Source code for gudhi.euclidean_witness_complex

# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
# Author(s):       Vincent Rouvreau
#
# Copyright (C) 2016 Inria
#
# Modification(s):
#   - 2025/03 Vincent Rouvreau: Use nanobind instead of Cython for python bindings.
#   - 2025/04 Hannah Schreiber: Re-add possibility of tensors (numpy, torch etc.) as input.
#   - YYYY/MM Author: Description of the modification

__license__ = "GPL v3"


from gudhi import _euclidean_witness_complex_ext as t
from gudhi.simplex_tree import SimplexTree


# EuclideanWitnessComplex python interface


class EuclideanWitnessComplex(t.Euclidean_witness_complex_interface):
    """Constructs (weak) witness complex for given sets of witnesses and
    landmarks in Euclidean space.
    """



    def __init__(self, landmarks=None, witnesses=None):
        """WitnessComplex constructor.

        :param landmarks: A list of landmarks (in the point cloud).
        :type landmarks (Sequence[Sequence[float]]): list of list of double

        :param witnesses: The point cloud.
        :type witnesses (Sequence[Sequence[float]]): list of list of double
        """
        if landmarks is None or witnesses is None:
            super().__init__()
        else:
            super().__init__(landmarks, witnesses)




    def create_simplex_tree(self, max_alpha_square, limit_dimension=-1):
        """
        :param max_alpha_square: The maximum alpha square threshold the
            simplices shall not exceed. Default is set to infinity.
        :type max_alpha_square: float
        :param limit_dimension: Represents the maximal dimension of the simplicial complex.
            Default value (-1) means no limit.
        :type limit_dimension: int
        :returns: A simplex tree created from the Delaunay Triangulation.
        :rtype: SimplexTree
        """
        stree = SimplexTree()
        if limit_dimension != -1:
            super().create_simplex_tree(stree, max_alpha_square, limit_dimension)
        else:
            super().create_simplex_tree(stree, max_alpha_square)
        return stree