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Shubham Gupta
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Add benchmark image
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‎.gitignore

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erl_crash.dump
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*.ez
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*.swp
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graphs/*
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snapshots/*

‎README.md

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MIX_ENV=test mix test
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```
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## Benchmarks
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- We use benchfella for the benchmark tests. Run it using the following
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```
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MIX_ENV=test mix bench
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MIX_ENV=test mix bench
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# Generate graphs of the above runs
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MIX_ENV=test mix bench.graph
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```
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- The report is available [here](http://htmlpreview.github.io/?https://github.com/scripbox/ex-xirr/blob/master/bench/graphs/index.html)
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## Credits
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This application is built on the fantastic [finance-elixir](https://github.com/tubedude/finance-elixir) package. Many thanks to [tubedude](https://github.com/tubedude) for his work.

‎bench/.gitignore

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graphs/*
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snapshots/*

‎bench/graphs/index.html

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<html>
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<head>
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<meta http-equiv="content-type" content="text/html; charset=utf-8">
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<title>Index</title>
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<script src="http://d3js.org/d3.v3.min.js" charset="utf-8"></script>
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<script src="http://code.jquery.com/jquery-2.1.1.min.js" charset="utf-8"></script>
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<script src="http://underscorejs.org/underscore-min.js" charset="utf-8"></script>
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<style>.data-axis path,
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.data-axis line {
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fill: none;
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stroke: black;
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shape-rendering: crispEdges;
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}
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.data-axis text {
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font-family: sans-serif;
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font-size: 11px;
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}
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.axis path,
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.axis line {
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fill: none;
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stroke: #000;
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shape-rendering: crispEdges;
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}
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rect {
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stroke: black;
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shape-rendering: crispEdges;
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}
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</style>
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</head>
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<body>
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<p>Scale:
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<select id="scale-selector">
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<option>linear</option>
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<option>log10</option>
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</select>
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</p>
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<script id="json-data" type="application/json" charset="utf-8">{"bench/snapshots/2018-06-08_12-22-07.snapshot": {
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"options": {"duration":1.0,"mem stats":false,"sys mem stats":false},
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"tests": [{"elapsed":2878368,"iter":1000,"module":"XirrComparisonBench","tags":[],"test":"long investment bisection method"},{"elapsed":2126197,"iter":10000,"module":"XirrComparisonBench","tags":[],"test":"long investment newton method"}]
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},"bench/snapshots/2018-06-08_12-22-13.snapshot": {
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"options": {"duration":1.0,"mem stats":false,"sys mem stats":false},
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"tests": [{"elapsed":1430888,"iter":500,"module":"XirrComparisonBench","tags":[],"test":"long investment bisection method"},{"elapsed":2122958,"iter":10000,"module":"XirrComparisonBench","tags":[],"test":"long investment newton method"}]
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}}</script>
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<script type="text/javascript">var CHART_OFFSET_X = 150;
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var CHART_WIDTH = 600;
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var DATA_LABEL_OFFSET_X = 10;
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var BAR_HEIGHT = 20;
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var BAR_SPACING = 10;
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var BAR_HEIGHT_TOTAL = BAR_HEIGHT + BAR_SPACING;
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var BLUES = ["#deebf7", "#c6dbef", "#9ecae1", "#6baed6", "#4292c6", "#2171b5", "#08519c"];
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var GREENS = ["#e5f5e0", "#c7e9c0", "#a1d99b", "#74c476", "#41ab5d", "#238b45", "#006d2c"];
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var BLACKS = ["#f0f0f0", "#d9d9d9", "#bdbdbd", "#969696", "#737373", "#525252", "#252525"];
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var ORANGES = ["#fee6ce", "#fdd0a2", "#fdae6b", "#fd8d3c", "#f16913", "#d94801", "#a63603"];
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var VIOLETS = ["#efedf5", "#dadaeb", "#bcbddc", "#9e9ac8", "#807dba", "#6a51a3", "#54278f"];
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var REDS = ["#fee0d2", "#fcbba1", "#fc9272", "#fb6a4a", "#ef3b2c", "#cb181d", "#a50f15"];
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var NCOLORS = 7;
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var COLORS = [BLUES, GREENS, ORANGES, VIOLETS, REDS, BLACKS];
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var PALETTE = ["#edf8fb", "#ccece6", "#99d8c9", "#66c2a4", "#2ca25f", "#006d2c"].reverse();
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//var PALETTE = ["#f1eef6", "#d4b9da", "#c994c7", "#df65b0", "#dd1c77", "#980043"].reverse();
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//var PALETTE = ["#fee5d9", "#fcbba1", "#fc9272", "#fb6a4a", "#de2d26", "#a50f15"].reverse();
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//var PALETTE = ["#f2f0f7", "#dadaeb", "#bcbddc", "#9e9ac8", "#756bb1", "#54278f"].reverse();
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//var PALETTE = ["#ffffcc", "#c7e9b4", "#7fcdbb", "#41b6c4", "#2c7fb8", "#253494"].reverse();
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function color_at(i, j) {
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if (!j) j = 0;
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return PALETTE[(i+j)%PALETTE.length];
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//return COLORS[i % COLORS.length][NCOLORS - 1 - j % NCOLORS];
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}
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function format_time(time) {
