def __init__(self, env, grid_size=64, occlusion_reward=False):
super().__init__(env)
self.grid_shape = ((grid_size, grid_size, grid_size))
self.observation_space = spaces.Box(0, 1, self.grid_shape, dtype=bool)
self.builder = VoxelGridBuilder(grid_size)
self.mesh_grid = None
self.gt_size = None
self.bounds = None
self.plot = k3d.plot(name='wrapper')
def points(plot_array, point_size=0.1, color=0x99bbff, plot=None, **kwargs):
plot_array = plot_array.astype(np.float32) # to avoid k3d warning
if plot is None:
plot = k3d.plot()
plot.display()
plot += k3d.points(plot_array,
point_size=point_size,
color=color,
**kwargs)
return plot
def new_plot(self, bs=1.0):
points_number = 1
positions = 50 * np.random.random_sample((points_number, 3)) - 25
colors = np.random.randint(0, 0x777777, points_number)
self.plot = k3d.plot()
self.pkts = k3d.points(positions, colors, point_size=.3)
self.plot += self.pkts
self.plot.camera_auto_fit = False
self.plot.grid_auto_fit = False
self.box = k3d.line(self.box_coords(bs=bs))
self.plot += self.box
def init_plot(self):
plot = k3d.plot(height=self.height)
self.meshes = []
for (corner, sizes), color in zip(iter_corner_sizes(self.L, self.D),
palette):
mesh = Box(corner=corner, sizes=sizes).mesh
mesh.color = color
plot += mesh
# set aside for updates
self.meshes.append(mesh)
self.plot = plot
# return the plot so it gets displayed
return self.plot
def visualize_mesh(vertices, faces, flip_axes=False):
plot = k3d.plot(name='points',
grid_visible=False,
grid=(-0.55, -0.55, -0.55, 0.55, 0.55, 0.55))
if flip_axes:
vertices[:, 2] = vertices[:, 2] * -1
vertices[:, [0, 1, 2]] = vertices[:, [0, 2, 1]]
plt_mesh = k3d.mesh(vertices.astype(np.float32),
faces.astype(np.uint32),
color=0xd0d0d0)
plot += plt_mesh
plt_mesh.shader = '3d'
plot.display()
class Animator3(type(k3d.plot())):
def __init__(self, L, D, height=800):
super().__init__(height=height)
self.L = L
self.D = D
# formerly in init_plot()
self.meshes = []
for (corner, sizes), color in zip(iter_corner_sizes(self.L, self.D),
palette):
mesh = Box(corner=corner, sizes=sizes).mesh
mesh.color = color
# former 'plot' attribute is now just self
self += mesh
# set aside for updates
self.meshes.append(mesh)
display(self)
def update_plot(self, newL, newD):
self.D = newD
self.L = newL
for (corner, sizes), mesh in zip(iter_corner_sizes(newL, newD),
self.meshes):
newBox = Box(corner=corner, sizes=sizes)
mesh.vertices = newBox.mesh.vertices
# limited control over the sliders arrangement
def interact_D(self, **slider_as_dict):
# closure just capture self in function
def update(L, D):
self.update_plot(L, D)
interact(update,
L=fixed(self.L),
D=FloatSlider(**slider_as_dict, value=self.D,
layout=Layout(width="90%")
))
# full control: here we put them in a simple horizontal box
def interact_LD(self, L_dict, D_dict):
# closure just capture self in function
def update(L, D):
self.update_plot(L, D)
layout = Layout(width="50%")
lw = FloatSlider(**L_dict, layout=layout, description="L")
dw = FloatSlider(**D_dict, layout=layout, description="D")
box = HBox([lw, dw])
interactive_output(update, {'L': lw, 'D': dw})
display(box)
def vectors_plot(self):
plot = k3d.plot()
plot.camera_auto_fit = False
plot.grid_auto_fit = False
field = self.get_field
coord, vect = field.get_coord_and_vect(field.mesh.coordinates)
colors = df.plot3d.get_colors(vect)
vectors = k3d.vectors(coord, vect, colors=colors)
plot += vectors
plot.display()
return vectors
def visualize_pointcloud(point_cloud,
point_size,
flip_axes=False,
name='point_cloud'):
plot = k3d.plot(name=name,
grid_visible=False,
grid=(-0.55, -0.55, -0.55, 0.55, 0.55, 0.55))
if flip_axes:
point_cloud[:, 2] = point_cloud[:, 2] * -1
point_cloud[:, [0, 1, 2]] = point_cloud[:, [0, 2, 1]]
plt_points = k3d.points(positions=point_cloud.astype(np.float32),
point_size=point_size,
color=0xd0d0d0)
plot += plt_points
plt_points.shader = '3d'
plot.display()
def visualization_inter3D_xyz(pa):
if (pa.shape[1] == 4):
pa = np.delete(pa, (3), axis=1)
plot = k3d.plot()
print(pa.shape[0])
points_number = pa.shape[0]
colors = np.random.randint(0, 0xFFFFFF, points_number)
points = k3d.points(pa, colors, point_size=0.01, shader='3d')
plot += points
plot.camera_auto_fit = False
plot.display()
print("(x) : {:2.1f}m".format(pa[:, 0:1].max() - pa[:, 0:1].min()))
print("(y) : {:2.1f}m".format(pa[:, 1:2].max() - pa[:, 1:2].min()))
print("(z) : {:2.1f}m".format(pa[:, 2:3].max() - pa[:, 2:3].min()))
def viz_dimer_positions_k3d(positions,
size=5,
cmap_name="tab20c",
color_feature_name=None):
try:
import k3d
except ImportError:
mess = "YOu need to install the k3d library. "
mess += (
"Please follow the official instructions at https://github.com/K3D-tools/K3D-jupyter/."
