Description Usage Arguments Details Value Author(s) References Examples

Computes the Poincare map of the reconstructed trajectories in the phase-space.

1 2 | ```
poincareMap(time.series = NULL, embedding.dim = 2, time.lag = 1,
takens = NULL, normal.hiperplane.vector = NULL, hiperplane.point)
``` |

`time.series` |
The original time series from which the phase-space reconstruction is done. |

`embedding.dim` |
Integer denoting the dimension in which we shall embed the |

`time.lag` |
Integer denoting the number of time steps that will be use to construct the Takens' vectors. |

`takens` |
Instead of specifying the |

`normal.hiperplane.vector` |
The normal vector of the hyperplane that will be used to compute the Poincare map. If the vector is not specifyed the program choses the vector (0,0,...,1). |

`hiperplane.point` |
A point on the hyperplane (an hyperplane is defined with a point and a normal vector). |

This function computes the Poincare map taking the Takens' vectors as the continuous trajectory
in the phase space. The *takens* param has been included so that the user may
specify the real phase-space instead of using the phase-space reconstruction (see
examples).

Since there are three different Poincare maps, an R list is returned storing all the information related which all of these maps:

The positive Poincare map is formed by all the intersections with the hyperplane in positive direction (defined by the normal vector). The

*pm.pos*returns the points of the map whereas that*pm.pos.time*returns the number of time steps since the beggining where the intersections occurred. Note that these time steps probably won't be integers since the algorithm uses an interpolation procedure for calculating the intersection with the hyperplane.Similarly we define a negative Poincare map (

*pm.neg*and*pm.neg.time*).Finally, we may define a two-side Poincare map that stores all the intersections (no matter the direction of the intersection) (

*pm*and*pm.time*).

Constantino A. Garcia

Parker, T. S., L. O. Chua, and T. S. Parker (1989). Practical numerical algorithms for chaotic systems. Springer New York

1 2 3 4 5 6 7 8 9 10 | ```
## Not run:
r=rossler(a = 0.2, b = 0.2, w = 5.7, start=c(-2, -10, 0.2),
time=seq(0,300,by = 0.01), do.plot=FALSE)
takens=cbind(r$x,r$y,r$z)
# calculate poincare sections
pm=poincareMap(takens = takens,normal.hiperplane.vector = c(0,1,0),
hiperplane.point=c(0,0,0) )
plot3d(takens,size=0.7)
points3d(pm$pm,col="red")
## End(Not run)
``` |

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