71 lines
1.5 KiB
Plaintext
71 lines
1.5 KiB
Plaintext
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<%@include file="includes/setup.md.rsp"%>
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<%@string fcnname="weightedMean_subset"%>
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<%@string subname="weightedMean"%>
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<%@meta title="${subname}() benchmarks on subsetted computation"%>
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<%@meta author="Dongcan Jiang"%>
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<%@meta date="2015-06-07"%>
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<%@include file="${header}"%>
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# <%@meta name="title"%>
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This report benchmark the performance of <%=subname%>() on subsetted computation.
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<% for (mode in c("integer", "double")) { %>
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## Data type "<%=mode%>"
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### Data
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```r
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<%=withCapture({
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<%@include file="R/random-vectors.R"%>
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data <- rvectors(mode = mode)
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data <- data[1:4]
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})%>
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```
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## Results
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<% for (ii in seq_along(data)) { %>
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<%
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dataLabel <- names(data)[ii]
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mprintf("%s: %s\n", mode, dataLabel)
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%>
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### <%=dataLabel%> vector
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```r
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<%=withCapture({
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x <- data[[.dataLabel.]]
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idxs <- sample.int(length(x), size = length(x)*0.7)
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x_S <- x[idxs]
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w <- runif(length(x))
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w_S <- w[idxs]
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gc()
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stats <- microbenchmark(
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"weightedMean_x_w_S" = weightedMean(x_S, w = w_S, na.rm = FALSE),
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"weightedMean(x, w, idxs)" = weightedMean(x, w = w, idxs = idxs, na.rm = FALSE),
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"weightedMean(x[idxs], w[idxs])" = weightedMean(x[idxs], w = w[idxs], na.rm = FALSE),
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unit = "ms"
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)
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})%>
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```
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<% benchmarkResults(stats, tags=c(mode, dataLabel)) %>
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<% } # for (ii ...) %>
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<% } # for (mode ...) %>
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<%@include file="${footer}"%>
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<%---------------------------------------------------------------------------
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HISTORY:
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2015-06-07
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o Created.
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---------------------------------------------------------------------------%>
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