python - Vertically fill 3d matplotlib plot

Question

I have a 3d plot made using matplotlib. I now want to fill the vertical space between the drawn line and the x,y axis to highlight the height of the line on the z axis. On a 2d plot this would be done with fill_between but there does not seem to be anything similar for a 3d plot. Can anyone help?

here is my current code

from stravalib import Client
import matplotlib as mpl
import numpy as np
import matplotlib.pyplot as plt

... code to get the data ....

mpl.rcParams['legend.fontsize'] = 10

fig = plt.figure()
ax = fig.gca(projection='3d')
zi = alt
x = df['x'].tolist()
y = df['y'].tolist()
ax.plot(x, y, zi, label='line')
ax.legend()
plt.show()     

and the current plot

just to be clear I want a vertical fill to the x,y axis intersection NOT this...

Answer 1

You're right. It seems that there is no equivalent in 3D plot for the 2D plot function fill_between. The solution I propose is to convert your data in 3D polygons. Here is the corresponding code:

import math as mt
import matplotlib.pyplot as pl
import numpy as np
import random as rd

from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection


# Parameter (reference height)
h = 0.0

# Code to generate the data
n = 200
alpha = 0.75 * mt.pi
theta = [alpha + 2.0 * mt.pi * (float(k) / float(n)) for k in range(0, n + 1)]
xs = [1.0 * mt.cos(k) for k in theta]
ys = [1.0 * mt.sin(k) for k in theta]
zs = [abs(k - alpha - mt.pi) * rd.random() for k in theta]

# Code to convert data in 3D polygons
v = []
for k in range(0, len(xs) - 1):
    x = [xs[k], xs[k+1], xs[k+1], xs[k]]
    y = [ys[k], ys[k+1], ys[k+1], ys[k]]
    z = [zs[k], zs[k+1],       h,     h]
    #list is necessary in python 3/remove for python 2
    v.append(list(zip(x, y, z))) 
poly3dCollection = Poly3DCollection(v)

# Code to plot the 3D polygons
fig = pl.figure()
ax = Axes3D(fig)
ax.add_collection3d(poly3dCollection)
ax.set_xlim([min(xs), max(xs)])
ax.set_ylim([min(ys), max(ys)])
ax.set_zlim([min(zs), max(zs)])
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.set_zlabel("z")

pl.show()

It produces the following figure:

I hope this will help you.