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return parseFloat(Math.round(time * 100) / 100).toFixed(2) + " µs/op";
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}
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function add_chart(name, tests, scale) {
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d3.select("body").append("h2").text(name);
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var svg = d3.select("body").append("svg");
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make_chart(svg, name, tests, scale);
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}
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function make_chart(svg, name, tests, scale) {
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var svgWidth = 1000;
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var svgHeight = _.keys(tests).length * BAR_HEIGHT_TOTAL + 50;
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svg.attr({
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width: svgWidth,
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height: svgHeight,
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});
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var nums = _.map(tests, function(val) { return val.elapsed / val.n; });
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var names = _.map(tests, function(val, name) { return name; });
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var dataScale;
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if (scale == "linear") {
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dataScale = d3.scale.linear().domain([0, d3.max(nums)]).range([0, CHART_WIDTH]);
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} else if (scale == "log10") {
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dataScale = d3.scale.log().domain([1, d3.max(nums)]).range([0, CHART_WIDTH]);
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}
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svg.selectAll("rect")
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.data(nums)
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.enter()
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.append("rect")
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.attr({
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x: CHART_OFFSET_X,
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y: function(d, i) { return i * (BAR_HEIGHT + BAR_SPACING); },
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width: function(d) { return dataScale(d); },
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height: BAR_HEIGHT,
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fill: function(d, i) { return color_at(i, 0); },
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});
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svg.selectAll("text.label")
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.data(names)
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.enter()
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.append("text")
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.attr({
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class: "label",
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y: function(d, i) { return i * BAR_HEIGHT_TOTAL + BAR_HEIGHT_TOTAL/2; },
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})
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.text(function(d) { return d; });
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svg.selectAll("text.timing")
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.data(nums)
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.enter()
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.append("text")
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.attr({
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class: "timing",
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x: CHART_OFFSET_X + CHART_WIDTH + DATA_LABEL_OFFSET_X,
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y: function(d, i) { return i * 30 + 15; },
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})
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.text(function(d) { return format_time(d); });
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var xAxis = d3.svg.axis()
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.scale(dataScale)
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.ticks(5);
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var axisY = nums.length * 30;
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svg.append("g")
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.attr({transform: "translate("+CHART_OFFSET_X+", "+axisY+")"})
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.attr("class", "data-axis")
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.call(xAxis);
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}
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function add_comparison_chart(name, categories, scale) {
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//d3.select("body").append("h2").text(name);
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var svg = d3.select("body").append("svg");
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make_comparison_chart(svg, categories, scale);
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}
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function make_comparison_chart(svg, categories, scale) {
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var svgWidth = 1200;
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var svgHeight = 500;
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svg.attr({width: svgWidth, height: svgHeight});
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var values = _.chain(categories)
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.map(function(snapshots) { return snapshots; })
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.flatten()
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.map(function(dict) { return dict.elapsed / dict.n; })
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.value();
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var snapshotCount;
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for (var key in categories) {
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snapshotCount = categories[key].length;
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break;
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}
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var catCount = _.size(categories);
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var xPadding = 0;
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var left = xPadding;
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var right = svgWidth-2*xPadding;
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var w0 = (right - left) / catCount;
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var pad = 0.3;
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var truePad = 1 - (1 - pad) / snapshotCount;
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var xScale = d3.scale.ordinal()
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.domain(_.map(categories, function(x, key) { return key; }))
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.rangeBands([left, right-w0], truePad, 0);
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//var nums = _.map(tests, function(val) { return val.elapsed / val.n; });
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//var names = _.map(tests, function(val, name) { return name; });
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var dataScale;
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var yExtent = [0, svgHeight-50];
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if (scale == "linear") {
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dataScale = d3.scale.linear()
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.domain([d3.max(values), 0])
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.range(yExtent);
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} else if (scale == "log10") {
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dataScale = d3.scale.log()
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.domain([d3.max(values), 0.01])
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.range(yExtent);
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}
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var xOffset = 60;
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var rectOffset = xOffset + 5;
