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

<%@string colname="colMeans2"%>
<%@string rowname="rowMeans2"%>
<%@string fcnname="colRowMeans2_subset"%>
<%@meta title="${colname}() and ${rowname}() benchmarks  on subsetted computation"%>
<%@meta author="Henrik Bengtsson"%>
<%@meta date="2017-03-31"%>

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



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

This report benchmark the performance of <%=colname%>() and <%=rowname%>() on subsetted computation.


<% 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.]]
rows <- sample.int(nrow(X), size = nrow(X)*0.7)
cols <- sample.int(ncol(X), size = ncol(X)*0.7)
X_S <- X[rows, cols]
gc()

colStats <- microbenchmark(
 "colMeans2_X_S"           = colMeans2(X_S, na.rm = FALSE),
 "colMeans2(X, rows, cols)"  = colMeans2(X, rows = rows, cols = cols, na.rm = FALSE),
 "colMeans2(X[rows, cols])" = colMeans2(X[rows, cols], na.rm = FALSE),
 unit = "ms"
)

X <- t(X)
X_S <- t(X_S)
gc()

rowStats <- microbenchmark(
 "rowMeans2_X_S"           = rowMeans2(X_S, na.rm = FALSE),
 "rowMeans2(X, cols, rows)"  = rowMeans2(X, rows = cols, cols = rows, na.rm = FALSE),
 "rowMeans2(X[cols, rows])" = rowMeans2(X[cols, rows], na.rm = FALSE),
 unit = "ms"
)
})%>
```

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

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

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


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