A persistence interval is described by a pair of cells, one that creates the feature and one that kills it. The filtration values of those 2 c

* This function compute integral of the landscape (defined formally as sum of integrals on R of all landscape * functions) **/

* \brief Evaluation of the kernel on a pair of diagrams. * * @pre approx and sigma attributes need to be the same for both instances. *

* @return true iff the simplex contains the difference \f$ a \setminus b \f$. */

\private \brief Test if the vertices have contiguous numbering: 0, 1, etc. */

Args: max_alpha_square (float): The maximum alpha square threshold the simplices shall not exceed. Default is set

:param max_alpha_square: The maximum alpha square threshold the simplices shall not exceed. Default is set to infinity. :

* A procedure used to check if the cell is deleted. It is used by the * subsequent implementation of Hasse diagram that is absed on lazy * delet

* Intersects the simplex with the simplex a. */

* @brief %Test if the complex is a cone. * @details Runs in O(n) where n is the number of vertices. */

* return true if reading did not meet problems. */

Assuming this is a lower-star filtration, this function returns the persistence pairs, where each simplex is replaced with the vertex that gav

@return max_radius value given at construction. */

TODO: would this method not make more sense as a friend to mirror `operation_on_pair_of_heat_maps`? Or as modifying the heat map itself instead of a c

* This function implements an operation of multiplying Vector_distances_in_diagram by a scalar. **/

Get the number of seconds between the timer start and: - the last call of end() if it was called - or now otherwise. In this case, the timer is not st

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

:Requires: `Matplotlib <installation.html#matplotlib>`_

This function plots the persistence diagram from persistence values list, a np.array of shape (N x 2) (representing a diagram in a single homology

Set x <- x + w * y*/

Reads a file containing persistence intervals. Each line might contain 2, 3 or 4 values: [[field] dimension] birth death The return value is an `std::

Set color from vector. \brief Computes the function used to color the nodes of the simplicial complex from a vector stored in memory. * * @param

Creates a graph G from a file containing the edges. :param graph_file_name: Name of the input graph file. The graph file contains

Set graph from file. \brief Creates a graph G from a file containing the edges. * * @param[in] graph_file_name name of the input

\brief Sets a number of intervals from a value stored in memory. * * @param[in] reso number of intervals. * */

*@brief allows to change the visitor. */

\brief Helper method that returns the corresponding Simplex_handle from a member element defined by a node. */

Outputs a subset of the input points so that the squared distance between any two points is greater than min_squared_dist. :param points: The

Array with the filtration values of the top-dimensional cells of the complex. Modifying the values is strongly discouraged. :returns:

Apply measure vectorisation on a list of measures. Parameters: X (list N x d numpy arrays): input measures in R^d to be

Array with the filtration values of the vertices of the complex. Modifying the values is strongly discouraged. :returns: numpy.ndarr

* Function returning a Vertices_iterator to the first vertex of the bitmap. */

* Function returning a Vertices_iterator to the first vertex of the bitmap. */

* Function returning a Vertices_iterator to the last vertex of the bitmap. */

* Function returning a Vertices_iterator to the last vertex of the bitmap. */

Constructor for the NerveComplex class. Parameters: input_type (string): type of input data. Either "point cloud" or "di

This is a function for projecting the points of a list of persistence diagrams (as well as their diagonal projections) onto a fixed number of lin

if min == max, then the program is requested to set up the values itself based on persistence intervals

:param X: (n x 2) numpy.array (dgm points) :param Y: (n x 2) numpy.array (dgm points) :param idX: indices to consider for this one dimens

Fetch the wanted license from the given url and save it in file_path. Parameters ---------- license_url : string The url to

Return the path of the remote datasets directory. This folder is used to store remotely fetched datasets. By default the datasets directo

Returns true if Persistence pointer is not None.

:param x: a list of 2D-points, off diagonal, x_0... x_{k-1} :param m: total amount of points taken into account, that is we have (m-k) copies

This function returns (min_birth, max_death) from the persistence. :param persistence: The persistence to plot. :type persistence: list of tu

This is a function for computing the persistence Fisher distance from two persistence diagrams. The persistence Fisher distance is obtained by co

This is a function for computing the persistence weighted Gaussian kernel value from two persistence diagrams. The persistence weighted Gaussian

:param X: (n x 2) numpy.array (points of a given diagram). :param order: exponent for Wasserstein. :param internal_p: Ground metric on th

:param X: (n x 2) array encoding the points of a persistent diagram. :returns: (n x 2) array encoding the (respective orthogonal) projections