From d0d9683df8398696147e7ee1fcffb2e4e957008c Mon Sep 17 00:00:00 2001
From: Daniel Mueller <deso@posteo.net>
Date: Sat, 4 Apr 2020 14:39:19 -0700
Subject: Remove vendored dependencies
While it appears that by now we actually can get successful builds
without Cargo insisting on Internet access by virtue of using the
--frozen flag, maintaining vendored dependencies is somewhat of a pain
point. This state will also get worse with upcoming changes that replace
argparse in favor of structopt and pull in a slew of new dependencies by
doing so. Then there is also the repository structure aspect, which is
non-standard due to the way we vendor dependencies and a potential
source of confusion.
In order to fix these problems, this change removes all the vendored
dependencies we have.
Delete subrepo argparse/:argparse
Delete subrepo base32/:base32
Delete subrepo cc/:cc
Delete subrepo cfg-if/:cfg-if
Delete subrepo getrandom/:getrandom
Delete subrepo lazy-static/:lazy-static
Delete subrepo libc/:libc
Delete subrepo nitrokey-sys/:nitrokey-sys
Delete subrepo nitrokey/:nitrokey
Delete subrepo rand/:rand
---
rand/.github/ISSUE_TEMPLATE/compile-issue.md | 16 -
rand/.github/ISSUE_TEMPLATE/feature_request.md | 18 -
rand/.github/ISSUE_TEMPLATE/other.md | 10 -
rand/.gitignore | 4 -
rand/.travis.yml | 315 ------
rand/CHANGELOG.md | 568 ----------
rand/COPYRIGHT | 12 -
rand/Cargo.toml | 90 --
rand/LICENSE-APACHE | 201 ----
rand/LICENSE-MIT | 26 -
rand/README.md | 118 ---
rand/appveyor.yml | 49 -
rand/benches/generators.rs | 220 ----
rand/benches/misc.rs | 140 ---
rand/benches/seq.rs | 177 ----
rand/benches/weighted.rs | 36 -
rand/examples/monte-carlo.rs | 48 -
rand/examples/monty-hall.rs | 112 --
rand/rand_chacha/CHANGELOG.md | 18 -
rand/rand_chacha/COPYRIGHT | 12 -
rand/rand_chacha/Cargo.toml | 28 -
rand/rand_chacha/LICENSE-APACHE | 201 ----
rand/rand_chacha/LICENSE-MIT | 26 -
rand/rand_chacha/README.md | 49 -
rand/rand_chacha/src/chacha.rs | 452 --------
rand/rand_chacha/src/lib.rs | 30 -
rand/rand_core/CHANGELOG.md | 58 --
rand/rand_core/COPYRIGHT | 12 -
rand/rand_core/Cargo.toml | 28 -
rand/rand_core/LICENSE-APACHE | 201 ----
rand/rand_core/LICENSE-MIT | 26 -
rand/rand_core/README.md | 82 --
rand/rand_core/src/block.rs | 437 --------
rand/rand_core/src/error.rs | 190 ----
rand/rand_core/src/impls.rs | 158 ---
rand/rand_core/src/le.rs | 68 --
rand/rand_core/src/lib.rs | 492 ---------
rand/rand_core/src/os.rs | 85 --
rand/rand_distr/CHANGELOG.md | 21 -
rand/rand_distr/COPYRIGHT | 12 -
rand/rand_distr/Cargo.toml | 27 -
rand/rand_distr/LICENSE-APACHE | 201 ----
rand/rand_distr/LICENSE-MIT | 25 -
rand/rand_distr/README.md | 42 -
rand/rand_distr/benches/distributions.rs | 316 ------
rand/rand_distr/src/binomial.rs | 329 ------
rand/rand_distr/src/cauchy.rs | 120 ---
rand/rand_distr/src/dirichlet.rs | 154 ---
rand/rand_distr/src/exponential.rs | 145 ---
rand/rand_distr/src/gamma.rs | 485 ---------
rand/rand_distr/src/lib.rs | 134 ---
rand/rand_distr/src/normal.rs | 219 ----
rand/rand_distr/src/pareto.rs | 89 --
rand/rand_distr/src/pert.rs | 132 ---
rand/rand_distr/src/poisson.rs | 233 -----
rand/rand_distr/src/triangular.rs | 125 ---
rand/rand_distr/src/unit_ball.rs | 69 --
rand/rand_distr/src/unit_circle.rs | 99 --
rand/rand_distr/src/unit_disc.rs | 66 --
rand/rand_distr/src/unit_sphere.rs | 94 --
rand/rand_distr/src/utils.rs | 234 -----
rand/rand_distr/src/weibull.rs | 86 --
rand/rand_distr/src/ziggurat_tables.rs | 279 -----
rand/rand_distr/tests/uniformity.rs | 59 --
rand/rand_hc/CHANGELOG.md | 16 -
rand/rand_hc/COPYRIGHT | 12 -
rand/rand_hc/Cargo.toml | 22 -
rand/rand_hc/LICENSE-APACHE | 201 ----
rand/rand_hc/LICENSE-MIT | 25 -
rand/rand_hc/README.md | 45 -
rand/rand_hc/src/hc128.rs | 464 ---------
rand/rand_hc/src/lib.rs | 23 -
rand/rand_isaac/CHANGELOG.md | 21 -
rand/rand_isaac/COPYRIGHT | 12 -
rand/rand_isaac/Cargo.toml | 31 -
rand/rand_isaac/LICENSE-APACHE | 201 ----
rand/rand_isaac/LICENSE-MIT | 26 -
rand/rand_isaac/README.md | 47 -
rand/rand_isaac/src/isaac.rs | 476 ---------
rand/rand_isaac/src/isaac64.rs | 466 ---------
rand/rand_isaac/src/isaac_array.rs | 136 ---
rand/rand_isaac/src/lib.rs | 27 -
rand/rand_jitter/CHANGELOG.md | 32 -
rand/rand_jitter/COPYRIGHT | 12 -
rand/rand_jitter/Cargo.toml | 30 -
rand/rand_jitter/LICENSE-APACHE | 201 ----
rand/rand_jitter/LICENSE-MIT | 26 -
rand/rand_jitter/README.md | 119 ---
rand/rand_jitter/benches/mod.rs | 17 -
rand/rand_jitter/src/error.rs | 77 --
rand/rand_jitter/src/lib.rs | 750 -------------
rand/rand_jitter/src/platform.rs | 44 -
rand/rand_jitter/tests/mod.rs | 28 -
rand/rand_os/CHANGELOG.md | 35 -
rand/rand_os/COPYRIGHT | 12 -
rand/rand_os/Cargo.toml | 26 -
rand/rand_os/LICENSE-APACHE | 201 ----
rand/rand_os/LICENSE-MIT | 26 -
rand/rand_os/README.md | 35 -
rand/rand_os/src/lib.rs | 106 --
rand/rand_pcg/CHANGELOG.md | 24 -
rand/rand_pcg/COPYRIGHT | 12 -
rand/rand_pcg/Cargo.toml | 32 -
rand/rand_pcg/LICENSE-APACHE | 201 ----
rand/rand_pcg/LICENSE-MIT | 26 -
rand/rand_pcg/README.md | 43 -
rand/rand_pcg/src/lib.rs | 49 -
rand/rand_pcg/src/pcg128.rs | 225 ----
rand/rand_pcg/src/pcg64.rs | 127 ---
rand/rand_pcg/tests/lcg128xsl64.rs | 55 -
rand/rand_pcg/tests/lcg64xsh32.rs | 54 -
rand/rand_pcg/tests/mcg128xsl64.rs | 54 -
rand/rand_xorshift/CHANGELOG.md | 19 -
rand/rand_xorshift/COPYRIGHT | 12 -
rand/rand_xorshift/Cargo.toml | 31 -
rand/rand_xorshift/LICENSE-APACHE | 201 ----
rand/rand_xorshift/LICENSE-MIT | 26 -
rand/rand_xorshift/README.md | 45 -
rand/rand_xorshift/src/lib.rs | 117 ---
rand/rand_xorshift/tests/mod.rs | 89 --
rand/rand_xoshiro/CHANGELOG.md | 24 -
rand/rand_xoshiro/COPYRIGHT | 12 -
rand/rand_xoshiro/Cargo.toml | 25 -
rand/rand_xoshiro/LICENSE-APACHE | 201 ----
rand/rand_xoshiro/LICENSE-MIT | 25 -
rand/rand_xoshiro/README.md | 34 -
