| <!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 of the Rust file `/root/sunhe/incubator-teaclave/third_party/rust-sgx-sdk/sgx_rand/src/distributions/mod.rs`."><meta name="keywords" content="rust, rustlang, rust-lang"><title>mod.rs - source</title><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../SourceSerif4-Regular.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../FiraSans-Regular.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../FiraSans-Medium.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../SourceCodePro-Regular.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../SourceSerif4-Bold.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../SourceCodePro-Semibold.ttf.woff2"><link rel="stylesheet" href="../../../normalize.css"><link rel="stylesheet" href="../../../rustdoc.css" id="mainThemeStyle"><link rel="stylesheet" href="../../../ayu.css" disabled><link rel="stylesheet" href="../../../dark.css" disabled><link rel="stylesheet" href="../../../light.css" id="themeStyle"><script id="default-settings" ></script><script src="../../../storage.js"></script><script defer src="../../../source-script.js"></script><script defer src="../../../source-files.js"></script><script defer src="../../../main.js"></script><noscript><link rel="stylesheet" href="../../../noscript.css"></noscript><link rel="alternate icon" type="image/png" href="../../../favicon-16x16.png"><link rel="alternate icon" type="image/png" href="../../../favicon-32x32.png"><link rel="icon" type="image/svg+xml" href="../../../favicon.svg"></head><body class="rustdoc source"><!--[if lte IE 11]><div class="warning">This old browser is unsupported and will most likely display funky things.</div><![endif]--><nav class="sidebar"><a class="sidebar-logo" href="../../../sgx_rand/index.html"><div class="logo-container"><img class="rust-logo" src="../../../rust-logo.svg" alt="logo"></div></a></nav><main><div class="width-limiter"><nav class="sub"><a class="sub-logo-container" href="../../../sgx_rand/index.html"><img class="rust-logo" src="../../../rust-logo.svg" alt="logo"></a><form class="search-form"><div class="search-container"><span></span><input class="search-input" name="search" autocomplete="off" spellcheck="false" placeholder="Click or press ‘S’ to search, ‘?’ for more options…" type="search"><div id="help-button" title="help" tabindex="-1"><a href="../../../help.html">?</a></div><div id="settings-menu" tabindex="-1"><a href="../../../settings.html" title="settings"><img width="22" height="22" alt="Change settings" src="../../../wheel.svg"></a></div></div></form></nav><section id="main-content" class="content"><div class="example-wrap"><pre class="src-line-numbers"><span id="1">1</span> |
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| </pre><pre class="rust"><code><span class="comment">// Licensed to the Apache Software Foundation (ASF) under one |
| // or more contributor license agreements. See the NOTICE file |
| // distributed with this work for additional information |
| // regarding copyright ownership. The ASF licenses this file |
| // to you under the Apache License, Version 2.0 (the |
| // "License"); you may not use this file except in compliance |
| // with the License. You may obtain a copy of the License at |
| // |
| // http://www.apache.org/licenses/LICENSE-2.0 |
| // |
| // Unless required by applicable law or agreed to in writing, |
| // software distributed under the License is distributed on an |
| // "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| // KIND, either express or implied. See the License for the |
| // specific language governing permissions and limitations |
| // under the License.. |
| |
| </span><span class="doccomment">//! Sampling from random distributions. |
