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    ## Do this in a separate file to see the generated help:
    #library(devtools)
    #document()
    #load_all(as.package("../../onlineforecast"))
    #?"%**%"
    
    #' Multiplication of each element in a list (x) with y
    #'
    #' Each element of x is multiplied with y using the usual elementwise '*' operator.
    #'
    #' Typical use is when a function, e.g. \code{\link{bspline}()}, returns a list of matrices (e.g. one for each base spline) and they should individually be multiplied with y (a vector, matrix, etc.).
    #' 
    #' Since this is intended to be used for forecast models in the transformation stage 
    #' then there are some percularities:
    #'
    #' If the number of columns or the names of the columns are not equal for one element in x
    #' and y, then only the columns with same names are used, hence the resulting matrices can be
    #' of lower dimensions.
    #'
    
    #' See the example \url{https://onlineforecasting.org/examples/solar-power-forecasting.html} where the operator is used.
    
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    #' 
    #' @title Multiplication of list with y, elementwise
    #' @param x a list of matrices, data.frames, etc.
    #' @param y a vector, data.frame or matrix
    #' @return A list of same length of x
    #' @examples
    #'
    #' x <- list(matrix(1:9,3), matrix(9:1,3))
    #' x
    #' 
    #' y <- matrix(2,3,3)
    #' y
    #'
    #' x %**% y
    #'
    #' y <- 1:3
    #'
    #' x %**% y
    #'
    #' # Naming percularity
    #' nams(x[[1]]) <- c("k1","k2","k3")
    #' nams(x[[2]]) <- c("k2","k3","k4")
    #' y <- matrix(2,3,3)
    #' nams(y) <- c("k1","k3","k7")
    #'
    #' # Now the only the horizons matching will be used
    #' x %**% y
    #' 
    #' @export
    
    "%**%" <- function(x, y) {
        if( is.null(dim(y)) ){
            ## y is not matrix like
            lapply(x, function(xx) {
                xx * y
            })
        }else{
            ## y is matrix like
            lapply(x, function(xx) {
                ## Check if different horizon k columns
                colmatch <- TRUE
                if (ncol(xx) != ncol(y)) {
                    colmatch <- FALSE
                }else if(any(nams(xx) != nams(y))){
                    colmatch <- FALSE
                }
                if(!colmatch){
                    ## Not same columns, take only the k in both
                    nms <- nams(xx)[nams(xx) %in% nams(y)]
                    xx <- xx[, nms]
                    y <- y[, nms]
                }
                ## Now multiply
                val <- xx * y
                ## Must be data.frame
                if( is.null(dim(val)) ){
                    val <- data.frame(val)
                    nams(val) <- nms
                }
                return(val)
            })
        }
    }