def test_ndim_paint(): test_array = np.zeros((5, 6, 7, 8), dtype=int) layer = Labels(test_array) layer.n_edit_dimensions = 3 with pytest.warns(FutureWarning): layer.brush_shape = 'circle' layer.brush_size = 2 # equivalent to 18-connected 3D neighborhood layer.paint((1, 1, 1, 1), 1) assert np.sum(layer.data) == 19 # 18 + center assert not np.any(layer.data[0]) and not np.any(layer.data[2:]) layer.n_edit_dimensions = 2 # 3x3 square layer._dims_order = [1, 2, 0, 3] layer.paint((4, 5, 6, 7), 8) assert len(np.flatnonzero(layer.data == 8)) == 4 # 2D square is in corner np.testing.assert_array_equal( test_array[:, 5, 6, :], np.array([ [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 8, 8], [0, 0, 0, 0, 0, 0, 8, 8], ]), )
def test_undo_redo( brush_shape, brush_size, mode, selected_label, preserve_labels, n_dimensional, ): blobs = data.binary_blobs(length=64, volume_fraction=0.3, n_dim=3) layer = Labels(blobs) data_history = [blobs.copy()] with pytest.warns(FutureWarning): layer.brush_shape = brush_shape layer.brush_size = brush_size layer.mode = mode layer.selected_label = selected_label layer.preserve_labels = preserve_labels layer.n_edit_dimensions = 3 if n_dimensional else 2 coord = np.random.random((3, )) * (np.array(blobs.shape) - 1) while layer.data[tuple(coord.astype(int))] == 0 and np.any(layer.data): coord = np.random.random((3, )) * (np.array(blobs.shape) - 1) if layer.mode == 'fill': layer.fill(coord, layer.selected_label) if layer.mode == 'erase': layer.paint(coord, 0) if layer.mode == 'paint': layer.paint(coord, layer.selected_label) data_history.append(np.copy(layer.data)) layer.undo() np.testing.assert_array_equal(layer.data, data_history[0]) layer.redo() np.testing.assert_array_equal(layer.data, data_history[1])
def test_paint_2d(): """Test painting labels with circle brush.""" data = np.zeros((40, 40), dtype=np.uint32) layer = Labels(data) layer.brush_size = 12 layer.mode = 'paint' layer.paint((0, 0), 3) layer.brush_size = 12 layer.paint((15, 8), 4) layer.brush_size = 13 layer.paint((30.2, 7.8), 5) layer.brush_size = 12 layer.paint((39, 39), 6) layer.brush_size = 20 layer.paint((15, 27), 7) assert np.sum(layer.data[:8, :8] == 3) == 41 assert np.sum(layer.data[9:22, 2:15] == 4) == 137 assert np.sum(layer.data[24:37, 2:15] == 5) == 137 assert np.sum(layer.data[33:, 33:] == 6) == 41 assert np.sum(layer.data[5:26, 17:38] == 7) == 349
def test_paint_2d(brush_shape, expected_sum): """Test painting labels with circle/square brush.""" data = np.zeros((40, 40)) layer = Labels(data) layer.brush_size = 12 layer.brush_shape = brush_shape layer.mode = 'paint' layer.paint((0, 0), 3) layer.brush_size = 12 layer.paint((15, 8), 4) layer.brush_size = 13 layer.paint((30.2, 7.8), 5) layer.brush_size = 12 layer.paint((39, 39), 6) layer.brush_size = 20 layer.paint((15, 27), 7) assert np.sum(layer.data[:8, :8] == 3) == expected_sum[0] assert np.sum(layer.data[9:22, 2:15] == 4) == expected_sum[1] assert np.sum(layer.data[24:37, 2:15] == 5) == expected_sum[2] assert np.sum(layer.data[33:, 33:] == 6) == expected_sum[3] assert np.sum(layer.data[5:26, 17:38] == 7) == expected_sum[4]
