xidulu commented on a change in pull request #17302: [numpy]add op
random.logistic, random.gumbel
URL: https://github.com/apache/incubator-mxnet/pull/17302#discussion_r367796729
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File path: python/mxnet/numpy/random.py
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@@ -200,6 +200,192 @@ def normal(loc=0.0, scale=1.0, size=None, dtype=None,
ctx=None, out=None):
return _mx_nd_np.random.normal(loc, scale, size, dtype, ctx, out)
+def logistic(loc=0.0, scale=1.0, size=None):
+ r"""Draw samples from a logistic distribution.
+
+ Samples are drawn from a logistic distribution with specified
+ parameters, loc (location or mean, also median), and scale (>0).
+
+ Parameters
+ ----------
+ loc : float or array_like of floats, optional
+ Parameter of the distribution. Default is 0.
+ scale : float or array_like of floats, optional
+ Parameter of the distribution. Must be non-negative.
+ Default is 1.
+ size : int or tuple of ints, optional
+ Output shape. If the given shape is, e.g., ``(m, n, k)``, then
+ ``m * n * k`` samples are drawn. If size is ``None`` (default),
+ a single value is returned if ``loc`` and ``scale`` are both scalars.
+ Otherwise, ``np.broadcast(loc, scale).size`` samples are drawn.
+
+ Returns
+ -------
+ out : ndarray or scalar
+ Drawn samples from the parameterized logistic distribution.
+
+ See Also
+ --------
+ scipy.stats.logistic : probability density function, distribution or
+ cumulative density function, etc.
+
+ Notes
+ -----
+ The probability density for the Logistic distribution is
+
+ .. math:: P(x) = P(x) = \frac{e^{-(x-\mu)/s}}{s(1+e^{-(x-\mu)/s})^2},
+
+ where :math:`\mu` = location and :math:`s` = scale.
+
+ The Logistic distribution is used in Extreme Value problems where it
+ can act as a mixture of Gumbel distributions, in Epidemiology, and by
+ the World Chess Federation (FIDE) where it is used in the Elo ranking
+ system, assuming the performance of each player is a logistically
+ distributed random variable.
+
+ References
+ ----------
+ .. [1] Reiss, R.-D. and Thomas M. (2001), "Statistical Analysis of
+ Extreme Values, from Insurance, Finance, Hydrology and Other
+ Fields," Birkhauser Verlag, Basel, pp 132-133.
+ .. [2] Weisstein, Eric W. "Logistic Distribution." From
+ MathWorld--A Wolfram Web Resource.
+ http://mathworld.wolfram.com/LogisticDistribution.html
+ .. [3] Wikipedia, "Logistic-distribution",
+ https://en.wikipedia.org/wiki/Logistic_distribution
+
+ Examples
+ --------
+ Draw samples from the distribution:
+
+ >>> loc, scale = 10, 1
+ >>> s = np.random.logistic(loc, scale, 10000)
+ >>> import matplotlib.pyplot as plt
+ >>> count, bins, ignored = plt.hist(s, bins=50)
+
+ # plot against distribution
+
+ >>> def logist(x, loc, scale):
+ ... return np.exp((loc-x)/scale)/(scale*(1+np.exp((loc-x)/scale))**2)
+ >>> lgst_val = logist(bins, loc, scale)
+ >>> plt.plot(bins, lgst_val * count.max() / lgst_val.max())
+ >>> plt.show()
+ """
+ return _mx_nd_np.random.logistic(loc, scale, size)
+
+
+def gumbel(loc=0.0, scale=1.0, size=None):
+ r"""Draw samples from a Gumbel distribution.
+
+ Draw samples from a Gumbel distribution with specified location and
+ scale. For more information on the Gumbel distribution, see
+ Notes and References below.
+
+ Parameters
+ ----------
+ loc : float or array_like of floats, optional
+ The location of the mode of the distribution. Default is 0.
+ scale : float or array_like of floats, optional
+ The scale parameter of the distribution. Default is 1. Must be non-
+ negative.
+ size : int or tuple of ints, optional
+ Output shape. If the given shape is, e.g., ``(m, n, k)``, then
+ ``m * n * k`` samples are drawn. If size is ``None`` (default),
+ a single value is returned if ``loc`` and ``scale`` are both scalars.
+ Otherwise, ``np.broadcast(loc, scale).size`` samples are drawn.
+
+ Returns
+ -------
+ out : ndarray or scalar
+ Drawn samples from the parameterized Gumbel distribution.
+
+ See Also
Review comment:
Remove this section.
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