rand/rand_xoshiro/src/common.rs | 243 -----
rand/rand_xoshiro/src/lib.rs | 94 --
rand/rand_xoshiro/src/splitmix64.rs | 149 ---
rand/rand_xoshiro/src/xoroshiro128plus.rs | 130 ---
rand/rand_xoshiro/src/xoroshiro128starstar.rs | 127 ---
rand/rand_xoshiro/src/xoroshiro64star.rs | 102 --
rand/rand_xoshiro/src/xoroshiro64starstar.rs | 101 --
rand/rand_xoshiro/src/xoshiro128plus.rs | 112 --
rand/rand_xoshiro/src/xoshiro128starstar.rs | 111 --
rand/rand_xoshiro/src/xoshiro256plus.rs | 131 ---
rand/rand_xoshiro/src/xoshiro256starstar.rs | 128 ---
rand/rand_xoshiro/src/xoshiro512plus.rs | 122 ---
rand/rand_xoshiro/src/xoshiro512starstar.rs | 122 ---
rand/rand_xoshiro/tests/serde.rs | 83 --
rand/rustfmt.toml | 30 -
rand/src/distributions/bernoulli.rs | 166 ---
rand/src/distributions/binomial.rs | 313 ------
rand/src/distributions/cauchy.rs | 103 --
rand/src/distributions/dirichlet.rs | 128 ---
rand/src/distributions/exponential.rs | 108 --
rand/src/distributions/float.rs | 259 -----
rand/src/distributions/gamma.rs | 371 -------
rand/src/distributions/integer.rs | 184 ----
rand/src/distributions/mod.rs | 381 -------
rand/src/distributions/normal.rs | 170 ---
rand/src/distributions/other.rs | 220 ----
rand/src/distributions/pareto.rs | 67 --
rand/src/distributions/poisson.rs | 151 ---
rand/src/distributions/triangular.rs | 79 --
rand/src/distributions/uniform.rs | 1270 -----------------------
rand/src/distributions/unit_circle.rs | 101 --
rand/src/distributions/unit_sphere.rs | 96 --
rand/src/distributions/utils.rs | 488 ---------
rand/src/distributions/weibull.rs | 64 --
rand/src/distributions/weighted/alias_method.rs | 499 ---------
rand/src/distributions/weighted/mod.rs | 363 -------
rand/src/distributions/ziggurat_tables.rs | 279 -----
rand/src/lib.rs | 720 -------------
rand/src/prelude.rs | 28 -
rand/src/rngs/adapter/mod.rs | 15 -
rand/src/rngs/adapter/read.rs | 148 ---
rand/src/rngs/adapter/reseeding.rs | 357 -------
rand/src/rngs/entropy.rs | 76 --
rand/src/rngs/mock.rs | 64 --
rand/src/rngs/mod.rs | 119 ---
rand/src/rngs/small.rs | 115 --
rand/src/rngs/std.rs | 100 --
rand/src/rngs/thread.rs | 124 ---
rand/src/seq/index.rs | 409 --------
rand/src/seq/mod.rs | 791 --------------
rand/tests/wasm_bindgen/Cargo.toml | 16 -
rand/tests/wasm_bindgen/js/index.js | 7 -
rand/tests/wasm_bindgen/src/lib.rs | 49 -
rand/utils/ci/install.sh | 49 -
rand/utils/ci/install_cargo_web.sh | 15 -
rand/utils/ci/miri.sh | 23 -
rand/utils/ci/script.sh | 27 -
rand/utils/ziggurat_tables.py | 125 ---
184 files changed, 25421 deletions(-)
delete mode 100644 rand/.github/ISSUE_TEMPLATE/compile-issue.md
delete mode 100644 rand/.github/ISSUE_TEMPLATE/feature_request.md
delete mode 100644 rand/.github/ISSUE_TEMPLATE/other.md
delete mode 100644 rand/.gitignore
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delete mode 100644 rand/CHANGELOG.md
delete mode 100644 rand/COPYRIGHT
delete mode 100644 rand/Cargo.toml
delete mode 100644 rand/LICENSE-APACHE
delete mode 100644 rand/LICENSE-MIT
delete mode 100644 rand/README.md
delete mode 100644 rand/appveyor.yml
delete mode 100644 rand/benches/generators.rs
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delete mode 100644 rand/benches/seq.rs
delete mode 100644 rand/benches/weighted.rs
delete mode 100644 rand/examples/monte-carlo.rs
delete mode 100644 rand/examples/monty-hall.rs
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delete mode 100644 rand/rand_core/src/le.rs
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delete mode 100644 rand/rand_distr/CHANGELOG.md
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delete mode 100644 rand/rand_distr/benches/distributions.rs
delete mode 100644 rand/rand_distr/src/binomial.rs
delete mode 100644 rand/rand_distr/src/cauchy.rs
delete mode 100644 rand/rand_distr/src/dirichlet.rs
delete mode 100644 rand/rand_distr/src/exponential.rs
delete mode 100644 rand/rand_distr/src/gamma.rs
delete mode 100644 rand/rand_distr/src/lib.rs
delete mode 100644 rand/rand_distr/src/normal.rs
delete mode 100644 rand/rand_distr/src/pareto.rs
delete mode 100644 rand/rand_distr/src/pert.rs
delete mode 100644 rand/rand_distr/src/poisson.rs
delete mode 100644 rand/rand_distr/src/triangular.rs
delete mode 100644 rand/rand_distr/src/unit_ball.rs
delete mode 100644 rand/rand_distr/src/unit_circle.rs
delete mode 100644 rand/rand_distr/src/unit_disc.rs
delete mode 100644 rand/rand_distr/src/unit_sphere.rs
delete mode 100644 rand/rand_distr/src/utils.rs
delete mode 100644 rand/rand_distr/src/weibull.rs
delete mode 100644 rand/rand_distr/src/ziggurat_tables.rs
delete mode 100644 rand/rand_distr/tests/uniformity.rs
delete mode 100644 rand/rand_hc/CHANGELOG.md
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delete mode 100644 rand/rand_hc/LICENSE-APACHE
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delete mode 100644 rand/rand_hc/src/hc128.rs
delete mode 100644 rand/rand_hc/src/lib.rs
delete mode 100644 rand/rand_isaac/CHANGELOG.md
delete mode 100644 rand/rand_isaac/COPYRIGHT
delete mode 100644 rand/rand_isaac/Cargo.toml
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delete mode 100644 rand/rand_isaac/src/isaac.rs
delete mode 100644 rand/rand_isaac/src/isaac64.rs
delete mode 100644 rand/rand_isaac/src/isaac_array.rs
delete mode 100644 rand/rand_isaac/src/lib.rs
delete mode 100644 rand/rand_jitter/CHANGELOG.md
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delete mode 100644 rand/rand_jitter/src/error.rs
delete mode 100644 rand/rand_jitter/src/lib.rs
delete mode 100644 rand/rand_jitter/src/platform.rs
delete mode 100644 rand/rand_jitter/tests/mod.rs
delete mode 100644 rand/rand_os/CHANGELOG.md
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delete mode 100644 rand/rand_pcg/CHANGELOG.md
delete mode 100644 rand/rand_pcg/COPYRIGHT
