histbary15B {T4transport} | R Documentation |
Given multiple histograms represented as "histogram"
S3 objects, compute
Wasserstein barycenter. We need one requirement that all histograms in an
input list hists
must have same breaks. See the example on how to
construct a histogram on predefined breaks/bins.
histbary15B(hists, p = 2, weights = NULL, lambda = NULL, ...)
hists |
a length- |
p |
an exponent for the order of the distance (default: 2). |
weights |
a weight of each image; if |
lambda |
a regularization parameter; if |
... |
extra parameters including
|
a "histogram"
object of barycenter.
Benamou J, Carlier G, Cuturi M, Nenna L, Peyré G (2015). “Iterative Bregman Projections for Regularized Transportation Problems.” SIAM Journal on Scientific Computing, 37(2), A1111–A1138. ISSN 1064-8275, 1095-7197.
#----------------------------------------------------------------------
# Binned from Two Gaussians
#
# EXAMPLE : Very Small Example for CRAN; just showing how to use it!
#----------------------------------------------------------------------
# GENERATE FROM TWO GAUSSIANS WITH DIFFERENT MEANS
set.seed(100)
x = stats::rnorm(1000, mean=-4, sd=0.5)
y = stats::rnorm(1000, mean=+4, sd=0.5)
bk = seq(from=-10, to=10, length.out=20)
# HISTOGRAMS WITH COMMON BREAKS
histxy = list()
histxy[[1]] = hist(x, breaks=bk, plot=FALSE)
histxy[[2]] = hist(y, breaks=bk, plot=FALSE)
# COMPUTE
hh = histbary15B(histxy, maxiter=5)
# VISUALIZE
opar <- par(no.readonly=TRUE)
par(mfrow=c(1,2))
barplot(histxy[[1]]$density, col=rgb(0,0,1,1/4),
ylim=c(0, 0.75), main="Two Histograms")
barplot(histxy[[2]]$density, col=rgb(1,0,0,1/4),
ylim=c(0, 0.75), add=TRUE)
barplot(hh$density, main="Barycenter",
ylim=c(0, 0.75))
par(opar)