class Labels2DSuite: """Benchmarks for the Labels layer with 2D data""" params = [2**i for i in range(4, 13)] def setup(self, n): np.random.seed(0) self.data = np.random.randint(20, size=(n, n)) self.layer = Labels(self.data) def time_create_layer(self, n): """Time to create layer.""" Labels(self.data) def time_set_view_slice(self, n): """Time to set view slice.""" self.layer._set_view_slice() def time_refresh(self, n): """Time to refresh view.""" self.layer.refresh() def time_update_thumbnail(self, n): """Time to update thumbnail.""" self.layer._update_thumbnail() def time_get_value(self, n): """Time to get current value.""" self.layer.get_value((0, ) * 2) def time_raw_to_displayed(self, n): """Time to convert raw to displayed.""" self.layer._raw_to_displayed(self.layer._data_raw) def time_paint_square(self, n): """Time to paint square.""" self.layer.brush_shape = 'square' self.layer.paint((0, ) * 2, self.layer.selected_label) def time_paint_circle(self, n): """Time to paint circle.""" self.layer.brush_shape = 'circle' self.layer.paint((0, ) * 2, self.layer.selected_label) def time_fill(self, n): """Time to fill.""" self.layer.fill( (0, ) * 2, 1, self.layer.selected_label, ) def mem_layer(self, n): """Memory used by layer.""" return self.layer def mem_data(self, n): """Memory used by raw data.""" return self.data
class Labels3DSuite: """Benchmarks for the Labels layer with 3D data.""" params = [2**i for i in range(4, 11)] def setup(self, n): np.random.seed(0) self.data = np.random.randint(20, size=(n, n, n)) self.layer = Labels(self.data) def time_create_layer(self, n): """Time to create layer.""" Labels(self.data) def time_set_view_slice(self, n): """Time to set view slice.""" self.layer._set_view_slice() def time_refresh(self, n): """Time to refresh view.""" self.layer.refresh() def time_update_thumbnail(self, n): """Time to update thumbnail.""" self.layer._update_thumbnail() def time_get_value(self, n): """Time to get current value.""" self.layer.get_value() def time_save_history(self, n): """Time to save history.""" self.layer._save_history() def time_raw_to_displayed(self, n): """Time to convert raw to displayed.""" self.layer._raw_to_displayed(self.layer._data_raw) def time_paint(self, n): """Time to paint.""" self.layer.paint(self.layer.coordinates, self.layer.selected_label) def time_fill(self, n): """Time to fill.""" self.layer.fill( self.layer.coordinates, self.layer._value, self.layer.selected_label, ) def mem_layer(self, n): """Memory used by layer.""" return self.layer def mem_data(self, n): """Memory used by raw data.""" return self.data
class Labels3DSuite: """Benchmarks for the Labels layer with 3D data.""" params = [2**i for i in range(4, 11)] def setup(self, n): if "CI" in os.environ and n > 512: raise NotImplementedError("Skip on CI (not enough memory)") np.random.seed(0) self.data = np.random.randint(20, size=(n, n, n)) self.layer = Labels(self.data) def time_create_layer(self, n): """Time to create layer.""" Labels(self.data) def time_set_view_slice(self, n): """Time to set view slice.""" self.layer._set_view_slice() def time_refresh(self, n): """Time to refresh view.""" self.layer.refresh() def time_update_thumbnail(self, n): """Time to update thumbnail.""" self.layer._update_thumbnail() def time_get_value(self, n): """Time to get current value.""" self.layer.get_value((0, ) * 3) def time_raw_to_displayed(self, n): """Time to convert raw to displayed.""" self.layer._raw_to_displayed(self.layer._slice.image.raw) def time_paint_circle(self, n): """Time to paint circle.""" self.layer.paint((0, ) * 3, self.layer.selected_label) def time_fill(self, n): """Time to fill.""" self.layer.fill( (0, ) * 3, 1, self.layer.selected_label, ) def mem_layer(self, n): """Memory used by layer.""" return self.layer def mem_data(self, n): """Memory used by raw data.""" return self.data
