"""A simple scatter plot"""
from vtkplotter import show
from vtkplotter.pyplot import plot
import numpy as np
x = np.random.randn(100)+10
y = np.random.randn(100)*20
plt = plot( x, y,
lw=0,
xtitle="variable x",
ytitle="variable y",
aspect=4/3, # aspect ratio
marker="*", # marker style
mc="dr", # marker color
axes=True,
)
# show Assembly object and lock interaction to 2d:
# (can zoom in a region w/ mouse, press r to reset)
show(plt, __doc__, viewup='2d')
from vtkplotter.pyplot import plot
# Make up same data
x = np.arange(0, 6, 0.1)
y = 2+2*np.sin(2*x)/(x+1)
ye= y**2 / 10
miny = np.min(y-ye)
idx = np.argmax(y)
# Plot the two variables, return a Plot(Assembly) object:
plt = plot(x,y,
yerrors=ye,
xtitle='time in seconds',
ytitle='y oscillation [a.u.]',
ylim=(0.5, 5),
aspect=4/3, # aspect ratio (any float = x_size/y_size)
errorBand=True, # join errors on y into an error band
lc="k", # line color
ec="r", # error band color
la=0.6, # error and line alphas
pad=0.0, # tight margins, no padding
)
# Add a grey transparent rectangle to represent an exclusion region:
plt += Rectangle([1,0.5], [2.7,5], alpha=0.2, c='k')
# Add some text and latex formula
plt += Text("excluded", s=0.2, c='k').rotateZ(20).pos(1.3, 3.7)
plt += Latex(r"y(t)=2+2\cdot\frac{\sin(2t)}{(t+1)}", pos=(4.7, 4.7), s=.8, c='db')
# Add a star marker at maximum of function (at z=0.1, so it stays on top):
plt += Marker('*', pos=(x[idx], y[idx], 0.1), c='blue')
n = 1000
x = np.random.randn(n)
y = np.random.randn(n)
# define what size must have each marker:
marker_sizes = np.sin(2*x)/8
# define a (r,g,b) list of colors for each marker:
marker_cols = np.c_[np.cos(2*x), np.zeros(n), np.zeros(n)]
txt0 = Text2D("A scatter plot of a\n 2D gaussian distribution")
plt0 = plot(x, y, ma=0.3, lw=0, # ma = marker alpha
marker="*", # marker style
xtitle="variable A",
ytitle="variable B",
)
txt1 = Text2D(" marker size = sin(2x) ")
plt1 = plot(x, y, ma=0.3, lw=0,
marker="*", # marker style
ms=marker_sizes, # VARIABLE marker sizes
mc='red', # same color for markers
)
txt2 = Text2D(" marker size = sin(2x)\n red level = cos(2x)")
plt2 = plot(x, y, ma=0.3, lw=0,
marker=">", # marker style
ms=marker_sizes, # VARIABLE marker sizes
mc=marker_cols, # VARIABLE marker colors
"""Probe a Volume with a line
and plot the intensity values"""
from vtkplotter import *
from vtkplotter.pyplot import plot
vol = load(datadir + 'vase.vti')
vol.addScalarBar3D(title='vase', c='k', italic=1)
p1, p2 = (10, 10, 10), (90, 90, 90)
pl = probeLine(vol, p1, p2, res=50).lineWidth(4)
xvals = pl.points()[:, 0]
yvals = pl.getPointArray()
plt = plot(
xvals,
yvals,
spline=True,
lc="r", # line color
marker="*", # marker style
mc="dr", # marker color
ms=0.6, # marker size
)
show([(vol, pl, __doc__), plt], N=2, sharecam=False)
"""Surface plotting in spherical coordinates
spherical harmonic function is:
Y(l=2, m=0) = 3*cos(theta)**2 - 1
(red points are made NaN on purpose)
"""
from vtkplotter import *
from vtkplotter.pyplot import plot
import numpy as np
def rhofunc(theta, phi):
if theta < 0.2:
return np.nan # make some points invalid
#return cos(theta)**2 # Y(l=1 m=0)
