fd_boxcount2D: 2D Boxcount for 1D signal

In FredHasselman/casnet: A Toolbox for Studying Complex Adaptive Systems and Networks

2D Boxcount for 1D signal

Description

2D Boxcount for 1D signal

Usage

fd_boxcount2D(
  y = NA,
  unitSquare = TRUE,
  image2D = NA,
  resolution = 1,
  removeTrend = FALSE,
  polyOrder = 1,
  standardise = c("none", "mean.sd", "median.mad")[1],
  adjustSumOrder = FALSE,
  scaleMin = 0,
  scaleMax = floor(log2(NROW(y) * resolution)),
  scaleS = NA,
  dataMin = 2^(scaleMin + 1),
  maxData = 2^(scaleMax - 1),
  doPlot = FALSE,
  returnPlot = FALSE,
  returnPLAW = FALSE,
  returnInfo = FALSE,
  returnLocalScaling = FALSE,
  silent = FALSE,
  noTitle = FALSE,
  tsName = "y"
)

Arguments

y	A numeric vector or time series object.
unitSquare	Create unit square image of y? This is required for estimating FD of time series (default = TRUE)
image2D	A matrix representing a 2D image, argument y and unitSquare will be ignored (default = NA)
resolution	The resolution used to embed the timeseries in 2D, a factor by which the dimensions the matrix will be multiplied (default = 1)
removeTrend	If TRUE, will call ts_detrend on y (default = FALSE)
polyOrder	Order of polynomial trend to remove if ⁠removeTrend = ⁠TRUE“
standardise	Standardise y using ts_standardise() with adjustN = FALSE (default = none)
adjustSumOrder	Adjust the order of the time series (by summation or differencing), based on the global scaling exponent, see e.g. https://www.frontiersin.org/files/Articles/23948/fphys-03-00141-r2/image_m/fphys-03-00141-t001.jpgIhlen (2012) (default = 'FALSE“)
scaleMin	Minimium scale value (as 2^scale) to use (default = 0)
scaleMax	Maximum scale value (as 2^scale) to use (default = max of log2(nrows) and log2(ncols))
scaleS	If not NA, pass a numeric vector listing the scales (as a power of 2) on which to evaluate the boxcount. Arguments scaleMax, scaleMin, and scaleResolution will be ignored (default = NA)
dataMin	Minimum number of time/data points inside a box for it to be included in the slope estimation (default = 2^scaleMin)
maxData	Maximum number of time/data points inside a box for it to be included in the slope estimation (default = 2^scaleMax)
doPlot	Return the log-log scale versus bulk plot with linear fit (default = TRUE).
returnPlot	Return ggplot2 object (default = FALSE)
returnPLAW	Return the power law data (default = FALSE)
returnInfo	Return all the data used in DFA (default = FALSE)
returnLocalScaling	Return estimates of FD for each scale
silent	Silent-ish mode (default = TRUE)
noTitle	Do not generate a title (only the subtitle)
tsName	Name of y added as a subtitle to the plot (default = y)

Value

The boxcount fractal dimension and the 'local' boxcount fractal dimension

Note

This function was inspired by the Matlab function boxcount.m written by F. Moisy. ⁠Fred Hasselman⁠ adapted the function for R for the purpose of the unit square boxcount analysis for 1D time series. The original Matlab toolbox has more options and contains more functions (e.g. ⁠1D⁠ and ⁠3D⁠ boxcount).

Examples

fd_boxcount2D(y = rnorm(100))

FredHasselman/casnet documentation built on March 10, 2024, 8:23 a.m.