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Type 'q()' to quit R. > library("matrixStats") > library("stats") > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Naive R implementation of binMeans() > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > binMeans0 <- function(y, x, bx, na.rm = TRUE, count = TRUE, right = FALSE) { + n_smooth <- length(bx) - 1L + res <- double(n_smooth) + counts <- rep(NaN, times = n_smooth) + + if (na.rm) { + keep <- !is.na(x) & !is.na(y) + x <- x[keep] + y <- y[keep] + } + + # For each bin... + for (kk in seq_len(n_smooth)) { + if (right) { + idxs <- which(bx[kk] < x & x <= bx[kk + 1L]) + } else { + idxs <- which(bx[kk] <= x & x < bx[kk + 1L]) + } + y_kk <- y[idxs] + res[kk] <- mean(y_kk) + counts[kk] <- length(idxs) + } # for (kk ...) + + if (count) attr(res, "count") <- counts + res + } > > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Case #1 > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > x <- 1:100 > nx <- length(x) > y <- double(nx) > y[1:25] <- 5 > y[51:75] <- -5 > y <- y + rnorm(nx) > > # Bins > bx <- c(0.5, 25.5, 50.5, 75.5, 100.5) > > y_smooth0 <- binMeans0(y, x = x, bx = bx) > y_smooth <- binMeans(y, x = x, bx = bx) > n_smooth <- binCounts(x, bx = bx) > # Sanity check > stopifnot(all.equal(y_smooth, y_smooth0)) > stopifnot(all.equal(attr(y_smooth, "count"), n_smooth)) > > y_smooth0r <- rev(binMeans0(y, x = -x, bx = rev(-bx), + count = FALSE, right = TRUE)) > y_smoothr <- rev(binMeans(y, x = -x, bx = rev(-bx), + count = FALSE, right = TRUE)) > # Sanity check > stopifnot(all.equal(y_smooth0r, y_smooth0, check.attributes = FALSE)) > stopifnot(all.equal(y_smoothr, y_smooth0r)) > > > # Integer input > y <- as.integer(y) > y_smooth0 <- binMeans0(y, x = x, bx = bx) > y_smooth <- binMeans(y, x = x, bx = bx) > n_smooth <- binCounts(x, bx = bx) > # Sanity check > stopifnot(is.integer(y), + all.equal(y_smooth, y_smooth0), + all.equal(attr(y_smooth, "count"), n_smooth)) > > # Logical input > y <- as.logical(y) > y_smooth0 <- binMeans0(y, x = x, bx = bx) > y_smooth <- binMeans(y, x = x, bx = bx) > n_smooth <- binCounts(x, bx = bx) > # Sanity check > stopifnot(is.logical(y), + all.equal(y_smooth, y_smooth0), + all.equal(attr(y_smooth, "count"), n_smooth)) > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Case #2 > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > nx <- 1e3 > x <- runif(nx) > y <- runif(nx) > > nb <- 10 > bx <- do.call(seq, c(as.list(range(x)), length.out = nb)) > bx1 <- c(bx[-1], bx[nb] + 1) > > y_smooth0 <- binMeans0(y, x = x, bx = bx1) > y_smooth <- binMeans(y, x = x, bx = bx1) > n_smooth <- binCounts(x, bx = bx1) > y_smoothr <- rev(binMeans(y, x = -x, bx = rev(-bx1), right = TRUE)) > > # Sanity check > stopifnot(all.equal(y_smooth, y_smooth0)) > stopifnot(all.equal(attr(y_smooth, "count"), n_smooth)) > stopifnot(all.equal(y_smoothr, y_smooth, check.attributes = FALSE)) > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Empty bins > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > x <- c(6:8, 16:19) > nx <- length(x) > y <- runif(nx) > bx <- c(0, 5, 10, 15, 20, 25) > y_smooth0 <- binMeans0(y, x = x, bx = bx) > y_smooth <- binMeans(y, x = x, bx = bx) > n_smooth <- binCounts(x, bx = bx) > stopifnot(all.equal(attr(y_smooth, "count"), n_smooth)) > stopifnot(all.equal(y_smooth, y_smooth0)) > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Missing values > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > x <- 1:100 > x[50] <- NA_integer_ > nx <- length(x) > y <- double(nx) > y[1:25] <- 5 > y[51:75] <- -5 > y[82:92] <- NA_real_ > y <- y + rnorm(nx) > > # Bins > bx <- c(0.5, 25.5, 75.5, 82.5, 100.5) > > y_smooth0 <- binMeans0(y, x = x, bx = bx) > y_smooth <- binMeans(y, x = x, bx = bx) > # Sanity check > stopifnot(all.equal(y_smooth, y_smooth0)) > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Exception handling > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Zero bin bounderies (invalid bin definition) > bx <- double(0L) > res <- try(y_smooth <- binMeans(x = 1:5, y = 1:5, bx = bx), silent = TRUE) > stopifnot(inherits(res, "try-error")) > > # One bin boundery (invalid bin definition) > bx <- double(1L) > res <- try(y_smooth <- binMeans(x = 1:5, y = 1:5, bx = bx), silent = TRUE) > stopifnot(inherits(res, "try-error")) > > proc.time() user system elapsed 0.17 0.03 0.18