tdads.PH_utils
==============

.. py:module:: tdads.PH_utils


Functions
---------

.. autoapisummary::

   tdads.PH_utils.enclosing_radius


Module Contents
---------------

.. py:function:: enclosing_radius(X: numpy.ndarray, distance_mat: bool = False)

   Compute the enclosing radius of a dataset. Beyond this filtration radius no
   topological changes can occur.

   :param `X`: The input dataset - either raw tabular data or a distance matrix of samples.
   :type `X`: numpy.ndarray (2D)
   :param `distance_mat`: Whether or not `X` is a distance matrix. If `False` then a Euclidean distance
                          matrix will be computed.
   :type `distance_mat`: bool, default `False`

   :returns: The enclosing radius value of `X`.
   :rtype: numpy.float64

   .. rubric:: Examples

   >>> from tdads.PH_utils import enclosing_radius
   >>> from ripser import ripser
   >>> from numpy.random import uniform
   >>> from numpy import array, cos, sin
   >>> from math import pi
   >>> from scipy.spatial.distance import cdist
   >>> # build circle dataset
   >>> theta = uniform(low = 0, high = 2*pi, size = 100)
   >>> data = array([[cos(theta[i]), sin(theta[i])] for i in range(100)])
   >>> # compute the enclosing radius
   >>> enc_rad = enclosing_radius(data)
   >>> # compute persistence diagram
   >>> diagram = ripser(data, enc_rad)
   >>> # now for a distance matrix
   >>> dist_data = cdist(data, data, 'euclidean')
   >>> enc_rad = enclosing_radius(dist_data, True)
   >>> diagram = ripser(dist_data, enc_rad, distance_matrix = True)