Exemple #1
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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])
Exemple #2
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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
Exemple #3
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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
Exemple #4
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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
Exemple #5
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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]