Source code for colour.volume.mesh

# -*- coding: utf-8 -*-
"""
Mesh Volume Computation Helpers
===============================

Defines the helpers objects related to volume computations.
"""

import numpy as np
from scipy.spatial import Delaunay

__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013-2021 - Colour Developers'
__license__ = 'New BSD License - https://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = 'colour-developers@colour-science.org'
__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