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delete mode 100644 rand/rand_pcg/src/lib.rs
delete mode 100644 rand/rand_pcg/src/pcg128.rs
delete mode 100644 rand/rand_pcg/src/pcg64.rs
delete mode 100644 rand/rand_pcg/tests/lcg128xsl64.rs
delete mode 100644 rand/rand_pcg/tests/lcg64xsh32.rs
delete mode 100644 rand/rand_pcg/tests/mcg128xsl64.rs
delete mode 100644 rand/rand_xorshift/CHANGELOG.md
delete mode 100644 rand/rand_xorshift/COPYRIGHT
delete mode 100644 rand/rand_xorshift/Cargo.toml
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delete mode 100644 rand/rand_xoshiro/CHANGELOG.md
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delete mode 100644 rand/rand_xoshiro/src/common.rs
delete mode 100644 rand/rand_xoshiro/src/lib.rs
delete mode 100644 rand/rand_xoshiro/src/splitmix64.rs
delete mode 100644 rand/rand_xoshiro/src/xoroshiro128plus.rs
delete mode 100644 rand/rand_xoshiro/src/xoroshiro128starstar.rs
delete mode 100644 rand/rand_xoshiro/src/xoroshiro64star.rs
delete mode 100644 rand/rand_xoshiro/src/xoroshiro64starstar.rs
delete mode 100644 rand/rand_xoshiro/src/xoshiro128plus.rs
delete mode 100644 rand/rand_xoshiro/src/xoshiro128starstar.rs
delete mode 100644 rand/rand_xoshiro/src/xoshiro256plus.rs
delete mode 100644 rand/rand_xoshiro/src/xoshiro256starstar.rs
delete mode 100644 rand/rand_xoshiro/src/xoshiro512plus.rs
delete mode 100644 rand/rand_xoshiro/src/xoshiro512starstar.rs
delete mode 100644 rand/rand_xoshiro/tests/serde.rs
delete mode 100644 rand/rustfmt.toml
delete mode 100644 rand/src/distributions/bernoulli.rs
delete mode 100644 rand/src/distributions/binomial.rs
delete mode 100644 rand/src/distributions/cauchy.rs
delete mode 100644 rand/src/distributions/dirichlet.rs
delete mode 100644 rand/src/distributions/exponential.rs
delete mode 100644 rand/src/distributions/float.rs
delete mode 100644 rand/src/distributions/gamma.rs
delete mode 100644 rand/src/distributions/integer.rs
delete mode 100644 rand/src/distributions/mod.rs
delete mode 100644 rand/src/distributions/normal.rs
delete mode 100644 rand/src/distributions/other.rs
delete mode 100644 rand/src/distributions/pareto.rs
delete mode 100644 rand/src/distributions/poisson.rs
delete mode 100644 rand/src/distributions/triangular.rs
delete mode 100644 rand/src/distributions/uniform.rs
delete mode 100644 rand/src/distributions/unit_circle.rs
delete mode 100644 rand/src/distributions/unit_sphere.rs
delete mode 100644 rand/src/distributions/utils.rs
delete mode 100644 rand/src/distributions/weibull.rs
delete mode 100644 rand/src/distributions/weighted/alias_method.rs
delete mode 100644 rand/src/distributions/weighted/mod.rs
delete mode 100644 rand/src/distributions/ziggurat_tables.rs
delete mode 100644 rand/src/lib.rs
delete mode 100644 rand/src/prelude.rs
delete mode 100644 rand/src/rngs/adapter/mod.rs
delete mode 100644 rand/src/rngs/adapter/read.rs
delete mode 100644 rand/src/rngs/adapter/reseeding.rs
delete mode 100644 rand/src/rngs/entropy.rs
delete mode 100644 rand/src/rngs/mock.rs
delete mode 100644 rand/src/rngs/mod.rs
delete mode 100644 rand/src/rngs/small.rs
delete mode 100644 rand/src/rngs/std.rs
delete mode 100644 rand/src/rngs/thread.rs
delete mode 100644 rand/src/seq/index.rs
delete mode 100644 rand/src/seq/mod.rs
delete mode 100644 rand/tests/wasm_bindgen/Cargo.toml
delete mode 100644 rand/tests/wasm_bindgen/js/index.js
delete mode 100644 rand/tests/wasm_bindgen/src/lib.rs
delete mode 100644 rand/utils/ci/install.sh
delete mode 100755 rand/utils/ci/install_cargo_web.sh
delete mode 100644 rand/utils/ci/miri.sh
delete mode 100644 rand/utils/ci/script.sh
delete mode 100755 rand/utils/ziggurat_tables.py
(limited to 'rand')
diff --git a/rand/.github/ISSUE_TEMPLATE/compile-issue.md b/rand/.github/ISSUE_TEMPLATE/compile-issue.md
deleted file mode 100644
index 8a8354b..0000000
--- a/rand/.github/ISSUE_TEMPLATE/compile-issue.md
+++ /dev/null
@@ -1,16 +0,0 @@
----
-name: Compile issue
-about: Report / ask about a compilation issue
-title: ''
-labels: ''
-assignees: ''
-
----
-
-# Common issues
-
-**Problem**: `rand_hc::Hc128Rng: rand_core::SeedableRng` (or other RNG)
-
-**Quick solution**: `cargo update`
-
-**Details**: This happens when multiple versions of the `rand_core` crate are in use. Check your `Cargo.lock` file for all versions of `rand_core`. Note that some versions (0.2.2 and 0.3.1) are compatibility shims and are not a problem by themselves.
diff --git a/rand/.github/ISSUE_TEMPLATE/feature_request.md b/rand/.github/ISSUE_TEMPLATE/feature_request.md
deleted file mode 100644
index 90c57c8..0000000
--- a/rand/.github/ISSUE_TEMPLATE/feature_request.md
+++ /dev/null
@@ -1,18 +0,0 @@
----
-name: Feature request
-about: Suggest an idea for this project
-title: ''
-labels: ''
-assignees: ''
-
----
-
-## Background
-
-**What is your motivation?**
-
-**What type of application is this?** (E.g. cryptography, game, numerical simulation)
-
-## Feature request
-
-<details here>
diff --git a/rand/.github/ISSUE_TEMPLATE/other.md b/rand/.github/ISSUE_TEMPLATE/other.md
deleted file mode 100644
index a3e76ca..0000000
--- a/rand/.github/ISSUE_TEMPLATE/other.md
+++ /dev/null
@@ -1,10 +0,0 @@
----
-name: Other
-about: empty template
-title: ''
-labels: ''
-assignees: ''
-
----
-
-
diff --git a/rand/.gitignore b/rand/.gitignore
deleted file mode 100644
index ac38e81..0000000
--- a/rand/.gitignore
+++ /dev/null
@@ -1,4 +0,0 @@
-target
-Cargo.lock
-rand_wasm_bindgen_test*.[tj]s
-rand_wasm_bindgen_test*.wasm
diff --git a/rand/.travis.yml b/rand/.travis.yml
deleted file mode 100644
index f3790dc..0000000
--- a/rand/.travis.yml
+++ /dev/null
@@ -1,315 +0,0 @@
-language: rust
-sudo: false
-
-# We support too many combinations of Rust releases, crate features, operating
-# systems, and architectures to even remotely test all combinations.
