (100, ), (40, )], list(chunks))
def _assert_from_func(self, shape, chunks):
def my_func(array_shape, array_dtype, block_shape, block_slices):
bsy, bsx = block_slices
bh, bw = block_shape
w = array_shape[-1]
i0 = bsx[0]
j0 = bsy[0]
a = np.ndarray((bh, bw), dtype=array_dtype)
for j in range(bh):
for i in range(bw):
a[j, i] = 0.1 * (i0 + i + (j0 + j) * w)
return a
a = compute_array_from_func(
my_func,
shape,
chunks,
np.float64,
ctx_arg_names=['shape', 'dtype', 'block_shape', 'block_slices'])
self.assertIsNotNone(a)
self.assertEqual(shape, a.shape)
self.assertEqual(tuple(get_chunk_sizes(shape, chunks)), a.chunks)
self.assertEqual(np.float64, a.dtype)
h, w = shape
n = w * h
# Compute result
actual = np.array(a)
expected = (0.1 *
np.linspace(0, n - 1, n, dtype=np.float64)).reshape(shape)
np.testing.assert_almost_equal(actual, expected)
def ij_bboxes(self) -> np.ndarray:
chunk_sizes = get_chunk_sizes((self.height, self.width),
(self.tile_height, self.tile_width))
_, _, block_slices = get_block_iterators(chunk_sizes)
block_slices = tuple(block_slices)
n = len(block_slices)
ij_bboxes = np.ndarray((n, 4), dtype=np.int64)
for i in range(n):
y_slice, x_slice = block_slices[i]
ij_bboxes[i, 0] = x_slice.start
ij_bboxes[i, 1] = y_slice.start
ij_bboxes[i, 2] = x_slice.stop - 1
ij_bboxes[i, 3] = y_slice.stop - 1
return ij_bboxes
def ij_bboxes(self) -> np.ndarray:
"""The image tiles' bounding boxes in image pixel coordinates."""
chunk_sizes = get_chunk_sizes((self.height, self.width),
(self.tile_height, self.tile_width))
_, _, block_slices = get_block_iterators(chunk_sizes)
block_slices = tuple(block_slices)
n = len(block_slices)
ij_bboxes = np.ndarray((n, 4), dtype=np.int64)
for i in range(n):
y_slice, x_slice = block_slices[i]
ij_bboxes[i, 0] = x_slice.start
ij_bboxes[i, 1] = y_slice.start
ij_bboxes[i, 2] = x_slice.stop
ij_bboxes[i, 3] = y_slice.stop
return ij_bboxes