def test_default(self):
a = np.linspace(0, 255, 24, dtype=np.int32).reshape((4, 6))
b = np.linspace(255, 0, 24, dtype=np.int32).reshape((4, 6))
c = np.linspace(50, 200, 24, dtype=np.int32).reshape((4, 6))
source_images = [
SourceArrayImage(a, (2, 2)),
SourceArrayImage(b, (2, 2)),
SourceArrayImage(c, (2, 2)),
]
cm_rgb_image = DirectRgbaImage(source_images, format='PNG')
self.assertEqual(cm_rgb_image.size, (6, 4))
self.assertEqual(cm_rgb_image.tile_size, (2, 2))
self.assertEqual(cm_rgb_image.num_tiles, (3, 2))
tile = cm_rgb_image.get_tile(0, 0)
self.assertIsInstance(tile, PIL.Image.Image)
def new_rgb_image(ml_dataset: MultiLevelDataset, image_id: str,
var_names: Tuple[str, ...],
norm_ranges: Tuple[Number, Number], z: int, labels,
labels_are_indices, tile_cache, trace_perf, exception_type):
tile_grid = ml_dataset.tile_grid
images = []
for i in range(3):
var_name = var_names[i]
array, _, _ = \
_get_var_2d_array_and_mask_info(
ml_dataset, var_name, z, labels,
labels_are_indices,
exception_type
)
image = SourceArrayImage(array,
image_id=f'ai-{image_id}',
tile_size=tile_grid.tile_size,
flip_y=tile_grid.is_j_axis_up,
trace_perf=trace_perf)
image = NormalizeArrayImage(image,
image_id=f'tai-{image_id}',
norm_range=norm_ranges[i],
trace_perf=trace_perf)
images.append(image)
return DirectRgbaImage((images[0], images[1], images[2]),
image_id=f'drgba-{image_id}',
encode=True,
format='PNG',
tile_cache=tile_cache,
trace_perf=trace_perf)
def test_force_2d(self):
a = np.arange(0, 48, dtype=np.int32).reshape((2, 4, 6))
source_image = SourceArrayImage(a[0], (2, 2))
target_image = NormalizeArrayImage(source_image, force_2d=True)
self.assertEqual(target_image.size, (6, 4))
self.assertEqual(target_image.tile_size, (2, 2))
self.assertEqual(target_image.num_tiles, (3, 2))
def test_default(self):
a = np.linspace(0, 255, 24, dtype=np.int32).reshape((4, 6))
source_image = SourceArrayImage(a, (2, 2))
cm_rgb_image = ColorMappedRgbaImage(source_image, format='PNG')
self.assertEqual(cm_rgb_image.size, (6, 4))
self.assertEqual(cm_rgb_image.tile_size, (2, 2))
self.assertEqual(cm_rgb_image.num_tiles, (3, 2))
tile = cm_rgb_image.get_tile(0, 0)
self.assertIsInstance(tile, PIL.Image.Image)
def test_flip_y_tiled_evenly(self):
a = np.arange(0, 24, dtype=np.int32).reshape((4, 6))
source_array_image = SourceArrayImage(a, (2, 2), flip_y=True)
self.assertEqual(source_array_image.size, (6, 4))
self.assertEqual(source_array_image.tile_size, (2, 2))
self.assertEqual(source_array_image.num_tiles, (3, 2))
self.assertEqual(
source_array_image.get_tile(0, 0).tolist(), [[18, 19], [12, 13]])
self.assertEqual(
source_array_image.get_tile(1, 0).tolist(), [[20, 21], [14, 15]])
self.assertEqual(
source_array_image.get_tile(2, 0).tolist(), [[22, 23], [16, 17]])
self.assertEqual(
source_array_image.get_tile(0, 1).tolist(), [[6, 7], [0, 1]])
self.assertEqual(
source_array_image.get_tile(1, 1).tolist(), [[8, 9], [2, 3]])
self.assertEqual(
source_array_image.get_tile(2, 1).tolist(), [[10, 11], [4, 5]])
def test_default(self):
a = np.arange(0, 24, dtype=np.int32).reshape((4, 6))
