<!DOCTYPE html><html lang="en"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1.0"><meta name="generator" content="rustdoc"><meta name="description" content="Source to the Rust file `libtest/stats.rs`."><meta name="keywords" content="rust, rustlang, rust-lang"><title>stats.rs.html -- source</title><link rel="stylesheet" type="text/css" href="../../normalize.css"><link rel="stylesheet" type="text/css" href="../../rustdoc.css" id="mainThemeStyle"><link rel="stylesheet" type="text/css" href="../../dark.css"><link rel="stylesheet" type="text/css" href="../../light.css" id="themeStyle"><script src="../../storage.js"></script><link rel="shortcut icon" href="https://doc.rust-lang.org/favicon.ico"></head><body class="rustdoc source"><!--[if lte IE 8]><div class="warning">This old browser is unsupported and will most likely display funky things.</div><![endif]--><nav class="sidebar"><div class="sidebar-menu">☰</div><a href='../../test/index.html'><img src='https://www.rust-lang.org/logos/rust-logo-128x128-blk-v2.png' alt='logo' width='100'></a></nav><div class="theme-picker"><button id="theme-picker" aria-label="Pick another theme!"><img src="../../brush.svg" width="18" alt="Pick another theme!"></button><div id="theme-choices"></div></div><script src="../../theme.js"></script><nav class="sub"><form class="search-form js-only"><div class="search-container"><input class="search-input" name="search" autocomplete="off" placeholder="Click or press ‘S’ to search, ‘?’ for more options…" type="search"><a id="settings-menu" href="../../settings.html"><img src="../../wheel.svg" width="18" alt="Change settings"></a></div></form></nav><section id="main" class="content"><pre class="line-numbers"><span id="1"> 1</span>
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</pre><pre class="rust ">
<span class="comment">// Copyright 2012 The Rust Project Developers. See the COPYRIGHT</span>
<span class="comment">// file at the top-level directory of this distribution and at</span>
<span class="comment">// http://rust-lang.org/COPYRIGHT.</span>
<span class="comment">//</span>
<span class="comment">// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or</span>
<span class="comment">// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license</span>
<span class="comment">// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your</span>
<span class="comment">// option. This file may not be copied, modified, or distributed</span>
<span class="comment">// except according to those terms.</span>
<span class="attribute">#![<span class="ident">allow</span>(<span class="ident">missing_docs</span>)]</span>
<span class="attribute">#![<span class="ident">allow</span>(<span class="ident">deprecated</span>)]</span> <span class="comment">// Float</span>
<span class="kw">use</span> <span class="ident">std</span>::<span class="ident">cmp</span>::<span class="ident">Ordering</span>::{<span class="self">self</span>, <span class="ident">Equal</span>, <span class="ident">Greater</span>, <span class="ident">Less</span>};
<span class="kw">use</span> <span class="ident">std</span>::<span class="ident">mem</span>;
<span class="kw">fn</span> <span class="ident">local_cmp</span>(<span class="ident">x</span>: <span class="ident">f64</span>, <span class="ident">y</span>: <span class="ident">f64</span>) <span class="op">-></span> <span class="ident">Ordering</span> {
<span class="comment">// arbitrarily decide that NaNs are larger than everything.</span>
<span class="kw">if</span> <span class="ident">y</span>.<span class="ident">is_nan</span>() {
<span class="ident">Less</span>
} <span class="kw">else</span> <span class="kw">if</span> <span class="ident">x</span>.<span class="ident">is_nan</span>() {
<span class="ident">Greater</span>
} <span class="kw">else</span> <span class="kw">if</span> <span class="ident">x</span> <span class="op"><</span> <span class="ident">y</span> {
<span class="ident">Less</span>
} <span class="kw">else</span> <span class="kw">if</span> <span class="ident">x</span> <span class="op">==</span> <span class="ident">y</span> {
<span class="ident">Equal</span>
} <span class="kw">else</span> {
<span class="ident">Greater</span>
}
}
<span class="kw">fn</span> <span class="ident">local_sort</span>(<span class="ident">v</span>: <span class="kw-2">&</span><span class="kw-2">mut</span> [<span class="ident">f64</span>]) {
<span class="ident">v</span>.<span class="ident">sort_by</span>(<span class="op">|</span><span class="ident">x</span>: <span class="kw-2">&</span><span class="ident">f64</span>, <span class="ident">y</span>: <span class="kw-2">&</span><span class="ident">f64</span><span class="op">|</span> <span class="ident">local_cmp</span>(<span class="kw-2">*</span><span class="ident">x</span>, <span class="kw-2">*</span><span class="ident">y</span>));
}
<span class="doccomment">/// Trait that provides simple descriptive statistics on a univariate set of numeric samples.</span>
<span class="kw">pub</span> <span class="kw">trait</span> <span class="ident">Stats</span> {
<span class="doccomment">/// Sum of the samples.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// Note: this method sacrifices performance at the altar of accuracy</span>
<span class="doccomment">/// Depends on IEEE-754 arithmetic guarantees. See proof of correctness at:</span>
<span class="doccomment">/// ["Adaptive Precision Floating-Point Arithmetic and Fast Robust Geometric</span>
<span class="doccomment">/// Predicates"][paper]</span>
<span class="doccomment">///</span>
<span class="doccomment">/// [paper]: http://www.cs.cmu.edu/~quake-papers/robust-arithmetic.ps</span>
<span class="kw">fn</span> <span class="ident">sum</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span>;
<span class="doccomment">/// Minimum value of the samples.</span>
<span class="kw">fn</span> <span class="ident">min</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span>;
<span class="doccomment">/// Maximum value of the samples.</span>
<span class="kw">fn</span> <span class="ident">max</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span>;
<span class="doccomment">/// Arithmetic mean (average) of the samples: sum divided by sample-count.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// See: <https://en.wikipedia.org/wiki/Arithmetic_mean></span>
<span class="kw">fn</span> <span class="ident">mean</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span>;
<span class="doccomment">/// Median of the samples: value separating the lower half of the samples from the higher half.</span>
<span class="doccomment">/// Equal to `self.percentile(50.0)`.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// See: <https://en.wikipedia.org/wiki/Median></span>
<span class="kw">fn</span> <span class="ident">median</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span>;
<span class="doccomment">/// Variance of the samples: bias-corrected mean of the squares of the differences of each</span>
<span class="doccomment">/// sample from the sample mean. Note that this calculates the _sample variance_ rather than the</span>
<span class="doccomment">/// population variance, which is assumed to be unknown. It therefore corrects the `(n-1)/n`</span>
<span class="doccomment">/// bias that would appear if we calculated a population variance, by dividing by `(n-1)` rather</span>
<span class="doccomment">/// than `n`.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// See: <https://en.wikipedia.org/wiki/Variance></span>
<span class="kw">fn</span> <span class="ident">var</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span>;
<span class="doccomment">/// Standard deviation: the square root of the sample variance.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// Note: this is not a robust statistic for non-normal distributions. Prefer the</span>
<span class="doccomment">/// `median_abs_dev` for unknown distributions.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// See: <https://en.wikipedia.org/wiki/Standard_deviation></span>
<span class="kw">fn</span> <span class="ident">std_dev</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span>;
<span class="doccomment">/// Standard deviation as a percent of the mean value. See `std_dev` and `mean`.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// Note: this is not a robust statistic for non-normal distributions. Prefer the</span>
<span class="doccomment">/// `median_abs_dev_pct` for unknown distributions.</span>
<span class="kw">fn</span> <span class="ident">std_dev_pct</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span>;
<span class="doccomment">/// Scaled median of the absolute deviations of each sample from the sample median. This is a</span>
