def render(self): """ """ self.apply_render_style() # Create camera and plotter if brainrender.WHOLE_SCREEN: sz = "full" else: sz = "auto" if brainrender.SHOW_AXES: axes = 4 else: axes = 0 mv = Plotter(N=2, axes=axes, size=sz, pos=brainrender.WINDOW_POS, bg=brainrender.BACKGROUND_COLOR, sharecam=True) actors = [] for scene in self.scenes: scene_actors = scene.get_actors() actors.append(scene_actors) mv.add(scene_actors) mv.show(actors[0], at=0, zoom=1.15, axes=axes, roll=180, interactive=False) mv.show(actors[1], at=1, interactive=False) interactive()
def render(self, _interactive=True, **kwargs):
"""
:param _interactive: (Default value = True)
:param **kwargs:
"""
camera = kwargs.pop("camera", None)
for scene in self.scenes:
scene.apply_render_style()
if camera is None:
if scene.atlas.default_camera is None:
scene_camera = brainrender.CAMERA
else:
scene_camera = scene.atlas.default_camera
else:
if camera:
scene_camera = camera
else:
scene_camera = None
if scene_camera is not None:
set_camera(scene, scene_camera)
if self.N > 4:
print("Rendering {} scenes. Might take a few minutes.".format(self.N))
mv = Plotter(N=self.N, axes=4, size="auto", sharecam=True, bg=brainrender.BACKGROUND_COLOR)
actors = []
for i, scene in enumerate(self.scenes):
scene_actors = scene.get_actors()
actors.append(scene_actors)
mv.add(scene_actors)
for i, scene_actors in enumerate(actors):
mv.show(scene_actors, at=i, interactive=False)
print("Rendering complete")
if _interactive:
interactive()
r = 20
u[...] = 1.0
U[n//2-r:n//2+r, n//2-r:n//2+r] = 0.50
V[n//2-r:n//2+r, n//2-r:n//2+r] = 0.25
u += 0.05*np.random.uniform(-1, 1, (n, n))
v += 0.05*np.random.uniform(-1, 1, (n, n))
sy, sx = V.shape
grd = Grid(sx=sx, sy=sy, resx=sx, resy=sy)
grd.lineWidth(0).wireframe(False).lighting(ambient=0.5)
for step in range(Nsteps):
for i in range(20):
Lu = ( U[0:-2, 1:-1] +
U[1:-1, 0:-2] - 4*U[1:-1, 1:-1] + U[1:-1, 2:] +
U[2: , 1:-1])
Lv = ( V[0:-2, 1:-1] +
V[1:-1, 0:-2] - 4*V[1:-1, 1:-1] + V[1:-1, 2:] +
V[2: , 1:-1])
uvv = u*v*v
u += (Du*Lu - uvv + F*(1-u))
v += (Dv*Lv + uvv - (F+k)*v)
vvals = np.flip(V, axis=0).ravel()
grd.cellColors(vvals, cmap='ocean_r').mapCellsToPoints()
newpts = np.c_[grd.points()[:,[0,1]], grd.getPointArray('cellColors')*20]
grd.points(newpts).show(axes=9, zoom=1.3, elevation=-.15, interactive=False)
interactive()
def setCarPose(self, x, y, theta):
self.lexus.pos(x=x, y=y, z=0.0).orientation(newaxis=[0, 0, 1.0],
rotation=theta,
rad=True)
def show(self):
vplt.show(self.goal, *self.obstacles, self.lexus, interactive=0)
# camera={'pos':[0, 0, 10],
# 'focalPoint':[0, 0, 10],
# 'viewup':[0, 0, -1],
# 'distance':43.871,
# 'clippingRange':[33.465, 57.074]} )
def close(self):
vplt.closeWindow()
if __name__ == '__main__':
viewer = CarWithObstacles()
for x, y in [(1, 1), (1, -1), (-1, -1), (-1, 1)]:
viewer.addObstacle(x, y, 0.8)
N = 500
pose = np.array([2, 0, -np.pi])
step = (np.array([0, 0, 0]) - pose) / N
step[2] = 0
for k in range(N):
viewer.setCarPose(*(pose + k * step))
viewer.show()
vplt.interactive()
viewer.close()
def view_mesh(
meshes: list,
output_file: str,
mesh_names: list = [],
patient_data="",
plid="",
scan_path="",
):
logging.info("Opening mesh viewer.")
settings.useDepthPeeling = True
vmeshes = []
def slider1(widget, event):
value = widget.GetRepresentation().GetValue()
vmeshes[index].color(value)
def slider2(widget, event):
value = widget.GetRepresentation().GetValue()
vmeshes[index].opacity(value)
def buttonfunc():
global index
bu.switch()
index = mesh_names.index(bu.status())
def background_swap():
bg_button.switch()
vp.backgroundRenderer.SetBackground(colors.getColor(
bg_button.status()))
def ar_view():
save()
holo_registration_wrapper.start_viewer(output_file, plid)
def save():
write_mesh_as_glb_with_colour(vmeshes, output_file)
def open_scan():
external_2d_viewer.start(scan_path)
vp = Plotter(
sharecam=False,
bg="./core/client/images/hologram_icon2.png",
bg2='black',
shape=[1, 1],
size=[640, 480],
interactive=False,
)
# pos = position corner number: horizontal [1-4] or vertical [11-14]
vp.addSlider2D(slider1, -9, 9, value=0, pos=4, title="color number")
left_side_x = 0.1
vp.addSlider2D(
slider2,
xmin=0.00,
xmax=1.00,
value=0.5,
pos=14,
c="blue",
title="alpha value (opacity)",
)
bu = vp.addButton(
buttonfunc,
pos=(0.5, 0.05), # x,y fraction from bottom left corner
states=mesh_names,
font=font_style, # arial, courier, times
size=25,
bold=True,
italic=False,
)
save_button = vp.addButton(
save,
pos=(left_side_x, 0.05), # x,y fraction from bottom left corner
states=["Save"],
font=font_style, # arial, courier, times
size=25,
bold=True,
italic=False,
)
if holo_registration_wrapper.is_supported(plid):
ar_button = vp.addButton(
ar_view,
pos=(left_side_x, 0.20),
states=["AR View"],
font=font_style,
size=25,
bold=True,
italic=False,
)
if scan_path != "":
scan_button = vp.addButton(
open_scan,
pos=(left_side_x, 0.15),
states=["2D View"],
font=font_style,
size=25,
bold=True,
italic=False,
)
bg_button = vp.addButton(
background_swap,
pos=(left_side_x, 0.10), # x,y fraction from bottom left corner
states=["black", "white"],
font=font_style,
size=25,
bold=True,
italic=False,
)
for i in range(0, len(meshes)):
vmeshes.append(trimesh2vtk(meshes[i], alphaPerCell=True))
doc = Text2D(patient_data, pos=4, c=(0, 113, 197))
vp.show(doc)
vp.backgroundRenderer.GetActiveCamera().Zoom(1.3)
vp.show(vmeshes)
interactive()