source_image = SourceArrayImage(a, (2, 2))
target_image = NormalizeArrayImage(source_image)
self.assertEqual(target_image.size, (6, 4))
self.assertEqual(target_image.tile_size, (2, 2))
self.assertEqual(target_image.num_tiles, (3, 2))
self.assertEqual(
target_image.get_tile(0, 0).tolist(), [[0, 1], [6, 7]])
self.assertEqual(
target_image.get_tile(1, 0).tolist(), [[2, 3], [8, 9]])
self.assertEqual(
target_image.get_tile(2, 0).tolist(), [[4, 5], [10, 11]])
self.assertEqual(
target_image.get_tile(0, 1).tolist(), [[12, 13], [18, 19]])
self.assertEqual(
target_image.get_tile(1, 1).tolist(), [[14, 15], [20, 21]])
self.assertEqual(
target_image.get_tile(2, 1).tolist(), [[16, 17], [22, 23]])
def new_color_mapped_image(ml_dataset: MultiLevelDataset, image_id: str,
var_name: str, cmap_name: str,
cmap_range: Tuple[float,
float], z: int, labels: Dict[str,
Any],
labels_are_indices: bool, tile_cache, trace_perf,
exception_type: Type[Exception]):
array, valid_range, var = \
_get_var_2d_array_and_mask_info(
ml_dataset, var_name, z, labels,
labels_are_indices,
exception_type
)
cmap_name, cmap_range = get_var_cmap_params(var, cmap_name, cmap_range,
valid_range)
tile_grid = ml_dataset.tile_grid
image = SourceArrayImage(array,
image_id=f'ai-{image_id}',
tile_size=tile_grid.tile_size,
flip_y=tile_grid.is_j_axis_up,
trace_perf=trace_perf)
image = NormalizeArrayImage(image,
image_id=f'tai-{image_id}',
norm_range=cmap_range,
trace_perf=trace_perf)
if cmap_name is None and cmap_range is None:
# TODO: Return a ColorMappedRawImage(...) whose tiles
# are binary, compressed numpy arrays
return image
return ColorMappedRgbaImage(image,
image_id=f'cmrgbai-{image_id}',
cmap_name=cmap_name,
encode=True,
format='PNG',
tile_cache=tile_cache,
trace_perf=trace_perf)
def test_flip_y_not_tiled_evenly(self):
a = np.arange(0, 30, dtype=np.int32).reshape((5, 6))
source_array_image = SourceArrayImage(a, (2, 2), flip_y=True)
self.assertEqual(source_array_image.size, (6, 5))
self.assertEqual(source_array_image.tile_size, (2, 2))
self.assertEqual(source_array_image.num_tiles, (3, 3))
self.assertEqual(
source_array_image.get_tile(0, 0).tolist(), [[24, 25], [18, 19]])
self.assertEqual(
source_array_image.get_tile(1, 0).tolist(), [[26, 27], [20, 21]])
self.assertEqual(
source_array_image.get_tile(2, 0).tolist(), [[28, 29], [22, 23]])
self.assertEqual(
source_array_image.get_tile(0, 1).tolist(), [[12, 13], [6, 7]])
self.assertEqual(
source_array_image.get_tile(1, 1).tolist(), [[14, 15], [8, 9]])
self.assertEqual(
source_array_image.get_tile(2, 1).tolist(), [[16, 17], [10, 11]])
tile_0_2 = source_array_image.get_tile(0, 2).tolist()
self.assertEqual(tile_0_2[0], [0, 1])
self.assertTrue(np.isnan(tile_0_2[1][0]))
self.assertTrue(np.isnan(tile_0_2[1][1]))
tile_1_2 = source_array_image.get_tile(1, 2).tolist()
self.assertEqual(tile_1_2[0], [2, 3])
self.assertTrue(tile_1_2[1][0])
self.assertTrue(tile_1_2[1][1])
tile_2_2 = source_array_image.get_tile(2, 2).tolist()
self.assertEqual(tile_2_2[0], [4, 5])
self.assertTrue(tile_2_2[1][0])
self.assertTrue(tile_2_2[1][1])