gatherSample collects all sample points, from all files, with the given temperature

This function assumes that each supplied RDS file contains a matrix of model MCMC parameters, with an attribute called "beta" that lists the temperature of each row.

Usage

gatherSample(files, beta = 1, size = NA)

Arguments

files: a list of file names
beta: the inverse temperture to extract sample for
size: a size the is smaller than the actual sample size, if left unchanged, all sampled points are returned

Value

a matrix of sampled points, all with the same temperature

Details

This function selects and collects all rows, from all files with the same (given) temperature.

This function should be used if you need to inspect only one of the temperatures, not all of them. This function is similar to loadSample_mpi, which returns all temperatures. But, whearas lodSample_mpi returns a list, this function returns the sample-matrix itself (because the result of this function is conceptually similar to sampling on one node, with one temperature).

Examples

rprior <- rNormalPrior(seq(3),seq(4,5)) # some nonsense
N <- 100
f <- c(tempfile(),tempfile())

## first fake sample
X <- rprior(N)
attr(X,"beta") <- sample(1/seq(2)^2,N,replace=TRUE)
attr(X,"acceptanceRate") <- 0.23
attr(X,"swapRate") <- 0.1
attr(X,"logLikelihood") <- rnorm(N,-100,30)
saveRDS(X,file=f[1])

## second fake sample
X <- rprior(N)
attr(X,"beta") <- sample(1/seq(2)^2,N,replace=TRUE)
attr(X,"acceptanceRate") <- 0.23
attr(X,"swapRate") <- 0.1
attr(X,"logLikelihood") <- rnorm(N,-100,30)
saveRDS(X,file=f[2])

Z <- gatherSample(f,beta=1)
print(N)
#> [1] 100
print(dim(Z)) ## should be c(2*N,3)
#> [1] 90  3
print(names(attributes(Z)))
#> [1] "dim"           "beta"          "logLikelihood" "stepSize"