I haven\'t been able to find a function to generate an array of random floats of a given length between a certain range.
I\'ve looked at Random sampling but no funct
Why not to combine random.uniform with a list comprehension?
>>> def random_floats(low, high, size):
... return [random.uniform(low, high) for _ in xrange(size)]
...
>>> random_floats(0.5, 2.8, 5)
[2.366910411506704, 1.878800401620107, 1.0145196974227986, 2.332600336488709, 1.945869474662082]
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.
This is the simplest way
np.random.uniform(start,stop,(rows,columns))
The for loop in list comprehension takes time and makes it slow. It is better to use numpy parameters (low, high, size, ..etc)
import numpy as np
import time
rang = 10000
tic = time.time()
for i in range(rang):
sampl = np.random.uniform(low=0, high=2, size=(182))
print("it took: ", time.time() - tic)
tic = time.time()
for i in range(rang):
ran_floats = [np.random.uniform(0,2) for _ in range(182)]
print("it took: ", time.time() - tic)
sample output:
('it took: ', 0.06406784057617188)
('it took: ', 1.7253198623657227)
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)