Question

I have a sequence of line plots for two variables (x,y) for a number of different values of a variable z. I would normally add the line plots with legends like this:

import matplotlib.pyplot as plt

fig = plt.figure()
ax  = fig.add_subplot(111)
# suppose mydata is a list of tuples containing (xs, ys, z) 
# where xs and ys are lists of x's and y's and z is a number. 
legns = []
for(xs,ys,z) in mydata:
   pl = ax.plot(xs,ys,color = (z,0,0))
   legns.append("z = %f"%(z))
ax.legends(legns) 
plt.show()

But I have too many graphs and the legends will cover the graph. I’d rather have a colorbar indicating the value of z corresponding to the color. I can’t find anything like that in the galery and all my attempts do deal with the colorbar failed. Apparently I must create a collection of plots before trying to add a colorbar.

Is there an easy way to do this? Thanks.

EDIT (clarification):

I wanted to do something like this:

import matplotlib.pyplot as plt
import matplotlib.cm     as cm

fig = plt.figure()
ax  = fig.add_subplot(111)
mycmap = cm.hot
# suppose mydata is a list of tuples containing (xs, ys, z) 
# where xs and ys are lists of x's and y's and z is a number between 0 and 1
plots = []
for(xs,ys,z) in mydata:
   pl = ax.plot(xs,ys,color = mycmap(z))
   plots.append(pl)
fig.colorbar(plots)
plt.show()

But this won’t work according to the Matplotlib reference because a list of plots is not a “mappable”, whatever this means.

I’ve created an alternative plot function using LineCollection:

def myplot(ax,xs,ys,zs, cmap):
    plot = lc([zip(x,y) for (x,y) in zip(xs,ys)], cmap = cmap)
    plot.set_array(array(zs))
    x0,x1 = amin(xs),amax(xs)
    y0,y1 = amin(ys),amax(ys)
    ax.add_collection(plot)
    ax.set_xlim(x0,x1)
    ax.set_ylim(y0,y1)
    return plot

xs and ys are lists of lists of x and y coordinates and zs is a list of the different conditions to colorize each line. It feels a bit like a cludge though… I thought that there would be a more neat way to do this. I like the flexibility of the plt.plot() function.

Answer 1

(I know this is an old question but…) Colorbars require a matplotlib.cm.ScalarMappable, plt.plot produces lines which are not scalar mappable, therefore, in order to make a colorbar, we are going to need to make a scalar mappable.

Ok. So the constructor of a ScalarMappable takes a cmap and a norm instance. (norms scale data to the range 0-1, cmaps you have already worked with and take a number between 0-1 and returns a color). So in your case:

import matplotlib.pyplot as plt
sm = plt.cm.ScalarMappable(cmap=my_cmap, norm=plt.normalize(min=0, max=1))
plt.colorbar(sm)

Because your data is in the range 0-1 already, you can simplify the sm creation to:

sm = plt.cm.ScalarMappable(cmap=my_cmap)

EDIT: For matplotlib v1.2 or greater the code becomes:

import matplotlib.pyplot as plt
sm = plt.cm.ScalarMappable(cmap=my_cmap, norm=plt.normalize(vmin=0, vmax=1))
# fake up the array of the scalar mappable. Urgh...
sm._A = []
plt.colorbar(sm)

EDIT: For matplotlib v1.3 or greater the code becomes:

import matplotlib.pyplot as plt
sm = plt.cm.ScalarMappable(cmap=my_cmap, norm=plt.Normalize(vmin=0, vmax=1))
# fake up the array of the scalar mappable. Urgh...
sm._A = []
plt.colorbar(sm)

EDIT: For matplotlib v3.1 or greater simplifies to:

import matplotlib.pyplot as plt
sm = plt.cm.ScalarMappable(cmap=my_cmap, norm=plt.Normalize(vmin=0, vmax=1))
plt.colorbar(sm)