3D plot with Matplotlib

Question

I'm simply trying to plot a surface and its contour in 3D, exactly as in this example.

This is the code I'm using to do it:

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

def plot_3d_contour(x_dim, y_dim, x_steps, y_steps, scalar_field, file_path):
    fig = plt.figure()

    x, y = numpy.mgrid[-x_dim/2:x_dim/2:x_steps*1j, -y_dim/2:y_dim/2:y_steps*1j]
    v_min = numpy.min(scalar_field)
    v_max = nupmy.max(scalar_field)

    ax = fig.gca(projection='3d')

    cset = ax.contourf(x, y, scalar_field, zdir='z', offset=v_min, cmap=cm.coolwarm)
    cset = ax.contourf(x, y, scalar_field, zdir='x', offset=-x_dim/2-1, cmap=cm.coolwarm)
    cset = ax.contourf(x, y, scalar_field, zdir='y', offset=y_dim/2+1, cmap=cm.coolwarm)

    ax.plot_surface(x, y, scalar_field, rstride=10, cstride=10, alpha=0.3)

    ax.set_xlabel('X')
    ax.set_xlim(-x_dim/2-1, x_dim/2+1)
    ax.set_ylabel('Y')
    ax.set_ylim(-y_dim/2-1, y_dim/2+1)
    ax.set_zlabel('Z')
    ax.set_zlim(v_min, v_max)

    plt.savefig(file_path + '.jpg')
    plt.close()

scalar_field = numpy.loadtxt('../scalar_field', delimiter=",")
plot_3d_contour(12, 12, 100, 100, scalar_field, 'scalar_field3D')

However, I'm getting a weird behavior in which the a contour ( zdir=y ) is being over the surface. Besides, I'm getting a weird contour in z_dir=z (with a section missing):

I'm wondering what I'm missing. The scalar field can be found here .

Answer 1

I agree with Ajean. I believe the problem arises because each matplotlib's artist (ie PolygonCollection ) is rendered separately. There is no way different faces from the same object to be rendered on different sides of another object in the scene.

Here is a useful piece of code :

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

file_path = "./3D_surface_and_contour.jpg"
p = 0.05
f = -0.01

def get_data(p):
    x, y, z = axes3d.get_test_data(p)
    z = f * z
    return x, y, z

def plot_3d_contour(p, f):
    nrows = 4
    ncols = 5

    x, y, z = get_data(p)

    x_min, x_max = np.min(x), np.max(x)
    y_min, y_max = np.min(y), np.max(y)
    z_min, z_max = np.min(z), np.max(z)

    fig = plt.figure(figsize=(15, 10))
    for n in range(nrows * ncols):
        i = n % ncols
        j = n / ncols
        k = n + 1
        if j == 0:
            azim = -60 + (i - 2) * 15
            elev = 30
        elif j == 1:
            azim = -60
            elev = 30 + (i - 2) * 5
        elif j == 2:
            azim = 60 + (i - 2) * 10
            elev = 30
        elif j == 3:
            azim = 60
            elev = 30 + (i - 2) * 5
        ax = fig.add_subplot(nrows, ncols, k, projection='3d')
        ax.set_title("azim=" + str(azim) + " elev=" + str(elev))
        ax.tick_params(labelsize=8)
        ax.view_init(azim=azim, elev=elev)
        ax.plot_surface(x, y, z, rstride=10, cstride=10, alpha=0.3)
        ax.contourf(x, y, z, zdir='z', offset=z_min, cmap=cm.coolwarm)
        ax.contourf(x, y, z, zdir='x', offset=x_min, cmap=cm.coolwarm)
        if j == 0 or j == 1:
            ax.contourf(x, y, z, zdir='y', offset=y_max, cmap=cm.coolwarm)
        elif j == 2 or j == 3:
            ax.contourf(x, y, z, zdir='y', offset=y_min, cmap=cm.coolwarm)

        ax.set_xlabel('X')
        ax.set_xlim(x_min, x_max)
        ax.set_ylabel('Y')
        ax.set_ylim(y_min, y_max)
        ax.set_zlabel('Z')
        ax.set_zlim(z_min, z_max)

    plt.savefig(file_path, dpi=80)
    plt.close()

plot_3d_contour(p, f)

which gives the following image :

The first two rows are produced by a code similar to yours. You might notice that setting the elevation with view_init to a higher value solve the problem. But it is not satisfactory. I have also determined the influence of the range of the z-values (not shown here), the bug seems to appear only when this range is small (you can use the f parameter to test it) which explain why the example does not suffer from it.

The solution I propose is to replace :

ax.contourf(x, y, scalar_field, zdir='y', offset=y_dim/2+1, cmap=cm.coolwarm)

by :

ax.contourf(x, y, scalar_field, zdir='y', offset=-y_dim/2-1, cmap=cm.coolwarm)

in your code and add this additional line :

ax.view_init(azim=60, elev=30)

As shown in the last two rows of the previous image, this way you will be able to avoid the whims of matplotlib.