numpy.random.uniform# random. uniform (low = 0.0, high = 1.0, size = None) # Draw samples from a uniform distribution. Samples are uniformly distributed over the half-open interval [low, high) (includes low, but excludes high). In other words, any value within the given interval is equally likely to be drawn by uniform.

That function takes a tuple to specify the size of the output, which is consistent with other NumPy functions like numpy.zeros and numpy.ones. Create an array of the given shape and populate it with random samples from a uniform distribution over [0, 1). Parameters: d0, d1, …, dn int, optional. The dimensions of the returned array, must be non-negative. If no argument is given a single ...

That function takes a tuple to specify the size of the output, which is consistent with other NumPy functions like numpy.zeros and numpy.ones. Note. New code should use the standard_normal method of a Generator instance instead; please see the Quick start. If positive int_like arguments are provided, randn generates an array of shape (d0, d1,..., dn), filled with random floats sampled from a ...

numpy.random.poisson# random. poisson (lam = 1.0, size = None) # Draw samples from a Poisson distribution. The Poisson distribution is the limit of the binomial distribution for large N. Note. New code should use the poisson method of a Generator instance instead; please see the Quick start. Parameters: lam float or array_like of floats. Expected number of events occurring in a fixed-time ...