-# Yet it turns out we can test most of these independent of each other, because
-# they serve different goals or test different pieces of code.
-#
-# RUST RELEASES
-# Goal: make sure we don't use language features unavailable on a certain
-# version, and build without warnings.
-# We have different builders use 4 Rust releases, a pinned stable release,
-# the latest stable, beta and nightly.
-#
-# ARCHITECTURES
-# Goal: test against issues caused by differences in endianness, pointer sizes,
-# etc.
-# We run tests on 4 different architectures.
-# - x64_84, default on Travis (Linux) and AppVeyor (Windows)
-# - i686, second AppVeyor (Windows) configuration
-# - MIPS, big-endian Linux emulated with QEMU (thanks to Trust)
-# - ARMv7, Android emulated with QEMU (thanks to Trust)
-#
-# OPERATING SYSTEMS
-# Goal: test on many operating systems, to verify the OsRng code, which is
-# mostly architecture-independent.
-# We run tests on Linux, OS X, Windows, Android (emulated), and Node.js (using
-# cargo-web).
-# One builder cross-compiles for many of the remaining OSes, which ensures we
-# keep building, but doesn't run tests.
-# OSes supported by Rand but which we can't cross-compile because there
-# is no pre-built standard library available: Dragonfly BSD, Haiku, OpenBSD.
-#
-# CRATE FEATURES, TESTS, AND SUB-CRATES
-# Goal: Run unit tests, doctests, examples, and test benchmarks for all crates,
-# in configurations that cover all interesting combinations of features.
-# Tests run on rand:
-# - test no_std support, but only the unit tests:
-# `cargo test --tests --no-default-features`
-# - test no_std support, including the alloc feature:
-# cargo test --tests --no-default-features --features=alloc
-# - run unit tests and doctests with all features which are available on stable:
-# `cargo test --features=serde1,log`
-# - test examples:
-# `cargo test --examples`
-# Additional tests on nightly:
-# - run unit tests and doctests with all features which are available on nightly:
-# `cargo test --all-features`
-# - run benchmarks as tests:
-# `cargo test --benches --features=nightly`
-# Tests on subcrates:
-# - select crates via --manifest-path (more reliable than --package)
-# - test appropriate feature matrix
-#
-# TODO: SIMD support on stable releases
-# NOTE: SIMD support is unreliable on nightly; we track the latest release
-# NOTE: Test for alloc feature in no_std is not included here because it depends
-# on the alloc crate stabilized in Rust 1.36.
-matrix:
- include:
- - rust: 1.32.0
- env: DESCRIPTION="Linux, 1.32.0"
- os: linux
- script:
- # Differs from standard script: rand_pcg features
- - cargo test --tests --no-default-features
- # TODO: add simd_support feature:
- - cargo test --features=serde1,log
- - cargo test --examples
- - cargo test --manifest-path rand_core/Cargo.toml
- - cargo test --manifest-path rand_core/Cargo.toml --no-default-features
- - cargo test --manifest-path rand_distr/Cargo.toml
- - cargo test --manifest-path rand_isaac/Cargo.toml --features=serde1
- # TODO: cannot test rand_pcg due to explicit dependency on i128
- - cargo test --manifest-path rand_xorshift/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xoshiro/Cargo.toml
- - cargo test --manifest-path rand_chacha/Cargo.toml
- - cargo test --manifest-path rand_hc/Cargo.toml
- - cargo test --manifest-path rand_jitter/Cargo.toml
- - cargo test --manifest-path rand_os/Cargo.toml
-
- - rust: 1.32.0
- env: DESCRIPTION="OSX, 1.32.0"
- os: osx
- script:
- # Differs from standard script: rand_pcg features
- - cargo test --tests --no-default-features
- # TODO: add simd_support feature:
- - cargo test --features=serde1,log
- - cargo test --examples
- - cargo test --manifest-path rand_core/Cargo.toml
- - cargo test --manifest-path rand_core/Cargo.toml --no-default-features
- - cargo test --manifest-path rand_distr/Cargo.toml
- - cargo test --manifest-path rand_isaac/Cargo.toml --features=serde1
- # TODO: cannot test rand_pcg due to explicit dependency on i128
- - cargo test --manifest-path rand_xorshift/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xoshiro/Cargo.toml
- - cargo test --manifest-path rand_chacha/Cargo.toml
- - cargo test --manifest-path rand_hc/Cargo.toml
- - cargo test --manifest-path rand_jitter/Cargo.toml
- - cargo test --manifest-path rand_os/Cargo.toml
-
- - rust: stable
- env: DESCRIPTION="Linux, stable"
-
- - rust: stable
- env: DESCRIPTION="OSX+iOS, stable"
- os: osx
- install:
- - rustup target add aarch64-apple-ios
- script:
- # Differs from standard script: includes aarch64-apple-ios cross-build
- - cargo test --tests --no-default-features
- # TODO: add simd_support feature:
- - cargo test --features=serde1,log
- - cargo test --examples
- - cargo test --manifest-path rand_core/Cargo.toml
- - cargo test --manifest-path rand_core/Cargo.toml --no-default-features
- - cargo test --manifest-path rand_distr/Cargo.toml
- - cargo test --manifest-path rand_isaac/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_pcg/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xorshift/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xoshiro/Cargo.toml
- - cargo test --manifest-path rand_chacha/Cargo.toml
- - cargo test --manifest-path rand_hc/Cargo.toml
- - cargo test --manifest-path rand_jitter/Cargo.toml
- - cargo test --manifest-path rand_os/Cargo.toml
- - cargo build --target=aarch64-apple-ios
-
- - rust: beta
- env: DESCRIPTION="Linux, beta"
-
- - rust: nightly
- os: linux
- env: DESCRIPTION="Linux, nightly, docs"
- install:
- - cargo --list | egrep "^\s*deadlinks$" -q || cargo install cargo-deadlinks
- - cargo deadlinks -V
- before_script:
- - pip install 'travis-cargo<0.2' --user && export PATH=$HOME/.local/bin:$PATH
- script:
- # Differs from standard script: all features, doc build
- - cargo test --tests --no-default-features --features=alloc
- - cargo test --all-features
- - cargo test --benches --features=nightly
- - cargo test --examples
- - cargo test --manifest-path rand_core/Cargo.toml
- - cargo test --manifest-path rand_core/Cargo.toml --no-default-features --features=alloc
- - cargo test --manifest-path rand_distr/Cargo.toml
- - cargo test --manifest-path rand_isaac/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_pcg/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xorshift/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xoshiro/Cargo.toml
- - cargo test --manifest-path rand_chacha/Cargo.toml
- - cargo test --manifest-path rand_hc/Cargo.toml