<span class="doccomment">/// robust (distribution-agnostic) estimator of sample variability. Use this in preference to</span>
<span class="doccomment">/// `std_dev` if you cannot assume your sample is normally distributed. Note that this is scaled</span>
<span class="doccomment">/// by the constant `1.4826` to allow its use as a consistent estimator for the standard</span>
<span class="doccomment">/// deviation.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// See: <http://en.wikipedia.org/wiki/Median_absolute_deviation></span>
<span class="kw">fn</span> <span class="ident">median_abs_dev</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span>;
<span class="doccomment">/// Median absolute deviation as a percent of the median. See `median_abs_dev` and `median`.</span>
<span class="kw">fn</span> <span class="ident">median_abs_dev_pct</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span>;
<span class="doccomment">/// Percentile: the value below which `pct` percent of the values in `self` fall. For example,</span>
<span class="doccomment">/// percentile(95.0) will return the value `v` such that 95% of the samples `s` in `self`</span>
<span class="doccomment">/// satisfy `s <= v`.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// Calculated by linear interpolation between closest ranks.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// See: <http://en.wikipedia.org/wiki/Percentile></span>
<span class="kw">fn</span> <span class="ident">percentile</span>(<span class="kw-2">&</span><span class="self">self</span>, <span class="ident">pct</span>: <span class="ident">f64</span>) <span class="op">-></span> <span class="ident">f64</span>;
<span class="doccomment">/// Quartiles of the sample: three values that divide the sample into four equal groups, each</span>
<span class="doccomment">/// with 1/4 of the data. The middle value is the median. See `median` and `percentile`. This</span>
<span class="doccomment">/// function may calculate the 3 quartiles more efficiently than 3 calls to `percentile`, but</span>
<span class="doccomment">/// is otherwise equivalent.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// See also: <https://en.wikipedia.org/wiki/Quartile></span>
<span class="kw">fn</span> <span class="ident">quartiles</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> (<span class="ident">f64</span>, <span class="ident">f64</span>, <span class="ident">f64</span>);
<span class="doccomment">/// Inter-quartile range: the difference between the 25th percentile (1st quartile) and the 75th</span>
<span class="doccomment">/// percentile (3rd quartile). See `quartiles`.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// See also: <https://en.wikipedia.org/wiki/Interquartile_range></span>
<span class="kw">fn</span> <span class="ident">iqr</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span>;
}
<span class="doccomment">/// Extracted collection of all the summary statistics of a sample set.</span>
<span class="attribute">#[<span class="ident">derive</span>(<span class="ident">Clone</span>, <span class="ident">PartialEq</span>, <span class="ident">Copy</span>)]</span>
<span class="attribute">#[<span class="ident">allow</span>(<span class="ident">missing_docs</span>)]</span>
<span class="kw">pub</span> <span class="kw">struct</span> <span class="ident">Summary</span> {
<span class="kw">pub</span> <span class="ident">sum</span>: <span class="ident">f64</span>,
<span class="kw">pub</span> <span class="ident">min</span>: <span class="ident">f64</span>,
<span class="kw">pub</span> <span class="ident">max</span>: <span class="ident">f64</span>,
<span class="kw">pub</span> <span class="ident">mean</span>: <span class="ident">f64</span>,
<span class="kw">pub</span> <span class="ident">median</span>: <span class="ident">f64</span>,
<span class="kw">pub</span> <span class="ident">var</span>: <span class="ident">f64</span>,
<span class="kw">pub</span> <span class="ident">std_dev</span>: <span class="ident">f64</span>,
<span class="kw">pub</span> <span class="ident">std_dev_pct</span>: <span class="ident">f64</span>,
<span class="kw">pub</span> <span class="ident">median_abs_dev</span>: <span class="ident">f64</span>,
<span class="kw">pub</span> <span class="ident">median_abs_dev_pct</span>: <span class="ident">f64</span>,
<span class="kw">pub</span> <span class="ident">quartiles</span>: (<span class="ident">f64</span>, <span class="ident">f64</span>, <span class="ident">f64</span>),
<span class="kw">pub</span> <span class="ident">iqr</span>: <span class="ident">f64</span>,
}
<span class="kw">impl</span> <span class="ident">Summary</span> {
<span class="doccomment">/// Construct a new summary of a sample set.</span>
<span class="kw">pub</span> <span class="kw">fn</span> <span class="ident">new</span>(<span class="ident">samples</span>: <span class="kw-2">&</span>[<span class="ident">f64</span>]) <span class="op">-></span> <span class="ident">Summary</span> {
<span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="ident">samples</span>.<span class="ident">sum</span>(),
<span class="ident">min</span>: <span class="ident">samples</span>.<span class="ident">min</span>(),
<span class="ident">max</span>: <span class="ident">samples</span>.<span class="ident">max</span>(),
<span class="ident">mean</span>: <span class="ident">samples</span>.<span class="ident">mean</span>(),
<span class="ident">median</span>: <span class="ident">samples</span>.<span class="ident">median</span>(),
<span class="ident">var</span>: <span class="ident">samples</span>.<span class="ident">var</span>(),
<span class="ident">std_dev</span>: <span class="ident">samples</span>.<span class="ident">std_dev</span>(),
<span class="ident">std_dev_pct</span>: <span class="ident">samples</span>.<span class="ident">std_dev_pct</span>(),
<span class="ident">median_abs_dev</span>: <span class="ident">samples</span>.<span class="ident">median_abs_dev</span>(),
<span class="ident">median_abs_dev_pct</span>: <span class="ident">samples</span>.<span class="ident">median_abs_dev_pct</span>(),
<span class="ident">quartiles</span>: <span class="ident">samples</span>.<span class="ident">quartiles</span>(),
<span class="ident">iqr</span>: <span class="ident">samples</span>.<span class="ident">iqr</span>(),
}
}
}
<span class="kw">impl</span> <span class="ident">Stats</span> <span class="kw">for</span> [<span class="ident">f64</span>] {
<span class="comment">// FIXME #11059 handle NaN, inf and overflow</span>
<span class="kw">fn</span> <span class="ident">sum</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="kw">let</span> <span class="kw-2">mut</span> <span class="ident">partials</span> <span class="op">=</span> <span class="macro">vec</span><span class="macro">!</span>[];
<span class="kw">for</span> <span class="kw-2">&</span><span class="ident">x</span> <span class="kw">in</span> <span class="self">self</span> {
<span class="kw">let</span> <span class="kw-2">mut</span> <span class="ident">x</span> <span class="op">=</span> <span class="ident">x</span>;
<span class="kw">let</span> <span class="kw-2">mut</span> <span class="ident">j</span> <span class="op">=</span> <span class="number">0</span>;
<span class="comment">// This inner loop applies `hi`/`lo` summation to each</span>
<span class="comment">// partial so that the list of partial sums remains exact.</span>
<span class="kw">for</span> <span class="ident">i</span> <span class="kw">in</span> <span class="number">0</span>..<span class="ident">partials</span>.<span class="ident">len</span>() {
<span class="kw">let</span> <span class="kw-2">mut</span> <span class="ident">y</span>: <span class="ident">f64</span> <span class="op">=</span> <span class="ident">partials</span>[<span class="ident">i</span>];
<span class="kw">if</span> <span class="ident">x</span>.<span class="ident">abs</span>() <span class="op"><</span> <span class="ident">y</span>.<span class="ident">abs</span>() {
<span class="ident">mem</span>::<span class="ident">swap</span>(<span class="kw-2">&</span><span class="kw-2">mut</span> <span class="ident">x</span>, <span class="kw-2">&</span><span class="kw-2">mut</span> <span class="ident">y</span>);
}
<span class="comment">// Rounded `x+y` is stored in `hi` with round-off stored in</span>
<span class="comment">// `lo`. Together `hi+lo` are exactly equal to `x+y`.</span>
<span class="kw">let</span> <span class="ident">hi</span> <span class="op">=</span> <span class="ident">x</span> <span class="op">+</span> <span class="ident">y</span>;
