python - Difference between functions generating random numbers in numpy -

i trying understand difference, if any, between these functions:

numpy.random.rand()  numpy.random.random()  numpy.random.uniform() 

it seems produce random sample uniform distribution. so, without parameter in function, there difference?

numpy.random.uniform(low=0.0, high=1.0, size=none) - uniform samples arbitrary range

draw samples uniform distribution.
samples uniformly distributed on half-open interval [low, high) (includes low, excludes high). in other words, value within given interval equally drawn uniform.

numpy.random.random(size=none) - uniform distribution between 0 , 1

return random floats in half-open interval [0.0, 1.0).
results “continuous uniform” distribution on stated interval. sample unif[a, b), b > a multiply output of random_sample by (b-a) , add a:
(b - a) * random_sample() + a

numpy.random.rand(d0, d1, ..., dn) - samples uniform distribution populate array of given shape

random values in given shape.
create array of given shape , propagate random samples uniform distribution on [0, 1).

to answer other question, given default parameters of functions numpy.random.uniform, numpy.random.random, , numpy.random.rand identical.