numpy 中范围 [-1,1] 的变换狄利克雷数组 [英] Transformed Dirichlet array with range [-1,1] in numpy

问题描述

从狄利克雷分布中采样的随机向量包含落在域 [0,1] 中的值，并且它们的总和为 1.在 numpy 中，可以像这样对向量大小为 5 进行编程:

A random vector sampled from the Dirichlet distribution contains values that fall in the domain [0,1] and they sum to 1. In numpy it can be programmed like this for a vector size of 5:

x = numpy.random.dirichlet(np.ones(5))

相反，我想要一个包含 [-1,1] 和总和为 1 的值的随机向量，其中 我被告知可以通过转换狄利克雷生成的x 向量为 y = 2x -1

Instead, I would like a random vector that contains values that are [-1,1] and sum to 1, which I was told can be achieved by transforming the Dirichlet generated x vector as y = 2x -1

下面是这种转变的尝试.然而，该脚本无法正常工作，因为 y 根据需要不等于 1.如何修复，或者 y = 2x -1 没有按照他们说的做?

Below is an attempt at this transformation. The script doesn't work properly however because y doesn't sum to 1 as needed. How can it be fixed, or could it be that y = 2x -1 does not do what they said?

x = numpy.random.dirichlet(np.ones(5))
y = 2*x -1
print(x, np.sum(x))
print(y, np.sum(y))

输出:

[0.0209344  0.44791586 0.21002354 0.04107336 0.28005284] 1.0
[-0.9581312  -0.10416828 -0.57995291 -0.91785327 -0.43989433] -3.0000000000000004

推荐答案

尝试 y=1/(dimension/3)-2*x.这对我有用.

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