:returns: A simplex tree that is a deep copy of itself. :rtype: SimplexTree :note: The persistence information is not copied

:param max_dimension: graph expansion for Rips until this given maximal dimension. :type max_dimension: int :returns: A simpl

* @private * @brief Deserialize the array of char (flatten version of the tree) to initialize a Simplex tree. * It is the user's responsibility

landscapes * This procedure takes two points in \f$ R^2 \f$ and a double value \f$ x \f$. It computes the line parsing through * those two points and

* @private * @brief Returns the serialization required buffer size. * * @return The exact serialization required size in number of bytes.

@brief Returns persistence intervals for a given dimension. * @param[in] dimension Dimension to get the birth and death pairs from. * @return A

Gives a set of pointers to the maximal simplices. * Gives not more than max_number maximal cofaces if max_number is strictly positive. */

observers of the multidimensional index space

* @brief Resets the matrix to an empty matrix. * * @param colSettings Pointer to an existing setting structure for the columns. The structure sh

* @private * @brief Serialize the Simplex tree - Flatten it in a user given array of char * * @param[in] buffer An array of char allocated wi

\brief Sets a gain from a value stored in memory (default value 0.3). * * @param[in] g gain. * */

* Function returning a Top_dimensional_cells_iterator to the first top dimensional cell of the bitmap. **/

This function is a wrapper for any metric between two persistence diagrams that takes two numpy arrays of shapes (nx2) and (mx2) as arguments.

\brief Returns the additive idendity \f$0_{\Bbbk}\f$ of the field.*/

* Function returning a All_cells_iterator to the first cell of the bitmap. **/

* Function returning a All_cells_iterator beyond the last cell of the bitmap. **/

\brief Returns the characteristic \f$p\f$ of the field.*/

* @details Clears the simplicial complex. After a call to this function, * blockers are destroyed. The 1-skeleton and the set of blockers * are

* Computations of maximum (y) value of landscape. **/

* @return true iff the simplicial complex contains an edge between * vertices a and b */

* @return The quadric quost defined by the scalar product v^T Q v where Q is the quadratic form of Garland/Heckbert */

* @brief return the graph degree of a vertex. */

* Removes the simplex sigma from the set of blockers * and deallocate sigma. */

\brief Returns an edge of `sh` that has the same filtration value as `sh` if it exists, and `null_simplex()` otherwise. * * For a flag-complex b

Inserts k-simplices given by a sparse array in a format similar to `torch.sparse <https://pytorch.org/docs/stable/sparse.html>`_. The

\brief Search for the k-nearest neighbors from a query point. @param[in] p The query point. @param[in] k Number of nearest points to search. @param[in

* @brief Multiplies the first element with the second one and adds the third one, that is * `(e * m + a) % characteristic`, such that the result is

Reads a file containing persistence intervals. Each line of persistence_file might contain 2, 3 or 4 values: [[field] dimension] birth death

Reads and stores the input point cloud from .(n)OFF file. :param off_file: Name of the input .OFF or .nOFF file. :type off_file: stri

* @brief returns the first vertex of an edge * @details it assumes that the edge is present in the complex */

Set cover with preimages of function. \brief Creates a cover C from the preimages of the function f. * */

* @brief Sets the row index stored in the entry. * * @param rowIndex @ref rowindex "Row index" of the entry. */

\brief Compute the star of a n simplex * \param simplex represent the simplex of which we search the star * \return Vector of Simplex_tree::Simp

In __call__, use transform on the object itself if it has been fitted, otherwise fit_transform on a clone of the object so it doesn't affect

@name Simplex manipulation */ @{ * Add the vertex v to the simplex: * Note that adding two times the same vertex is * the same that adding it

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

The result is the same as fit(X) followed by transform(X), but potentially faster.

\brief Search incrementally for the nearest neighbors from a query point. @param[in] p The query point. @param[in] eps Approximation factor. @return A

This function computes and returns the persistence of the complex. :param homology_coeff_field: The homology coefficient field. Must be a

\brief Reads and stores the input point cloud from .(n)OFF file. * * @param[in] off_file_name name of the input .OFF or .nOFF file. * */

* @brief Remove a vertex from the simplicial complex * @remark It just deactivates the vertex with a boolean flag but does not * remove it from

* @brief Sets the column index to the given value. * * @param columnIndex Column index of the entry. */

Constructor for the Perslay class. Parameters: weight (function): weight function for the persistence diagram points. Ca

* adds the simplex to the trie */

Subsample by a greedy strategy of iteratively adding the farthest point from the current chosen point set to the subsampling. The iteration st

\brief Compute the cofaces of a n simplex * \param simplex represent the n-simplex of which we search the n+codimension cofaces * \param codimen