Plot multiple lines with matplotlib, using only 3 lists/arrays - matplotlib

Question

I would like to plot say 10 lines in 3D in matplotlib, but without having to use ax.plot(x,y,z) 10 times.
This is the ridiculous code I've come up with b/c I can't envision how the zip and arrays actually work together.
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = np.array([0.,3.])
y = np.array([0.,0.])
z = np.array([0.,0.])
u = np.array([0.,3.])
v = np.array([.5,.5])
w = np.array([0.,0.])
a = np.array([0.,3.])
b = np.array([1.,1.])
c = np.array([0.,0.])
e = np.array([0.,3.])
d = np.array([1.5,1.5])
f = np.array([0.,0.])
r = np.array([0.,3.])
s = np.array([2.,2.])
t = np.array([0.,0.])
ax.set_xlabel("x axis")
ax.set_ylabel("y axis")
ax.set_zlabel("z axis")
ax.plot(x,y,z)
ax.plot(a,b,c)
ax.plot(r,s,t)
ax.plot(u,v,w)
ax.plot(e,d,f)
plt.show()
I'm guessing I'll use zip and/or a for loop.
Thanks, and here's the figure.

Answer 1

You could store all your data points in a large data array. This way you can loop over the array and do something like this:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
# initialize array with size number of lines
data = np.full((2,3), None)
# fill data array with data points [x,y,z]
data[0] = [[0,3],[0,0],[0,0]]
data[1] = [[0,3],[0.5,0.5],[0,0]]
# etc...
# loop over data array and plot lines
for line in data:
ax.plot(line[0],line[1],line[2])
plt.show()
There are many different ways on how to store your data, you could also skip the initialization step by just creating the array in one take:
data = np.array([[[0,3],[0,0],[0,0]],
[[0,3],[0.5,0.5],[0,0]],
[[0,3],[0.5,0.5],[0,0]],
[...] ])
Or use numpy functions like numpy.concatenate to add new lines to the data array.