This function returns the Betti numbers of the complex. :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). :note: betti

\brief Change the linear transformation matrix to a given value. * @param[in] matrix New value of the linear transformation matrix. */

TODO: replace all use of this method with a GUDHI_CHECK? * The procedure checks if min_, max_ and this->heat_maps_ sizes are the same. **/

\brief Returns the codomain dimension. */

Assuming the complex is a graph (simplices of higher dimension are ignored), this method implicitly interprets it as the 1-skeleton of a flag

\brief Returns a range over the vertices of the simplicial complex. * The order is increasing according to < on Vertex_handles.*/

* This procedure compute incidence numbers between cubes. For a cube \f$A\f$ of * dimension n and a cube \f$B \subset A\f$ of dimension n-1, an inci

This function computes the persistence of the complex, so it can be accessed through :func:`persistent_betti_numbers`, :func:`persiste

* \brief Constructs the the cell complex that approximates an \f$m\f$-dimensional manifold * without boundary embedded in the \f$ d \f$-dimensiona

:param max_alpha_square: The maximum relaxation parameter. Default is set to infinity. :type max_alpha_square: float

Args: max_dimension (int): graph expansion until this given dimension.

* Subtracts a from the simplex. */

TODO: externalize this method and `decode_extended_filtration` \brief Extend filtration for computing extended persistence. * This function only us

Args: X (numpy.array): coordinates for reference points.

Calibration step: fit centers to the target sample measures and derive inertias between centers. If the target does not contain enoug

Assuming this is a flag complex, this function returns the persistence pairs, where each simplex is replaced with the vertices of the edges th

* @brief Returns the current persistence diagram. * * @param shortestInterval Threshold. Every bar shorter than the given value will not be retu

Inserts edges given by a sparse matrix in `COOrdinate format <https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.coo_matrix.htm

\brief Returns true, if the simplex is a face of other simplex. * * @param[in] other A simplex that is potential a coface of the current simplex

* @brief The complex is reduced to its set of vertices. * All the edges and blockers are removed. */

* @return If ignore_popable_blockers is true * then the result is true iff the link condition at edge ab is satisfied * or equivalently iff no b

\brief Computes and returns the number of simplices of each dimension in the complex. */

This function computes the kernel matrix between two lists of persistence diagrams given as numpy arrays of shape (nx2). Parameters:

This function returns the persistence intervals of the complex in a specific dimension. :param dimension: The specific dimension.

Set function from kth coordinate \brief Creates the function f from the k-th coordinate of the point cloud P. * * @param[in] k c

Set graph from OFF file. \brief Creates a graph G from the triangulation given by the input .OFF file. * */

Args: X (numpy.array): coordinates for query points, or distance matrix if metric is "precomputed". Returns:

Compute all bottleneck distances between the persistence diagrams that were stored after calling the fit() method, and a given list o

* @brief Un-pairs a column. */

:param X: (n x 2) numpy array encoding a persistence diagram. :returns: The finite part of a diagram `X` (points with finite coordinates).

:param a: * If array, assumes it is a (n x 2) np.array * If iterable of array, assumes it is an iterable on (n x 2) np.array

Get archive path based on file_path given by user and label. Parameters ---------- file_path: string Full path of the file t

:param X: (n x 2) numpy array, first diagram. :param Y: (n x 2) numpy array, second diagram. :order: Wasserstein order for cost computati

This function returns truncated persistence if length is bigger than max_intervals and a boolean which is `True` if and only if the persistence ar

This function returns True if matplotlib can deal with LaTeX, False otherwise. The returned value is cached. This code is taken https://g

Version of _perstot that works on eagerpy tensors.

warning, this function can be only called after filling in the intervals vector.

* @brief Adds the first element to the second one and multiplies the third one with it, that is * `((e + a) * m) % characteristic`, such that the r

* @brief Adds the first element to the second one and multiplies the third one with it, that is * `((e + a) * m) % characteristic`, such that the r

* @brief Adds an edge between vertices a and b. * @details For instance, the complex contains edge 01 and 12, then calling * add_edge with verte

* @details Adds to simplex the neighbours of v e.g. \f$ n \leftarrow n \cup N(v) \f$. * If keep_only_superior is true then only vertices that are g

\brief Returns the domain (ambient) dimension. */

* @brief Sets the value of the pair. * * @param other_col @ref MatIdx of the pair column. */