return (3*cos(theta)**2 - 1)**2 # Y(l=2 m=0)
#return (5*cos(theta)**3 - 3*cos(theta))**2 # Y(l=3 m=0)
# Build the plot,
# return an Assembly of 3 meshes, the unit
# grid sphere, the surface rho(theta, phi) and
# the red Points where rho is a complex number:
spl = plot(rhofunc, mode='spheric', cmap='viridis')
show(spl, __doc__, axes=12, viewup='z')
"""Use of plot() function analogous to matplotlib"""
import numpy as np, vtk
from vtkplotter import *
from vtkplotter.pyplot import plot
x = np.linspace(0, 5, 10)
plt1 = plot(x, x * x, 'sg-', title='Plot1: y=x*x')
plt2 = plot(x, cos(x), 'pr--', title='Plot2: y=cos(x)')
plt3 = plot(x, sqrt(x), 'Db-', title='Plot3: y=sqrt(x)')
plt4 = plot(x, sin(x), '*t--', title='Plot4: y=sin(x)')
# window shape can be expressed as "n/m" or "n|m"
show(plt1, plt2, plt3, plt4, shape="3|1", sharecam=False, size=(1300, 900))
printc('plt1 is vtkAssembly?', isinstance(plt1, vtk.vtkAssembly))
z = (x - 1)**2 + (y - 1)**2 + 9 * sin(y - 1)**2 + 1
return z / 12
def func(v):
return f(v[0], v[1])
def callbk(optimizer, v, value):
global minv
if value < minv:
pts.append([v.value[0], v.value[1], value])
minv = value
optimizer = ng.optimizers.OnePlusOne(parametrization=2, budget=100)
pts, minv = [], 1e30
optimizer.register_callback("tell", callbk)
# define a constraint on first variable of x:
#optimizer.parametrization.register_cheap_constraint(lambda v: v[0]>-3)
res = optimizer.minimize(func) # best value
printc('Minimum at:', res.value)
ln = Line(pts, lw=3)
fu = plot(f, xlim=[-3, 4], ylim=[-3, 4], alpha=0.5)
show(fu, ln, __doc__)
from vtkplotter import *
from vtkplotter.pyplot import plot
########################################################### REAL
#Draw a surface representing a 2-var function specified
#as a string or as a reference to an external existing function.
#Red points indicate where the function does not exist.
# an existing function z(x,y) can be passed:
def my_z(x, y):
return sin(2 * x * y) * cos(3 * y) / 2
f1 = plot(my_z)
# red dots are shown where the function does not exist (y>x):
f2 = plot("sin(3*x)*log(x-y)/3")
# specify x and y ranges and z vertical limits:
f3 = plot("log(x**2+y**2-1)", xlim=[-2, 2], ylim=[-1, 8], zlim=[-1, None])
show(f1, f2, f3, N=3, sharecam=False)
########################################################## COMPLEX
comment = """Vertical axis shows the real part of complex z:
z = sin(log(x*y))
Color map the value of the imaginary part
(green=positive, purple=negative)"""
plt = plot(lambda x, y: sin(log(x * y)) / 25, mode='complex')
from vtkplotter.pyplot import plot
import numpy as np
x = np.linspace(0, 10, num=21)
y = 3 * np.sin(x)
errs = np.ones_like(x) / 2
################# first plot
plt = plot(
x,
y,
"*r-", # markers: *,o,p,h,D,d,v,^,s,x,a
xtitle="x variable (mm)",
ytitle="y(x)",
aspect=16 / 9, # aspect ratio x/y of plot
# xlim=(-1, 14), # specify x range
# ylim=(-4, 5), # specify y range
)
################# plot on top of plt
plt.plot(
x + 3,
y,
"sb--",
xerrors=errs, # set error bars on x
yerrors=errs, # set error bars on y
spline=True, # continous line through points
lw=1.5,
)
################## plot again on top of plt