)
raise ImportError(mess)
# Only show visible dimers
selected_dimers = positions[positions["visible"]]
coordinates = selected_dimers[["x", "y", "z"]].values.astype("float")
coordinates = coordinates.astype("float32")
if color_feature_name:
# TODO: that code should be much simpler...
cmap = matplotlib.cm.get_cmap(cmap_name)
categories = selected_dimers[color_feature_name].unique()
color_indices = cmap([i / len(categories) for i in categories])
colors = np.zeros((len(selected_dimers[color_feature_name]), ),
dtype="uint32")
for color_index, _ in enumerate(categories):
mask = selected_dimers[color_feature_name] == categories[
color_index]
color = color_indices[color_index]
color = "".join([format(int(x * 255), "02X") for x in color[:-1]])
color = int(color, 16)
colors[mask] = color
else:
colors = "#e4191b"
plot = k3d.plot()
plt_points = k3d.points(positions=coordinates,
point_size=size,
colors=colors)
plot += plt_points
plot.display()
return plot
def k3d(self, point_size=.8, color=True):
'''makes a 3d plot of the lattice using k3d visualization'''
import k3d
plot = k3d.plot(name='lattice_plot')
if not color:
for layer in range(self.n_layers):
plot += k3d.points(positions=self.layer_coords(layer, z=True),
point_size=point_size)
if color:
color_list = [
0x0054a7, 0xe41134, 0x75ac4f, 0xf4ea19, 0xffaff8, 0xa35112,
0x15e3f4, 0xcfc7ff
]
for layer in range(self.n_layers):
plot += k3d.points(positions=self.layer_coords(layer, z=True),
point_size=point_size,
color=color_list[layer % 8])
plot.display()
def display_3d(K,show_labels=False):
"""display a 3d simplicial complex using k3d, in jupyter
to install it:
sudo pip install k3d
sudo jupyter nbextension install --py k3d
sudo jupyter nbextension enable --py k3d
"""
import k3d
if not isinstance(K.vertices[0] ,Point):
raise Exception("Can display only Point-class vertices of dim 3!!!")
dim=K.vertices[0].dim
if dim != 3:
sys.stderr.write("Not yet implemented display in dim = %s\n" % dim )
return None
vertices = [v.coords for v in K.vertices]
edges = [ s for s in K.simplices[1] ]
faces = []
if 2 in K.simplices:
faces = [ s for s in K.simplices[2] ]
plt=k3d.plot(name='points')
plt_points = k3d.points( positions=vertices , point_size=0.05)
plt_points.shader ='3dSpecular'
plt_points.color = 14
plt += plt_points
# now lines:
for s in edges:
plt_line = k3d.line([vertices[s[0]],vertices[s[1]] ],shader='mesh', width=0.01,
color=0xff0000)
plt += plt_line
# now convert all faces to a mesh
plt_mesh = k3d.mesh(vertices,faces,color=0xff, wireframe=False, opacity=0.7, name="Simplicial Complex")
plt += plt_mesh
# now add the text
for P in K.vertices:
if show_labels and P.label is not None:
plt_text = k3d.text("%s" % repr(P), position = P.coords, color=0x7700,size=1)
plt += plt_text
#finally display
plt.display()
def create(self, data):
self.plot = k3d.plot()
self.data = data
# Equatorial slice
self.equatorial_slice \
= k3d.vtk_poly_data(serpentine.tools.extract_plane(data, [0, 0, 0], [0, 0, 1]),
color_attribute=self.color_attribute,
color_map=self.color_map)
# Meridional slice
self.meridional_slice \
= k3d.vtk_poly_data(serpentine.tools.extract_plane(data, [0, 0, 0], [0, 1, 0]),
color_attribute=self.color_attribute,
color_map=self.color_map)
# Spherical slice
self.spherical_slice \
= k3d.vtk_poly_data(serpentine.tools.extract_sphere(data, [0, 0, 0], 0.105),
color_attribute=self.color_attribute,
color_map=self.color_map)
self.boundary_sphere = k3d.points([0, 0, 0],
point_size=0.2,
shader="mesh",
color=0xffffff,
mesh_detail=3)
# Get rmin and rmax
x, y, z = np.split(self.equatorial_slice.vertices.T, 1, axis=0)[0]
rsqr = x**2 + y**2 + z**2
self.r_bounds = (np.sqrt(min(rsqr)), np.sqrt(max(rsqr)))
# Add to plot
self.plot += self.equatorial_slice
self.plot += self.meridional_slice
self.plot += self.spherical_slice
self.plot += self.boundary_sphere
# Modify defaults
self.plot.grid_auto_fit = False
self.initialize_sliders()
def show_points(points,
colors=[],
normals=None,
point_size=0.1,
line_width=0.00001):
plot = k3d.plot(grid_visible=False, axes_helper=0)
