<%@include file="includes/setup.md.rsp"%>

<%@string fcnname="binMeans"%>
<% fcnname <- "<%@string name="fcnname"%>" %>
<%@meta title="${fcnname}() benchmarks"%>
<%@meta author="Henrik Bengtsson"%>
<%@meta date="2014-06-04"%>

<%@include file="${header}"%>


# <%@meta name="title"%>

This report benchmark the performance of <%=fcnname%>() against alternative methods.

## Alternative methods

* binMeans_R()

which is defined as

```r
<%=withCapture({
binMeans_R <- function(y, x, bx, na.rm = FALSE, count = TRUE, right = FALSE) {
  B <- length(bx)-1L
  res <- double(B)
  counts <- integer(B)

  # For each bin...
  for (kk in seq_len(B)) {
    if (right) {
      idxs <- which(bx[kk] <  x & x <= bx[kk+1L])
    } else {
      idxs <- which(bx[kk] <= x & x <  bx[kk+1L])
    }
    yKK <- y[idxs]
    muKK <- mean(yKK)
    res[kk] <- muKK
    counts[kk] <- length(idxs)
  } # for (kk ...)

  if (count) attr(res, "count") <- counts
  res
} # binMeans_R()
})%>
```

## Results

### Non-sorted simulated data
```r
<%=withCapture({
nx <- 10e3 # Number of data points
set.seed(0xBEEF)
x <- runif(nx, min = 0, max = 1)
y <- runif(nx, min = 0, max = 1)

# Uniformely distributed bins
nb <- 1e3 # Number of bins
bx <- seq(from = 0, to = 1, length.out = nb+1L)
bx <- c(-1, bx, 2)
})%>
```

<% benchmark <- function() { %>
<% dataLabel <- if (is.unsorted(x)) "unsorted" else "sorted" %>
<% message(dataLabel) %>
```r
<%=withCapture({
gc()

stats <- microbenchmark(
 binMeans   = binMeans(x = x, y = y, bx = bx, count = TRUE),
 binMeans_R = binMeans_R(x = x, y = y, bx = bx, count = TRUE),
 unit = "ms"
)
})%>
```

<% benchmarkResults(stats, tags=dataLabel) %>
<% } # benchmark() %>

<% benchmark() %>


### Sorted simulated data
```r
<%=withCapture({
  x <- sort(x)
})%>
```
<% benchmark() %>


<%@include file="${footer}"%>


<%---------------------------------------------------------------------------
HISTORY:
2014-06-02
o Restructured.
2014-05-25
o Created.
---------------------------------------------------------------------------%>