refer to this tutorial: <http://matplotlib.org/1.4.0/examples/pylab_examples/contour_demo.html>

Here is the prototype for the bivariate\_normal function from mplotlib.mlab:

```
bivariate_normal(X, Y, sigmax=1.0, sigmay=1.0, mux=0.0, muy=0.0, sigmaxy=0.0)

```

X and Y define the grid, and we have arguments for the 2 dimensional means and covariance terms.
As you can see, there is an argument at the end for a the covariance between x and y. Here's the thing:
plt.contour() will plot bivariate normal contours if sigmaxy = 0. However, if sigmaxy has any other value, I get a 

```
ValueError: zero-size array to reduction operation minimum which has no identity

```

For example,

```
Z =  bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0, 0.0)
plt.contour(X,Y,Z)

```

works

But, the following does not work:

```
Z = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0, 1.0)
plt.contour(X,Y,Z)

```

Anyone familiar with matplotlib have any ideas? Thanks.