| //! |
| //! This is a generalization of `Rand` to allow parameters to control the |
| //! exact properties of the generated values, e.g. the mean and standard |
| //! deviation of a normal distribution. The `Sample` trait is the most |
| //! general, and allows for generating values that change some state |
| //! internally. The `IndependentSample` trait is for generating values |
| //! that do not need to record state. |
| |
| </span><span class="kw">use </span>std::marker; |
| |
| <span class="kw">use crate</span>::{Rand, Rng}; |
| |
| <span class="kw">pub use </span><span class="self">self</span>::exponential::Exp; |
| <span class="kw">pub use </span><span class="self">self</span>::gamma::{ChiSquared, FisherF, Gamma, StudentT}; |
| <span class="kw">pub use </span><span class="self">self</span>::normal::{LogNormal, Normal}; |
| <span class="kw">pub use </span><span class="self">self</span>::range::Range; |
| |
| <span class="kw">pub mod </span>exponential; |
| <span class="kw">pub mod </span>gamma; |
| <span class="kw">pub mod </span>normal; |
| <span class="kw">pub mod </span>range; |
| |
| <span class="doccomment">/// Types that can be used to create a random instance of `Support`. |
| </span><span class="kw">pub trait </span>Sample<Support> { |
| <span class="doccomment">/// Generate a random value of `Support`, using `rng` as the |
| /// source of randomness. |
| </span><span class="kw">fn </span>sample<R: Rng>(<span class="kw-2">&mut </span><span class="self">self</span>, rng: <span class="kw-2">&mut </span>R) -> Support; |
| } |
| |
| <span class="doccomment">/// `Sample`s that do not require keeping track of state. |
| /// |
| /// Since no state is recorded, each sample is (statistically) |
| /// independent of all others, assuming the `Rng` used has this |
| /// property. |
| </span><span class="comment">// FIXME maybe having this separate is overkill (the only reason is to |
| // take &self rather than &mut self)? or maybe this should be the |
| // trait called `Sample` and the other should be `DependentSample`. |
| </span><span class="kw">pub trait </span>IndependentSample<Support>: Sample<Support> { |
| <span class="doccomment">/// Generate a random value. |
| </span><span class="kw">fn </span>ind_sample<R: Rng>(<span class="kw-2">&</span><span class="self">self</span>, rng: <span class="kw-2">&mut </span>R) -> Support; |
| } |
| |
| <span class="doccomment">/// A wrapper for generating types that implement `Rand` via the |
| /// `Sample` & `IndependentSample` traits. |
| </span><span class="attribute">#[derive(Debug)] |
| </span><span class="kw">pub struct </span>RandSample<Sup> { |
| _marker: marker::PhantomData<<span class="kw">fn</span>() -> Sup>, |
| } |
| |
| <span class="kw">impl</span><Sup> Copy <span class="kw">for </span>RandSample<Sup> {} |
| <span class="kw">impl</span><Sup> Clone <span class="kw">for </span>RandSample<Sup> { |
| <span class="kw">fn </span>clone(<span class="kw-2">&</span><span class="self">self</span>) -> <span class="self">Self </span>{ |
| <span class="kw-2">*</span><span class="self">self |
| </span>} |
| } |
| |
| <span class="kw">impl</span><Sup: Rand> Sample<Sup> <span class="kw">for </span>RandSample<Sup> { |
| <span class="kw">fn </span>sample<R: Rng>(<span class="kw-2">&mut </span><span class="self">self</span>, rng: <span class="kw-2">&mut </span>R) -> Sup { |
| <span class="self">self</span>.ind_sample(rng) |
| } |
| } |
| |
| <span class="kw">impl</span><Sup: Rand> IndependentSample<Sup> <span class="kw">for </span>RandSample<Sup> { |
| <span class="kw">fn </span>ind_sample<R: Rng>(<span class="kw-2">&</span><span class="self">self</span>, rng: <span class="kw-2">&mut </span>R) -> Sup { |
| rng.gen() |
| } |
| } |
| |