<span class="kw">let</span> <span class="ident">lo</span> <span class="op">=</span> <span class="ident">y</span> <span class="op">-</span> (<span class="ident">hi</span> <span class="op">-</span> <span class="ident">x</span>);
<span class="kw">if</span> <span class="ident">lo</span> <span class="op">!=</span> <span class="number">0.0</span> {
<span class="ident">partials</span>[<span class="ident">j</span>] <span class="op">=</span> <span class="ident">lo</span>;
<span class="ident">j</span> <span class="op">+=</span> <span class="number">1</span>;
}
<span class="ident">x</span> <span class="op">=</span> <span class="ident">hi</span>;
}
<span class="kw">if</span> <span class="ident">j</span> <span class="op">>=</span> <span class="ident">partials</span>.<span class="ident">len</span>() {
<span class="ident">partials</span>.<span class="ident">push</span>(<span class="ident">x</span>);
} <span class="kw">else</span> {
<span class="ident">partials</span>[<span class="ident">j</span>] <span class="op">=</span> <span class="ident">x</span>;
<span class="ident">partials</span>.<span class="ident">truncate</span>(<span class="ident">j</span> <span class="op">+</span> <span class="number">1</span>);
}
}
<span class="kw">let</span> <span class="ident">zero</span>: <span class="ident">f64</span> <span class="op">=</span> <span class="number">0.0</span>;
<span class="ident">partials</span>.<span class="ident">iter</span>().<span class="ident">fold</span>(<span class="ident">zero</span>, <span class="op">|</span><span class="ident">p</span>, <span class="ident">q</span><span class="op">|</span> <span class="ident">p</span> <span class="op">+</span> <span class="kw-2">*</span><span class="ident">q</span>)
}
<span class="kw">fn</span> <span class="ident">min</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="macro">assert</span><span class="macro">!</span>(<span class="op">!</span><span class="self">self</span>.<span class="ident">is_empty</span>());
<span class="self">self</span>.<span class="ident">iter</span>().<span class="ident">fold</span>(<span class="self">self</span>[<span class="number">0</span>], <span class="op">|</span><span class="ident">p</span>, <span class="ident">q</span><span class="op">|</span> <span class="ident">p</span>.<span class="ident">min</span>(<span class="kw-2">*</span><span class="ident">q</span>))
}
<span class="kw">fn</span> <span class="ident">max</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="macro">assert</span><span class="macro">!</span>(<span class="op">!</span><span class="self">self</span>.<span class="ident">is_empty</span>());
<span class="self">self</span>.<span class="ident">iter</span>().<span class="ident">fold</span>(<span class="self">self</span>[<span class="number">0</span>], <span class="op">|</span><span class="ident">p</span>, <span class="ident">q</span><span class="op">|</span> <span class="ident">p</span>.<span class="ident">max</span>(<span class="kw-2">*</span><span class="ident">q</span>))
}
<span class="kw">fn</span> <span class="ident">mean</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="macro">assert</span><span class="macro">!</span>(<span class="op">!</span><span class="self">self</span>.<span class="ident">is_empty</span>());
<span class="self">self</span>.<span class="ident">sum</span>() <span class="op">/</span> (<span class="self">self</span>.<span class="ident">len</span>() <span class="kw">as</span> <span class="ident">f64</span>)
}
<span class="kw">fn</span> <span class="ident">median</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="self">self</span>.<span class="ident">percentile</span>(<span class="number">50</span> <span class="kw">as</span> <span class="ident">f64</span>)
}
<span class="kw">fn</span> <span class="ident">var</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="kw">if</span> <span class="self">self</span>.<span class="ident">len</span>() <span class="op"><</span> <span class="number">2</span> {
<span class="number">0.0</span>
} <span class="kw">else</span> {
<span class="kw">let</span> <span class="ident">mean</span> <span class="op">=</span> <span class="self">self</span>.<span class="ident">mean</span>();
<span class="kw">let</span> <span class="kw-2">mut</span> <span class="ident">v</span>: <span class="ident">f64</span> <span class="op">=</span> <span class="number">0.0</span>;
<span class="kw">for</span> <span class="ident">s</span> <span class="kw">in</span> <span class="self">self</span> {
<span class="kw">let</span> <span class="ident">x</span> <span class="op">=</span> <span class="kw-2">*</span><span class="ident">s</span> <span class="op">-</span> <span class="ident">mean</span>;
<span class="ident">v</span> <span class="op">=</span> <span class="ident">v</span> <span class="op">+</span> <span class="ident">x</span> <span class="op">*</span> <span class="ident">x</span>;
}
<span class="comment">// NB: this is _supposed to be_ len-1, not len. If you</span>
<span class="comment">// change it back to len, you will be calculating a</span>
<span class="comment">// population variance, not a sample variance.</span>
<span class="kw">let</span> <span class="ident">denom</span> <span class="op">=</span> (<span class="self">self</span>.<span class="ident">len</span>() <span class="op">-</span> <span class="number">1</span>) <span class="kw">as</span> <span class="ident">f64</span>;
<span class="ident">v</span> <span class="op">/</span> <span class="ident">denom</span>
}
}
<span class="kw">fn</span> <span class="ident">std_dev</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="self">self</span>.<span class="ident">var</span>().<span class="ident">sqrt</span>()
}
<span class="kw">fn</span> <span class="ident">std_dev_pct</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="kw">let</span> <span class="ident">hundred</span> <span class="op">=</span> <span class="number">100</span> <span class="kw">as</span> <span class="ident">f64</span>;
(<span class="self">self</span>.<span class="ident">std_dev</span>() <span class="op">/</span> <span class="self">self</span>.<span class="ident">mean</span>()) <span class="op">*</span> <span class="ident">hundred</span>
}
<span class="kw">fn</span> <span class="ident">median_abs_dev</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="kw">let</span> <span class="ident">med</span> <span class="op">=</span> <span class="self">self</span>.<span class="ident">median</span>();
<span class="kw">let</span> <span class="ident">abs_devs</span>: <span class="ident">Vec</span><span class="op"><</span><span class="ident">f64</span><span class="op">></span> <span class="op">=</span> <span class="self">self</span>.<span class="ident">iter</span>().<span class="ident">map</span>(<span class="op">|</span><span class="kw-2">&</span><span class="ident">v</span><span class="op">|</span> (<span class="ident">med</span> <span class="op">-</span> <span class="ident">v</span>).<span class="ident">abs</span>()).<span class="ident">collect</span>();
<span class="comment">// This constant is derived by smarter statistics brains than me, but it is</span>
<span class="comment">// consistent with how R and other packages treat the MAD.</span>
<span class="kw">let</span> <span class="ident">number</span> <span class="op">=</span> <span class="number">1.4826</span>;
<span class="ident">abs_devs</span>.<span class="ident">median</span>() <span class="op">*</span> <span class="ident">number</span>
}
<span class="kw">fn</span> <span class="ident">median_abs_dev_pct</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="kw">let</span> <span class="ident">hundred</span> <span class="op">=</span> <span class="number">100</span> <span class="kw">as</span> <span class="ident">f64</span>;
(<span class="self">self</span>.<span class="ident">median_abs_dev</span>() <span class="op">/</span> <span class="self">self</span>.<span class="ident">median</span>()) <span class="op">*</span> <span class="ident">hundred</span>
}
<span class="kw">fn</span> <span class="ident">percentile</span>(<span class="kw-2">&</span><span class="self">self</span>, <span class="ident">pct</span>: <span class="ident">f64</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="kw">let</span> <span class="kw-2">mut</span> <span class="ident">tmp</span> <span class="op">=</span> <span class="self">self</span>.<span class="ident">to_vec</span>();
<span class="ident">local_sort</span>(<span class="kw-2">&</span><span class="kw-2">mut</span> <span class="ident">tmp</span>);
<span class="ident">percentile_of_sorted</span>(<span class="kw-2">&</span><span class="ident">tmp</span>, <span class="ident">pct</span>)
}
<span class="kw">fn</span> <span class="ident">quartiles</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> (<span class="ident">f64</span>, <span class="ident">f64</span>, <span class="ident">f64</span>) {