if normals is not None:
normal_vectors = k3d.vectors(points,
normals,
line_width=line_width,
use_head=False)
plot += normal_vectors
point_cloud = k3d.points(points,
colors=colors,
point_size=point_size,
shader='flat')
plot += point_cloud
plot.display()
return None
def plot_pcd(x, point_size=0.005, c='g'):
"""
x: point_nr,3
"""
if c == 'b':
k = 245
elif c == 'g':
k = 25811000
elif c == 'r':
k = 11801000
elif c == 'black':
k = 2580
else:
k = 2580
colors = np.ones(x.shape[0]) * k
plot = k3d.plot(name='points')
plt_points = k3d.points(x, colors.astype(np.uint32), point_size=point_size)
plot += plt_points
plt_points.shader = '3d'
plot.display()
def init_scene(d):
plot = k3d.plot(height=800)
m000 = Box((0,0,0), (3,3,3)).mesh
plot += m000
m100 = Box((3+d,0,0), (1,3,3)).mesh
plot += m100
m010 = Box((0,3+d,0), (3,1,3)).mesh
plot += m010
m001 = Box((0,0,3+d), (3,3,1)).mesh
plot += m001
m110 = Box((3+d,3+d,0), (1,1,3)).mesh
plot += m110
m101 = Box((3+d,0,3+d), (1,3,1)).mesh
plot += m101
m011 = Box((0,3+d,3+d), (3,1,1)).mesh
plot += m011
m111 = Box((3+d,3+d,3+d), (1,1,1)).mesh
plot += m111
return plot
def _load_k3d_objects(self):
# text objects
self.finish_text = k3d.text2d(
"FINISHED",
position=(.5, .5),
size=3,
)
self.processing_text = k3d.text2d(
"PROCESSING",
position=(.5, .5),
size=3,
)
# the plot area
self.plot = k3d.plot()
# gosht objects
self.m1 = None
self.m2 = None
self.m3 = None
def reset(self):
"""
Reset the environment for new episode.
Randomly (or not) generate CAD model for this episode.
"""
if self.models_path is not None:
self.model_path = os.path.join(self.models_path,
random.sample(os.listdir(self.models_path), 1)[0])
self.model = Model(self.model_path, resolution_image=self.image_size)
self.model.generate_view_points(self.number_of_view_points)
if self.illustrate:
self.model.illustrate().display()
self.plot = k3d.plot()
self.plot.display()
init_action = self.action_space.sample()
observation = self.model.get_observation(init_action)
return observation, init_action
def vis_depth_interactive(Z):
import k3d
Nx, Ny = 1, 1
xmin, xmax = 0, Z.shape[0]
ymin, ymax = 0, Z.shape[1]
x = np.linspace(xmin, xmax, Nx)
y = np.linspace(ymin, ymax, Ny)
x, y = np.meshgrid(x, y)
plot = k3d.plot(grid_auto_fit=True, camera_auto_fit=False)
plt_surface = k3d.surface(-Z.astype(np.float32),
color=0xb2ccff,
bounds=[xmin, xmax, ymin,
ymax]) # -Z for mirroring
plot += plt_surface
plot.display()
plot.camera = [
242.57934019166004, 267.50948550191197, -406.62328311352337, 256, 256,
-8.300323486328125, -0.13796270478729053, -0.987256298362836,
-0.07931767413815752
]
return plot
def voxels(plot_array,
pmin,
pmax,
colormap,
outlines=False,
plot=None,
**kwargs):
plot_array = plot_array.astype(np.uint8) # to avoid k3d warning
if plot is None:
plot = k3d.plot()
plot.display()
xmin, ymin, zmin = pmin
xmax, ymax, zmax = pmax
bounds = [xmin, xmax, ymin, ymax, zmin, zmax]
plot += k3d.voxels(plot_array,
color_map=colormap,
bounds=bounds,
outlines=outlines,
**kwargs)
return plot
def __init_skeleton_plot(
self,
skeletons: np.ndarray,
automatic_camera_orientation: bool = False) -> None:
self.plot = k3d.plot(antialias=1, camera_auto_fit=False)
centroid: np.ndarray = np.average(np.average(skeletons, axis=0),
axis=0)
if automatic_camera_orientation:
camera_up_vector: np.ndarray = np.zeros(shape=(3, ))
for line_indices in self.joint_set.vertically_aligned_line_indices:
camera_up_vector += np.sum(skeletons[:, line_indices[1]] -
skeletons[:, line_indices[0]],
axis=0)
camera_up_vector /= np.linalg.norm(camera_up_vector, ord=2)
self.plot.camera = [
0.0,
0.0,
0.0, # Camera position
centroid[0],
centroid[1],
centroid[2], # Camera looking at
camera_up_vector[0],
camera_up_vector[1],
camera_up_vector[2]
] # Camera up vector
else:
self.plot.camera = [
0.0,
0.0,
0.0, # Camera position
0.0,
0.0,
centroid[2], # Camera looking at
0.0,
-1.0,
0.0
] # Camera up vector
def plot_pcd(x, point_size=0.005, c='g'):
"""[summary]
Args:
x ([type]): point_nr,3
point_size (float, optional): [description]. Defaults to 0.005.
