def test_add_multichannel_tiff(builtins, single_tiff):
image_files = single_tiff
viewer = ViewerModel()
viewer.open(image_files, channel_axis=0, plugin=builtins.name)
assert len(viewer.layers) == 2
assert viewer.dims.ndim == 2
assert isinstance(viewer.layers[0].data, np.ndarray)
assert viewer.layers[0].data.shape == (15, 10)
assert viewer.layers[0].data.dtype == np.uint8
def test_add_vectors():
"""Test adding vectors."""
viewer = ViewerModel()
np.random.seed(0)
data = 20 * np.random.random((10, 2, 2))
viewer.add_vectors(data)
assert len(viewer.layers) == 1
assert np.all(viewer.layers[0].data == data)
assert viewer.dims.ndim == 2
def test_add_labels():
"""Test adding labels image."""
viewer = ViewerModel()
np.random.seed(0)
data = np.random.randint(20, size=(10, 15))
viewer.add_labels(data)
assert len(viewer.layers) == 1
assert np.all(viewer.layers[0].data == data)
assert viewer.dims.ndim == 2
def test_add_empty_points_on_top_of_image():
viewer = ViewerModel()
image = np.random.random((8, 64, 64))
# add_image always returns the corresponding layer
_ = viewer.add_image(image)
layer = viewer.add_points(ndim=3)
assert layer.ndim == 3
layer.add([5.0, 32.0, 61.0])
assert layer.data.shape == (1, 3)
def test_grid():
"Test grid_view"
viewer = ViewerModel()
np.random.seed(0)
# Add image
for i in range(6):
data = np.random.random((15, 15))
viewer.add_image(data)
assert not viewer.grid.enabled
assert viewer.grid.actual_shape(6) == (1, 1)
assert viewer.grid.stride == 1
translations = [layer.translate_grid for layer in viewer.layers]
expected_translations = np.zeros((6, 2))
np.testing.assert_allclose(translations, expected_translations)
# enter grid view
viewer.grid.enabled = True
assert viewer.grid.enabled
assert viewer.grid.actual_shape(6) == (2, 3)
assert viewer.grid.stride == 1
translations = [layer.translate_grid for layer in viewer.layers]
expected_translations = [
[0, 0],
[0, 15],
[0, 30],
[15, 0],
[15, 15],
[15, 30],
]
np.testing.assert_allclose(translations, expected_translations[::-1])
# return to stack view
viewer.grid.enabled = False
assert not viewer.grid.enabled
assert viewer.grid.actual_shape(6) == (1, 1)
assert viewer.grid.stride == 1
translations = [layer.translate_grid for layer in viewer.layers]
expected_translations = np.zeros((6, 2))
np.testing.assert_allclose(translations, expected_translations)
# reenter grid view with new stride
viewer.grid.stride = -2
viewer.grid.enabled = True
assert viewer.grid.enabled
assert viewer.grid.actual_shape(6) == (2, 2)
assert viewer.grid.stride == -2
translations = [layer.translate_grid for layer in viewer.layers]
expected_translations = [
[0, 0],
[0, 0],
[0, 15],
[0, 15],
[15, 0],
[15, 0],
]
np.testing.assert_allclose(translations, expected_translations)
def test_add_volume():
"""Test adding volume."""
viewer = ViewerModel(ndisplay=3)
np.random.seed(0)
data = np.random.random((10, 15, 20))
viewer.add_image(data)
assert len(viewer.layers) == 1
assert np.all(viewer.layers[0].data == data)
assert viewer.dims.ndim == 3
def test_new_labels_empty():
"""Test adding new labels layer to empty viewer."""
viewer = ViewerModel()
viewer._new_labels()
assert len(viewer.layers) == 1
assert np.max(viewer.layers[0].data) == 0
assert viewer.dims.ndim == 2
# Default shape when no data is present is 512x512
np.testing.assert_equal(viewer.layers[0].data.shape, (512, 512))
def test_new_shapes():
"""Test adding new shapes layer."""
