# How to plot a gradient color line

Note that if you have many points, calling `plt.plot` for each line segment can be quite slow. It’s more efficient to use a LineCollection object.

Using the `colorline` recipe you could do the following:

``````import matplotlib.pyplot as plt
import numpy as np
import matplotlib.collections as mcoll
import matplotlib.path as mpath

def colorline(
x, y, z=None, cmap=plt.get_cmap('copper'), norm=plt.Normalize(0.0, 1.0),
linewidth=3, alpha=1.0):
"""
http://nbviewer.ipython.org/github/dpsanders/matplotlib-examples/blob/master/colorline.ipynb
http://matplotlib.org/examples/pylab_examples/multicolored_line.html
Plot a colored line with coordinates x and y
Optionally specify colors in the array z
Optionally specify a colormap, a norm function and a line width
"""

# Default colors equally spaced on [0,1]:
if z is None:
z = np.linspace(0.0, 1.0, len(x))

# Special case if a single number:
if not hasattr(z, "__iter__"):  # to check for numerical input -- this is a hack
z = np.array([z])

z = np.asarray(z)

segments = make_segments(x, y)
lc = mcoll.LineCollection(segments, array=z, cmap=cmap, norm=norm,
linewidth=linewidth, alpha=alpha)

ax = plt.gca()
ax.add_collection(lc)

return lc

def make_segments(x, y):
"""
Create list of line segments from x and y coordinates, in the correct format
for LineCollection: an array of the form numlines x (points per line) x 2 (x
and y) array
"""

points = np.array([x, y]).T.reshape(-1, 1, 2)
segments = np.concatenate([points[:-1], points[1:]], axis=1)
return segments

N = 10
np.random.seed(101)
x = np.random.rand(N)
y = np.random.rand(N)
fig, ax = plt.subplots()

path = mpath.Path(np.column_stack([x, y]))
verts = path.interpolated(steps=3).vertices
x, y = verts[:, 0], verts[:, 1]
z = np.linspace(0, 1, len(x))
colorline(x, y, z, cmap=plt.get_cmap('jet'), linewidth=2)

plt.show()
``````