a = quickshift(data)
a = quickshift(data, sigma)
# cluster ndim x nsamplex matrix data.
# sigma: Gaussian kernel width, see paper
labels = quickshiftlabels(a::QuickShift)
labels = quickshiftlabels(a::QuickShift, maxlinklength)
# cut links in the tree with length > maxlinklength
# return cluster labels for data points.
quickshiftplot(a, data, labels)
# plot data points and hierarchical links
# needs PyPlot installed, only for 2D

using Clustering, QuickShiftClustering, FunctionalDataUtils
data = rand(2,20000)
@time a = kmedoids(1-exp(-distance(data,data)*10),10)
#  =>  elapsed time: 56.666481916 seconds (41126243444 bytes allocated, 15.31% gc time)
@time labels = quickshiftlabels(quickshift(data))
#  =>  elapsed time: 1.187448525 seconds (277816624 bytes allocated, 28.79% gc time)

using FunctionalData
data = @p map unstack(1:10) (x->10*randn(2,1).+randn(2,100)) | flatten
using QuickShiftClustering
a = quickshift(data)           
labels = quickshiftlabels(a)   
quickshiftplot(a, data, labels)