def test_screenshot(qtbot):
"Test taking a screenshot"
viewer = Viewer()
view = viewer.window.qt_viewer
qtbot.addWidget(view)
np.random.seed(0)
# Add image
data = np.random.random((10, 15))
viewer.add_image(data)
# Add labels
data = np.random.randint(20, size=(10, 15))
viewer.add_labels(data)
# Add points
data = 20 * np.random.random((10, 2))
viewer.add_points(data)
# Add vectors
data = 20 * np.random.random((10, 2, 2))
viewer.add_vectors(data)
# Add shapes
data = 20 * np.random.random((10, 4, 2))
viewer.add_shapes(data)
# Take screenshot
screenshot = viewer.screenshot()
assert screenshot.ndim == 3
# Close the viewer
viewer.window.close()
def test_nD_shapes(qtbot):
"""Test adding vectors."""
viewer = Viewer()
view = viewer.window.qt_viewer
qtbot.addWidget(view)
np.random.seed(0)
# create one random rectangle per "plane"
planes = np.tile(np.arange(10).reshape((10, 1, 1)), (1, 4, 1))
corners = np.random.uniform(0, 10, size=(10, 4, 2))
data = np.concatenate((planes, corners), axis=2)
viewer.add_shapes(data)
assert np.all(
[np.all(ld == d) for ld, d in zip(viewer.layers[0].data, data)]
)
assert len(viewer.layers) == 1
assert view.layers.vbox_layout.count() == 2 * len(viewer.layers) + 2
assert viewer.dims.ndim == 3
assert view.dims.nsliders == viewer.dims.ndim
assert np.sum(view.dims._displayed_sliders) == 1
# Flip dims order displayed
viewer.dims.order = [0, 2, 1]
assert viewer.dims.order == [0, 2, 1]
# Flip dims order including non-displayed
viewer.dims.order = [1, 0, 2]
assert viewer.dims.order == [1, 0, 2]
# Close the viewer
viewer.window.close()
def test_add_shapes(qtbot):
"""Test adding shapes."""
viewer = Viewer()
view = viewer.window.qt_viewer
qtbot.addWidget(view)
np.random.seed(0)
data = 20 * np.random.random((10, 4, 2))
viewer.add_shapes(data)
assert np.all(viewer.layers[0].data == data)
assert len(viewer.layers) == 1
assert view.layers.vbox_layout.count() == 2 * len(viewer.layers) + 2
assert viewer.dims.ndim == 2
assert view.dims.nsliders == viewer.dims.ndim
assert np.sum(view.dims._displayed_sliders) == 0
# Switch to 3D rendering mode and back to 2D rendering mode
viewer.dims.ndisplay = 3
assert viewer.dims.ndisplay == 3
viewer.dims.ndisplay = 2
assert viewer.dims.ndisplay == 2
# Close the viewer
viewer.window.close()
def __init__(
self,
viewer: Viewer,
im_shape: tuple,
cell_masks: list = [],
initial_state: Union[str, np.ndarray] = "good",
selection_layer_name: str = 'selected_cell',
accepted_layer_name: str = 'accepted_mask',
rejected_layer_name: str = 'rejected_mask',
mode: str = 'all',
):
self.selected_shapes = viewer.add_shapes(name=selection_layer_name)
self.initialize_masks(
viewer=viewer,
im_shape=im_shape,
cell_masks=cell_masks,
initial_state=initial_state,
accepted_layer_name=accepted_layer_name,
rejected_layer_name=rejected_layer_name,
)
viewer.bind_key("t", self.toggle_selected_mask)
self._mode = mode
def test_add_shapes(qtbot):
"""Test adding vectors."""
viewer = Viewer()
view = viewer.window.qt_viewer
qtbot.addWidget(view)
np.random.seed(0)
data = 20 * np.random.random((10, 4, 2))
viewer.add_shapes(data)
assert np.all(viewer.layers[0].data == data)
assert len(viewer.layers) == 1
assert view.layers.vbox_layout.count() == 2 * len(viewer.layers) + 2
assert viewer.dims.ndim == 2
assert view.dims.nsliders == 0
assert np.sum(view.dims._displayed) == 0
# Close the viewer
viewer.window.close()
def test_data_change_ndisplay_shapes(qtbot):
"""Test change data calls for shapes layer with ndisplay change."""
