def showSolution3D(S, start, goal):
from vedo import Text3D, Cube, Line, Grid, merge, show
pts, cubes, txts = [], [], []
pts = [(x, -y) for y, x in S[0]]
for y, line in enumerate(Z):
for x, c in enumerate(line):
if c: cubes.append(Cube([x, -y, 0]))
path = Line(pts).lw(6).c('tomato')
walls = merge(cubes).clean().flat().texture('wood1')
sy, sx = S[1].shape
gradient = np.flip(S[1], axis=0).ravel()
grd = Grid(pos=((sx - 1) / 2, -(sy - 1) / 2, -0.49),
sx=sx,
sy=sy,
resx=sx,
resy=sy)
grd.lw(0).wireframe(False).cmap('gist_earth_r', gradient, on='cells')
grd.addScalarBar(title='Gradient', horizontal=True, c='k', nlabels=2)
txts.append(__doc__)
txts.append(Text3D('Start', pos=[start[1] - 1, -start[0] + 1.5, 1], c='k'))
txts.append(Text3D('Goal!', pos=[goal[1] - 2, -goal[0] - 2.7, 1], c='k'))
show(path, walls, grd, txts, axes=0, zoom=1.2)
counts = [1946, 8993, 3042, 1190, 1477, 0, 0]
percent = [11.68909178, 54.01850072, 18.27246516, 7.14800577, 8.87193657, 0, 0]
labels = [
'<100', '100-250', '250-500', '500-750', '750-1000', '1000-2000', '>2000'
]
colors = colorMap(range(len(counts)), "hot")
plt = plot(
[counts, labels, colors],
mode="bars",
ylim=(0, 10500),
aspect=4 / 3,
axes=dict(
htitle="Clusters in lux range",
hTitleItalic=False,
xLabelRotation=35,
xLabelSize=0.02,
tipSize=0, # axes arrow tip size
),
)
for i in range(len(percent)):
val = precision(percent[i], 3) + '%'
txt = Text3D(val,
pos=(plt.centers[i], counts[i]),
justify="bottom-center",
c="blue2")
plt += txt.scale(200).shift(0, 150, 0)
plt.show(size=(1000, 750), zoom=1.3, viewup='2d').close()
)
plt += DashedLine(x, y)
# Fit points and evaluate, with a boostrap and Monte-Carlo technique,
# the correct errors and error bands. Return a Line object:
pfit = fit([x, y+noise],
deg=deg, # degree of the polynomial
niter=500, # nr. of MC iterations to compute error bands
nstd=2, # nr. of std deviations to display
xerrors=xerrs, # optional array of errors on x
yerrors=yerrs, # optional array of errors on y
vrange=(-3,15), # specify the domain of fit
)
plt += [pfit, pfit.errorBand, *pfit.errorLines] # add these objects to Plot
txt = "fit coefficients:\n " + precision(pfit.coefficients, 2) \
+ "\n\pm" + precision(pfit.coefficientErrors, 2) \
+ "\n\Chi^2_\nu = " + precision(pfit.reducedChi2, 3)
plt += Text3D(txt, s=0.42, font='VictorMono').pos(2,-2).c('k')
# Create an histo to show the correlation of fit parameters
h = histogram(pfit.MonteCarloCoefficients[:,0],
pfit.MonteCarloCoefficients[:,1],
title="parameters correlation",
xtitle='coeff_0', ytitle='coeff_1',
cmap='bone_r', scalarbar=True)
h.scale(150).shift(-1,11) # make it a lot bigger and move it
show(plt, h, zoom=1.3, mode="image").close()
from vedo import Volume, Text3D, show, dataurl
vol = Volume(dataurl+"embryo.slc").mode(0).c('b2').alphaUnit(5)
t = Text3D("Sharpe\n~~~Lab", s=40, font="Spears", vspacing=1.4, depth=.04)
t.c('k1').rotateX(90).pos(200,150,70)
cam = dict(pos=(363, -247, 121),
focalPoint=(240, 137, 116),
viewup=(4.45e-3, 0.0135, 1.00),
distance=403)
show(vol, t, size=(700,400), camera=cam)
\intx\dot~dx = \onehalf x\^2 + const.
d^2 x^\mu + \Gamma^\mu_\alpha\beta ~dx^\alpha ~dx^\beta = 0
-∇\^2u(x) = f(x) in Ω, u(x)~=~u_D (x) in \partial\Omega
Protect underscore \\\_ and \\\^ with a backslash.
