piecewiseRQA: Compute recurrence plots for long time-series data series...

In crqa: Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis

Compute recurrence plots for long time-series data series using a block (piece-wise) method.

Description

This is a convenience function which breaks down the computation of large recurrence plots into a collection of smaller recurrence plots. It can ease speed and memory issues if an appropriate size for the block is found.

Usage

piecewiseRQA(ts1, ts2, blockSize, delay, embed, rescale, radius,
normalize, mindiagline, minvertline, tw, whiteline, recpt, side, 
method, metric, datatype, typeRQA, windowsize)

Arguments

ts1	First time-series.
ts2	Second time-series.
blockSize	The dimension of the time-series subunit in which the-recurrence plot will be computed
delay	The delay unit by which the series are lagged.
embed	The number of embedding dimension for phase-reconstruction, i.e., the lag intervals.
rescale	Rescale the distance matrix; if rescale = 0 (do nothing); if rescale = 1 (mean distance of entire matrix); if rescale = 2 (maximum distance of entire matrix). if rescale = 3 (minimum distance of entire matrix). if rescale = 4 (euclidean distance of entire matrix).
radius	A threshold, cut-off, constant used to decide whether two points are recurrent or not.
normalize	Normalize the time-series; if normalize = 0 (do nothing); if normalize = 1 (Unit interval); if normalize = 2 (z-score).
mindiagline	A minimum diagonal length of recurrent points. Usually set to 2, as it takes a minimum of two points to define any line.
minvertline	A minimum vertical length of recurrent points.
tw	The Theiler window parameter
whiteline	A logical flag to calculate (TRUE) or not (FALSE) empty vertical lines.
recpt	A logical flag indicating whether measures of cross-recurrence are calculated directly from a recurrent plot (TRUE) or not (FALSE).
side	A string indicating whether recurrence measures should be calculated in the 'upper' triangle of the RP 'lower' triangle of the matrix, or 'both'. LOC is automatically excluded for 'upper' and 'lower'.
method	A string to indicate the type of recurrence analysis to peform. There are three options: rqa (autorecurrence); crqa(cross-recurrence); mdcrqa(multidimensional recurrence). Default value is crqa
metric	A string to indicate the type of distance metric used, default is euclidean but see help rdist() to list all other possible metrics.
datatype	a string (continuous or categorical) to indicate whether the nature of the data type
typeRQA	a string (full or diagonal) to indicate whether piecewise recurrence quantification measures should be returned for full plot or for the diagonal profile
windowsize	the size of the window around the diagonal of the recurrence (if typeRQA = diagonal)

Details

It is important to estimate the size of the block that may maximize the speed of the computation. We suggest to monitor how speed and memory usage changes as a result of increasing the time-series and the block size. We also recommend setting whiteline = FALSE, as the current version of the library does not make use of such information to extract measures of recurrence.

Value

If an RP can be calculated and recurrence is found, the piecewiseRQA will return exactly the same measures as crqa() if the typeRQA is set to 'full' and drpdfromts() if the typeRQA is set to 'diagonal'. Please refer to the help file for those two functions for details about the measures.

RP	The Recurrence Plot sparse matrix data

Author(s)

Moreno I. Coco ([e-mail]) based on Matlab code by Sebastian Wallot

See Also

crqa, spdiags, simts

Examples

## Uncomment and run locally

## generate some data using pracma

# ts1 = seq(0.1, 200, .1)
# ts1 = sin(ts1) + linspace(0, 1,length(ts1));

# ts2 = ts1

## initialize the parameters
# blockSize = 100; delay  = 15; embed  = 2; rescale = 0; radius = 0.5;
# normalize = 0; mindiagline = 2; minvertline = 2;
# tw = 1; whiteline = FALSE; recpt = FALSE; side = 'both'
# method = "crqa"; metric = 'euclidean'; datatype = "continuous"
# typeRQA = "full"; windowsize = NA

# pieceRP = piecewiseRQA(ts1, ts2, blockSize, delay, embed, rescale,
#                       radius, normalize, mindiagline, minvertline,
#                       tw, whiteline, recpt, side,
#                       method, metric, datatype, typeRQA, 
#                       windowsize)
                       
# print(unlist(pieceRP[1:10]))
                       

crqa documentation built on Nov. 27, 2023, 5:10 p.m.