clusterTracks: Cluster Tracks
In jtextor/MotilityLab: Quantitative Analysis of Motion

Description Usage Arguments Details Value Examples

Perform a hierarchical clustering of a set of tracks according to a given vector of track measures.

1	clusterTracks(tracks, measures, scale = TRUE, ...)

`tracks`	the tracks that are to be clustered.
`measures`	a function, or a vector of functions (see TrackMeasures). Each function is expected to return a single number given a single track.
`scale`	logical indicating whether the measures values shall be scaled using the function `scale` before the clustering.
`...`	additional parameters to be passed to `hclust`.

The measures are applied to each of the tracks in the given tracks object. According to the resulting values, the tracks are clustered using a hierarchical clustering (see hclust). If scale is TRUE, the measure values are scaled to mean value 0 and standard deviation 1 (per measure) before the clustering.

An object of class *hclust*, see hclust.

## Cluster tracks according to the mean of their Hust exponents along X and Y

cells <- c(TCells,Neutrophils)
real.celltype <- rep(c("T","N"),c(length(TCells),length(Neutrophils)))
## Prefix each track ID with its cell class to evaluate the clustering visually
names(cells) <- paste0(real.celltype,seq_along(cells))
clust <- clusterTracks( cells, hurstExponent )
plot( clust )
## How many cells are "correctly" clustered?
sum( real.celltype == c("T","N")[cutree(clust,2)] )