| <span class="kw">impl</span><Sup> RandSample<Sup> { |
| <span class="kw">pub fn </span>new() -> RandSample<Sup> { |
| RandSample { |
| _marker: marker::PhantomData, |
| } |
| } |
| } |
| |
| <span class="kw">impl</span><Sup> Default <span class="kw">for </span>RandSample<Sup> { |
| <span class="kw">fn </span>default() -> RandSample<Sup> { |
| <span class="self">Self</span>::new() |
| } |
| } |
| |
| <span class="doccomment">/// A value with a particular weight for use with `WeightedChoice`. |
| </span><span class="attribute">#[derive(Copy, Clone, Debug)] |
| </span><span class="kw">pub struct </span>Weighted<T> { |
| <span class="doccomment">/// The numerical weight of this item |
| </span><span class="kw">pub </span>weight: u32, |
| <span class="doccomment">/// The actual item which is being weighted |
| </span><span class="kw">pub </span>item: T, |
| } |
| |
| <span class="doccomment">/// A distribution that selects from a finite collection of weighted items. |
| /// |
| /// Each item has an associated weight that influences how likely it |
| /// is to be chosen: higher weight is more likely. |
| /// |
| /// The `Clone` restriction is a limitation of the `Sample` and |
| /// `IndependentSample` traits. Note that `&T` is (cheaply) `Clone` for |
| /// all `T`, as is `u32`, so one can store references or indices into |
| /// another vector. |
| /// |
| /// # Example |
| /// |
| /// ```rust |
| /// use sgx_rand::distributions::{Weighted, WeightedChoice, IndependentSample}; |
| /// |
| /// let mut items = vec!(Weighted { weight: 2, item: 'a' }, |
| /// Weighted { weight: 4, item: 'b' }, |
| /// Weighted { weight: 1, item: 'c' }); |
| /// let wc = WeightedChoice::new(&mut items); |
| /// let mut rng = sgx_rand::thread_rng(); |
| /// for _ in 0..16 { |
| /// // on average prints 'a' 4 times, 'b' 8 and 'c' twice. |
| /// println!("{}", wc.ind_sample(&mut rng)); |
| /// } |
| /// ``` |
| </span><span class="attribute">#[derive(Debug)] |
| </span><span class="kw">pub struct </span>WeightedChoice<<span class="lifetime">'a</span>, T: <span class="lifetime">'a</span>> { |
| items: <span class="kw-2">&</span><span class="lifetime">'a </span><span class="kw-2">mut </span>[Weighted<T>], |
| weight_range: Range<u32>, |
| } |
| |
| <span class="kw">impl</span><<span class="lifetime">'a</span>, T: Clone> WeightedChoice<<span class="lifetime">'a</span>, T> { |
| <span class="doccomment">/// Create a new `WeightedChoice`. |
| /// |
| /// Panics if: |
| /// - `v` is empty |
| /// - the total weight is 0 |
| /// - the total weight is larger than a `u32` can contain. |
| </span><span class="kw">pub fn </span>new(items: <span class="kw-2">&</span><span class="lifetime">'a </span><span class="kw-2">mut </span>[Weighted<T>]) -> WeightedChoice<<span class="lifetime">'a</span>, T> { |
| <span class="comment">// strictly speaking, this is subsumed by the total weight == 0 case |
| </span><span class="macro">assert!</span>( |
| !items.is_empty(), |
| <span class="string">"WeightedChoice::new called with no items" |
| </span>); |
| |
| <span class="kw">let </span><span class="kw-2">mut </span>running_total: u32 = <span class="number">0</span>; |
| |
| <span class="comment">// we convert the list from individual weights to cumulative |
| // weights so we can binary search. This *could* drop elements |
| // with weight == 0 as an optimisation. |
| </span><span class="kw">for </span>item <span class="kw">in </span>items.iter_mut() { |
| running_total = <span class="kw">match </span>running_total.checked_add(item.weight) { |
| <span class="prelude-val">Some</span>(n) => n, |
| <span class="prelude-val">None </span>=> <span class="macro">panic!</span>( |
| <span class="string">"WeightedChoice::new called with a total weight \ |
