plot.biwavelet: Plot 'biwavelet' objects
In biwavelet: Conduct univariate and bivariate wavelet analyses

Description Usage Arguments Details Author(s) References See Also Examples

Plot biwavelet objects such as the cwt, cross-wavelet and wavelet coherence

## S3 method for class 'biwavelet'
 plot(x, ncol = 64, xlab = "Time", ylab = "Period",
               tol = 0.95, plot.cb = FALSE, plot.phase = FALSE, 
               type=c("power.corr.norm", "power.corr", "power.norm", "power", 
               "wavelet", "phase"), 
               plot.coi = TRUE, lwd.coi=4, col.coi="white", lty.coi=2,
               plot.sig = TRUE, lwd.sig=4, col.sig="black", lty.sig=1,
               bw = FALSE, legend.loc = NULL, legend.horiz = FALSE, 
               arrow.size = 0.08, arrow.size.head = 0.05, arrow.lwd = 2, 
               arrow.cutoff = 0.9, arrow.col="black",
               arrow.nlocs.x = round(length(x$period)/2), 
               arrow.nlocs.y = round(NCOL(x$wave)/2),
               xlim = NULL, ylim = NULL, xaxt = "s", yaxt = "s", 
               form='%Y', ...)

`x`	`biwavelet` object generated by `wt`, `xwt`, or `wtc`.
`ncol`	number of colors to use. Default is 64.
`xlab`	xlabel of the figure. Default is "Time"
`ylab`	ylabel of the figure. Default is "Period"
`tol`	tolerance level for significance contours. Sigificance contours will be drawn around all regions of the spectrum where `spectrum/percentile >= tol`. Default is `0.95`. If strict `i^{th}` percentile regions are desired, then set `tol=1`.
`plot.cb`	plot color bar if TRUE. Default is FALSE.
`plot.phase`	Plot phases with black arrows. Default is FALSE.
`type`	type of plot to create. Can be `power` to plot the power, `power.corr` to plot the bias-corrected power, `power.norm` to plot the power normalized by the variance, `power.corr.norm` to plot the bias-corrected power normalized by the variance, `wavelet` to plot thewavelet coefficients, or `phase` to plot the phase. Default is `power.corr.norm`.
`plot.coi`	plot cone of influence (COI) if TRUE. Default is TRUE. Areas that fall outside of the COI can be affected by edge effects.
`lwd.coi`	Line width of COI. Default is 4.
`col.coi`	Color of cone of COI. Default is `white`.
`lty.coi`	Line type of COI
`plot.sig`	plot contours for significance if TRUE. Default is TRUE.
`lwd.sig`	Line width of significance contours. Default is 4.
`col.sig`	Color of significance contours. Default is `black`.
`lty.sig`	Line type of significance contours. Default is 1.
`bw`	plot in black and white if TRUE. Default is FALSE.
`legend.loc`	legend location coordinates as defined by `image.plot`. Default is `NULL`.
`legend.horiz`	plot a horizontal legend if TRUE. Default is FALSE.
`arrow.size`	size of the arrows. Default is 0.08.
`arrow.size.head`	size of the arrow head. Default is 0.05.
`arrow.lwd`	width/thickness of arrows. Default is 2.
`arrow.cutoff`	cutoff value for plotting arrows. z-values that fall below the `arrow.cutoff` quantile will not be plotted. Default is 0.9.
`arrow.col`	Color of arrows. Default is `black`.
`arrow.nlocs.x`	Integer number of x- or time-locations where phase arrows should be plotted. Default is 1/2 of the time-locations
`arrow.nlocs.y`	Integer number of y- or period-locations where phase arrows should be plotted. Default is 1/2 of the period-locations
`xlim`	the x limits. The default is `NULL`.
`ylim`	the y limits. The default is `NULL`.
`xaxt`	Add x-axis? The default is `s`; use `n` for none.
`yaxt`	Add y-axis? The default is `s`; use `n` for none.
`form`	format to use to display dates on the x-axis. Default is '%Y' for 4-digit year. See `?Date` for other valid formats.
`...`	other parameters.

Arrows pointing to the right mean that x and y are in phase.

Arrows pointing to the left mean that x and y are in anti-phase.

Arrows pointing up mean that y leads x by π/2.

Arrows pointing down mean that x leads y by π/2.

Tarik C. Gouhier (tarik.gouhier@gmail.com)

Code based on WTC MATLAB package written by Aslak Grinsted.

Cazelles, B., M. Chavez, D. Berteaux, F. Menard, J. O. Vik, S. Jenouvrier, and N. C. Stenseth. 2008. Wavelet analysis of ecological time series. Oecologia 156:287-304.

Grinsted, A., J. C. Moore, and S. Jevrejeva. 2004. Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics 11:561-566.

Torrence, C., and G. P. Compo. 1998. A Practical Guide to Wavelet Analysis. Bulletin of the American Meteorological Society 79:61-78.

Liu, Y., X. San Liang, and R. H. Weisberg. 2007. Rectification of the Bias in the Wavelet Power Spectrum. Journal of Atmospheric and Oceanic Technology 24:2093-2102.

image.plot

t1=cbind(1:100, rnorm(100))
t2=cbind(1:100, rnorm(100))
## Continuous wavelet transform
wt.t1=wt(t1)
## Plot power
## Make room to the right for the color bar
par(oma=c(0, 0, 0, 1), mar=c(5, 4, 4, 5) + 0.1)
plot(wt.t1, plot.cb=TRUE, plot.phase=FALSE)

## Cross-wavelet transform
xwt.t1t2=xwt(t1, t2)
## Plot cross-wavelet
par(oma=c(0, 0, 0, 1), mar=c(5, 4, 4, 5) + 0.1)
plot(xwt.t1t2, plot.cb=TRUE)

## Example of bias-correction
t1=sin(seq(from=0, to=2*5*pi, length=1000))
t2=sin(seq(from=0, to=2*15*pi, length=1000))
t3=sin(seq(from=0, to=2*40*pi, length=1000))
## This aggregate time series should have the same power at three distinct periods
s=t1+t2+t3
## Compare plots to see bias-effect on CWT: biased power spectrum artificially
## reduces the power of higher-frequency fluctuations.
wt1=wt(cbind(1:1000, s))
par(mfrow=c(1,2))
plot(wt1, type="power.corr.norm", main="Bias-corrected")
plot(wt1, type="power.norm", main="Biased")

## Compare plots to see bias-effect on XWT: biased power spectrum artificially
## reduces the power of higher-frequency fluctuations.
x1=xwt(cbind(1:1000, s), cbind(1:1000, s))
par(mfrow=c(1,2))
plot(x1, type="power.corr.norm", main="Bias-corrected")
plot(x1, type="power.norm", main="Biased")