Generate random array of floats between a range
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
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.