def test_qt_properties_table():
# create a viewer with a points layer
points_data = np.random.random((10, 2))
points_properties = {'probability': np.random.random((10, ))}
layer_name = 'points_layer'
viewer = napari.view_points(points_data,
properties=points_properties,
name=layer_name)
properties_widget = QtPropertiesTable(viewer)
assert isinstance(properties_widget, QWidget)
assert properties_widget.selected_layer == layer_name
def viz_neurons_and_vasc(neuron_and_colls, vascular_data):
with napari.gui_qt():
viewer = napari.view_points(
vascular_data[:, :3],
size=vascular_data[:, 3],
face_color="magenta",
name="vasculature",
)
for (neuron, coll), neuron_name in zip(neuron_and_colls, neuron_names):
viewer.add_points(neuron.to_numpy(), size=3, name=f"{neuron_name}")
viewer.add_points(
coll.to_numpy(),
size=3,
face_color="g",
name=f"{len(coll)} collisions ({neuron_name})",
)
def test_view_points(qtbot):
"""Test adding points."""
np.random.seed(0)
data = 20 * np.random.random((10, 2))
viewer = napari.view_points(data)
view = viewer.window.qt_viewer
qtbot.addWidget(view)
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
# Close the viewer
viewer.window.close()
# neuron_obj_fname = '/data/neural_collision_detection/yoav/artificial_270120/neuron.obj'
surface = client.submit(create_napari_surface, neuron_obj_fname)
# colls_fname = "/data/neural_collision_detection/results/for_article/fig1/normalized_artificial_neuron_results_agg_thresh_0.npz"
# collisions = client.submit(load_collisions, colls_fname, 1, "neuron_coords")
# collisions = client.submit(filter_nans, collisions)
surface = surface.result()
# closest_idx = client.submit(connect_collisions_to_neural_points, collisions, surface[0])
# neural_collisions = client.submit(NeuronToGraph.coerce_collisions_to_neural_coords, surface[3], closest_idx)
# binsize = (1, 1, 1)
# hist_and_edges = gen_hist(collisions, binsize)
# hist_and_metadata = filter_relevant_bins(hist_and_edges)
# points_and_color = hist_into_points(hist_and_metadata)
# surface_with_collisions = client.submit(add_colls_data_to_surface, surface, neural_collisions)
# surface_with_collisions = surface_with_collisions.result()
# colors = np.zeros((len(surface_with_collisions[0]), 4))
# colors[:, 0] = 1.0
# colors[:, 3] = surface_with_collisions[2]
# colors = ColorArray(colors)
# colors = [color.rgba.ravel() for color in colors]
raw_neuron = pd.read_csv(
f"/data/neural_collision_detection/src/convert_obj_matlab/{neuron_name}_balls_yz_flipped.csv",
header=None,
names=["x", "y", "z", "r"],
)
with napari.gui_qt():
# viewer = napari.view_points(collisions.result()[::10], size=1, face_color='pink')
viewer = napari.view_points(raw_neuron.iloc[:, :3].to_numpy(),
size=1,
face_color="white")
viewer.add_surface(surface, colormap="magenta")
viewer.layers.selection.active.selected_data = []
def on_transform_changed_drag(event):
sel_i = viewer.layers.selection.active.selected_data
points = viewer.overlays.interaction_box.points
for i, index in enumerate(sel_i):
viewer.layers.selection.active._data[
index] = viewer.layers.selection.active.world_to_data(
event.value(points[i]))
viewer.layers.selection.active._update_dims()
viewer.layers.selection.active.events.data(
value=viewer.layers.selection.active.data)
X, Y = np.mgrid[-500:500:50, -500:500:50]
positions = np.dstack([X.ravel(), Y.ravel()])
viewer = napari.view_points(positions[0, :, :])
viewer.layers.selection.active.interactive = False
viewer.overlays.interaction_box.show = True
viewer.overlays.interaction_box.events.selection_box_drag.connect(
on_selection_box_drag)
viewer.overlays.interaction_box.events.selection_box_final.connect(
on_selection_box_final)
viewer.overlays.interaction_box.events.transform_drag.connect(
on_transform_changed_drag)
if __name__ == '__main__':
napari.run()
"""Add points on nD shapes in 3D using a mouse callback"""
import napari
import numpy as np
# Create rectangles in 4D
shapes_data = np.array([[[0, 50, 75, 75], [0, 50, 125, 75], [0, 100, 125, 125],
[0, 100, 75, 125]],
[[0, 10, 75, 75], [0, 10, 125, 75], [0, 40, 125, 125],
[0, 40, 75, 125]],
[[1, 100, 75, 75], [1, 100, 125, 75],
[1, 50, 125, 125], [1, 50, 75, 125]]])
# add an empty 4d points layer
viewer = napari.view_points(ndim=4, size=3)
points_layer = viewer.layers[0]
# add the shapes layer to the viewer
properties = {'index': [0, 1, 2]}
shapes_layer = viewer.add_shapes(shapes_data,
face_color=['magenta', 'green', 'blue'],
edge_color='white',
blending='additive',
properties=properties,
text='index')
@shapes_layer.mouse_drag_callbacks.append
def on_click(layer, event):
shape_index, intersection_point = layer.get_index_and_intersection(
event.position, event.view_direction, event.dims_displayed)
"""Test converting an image to a pyramid.
"""
import numpy as np
import napari
points = np.random.randint(100, size=(50_000, 2))
with napari.gui_qt():
viewer = napari.view_points(points, face_color='red')