Incidentally, if anyone else wants to do this and is unable to update their
matplotlib to v1.2.0, this code snippet achieves the same effect.
#######################################
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
# the line to plot
x = np.linspace(0,1,101)
y = x*0.5-0.25
scaling = np.exp(-(x-0.5)**2/0.5**2) # scale the transparency of the line
according to this
points = np.array([x, y]).T.reshape(-1, 1, 2)
segments = np.concatenate([points[:-1], points[1:]], axis=1)
smin = scaling.min()
smax = scaling.max()
# inline function to convert scaling value to alpha value in [0,1]
alpha = lambda s0: (s0-smin)/(smax-smin)
# create a (r,g,b,a) color description for each line segment
cmap = []
for a in segments:
# the x-value for this segment is:
x0 = a.mean(0)[0]
# so it has a scaling value of:
s0 = np.interp(x0,x,scaling)
# and it has an alpha value of:
a0 = alpha(s0)
cmap.append([0.0,0.0,0.0,a0])
# Create the line collection object, and set the color parameters.
lc = LineCollection(segments)
lc.set_color(cmap)
ax = plt.subplot(111)
ax.add_collection(lc)
ax.set_xlim(x.min(), x.max())
ax.set_ylim(y.min(), y.max())
plt.show()
#######################################
------------------------------------------------------------------------------
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