Apply a warping to a given timeseries
Returns the indexing required to apply the optimal warping curve to a given timeseries (warps either into a query or into a reference).
dtwobject specifying the warping curve to apply
TRUEto warp a reference,
FALSEto warp a query
The warping is returned as a set of indices, which can be used to subscript the timeseries to be warped (or rows in a matrix, if one wants to warp a multivariate time series). In other words,
warp converts the warping curve, or its inverse, into a
function in the explicit form.
Multiple indices that would be mapped to a single point are averaged, with a warning. Gaps in the index sequence are filled by linear interpolation.
A list of indices to subscript the timeseries.
dtw show how to graphically
apply the warping via parametric plots.
idx<-seq(0,6.28,len=100); query<-sin(idx)+runif(100)/10; reference<-cos(idx) alignment<-dtw(query,reference); wq<-warp(alignment,index.reference=FALSE); wt<-warp(alignment,index.reference=TRUE); old.par <- par(no.readonly = TRUE); par(mfrow=c(2,1)); plot(reference,main="Warping query"); lines(query[wq],col="blue"); plot(query,type="l",col="blue", main="Warping reference"); points(reference[wt]); par(old.par); ############## ## ## Asymmetric step makes it "natural" to warp ## the reference, because every query index has ## exactly one image (q->t is a function) ## alignment<-dtw(query,reference,step=asymmetric) wt<-warp(alignment,index.reference=TRUE); plot(query,type="l",col="blue", main="Warping reference, asymmetric step"); points(reference[wt]);