def test_paint_2d_xarray(): """Test the memory usage of painting an xarray indirectly via timeout.""" data = xr.DataArray(np.zeros((3, 3, 1024, 1024), dtype=np.uint32)) layer = Labels(data) layer.brush_size = 12 layer.mode = 'paint' layer.paint((1, 1, 512, 512), 3) assert isinstance(layer.data, xr.DataArray) assert layer.data.sum() == 411
def test_paint_3d_negative_scale(scale): labels = np.zeros((3, 5, 11, 11), dtype=int) labels_layer = Labels(labels, scale=(1, ) + scale, translate=(-200, 100, 100)) labels_layer.n_edit_dimensions = 3 labels_layer.brush_size = 8 labels_layer.paint((1, 2, 5, 5), 1) np.testing.assert_array_equal(np.sum(labels_layer.data, axis=(1, 2, 3)), [0, 95, 0])
def test_negative_label(): """Test negative label values are supported.""" data = np.random.randint(low=-1, high=20, size=(10, 10)) original_data = np.copy(data) layer = Labels(data) layer.selected_label = -1 layer.brush_size = 3 layer.paint((5, 5), -1) assert np.count_nonzero(layer.data == -1) > np.count_nonzero( original_data == -1)
def test_paint_2d_xarray(brush_shape, expected_sum): """Test the memory usage of painting an xarray indirectly via timeout.""" data = xr.DataArray(np.zeros((3, 3, 1024, 1024), dtype=np.uint32)) layer = Labels(data) layer.brush_size = 12 with pytest.warns(FutureWarning): layer.brush_shape = brush_shape layer.mode = 'paint' layer.paint((1, 1, 512, 512), 3) assert isinstance(layer.data, xr.DataArray) assert layer.data.sum() == expected_sum
def test_paint_2d_xarray(): """Test the memory usage of painting an xarray indirectly via timeout.""" now = time.monotonic() data = xr.DataArray(np.zeros((3, 3, 1024, 1024), dtype=np.uint32)) layer = Labels(data) layer.brush_size = 12 layer.mode = 'paint' layer.paint((1, 1, 512, 512), 3) assert isinstance(layer.data, xr.DataArray) assert layer.data.sum() == 411 elapsed = time.monotonic() - now assert elapsed < 1, "test was too slow, computation was likely not lazy"
def test_paint_with_preserve_labels(): """Test painting labels while preserving existing labels""" data = np.zeros((15, 10)) data[:3, :3] = 1 layer = Labels(data) layer.preserve_labels = True assert np.unique(layer.data[:3, :3]) == 1 layer.brush_size = 9 layer.paint([0, 0], 2) assert np.unique(layer.data[3:5, 0:5]) == 2 assert np.unique(layer.data[0:5, 3:5]) == 2 assert np.unique(layer.data[:3, :3]) == 1
def test_paint_with_preserve_labels(): """Test painting labels with square brush while preserving existing labels.""" data = np.zeros((15, 10), dtype=np.uint32) data[:3, :3] = 1 layer = Labels(data) with pytest.warns(FutureWarning): layer.brush_shape = 'square' layer.preserve_labels = True assert np.unique(layer.data[:3, :3]) == 1 layer.brush_size = 9 layer.paint([0, 0], 2) assert np.unique(layer.data[3:5, 0:5]) == 2 assert np.unique(layer.data[0:5, 3:5]) == 2 assert np.unique(layer.data[:3, :3]) == 1
