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79 lines
2.3 KiB
79 lines
2.3 KiB
9 years ago
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#!/usr/bin/env Rscript
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library(ggplot2);
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library(plyr);
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# get __dirname and load ./_cli.R
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args = commandArgs(trailingOnly = F);
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dirname = dirname(sub("--file=", "", args[grep("--file", args)]));
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source(paste0(dirname, '/_cli.R'), chdir=T);
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if (is.null(args.options$xaxis) || is.null(args.options$category) ||
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(!is.null(args.options$plot) && args.options$plot == TRUE)) {
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stop("usage: cat file.csv | Rscript scatter.R [variable=value ...]
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--xaxis variable variable name to use as xaxis (required)
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--category variable variable name to use as colored category (required)
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--plot filename save plot to filename
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--log use a log-2 scale for xaxis in the plot");
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}
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plot.filename = args.options$plot;
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# parse options
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x.axis.name = args.options$xaxis;
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category.name = args.options$category;
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use.log2 = !is.null(args.options$log);
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# parse data
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dat = read.csv(file('stdin'), strip.white=TRUE);
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dat = data.frame(dat);
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# List of aggregated variables
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aggregate = names(dat);
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aggregate = aggregate[
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! aggregate %in% c('rate', 'time', 'filename', x.axis.name, category.name)
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];
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# Variables that don't change aren't aggregated
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for (aggregate.key in aggregate) {
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if (length(unique(dat[[aggregate.key]])) == 1) {
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aggregate = aggregate[aggregate != aggregate.key];
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}
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}
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# Print out aggregated variables
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for (aggregate.variable in aggregate) {
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cat(sprintf('aggregating variable: %s\n', aggregate.variable));
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}
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if (length(aggregate) > 0) {
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cat('\n');
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}
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# Calculate statistics
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stats = ddply(dat, c(x.axis.name, category.name), function(subdat) {
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rate = subdat$rate;
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# calculate standard error of the mean
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se = sqrt(var(rate)/length(rate));
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# calculate mean and 95 % confidence interval
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r = list(
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rate = mean(rate),
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confidence.interval = se * qt(0.975, length(rate) - 1)
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);
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return(data.frame(r));
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});
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print(stats, row.names=F);
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if (!is.null(plot.filename)) {
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p = ggplot(stats, aes_string(x=x.axis.name, y='mean', colour=category.name));
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if (use.log2) {
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p = p + scale_x_continuous(trans='log2');
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}
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p = p + geom_errorbar(aes(ymin=mean-confidence.interval, ymax=mean+confidence.interval), width=.1);
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p = p + geom_point();
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p = p + ylab("rate of operations (higher is better)");
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p = p + ggtitle(dat[1, 1]);
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ggsave(plot.filename, p);
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}
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