jrp
Creates a joint recurrence plot.
Syntax
jrp(x)
jrp(x,y)
jrp(x,m,t,e)
r=jrp(x,[],m,t,e)
r=jrp(x,m,t,e,'param1','param2',...)
r=jrp(x,y,m,'param1')
Description
Creates a simple joint recurrence plot of maximal two data series, based on different norms or recurrence plots. Embedding parameters will be the same for both systems. Results can be stored into the workspace.
Allows to change the parameters interactively by using a GUI.
The source-data x and test-data y can be one- or a two-coloumn vectors (then, in the first column have to be the time); if the test-data y is not specified, a simple (auto) recurrence plot is created.
Parameters
Dimension m, delay t and the size of neighbourhood e are the first three numbers after the data series; further parameters can be used to switch between various methods of finding the neighbours of the phasespace trajectory, to suppress the normalization of the data and to suppress the GUI (useful in order to use this programme by other programmes).
Methods of finding the neighbours/ of plot. | ||
'maxnorm' | - | Maximum norm. |
'euclidean' | - | Euclidean norm. |
'minnorm' | - | Minimum norm. |
'nrmnorm' | - | Euclidean norm between normalized vectors (all vectors have the length one). |
'rr' | - | Maximum norm, fixed recurrence rate. |
'fan' | - | Fixed amount of nearest neighbours. |
'inter' | - | Interdependent neighbours. |
'omatrix' | - | Order matrix. |
'opattern' | - | Order patterns recurrence plot. |
'distance' | - | Distance coded matrix (global JRP, Euclidean norm). |
Normalization of the data series. | ||
'normalize' | - | Normalization of the data. |
'nonormalize' | - | No normalization of the data. |
Suppressing the GUI. | ||
'gui' | - | Creates the GUI and the output plot. |
'nogui' | - | Suppresses the GUI and the output plot. |
'silent' | - | Suppresses all output. |
Parameters not needed to specify.
Limitations
For higher speed in output the whole matrix of the recurrence plot is in the work space - this limits the application of long data series. However, with a little Matlab script, long data series can be handled too (cf. Examples for crp).
Examples
a=sin((1:1000)*2*pi/67);
b=sin(.01*([1:1000]*2*pi/67).^2);
jrp(a,b,3,12,'fan')
See Also
References
Romano, M., Thiel, M., Kurths, J., von Bloh, W.: Multivariate Recurrence Plots, Phys. Lett. A, 330, 2004.