Difference between various numpy random functions

Question

The numpy.random module defines the following 4 functions that all seem to return a float betweeb [0, 1.0) from the continuous uniform distribution. What (if any) is the difference between these functions?

random_sample([size]) Return random floats in the half-open interval [0.0, 1.0).

random([size]) Return random floats in the half-open interval [0.0, 1.0).

ranf([size]) Return random floats in the half-open interval [0.0, 1.0).

sample([size]) Return random floats in the half-open interval [0.0, 1.0).

--------------------------- Edit Follows ---------------------------------------

I found the following in numpy.random source code that supports @askewchan's answer:

# Some aliases: ranf = random = sample = random_sample __all__.extend(['ranf','random','sample']) 

Answer 1

Nothing.

They're just aliases to random_sample:

In [660]: np.random.random Out[660]: <function random_sample>  In [661]: np.random.ranf Out[661]: <function random_sample>  In [662]: np.random.sample Out[662]: <function random_sample>  In [663]: np.random.random_sample is np.random.random Out[663]: True  In [664]: np.random.random_sample is np.random.ranf Out[664]: True  In [665]: np.random.random_sample is np.random.sample Out[665]: True