#' Print an overview of a fitted combi x
#' @param x a fitted combi x
#' @param ... Further arguments, currently ignored
#'
#' @return An overview of the number of dimensions, views and parameters,
#' type of ordination and importance parameters
#' @method print combi
#'
#' @export
#' @examples
#' data(Zhang)
#' \dontrun{
#' #Unconstrained
#' microMetaboInt = combi(
#' list("microbiome" = zhangMicrobio, "metabolomics" = zhangMetabo),
#' distributions = c("quasi", "gaussian"), compositional = c(TRUE, FALSE),
#' logTransformGaussian = FALSE, verbose = TRUE)
#' #Constrained
#' microMetaboIntConstr = combi(
#' list("microbiome" = zhangMicrobio, "metabolomics" = zhangMetabo),
#' distributions = c("quasi", "gaussian"), compositional = c(TRUE, FALSE),
#' logTransformGaussian = FALSE, covariates = zhangMetavars, verbose = TRUE)}
#' #Load the fits
#' load(system.file("extdata", "zhangFits.RData", package = "combi"))
#' print(microMetaboInt)
#' print(microMetaboIntConstr)
#' #Or simply
#' microMetaboInt
print.combi = function(x, ...){
constr = if(is.null(x$covariates)) "Unconstrained" else "Constrained"
dim = length(x$iter)
datSets = length(x$data)
nSam = nrow(x$latentVars)
psis = signif(diag(crossprod(x$latentVars)), 3) #Some measure of importance
viewsString = vapply(seq_along(x$data), FUN.VALUE = character(1),
function(i){
paste0(names(x$data[i]),": ", ncol(x$paramEsts[[i]]), "\n")
})
cat(constr, "combi ordination of", dim, "dimensions on",
datSets, "views with", nSam,
"samples.\nViews and number of features were:\n", viewsString,
if(!is.null(x$covariates)) {
paste0("Number of sample variables included was ",ncol(x$covariates),
",\nfor which ", ncol(x$covMat),
" parameters were estimated per dimension.\n")
}, "Importance parameters of dimensions", 1, "to", dim,
"are", paste(psis[-dim], collapse = ","), "and", psis[dim])
}
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