reservoirpy.datasets.logistic_map#

reservoirpy.datasets.logistic_map(
n_timesteps: int,
r: float = 3.9,
x0: float = 0.5,
**kwargs,
) → ndarray[source]#

Logistic map discrete timeseries [4] [5].

\[x(n+1) = rx(n)(1-x(n))\]
Parameters:

  • n_timesteps (int) – Number of timesteps to generate.

  • r (float, default to 3.9) – \(r\) parameter of the system.

  • x0 (float, default to 0.5) – Initial condition of the system.

Returns:

Logistic map discrete timeseries.

Return type:

array of shape (n_timesteps, 1)

Examples

>>> from reservoirpy.datasets import logistic_map
>>> timeseries = logistic_map(n_timesteps=100)
>>> timeseries.shape
(100, 1)
../../_images/reservoirpy-datasets-logistic_map-1.png

References