Create an rng object with np.random.default_rng(), you can seed it for reproducible results. You can draw samples from probability distributions, including from the binomial and normal distributions.

Making random numbers is a hot business in computer science. Graphics and cryptography, in particular, rely on randomness or at least randomness that’s good enough to fool users/hackers/gamers. Mostly ...

The NumPy 2.5.0 release notes state that the return values of eig and eigvals will always be complex, and that ...

To simulate chance occurrences, a computer can’t literally toss a coin or roll a die. Instead, it relies on special numerical recipes for generating strings of shuffled digits that pass for random ...