<span class="kw">let</span> <span class="kw-2">mut</span> <span class="ident">tmp</span> <span class="op">=</span> <span class="self">self</span>.<span class="ident">to_vec</span>();
<span class="ident">local_sort</span>(<span class="kw-2">&</span><span class="kw-2">mut</span> <span class="ident">tmp</span>);
<span class="kw">let</span> <span class="ident">first</span> <span class="op">=</span> <span class="number">25f64</span>;
<span class="kw">let</span> <span class="ident">a</span> <span class="op">=</span> <span class="ident">percentile_of_sorted</span>(<span class="kw-2">&</span><span class="ident">tmp</span>, <span class="ident">first</span>);
<span class="kw">let</span> <span class="ident">second</span> <span class="op">=</span> <span class="number">50f64</span>;
<span class="kw">let</span> <span class="ident">b</span> <span class="op">=</span> <span class="ident">percentile_of_sorted</span>(<span class="kw-2">&</span><span class="ident">tmp</span>, <span class="ident">second</span>);
<span class="kw">let</span> <span class="ident">third</span> <span class="op">=</span> <span class="number">75f64</span>;
<span class="kw">let</span> <span class="ident">c</span> <span class="op">=</span> <span class="ident">percentile_of_sorted</span>(<span class="kw-2">&</span><span class="ident">tmp</span>, <span class="ident">third</span>);
(<span class="ident">a</span>, <span class="ident">b</span>, <span class="ident">c</span>)
}
<span class="kw">fn</span> <span class="ident">iqr</span>(<span class="kw-2">&</span><span class="self">self</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="kw">let</span> (<span class="ident">a</span>, <span class="kw">_</span>, <span class="ident">c</span>) <span class="op">=</span> <span class="self">self</span>.<span class="ident">quartiles</span>();
<span class="ident">c</span> <span class="op">-</span> <span class="ident">a</span>
}
}
<span class="comment">// Helper function: extract a value representing the `pct` percentile of a sorted sample-set, using</span>
<span class="comment">// linear interpolation. If samples are not sorted, return nonsensical value.</span>
<span class="kw">fn</span> <span class="ident">percentile_of_sorted</span>(<span class="ident">sorted_samples</span>: <span class="kw-2">&</span>[<span class="ident">f64</span>], <span class="ident">pct</span>: <span class="ident">f64</span>) <span class="op">-></span> <span class="ident">f64</span> {
<span class="macro">assert</span><span class="macro">!</span>(<span class="op">!</span><span class="ident">sorted_samples</span>.<span class="ident">is_empty</span>());
<span class="kw">if</span> <span class="ident">sorted_samples</span>.<span class="ident">len</span>() <span class="op">==</span> <span class="number">1</span> {
<span class="kw">return</span> <span class="ident">sorted_samples</span>[<span class="number">0</span>];
}
<span class="kw">let</span> <span class="ident">zero</span>: <span class="ident">f64</span> <span class="op">=</span> <span class="number">0.0</span>;
<span class="macro">assert</span><span class="macro">!</span>(<span class="ident">zero</span> <span class="op"><=</span> <span class="ident">pct</span>);
<span class="kw">let</span> <span class="ident">hundred</span> <span class="op">=</span> <span class="number">100f64</span>;
<span class="macro">assert</span><span class="macro">!</span>(<span class="ident">pct</span> <span class="op"><=</span> <span class="ident">hundred</span>);
<span class="kw">if</span> <span class="ident">pct</span> <span class="op">==</span> <span class="ident">hundred</span> {
<span class="kw">return</span> <span class="ident">sorted_samples</span>[<span class="ident">sorted_samples</span>.<span class="ident">len</span>() <span class="op">-</span> <span class="number">1</span>];
}
<span class="kw">let</span> <span class="ident">length</span> <span class="op">=</span> (<span class="ident">sorted_samples</span>.<span class="ident">len</span>() <span class="op">-</span> <span class="number">1</span>) <span class="kw">as</span> <span class="ident">f64</span>;
<span class="kw">let</span> <span class="ident">rank</span> <span class="op">=</span> (<span class="ident">pct</span> <span class="op">/</span> <span class="ident">hundred</span>) <span class="op">*</span> <span class="ident">length</span>;
<span class="kw">let</span> <span class="ident">lrank</span> <span class="op">=</span> <span class="ident">rank</span>.<span class="ident">floor</span>();
<span class="kw">let</span> <span class="ident">d</span> <span class="op">=</span> <span class="ident">rank</span> <span class="op">-</span> <span class="ident">lrank</span>;
<span class="kw">let</span> <span class="ident">n</span> <span class="op">=</span> <span class="ident">lrank</span> <span class="kw">as</span> <span class="ident">usize</span>;
<span class="kw">let</span> <span class="ident">lo</span> <span class="op">=</span> <span class="ident">sorted_samples</span>[<span class="ident">n</span>];
<span class="kw">let</span> <span class="ident">hi</span> <span class="op">=</span> <span class="ident">sorted_samples</span>[<span class="ident">n</span> <span class="op">+</span> <span class="number">1</span>];
<span class="ident">lo</span> <span class="op">+</span> (<span class="ident">hi</span> <span class="op">-</span> <span class="ident">lo</span>) <span class="op">*</span> <span class="ident">d</span>
}
<span class="doccomment">/// Winsorize a set of samples, replacing values above the `100-pct` percentile</span>
<span class="doccomment">/// and below the `pct` percentile with those percentiles themselves. This is a</span>
<span class="doccomment">/// way of minimizing the effect of outliers, at the cost of biasing the sample.</span>
<span class="doccomment">/// It differs from trimming in that it does not change the number of samples,</span>
<span class="doccomment">/// just changes the values of those that are outliers.</span>
<span class="doccomment">///</span>
<span class="doccomment">/// See: <http://en.wikipedia.org/wiki/Winsorising></span>
<span class="kw">pub</span> <span class="kw">fn</span> <span class="ident">winsorize</span>(<span class="ident">samples</span>: <span class="kw-2">&</span><span class="kw-2">mut</span> [<span class="ident">f64</span>], <span class="ident">pct</span>: <span class="ident">f64</span>) {
<span class="kw">let</span> <span class="kw-2">mut</span> <span class="ident">tmp</span> <span class="op">=</span> <span class="ident">samples</span>.<span class="ident">to_vec</span>();
<span class="ident">local_sort</span>(<span class="kw-2">&</span><span class="kw-2">mut</span> <span class="ident">tmp</span>);
<span class="kw">let</span> <span class="ident">lo</span> <span class="op">=</span> <span class="ident">percentile_of_sorted</span>(<span class="kw-2">&</span><span class="ident">tmp</span>, <span class="ident">pct</span>);
<span class="kw">let</span> <span class="ident">hundred</span> <span class="op">=</span> <span class="number">100</span> <span class="kw">as</span> <span class="ident">f64</span>;
<span class="kw">let</span> <span class="ident">hi</span> <span class="op">=</span> <span class="ident">percentile_of_sorted</span>(<span class="kw-2">&</span><span class="ident">tmp</span>, <span class="ident">hundred</span> <span class="op">-</span> <span class="ident">pct</span>);
<span class="kw">for</span> <span class="ident">samp</span> <span class="kw">in</span> <span class="ident">samples</span> {
<span class="kw">if</span> <span class="kw-2">*</span><span class="ident">samp</span> <span class="op">></span> <span class="ident">hi</span> {
<span class="kw-2">*</span><span class="ident">samp</span> <span class="op">=</span> <span class="ident">hi</span>
} <span class="kw">else</span> <span class="kw">if</span> <span class="kw-2">*</span><span class="ident">samp</span> <span class="op"><</span> <span class="ident">lo</span> {
<span class="kw-2">*</span><span class="ident">samp</span> <span class="op">=</span> <span class="ident">lo</span>
}
}
}
<span class="comment">// Test vectors generated from R, using the script src/etc/stat-test-vectors.r.</span>
<span class="attribute">#[<span class="ident">cfg</span>(<span class="ident">test</span>)]</span>
<span class="kw">mod</span> <span class="ident">tests</span> {
<span class="kw">use</span> <span class="ident">stats</span>::<span class="ident">Stats</span>;
<span class="kw">use</span> <span class="ident">stats</span>::<span class="ident">Summary</span>;
<span class="kw">use</span> <span class="ident">std</span>::<span class="ident">f64</span>;
