This PR adds a discrete colormap / colorbar option to xray plots.

closes #500

``` python import matplotlib.pyplot as plt import numpy as np import xray

sample DataArray

x = np.arange(start=0, stop=10, step=2) y = np.arange(start=9, stop=-7, step=-3) xy = np.dstack(np.meshgrid(x, y)) distance = np.linalg.norm(xy, axis=2) distance = xray.DataArray(distance, list(zip(('y', 'x'), (y, x))))

Sample plots

fig, axes = plt.subplots(2, 2, figsize=(8, 8), sharex=True, sharey=True) distance.plot(ax=axes[0, 0]) axes[0, 0].set_title('Default') distance.plot(vmin=0, vmax=12, levels=6, ax=axes[1, 0]) axes[1, 0].set_title('Setting with integer levels') distance.plot(levels=[1, 2, 4, 5, 7, 9], extend='both', cmap='Spectral', ax=axes[0, 1]) axes[0, 1].set_title('Setting with list of levels') flatui = ["#9b59b6", "#3498db", "#95a5a6", "#e74c3c", "#34495e", "#2ecc71"] distance.plot(levels=[1, 2, 4, 5, 7], cmap=flatui, extend='both', ax=axes[1, 1]) axes[1, 1].set_title('Using custom list of colors') ```

Produces these plots:

There are potential issues that I'd still like to look into a bit further. 1. Does discretizing cmap impact the contour and contourf plot types? We may need some logic to only discretize when the plot type is imshow or pcolormesh. 2. It is possible, in some cases, to end up masking out values equal to vmax:

python distance.plot(levels=6)

Produces this plot:

In the first example, we corrected for this by setting extend='max'.