takens_embedding_optimal_parameters¶
-
gtda.time_series.
takens_embedding_optimal_parameters
(X, max_time_delay, max_dimension, stride=1, n_jobs=None, validate=True)[source]¶ Compute the “optimal” parameters for a Takens (time-delay) embedding 1 of a univariate time series.
First, an optimal time delay is found by minimising the time-delayed mutual information among values no greater than max_time_delay. Then, a heuristic based on an algorithm in 2 is used to select an embedding dimension which, when increased, does not reveal a large proportion of “false nearest neighbors”.
- Parameters
X (ndarray of shape (n_samples,) or (n_samples, 1)) – Input data representing a single univariate time series.
max_time_delay (int, required) – Maximum time delay between two consecutive values for constructing one embedded point.
max_dimension (int, required) – Maximum embedding dimension that will be considered in the optimization.
stride (int, optional, default:
1
) – Stride duration between two consecutive embedded points. It defaults to 1 as this is the usual value in the statement of Takens’s embedding theorem.n_jobs (int or None, optional, default:
None
) – The number of jobs to use for the computation.None
means 1 unless in ajoblib.parallel_backend
context.-1
means using all processors.validate (bool, optional, default:
True
) – Whether the input and hyperparameters should be validated.
- Returns
time_delay (int) – The “optimal” time delay less than or equal to max_dimension, as determined by minimizing the time-delayed mutual information.
dimension (int) – The “optimal” embedding dimension less than or equal to max_dimension, as determined by a false nearest neighbors heuristic once time_delay is computed.
See also
References
- 1
F. Takens, “Detecting strange attractors in turbulence”. In: Rand D., Young LS. (eds) Dynamical Systems and Turbulence, Warwick 1980. Lecture Notes in Mathematics, vol. 898. Springer, 1981; DOI: 10.1007/BFb0091924.
- 2
M. B. Kennel, R. Brown, and H. D. I. Abarbanel, “Determining embedding dimension for phase-space reconstruction using a geometrical construction”; Phys. Rev. A 45, pp. 3403–3411, 1992; DOI: 10.1103/PhysRevA.45.3403.