<span class="kw">use</span> <span class="ident">std</span>::<span class="ident">io</span>::<span class="ident">prelude</span>::<span class="kw-2">*</span>;
<span class="kw">use</span> <span class="ident">std</span>::<span class="ident">io</span>;
<span class="macro">macro_rules</span><span class="macro">!</span> <span class="ident">assert_approx_eq</span> {
(<span class="macro-nonterminal">$</span><span class="macro-nonterminal">a</span>: <span class="ident">expr</span>, <span class="macro-nonterminal">$</span><span class="macro-nonterminal">b</span>: <span class="ident">expr</span>) <span class="op">=></span> {{
<span class="kw">let</span> (<span class="ident">a</span>, <span class="ident">b</span>) <span class="op">=</span> (<span class="kw-2">&</span><span class="macro-nonterminal">$</span><span class="macro-nonterminal">a</span>, <span class="kw-2">&</span><span class="macro-nonterminal">$</span><span class="macro-nonterminal">b</span>);
<span class="macro">assert</span><span class="macro">!</span>(
(<span class="kw-2">*</span><span class="ident">a</span> <span class="op">-</span> <span class="kw-2">*</span><span class="ident">b</span>).<span class="ident">abs</span>() <span class="op"><</span> <span class="number">1.0e-6</span>,
<span class="string">"{} is not approximately equal to {}"</span>,
<span class="kw-2">*</span><span class="ident">a</span>,
<span class="kw-2">*</span><span class="ident">b</span>
);
}};
}
<span class="kw">fn</span> <span class="ident">check</span>(<span class="ident">samples</span>: <span class="kw-2">&</span>[<span class="ident">f64</span>], <span class="ident">summ</span>: <span class="kw-2">&</span><span class="ident">Summary</span>) {
<span class="kw">let</span> <span class="ident">summ2</span> <span class="op">=</span> <span class="ident">Summary</span>::<span class="ident">new</span>(<span class="ident">samples</span>);
<span class="kw">let</span> <span class="kw-2">mut</span> <span class="ident">w</span> <span class="op">=</span> <span class="ident">io</span>::<span class="ident">sink</span>();
<span class="kw">let</span> <span class="ident">w</span> <span class="op">=</span> <span class="kw-2">&</span><span class="kw-2">mut</span> <span class="ident">w</span>;
(<span class="macro">write</span><span class="macro">!</span>(<span class="ident">w</span>, <span class="string">"\n"</span>)).<span class="ident">unwrap</span>();
<span class="macro">assert_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">sum</span>, <span class="ident">summ2</span>.<span class="ident">sum</span>);
<span class="macro">assert_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">min</span>, <span class="ident">summ2</span>.<span class="ident">min</span>);
<span class="macro">assert_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">max</span>, <span class="ident">summ2</span>.<span class="ident">max</span>);
<span class="macro">assert_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">mean</span>, <span class="ident">summ2</span>.<span class="ident">mean</span>);
<span class="macro">assert_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">median</span>, <span class="ident">summ2</span>.<span class="ident">median</span>);
<span class="comment">// We needed a few more digits to get exact equality on these</span>
<span class="comment">// but they're within float epsilon, which is 1.0e-6.</span>
<span class="macro">assert_approx_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">var</span>, <span class="ident">summ2</span>.<span class="ident">var</span>);
<span class="macro">assert_approx_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">std_dev</span>, <span class="ident">summ2</span>.<span class="ident">std_dev</span>);
<span class="macro">assert_approx_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">std_dev_pct</span>, <span class="ident">summ2</span>.<span class="ident">std_dev_pct</span>);
<span class="macro">assert_approx_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">median_abs_dev</span>, <span class="ident">summ2</span>.<span class="ident">median_abs_dev</span>);
<span class="macro">assert_approx_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">median_abs_dev_pct</span>, <span class="ident">summ2</span>.<span class="ident">median_abs_dev_pct</span>);
<span class="macro">assert_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">quartiles</span>, <span class="ident">summ2</span>.<span class="ident">quartiles</span>);
<span class="macro">assert_eq</span><span class="macro">!</span>(<span class="ident">summ</span>.<span class="ident">iqr</span>, <span class="ident">summ2</span>.<span class="ident">iqr</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_min_max_nan</span>() {
<span class="kw">let</span> <span class="ident">xs</span> <span class="op">=</span> <span class="kw-2">&</span>[<span class="number">1.0</span>, <span class="number">2.0</span>, <span class="ident">f64</span>::<span class="ident">NAN</span>, <span class="number">3.0</span>, <span class="number">4.0</span>];
<span class="kw">let</span> <span class="ident">summary</span> <span class="op">=</span> <span class="ident">Summary</span>::<span class="ident">new</span>(<span class="ident">xs</span>);
<span class="macro">assert_eq</span><span class="macro">!</span>(<span class="ident">summary</span>.<span class="ident">min</span>, <span class="number">1.0</span>);
<span class="macro">assert_eq</span><span class="macro">!</span>(<span class="ident">summary</span>.<span class="ident">max</span>, <span class="number">4.0</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_norm2</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[<span class="number">958.0000000000</span>, <span class="number">924.0000000000</span>];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">1882.0000000000</span>,
<span class="ident">min</span>: <span class="number">924.0000000000</span>,
<span class="ident">max</span>: <span class="number">958.0000000000</span>,
<span class="ident">mean</span>: <span class="number">941.0000000000</span>,
<span class="ident">median</span>: <span class="number">941.0000000000</span>,
<span class="ident">var</span>: <span class="number">578.0000000000</span>,
<span class="ident">std_dev</span>: <span class="number">24.0416305603</span>,
<span class="ident">std_dev_pct</span>: <span class="number">2.5549022912</span>,
<span class="ident">median_abs_dev</span>: <span class="number">25.2042000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">2.6784484591</span>,
<span class="ident">quartiles</span>: (<span class="number">932.5000000000</span>, <span class="number">941.0000000000</span>, <span class="number">949.5000000000</span>),
<span class="ident">iqr</span>: <span class="number">17.0000000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_norm10narrow</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">966.0000000000</span>,
<span class="number">985.0000000000</span>,
<span class="number">1110.0000000000</span>,
<span class="number">848.0000000000</span>,
<span class="number">821.0000000000</span>,
<span class="number">975.0000000000</span>,
<span class="number">962.0000000000</span>,
<span class="number">1157.0000000000</span>,
<span class="number">1217.0000000000</span>,
<span class="number">955.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">9996.0000000000</span>,
<span class="ident">min</span>: <span class="number">821.0000000000</span>,
<span class="ident">max</span>: <span class="number">1217.0000000000</span>,
<span class="ident">mean</span>: <span class="number">999.6000000000</span>,
<span class="ident">median</span>: <span class="number">970.5000000000</span>,
<span class="ident">var</span>: <span class="number">16050.7111111111</span>,
<span class="ident">std_dev</span>: <span class="number">126.6914010938</span>,
<span class="ident">std_dev_pct</span>: <span class="number">12.6742097933</span>,
<span class="ident">median_abs_dev</span>: <span class="number">102.2994000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">10.5408964451</span>,
<span class="ident">quartiles</span>: (<span class="number">956.7500000000</span>, <span class="number">970.5000000000</span>, <span class="number">1078.7500000000</span>),
<span class="ident">iqr</span>: <span class="number">122.0000000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_norm10medium</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">954.0000000000</span>,
<span class="number">1064.0000000000</span>,
<span class="number">855.0000000000</span>,
<span class="number">1000.0000000000</span>,
<span class="number">743.0000000000</span>,
<span class="number">1084.0000000000</span>,