- - cargo test --manifest-path rand_jitter/Cargo.toml
- - cargo test --manifest-path rand_os/Cargo.toml
- # remove cached documentation, otherwise files from previous PRs can get included
- - rm -rf target/doc
- - cargo doc --no-deps --all --all-features
- - cargo deadlinks --dir target/doc
- after_success:
- - travis-cargo --only nightly doc-upload
-
- - rust: nightly
- os: osx
- env: DESCRIPTION="OSX, nightly, docs"
- install:
- - cargo --list | egrep "^\s*deadlinks$" -q || cargo install cargo-deadlinks
- - cargo deadlinks -V
- script:
- # Differs from standard script: all features, doc build
- - cargo test --tests --no-default-features --features=alloc
- - cargo test --all-features
- - cargo test --benches --features=nightly
- - cargo test --examples
- - cargo test --manifest-path rand_core/Cargo.toml
- - cargo test --manifest-path rand_core/Cargo.toml --no-default-features --features=alloc
- - cargo test --manifest-path rand_distr/Cargo.toml
- - cargo test --manifest-path rand_isaac/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_pcg/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xorshift/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xoshiro/Cargo.toml
- - cargo test --manifest-path rand_chacha/Cargo.toml
- - cargo test --manifest-path rand_hc/Cargo.toml
- - cargo test --manifest-path rand_jitter/Cargo.toml
- - cargo test --manifest-path rand_os/Cargo.toml
- # remove cached documentation, otherwise files from previous PRs can get included
- - rm -rf target/doc
- - cargo doc --no-deps --all --all-features
- - cargo deadlinks --dir target/doc
-
- - rust: nightly
- env: DESCRIPTION="WASM via emscripten, stdweb and wasm-bindgen"
- install:
- - rustup target add wasm32-unknown-unknown
- - rustup target add wasm32-unknown-emscripten
- - nvm install 9
- - ./utils/ci/install_cargo_web.sh
- - cargo web prepare-emscripten
- - cargo web -V
- - cargo list | grep install-update || cargo install -f cargo-update
- - cargo install-update -i cargo-update wasm-bindgen-cli wasm-pack
- addons:
- chrome: stable
- script:
- # Testing wasm32-unknown-emscripten fails because of rust-lang/rust#49877
- # However, we can still build and link all tests to make sure that works.
- # This is actually useful as it finds stuff such as rust-random/rand#669
- - EMCC_CFLAGS="-s ERROR_ON_UNDEFINED_SYMBOLS=0" cargo web test --target wasm32-unknown-emscripten --no-run
- #- cargo web test --target wasm32-unknown-emscripten
- #- cargo web test --nodejs --target wasm32-unknown-emscripten
- #- cargo build --target wasm32-unknown-unknown # without any features
- - cargo build --target wasm32-unknown-unknown --features=wasm-bindgen
- - cargo web test --target wasm32-unknown-unknown --features=stdweb
- - cargo build --manifest-path tests/wasm_bindgen/Cargo.toml --target wasm32-unknown-unknown
- - wasm-bindgen --nodejs target/wasm32-unknown-unknown/debug/rand_wasm_bindgen_test.wasm --out-dir tests/wasm_bindgen/js
- - node tests/wasm_bindgen/js/index.js
- - wasm-pack test --node tests/wasm_bindgen
-
- - rust: nightly
- env: DESCRIPTION="cross-platform builder (doesn't run tests)"
- install:
- - rustup target add x86_64-sun-solaris
- - rustup target add x86_64-unknown-cloudabi
- - rustup target add x86_64-unknown-freebsd
- #- rustup target add x86_64-unknown-fuchsia
- - rustup target add x86_64-unknown-netbsd
- - rustup target add x86_64-unknown-redox
- script:
- # Test the top-level crate with all features:
- - cargo build --target=x86_64-sun-solaris --all-features
- - cargo build --target=x86_64-unknown-cloudabi --all-features
- - cargo build --target=x86_64-unknown-freebsd --all-features
- #- cargo build --target=x86_64-unknown-fuchsia --all-features
- - cargo build --target=x86_64-unknown-netbsd --all-features
- - cargo build --target=x86_64-unknown-redox --all-features
-
- # Trust cross-built/emulated targets. We must repeat all non-default values.
- - rust: stable
- sudo: required
- dist: trusty
- services: docker
- env: DESCRIPTION="Linux (MIPS, big-endian)" TARGET=mips-unknown-linux-gnu
- install:
- - sh utils/ci/install.sh
- - source ~/.cargo/env || true
- script:
- - bash utils/ci/script.sh
- - rust: stable
- sudo: required
- dist: trusty
- services: docker
- env: DESCRIPTION="Android (ARMv7)" TARGET=armv7-linux-androideabi
- install:
- - sh utils/ci/install.sh
- - source ~/.cargo/env || true
- script:
- - bash utils/ci/script.sh
- - rust: nightly
- env: DESCRIPTION="no_std platform test"
- install:
- - rustup target add thumbv6m-none-eabi
- script:
- # Test the top-level crate with all features:
- - cargo build --target=thumbv6m-none-eabi --no-default-features
-
- - rust: nightly
- os: linux
- env: DESCRIPTION="Miri, nightly"
- script:
- - sh utils/ci/miri.sh
-
-before_install:
- - set -e
- - rustup self update
-
-script:
- - cargo test --tests --no-default-features
- - cargo test --tests --no-default-features --features getrandom
- - cargo test --tests --no-default-features --features=alloc
- # TODO: add simd_support feature:
- - cargo test --features=serde1,log
- - cargo test --examples
- - cargo test --manifest-path rand_core/Cargo.toml
- - cargo test --manifest-path rand_core/Cargo.toml --no-default-features
- - cargo test --manifest-path rand_core/Cargo.toml --no-default-features --features=alloc
- - cargo test --manifest-path rand_distr/Cargo.toml
- - cargo test --manifest-path rand_isaac/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_pcg/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xorshift/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xoshiro/Cargo.toml
- - cargo test --manifest-path rand_chacha/Cargo.toml
- - cargo test --manifest-path rand_hc/Cargo.toml
- - cargo test --manifest-path rand_jitter/Cargo.toml
- - cargo test --manifest-path rand_os/Cargo.toml
-
-after_script: set +e
-
-cache:
- cargo: true
- directories:
- - .local/share/cargo-web
-
-before_cache:
- # Travis can't cache files that are not readable by "others"
- - chmod -R a+r $HOME/.cargo
-
-env:
- global:
- secure: "BdDntVHSompN+Qxz5Rz45VI4ZqhD72r6aPl166FADlnkIwS6N6FLWdqs51O7G5CpoMXEDvyYrjmRMZe/GYLIG9cmqmn/wUrWPO+PauGiIuG/D2dmfuUNvSTRcIe7UQLXrfP3yyfZPgqsH6pSnNEVopquQKy3KjzqepgriOJtbyY="
-
-notifications:
- email:
- on_success: never
diff --git a/rand/CHANGELOG.md b/rand/CHANGELOG.md
deleted file mode 100644
index a2ae496..0000000
--- a/rand/CHANGELOG.md
+++ /dev/null
@@ -1,568 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-A [separate changelog is kept for rand_core](rand_core/CHANGELOG.md).
