numpy.cov() and numpy.var() default bias are inconsistent (numpy 1.9.2)

cov() uses a bias of 1 by default. var() uses a bias of 0 by default.

Such that

import numpy as np

x = np.random.rand(100)

if np.isclose(np.cov([x,x])[0,0], np.var(x)):
    print("Consistent by default.")

if np.isclose(np.cov([x,x],ddof=0)[0,0], np.var(x,ddof=0))
    print("Consistent.")

will only print the second line.

[AllenDowney]

@rgommers Yeah, “never break valid code” is a pretty good rule.

How about a warning if you call cov without bias or ddof, and then never change the behavior?

[rgommers]

How about a warning if you call cov without bias or ddof, and then never change the behavior?

That does seem like a reasonable thing to do. Better than deprecating cov. Having to add ddof=0/1 is a slight annoyance but makes the code more understandable, so I like the idea.