np.random.RandomState vs np.rand

np.random.seed

np.random.seed(1234)
np.random.uniform(0, 10, 5)
#array([ 1.9151945 ,  6.22108771,  4.37727739,  7.85358584,  7.79975808])
np.random.rand(2,3)
#array([[ 0.27259261,  0.27646426,  0.80187218],
#       [ 0.95813935,  0.87593263,  0.35781727]])

If you want to use the class, you must save an instance of the class, initiated with a seed: nprandom.RandomState

r = np.random.RandomState(1234)
r.uniform(0, 10, 5)
#array([ 1.9151945 ,  6.22108771,  4.37727739,  7.85358584,  7.79975808])

And it maintains the state just as before:

r.rand(2,3)
#array([[ 0.27259261,  0.27646426,  0.80187218],
#       [ 0.95813935,  0.87593263,  0.35781727]])

You can see the state of the sort of 'global' class with

np.random.get_state()

and of your own class instance with

r.get_state()