viewer = Viewer()
view = viewer.window.qt_viewer
qtbot.addWidget(view)
np.random.seed(0)
data = 20 * np.random.random((10, 4, 3))
layer = viewer.add_shapes(data)
visual = view.layer_to_visual[layer]
@patch.object(visual, '_on_data_change', wraps=visual._on_data_change)
def test_ndisplay_change(mocked_method, ndisplay=3):
viewer.dims.ndisplay = ndisplay
mocked_method.assert_called_once()
# Switch to 3D rendering mode and back to 2D rendering mode
test_ndisplay_change(ndisplay=3)
test_ndisplay_change(ndisplay=2)
# Close the viewer
viewer.window.close()
# add the timeseries
movie_layer = viewer.add_image(movie,
name='timeseries',
contrast_limits=(0.0, 600.0),
colormap='gray')
mean_layer = viewer.add_image(mean,
name='mean',
contrast_limits=(0.0, 600.0),
colormap='gray',
visible=False)
#
# lc_layer = viewer.add_image(localcorr, name='localcorr', contrast_limits=(0.35, 1.0), colormap='gray', visible=False)
#
# centers_layer = viewer.add_points(centers, name='centers', edge_width=0, face_color='green', visible=False, opacity=0.5)
#
shapes_layer = viewer.add_shapes(polygons,
shape_type='polygon',
edge_width=0,
face_color='green',
opacity=0.5,
name='neurons',
visible=False)
#
labels = label(mask)
labels_layer = viewer.add_labels(labels, name='rois')
# polygons_edit = shapes_layer.data
# np.save('data/neurofinder/polygons_edit.npy', polygons_edit)
base_cols = ['red', 'green', 'blue', 'white']
colors = [base_cols[i] for i in id]
with gui_qt():
# create an empty viewer
viewer = Viewer()
# add the images
layer = viewer.add_image(tiles, name=slide_name, clim_range=[0, 255])
# add borders
viewer.add_shapes(np.array(shapes),
shape_type='rectangle',
face_color=[0, 0, 0, 0],
edge_color=colors,
edge_width=border * 2,
opacity=0.75,
name='annotation')
viewer.layers.unselect_all()
@viewer.bind_key('c')
def cored(viewer):
"""Set the current annotation to cored
"""
msg = 'cored'
shapes = viewer.layers['annotation']
shapes._data_view.update_edge_color(0,
base_cols[annot_types.index(msg)])
shapes.refresh()
shape_1 = np.array([[float(c.attrib['X']),
float(c.attrib['Y'])] for c in root[0][0][0]])
shape_2 = np.array([[float(c.attrib['X']),
float(c.attrib['Y'])] for c in root[0][1][0]])
tumors = [shape_1, shape_2]
#print([p.shape[:2] for p in pyramid])
with gui_qt():
# create an empty viewer
viewer = Viewer()
# add the pyramid
#viewer.open(file_name, layer_type='image', name='slide', multiscale=True, scale=[10, 10], translate=[1000, 100])
#viewer.open(file_name, layer_type='image', name='slide', multiscale=True, scale=[10, 10])
viewer.open(file_name,
layer_type='image',
name='H&E stained lymph node',
multiscale=True)
layer = viewer.layers[0]
tumor_layer = viewer.add_shapes(tumors,
shape_type='polygon',
edge_width=50,
edge_color='blue',
face_color=[0, 0, 1, 0.5],
opacity=0.5,
name='Tumors')
def build_plugin_(viewer: Viewer) -> None:
"""
This part of the code sort of ended up as the controller for the plugin.
