Generate random array of floats between a range

Question

np.random.uniform fits your use case:

sampl = np.random.uniform(low=0.5, high=13.3, size=(50,))

Update Oct 2019:

While the syntax is still supported, it looks like the API changed with NumPy 1.17 to support greater control over the random number generator. Going forward the API has changed and you should look at https://docs.scipy.org/doc/numpy/reference/random/generated/numpy.random.Generator.uniform.html

The enhancement proposal is here: https://numpy.org/neps/nep-0019-rng-policy.html

Why not use a list comprehension?

In Python 2

ran_floats = [random.uniform(low,high) for _ in xrange(size)]

In Python 3, range works like xrange(ref)

ran_floats = [random.uniform(low,high) for _ in range(size)]

There may already be a function to do what you're looking for, but I don't know about it (yet?). In the meantime, I would suggess using:

ran_floats = numpy.random.rand(50) * (13.3-0.5) + 0.5

This will produce an array of shape (50,) with a uniform distribution between 0.5 and 13.3.

You could also define a function:

def random_uniform_range(shape=[1,],low=0,high=1):
    """
    Random uniform range

    Produces a random uniform distribution of specified shape, with arbitrary max and
    min values. Default shape is [1], and default range is [0,1].
    """
    return numpy.random.rand(shape) * (high - min) + min

EDIT: Hmm, yeah, so I missed it, there is numpy.random.uniform() with the same exact call you want! Try import numpy; help(numpy.random.uniform) for more information.

Alternatively you could use SciPy

from scipy import stats
stats.uniform(0.5, 13.3).rvs(50)

and for the record to sample integers it's

stats.randint(10, 20).rvs(50)