#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Mesh Volume Computations Helpers
================================
Defines helpers objects related to volume computations.
"""
from __future__ import division, unicode_literals
import numpy as np
from scipy.spatial import Delaunay
__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013-2016 - Colour Developers'
__license__ = 'New BSD License - http://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = 'colour-science@googlegroups.com'
__status__ = 'Production'
__all__ = ['is_within_mesh_volume']
[docs]def is_within_mesh_volume(points, mesh, tolerance=None):
"""
Returns if given points are within given mesh volume using Delaunay
triangulation.
Parameters
----------
points : array_like
Points to check if they are within `mesh` volume.
mesh : array_like
Points of the volume used to generate the Delaunay triangulation.
tolerance : numeric, optional
Tolerance allowed in the inside-triangle check.
Returns
-------
bool
Is within mesh volume.
Examples
--------
>>> mesh = np.array([[-1.0, -1.0, 1.0],
... [1.0, -1.0, 1.0],
... [1.0, -1.0, -1.0],
... [-1.0, -1.0, -1.0],
... [0.0, 1.0, 0.0]])
>>> is_within_mesh_volume(np.array([0.0005, 0.0031, 0.0010]), mesh)
array(True, dtype=bool)
>>> a = np.array([[0.0005, 0.0031, 0.0010],
... [0.3205, 0.4131, 0.5100]])
>>> is_within_mesh_volume(a, mesh)
array([ True, False], dtype=bool)
"""
triangulation = Delaunay(mesh)
simplex = triangulation.find_simplex(points, tol=tolerance)
simplex = np.where(simplex >= 0, True, False)
return simplex