-
-You may also find the [Upgrade Guide](https://rust-random.github.io/book/update.html) useful.
-
-## [Unreleased]
-- Fix `no_std` behaviour, appropriately enable c2-chacha's `std` feature (#844)
-- Add a `no_std` target to CI to continously evaluate `no_std` status (#844)
-- `alloc` feature in `no_std` is available since Rust 1.36 (#856)
-
-## [0.7.0] - 2019-06-28
-
-### Fixes
-- Fix incorrect pointer usages revealed by Miri testing (#780, #781)
-- Fix (tiny!) bias in `Uniform` for 8- and 16-bit ints (#809)
-
-### Crate
-- Bumped MSRV (min supported Rust version) to 1.32.0
-- Updated to Rust Edition 2018 (#823, #824)
-- Removed dependence on `rand_xorshift`, `rand_isaac`, `rand_jitter` crates (#759, #765)
-- Remove dependency on `winapi` (#724)
-- Removed all `build.rs` files (#824)
-- Removed code already deprecated in version 0.6 (#757)
-- Removed the serde1 feature (It's still available for backwards compatibility, but it does not do anything. #830)
-- Many documentation changes
-
-### rand_core
-- Updated to `rand_core` 0.5.0
-- `Error` type redesigned with new API (#800)
-- Move `from_entropy` method to `SeedableRng` and remove `FromEntropy` (#800)
-- `SeedableRng::from_rng` is now expected to be value-stable (#815)
-
-### Standard RNGs
-- OS interface moved from `rand_os` to new `getrandom` crate (#765, [getrandom](https://github.com/rust-random/getrandom))
-- Use ChaCha for `StdRng` and `ThreadRng` (#792)
-- Feature-gate `SmallRng` (#792)
-- `ThreadRng` now supports `Copy` (#758)
-- Deprecated `EntropyRng` (#765)
-- Enable fork protection of ReseedingRng without `std` (#724)
-
-### Distributions
-- Many distributions have been moved to `rand_distr` (#761)
-- `Bernoulli::new` constructor now returns a `Result` (#803)
-- `Distribution::sample_iter` adjusted for more flexibility (#758)
-- Added `distributions::weighted::alias_method::WeightedIndex` for `O(1)` sampling (#692)
-- Support sampling `NonZeroU*` types with the `Standard` distribution (#728)
-- Optimised `Binomial` distribution sampling (#735, #740, #752)
-- Optimised SIMD float sampling (#739)
-
-### Sequences
-- Make results portable across 32- and 64-bit by using `u32` samples for `usize` where possible (#809)
-
-## [0.6.5] - 2019-01-28
-### Crates
-- Update `rand_core` to 0.4 (#703)
-- Move `JitterRng` to its own crate (#685)
-- Add a wasm-bindgen test crate (#696)
-
-### Platforms
-- Fuchsia: Replaced fuchsia-zircon with fuchsia-cprng
-
-### Doc
-- Use RFC 1946 for doc links (#691)
-- Fix some doc links and notes (#711)
-
-## [0.6.4] - 2019-01-08
-### Fixes
-- Move wasm-bindgen shims to correct crate (#686)
-- Make `wasm32-unknown-unknown` compile but fail at run-time if missing bindingsg (#686)
-
-## [0.6.3] - 2019-01-04
-### Fixes
-- Make the `std` feature require the optional `rand_os` dependency (#675)
-- Re-export the optional WASM dependencies of `rand_os` from `rand` to avoid breakage (#674)
-
-## [0.6.2] - 2019-01-04
-### Additions
-- Add `Default` for `ThreadRng` (#657)
-- Move `rngs::OsRng` to `rand_os` sub-crate; clean up code; use as dependency (#643) ##BLOCKER##
-- Add `rand_xoshiro` sub-crate, plus benchmarks (#642, #668)
-
-### Fixes
-- Fix bias in `UniformInt::sample_single` (#662)
-- Use `autocfg` instead of `rustc_version` for rustc version detection (#664)
-- Disable `i128` and `u128` if the `target_os` is `emscripten` (#671: work-around Emscripten limitation)
-- CI fixes (#660, #671)
-
-### Optimisations
-- Optimise memory usage of `UnitCircle` and `UnitSphereSurface` distributions (no PR)
-
-## [0.6.1] - 2018-11-22
-- Support sampling `Duration` also for `no_std` (only since Rust 1.25) (#649)
-- Disable default features of `libc` (#647)
-
-## [0.6.0] - 2018-11-14
-
-### Project organisation
-- Rand has moved from [rust-lang-nursery](https://github.com/rust-lang-nursery/rand)
- to [rust-random](https://github.com/rust-random/rand)! (#578)
-- Created [The Rust Random Book](https://rust-random.github.io/book/)
- ([source](https://github.com/rust-random/book))
-- Update copyright and licence notices (#591, #611)
-- Migrate policy documentation from the wiki (#544)
-
-### Platforms
-- Add fork protection on Unix (#466)
-- Added support for wasm-bindgen. (#541, #559, #562, #600)
-- Enable `OsRng` for powerpc64, sparc and sparc64 (#609)
-- Use `syscall` from `libc` on Linux instead of redefining it (#629)
-
-### RNGs
-- Switch `SmallRng` to use PCG (#623)
-- Implement `Pcg32` and `Pcg64Mcg` generators (#632)
-- Move ISAAC RNGs to a dedicated crate (#551)
-- Move Xorshift RNG to its own crate (#557)
-- Move ChaCha and HC128 RNGs to dedicated crates (#607, #636)
-- Remove usage of `Rc` from `ThreadRng` (#615)
-
-### Sampling and distributions
-- Implement `Rng.gen_ratio()` and `Bernoulli::new_ratio()` (#491)
-- Make `Uniform` strictly respect `f32` / `f64` high/low bounds (#477)
-- Allow `gen_range` and `Uniform` to work on non-`Copy` types (#506)
-- `Uniform` supports inclusive ranges: `Uniform::from(a..=b)`. This is
- automatically enabled for Rust >= 1.27. (#566)
-- Implement `TrustedLen` and `FusedIterator` for `DistIter` (#620)
-
-#### New distributions
-- Add the `Dirichlet` distribution (#485)
-- Added sampling from the unit sphere and circle. (#567)
-- Implement the triangular distribution (#575)
-- Implement the Weibull distribution (#576)
-- Implement the Beta distribution (#574)
-
-#### Optimisations
-
-- Optimise `Bernoulli::new` (#500)
-- Optimise `char` sampling (#519)
-- Optimise sampling of `std::time::Duration` (#583)
-
-### Sequences
-- Redesign the `seq` module (#483, #515)
-- Add `WeightedIndex` and `choose_weighted` (#518, #547)
-- Optimised and changed return type of the `sample_indices` function. (#479)
-- Use `Iterator::size_hint()` to speed up `IteratorRandom::choose` (#593)
-
-### SIMD
-- Support for generating SIMD types (#523, #542, #561, #630)
-
-### Other
-- Revise CI scripts (#632, #635)
-- Remove functionality already deprecated in 0.5 (#499)
-- Support for `i128` and `u128` is automatically enabled for Rust >= 1.26. This
- renders the `i128_support` feature obsolete. It still exists for backwards
- compatibility but does not have any effect. This breaks programs using Rand
- with `i128_support` on nightlies older than Rust 1.26. (#571)
-
-
-## [0.5.5] - 2018-08-07
-### Documentation
-- Fix links in documentation (#582)
-
-
-## [0.5.4] - 2018-07-11
-### Platform support
-- Make `OsRng` work via WASM/stdweb for WebWorkers
-
-
-## [0.5.3] - 2018-06-26
-### Platform support
-- OpenBSD, Bitrig: fix compilation (broken in 0.5.1) (#530)
-
-
-## [0.5.2] - 2018-06-18
-### Platform support
-- Hide `OsRng` and `JitterRng` on unsupported platforms (#512; fixes #503).