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for (var i = 0; i < snapshotCount; i++) {
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// Go through the ith snapshot of each category
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var sample = _.map(categories, function(snapshots, key) {
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var val = snapshots[i];
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return {cat: key, val: val.elapsed / val.n};
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});
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console.log(sample);
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svg.append("g").selectAll("rect")
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.data(sample)
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.enter()
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.append("rect")
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.attr({
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x: function(d) { return rectOffset+xScale(d.cat); },
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y: function(d) { return dataScale(d.val); },
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width: xScale.rangeBand(),
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height: function(d) { return yExtent[1] - dataScale(d.val); },
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fill: color_at(i),
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});
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rectOffset += xScale.rangeBand();
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}
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var xAxis = d3.svg.axis()
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.scale(xScale)
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.orient("bottom");
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svg.append("g")
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.attr("class", "x axis")
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.attr("transform", "translate("+xOffset+"," + (svgHeight-45) + ")")
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.call(xAxis)
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.selectAll(".tick text")
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.call(wordWrap, xScale.rangeBand());
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var yAxis = d3.svg.axis()
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.scale(dataScale)
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.orient("left");
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svg.append("g")
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.attr("class", "y axis")
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.attr("transform", "translate("+xOffset+",0)")
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.call(yAxis);
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}
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function wordWrap(text, width) {
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text.each(function() {
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var text = d3.select(this),
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words = text.text().split(/\s+/).reverse(),
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word,
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line = [],
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lineNumber = 0,
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lineHeight = 1.1, // ems
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y = text.attr("y"),
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dy = parseFloat(text.attr("dy")),
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tspan = text.text(null).append("tspan").attr("x", 0).attr("y", y).attr("dy", dy + "em");
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while (word = words.pop()) {
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line.push(word);
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tspan.text(line.join(" "));
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if (tspan.node().getComputedTextLength() > width) {
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line.pop();
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tspan.text(line.join(" "));
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line = [word];
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tspan = text.append("tspan").attr("x", 0).attr("y", y).attr("dy", ++lineNumber * lineHeight + dy + "em").text(word);
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}
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}
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});
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}
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var data = JSON.parse($("#json-data").html());
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function make_tuple(size) {
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var tuple = [];
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for (var i = 0; i < size; i++) {
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tuple.push(null);
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}
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return tuple;
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}
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var allTests = {};
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var count = 0;
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// loop over snapshots
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_.each(data, function(dict, name) {
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// loop tests
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_.each(dict.tests, function(test) {
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var modName = test["module"];
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var testName = test["test"];
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//var fullName = modName + "." + testName;
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var fullName = testName;
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if (!allTests[fullName]) {
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allTests[fullName] = make_tuple(count);
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}
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var testCase = {
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elapsed: test["elapsed"],
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n: test["iter"],
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};
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allTests[fullName].push(testCase);
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});
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count++;
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// fill missing snapshots
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_.each(allTests, function(snapshots) {
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while (snapshots.length < count) {
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snapshots.push(null);
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}
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});
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});
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function redrawCharts(scale) {
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$("h1").remove();
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$("h2").remove();
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$("svg").remove();
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//add_chart(name, tests, scale);
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add_comparison_chart("Snapshotting", allTests, scale);
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}
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$("#scale-selector").click(function() {
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var scale = $(this).val();
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redrawCharts(scale);
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});
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$(function() {
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redrawCharts("linear");
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});
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</script>
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</body>
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</html>

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