c (str, optional): [description]. Defaults to 'g'.
"""
if c == 'b':
k = 245
elif c == 'g':
k = 25811000
elif c == 'r':
k = 11801000
elif c == 'black':
k = 2580
else:
k = 2580
colors = np.ones(x.shape[0]) * k
plot = k3d.plot(name='points')
plt_points = k3d.points(x, colors.astype(np.uint32), point_size=point_size)
plot += plt_points
plt_points.shader = '3d'
plot.display()
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
if self._get_mode() != 0:
raise ValueError(
"Sorry, K3D backend only works within Jupyter Notebook")
self._bounds = []
self._clipping = []
self._handles = dict()
self._init_cyclers()
self._fig = k3d.plot(
grid_visible=self.grid,
menu_visibility=True,
background_color=int(cfg["k3d"]["bg_color"]),
grid_color=int(cfg["k3d"]["grid_color"]),
label_color=int(cfg["k3d"]["label_color"]),
)
if (self.xscale == "log") or (self.yscale == "log"):
warnings.warn("K3D-Jupyter doesn't support log scales. We will " +
"continue with linear scales.")
self.plot_shown = False
self._process_series(self._series)
def visualize_shape_alignment(R=None, t=None):
mesh_input = trimesh.load(
Path(__file__).parent.parent / "resources" / "mesh_input.obj")
mesh_target = trimesh.load(
Path(__file__).parent.parent / "resources" / "mesh_target.obj")
plot = k3d.plot(name='aligment',
grid_visible=False,
grid=(-0.55, -0.55, -0.55, 0.55, 0.55, 0.55))
input_vertices = np.array(mesh_input.vertices)
if not (R is None or t is None):
t_broadcast = np.broadcast_to(t[:, np.newaxis],
(3, mesh_input.vertices.shape[0]))
input_vertices = (R @ input_vertices.T + t_broadcast).T
plt_mesh_0 = k3d.mesh(input_vertices.astype(np.float32),
np.array(mesh_input.faces).astype(np.uint32),
color=0xd00d0d)
plt_mesh_1 = k3d.mesh(np.array(mesh_target.vertices).astype(np.float32),
np.array(mesh_target.faces).astype(np.uint32),
color=0x0dd00d)
plot += plt_mesh_0
plot += plt_mesh_1
plt_mesh_0.shader = '3d'
plt_mesh_1.shader = '3d'
plot.display()
def PlantGL(pglobject, plot=None, group_by_color=True, property=None):
"""Return a k3d plot from PlantGL shape, geometry and scene objects"""
if plot is None:
plot = k3d.plot()
if isinstance(pglobject, Geometry):
mesh = tomesh(pglobject)
plot += mesh
elif isinstance(pglobject, Shape):
mesh = tomesh(pglobject.geometry)
mesh.color = pglobject.appearance.ambient.toUint()
plot += mesh
elif isinstance(pglobject, Scene):
if group_by_color:
meshes = group_meshes_by_color(pglobject)
for mesh in meshes:
plot += mesh
else:
mesh = scene2mesh(pglobject, property)
plot += mesh
plot.lighting = 3
#plot.colorbar_object_id = randint(0, 1000)
return plot
def getNotebookBackend(actors2show, zoom, viewup):
vp = settings.plotter_instance
if isinstance(vp.shape, str) or sum(vp.shape) > 2:
colors.printc("Multirendering is not supported in jupyter.", c=1)
return
####################################################################################
# https://github.com/InsightSoftwareConsortium/itkwidgets
# /blob/master/itkwidgets/widget_viewer.py
if 'itk' in settings.notebookBackend:
from itkwidgets import view
settings.notebook_plotter = view(actors=actors2show,
cmap='jet', ui_collapsed=True,
gradient_opacity=False)
####################################################################################
elif settings.notebookBackend == 'k3d':
try:
import k3d # https://github.com/K3D-tools/K3D-jupyter
except:
print("Cannot find k3d, install with: pip install k3d")
return
actors2show2 = []
for ia in actors2show:
if not ia:
continue
if isinstance(ia, vtk.vtkAssembly): #unpack assemblies
acass = ia.unpack()
actors2show2 += acass
else:
actors2show2.append(ia)
# vbb, sizes, _, _ = addons.computeVisibleBounds()
# kgrid = vbb[0], vbb[2], vbb[4], vbb[1], vbb[3], vbb[5]
settings.notebook_plotter = k3d.plot(axes=[vp.xtitle, vp.ytitle, vp.ztitle],
menu_visibility=True,
# height=int(vp.size[1]/2),
)
# settings.notebook_plotter.grid = kgrid
settings.notebook_plotter.lighting = 1.2
