76 lines
1.9 KiB
Plaintext
76 lines
1.9 KiB
Plaintext
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<%@include file="includes/setup.md.rsp"%>
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<%@string colname="colWeightedMeans"%>
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<%@string rowname="rowWeightedMeans"%>
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<%@string fcnname="colRowWeightedMeans_subset"%>
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<%@meta title="${colname}() and ${rowname}() benchmarks on subsetted computation"%>
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<%@meta author="Dongcan Jiang"%>
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<%@meta date="2015-06-07"%>
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<%@include file="${header}"%>
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# <%@meta name="title"%>
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This report benchmark the performance of <%=colname%>() and <%=rowname%>() on subsetted computation.
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## Data
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```r
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<%=withCapture({
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<%@include file="R/random-matrices.R"%>
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data <- rmatrices(mode = "double")
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})%>
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```
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## Results
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<% for (dataLabel in names(data)) { %>
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<% message(dataLabel) %>
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### <%=dataLabel%> matrix
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```r
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<%=withCapture({
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X <- data[[.dataLabel.]]
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rows <- sample.int(nrow(X), size = nrow(X)*0.7)
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cols <- sample.int(ncol(X), size = ncol(X)*0.7)
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X_S <- X[rows, cols]
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w <- runif(nrow(X))
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w_S <- w[rows]
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gc()
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colStats <- microbenchmark(
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"colWeightedMeans_X_w_S" = colWeightedMeans(X_S, w = w_S, na.rm = FALSE),
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"colWeightedMeans(X, w, rows, cols)" = colWeightedMeans(X, w = w, rows = rows, cols = cols, na.rm = FALSE),
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"colWeightedMeans(X[rows, cols], w[rows])" = colWeightedMeans(X[rows, cols], w = w[rows], na.rm = FALSE),
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unit = "ms"
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)
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X <- t(X)
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X_S <- t(X_S)
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gc()
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rowStats <- microbenchmark(
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"rowWeightedMeans_X_w_S" = rowWeightedMeans(X_S, w = w_S, na.rm = FALSE),
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"rowWeightedMeans(X, w, cols, rows)" = rowWeightedMeans(X, w = w, rows = cols, cols = rows, na.rm = FALSE),
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"rowWeightedMeans(X[cols, rows], w[rows])" = rowWeightedMeans(X[cols, rows], w = w[rows], 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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<% crBenchmarkResults(colStats, rowStats, tags=dataLabel) %>
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<% } # for (dataLabel ...) %>
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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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