R Under development (unstable) (2023-12-09 r85665 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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 
   0.14    0.07    0.20