# set k3d camera
settings.notebook_plotter.camera_auto_fit = True
if settings.plotter_instance and settings.plotter_instance.camera:
k3dc = utils.vtkCameraToK3D(settings.plotter_instance.camera)
if zoom:
k3dc[0] /= zoom
k3dc[1] /= zoom
k3dc[2] /= zoom
settings.notebook_plotter.camera = k3dc
# else:
# vsx, vsy, vsz = vbb[0]-vbb[1], vbb[2]-vbb[3], vbb[4]-vbb[5]
# vss = numpy.linalg.norm([vsx, vsy, vsz])
# if zoom:
# vss /= zoom
# vfp = (vbb[0]+vbb[1])/2, (vbb[2]+vbb[3])/2, (vbb[4]+vbb[5])/2 # camera target
# if viewup == 'z':
# vup = (0,0,1) # camera up vector
# vpos= vfp[0] + vss/1.9, vfp[1] + vss/1.9, vfp[2]+vss*0.01 # camera position
# elif viewup == 'x':
# vup = (1,0,0)
# vpos= vfp[0]+vss*0.01, vfp[1] + vss/1.5, vfp[2] # camera position
# else:
# vup = (0,1,0)
# vpos= vfp[0]+vss*0.01, vfp[1]+vss*0.01, vfp[2] + vss/1.5 # camera position
# settings.notebook_plotter.camera = [vpos[0], vpos[1], vpos[2],
# vfp[0], vfp[1], vfp[2],
# vup[0], vup[1], vup[2] ]
if not vp.axes:
settings.notebook_plotter.grid_visible = False
for ia in actors2show2:
if isinstance(ia, (vtk.vtkCornerAnnotation, vtk.vtkAssembly)):
continue
kobj = None
kcmap= None
name = None
if hasattr(ia, 'filename'):
if ia.filename:
name = os.path.basename(ia.filename)
if ia.name:
name = os.path.basename(ia.name)
#####################################################################scalars
# work out scalars first, Points Lines are also Mesh objs
if isinstance(ia, (Mesh, shapes.Line, Points)):
# print('scalars', ia.name, ia.N())
iap = ia.GetProperty()
if isinstance(ia, (shapes.Line, Points)):
iapoly = ia.polydata()
else:
iapoly = ia.clone().clean().triangulate().computeNormals().polydata()
vtkscals = None
color_attribute = None
if ia.mapper().GetScalarVisibility():
vtkdata = iapoly.GetPointData()
vtkscals = vtkdata.GetScalars()
if vtkscals is None:
vtkdata = iapoly.GetCellData()
vtkscals = vtkdata.GetScalars()
if vtkscals is not None:
c2p = vtk.vtkCellDataToPointData()
c2p.SetInputData(iapoly)
c2p.Update()
iapoly = c2p.GetOutput()
vtkdata = iapoly.GetPointData()
vtkscals = vtkdata.GetScalars()
if vtkscals is not None:
if not vtkscals.GetName():
vtkscals.SetName('scalars')
scals_min, scals_max = ia.mapper().GetScalarRange()
color_attribute = (vtkscals.GetName(), scals_min, scals_max)
lut = ia.mapper().GetLookupTable()
lut.Build()
kcmap=[]
nlut = lut.GetNumberOfTableValues()
for i in range(nlut):
r,g,b,a = lut.GetTableValue(i)
kcmap += [i/(nlut-1), r,g,b]
#####################################################################Volume
if isinstance(ia, Volume):
# print('Volume', ia.name, ia.dimensions())
kx, ky, kz = ia.dimensions()
arr = ia.getPointArray()
kimage = arr.reshape(-1, ky, kx)
colorTransferFunction = ia.GetProperty().GetRGBTransferFunction()
kcmap=[]
for i in range(128):
r,g,b = colorTransferFunction.GetColor(i/127)
kcmap += [i/127, r,g,b]
kbounds = numpy.array(ia.imagedata().GetBounds()) \
+ numpy.repeat(numpy.array(ia.imagedata().GetSpacing()) / 2.0, 2)\
* numpy.array([-1,1] * 3)
kobj = k3d.volume(kimage.astype(numpy.float32),
color_map=kcmap,
#color_range=ia.imagedata().GetScalarRange(),
alpha_coef=10,
bounds=kbounds,
name=name,
)
settings.notebook_plotter += kobj
#####################################################################text
elif hasattr(ia, 'info') and 'formula' in ia.info.keys():
pos = (ia.GetPosition()[0],ia.GetPosition()[1])
kobj = k3d.text2d(ia.info['formula'], position=pos)
settings.notebook_plotter += kobj
#####################################################################Mesh
elif isinstance(ia, Mesh) and ia.N() and len(ia.faces()):
# print('Mesh', ia.name, ia.N(), len(ia.faces()))
kobj = k3d.vtk_poly_data(iapoly,
name=name,
# color=_rgb2int(iap.GetColor()),
color_attribute=color_attribute,
color_map=kcmap,
opacity=iap.GetOpacity(),
wireframe=(iap.GetRepresentation()==1))