-
-
-## [0.5.1] - 2018-06-08
-
-### New distributions
-- Added Cauchy distribution. (#474, #486)
-- Added Pareto distribution. (#495)
-
-### Platform support and `OsRng`
-- Remove blanket Unix implementation. (#484)
-- Remove Wasm unimplemented stub. (#484)
-- Dragonfly BSD: read from `/dev/random`. (#484)
-- Bitrig: use `getentropy` like OpenBSD. (#484)
-- Solaris: (untested) use `getrandom` if available, otherwise `/dev/random`. (#484)
-- Emscripten, `stdweb`: split the read up in chunks. (#484)
-- Emscripten, Haiku: don't do an extra blocking read from `/dev/random`. (#484)
-- Linux, NetBSD, Solaris: read in blocking mode on first use in `fill_bytes`. (#484)
-- Fuchsia, CloudABI: fix compilation (broken in Rand 0.5). (#484)
-
-
-## [0.5.0] - 2018-05-21
-
-### Crate features and organisation
-- Minimum Rust version update: 1.22.0. (#239)
-- Create a separate `rand_core` crate. (#288)
-- Deprecate `rand_derive`. (#256)
-- Add `prelude` (and module reorganisation). (#435)
-- Add `log` feature. Logging is now available in `JitterRng`, `OsRng`, `EntropyRng` and `ReseedingRng`. (#246)
-- Add `serde1` feature for some PRNGs. (#189)
-- `stdweb` feature for `OsRng` support on WASM via stdweb. (#272, #336)
-
-### `Rng` trait
-- Split `Rng` in `RngCore` and `Rng` extension trait.
- `next_u32`, `next_u64` and `fill_bytes` are now part of `RngCore`. (#265)
-- Add `Rng::sample`. (#256)
-- Deprecate `Rng::gen_weighted_bool`. (#308)
-- Add `Rng::gen_bool`. (#308)
-- Remove `Rng::next_f32` and `Rng::next_f64`. (#273)
-- Add optimized `Rng::fill` and `Rng::try_fill` methods. (#247)
-- Deprecate `Rng::gen_iter`. (#286)
-- Deprecate `Rng::gen_ascii_chars`. (#279)
-
-### `rand_core` crate
-- `rand` now depends on new `rand_core` crate (#288)
-- `RngCore` and `SeedableRng` are now part of `rand_core`. (#288)
-- Add modules to help implementing RNGs `impl` and `le`. (#209, #228)
-- Add `Error` and `ErrorKind`. (#225)
-- Add `CryptoRng` marker trait. (#273)
-- Add `BlockRngCore` trait. (#281)
-- Add `BlockRng` and `BlockRng64` wrappers to help implementations. (#281, #325)
-- Revise the `SeedableRng` trait. (#233)
-- Remove default implementations for `RngCore::next_u64` and `RngCore::fill_bytes`. (#288)
-- Add `RngCore::try_fill_bytes`. (#225)
-
-### Other traits and types
-- Add `FromEntropy` trait. (#233, #375)
-- Add `SmallRng` wrapper. (#296)
-- Rewrite `ReseedingRng` to only work with `BlockRngCore` (substantial performance improvement). (#281)
-- Deprecate `weak_rng`. Use `SmallRng` instead. (#296)
-- Deprecate `AsciiGenerator`. (#279)
-
-### Random number generators
-- Switch `StdRng` and `thread_rng` to HC-128. (#277)
-- `StdRng` must now be created with `from_entropy` instead of `new`
-- Change `thread_rng` reseeding threshold to 32 MiB. (#277)
-- PRNGs no longer implement `Copy`. (#209)
-- `Debug` implementations no longer show internals. (#209)
-- Implement `Clone` for `ReseedingRng`, `JitterRng`, OsRng`. (#383, #384)
-- Implement serialization for `XorShiftRng`, `IsaacRng` and `Isaac64Rng` under the `serde1` feature. (#189)
-- Implement `BlockRngCore` for `ChaChaCore` and `Hc128Core`. (#281)
-- All PRNGs are now portable across big- and little-endian architectures. (#209)
-- `Isaac64Rng::next_u32` no longer throws away half the results. (#209)
-- Add `IsaacRng::new_from_u64` and `Isaac64Rng::new_from_u64`. (#209)
-- Add the HC-128 CSPRNG `Hc128Rng`. (#210)
-- Change ChaCha20 to have 64-bit counter and 64-bit stream. (#349)
-- Changes to `JitterRng` to get its size down from 2112 to 24 bytes. (#251)
-- Various performance improvements to all PRNGs.
-
-### Platform support and `OsRng`
-- Add support for CloudABI. (#224)
-- Remove support for NaCl. (#225)
-- WASM support for `OsRng` via stdweb, behind the `stdweb` feature. (#272, #336)
-- Use `getrandom` on more platforms for Linux, and on Android. (#338)
-- Use the `SecRandomCopyBytes` interface on macOS. (#322)
-- On systems that do not have a syscall interface, only keep a single file descriptor open for `OsRng`. (#239)
-- On Unix, first try a single read from `/dev/random`, then `/dev/urandom`. (#338)
-- Better error handling and reporting in `OsRng` (using new error type). (#225)
-- `OsRng` now uses non-blocking when available. (#225)
-- Add `EntropyRng`, which provides `OsRng`, but has `JitterRng` as a fallback. (#235)
-
-### Distributions
-- New `Distribution` trait. (#256)
-- Add `Distribution::sample_iter` and `Rng::::sample_iter`. (#361)
-- Deprecate `Rand`, `Sample` and `IndependentSample` traits. (#256)
-- Add a `Standard` distribution (replaces most `Rand` implementations). (#256)
-- Add `Binomial` and `Poisson` distributions. (#96)
-- Add `Bernoulli` dsitribution. (#411)
-- Add `Alphanumeric` distribution. (#279)
-- Remove `Closed01` distribution, add `OpenClosed01`. (#274, #420)
-- Rework `Range` type, making it possible to implement it for user types. (#274)
-- Rename `Range` to `Uniform`. (#395)
-- Add `Uniform::new_inclusive` for inclusive ranges. (#274)
-- Use widening multiply method for much faster integer range reduction. (#274)
-- `Standard` distribution for `char` uses `Uniform` internally. (#274)
-- `Standard` distribution for `bool` uses sign test. (#274)
-- Implement `Standard` distribution for `Wrapping<T>`. (#436)
-- Implement `Uniform` distribution for `Duration`. (#427)
-
-
-## [0.4.3] - 2018-08-16
-### Fixed
-- Use correct syscall number for PowerPC (#589)
-
-
-## [0.4.2] - 2018-01-06
-### Changed
-- Use `winapi` on Windows
-- Update for Fuchsia OS
-- Remove dev-dependency on `log`
-
-
-## [0.4.1] - 2017-12-17
-### Added
-- `no_std` support
-
-
-## [0.4.0-pre.0] - 2017-12-11
-### Added
-- `JitterRng` added as a high-quality alternative entropy source using the
- system timer
-- new `seq` module with `sample_iter`, `sample_slice`, etc.