<span class="number">704.0000000000</span>,
<span class="number">1023.0000000000</span>,
<span class="number">357.0000000000</span>,
<span class="number">869.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">8653.0000000000</span>,
<span class="ident">min</span>: <span class="number">357.0000000000</span>,
<span class="ident">max</span>: <span class="number">1084.0000000000</span>,
<span class="ident">mean</span>: <span class="number">865.3000000000</span>,
<span class="ident">median</span>: <span class="number">911.5000000000</span>,
<span class="ident">var</span>: <span class="number">48628.4555555556</span>,
<span class="ident">std_dev</span>: <span class="number">220.5186059170</span>,
<span class="ident">std_dev_pct</span>: <span class="number">25.4846418487</span>,
<span class="ident">median_abs_dev</span>: <span class="number">195.7032000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">21.4704552935</span>,
<span class="ident">quartiles</span>: (<span class="number">771.0000000000</span>, <span class="number">911.5000000000</span>, <span class="number">1017.2500000000</span>),
<span class="ident">iqr</span>: <span class="number">246.2500000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_norm10wide</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">505.0000000000</span>,
<span class="number">497.0000000000</span>,
<span class="number">1591.0000000000</span>,
<span class="number">887.0000000000</span>,
<span class="number">1026.0000000000</span>,
<span class="number">136.0000000000</span>,
<span class="number">1580.0000000000</span>,
<span class="number">940.0000000000</span>,
<span class="number">754.0000000000</span>,
<span class="number">1433.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">9349.0000000000</span>,
<span class="ident">min</span>: <span class="number">136.0000000000</span>,
<span class="ident">max</span>: <span class="number">1591.0000000000</span>,
<span class="ident">mean</span>: <span class="number">934.9000000000</span>,
<span class="ident">median</span>: <span class="number">913.5000000000</span>,
<span class="ident">var</span>: <span class="number">239208.9888888889</span>,
<span class="ident">std_dev</span>: <span class="number">489.0899599142</span>,
<span class="ident">std_dev_pct</span>: <span class="number">52.3146817750</span>,
<span class="ident">median_abs_dev</span>: <span class="number">611.5725000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">66.9482758621</span>,
<span class="ident">quartiles</span>: (<span class="number">567.2500000000</span>, <span class="number">913.5000000000</span>, <span class="number">1331.2500000000</span>),
<span class="ident">iqr</span>: <span class="number">764.0000000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_norm25verynarrow</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">991.0000000000</span>,
<span class="number">1018.0000000000</span>,
<span class="number">998.0000000000</span>,
<span class="number">1013.0000000000</span>,
<span class="number">974.0000000000</span>,
<span class="number">1007.0000000000</span>,
<span class="number">1014.0000000000</span>,
<span class="number">999.0000000000</span>,
<span class="number">1011.0000000000</span>,
<span class="number">978.0000000000</span>,
<span class="number">985.0000000000</span>,
<span class="number">999.0000000000</span>,
<span class="number">983.0000000000</span>,
<span class="number">982.0000000000</span>,
<span class="number">1015.0000000000</span>,
<span class="number">1002.0000000000</span>,
<span class="number">977.0000000000</span>,
<span class="number">948.0000000000</span>,
<span class="number">1040.0000000000</span>,
<span class="number">974.0000000000</span>,
<span class="number">996.0000000000</span>,
<span class="number">989.0000000000</span>,
<span class="number">1015.0000000000</span>,
<span class="number">994.0000000000</span>,
<span class="number">1024.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">24926.0000000000</span>,
<span class="ident">min</span>: <span class="number">948.0000000000</span>,
<span class="ident">max</span>: <span class="number">1040.0000000000</span>,
<span class="ident">mean</span>: <span class="number">997.0400000000</span>,
<span class="ident">median</span>: <span class="number">998.0000000000</span>,
<span class="ident">var</span>: <span class="number">393.2066666667</span>,
<span class="ident">std_dev</span>: <span class="number">19.8294393937</span>,
<span class="ident">std_dev_pct</span>: <span class="number">1.9888308788</span>,
<span class="ident">median_abs_dev</span>: <span class="number">22.2390000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">2.2283567134</span>,
<span class="ident">quartiles</span>: (<span class="number">983.0000000000</span>, <span class="number">998.0000000000</span>, <span class="number">1013.0000000000</span>),
<span class="ident">iqr</span>: <span class="number">30.0000000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_exp10a</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">23.0000000000</span>,
<span class="number">11.0000000000</span>,
<span class="number">2.0000000000</span>,
<span class="number">57.0000000000</span>,
<span class="number">4.0000000000</span>,
<span class="number">12.0000000000</span>,
<span class="number">5.0000000000</span>,
<span class="number">29.0000000000</span>,
<span class="number">3.0000000000</span>,
<span class="number">21.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">167.0000000000</span>,
<span class="ident">min</span>: <span class="number">2.0000000000</span>,
<span class="ident">max</span>: <span class="number">57.0000000000</span>,
<span class="ident">mean</span>: <span class="number">16.7000000000</span>,
<span class="ident">median</span>: <span class="number">11.5000000000</span>,
<span class="ident">var</span>: <span class="number">287.7888888889</span>,
<span class="ident">std_dev</span>: <span class="number">16.9643416875</span>,
<span class="ident">std_dev_pct</span>: <span class="number">101.5828843560</span>,
<span class="ident">median_abs_dev</span>: <span class="number">13.3434000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">116.0295652174</span>,
<span class="ident">quartiles</span>: (<span class="number">4.2500000000</span>, <span class="number">11.5000000000</span>, <span class="number">22.5000000000</span>),
<span class="ident">iqr</span>: <span class="number">18.2500000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_exp10b</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">24.0000000000</span>,
<span class="number">17.0000000000</span>,
<span class="number">6.0000000000</span>,
<span class="number">38.0000000000</span>,
<span class="number">25.0000000000</span>,
<span class="number">7.0000000000</span>,
<span class="number">51.0000000000</span>,
<span class="number">2.0000000000</span>,
<span class="number">61.0000000000</span>,
<span class="number">32.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">263.0000000000</span>,
<span class="ident">min</span>: <span class="number">2.0000000000</span>,
<span class="ident">max</span>: <span class="number">61.0000000000</span>,
<span class="ident">mean</span>: <span class="number">26.3000000000</span>,
<span class="ident">median</span>: <span class="number">24.5000000000</span>,
<span class="ident">var</span>: <span class="number">383.5666666667</span>,
<span class="ident">std_dev</span>: <span class="number">19.5848580967</span>,
<span class="ident">std_dev_pct</span>: <span class="number">74.4671410520</span>,
<span class="ident">median_abs_dev</span>: <span class="number">22.9803000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">93.7971428571</span>,
<span class="ident">quartiles</span>: (<span class="number">9.5000000000</span>, <span class="number">24.5000000000</span>, <span class="number">36.5000000000</span>),
<span class="ident">iqr</span>: <span class="number">27.0000000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_exp10c</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">71.0000000000</span>,
<span class="number">2.0000000000</span>,
<span class="number">32.0000000000</span>,
<span class="number">1.0000000000</span>,
<span class="number">6.0000000000</span>,
<span class="number">28.0000000000</span>,
<span class="number">13.0000000000</span>,
<span class="number">37.0000000000</span>,
<span class="number">16.0000000000</span>,
<span class="number">36.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">242.0000000000</span>,
<span class="ident">min</span>: <span class="number">1.0000000000</span>,
<span class="ident">max</span>: <span class="number">71.0000000000</span>,