# Add labels to empty viewer
viewer = ViewerModel()
viewer.add_shapes()
assert len(viewer.layers) == 1
assert len(viewer.layers[0].data) == 0
assert viewer.dims.ndim == 2
# Add points with image already present
viewer = ViewerModel()
np.random.seed(0)
data = np.random.random((10, 15))
viewer.add_image(data)
viewer.add_shapes()
assert len(viewer.layers) == 2
assert len(viewer.layers[1].data) == 0
assert viewer.dims.ndim == 2
def test_add_pyramid():
"""Test adding image pyramid."""
viewer = ViewerModel()
shapes = [(40, 20), (20, 10), (10, 5)]
np.random.seed(0)
data = [np.random.random(s) for s in shapes]
viewer.add_pyramid(data)
assert len(viewer.layers) == 1
assert np.all(viewer.layers[0].data == data)
def test_add_single_filename(builtins, single_tiff):
image_files = single_tiff[0]
viewer = ViewerModel()
viewer.open(image_files, plugin=builtins.name)
assert len(viewer.layers) == 1
assert viewer.dims.ndim == 3
assert isinstance(viewer.layers[0].data, np.ndarray)
assert viewer.layers[0].data.shape == (2, 15, 10)
assert viewer.layers[0].data.dtype == np.uint8
def test_add_many_tiffs(builtins, single_tiff):
image_files = single_tiff * 3
viewer = ViewerModel()
viewer.open(image_files, stack=True, plugin=builtins.name)
assert len(viewer.layers) == 1
assert viewer.dims.ndim == 4
assert isinstance(viewer.layers[0].data, da.Array)
assert viewer.layers[0].data.shape == (3, 2, 15, 10)
assert viewer.layers[0].data.dtype == np.uint8
def test_no_warning_non_affine_slicing():
"""Test no warning if not slicing into an affine."""
viewer = ViewerModel()
np.random.seed(0)
data = np.random.random((10, 10, 10))
viewer.add_image(data, scale=[2, 1, 1], translate=[10, 15, 20])
with pytest.warns(None) as recorded_warnings:
viewer.layers[0].refresh()
assert len(recorded_warnings) == 0
def test_multichannel(shape, kwargs):
"""Test adding multichannel image."""
viewer = ViewerModel()
np.random.seed(0)
data = np.random.random(shape or (15, 10, 5))
channel_axis = kwargs.pop('channel_axis', -1)
viewer.add_image(data, channel_axis=channel_axis, **kwargs)
# make sure the right number of layers got added
n_channels = data.shape[channel_axis]
assert len(viewer.layers) == n_channels
for i in range(n_channels):
# make sure that the data has been divided into layers
assert np.all(viewer.layers[i].data == data.take(i, axis=channel_axis))
# make sure colors have been assigned properly
if 'colormap' not in kwargs:
if n_channels == 1:
assert viewer.layers[i].colormap.name == 'gray'
elif n_channels == 2:
assert viewer.layers[i].colormap.name == two_colormaps[i]
else:
assert viewer.layers[i].colormap.name == base_colormaps[i]
if 'blending' not in kwargs:
assert (viewer.layers[i].blending == 'translucent_no_depth'
if i == 0 else 'additive')
for key, expectation in kwargs.items():
# broadcast exceptions
if key in {
'scale',
'translate',
'rotate',
'shear',
'contrast_limits',
'metadata',
'experimental_clipping_planes',
}:
expectation = ensure_sequence_of_iterables(expectation,
repeat_empty=True)
elif key == 'colormap' and expectation is not None:
if isinstance(expectation, list):
exp = [ensure_colormap(c).name for c in expectation]
else:
exp = ensure_colormap(expectation).name
expectation = ensure_iterable(exp)
else:
expectation = ensure_iterable(expectation)
expectation = [v for i, v in zip(range(i + 1), expectation)]
result = getattr(viewer.layers[i], key)
if key == 'colormap': # colormaps are tuples of (name, cmap)
result = result.name
if isinstance(result, np.ndarray):
np.testing.assert_almost_equal(result, expectation[i])
else:
assert result == expectation[i]
def test_names():
"""Test adding multichannel image with custom names."""