def test_paint(): """Test painting labels with different brush sizes.""" np.random.seed(0) data = np.random.randint(20, size=(10, 15)) data[:10, :10] = 1 layer = Labels(data) assert np.unique(layer.data[:5, :5]) == 1 assert np.unique(layer.data[5:10, 5:10]) == 1 layer.brush_size = 10 layer.paint([0, 0], 2) assert np.unique(layer.data[:5, :5]) == 2 assert np.unique(layer.data[5:10, 5:10]) == 1 layer.brush_size = 20 layer.paint([0, 0], 2) assert np.unique(layer.data[:5, :5]) == 2 assert np.unique(layer.data[5:10, 5:10]) == 2
def test_paint(): """Test painting labels with different circle brush sizes.""" np.random.seed(0) data = np.random.randint(20, size=(10, 15)) data[:10, :10] = 1 layer = Labels(data) assert np.unique(layer.data[:5, :5]) == 1 assert np.unique(layer.data[5:10, 5:10]) == 1 layer.brush_size = 9 layer.paint([0, 0], 2) assert np.unique(layer.data[:4, :4]) == 2 assert np.unique(layer.data[5:10, 5:10]) == 1 layer.brush_size = 10 layer.paint([0, 0], 2) assert np.unique(layer.data[0:6, 0:3]) == 2 assert np.unique(layer.data[0:3, 0:6]) == 2 assert np.unique(layer.data[6:10, 6:10]) == 1 layer.brush_size = 19 layer.paint([0, 0], 2) assert np.unique(layer.data[0:4, 0:10]) == 2 assert np.unique(layer.data[0:10, 0:4]) == 2 assert np.unique(layer.data[3:7, 3:7]) == 2 assert np.unique(layer.data[7:10, 7:10]) == 1
def test_paint(): """Test painting labels with different square brush sizes.""" np.random.seed(0) data = np.random.randint(20, size=(10, 15)) data[:10, :10] = 1 layer = Labels(data) with pytest.warns(FutureWarning): layer.brush_shape = 'square' assert np.unique(layer.data[:5, :5]) == 1 assert np.unique(layer.data[5:10, 5:10]) == 1 layer.brush_size = 9 layer.paint([0, 0], 2) assert np.unique(layer.data[:5, :5]) == 2 assert np.unique(layer.data[5:10, 5:10]) == 1 layer.brush_size = 10 layer.paint([0, 0], 2) assert np.unique(layer.data[:6, :6]) == 2 assert np.unique(layer.data[6:10, 6:10]) == 1 layer.brush_size = 19 layer.paint([0, 0], 2) assert np.unique(layer.data[:5, :5]) == 2 assert np.unique(layer.data[5:10, 5:10]) == 2
def test_paint_3d(): """Test painting labels with circle brush on 3D image.""" data = np.zeros((30, 40, 40), dtype=np.uint32) layer = Labels(data) layer.brush_size = 12 layer.mode = 'paint' # Paint in 2D layer.paint((10, 10, 10), 3) # Paint in 3D layer.n_edit_dimensions = 3 layer.paint((10, 25, 10), 4) # Paint in 3D, preserve labels layer.n_edit_dimensions = 3 layer.preserve_labels = True layer.paint((10, 15, 15), 5) assert np.sum(layer.data[4:17, 4:17, 4:17] == 3) == 137 assert np.sum(layer.data[4:17, 19:32, 4:17] == 4) == 1189 assert np.sum(layer.data[4:17, 9:32, 9:32] == 5) == 1103
def test_paint_3d(brush_shape, expected_sum): """Test painting labels with circle/square brush on 3D image.""" data = np.zeros((30, 40, 40)) layer = Labels(data) layer.brush_size = 12 layer.brush_shape = brush_shape layer.mode = 'paint' # Paint in 2D layer.paint((10, 10, 10), 3) # Paint in 3D layer.n_dimensional = True layer.paint((10, 25, 10), 4) # Paint in 3D, preserve labels layer.n_dimensional = True layer.preserve_labels = True layer.paint((10, 15, 15), 5) assert np.sum(layer.data[4:17, 4:17, 4:17] == 3) == expected_sum[0] assert np.sum(layer.data[4:17, 19:32, 4:17] == 4) == expected_sum[1] assert np.sum(layer.data[4:17, 9:32, 9:32] == 5) == expected_sum[2]