R/RcppExports.R

In rtrend: Trend Estimating Tools

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

#' @rdname slope
#' @export
slope_sen <- function(y, x = NULL) {
    .Call(`_rtrend_slope_sen`, y, x)
}

Sf <- function(x) {
    .Call(`_rtrend_Sf`, x)
}

varS <- function(x, rof, S) {
    .Call(`_rtrend_varS`, x, rof, S)
}

sgmat_S <- function(halfwin = 5L, d = 2L) {
    .Call(`_rtrend_sgmat_S`, halfwin, d)
}

sgmat_B <- function(S) {
    .Call(`_rtrend_sgmat_B`, S)
}

sgmat_wB <- function(S, w) {
    .Call(`_rtrend_sgmat_wB`, S, w)
}

#' Weighted Savitzky-Golay
#'
#' NA and Inf values in the y has been ignored automatically.
#'
#' @param y colvec
#' @param w colvec of weight
#' @param halfwin halfwin of Savitzky-Golay
#' @param d polynomial of degree. When d = 1, it becomes moving average.
#'
#' @examples
#' y <- c(1, 3, 2, 5, 6, 8, 10, 1)
#' w <- seq_along(y)/length(y)
#'
#' halfwin = 2
#' d = 2
#' s1 <- smooth_wSG(y, halfwin, d, w)
#' s2 <- smooth_SG(y, halfwin, d)
#' @export
smooth_wSG <- function(y, halfwin = 1L, d = 1L, w = NULL) {
    .Call(`_rtrend_smooth_wSG`, y, halfwin, d, w)
}

#' @rdname smooth_wSG
#' @export
smooth_SG <- function(y, halfwin = 1L, d = 1L) {
    .Call(`_rtrend_smooth_SG`, y, halfwin, d)
}

#' movmean
#'
#' NA and Inf values in the y will be ignored automatically.
#'
#' @param y A numeric vector.
#' @param halfwin Integer, half of moving window size
#' @param w Corresponding weights of y, with the same length.
#' @param SG_style If true, head and tail values will be in the style of SG
#' (more weights on the center point), else traditional moving mean style.
#'
#' @examples
#' x <- 1:100
#' x[50] <- NA; x[80] <- Inf
#' s1 <- movmean(x, 2, SG_style = TRUE)
#' s2 <- movmean(x, 2, SG_style = FALSE)
#' movmean2(c(4, 8, 6, -1, -2, -3, -1), 2, 0)
#' movmean2(c(4, 8, NA, -1, -2, Inf, -1), 2, 0)
#' @export
movmean <- function(y, halfwin = 1L, SG_style = FALSE, w = NULL) {
    .Call(`_rtrend_movmean`, y, halfwin, SG_style, w)
}

#' @param win_left,win_right windows size in the left and right
#' @rdname movmean
#' @export
movmean2 <- function(y, win_left = 1L, win_right = 0L, w = NULL) {
    .Call(`_rtrend_movmean2`, y, win_left, win_right, w)
}

#' @param mat numeric matrix
#' @rdname movmean
#' @export
movmean_2d <- function(mat, win_left = 3L, win_right = 0L) {
    .Call(`_rtrend_movmean_2d`, mat, win_left, win_right)
}