It’s easiest to use a LineCollection
for this. In fact, it expects the lines to be in a similar format to what you already have. To color the lines by a third variable, just specify the array=floats_list
. As an example:
import numpy
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
# The line format you curently have:
lines = [[(0, 1, 2, 3, 4), (4, 5, 6, 7, 8)],
[(0, 1, 2, 3, 4), (0, 1, 2, 3, 4)],
[(0, 1, 2, 3, 4), (8, 7, 6, 5, 4)],
[(4, 5, 6, 7, 8), (0, 1, 2, 3, 4)]]
# Reformat it to what `LineCollection` expects:
lines = [zip(x, y) for x, y in lines]
z = np.array([0.1, 9.4, 3.8, 2.0])
fig, ax = plt.subplots()
lines = LineCollection(lines, array=z, cmap=plt.cm.rainbow, linewidths=5)
ax.add_collection(lines)
fig.colorbar(lines)
# Manually adding artists doesn't rescale the plot, so we need to autoscale
ax.autoscale()
plt.show()
There are two main advantages of this over repeatedly calling plot
.
- Rendering speed.
Collections
render much faster than a large number of similar artists. - It’s easier to color the data by another variable according to a colormap (and/or update the colormap later).