dask.array.random.random_sample
dask.array.random.random_sample¶
- dask.array.random.random_sample(*args, **kwargs)¶
Return random floats in the half-open interval [0.0, 1.0).
This docstring was copied from numpy.random.mtrand.RandomState.random_sample.
Some inconsistencies with the Dask version may exist.
Results are from the “continuous uniform” distribution over the stated interval. To sample \(Unif[a, b), b > a\) multiply the output of random_sample by (b-a) and add a:
(b - a) * random_sample() + a
Note
New code should use the ~numpy.random.Generator.random method of a ~numpy.random.Generator instance instead; please see the Quick start.
- Parameters
- sizeint or tuple of ints, optional
Output shape. If the given shape is, e.g.,
(m, n, k)
, thenm * n * k
samples are drawn. Default is None, in which case a single value is returned.
- Returns
- outfloat or ndarray of floats
Array of random floats of shape size (unless
size=None
, in which case a single float is returned).
See also
random.Generator.random
which should be used for new code.
Examples
>>> np.random.random_sample() 0.47108547995356098 # random >>> type(np.random.random_sample()) <class 'float'> >>> np.random.random_sample((5,)) array([ 0.30220482, 0.86820401, 0.1654503 , 0.11659149, 0.54323428]) # random
Three-by-two array of random numbers from [-5, 0):
>>> 5 * np.random.random_sample((3, 2)) - 5 array([[-3.99149989, -0.52338984], # random [-2.99091858, -0.79479508], [-1.23204345, -1.75224494]])