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numpy.random.Generator.dirichlet

method

Generator.dirichlet(alpha, size=None)

Draw samples from the Dirichlet distribution.

Draw size samples of dimension k from a Dirichlet distribution. A Dirichlet-distributed random variable can be seen as a multivariate generalization of a Beta distribution. The Dirichlet distribution is a conjugate prior of a multinomial distribution in Bayesian inference.

Parameters:	`alpha : array` Parameter of the distribution (k dimension for sample of dimension k). `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. Default is None, in which case a single value is returned.
Returns:	`samples : ndarray,` The drawn samples, of shape (size, alpha.ndim).
Raises:	ValueError If any value in alpha is less than or equal to zero

Notes

The Dirichlet distribution is a distribution over vectors $x$ that fulfil the conditions $x_i>0$ and $\sum_{i=1}^k x_i = 1$ .

The probability density function $p$ of a Dirichlet-distributed random vector $X$ is proportional to

$p(x) \propto \prod_{i=1}^{k}{x^{\alpha_i-1}_i},$

where $\alpha$ is a vector containing the positive concentration parameters.

The method uses the following property for computation: let $Y$ be a random vector which has components that follow a standard gamma distribution, then $X = \frac{1}{\sum_{i=1}^k{Y_i}} Y$ is Dirichlet-distributed

References

[1]	David McKay, “Information Theory, Inference and Learning Algorithms,” chapter 23, http://www.inference.org.uk/mackay/itila/

[2]	Wikipedia, “Dirichlet distribution”, https://en.wikipedia.org/wiki/Dirichlet_distribution

Examples

Taking an example cited in Wikipedia, this distribution can be used if one wanted to cut strings (each of initial length 1.0) into K pieces with different lengths, where each piece had, on average, a designated average length, but allowing some variation in the relative sizes of the pieces.

>>> s = np.random.default_rng().dirichlet((10, 5, 3), 20).transpose()

>>> import matplotlib.pyplot as plt
>>> plt.barh(range(20), s[0])
>>> plt.barh(range(20), s[1], left=s[0], color='g')
>>> plt.barh(range(20), s[2], left=s[0]+s[1], color='r')
>>> plt.title("Lengths of Strings")

../../../_images/numpy-random-Generator-dirichlet-1.png

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https://docs.scipy.org/doc/numpy-1.17.0/reference/random/generated/numpy.random.Generator.dirichlet.html