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

<%@string colname="colMeans2"%>
<%@string rowname="rowMeans2"%>
<%@meta title="${colname}() and ${rowname}() benchmarks"%>
<%@meta author="Henrik Bengtsson"%>
<%@meta date="2017-03-31"%>

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

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

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

## Alternative methods

* apply() + mean()
* .colMeans() and .rowMeans()
* colMeans() and rowMeans()

<% for (mode in c("integer", "double")) { %>

## Data type "<%=mode%>"

### Data
```r
<%=withCapture({
<%@include file="R/random-matrices.R"%>
data <- rmatrices(mode = mode)
})%>
```

### Results

<% for (dataLabel in names(data)) { %>
<% mprintf("%s: %s\n", mode, dataLabel)  %>
#### <%=dataLabel%> <%=mode%> matrix

```r
<%=withCapture({
X <- data[[.dataLabel.]]
gc()

colStats <- microbenchmark(
 colMeans2    = colMeans2(X, na.rm = FALSE),
 .colMeans    = .colMeans(X, m = nrow(X), n = ncol(X), na.rm = FALSE),
 colMeans     = colMeans(X, na.rm = FALSE),
"apply+mean"  = apply(X, MARGIN = 2L, FUN = mean, na.rm = FALSE),
 unit = "ms"
)

X <- t(X)
gc()

rowStats <- microbenchmark(
 rowMeans2    = rowMeans2(X, na.rm = FALSE),
 .rowMeans    = .rowMeans(X, m = nrow(X), n = ncol(X), na.rm = FALSE),
 rowMeans     = rowMeans(X, na.rm = FALSE),
"apply+mean"  = apply(X, MARGIN = 1L, FUN = mean, na.rm = FALSE),
 unit = "ms"
)
})%>
```

<% crBenchmarkResults(colStats, rowStats, tags=c(mode, dataLabel)) %>

<% } # for (dataLabel ...) %>

<% } # for (mode ...) %>


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