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## Slightly optimised version of
## coda::effectiveSize
## https://cran.r-project.org/web/packages/coda/
#' @importFrom matrixStats colVars
#' @importFrom stats ar setNames
ess <- function(x) {
vars <- matrixStats::colVars(x)
spec <- numeric(ncol(x))
has_var <- vars != 0
if (any(has_var, na.rm = TRUE)) {
spec[which(has_var)] <- apply(x[, which(has_var), drop = FALSE],
2,
function(y) {
a <- ar(y, aic = TRUE)
a$var.pred / (1 - sum(a$ar)) ^ 2
}
)
}
setNames(ifelse(spec == 0, 0, nrow(x) * vars / spec), colnames(x))
}
.ScaleName <- function(Measure = c("ess", "geweke.diag"),
Parameter = NULL) {
Measure <- match.arg(Measure)
measure_name <- switch(Measure,
ess = "Effective sample size",
geweke.diag = "Geweke diagnostic"
)
if (!is.null(Parameter)) {
measure_name <- paste0(measure_name, ": ", Parameter)
}
measure_name
}
#' @importFrom coda geweke.diag
.GetMeasure <- function(Chain,
Parameter,
Measure = c("ess", "geweke.diag"),
na.rm = FALSE) {
Measure <- match.arg(Measure)
MeasureFun <- match.fun(Measure)
mat <- .GetParam(Chain, Parameter)
if (Measure == "ess" & !is.null(attr(mat, "ESS"))) {
return(attr(mat, "ESS"))
}
if (na.rm) {
mat <- mat[, !apply(mat, 2, function(col) any(is.na(col)))]
if (!ncol(mat)) {
stop(paste("No non-NA samples for", Parameter))
}
}
metric <- MeasureFun(coda::mcmc(mat))
if (Measure == "geweke.diag") {
metric <- metric$z
}
metric
}
.GetParam <- function(object, Parameter = "mu") {
if (is.null(Parameter) ||
is.na(Parameter) ||
length(Parameter) > 1 ||
!(Parameter %in% names(object@parameters))) {
stop("'Parameter' argument is invalid")
}
object@parameters[[Parameter]]
}
.CheckValidCombination <- function(...) {
Params <- list(...)
Check1 <- vapply(Params,
FUN = function(x) is.null(x) || x %in% .GeneParams(),
FUN.VALUE = TRUE)
Check2 <- vapply(Params,
FUN = function(x) is.null(x) || x %in% .CellParams(),
FUN.VALUE = TRUE)
if (!(all(Check1) || all(Check2))) {
stop(paste("Invalid combination of parameters:",
paste(list(...), collapse = ", "), " \n"))
}
}
.GeneParams <- function() c("mu", "delta", "epsilon", "lambda")
.CellParams <- function() c("s", "phi", "nu")
.NClassFD2D <- function(x, y) {
max(nclass.FD(x), nclass.FD(y))
}
.MeasureName <- function(measure) {
switch(measure,
"Mean" = "mean expression",
"Disp" = "over dispersion",
"ResDisp" = "residual over dispersion"
)
}
.DistanceName <- function(measure) {
switch(measure,
"ResDisp" = "distance",
"fold change")
}
.LogDistanceName <- function(measure) {
switch(measure,
"ResDisp" = "distance",
"log2(fold change)"
)
}
.DistanceVar <- function(measure) {
switch(measure,
"ResDisp" = "Distance",
"Log2FC"
)
}
.cap <- function(s) {
sub("([[:alpha:]])([[:alpha:]]+)", "\\U\\1\\L\\2", s, perl = TRUE)
}
.NSamples <- function(Chain) {
nrow(Chain@parameters[[1]])
}
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