viewer = ViewerModel()
np.random.seed(0)
data = np.random.random((15, 10, 5))
names = ['multi ' + str(i + 3) for i in range(data.shape[-1])]
viewer.add_multichannel(data, name=names)
assert len(viewer.layers) == data.shape[-1]
for i in range(data.shape[-1]):
assert viewer.layers[i].name == names[i]
viewer = ViewerModel()
name = 'example'
names = [name
] + [name + ' ' + str(i + 1) for i in range(data.shape[-1] - 1)]
viewer.add_multichannel(data, name=name)
assert len(viewer.layers) == data.shape[-1]
for i in range(data.shape[-1]):
assert viewer.layers[i].name == names[i]
def test_add_multiscale():
"""Test adding image multiscale."""
viewer = ViewerModel()
shapes = [(40, 20), (20, 10), (10, 5)]
np.random.seed(0)
data = [np.random.random(s) for s in shapes]
viewer.add_image(data, multiscale=True)
assert len(viewer.layers) == 1
assert np.all(viewer.layers[0].data == data)
assert viewer.dims.ndim == 2
def test_add_layer_from_data(data):
# make sure adding valid layer data calls the proper corresponding add_*
# method for all layer types
viewer = ViewerModel()
viewer._add_layer_from_data(*data)
# make sure a layer of the correct type got added
assert len(viewer.layers) == 1
expected_layer_type = data[2] if len(data) > 2 else 'image'
assert viewer.layers[0]._type_string == expected_layer_type
def view(qtbot):
"""basic viewer with data that we will use a few times"""
viewer = ViewerModel()
view = QtViewer(viewer)
qtbot.addWidget(view)
np.random.seed(0)
data = np.random.random((10, 10, 15))
viewer.add_image(data)
return view
def test_multichannel_dask_array():
"""Test adding multichannel dask array."""
viewer = ViewerModel()
np.random.seed(0)
data = da.random.random((2, 10, 10, 5))
viewer.add_image(data, channel_axis=0)
assert len(viewer.layers) == data.shape[0]
for i in range(data.shape[0]):
assert viewer.layers[i].data.shape == data.shape[1:]
assert isinstance(viewer.layers[i].data, da.Array)
def test_open_or_get_error_preferred_fails(tmp_path):
viewer = ViewerModel()
pth = tmp_path / 'my-file.npy'
with restore_settings_on_exit():
get_settings().plugins.extension2reader = {'.npy': 'napari'}
with pytest.raises(ReaderPluginError,
match='Tried opening with napari, but failed.'):
viewer._open_or_raise_error([str(pth)])
def test_open_labels(suffix):
viewer = ViewerModel()
blobs = binary_blobs(length=128, volume_fraction=0.1, n_dim=2)
labeled = ndi.label(blobs)[0].astype(np.uint8)
with temporary_file(suffix) as fout:
imwrite(fout, labeled, format=suffix)
viewer.open(fout, layer_type='labels')
assert len(viewer.layers) == 1
assert np.all(labeled == viewer.layers[0].data)
assert isinstance(viewer.layers[0], Labels)
def test_open_or_get_error_multiple_readers(mock_npe2_pm, tmp_reader):
"""Assert error is returned when multiple plugins are available to read."""
viewer = ViewerModel()
tmp_reader(mock_npe2_pm, 'p1')
tmp_reader(mock_npe2_pm, 'p2')
with pytest.raises(MultipleReaderError,
match='Multiple plugins found capable'):
viewer._open_or_raise_error(['my_file.fake'])
def test_split_rgb_image():
"""Test adding multichannel image with custom colormaps."""
