<filename>rowan/random/__init__.py<gh_stars>0
# Copyright (c) 2018 The Regents of the University of Michigan
# All rights reserved.
# This software is licensed under the BSD 3-Clause License.
"""
Various functions for generating random sets of rotation quaternions. Note
that if you simply want random quaternions not restricted to :math:`SO(3)` you
can just generate these directly using ``np.random.rand(... 4)``. This
subpackage is entirely focused on generating rotation quaternions.
"""

# TODO: Try implementing randomness using this paper or one of the ones it
# cites:
#    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896220/
#
#    other alternatives:
#    http://home.lu.lv/~sd20008/papers/essays/Random%20unitary%20[paper].pdf
from __future__ import division, print_function, absolute_import

import numpy as np

__all__ = ['rand',
           'random_sample'
           ]


def rand(*args):
    R"""Generate random rotations that are uniformly distributed on a unit sphere.

    This is a convenience function *a la* ``np.random.rand``. If you want a
    function that takes a tuple as input, use :py:func:`random_sample` instead.

    Args:
        shape (tuple): The shape of the array to generate.

    Return:
        Random quaternions of the shape provided with an additional axis of
        length 4.

    Example::

        q_rand = rowan.random.rand(3, 3, 2)
    """
    if len(args) == 0:
        return random_sample()
    else:
        return random_sample(args)


def random_sample(size=None):
    R"""Generate random rotations uniformly

    In general, sampling from the space of all quaternions will not generate
    uniform rotations. What we want is a distribution that accounts for the
    density of rotations, *i.e.*, a distribution that is uniform with respect
    to the appropriate measure. The algorithm used here is detailed in
    [Shoe92]_.

    .. [Shoe92] Shoemake, K.: Uniform random rotations. In: <NAME>, editor,
        Graphics Gems III, pages 124-132. Academic, New York, 1992.

    Args:
        size (tuple): The shape of the array to generate.

    Return:
        Random quaternions of the shape provided with an additional axis of
        length 4.

    Example::

        q_rand = rowan.random.random_sample((3, 3, 2))
    """
    if size is None:
        size = (3,)
    else:
        size += (3,)

    u = np.random.random_sample(size)

    theta1 = 2*np.pi*u[..., 1]
    s1 = np.sin(theta1)
    c1 = np.cos(theta1)
    theta2 = 2*np.pi*u[..., 2]
    s2 = np.sin(theta2)
    c2 = np.cos(theta2)

    r1 = np.sqrt(1-u[..., 0])
    r2 = np.sqrt(u[..., 0])

    quats = np.stack((s1*r1, c1*r1, s2*r2, c2*r2), axis=-1)
    return quats.squeeze()

<filename>rowan/random/__init__.py<gh_stars>0
# Copyright (c) 2018 The Regents of the University of Michigan
# All rights reserved.
# This software is licensed under the BSD 3-Clause License.
"""
Various functions for generating random sets of rotation quaternions. Note
that if you simply want random quaternions not restricted to :math:`SO(3)` you
can just generate these directly using ``np.random.rand(... 4)``. This
subpackage is entirely focused on generating rotation quaternions.
"""

# TODO: Try implementing randomness using this paper or one of the ones it
# cites:
#    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896220/
#
#    other alternatives:
#    http://home.lu.lv/~sd20008/papers/essays/Random%20unitary%20[paper].pdf
from __future__ import division, print_function, absolute_import

import numpy as np

__all__ = ['rand',
           'random_sample'
           ]


def rand(*args):
    R"""Generate random rotations that are uniformly distributed on a unit sphere.

    This is a convenience function *a la* ``np.random.rand``. If you want a
    function that takes a tuple as input, use :py:func:`random_sample` instead.

    Args:
        shape (tuple): The shape of the array to generate.

    Return:
        Random quaternions of the shape provided with an additional axis of
        length 4.

    Example::

        q_rand = rowan.random.rand(3, 3, 2)
    """
    if len(args) == 0:
        return random_sample()
    else:
        return random_sample(args)


def random_sample(size=None):
    R"""Generate random rotations uniformly

    In general, sampling from the space of all quaternions will not generate
    uniform rotations. What we want is a distribution that accounts for the
    density of rotations, *i.e.*, a distribution that is uniform with respect
    to the appropriate measure. The algorithm used here is detailed in
    [Shoe92]_.

    .. [Shoe92] Shoemake, K.: Uniform random rotations. In: <NAME>, editor,
        Graphics Gems III, pages 124-132. Academic, New York, 1992.

    Args:
        size (tuple): The shape of the array to generate.

    Return:
        Random quaternions of the shape provided with an additional axis of
        length 4.

    Example::

        q_rand = rowan.random.random_sample((3, 3, 2))
    """
    if size is None:
        size = (3,)
    else:
        size += (3,)

    u = np.random.random_sample(size)

    theta1 = 2*np.pi*u[..., 1]
    s1 = np.sin(theta1)
    c1 = np.cos(theta1)
    theta2 = 2*np.pi*u[..., 2]
    s2 = np.sin(theta2)
    c2 = np.cos(theta2)

    r1 = np.sqrt(1-u[..., 0])
    r2 = np.sqrt(u[..., 0])

    quats = np.stack((s1*r1, c1*r1, s2*r2, c2*r2), axis=-1)
    return quats.squeeze()

# Copyright (c) 2018 The Regents of the University of Michigan # All rights reserved. # This software is licensed under the BSD 3-Clause License. Various functions for generating random sets of rotation quaternions. Note that if you simply want random quaternions not restricted to :math:`SO(3)` you can just generate these directly using ``np.random.rand(... 4)``. This subpackage is entirely focused on generating rotation quaternions. # TODO: Try implementing randomness using this paper or one of the ones it # cites: #    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896220/ # #    other alternatives: #    http://home.lu.lv/~sd20008/papers/essays/Random%20unitary%20[paper].pdf Generate random rotations that are uniformly distributed on a unit sphere.      This is a convenience function *a la* ``np.random.rand``. If you want a     function that takes a tuple as input, use :py:func:`random_sample` instead.      Args:         shape (tuple): The shape of the array to generate.      Return:         Random quaternions of the shape provided with an additional axis of         length 4.      Example::          q_rand = rowan.random.rand(3, 3, 2) Generate random rotations uniformly      In general, sampling from the space of all quaternions will not generate     uniform rotations. What we want is a distribution that accounts for the     density of rotations, *i.e.*, a distribution that is uniform with respect     to the appropriate measure. The algorithm used here is detailed in     [Shoe92]_.      .. [Shoe92] Shoemake, K.: Uniform random rotations. In: <NAME>, editor,         Graphics Gems III, pages 124-132. Academic, New York, 1992.      Args:         size (tuple): The shape of the array to generate.      Return:         Random quaternions of the shape provided with an additional axis of         length 4.      Example::          q_rand = rowan.random.random_sample((3, 3, 2))