`scipy.stats._multivariate:uniform_direction_gen`

source: /scipy/stats/_multivariate.py :6537

Signature

class uniform_direction_gen ( seed = None )

Members

Summary

A vector-valued uniform direction.

Extended Summary

Return a random direction (unit vector). The dim keyword specifies the dimensionality of the space.

Parameters

dim : scalar: Dimension of directions.
seed : {None, int, `numpy.random.Generator`,: numpy.random.RandomState}, optional
Used for drawing random variates. If seed is None, the ~np.random.RandomState singleton is used. If seed is an int, a new RandomState instance is used, seeded with seed. If seed is already a RandomState or Generator instance, then that object is used. Default is None.

Methods

rvs(dim=None, size=1, random_state=None): Draw random directions.

Notes

This distribution generates unit vectors uniformly distributed on the surface of a hypersphere. These can be interpreted as random directions. For example, if dim is 3, 3D vectors from the surface of $S^{2}$ will be sampled.

Examples

import numpy as np
from scipy.stats import uniform_direction
x = uniform_direction.rvs(3)

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np.linalg.norm(x)

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This generates one random direction, a vector on the surface of :math:`S^2`. Alternatively, the object may be called (as a function) to return a frozen distribution with fixed `dim` parameter. Here, we create a `uniform_direction` with ``dim=3`` and draw 5 observations. The samples are then arranged in an array of shape 5x3.

rng = np.random.default_rng()
uniform_sphere_dist = uniform_direction(3)
unit_vectors = uniform_sphere_dist.rvs(5, random_state=rng)

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unit_vectors

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Aliases

scipy.stats._multivariate.uniform_direction_gen