if iap.GetInterpolation() == 0:
kobj.flat_shading = True
settings.notebook_plotter += kobj
#####################################################################Points
elif isinstance(ia, Points) or ia.NPoints() == ia.NCells():
# print('Points', ia.name, ia.N())
kcols=[]
if color_attribute is not None:
scals = utils.vtk2numpy(vtkscals)
kcols = k3d.helpers.map_colors(scals, kcmap,
[scals_min,scals_max]).astype(numpy.uint32)
# sqsize = numpy.sqrt(numpy.dot(sizes, sizes))
kobj = k3d.points(ia.points().astype(numpy.float32),
color=_rgb2int(iap.GetColor()),
colors=kcols,
opacity=iap.GetOpacity(),
shader="dot",
point_size=3, # point_size=iap.GetPointSize()*sqsize/800,
name=name,
)
settings.notebook_plotter += kobj
#####################################################################Line
elif ia.polydata(False).GetNumberOfLines():
# print('Line', ia.name, ia.N(), len(ia.faces()),
# ia.polydata(False).GetNumberOfLines(), len(ia.lines()),
# color_attribute, [vtkscals])
# kcols=[]
# if color_attribute is not None:
# scals = utils.vtk2numpy(vtkscals)
# kcols = k3d.helpers.map_colors(scals, kcmap,
# [scals_min,scals_max]).astype(numpy.uint32)
# sqsize = numpy.sqrt(numpy.dot(sizes, sizes))
for i, ln_idx in enumerate(ia.lines()):
if i>200:
print('WARNING: K3D nr of line segments is limited to 200.')
break
pts = ia.points()[ln_idx]
kobj = k3d.line(pts.astype(numpy.float32),
color=_rgb2int(iap.GetColor()),
# colors=kcols,
opacity=iap.GetOpacity(),
shader="thick",
# width=iap.GetLineWidth()*sqsize/1000,
name=name,
)
settings.notebook_plotter += kobj
####################################################################################
elif settings.notebookBackend == 'panel' and hasattr(vp, 'window') and vp.window:
import panel # https://panel.pyviz.org/reference/panes/VTK.html
vp.renderer.ResetCamera()
settings.notebook_plotter = panel.pane.VTK(vp.window,
width=int(vp.size[0]/1.5),
height=int(vp.size[1]/2))
####################################################################################
elif 'ipyvtk' in settings.notebookBackend and hasattr(vp, 'window') and vp.window:
from ipyvtklink.viewer import ViewInteractiveWidget
vp.renderer.ResetCamera()
settings.notebook_plotter = ViewInteractiveWidget(vp.window)
####################################################################################
elif '2d' in settings.notebookBackend.lower() and hasattr(vp, 'window') and vp.window:
import PIL.Image
try:
import IPython
except ImportError:
raise Exception('IPython not available.')
from vedo.io import screenshot
settings.screeshotLargeImage = True
nn = screenshot(returnNumpy=True, scale=settings.screeshotScale+2)
pil_img = PIL.Image.fromarray(nn)
settings.notebook_plotter = IPython.display.display(pil_img)
return settings.notebook_plotter
def _ipython_display_(self, **kwargs):
"""Called when `IPython.display.display` is called on the widget."""
import k3d
plot = k3d.plot()
plot += self
plot.display()
def k3d(self,
*,
plot=None,
color=dfu.cp_int[0],
multiplier=None,
**kwargs):
"""``k3d`` plot.
If ``plot`` is not passed, ``k3d.Plot`` object is created
automatically. The colour of the region can be specified using
``color`` argument.
For details about ``multiplier``, please refer to
``discretisedfield.Region.mpl``.
This method is based on ``k3d.voxels``, so any keyword arguments
accepted by it can be passed (e.g. ``wireframe``).
Parameters
----------
plot : k3d.Plot, optional
Plot to which the plot is added. Defaults to ``None`` - plot is
created internally.
color : int, optional
Colour of the region. Defaults to the default color palette.
multiplier : numbers.Real, optional
Axes multiplier. Defaults to ``None``.
Examples
--------
1. Visualising the region using ``k3d``.
>>> import discretisedfield as df
...
>>> p1 = (-50e-9, -50e-9, 0)
>>> p2 = (50e-9, 50e-9, 10e-9)
>>> region = df.Region(p1=p1, p2=p2)
>>> region.k3d()
Plot(...)
