matplotlib not displaying intersection of 3D planes correctly [duplicate]

Question

I want to plot two planes and find their intersection line, but I get this result, where it's impossible to tell where they intersect, because one plane overlays the other.

A 3D projection should hide the non-visible part of the plane, how do I attain this result using matplotlib?

You can clearly see that these to plains should intersect.

Here's the code I've used to get this result

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

values = range(-10, 11)

def plotPlane(plot, normal, d, values, colorName):
    # x, y, z
    x, y = np.meshgrid(values, values)
    z = (-normal[0] * x - normal[1] * y - d) * 1. / normal[2]

    # draw plot
    plot.plot_surface(x, y, z, color=colorName)

image = plt.figure().gca(projection='3d')

plotPlane(image, [3, 2, -4], 1, values, "red")
plotPlane(image, [5, -1, 2], 4, values, "gray")

plt.show()

Extradite

See my answer here. – Oddity

Answer 1

See How to draw intersecting planes? for a long explanation + possible work around.

The short answer in that matplotlib's 3D support is clever use of projections to generate a 2D view of the 3D object which is then rendered to the canvas. Due to the way that matplotlib renders (artist at a time) one artist is either fully above or fully below another. If you need real 3D support look into mayavi.

Per

Thanks! I've took a huge detour into MATLAB, as far as I can tell, it's straight 3D. But I'll check out mayavi too. – Extradite

I am confused, where did MATLAB come into this? – Per

matplotlib is a tool, MATLAB is a tool, so I'm just switching tools. – Extradite

this answer i posted a while ago is a better way of doing this. – Oddity

Answer 2

Use plotly. You will get an interactive plot which you will be able to snapshot at any angle.

import numpy as np
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from typing import Tuple, Iterable


def plotPlane(fig: go.Figure,
              normal: Tuple[int, int, int],
              d: int,
              values: Iterable,
              colorScaleName: str) -> None:
    """
        :param fig: figure to plot on
        :param colorScaleName: choose from <https://plotly.com/javascript/colorscales/>
    """
    # x, y, z
    x, y = np.meshgrid(values, values)
    z = (-normal[0] * x - normal[1] * y - d) * 1. / normal[2]

    # draw plane
    surface = go.Surface(x=x, y=y, z=z, colorscale=colorScaleName, showscale=False)
    fig.add_trace(surface, row=1, col=1)


# create figure
fig = make_subplots(rows=1, cols=1, specs=[[{'type': 'surface'}]])
# plot two intersectioned surfaces
values = range(-10, 11)
plotPlane(fig, (3, 2, -4), 1, values, "Hot")
plotPlane(fig, (5, -1, 2), 4, values, "Greys")
fig.show()

I ran it in jupyter-notebbok.

Wolfenbarger

Epic example! But please add from plotly.subplots import make_subplots – Varia