def test_eq():
camera = pyvista.Camera()
other = pyvista.Camera()
for camera_now in camera, other:
for name, value, _ in configuration:
setattr(camera_now, name, value)
assert camera == other
# check that changing anything will break equality
for name, value, _ in configuration:
original_value = getattr(other, name)
if isinstance(value, bool):
changed_value = not value
elif isinstance(value, (int, float)):
changed_value = 0
elif isinstance(value, tuple):
changed_value = (0.5, 0.5, 0.5)
else:
changed_value = -value
setattr(other, name, changed_value)
assert camera != other
setattr(other, name, original_value)
# sanity check that we managed to restore the original state
assert camera == other
def test_copy():
camera = pyvista.Camera()
for name, value, _ in configuration:
setattr(camera, name, value)
deep = camera.copy()
assert deep == camera
def test_camera():
camera = pyvista.Camera()
position = np.random.random(3)
camera.position = position
assert np.all(camera.GetPosition() == position)
assert np.all(camera.position == position)
focal_point = np.random.random(3)
camera.focal_point = focal_point
assert np.all(camera.GetFocalPoint() == focal_point)
assert np.all(camera.focal_point == focal_point)
model_transform_matrix = np.random.random((4, 4))
camera.model_transform_matrix = model_transform_matrix
assert np.all(camera.model_transform_matrix == model_transform_matrix)
camera.distance == np.linalg.norm(focal_point - position, ord=2)
thickness = np.random.random(1)
camera.thickness = thickness
assert camera.thickness == thickness
parallel_scale = np.random.random(1)
camera.parallel_scale = parallel_scale
assert camera.parallel_scale == parallel_scale
value = np.random.random(1)
camera.zoom(value)
vector = np.random.random(3)
camera.up(vector)
camera.up()
camera.enable_parallel_projection()
assert camera.GetParallelProjection()
assert camera.is_parallel_projection
camera.disable_parallel_projection()
assert not camera.GetParallelProjection()
assert not camera.is_parallel_projection
near_point = np.random.random(1)
far_point = near_point + np.random.random(1)
points = (near_point, far_point)
camera.clipping_range = points
assert camera.GetClippingRange() == points
assert camera.clipping_range == points
with pytest.raises(ValueError):
far_point = near_point - np.random.random(1)
points = (near_point, far_point)
camera.clipping_range = points
tm_vis = pv.make_tri_mesh(shape_model.V, shape_model.F)
tm_vis.cell_arrays['vis'] = vis
# ... and one with their difference.
tm_vis_diff = pv.make_tri_mesh(shape_model.V, shape_model.F)
tm_vis_diff.cell_arrays['diff'] = vis_f - vis
# The keyword argument "shape=(1, 3)" indicates that we'll have a
# row with three columns of subplots.
# plotter = pvqt.BackgroundPlotter(window_size=(900, 400), shape=(1, 3))
plotter = pv.Plotter(window_size=(900, 400), shape=(1, 3))
# We want to use the same camera for each plot. We set it up here.
V_ptp = shape_model.V.ptp(0)
V_mean = shape_model.V.mean(0)
camera = pv.Camera()
camera.position = V_mean + np.array([0, 0, 2.2 * V_ptp[:2].mean()])
camera.focal_point = V_mean
camera.up = np.array([1, 0, 0])
plotter.subplot(0, 0)
plotter.add_text(f'From form factor matrix (eps = {eps_f})', font_size=12)
plotter.add_mesh(tm_vis_f, lighting=False, cmap=cc.cm.fire)
plotter.camera = camera
plotter.subplot(0, 1)
plotter.add_text(f'Raytracing (eps = {eps})', font_size=12)
plotter.add_mesh(tm_vis, lighting=False, cmap=cc.cm.fire)
plotter.camera = camera
plotter.subplot(0, 2)
def camera():
return pyvista.Camera()
def test_invalid_init():
with pytest.raises(TypeError):
pyvista.Camera(1)
