Axes3d.plot_wireframe(x,y,z) Error

I'm trying to learn Python through a tutorial on youtube and I'm having some difficulies working with 3D graphs. Long stories short, I continuously get (if Z.ndim != 2: AttributeE

Solution 1:

I walked around this problem by doing two things.

1. import numpy as np
2. making the z-axis a multidimensional array

#My 3d graph

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
import numpy as np

figure = plt.figure()
axis = figure.add_subplot(111, projection = '3d')

x = [1,2,3,4,5,6,7,8,9,10]
y = [5,6,7,8,2,5,6,3,7,2]
z = np.array([[1,2,6,3,2,7,3,3,7,2],[1,2,6,3,2,7,3,3,7,2]])

axis.plot_wireframe(x, y, z)

axis.set_xlabel('x-axis')
axis.set_ylabel('y-axis')
axis.set_zlabel('z-axis')

plt.show()

Take special note of the z variable. If z is not multidimensional, it will throw an error.

Hope it solves your problem

Solution 2:

Running your code with either Python 2.7.10 or Python 3.6.0, with matplotlib version 2.0.2, yields the same image with no error:

This is not a wireframe though, and a simple ax.plot(X, Y, Z) would have generated it. As DavidG and ImportanceOfBeingErnest cleverly mentioned, it makes no sense to pass 1D lists to the wireframe function, as X, Y and Z should be two-dimensional.

The following code (an example taken from the matplotlib official documentation) shows exactly how the parameters of the plot_wireframe function should be (using numpy arrays):

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np

'''
def get_test_data(delta=0.05):

    from matplotlib.mlab import  bivariate_normal
    x = y = np.arange(-3.0, 3.0, delta)
    X, Y = np.meshgrid(x, y)

    Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
    Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
    Z = Z2 - Z1

    X = X * 10
    Y = Y * 10
    Z = Z * 500
    return X, Y, Z

'''


fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

x, y, z = axes3d.get_test_data(0.05)

ax.plot_wireframe(x,y,z, rstride=2, cstride=2)

plt.show()

The output image is a true wireframe:

Printing x.shape, for instance, yields you (120, 120), showing that the array is two-dimensional and have 120 positions in the first dimension and 120 positions in the second one.

Solution 3:

I had the exact problem (example from video not working though exactly copied). Without looking into the source code I'm assuming a reality check was added to matplotlib 2.1.0 that NOW stops 1D arrays from being used in plot_wireframe. Changing that method call to simply "plot" did indeed fix the problem.

Solution 4:

The command ax.plot_wireframe(x,y,z, rstride=2, cstride=2) is creating the problems with the latest versions. Try using:

ax.plot(x,y,z)

This will definitely solve your issues. Python has been known for being inconsistent with the older libraries. I am getting this image as the output: This is the 3d Image I am getting