viewer = ViewerModel()
np.random.seed(0)
data = np.random.random((15, 10, 3))
colormaps = ['red', 'green', 'blue']
viewer.add_image(data, colormap=colormaps, channel_axis=-1)
assert len(viewer.layers) == data.shape[-1]
for i in range(data.shape[-1]):
assert viewer.layers[i].colormap[0] == colormaps[i]
def test_multichannel():
"""Test adding multichannel image."""
viewer = ViewerModel()
np.random.seed(0)
data = np.random.random((15, 10, 5))
viewer.add_image(data, channel_axis=-1)
assert len(viewer.layers) == data.shape[-1]
for i in range(data.shape[-1]):
assert np.all(viewer.layers[i].data == data.take(i, axis=-1))
assert viewer.layers[i].colormap[0] == base_colormaps[i]
def test_rgb_images():
"""Test adding multiple rgb images."""
viewer = ViewerModel()
np.random.seed(0)
data = np.random.random((15, 10, 5, 3))
viewer.add_image(data, channel_axis=2, rgb=True)
assert len(viewer.layers) == data.shape[2]
for i in range(data.shape[-1]):
assert viewer.layers[i].rgb is True
assert viewer.layers[i]._data_view.ndim == 3
def test_add_multi_png_defaults(two_pngs):
image_files = two_pngs
viewer = ViewerModel()
viewer.open(image_files, stack=True, plugin='builtins')
assert len(viewer.layers) == 1
assert viewer.dims.ndim == 3
assert isinstance(viewer.layers[0].data, da.Array)
assert viewer.layers[0].data.shape == (2, 512, 512)
viewer.open(image_files, stack=False, plugin='builtins')
assert len(viewer.layers) == 3
def test_update_scale():
viewer = ViewerModel()
np.random.seed(0)
shape = (10, 15, 20)
data = np.random.random(shape)
viewer.add_image(data)
assert viewer.dims.range == tuple((0.0, x - 1.0, 1.0) for x in shape)
scale = (3.0, 2.0, 1.0)
viewer.layers[0].scale = scale
assert viewer.dims.range == tuple(
(0.0, (x - 1) * s, s) for x, s in zip(shape, scale))
def test_active_layer_status_update():
"""Test status updates from active layer on cursor move."""
viewer = ViewerModel()
np.random.seed(0)
viewer.add_image(np.random.random((5, 5, 10, 15)))
viewer.add_image(np.random.random((5, 6, 5, 10, 15)))
assert len(viewer.layers) == 2
assert viewer.active_layer == viewer.layers[1]
viewer.cursor.position = [1, 1, 1, 1, 1]
assert viewer.status == viewer.active_layer.status
def test_add_zarr():
viewer = ViewerModel()
image = np.random.random((10, 20, 20))
with TemporaryDirectory(suffix='.zarr') as fout:
z = zarr.open(fout, 'a', shape=image.shape)
z[:] = image
viewer.add_image(path=[fout])
assert len(viewer.layers) == 1
# Note: due to lazy loading, the next line needs to happen within
# the context manager. Alternatively, we could convert to NumPy here.
np.testing.assert_array_equal(image, viewer.layers[0].data)
def test_multichannel_index_error_hint():
"""Test multichannel error when arg length != n_channels."""
viewer = ViewerModel()
np.random.seed(0)
data = da.random.random((5, 10, 5))
with pytest.raises(IndexError) as e:
viewer.add_image(data, channel_axis=0, name=['a', 'b'])
assert (
"Requested channel_axis (0) had length 5, but the "
"'name' argument only provided 2 values." in str(e)
)
def test_add_zarr_1d_array_is_ignored():
# For more details: https://github.com/napari/napari/issues/1471
viewer = ViewerModel()
with TemporaryDirectory(suffix='.zarr') as zarr_dir:
z = zarr.open(zarr_dir, 'w')
z['1d'] = np.zeros(3)
image_path = os.path.join(zarr_dir, '1d')
viewer.open(image_path, plugin='builtins')
assert len(viewer.layers) == 0