| larger than a u32 can contain" |
| </span>), |
| }; |
| |
| item.weight = running_total; |
| } |
| <span class="macro">assert!</span>( |
| running_total != <span class="number">0</span>, |
| <span class="string">"WeightedChoice::new called with a total weight of 0" |
| </span>); |
| |
| WeightedChoice { |
| items, |
| <span class="comment">// we're likely to be generating numbers in this range |
| // relatively often, so might as well cache it |
| </span>weight_range: Range::new(<span class="number">0</span>, running_total), |
| } |
| } |
| } |
| |
| <span class="kw">impl</span><<span class="lifetime">'a</span>, T: Clone> Sample<T> <span class="kw">for </span>WeightedChoice<<span class="lifetime">'a</span>, T> { |
| <span class="kw">fn </span>sample<R: Rng>(<span class="kw-2">&mut </span><span class="self">self</span>, rng: <span class="kw-2">&mut </span>R) -> T { |
| <span class="self">self</span>.ind_sample(rng) |
| } |
| } |
| |
| <span class="kw">impl</span><<span class="lifetime">'a</span>, T: Clone> IndependentSample<T> <span class="kw">for </span>WeightedChoice<<span class="lifetime">'a</span>, T> { |
| <span class="kw">fn </span>ind_sample<R: Rng>(<span class="kw-2">&</span><span class="self">self</span>, rng: <span class="kw-2">&mut </span>R) -> T { |
| <span class="comment">// we want to find the first element that has cumulative |
| // weight > sample_weight, which we do by binary since the |
| // cumulative weights of self.items are sorted. |
| |
| // choose a weight in [0, total_weight) |
| </span><span class="kw">let </span>sample_weight = <span class="self">self</span>.weight_range.ind_sample(rng); |
| |
| <span class="comment">// short circuit when it's the first item |
| </span><span class="kw">if </span>sample_weight < <span class="self">self</span>.items[<span class="number">0</span>].weight { |
| <span class="kw">return </span><span class="self">self</span>.items[<span class="number">0</span>].item.clone(); |
| } |
| |
| <span class="kw">let </span><span class="kw-2">mut </span>idx = <span class="number">0</span>; |
| <span class="kw">let </span><span class="kw-2">mut </span>modifier = <span class="self">self</span>.items.len(); |
| |
| <span class="comment">// now we know that every possibility has an element to the |
| // left, so we can just search for the last element that has |
| // cumulative weight <= sample_weight, then the next one will |
| // be "it". (Note that this greatest element will never be the |
| // last element of the vector, since sample_weight is chosen |
| // in [0, total_weight) and the cumulative weight of the last |
| // one is exactly the total weight.) |
| </span><span class="kw">while </span>modifier > <span class="number">1 </span>{ |
| <span class="kw">let </span>i = idx + modifier / <span class="number">2</span>; |
| <span class="kw">if </span><span class="self">self</span>.items[i].weight <= sample_weight { |
| <span class="comment">// we're small, so look to the right, but allow this |
| // exact element still. |
| </span>idx = i; |
| <span class="comment">// we need the `/ 2` to round up otherwise we'll drop |
| // the trailing elements when `modifier` is odd. |
| </span>modifier += <span class="number">1</span>; |
| } <span class="kw">else </span>{ |
| <span class="comment">// otherwise we're too big, so go left. (i.e. do |
| // nothing) |
| </span>} |
| modifier /= <span class="number">2</span>; |
| } |
| <span class="self">self</span>.items[idx + <span class="number">1</span>].item.clone() |
| } |
| } |
| |
| <span class="kw">mod </span>ziggurat_tables; |
| |
| <span class="doccomment">/// Sample a random number using the Ziggurat method (specifically the |
| /// ZIGNOR variant from Doornik 2005). Most of the arguments are |