"""
if plot is None:
plot = k3d.plot()
plot.display()
if multiplier is None:
multiplier = uu.si_max_multiplier(self.edges)
unit = f'({uu.rsi_prefixes[multiplier]}m)'
plot_array = np.ones((1, 1, 1)).astype(np.uint8) # avoid k3d warning
bounds = [
i for sublist in zip(np.divide(self.pmin, multiplier),
np.divide(self.pmax, multiplier))
for i in sublist
]
plot += k3d.voxels(plot_array,
color_map=color,
bounds=bounds,
outlines=False,
**kwargs)
plot.axes = [
i + r'\,\text{{{}}}'.format(unit) for i in dfu.axesdict.keys()
]
head_size=1.5,
labels=['a'])
b_vec = k3d.vectors(red_point.positions,
cubic_system[9],
head_size=1.5,
labels=['b'])
c_vec = k3d.vectors(red_point.positions,
cubic_system[1],
head_size=1.5,
labels=['c'])
ab_vec = k3d.vectors(red_point.positions,
cubic_system[3] + 2 * cubic_system[9],
head_size=1.5,
labels=['a+2b'])
plot1 = k3d.plot()
plot1 += red_point + system + a_vec + b_vec + c_vec + ab_vec
### SECOND DRAWING
cubic_system = cubic(0, 0, 0, 3, 3, 3)
mask = np.arange(cubic_system.shape[0])
chosen = [0, 1, 3, 4, 21, 22, 24, 25]
red_points = k3d.points(cubic_system[chosen], point_size=0.2, color=0xff0000)
system = k3d.points(np.delete(cubic_system, chosen, axis=0),
point_size=0.2,
color=0)
ab_vec = k3d.vectors(red_point.positions,
cubic_system[3] + 2 * cubic_system[9],
head_size=1.5,
labels=['a+2b'])
def getNotebookBackend(actors2show, zoom, viewup):
vp = settings.plotter_instance
####################################################################################
# https://github.com/InsightSoftwareConsortium/itkwidgets
# /blob/master/itkwidgets/widget_viewer.py
if 'itk' in settings.notebookBackend:
from itkwidgets import view
if sum(vp.shape) != 2:
colors.printc("Warning: multirendering is not supported in jupyter.", c=1)
settings.notebook_plotter = view(actors=actors2show,
cmap='jet', ui_collapsed=True,
gradient_opacity=False)
####################################################################################
elif settings.notebookBackend == 'k3d':
import k3d # https://github.com/K3D-tools/K3D-jupyter
if vp.shape[0] != 1 or vp.shape[1] != 1:
colors.printc("Warning: multirendering is not supported in jupyter.", c=1)
actors2show2 = []
for ia in actors2show:
if isinstance(ia, vtk.vtkAssembly): #unpack assemblies
acass = ia.unpack()
#for a in acass:
# a.SetScale(ia.GetScale())
actors2show2 += acass
else:
actors2show2.append(ia)
vbb, sizes, min_bns, max_bns = addons.computeVisibleBounds()
kgrid = vbb[0], vbb[2], vbb[4], vbb[1], vbb[3], vbb[5]
settings.notebook_plotter = k3d.plot(axes=[vp.xtitle, vp.ytitle, vp.ztitle],
menu_visibility=True,
height=int(vp.size[1]/2) )
settings.notebook_plotter.grid = kgrid
settings.notebook_plotter.lighting = 1.2
# set k3d camera
settings.notebook_plotter.camera_auto_fit = False
eps = 1 + numpy.random.random()*1.0e-04 # workaround to bug in k3d
# https://github.com/K3D-tools/K3D-jupyter/issues/180
if settings.plotter_instance and settings.plotter_instance.camera:
k3dc = utils.vtkCameraToK3D(settings.plotter_instance.camera)
k3dc[2] = k3dc[2]*eps
settings.notebook_plotter.camera = k3dc
else:
vsx, vsy, vsz = vbb[0]-vbb[1], vbb[2]-vbb[3], vbb[4]-vbb[5]
vss = numpy.linalg.norm([vsx, vsy, vsz])
if zoom:
vss /= zoom
vfp = (vbb[0]+vbb[1])/2, (vbb[2]+vbb[3])/2, (vbb[4]+vbb[5])/2 # camera target
if viewup == 'z':
vup = (0,0,1) # camera up vector
vpos= vfp[0] + vss/1.9, vfp[1] + vss/1.9, vfp[2]+vss*0.01 # camera position
elif viewup == 'x':
vup = (1,0,0)
vpos= vfp[0]+vss*0.01, vfp[1] + vss/1.5, vfp[2] # camera position
else:
vup = (0,1,0)
vpos= vfp[0]+vss*0.01, vfp[1]+vss*0.01, vfp[2] + vss/1.5 # camera position
settings.notebook_plotter.camera = [vpos[0], vpos[1], vpos[2]*eps,
vfp[0], vfp[1], vfp[2],
vup[0], vup[1], vup[2] ]
if not vp.axes:
settings.notebook_plotter.grid_visible = False
for ia in actors2show2:
kobj = None
