numpy.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
.
Parameters: |
low : float, optional Lower boundary of the output interval. All values generated will be greater than or equal to low. The default value is 0. high : float Upper boundary of the output interval. All values generated will be less than high. The default value is 1.0. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., |
---|---|
Returns: |
out : ndarray Drawn samples, with shape |
See also
randint
random_integers
[low, high]
.random_sample
[0, 1)
.random
random_sample
.rand
rand(2,2)
would generate a 2-by-2 array of floats, uniformly distributed over [0, 1)
.The probability density function of the uniform distribution is
anywhere within the interval [a, b)
, and zero elsewhere.
Draw samples from the distribution:
>>> s = np.random.uniform(-1,0,1000)
All values are within the given interval:
>>> np.all(s >= -1) True >>> np.all(s < 0) True
Display the histogram of the samples, along with the probability density function:
>>> import matplotlib.pyplot as plt >>> count, bins, ignored = plt.hist(s, 15, normed=True) >>> plt.plot(bins, np.ones_like(bins), linewidth=2, color='r') >>> plt.show()
(Source code, png, pdf)
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Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.random.uniform.html