| /// directly from the paper: |
| /// |
| /// * `rng`: source of randomness |
| /// * `symmetric`: whether this is a symmetric distribution, or one-sided with P(x < 0) = 0. |
| /// * `X`: the $x_i$ abscissae. |
| /// * `F`: precomputed values of the PDF at the $x_i$, (i.e. $f(x_i)$) |
| /// * `F_DIFF`: precomputed values of $f(x_i) - f(x_{i+1})$ |
| /// * `pdf`: the probability density function |
| /// * `zero_case`: manual sampling from the tail when we chose the |
| /// bottom box (i.e. i == 0) |
| |
| </span><span class="comment">// the perf improvement (25-50%) is definitely worth the extra code |
| // size from force-inlining. |
| </span><span class="attribute">#[inline(always)] |
| </span><span class="kw">fn </span>ziggurat<R: Rng, P, Z>( |
| rng: <span class="kw-2">&mut </span>R, |
| symmetric: bool, |
| x_tab: ziggurat_tables::ZigTable, |
| f_tab: ziggurat_tables::ZigTable, |
| <span class="kw-2">mut </span>pdf: P, |
| <span class="kw-2">mut </span>zero_case: Z, |
| ) -> f64 |
| <span class="kw">where |
| </span>P: FnMut(f64) -> f64, |
| Z: FnMut(<span class="kw-2">&mut </span>R, f64) -> f64, |
| { |
| <span class="kw">const </span>SCALE: f64 = (<span class="number">1u64 </span><< <span class="number">53</span>) <span class="kw">as </span>f64; |
| <span class="kw">loop </span>{ |
| <span class="comment">// reimplement the f64 generation as an optimisation suggested |
| // by the Doornik paper: we have a lot of precision-space |
| // (i.e. there are 11 bits of the 64 of a u64 to use after |
| // creating a f64), so we might as well reuse some to save |
| // generating a whole extra random number. (Seems to be 15% |
| // faster.) |
| // |
| // This unfortunately misses out on the benefits of direct |
| // floating point generation if an RNG like dSMFT is |
| // used. (That is, such RNGs create floats directly, highly |
| // efficiently and overload next_f32/f64, so by not calling it |
| // this may be slower than it would be otherwise.) |
| // FIXME: investigate/optimise for the above. |
| </span><span class="kw">let </span>bits: u64 = rng.gen(); |
| <span class="kw">let </span>i = (bits & <span class="number">0xff</span>) <span class="kw">as </span>usize; |
| <span class="kw">let </span>f = (bits >> <span class="number">11</span>) <span class="kw">as </span>f64 / SCALE; |
| |
| <span class="comment">// u is either U(-1, 1) or U(0, 1) depending on if this is a |
| // symmetric distribution or not. |
| </span><span class="kw">let </span>u = <span class="kw">if </span>symmetric { <span class="number">2.0 </span>* f - <span class="number">1.0 </span>} <span class="kw">else </span>{ f }; |
| <span class="kw">let </span>x = u * x_tab[i]; |
| |
| <span class="kw">let </span>test_x = <span class="kw">if </span>symmetric { x.abs() } <span class="kw">else </span>{ x }; |
| |
| <span class="comment">// algebraically equivalent to |u| < x_tab[i+1]/x_tab[i] (or u < x_tab[i+1]/x_tab[i]) |
| </span><span class="kw">if </span>test_x < x_tab[i + <span class="number">1</span>] { |
| <span class="kw">return </span>x; |
| } |
| <span class="kw">if </span>i == <span class="number">0 </span>{ |
| <span class="kw">return </span>zero_case(rng, u); |
| } |
| <span class="comment">// algebraically equivalent to f1 + DRanU()*(f0 - f1) < 1 |
| </span><span class="kw">if </span>f_tab[i + <span class="number">1</span>] + (f_tab[i] - f_tab[i + <span class="number">1</span>]) * rng.gen::<f64>() < pdf(x) { |
| <span class="kw">return </span>x; |
| } |
| } |
| } |
| </code></pre></div> |
| </section></div></main><div id="rustdoc-vars" data-root-path="../../../" data-current-crate="sgx_rand" data-themes="ayu,dark,light" data-resource-suffix="" data-rustdoc-version="1.66.0-nightly (5c8bff74b 2022-10-21)" ></div></body></html> |