<span class="ident">mean</span>: <span class="number">24.2000000000</span>,
<span class="ident">median</span>: <span class="number">22.0000000000</span>,
<span class="ident">var</span>: <span class="number">458.1777777778</span>,
<span class="ident">std_dev</span>: <span class="number">21.4050876611</span>,
<span class="ident">std_dev_pct</span>: <span class="number">88.4507754589</span>,
<span class="ident">median_abs_dev</span>: <span class="number">21.4977000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">97.7168181818</span>,
<span class="ident">quartiles</span>: (<span class="number">7.7500000000</span>, <span class="number">22.0000000000</span>, <span class="number">35.0000000000</span>),
<span class="ident">iqr</span>: <span class="number">27.2500000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_exp25</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">3.0000000000</span>,
<span class="number">24.0000000000</span>,
<span class="number">1.0000000000</span>,
<span class="number">19.0000000000</span>,
<span class="number">7.0000000000</span>,
<span class="number">5.0000000000</span>,
<span class="number">30.0000000000</span>,
<span class="number">39.0000000000</span>,
<span class="number">31.0000000000</span>,
<span class="number">13.0000000000</span>,
<span class="number">25.0000000000</span>,
<span class="number">48.0000000000</span>,
<span class="number">1.0000000000</span>,
<span class="number">6.0000000000</span>,
<span class="number">42.0000000000</span>,
<span class="number">63.0000000000</span>,
<span class="number">2.0000000000</span>,
<span class="number">12.0000000000</span>,
<span class="number">108.0000000000</span>,
<span class="number">26.0000000000</span>,
<span class="number">1.0000000000</span>,
<span class="number">7.0000000000</span>,
<span class="number">44.0000000000</span>,
<span class="number">25.0000000000</span>,
<span class="number">11.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">593.0000000000</span>,
<span class="ident">min</span>: <span class="number">1.0000000000</span>,
<span class="ident">max</span>: <span class="number">108.0000000000</span>,
<span class="ident">mean</span>: <span class="number">23.7200000000</span>,
<span class="ident">median</span>: <span class="number">19.0000000000</span>,
<span class="ident">var</span>: <span class="number">601.0433333333</span>,
<span class="ident">std_dev</span>: <span class="number">24.5161851301</span>,
<span class="ident">std_dev_pct</span>: <span class="number">103.3565983562</span>,
<span class="ident">median_abs_dev</span>: <span class="number">19.2738000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">101.4410526316</span>,
<span class="ident">quartiles</span>: (<span class="number">6.0000000000</span>, <span class="number">19.0000000000</span>, <span class="number">31.0000000000</span>),
<span class="ident">iqr</span>: <span class="number">25.0000000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_binom25</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">18.0000000000</span>,
<span class="number">17.0000000000</span>,
<span class="number">27.0000000000</span>,
<span class="number">15.0000000000</span>,
<span class="number">21.0000000000</span>,
<span class="number">25.0000000000</span>,
<span class="number">17.0000000000</span>,
<span class="number">24.0000000000</span>,
<span class="number">25.0000000000</span>,
<span class="number">24.0000000000</span>,
<span class="number">26.0000000000</span>,
<span class="number">26.0000000000</span>,
<span class="number">23.0000000000</span>,
<span class="number">15.0000000000</span>,
<span class="number">23.0000000000</span>,
<span class="number">17.0000000000</span>,
<span class="number">18.0000000000</span>,
<span class="number">18.0000000000</span>,
<span class="number">21.0000000000</span>,
<span class="number">16.0000000000</span>,
<span class="number">15.0000000000</span>,
<span class="number">31.0000000000</span>,
<span class="number">20.0000000000</span>,
<span class="number">17.0000000000</span>,
<span class="number">15.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">514.0000000000</span>,
<span class="ident">min</span>: <span class="number">15.0000000000</span>,
<span class="ident">max</span>: <span class="number">31.0000000000</span>,
<span class="ident">mean</span>: <span class="number">20.5600000000</span>,
<span class="ident">median</span>: <span class="number">20.0000000000</span>,
<span class="ident">var</span>: <span class="number">20.8400000000</span>,
<span class="ident">std_dev</span>: <span class="number">4.5650848842</span>,
<span class="ident">std_dev_pct</span>: <span class="number">22.2037202539</span>,
<span class="ident">median_abs_dev</span>: <span class="number">5.9304000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">29.6520000000</span>,
<span class="ident">quartiles</span>: (<span class="number">17.0000000000</span>, <span class="number">20.0000000000</span>, <span class="number">24.0000000000</span>),
<span class="ident">iqr</span>: <span class="number">7.0000000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_pois25lambda30</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">27.0000000000</span>,
<span class="number">33.0000000000</span>,
<span class="number">34.0000000000</span>,
<span class="number">34.0000000000</span>,
<span class="number">24.0000000000</span>,
<span class="number">39.0000000000</span>,
<span class="number">28.0000000000</span>,
<span class="number">27.0000000000</span>,
<span class="number">31.0000000000</span>,
<span class="number">28.0000000000</span>,
<span class="number">38.0000000000</span>,
<span class="number">21.0000000000</span>,
<span class="number">33.0000000000</span>,
<span class="number">36.0000000000</span>,
<span class="number">29.0000000000</span>,
<span class="number">37.0000000000</span>,
<span class="number">32.0000000000</span>,
<span class="number">34.0000000000</span>,
<span class="number">31.0000000000</span>,
<span class="number">39.0000000000</span>,
<span class="number">25.0000000000</span>,
<span class="number">31.0000000000</span>,
<span class="number">32.0000000000</span>,
<span class="number">40.0000000000</span>,
<span class="number">24.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">787.0000000000</span>,
<span class="ident">min</span>: <span class="number">21.0000000000</span>,
<span class="ident">max</span>: <span class="number">40.0000000000</span>,
<span class="ident">mean</span>: <span class="number">31.4800000000</span>,
<span class="ident">median</span>: <span class="number">32.0000000000</span>,
<span class="ident">var</span>: <span class="number">26.5933333333</span>,
<span class="ident">std_dev</span>: <span class="number">5.1568724372</span>,
<span class="ident">std_dev_pct</span>: <span class="number">16.3814245145</span>,
<span class="ident">median_abs_dev</span>: <span class="number">5.9304000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">18.5325000000</span>,
<span class="ident">quartiles</span>: (<span class="number">28.0000000000</span>, <span class="number">32.0000000000</span>, <span class="number">34.0000000000</span>),
<span class="ident">iqr</span>: <span class="number">6.0000000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_pois25lambda40</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">42.0000000000</span>,
<span class="number">50.0000000000</span>,
<span class="number">42.0000000000</span>,
<span class="number">46.0000000000</span>,
<span class="number">34.0000000000</span>,
<span class="number">45.0000000000</span>,
<span class="number">34.0000000000</span>,
<span class="number">49.0000000000</span>,
<span class="number">39.0000000000</span>,
<span class="number">28.0000000000</span>,
<span class="number">40.0000000000</span>,
<span class="number">35.0000000000</span>,
<span class="number">37.0000000000</span>,
<span class="number">39.0000000000</span>,
<span class="number">46.0000000000</span>,
<span class="number">44.0000000000</span>,
<span class="number">32.0000000000</span>,
<span class="number">45.0000000000</span>,
<span class="number">42.0000000000</span>,
<span class="number">37.0000000000</span>,
<span class="number">48.0000000000</span>,
<span class="number">42.0000000000</span>,
<span class="number">33.0000000000</span>,
<span class="number">42.0000000000</span>,
<span class="number">48.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">1019.0000000000</span>,
<span class="ident">min</span>: <span class="number">28.0000000000</span>,
<span class="ident">max</span>: <span class="number">50.0000000000</span>,
<span class="ident">mean</span>: <span class="number">40.7600000000</span>,
