wccHeatMap: wccHeatmap

In wcc: Windowed Cross Correlation

wccHeatmap

Description

This function plots a heatmap of a chosen aggregate statistic from the results of wccFindDyadParam

Usage

wccHeatmap(xparam=NA, yparam=NA, aggstat=NA, xlabel=NA, ylabel=NA, pdffile=NA)

Arguments

xparam	One of the parameter columns from the dataframe returned by wccFindDyadParam. This parameter will be used as the x axis of the heatmap plot.
yparam	One of the parameter columns from the dataframe returned by wccFindDyadParam. This parameter will be used as the y axis of the heatmap plot.
aggstat	One of the aggregate statistics columns from the dataframe returned by wccFindDyadParam. aggstat will be the value that determines the color in each cell of the heatmap.
xlabel	A character string that will be used as the label for the x axis.
ylabel	A character string that will be used as the label for the y axis.
pdffile	A character string with the filename of a pdf file to create. If pdffile=NA then the plot is sent to the default device.

Details

This function produces a heat map plot of selected aggregated statistics returned by wccFindDyadParam for combinations of selected parameter values. First run wccFindDyadParam using two or more parameter vectors for a grid search. Next select two colums of parameters and one aggregated statistic to plot and send it to wccHeatmap. If the optional parameter pdffile exists, then a publication quality pdf file will be saved. Otherwise the heatmap will be displayed on the default device.

Value

Returns nothing.

References

Boker, S. M., Rotondo, J. L., Xu, M., & King, K. (2002). Windowed cross-correlation and peak picking for the analysis of variability in the association between behavioral time series. Psychological methods, 7(3), 338.

See Also

wccFindDyadParam for the definition of the dataframe columns used by wccHeatmap.

Examples

# Create two arrays of timeseries with dyadic dependence
array1 <- matrix(NA, nrow=10, ncol=500)
array2 <- matrix(NA, nrow=10, ncol=500)
for(i in 1:10) {
    array1[i,] <- sin(c(1:500)/runif(1, min=5, max=20)) + rnorm(500, mean=0, sd=.5)
    array2[i,] <- array1[i,] + rnorm(500, mean=0, sd=.5)
}
# Select parameters to explore
wMaxVec <- c(50,100)
tMaxVec <- c(25,50)
wccFDPout <- wccFindDyadParam(inArray1=array1, inArray2=array2, wMaxvector=wMaxVec,
    tMaxvector=tMaxVec, nSurrogates=30, samplespersecond=1, method="r")
# Plot the heatmap
wccHeatmap(xparam=wccFDPout$wMax, yparam=wccFDPout$tMax, aggstat=wccFDPout$maxMean,
    xlabel="Window Max", ylabel="Max Lag")

wcc documentation built on July 14, 2026, 5:07 p.m.