Matplotlib contains the spy method for plotting the sparsity pattern of a matrix. However, the routine does not choose the markersize in any useful way, causing the marker boxes for neighboring elements to either be separated by white space or to overlap, as in the example below (using the 27×27 sparse matrix in sparse.npz):

In [1]:

import matplotlib.pylab as plt
import scipy.sparse
H = scipy.sparse.load_npz('sparse.npz')
fig, ax = plt.subplots(figsize=(3, 3))
ax.spy(H)

Out[1]:

<matplotlib.lines.Line2D at 0x10e87b6a0>

The following custom spy routine generates a similar plot, but uses markers of the correct size by drawing manual rectangles on the canvas.

In [2]:

def spy(m, ax):
    from scipy.sparse import coo_matrix
    from matplotlib.patches import Rectangle
    if not isinstance(m, coo_matrix):
        m = coo_matrix(m)
    for (x, y) in zip(m.col, m.row):
        ax.add_artist(Rectangle(
            xy=(x-0.5, y-0.5), width=1, height=1))
    ax.set_xlim(-0.5, m.shape[1]-0.5)
    ax.set_ylim(-0.5, m.shape[0]-0.5)
    ax.invert_yaxis()
    ax.set_aspect(float(m.shape[0])/float(m.shape[1]))

In [3]:

fig, ax = plt.subplots(figsize=(3, 3))
spy(H, ax)

The ticks mark the center of the marker for each element. Note that the 0-0 element in the top left corner is zero.