I have an array with values (0.7, 0.4, 0.1) and I would like to plot the corresponding ellipsoid with this code:
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)
x = 0.7 * np.outer(np.cos(u), np.sin(v))
y = 0.4 * np.outer(np.sin(u), np.sin(v))
z = 0.1 * np.outer(np.ones(np.size(u)), np.cos(v))
ax.plot_surface(x, y, z, rstride=4, cstride=4, color='b')
plt.show()
When I plot the figure, it looks like a sphere more than the expected ellipsoid. I suppose the problem is setting the "correct" range for the axes.
How could I solve this "problem"?
You could set proper ranges with ax.set_xlim(), ax.set_ylim() and ax.set_zlim() methods.
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)
x = 0.7 * np.outer(np.cos(u), np.sin(v))
y = 0.4 * np.outer(np.sin(u), np.sin(v))
z = 0.1 * np.outer(np.ones(np.size(u)), np.cos(v))
ax.plot_surface(x, y, z, rstride=4, cstride=4, color='b')
ax.set_xlim([-0.5, 0.5])
ax.set_ylim([-0.5, 0.5])
ax.set_zlim([-0.5, 0.5])
plt.show()
Related
I am trying to plot the following function on a unit sphere, the points should be on the sphere and fill up the whole sphere however some of the points are falling off. Any suggestions why? I believe it is because the sphere is not spanning 1,1,1 3D grid but I am not sure how to edit my code to fix this.
from itertools import product, combinations
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
def d(kx,ky):
M = 1
B = 1
vf = 1
kxx,kyy = np.meshgrid(kx,ky)
x = (vf*kxx)/(np.sqrt(((((vf**2)*(kxx**2)))+((vf**2)*(kyy**2))+(M-B*(kxx**2+(kyy**2)))**2)))
y = (vf*kxx)/(np.sqrt(((((vf**2)*(kxx**2)))+((vf**2)*(kyy**2))+(M-B*(kxx**2+(kyy**2)))**2)))
z = (M-B*(kxx**2+(kyy**2)))/(np.sqrt(((((vf**2)*(kxx**2)))+((vf**2)*(kyy**2))+(M-B*(kxx**2+(kyy**2)))**2)))
return x,y,z
kx = np.linspace(-2, 2, 10)
ky = np.linspace(-2, 2, 10)
xi, yi, zi = d(kx,ky)
phi = np.linspace(0, np.pi, 100)
theta = np.linspace(0, 2*np.pi, 100)
phi, theta = np.meshgrid(phi, theta)
x = np.sin(phi) * np.cos(theta)
y = np.sin(phi) * np.sin(theta)
z = np.cos(phi)
fig = plt.figure(figsize=plt.figaspect(1.))
ax = fig.add_subplot(111, projection='3d')
ax.plot_surface(x, y, z, color="w", rstride=1, cstride=1)
ax.scatter(xi,yi,zi,color="k",s=20)
plt.show()
Thank you kindly,
How can one plot a spherical segment, specifically a sphere "slice" in Python?
I know how to plot a sphere surface via
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)
x = 10 * np.outer(np.cos(u), np.sin(v))
y = 10 * np.outer(np.sin(u), np.sin(v))
z = 10 * np.outer(np.ones(np.size(u)), np.cos(v))
ax.plot_surface(x, y, z, rstride=4, cstride=4, color='b')
plt.show()
or some variation of that code, but I'm struggeling to plot only a part of the sphere, leading to an image like the following:
https://en.wikipedia.org/wiki/Spherical_segment#/media/File:LaoHaiKugelschicht1.png
If I vary the code I presented above by manipulating the definitions of u and v, e.g.:
u = np.linspace(0, 2 * np.pi, 20)
v = np.linspace(0, np.pi, 20)
the sphere is still presented as a whole, but with a very poor resolution.
Changing the starting point of the linspace range doens't seem to change anything.
I have figured out something that works for me. Here you go:
q = 0.5 # defines upper starting point of the spherical segment
p = 0.8 # defines ending point of the spherical segment as ratio
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(q, p * np.pi, p * 100)
x = r * np.outer(np.cos(u), np.sin(v)) + x_0
y = r * np.outer(np.sin(u), np.sin(v)) + y_0
z = r * np.outer(np.ones(np.size(u)), np.cos(v)) + z_0
ax.plot_surface(x, y, z, color='b')
Basically I have two graphs and I want to plot them both without overlapping one over the other.
from matplotlib import cm
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X = np.arange(0, 5, 0.05)
Y = np.arange(0, 5, 0.05)
X, Y = np.meshgrid(X, Y)
Z = (np.sin(X) / X) + 2
X1 = np.arange(0, 5, 0.05)
Y1 = np.arange(0, 5, 0.05)
X1, Y1 = np.meshgrid(X1, Y1)
Z1 = (X / X) + 1
ax.plot_surface(X, Y, Z, alpha = 1, rstride=10, cstride=10, cmap=cm.autumn,linewidth=0.5, antialiased=True, zorder = 0.3)
ax.plot_surface(X, Y, Z1, alpha = 1, rstride=10, cstride=10, cmap=cm.winter, linewidth=0.5, antialiased=True, zorder = 0.5)
plt.show()
We can see here that we have two graphs However when viewed at 90 degrees
Why does this happen and how to proceed?
I would like to draw a sphere with points on its surface using Matplotlib. These points shall be connected by a spiral that spirals from one side of the sphere to the other.
To clarify this a little bit the plot should more or less look like this:
Has anyone a tip about how to do this?
Need to know parameters of spiral, formula or set of points.
However I post a code to plot a line with markers on a sphere for your start:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.set_aspect('equal')
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)
x = 1 * np.outer(np.cos(u), np.sin(v))
y = 1 * np.outer(np.sin(u), np.sin(v))
z = 1 * np.outer(np.ones(np.size(u)), np.cos(v))
elev = 10.
rot = 80. / 180. * np.pi
ax.plot_surface(x, y, z, rstride=1, cstride=1, color='y', linewidth=0, alpha=0.5)
# plot lines in spherical coordinates system
a = np.array([-np.sin(elev / 180 * np.pi), 0, np.cos(elev / 180 * np.pi)])
b = np.array([0, 1, 0])
b = b * np.cos(rot) + np.cross(a, b) * np.sin(rot) + a * np.dot(a, b) * (1 - np.cos(rot))
ax.plot(np.sin(u),np.cos(u),0,color='r', linestyle = '-', marker='o', linewidth=2.5)
ax.view_init(elev = elev, azim = 0)
plt.show()
I am having problems with matplotlibs 3dplot. If I plot two 3d objects, the one that is supposed to be in front is sometimes in the back. Take for example the following code
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as pl
import numpy as np
fig = pl.figure()
ax = fig.add_subplot(111, projection='3d')
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)
X = 10 * np.outer(np.cos(u), np.sin(v))
Y = 10 * np.outer(np.sin(u), np.sin(v))
Z = 10 * np.outer(np.ones(np.size(u)), np.cos(v))
ax.plot_surface(X+10,Y,Z, rstride=4, cstride=4, color='b')
u=np.linspace(-2,2,100)
X = 10 * np.outer(np.ones(len(u)), u)
Y = 10 * np.outer(u, np.ones(len(u)))
Z = 10 * np.zeros((len(u), len(u)))
ax.plot_surface(Z,X,Y, rstride=4, cstride=4, color='b')
pl.show()
It is supposed to plot a plane, with a sphere in from of it, but the sphere appears to be behind the plane.