crqa (version 2.0.5)

piecewiseRQA: 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)

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

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)

Author

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

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.

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]))