gudhi.point_cloud.timedelay.TimeDelayEmbedding Class Reference

Public Member Functions

def __call__ (self, ts)
 
def transform (self, ts)
 

Detailed Description

Point cloud transformation class. Embeds time-series data in the R^d according to
`Takens' Embedding Theorem <https://en.wikipedia.org/wiki/Takens%27s_theorem>`_ and obtains the
coordinates of each point.

Parameters
----------
dim : int, optional (default=3)
    `d` of R^d to be embedded.
delay : int, optional (default=1)
    Time-Delay embedding.
skip : int, optional (default=1)
    How often to skip embedded points.

Example
-------

Given delay=3 and skip=2, a point cloud which is obtained by embedding
a scalar time-series into R^3 is as follows::

    time-series = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
    point cloud = [[1, 4, 7],
                   [3, 6, 9]]

Given delay=1 and skip=1, a point cloud which is obtained by embedding
a 2D vector time-series data into R^4 is as follows::

    time-series = [[0, 1], [2, 3], [4, 5], [6, 7], [8, 9]]
    point cloud = [[0, 1, 2, 3],
                   [2, 3, 4, 5],
                   [4, 5, 6, 7],
                   [6, 7, 8, 9]]

Member Function Documentation

◆ __call__()

def gudhi.point_cloud.timedelay.TimeDelayEmbedding.__call__ (   self,
  ts 
)
Transform method for single time-series data.

Parameters
----------
ts : Iterable[float] or Iterable[Iterable[float]]
    A single time-series data, with scalar or vector values.

Returns
-------
point cloud : n x dim numpy arrays
    Makes point cloud from a single time-series data.

◆ transform()

def gudhi.point_cloud.timedelay.TimeDelayEmbedding.transform (   self,
  ts 
)
Transform method for multiple time-series data.

Parameters
----------
ts : Iterable[Iterable[float]] or Iterable[Iterable[Iterable[float]]]
    Multiple time-series data, with scalar or vector values.

Returns
-------
point clouds : list of n x dim numpy arrays
    Makes point cloud from each time-series data.

The documentation for this class was generated from the following file:
GUDHI  Version 3.3.0  - C++ library for Topological Data Analysis (TDA) and Higher Dimensional Geometry Understanding.  - Copyright : MIT Generated on Tue Aug 11 2020 11:58:59 for GUDHI by Doxygen 1.8.18