# mx.nd.random.pdf.uniform¶

## Description¶

Computes the value of the PDF of sample of uniform distributions on the intervals given by [low,high).

low and high must have the same shape, which must match the leftmost subshape of sample. That is, sample can have the same shape as low and high, in which case the output contains one density per distribution, or sample can be a tensor of tensors with that shape, in which case the output is a tensor of densities such that the densities at index i in the output are given by the samples at index i in sample parameterized by the values of low and high at index i.

Example:

random_pdf_uniform(sample=[[1,2,3,4]], low=[0], high=[10]) = [0.1, 0.1, 0.1, 0.1]

sample = [[[1, 2, 3],
[1, 2, 3]],
[[1, 2, 3],
[1, 2, 3]]]
low  = [[0, 0],
[0, 0]]
high = [[ 5, 10],
[15, 20]]
random_pdf_uniform(sample=sample, low=low, high=high) =
[[[0.2,        0.2,        0.2    ],
[0.1,        0.1,        0.1    ]],
[[0.06667,    0.06667,    0.06667],
[0.05,       0.05,       0.05   ]]]


## Arguments¶

Argument

Description

sample

NDArray-or-Symbol.

Samples from the distributions.

low

NDArray-or-Symbol.

Lower bounds of the distributions.

is.log

boolean, optional, default=0.

If set, compute the density of the log-probability instead of the probability.

high

NDArray-or-Symbol.

Upper bounds of the distributions.

## Value¶

out The result mx.ndarray