<span class="ident">median</span>: <span class="number">42.0000000000</span>,
<span class="ident">var</span>: <span class="number">34.4400000000</span>,
<span class="ident">std_dev</span>: <span class="number">5.8685603004</span>,
<span class="ident">std_dev_pct</span>: <span class="number">14.3978417577</span>,
<span class="ident">median_abs_dev</span>: <span class="number">5.9304000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">14.1200000000</span>,
<span class="ident">quartiles</span>: (<span class="number">37.0000000000</span>, <span class="number">42.0000000000</span>, <span class="number">45.0000000000</span>),
<span class="ident">iqr</span>: <span class="number">8.0000000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_pois25lambda50</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">45.0000000000</span>,
<span class="number">43.0000000000</span>,
<span class="number">44.0000000000</span>,
<span class="number">61.0000000000</span>,
<span class="number">51.0000000000</span>,
<span class="number">53.0000000000</span>,
<span class="number">59.0000000000</span>,
<span class="number">52.0000000000</span>,
<span class="number">49.0000000000</span>,
<span class="number">51.0000000000</span>,
<span class="number">51.0000000000</span>,
<span class="number">50.0000000000</span>,
<span class="number">49.0000000000</span>,
<span class="number">56.0000000000</span>,
<span class="number">42.0000000000</span>,
<span class="number">52.0000000000</span>,
<span class="number">51.0000000000</span>,
<span class="number">43.0000000000</span>,
<span class="number">48.0000000000</span>,
<span class="number">48.0000000000</span>,
<span class="number">50.0000000000</span>,
<span class="number">42.0000000000</span>,
<span class="number">43.0000000000</span>,
<span class="number">42.0000000000</span>,
<span class="number">60.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">1235.0000000000</span>,
<span class="ident">min</span>: <span class="number">42.0000000000</span>,
<span class="ident">max</span>: <span class="number">61.0000000000</span>,
<span class="ident">mean</span>: <span class="number">49.4000000000</span>,
<span class="ident">median</span>: <span class="number">50.0000000000</span>,
<span class="ident">var</span>: <span class="number">31.6666666667</span>,
<span class="ident">std_dev</span>: <span class="number">5.6273143387</span>,
<span class="ident">std_dev_pct</span>: <span class="number">11.3913245723</span>,
<span class="ident">median_abs_dev</span>: <span class="number">4.4478000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">8.8956000000</span>,
<span class="ident">quartiles</span>: (<span class="number">44.0000000000</span>, <span class="number">50.0000000000</span>, <span class="number">52.0000000000</span>),
<span class="ident">iqr</span>: <span class="number">8.0000000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_unif25</span>() {
<span class="kw">let</span> <span class="ident">val</span> <span class="op">=</span> <span class="kw-2">&</span>[
<span class="number">99.0000000000</span>,
<span class="number">55.0000000000</span>,
<span class="number">92.0000000000</span>,
<span class="number">79.0000000000</span>,
<span class="number">14.0000000000</span>,
<span class="number">2.0000000000</span>,
<span class="number">33.0000000000</span>,
<span class="number">49.0000000000</span>,
<span class="number">3.0000000000</span>,
<span class="number">32.0000000000</span>,
<span class="number">84.0000000000</span>,
<span class="number">59.0000000000</span>,
<span class="number">22.0000000000</span>,
<span class="number">86.0000000000</span>,
<span class="number">76.0000000000</span>,
<span class="number">31.0000000000</span>,
<span class="number">29.0000000000</span>,
<span class="number">11.0000000000</span>,
<span class="number">41.0000000000</span>,
<span class="number">53.0000000000</span>,
<span class="number">45.0000000000</span>,
<span class="number">44.0000000000</span>,
<span class="number">98.0000000000</span>,
<span class="number">98.0000000000</span>,
<span class="number">7.0000000000</span>,
];
<span class="kw">let</span> <span class="ident">summ</span> <span class="op">=</span> <span class="kw-2">&</span><span class="ident">Summary</span> {
<span class="ident">sum</span>: <span class="number">1242.0000000000</span>,
<span class="ident">min</span>: <span class="number">2.0000000000</span>,
<span class="ident">max</span>: <span class="number">99.0000000000</span>,
<span class="ident">mean</span>: <span class="number">49.6800000000</span>,
<span class="ident">median</span>: <span class="number">45.0000000000</span>,
<span class="ident">var</span>: <span class="number">1015.6433333333</span>,
<span class="ident">std_dev</span>: <span class="number">31.8691595957</span>,
<span class="ident">std_dev_pct</span>: <span class="number">64.1488719719</span>,
<span class="ident">median_abs_dev</span>: <span class="number">45.9606000000</span>,
<span class="ident">median_abs_dev_pct</span>: <span class="number">102.1346666667</span>,
<span class="ident">quartiles</span>: (<span class="number">29.0000000000</span>, <span class="number">45.0000000000</span>, <span class="number">79.0000000000</span>),
<span class="ident">iqr</span>: <span class="number">50.0000000000</span>,
};
<span class="ident">check</span>(<span class="ident">val</span>, <span class="ident">summ</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_sum_f64s</span>() {
<span class="macro">assert_eq</span><span class="macro">!</span>([<span class="number">0.5f64</span>, <span class="number">3.2321f64</span>, <span class="number">1.5678f64</span>].<span class="ident">sum</span>(), <span class="number">5.2999</span>);
}
<span class="attribute">#[<span class="ident">test</span>]</span>
<span class="kw">fn</span> <span class="ident">test_sum_f64_between_ints_that_sum_to_0</span>() {
<span class="macro">assert_eq</span><span class="macro">!</span>([<span class="number">1e30f64</span>, <span class="number">1.2f64</span>, <span class="op">-</span><span class="number">1e30f64</span>].<span class="ident">sum</span>(), <span class="number">1.2</span>);
}
}
<span class="attribute">#[<span class="ident">cfg</span>(<span class="ident">test</span>)]</span>
<span class="kw">mod</span> <span class="ident">bench</span> {
<span class="kw">use</span> <span class="ident">Bencher</span>;
<span class="kw">use</span> <span class="ident">stats</span>::<span class="ident">Stats</span>;
<span class="attribute">#[<span class="ident">bench</span>]</span>
<span class="kw">pub</span> <span class="kw">fn</span> <span class="ident">sum_three_items</span>(<span class="ident">b</span>: <span class="kw-2">&</span><span class="kw-2">mut</span> <span class="ident">Bencher</span>) {
<span class="ident">b</span>.<span class="ident">iter</span>(<span class="op">||</span> {
[<span class="number">1e20f64</span>, <span class="number">1.5f64</span>, <span class="op">-</span><span class="number">1e20f64</span>].<span class="ident">sum</span>();
})
}
<span class="attribute">#[<span class="ident">bench</span>]</span>
<span class="kw">pub</span> <span class="kw">fn</span> <span class="ident">sum_many_f64</span>(<span class="ident">b</span>: <span class="kw-2">&</span><span class="kw-2">mut</span> <span class="ident">Bencher</span>) {
<span class="kw">let</span> <span class="ident">nums</span> <span class="op">=</span> [<span class="op">-</span><span class="number">1e30f64</span>, <span class="number">1e60</span>, <span class="number">1e30</span>, <span class="number">1.0</span>, <span class="op">-</span><span class="number">1e60</span>];
<span class="kw">let</span> <span class="ident">v</span> <span class="op">=</span> (<span class="number">0</span>..<span class="number">500</span>).<span class="ident">map</span>(<span class="op">|</span><span class="ident">i</span><span class="op">|</span> <span class="ident">nums</span>[<span class="ident">i</span> <span class="op">%</span> <span class="number">5</span>]).<span class="ident">collect</span>::<span class="op"><</span><span class="ident">Vec</span><span class="op"><</span><span class="kw">_</span><span class="op">>></span>();
<span class="ident">b</span>.<span class="ident">iter</span>(<span class="op">||</span> {
<span class="ident">v</span>.<span class="ident">sum</span>();
})
}
<span class="attribute">#[<span class="ident">bench</span>]</span>
<span class="kw">pub</span> <span class="kw">fn</span> <span class="ident">no_iter</span>(<span class="kw">_</span>: <span class="kw-2">&</span><span class="kw-2">mut</span> <span class="ident">Bencher</span>) {}
}
</pre>
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