mxnet.np.random.power¶
-
power
(a, size=None, device=None, out=None)¶ Draw samples in [0, 1] from a power distribution with given parameter a.
- Parameters
a (float or array_like of floats) – Shape of the distribution. Must be > 0.
size (int or tuple of ints, optional) – Output shape. If the given shape is, e.g.,
(m, n, k)
, thenm * n * k
samples are drawn. If size isNone
(default), a single value is returned ifa
is a scalar. Otherwise,np.array(a).size
samples are drawn.
- Returns
out – Drawn samples from the power distribution.
- Return type
ndarray or scalar
Examples
>>> np.random.power(a=5) array(0.8602478) >>> np.random.power(a=5, size=[2,3]) array([[0.988391 , 0.5153122 , 0.9383134 ], [0.9078098 , 0.87819266, 0.730635]]) >>> np.random.power(a=np.array([2,3]) array([0.7499419 , 0.88894516]) The probability density function is f(x; a) = ax^{a-1}, 0 \le x \le 1, a>0. The power distribution is just the inverse of the Pareto distribution and a special case of the Beta distribution.
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