"""
plt = Plotter(N=4, pos=(300, 0), size=(1600, 950))
cam = dict(pos=(3.99e+5, 8.51e+3, 6.47e+5),
focalPoint=(2.46e+5, 1.16e+5, -9.24e+3),
viewup=(-0.0591, 0.983, 0.175),
distance=6.82e+5,
clippingRange=(5.26e+5, 8.92e+5))
for i, fnt in enumerate(["Kanopus", "Normografo", "Theemim", "VictorMono"]):
t = Text3D(txt, font=fnt, italic=0).c('darkblue').scale(12300)
plt.show(
t,
Text2D("Font: " + fnt, font=fnt, bg='r'),
axes=dict(
xtitle='my units for L_x (\mum)',
ytitle='my Y-axis with\na long description',
titleFont=fnt,
labelFont=fnt,
digits=2,
),
at=i,
camera=cam,
resetcam=not bool(i),
)
def make_actor_label(
atlas,
actors,
labels,
size=300,
color=None,
radius=100,
xoffset=0,
yoffset=-500,
zoffset=0,
):
"""
Adds a 2D text ancored to a point on the actor's mesh
to label what the actor is
:param kwargs: key word arguments can be passed to determine
text appearance and location:
- size: int, text size. Default 300
- color: str, text color. A list of colors can be passed
if None the actor's color is used. Default None.
- xoffset, yoffset, zoffset: integers that shift the label position
- radius: radius of sphere used to denote label anchor. Set to 0 or None to hide.
"""
offset = [-yoffset, -zoffset, xoffset]
default_offset = np.array([0, -200, 100])
new_actors = []
for n, (actor, label) in enumerate(zip(listify(actors), listify(labels))):
# Get label color
if color is None:
color = [0.2, 0.2, 0.2]
# Get mesh's highest point
points = actor.points().copy()
point = points[np.argmin(points[:, 1]), :]
point += np.array(offset) + default_offset
try:
if atlas.hemisphere_from_coords(point, as_string=True) == "left":
point = atlas.mirror_point_across_hemispheres(point)
except IndexError:
pass
# Create label
txt = Text3D(label, point, s=size, c=color)
txt._kwargs = dict(
size=size,
color=color,
radius=radius,
xoffset=xoffset,
yoffset=yoffset,
zoffset=zoffset,
)
# rotate label
p = txt.pos()
txt.pos(x=0, y=0, z=0).rotateX(180).rotateY(180).pos(p)
new_actors.append(txt)
# Mark a point on Mesh that corresponds to the label location
if radius is not None:
pt = actor.closestPoint(point)
sphere = Sphere(pt, r=radius, c=color)
sphere.ancor = pt
new_actors.append(sphere)
return new_actors
"""Embed a 3D scene
in a webpage with x3d"""
from vedo import dataurl, Plotter, Volume, Text3D
plt = Plotter(size=(800, 600), bg='GhostWhite')
embryo = Volume(dataurl + 'embryo.tif').isosurface().decimate(0.5)
coords = embryo.points()
embryo.cmap('PRGn', coords[:, 1]) # add dummy colors along y
txt = Text3D(__doc__, font='Bongas', s=350, c='red2', depth=0.05)
txt.pos(2500, 300, 500)
plt.show(embryo, txt, txt.box(pad=250), axes=1, viewup='z', zoom=1.2)
# This exports the scene and generates 2 files:
# embryo.x3d and an example embryo.html to inspect in the browser
plt.export('embryo.x3d', binary=False)
print("Type: \n firefox embryo.html")
"""Markers set, analogous to matplotlib"""
from vedo import Plotter, Marker, Text3D
symbols = [
'.', 'p', '*', 'h', 'D', 'd', 'o', 'v', '>', '<', 's', 'x', '+', 'a'
]
plt = Plotter(size=(1500, 300), axes=0)
for i, s in enumerate(symbols):
plt += Marker(s, filled=True).x(i * 0.6).color(i)
plt += Text3D(s, pos=[i * 0.6, -0.6, 0], s=0.12).color('k')
plt += __doc__
plt.show(zoom=5, viewup='2d').close()