"""
# validate state
image_layers = [l for l in viewer.layers if isinstance(l, Image)]
if len(image_layers) < 1:
return
layer: Image = image_layers[0] # the image to visualize is the first
image: np.ndarray = layer.data
if image.ndim != 3:
return
if image.shape[2] <= 1:
return
n_channels = image.shape[2]
# set up dock widgets
topograph_pixels = _TopographPixels(n_channels)
topograph_cells = TopographCells()
viewer.window.add_dock_widget(
topograph_pixels.view, name="TopographPixels", area="right"
)
# viewer.window.add_dock_widget(topograph_cells, name='TopographCells', area='right')
init_rect = np.asarray([[0, 0], [0, 500], [500, 500], [500, 0]])
shapes_layer: Shapes = viewer.add_shapes(
[init_rect],
shape_type="rectangle",
name="Annotations",
ndim=2,
edge_color=[(1, 1, 1, 1)], # black
face_color=[(0, 0, 0, 0)], # clear
)
_shape: Optional[np.ndarray] = None
def update_plots():
# at least one rectangle
shapes: List[np.ndarray] = shapes_layer.data
shapes: List[np.ndarray] = [s for s in shapes if is_rectangle(s)]
if len(shapes) == 0:
return
# check if it's changed at all
shape: np.ndarray = shapes[0]
nonlocal _shape
if (shape == _shape).all():
return
_shape = np.copy(shape)
# get shape extents
ymin, ymax = shape[:, 0].min(), shape[:, 0].max()
ymin, ymax = int(round(ymin)), int(round(ymax))
# ymin, ymax = int(round(ymin)), int(round(ymax)) + 1
xmin, xmax = shape[:, 1].min(), shape[:, 1].max()
xmin, xmax = int(round(xmin)), int(round(xmax))
# xmin, xmax = int(round(xmin)), int(round(xmax)) + 1
# clip extents
ymin = min(max(ymin, 0), image.shape[0])
ymax = max(min(ymax, image.shape[0]), 0)
xmin = min(max(xmin, 0), image.shape[1])
xmax = max(min(xmax, image.shape[1]), 0)
# get desired region of image
region = image[ymin:ymax, xmin:xmax, :]
topograph_pixels.plotLayout.updatePlots(region)
def on_change(event: Event) -> None:
event_type = getattr(event, "type", None)
if event_type != "set_data":
return
update_plots()
shapes_layer.events.connect(on_change)
update_plots()
def build_plugin(viewer: Viewer) -> None:
# prepare viewer window
viewer.window.qt_viewer.layerButtons.deleteButton.setDisabled(True)
# add annotation layer with a single window
init_rect = np.asarray([[0, 0], [500, 0], [500, 500], [0, 500]])
annotation_layer: Shapes = viewer.add_shapes(
[init_rect],
shape_type="rectangle",
name="Annotations",
ndim=2,
edge_color=[(1, 1, 1, 1)],
face_color=[(0, 0, 0, 0)],
)
topograph_pixels = TopographPixels(viewer.layers)
dock_widget: QtViewerDockWidget = viewer.window.add_dock_widget(
topograph_pixels.view, name="TopographPixels", area="right"
)
viewer.window._qt_window.resizeDocks([dock_widget], [300], Qt.Horizontal)
# update annotation rectangle
_rect: Optional[np.ndarray] = None
def update_plots() -> None:
"""
Note that all coordinate values are in world coordinates; they correspond to
*microns*. It is the responsibility of whoever is interacting with the image to
convert these values from microns to pixels.
"""
# at least one rectangle
shapes: List[np.ndarray] = annotation_layer.data
rects: List[np.ndarray] = [s for s in shapes if is_rectangle(s)]
if len(rects) == 0:
return
# did rect change?
rect = rects[0]
nonlocal _rect
if (_rect == rect).all():
return
_rect = np.copy(rect)
# polygon to rectangle
ymin, ymax = rect[:, 0].min(), rect[:, 0].max()
ymin, ymax = int(round(ymin)), int(round(ymax)) + 1
xmin, xmax = rect[:, 1].min(), rect[:, 1].max()
xmin, xmax = int(round(xmin)), int(round(xmax)) + 1
topograph_pixels.update_plots(xmin, xmax, ymin, ymax)
@thread_worker
def run_update():
topograph_pixels.runButton.setDisabled(True)
topograph_pixels.runButton.setText("Running...")
update_plots()
topograph_pixels.runButton.setEnabled(True)
topograph_pixels.runButton.setText("Update")
def run():
worker = run_update()
worker.start()
topograph_pixels.runButton.clicked.connect(run)
# viewer.layers.events.moved.connect(update_plots)
#
# def on_change(event: Event) -> None:
# event_type = getattr(event, "type", None)
# if event_type != "set_data":
# return
#
# update_plots()
#
# annotation_layer.events.connect(on_change)
# updating edge width
_edge_width: Optional[float] = None
def update_edge_width() -> None:
edge_width = min(5 / viewer.camera.zoom, 200)
nonlocal _edge_width
if _edge_width == edge_width:
return
_edge_width = edge_width
# current_edge_width.setter from `shapes.py`
annotation_layer._current_edge_width = edge_width
for i in range(len(annotation_layer._data_view.shapes)):
annotation_layer._data_view.update_edge_width(i, edge_width)
annotation_layer.status = format_float(annotation_layer.current_edge_width)
annotation_layer.events.edge_width()
def on_camera_event(event: Event):
if event.type != "zoom":
return
update_edge_width()
viewer.camera.events.connect(on_camera_event)
update_edge_width()