numpy generate reproducible random floats in a range-CodePudding

With numpy, how can I generate an array of random floats within a range?

Say I'd like to generate floats within 8 to 10. The seed is set

eg = np.random.default_rng(567)

how can I generate floats with eg?

CodePudding user response：

You can do it by setting a seed to an existing random number generator by calling np.random.seed(567) each time you want to restart the sequence.

If you'd like to create a new Generator, you can do it as in your question:

rng = np.random.default_rng(seed=567)

Then, you can sample random numbers just by calling uniform method which takes min, max and size parameters. In your case:

size = (3, 4)
rng.uniform(8, 10, size)

will return an array with 3 row and 4 columns that consists of floats between 8 and 10. Apart from uniform distribution there are many more predefined ones that are accessible the same way as uniform (https://numpy.org/doc/stable/reference/random/generator.html#distributions).

You can also do it with random that also can take an argument of size. In your case:

rng.random(size) * 2   8

will do the same.

CodePudding user response：

np.random.random() generates floats between 0 and 1. So, multiply by 2 and add 8.

def make_8_10():
    return np.random.random() * 2   8