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Is it possible to disable the perspective when plotting in mplot3d, i.e. to use the orthogonal projection?

user3670781
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2 Answers2

35

This is now official included since matplot version 2.2.2 Whats new | github

So for plotting a perspective orthogonal plot you have to add proj_type = 'ortho' then you should have something like that:

fig.add_subplot(121, projection='3d', proj_type = 'ortho')

Example Picture

3D Plot of Example Code]2 Example is taken from the official example script and edited

'''
======================
3D surface (color map)
======================

Demonstrates plotting a 3D surface colored with the coolwarm color map.
The surface is made opaque by using antialiased=False.

Also demonstrates using the LinearLocator and custom formatting for the
z axis tick labels.
'''

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import numpy as np

# Make data.
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)

# Plot the surface.
fig = plt.figure(figsize=(16,4))
ax.view_init(40, 60)
ax = fig.add_subplot(121, projection='3d')
surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
                       linewidth=0, antialiased=False)
ax.set_zlim(-1.01, 1.01)
ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))


ax = fig.add_subplot(122, projection='3d', proj_type = 'ortho')
# Plot the surface.
surf = ax.plot_surface(X, Y, Z, cmap=cm.viridis, linewidth=0, antialiased=False)
ax.set_zlim(-1.01, 1.01)
ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

plt.show()
TimK
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12

NOTE: This has been updated see this answer instead.

Sort of, you can run this snippet of code before you plot:

import numpy
from mpl_toolkits.mplot3d import proj3d
def orthogonal_proj(zfront, zback):
    a = (zfront+zback)/(zfront-zback)
    b = -2*(zfront*zback)/(zfront-zback)
    return numpy.array([[1,0,0,0],
                        [0,1,0,0],
                        [0,0,a,b],
                        [0,0,0,zback]])
proj3d.persp_transformation = orthogonal_proj

It is currently an open issue found here.

Dair
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  • It worked, thanks! The axes directions look opposite though, but this could probably be solved playing with the signs/order in this transformation matrix. – user3670781 May 26 '14 at 00:01
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    It seems, that putting a small negative number (e.g. -0.0001) instead of zero in the third column of the last row helps avoiding matrix singularity problems, and solves a strange inversion of axes direction. – user3670781 May 26 '14 at 00:16
  • @user3670781 Adding the small neg number helped! Thanks :-) – Ashwin Nanjappa Nov 13 '14 at 02:00
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    and how can I go back to the prospective view after that ? – Ahmad Sultan Feb 20 '17 at 00:56
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    @AhmadSultan: I would guess you need to store the original projection before replacing it, something like `persp_proj = proj3d.persp_transformation` before assigning `orthogonal_proj` to it. But starting version 2.2.2 you can just set_proj_type('persp'). – danuker Jul 20 '19 at 14:49
  • See **[newer answer](https://stackoverflow.com/a/49856771/3904031)!** – uhoh Jun 11 '20 at 09:16
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    @uhoh I have added a note at the top to look at the answer below. – Dair Jun 11 '20 at 22:55