Naive Bayes: Divide by Zero error
Although I haven't verified it, a first glance at the features and training set you used shows an obvious problem. You have just two data samples with the exact same features while you give it different labels. 

Although other types of models might not break and just give both samples an equal probability of being 0 or 1, something in the Naive Bayes classifier internal calculations probably requires there to be at least some difference in differently labeled samples (not an unreasonable assumption). 

I can't confirm this for myself as I'd have to go deeper into the source code to actually check the scikit implementation so perhaps someone else more familiar with it can check.

EDIT: I just tested this out by changing one line in your code to 

features = np.array([[-1, 1],[-1, 0]])


It worked.