kcmap= None
if isinstance(ia, Mesh) and ia.N():
iap = ia.GetProperty()
#ia.clean().triangulate().computeNormals()
#ia.triangulate())
iapoly = ia.clone().clean().triangulate().computeNormals().polydata()
vtkscals = None
color_attribute = None
if ia.mapper().GetScalarVisibility():
vtkdata = iapoly.GetPointData()
vtkscals = vtkdata.GetScalars()
if vtkscals is None:
vtkdata = iapoly.GetCellData()
vtkscals = vtkdata.GetScalars()
if vtkscals is not None:
c2p = vtk.vtkCellDataToPointData()
c2p.SetInputData(iapoly)
c2p.Update()
iapoly = c2p.GetOutput()
vtkdata = iapoly.GetPointData()
vtkscals = vtkdata.GetScalars()
if vtkscals is not None:
if not vtkscals.GetName():
vtkscals.SetName('scalars')
scals_min, scals_max = ia.mapper().GetScalarRange()
color_attribute = (vtkscals.GetName(), scals_min, scals_max)
lut = ia.mapper().GetLookupTable()
lut.Build()
kcmap=[]
nlut = lut.GetNumberOfTableValues()
for i in range(nlut):
r,g,b,a = lut.GetTableValue(i)
kcmap += [i/(nlut-1), r,g,b]
if iapoly.GetNumberOfPolys() > 0:
name = None
if ia.filename:
name = os.path.basename(ia.filename)
kobj = k3d.vtk_poly_data(iapoly,
name=name,
color=colors.rgb2int(iap.GetColor()),
color_attribute=color_attribute,
color_map=kcmap,
opacity=iap.GetOpacity(),
wireframe=(iap.GetRepresentation()==1))
if iap.GetInterpolation() == 0:
kobj.flat_shading = True
else:
kcols=[]
if color_attribute is not None:
scals = vtk_to_numpy(vtkscals)
kcols = k3d.helpers.map_colors(scals, kcmap,
[scals_min,scals_max]).astype(numpy.uint32)
sqsize = numpy.sqrt(numpy.dot(sizes, sizes))
if ia.NPoints() == ia.NCells():
kobj = k3d.points(ia.points().astype(numpy.float32),
color=colors.rgb2int(iap.GetColor()),
colors=kcols,
opacity=iap.GetOpacity(),
shader="3d",
point_size=iap.GetPointSize()*sqsize/400,
#compression_level=9,
)
else:
kobj = k3d.line(ia.points().astype(numpy.float32),
color=colors.rgb2int(iap.GetColor()),
colors=kcols,
opacity=iap.GetOpacity(),
shader="thick",
width=iap.GetLineWidth()*sqsize/1000,
)
settings.notebook_plotter += kobj
elif isinstance(ia, Volume):
kx, ky, kz = ia.dimensions()
arr = ia.getPointArray()
kimage = arr.reshape(-1, ky, kx)
colorTransferFunction = ia.GetProperty().GetRGBTransferFunction()
kcmap=[]
for i in range(128):
r,g,b = colorTransferFunction.GetColor(i/127)
kcmap += [i/127, r,g,b]
#print('vol scal range', ia.imagedata().GetScalarRange())
#print(numpy.min(kimage), numpy.max(kimage))
kbounds = numpy.array(ia.imagedata().GetBounds()) \
+ numpy.repeat(numpy.array(ia.imagedata().GetSpacing()) / 2.0, 2)\
* numpy.array([-1,1] * 3)
kobj = k3d.volume(kimage.astype(numpy.float32),
color_map=kcmap,
#color_range=ia.imagedata().GetScalarRange(),
alpha_coef=10,
bounds=kbounds,
)
settings.notebook_plotter += kobj
elif hasattr(ia, 'info') and 'formula' in ia.info.keys():
pos = (ia.GetPosition()[0],ia.GetPosition()[1])
kobj = k3d.text2d(ia.info['formula'], position=pos)
settings.notebook_plotter += kobj
####################################################################################
elif settings.notebookBackend == 'panel' and hasattr(vp, 'window') and vp.window:
import panel # https://panel.pyviz.org/reference/panes/VTK.html
vp.renderer.ResetCamera()
settings.notebook_plotter = panel.pane.VTK(vp.window,
width=int(vp.size[0]/1.5),
height=int(vp.size[1]/2))
####################################################################################
elif '2d' in settings.notebookBackend.lower() and hasattr(vp, 'window') and vp.window:
import PIL.Image
try:
import IPython
except ImportError:
raise Exception('IPython not available.')
return
from vtkplotter.vtkio import screenshot
settings.screeshotLargeImage = True
nn = screenshot(returnNumpy=True, scale=settings.screeshotScale+2)
pil_img = PIL.Image.fromarray(nn)
settings.notebook_plotter = IPython.display.display(pil_img)
return settings.notebook_plotter