-- WASM support via dummy implementations (fail at run-time)
-- Additional benchmarks, covering generators and new seq code
-
-### Changed
-- `thread_rng` uses `JitterRng` if seeding from system time fails
- (slower but more secure than previous method)
-
-### Deprecated
- - `sample` function deprecated (replaced by `sample_iter`)
-
-
-## [0.3.20] - 2018-01-06
-### Changed
-- Remove dev-dependency on `log`
-- Update `fuchsia-zircon` dependency to 0.3.2
-
-
-## [0.3.19] - 2017-12-27
-### Changed
-- Require `log <= 0.3.8` for dev builds
-- Update `fuchsia-zircon` dependency to 0.3
-- Fix broken links in docs (to unblock compiler docs testing CI)
-
-
-## [0.3.18] - 2017-11-06
-### Changed
-- `thread_rng` is seeded from the system time if `OsRng` fails
-- `weak_rng` now uses `thread_rng` internally
-
-
-## [0.3.17] - 2017-10-07
-### Changed
- - Fuchsia: Magenta was renamed Zircon
-
-## [0.3.16] - 2017-07-27
-### Added
-- Implement Debug for mote non-public types
-- implement `Rand` for (i|u)i128
-- Support for Fuchsia
-
-### Changed
-- Add inline attribute to SampleRange::construct_range.
- This improves the benchmark for sample in 11% and for shuffle in 16%.
-- Use `RtlGenRandom` instead of `CryptGenRandom`
-
-
-## [0.3.15] - 2016-11-26
-### Added
-- Add `Rng` trait method `choose_mut`
-- Redox support
-
-### Changed
-- Use `arc4rand` for `OsRng` on FreeBSD.
-- Use `arc4random(3)` for `OsRng` on OpenBSD.
-
-### Fixed
-- Fix filling buffers 4 GiB or larger with `OsRng::fill_bytes` on Windows
-
-
-## [0.3.14] - 2016-02-13
-### Fixed
-- Inline definitions from winapi/advapi32, wich decreases build times
-
-
-## [0.3.13] - 2016-01-09
-### Fixed
-- Compatible with Rust 1.7.0-nightly (needed some extra type annotations)
-
-
-## [0.3.12] - 2015-11-09
-### Changed
-- Replaced the methods in `next_f32` and `next_f64` with the technique described
- Saito & Matsumoto at MCQMC'08. The new method should exhibit a slightly more
- uniform distribution.
-- Depend on libc 0.2
-
-### Fixed
-- Fix iterator protocol issue in `rand::sample`
-
-
-## [0.3.11] - 2015-08-31
-### Added
-- Implement `Rand` for arrays with n <= 32
-
-
-## [0.3.10] - 2015-08-17
-### Added
-- Support for NaCl platforms
-
-### Changed
-- Allow `Rng` to be `?Sized`, impl for `&mut R` and `Box<R>` where `R: ?Sized + Rng`
-
-
-## [0.3.9] - 2015-06-18
-### Changed
-- Use `winapi` for Windows API things
-
-### Fixed
-- Fixed test on stable/nightly
-- Fix `getrandom` syscall number for aarch64-unknown-linux-gnu
-
-
-## [0.3.8] - 2015-04-23
-### Changed
-- `log` is a dev dependency
-
-### Fixed
-- Fix race condition of atomics in `is_getrandom_available`
-
-
-## [0.3.7] - 2015-04-03
-### Fixed
-- Derive Copy/Clone changes
-
-
-## [0.3.6] - 2015-04-02
-### Changed
-- Move to stable Rust!
-
-
-## [0.3.5] - 2015-04-01
-### Fixed
-- Compatible with Rust master
-
-
-## [0.3.4] - 2015-03-31
-### Added
-- Implement Clone for `Weighted`
-
-### Fixed
-- Compatible with Rust master
-
-
-## [0.3.3] - 2015-03-26
-### Fixed
-- Fix compile on Windows
-
-
-## [0.3.2] - 2015-03-26
-
-
-## [0.3.1] - 2015-03-26
-### Fixed
-- Fix compile on Windows
-
-
-## [0.3.0] - 2015-03-25
-### Changed
-- Update to use log version 0.3.x
-
-
-## [0.2.1] - 2015-03-22
-### Fixed
-- Compatible with Rust master
-- Fixed iOS compilation
-
-
-## [0.2.0] - 2015-03-06
-### Fixed
-- Compatible with Rust master (move from `old_io` to `std::io`)
-
-
-## [0.1.4] - 2015-03-04
-### Fixed
-- Compatible with Rust master (use wrapping ops)
-
-
-## [0.1.3] - 2015-02-20
-### Fixed
-- Compatible with Rust master
-
-### Removed
-- Removed Copy implementations from RNGs
-
-
-## [0.1.2] - 2015-02-03
-### Added
-- Imported functionality from `std::rand`, including:
- - `StdRng`, `SeedableRng`, `TreadRng`, `weak_rng()`
- - `ReaderRng`: A wrapper around any Reader to treat it as an RNG.
-- Imported documentation from `std::rand`
-- Imported tests from `std::rand`
-
-
-## [0.1.1] - 2015-02-03
-### Added
-- Migrate to a cargo-compatible directory structure.
-
-### Fixed
-- Do not use entropy during `gen_weighted_bool(1)`
-
-
-## [Rust 0.12.0] - 2014-10-09
-### Added
-- Impl Rand for tuples of arity 11 and 12
-- Include ChaCha pseudorandom generator
-- Add `next_f64` and `next_f32` to Rng
-- Implement Clone for PRNGs
-
-### Changed
-- Rename `TaskRng` to `ThreadRng` and `task_rng` to `thread_rng` (since a
- runtime is removed from Rust).
-
-### Fixed
-- Improved performance of ISAAC and ISAAC64 by 30% and 12 % respectively, by
- informing the optimiser that indexing is never out-of-bounds.
-
-### Removed
-- Removed the Deprecated `choose_option`
-
-
-## [Rust 0.11.0] - 2014-07-02
-### Added
-- document when to use `OSRng` in cryptographic context, and explain why we use `/dev/urandom` instead of `/dev/random`
-- `Rng::gen_iter()` which will return an infinite stream of random values
-- `Rng::gen_ascii_chars()` which will return an infinite stream of random ascii characters
-
-### Changed
-- Now only depends on libcore!
-- Remove `Rng.choose()`, rename `Rng.choose_option()` to `.choose()`
-- Rename OSRng to OsRng
-- The WeightedChoice structure is no longer built with a `Vec<Weighted<T>>`,
- but rather a `&mut [Weighted<T>]`. This means that the WeightedChoice
- structure now has a lifetime associated with it.
-- The `sample` method on `Rng` has been moved to a top-level function in the
- `rand` module due to its dependence on `Vec`.
-
-### Removed
-- `Rng::gen_vec()` was removed. Previous behavior can be regained with
- `rng.gen_iter().take(n).collect()`
-- `Rng::gen_ascii_str()` was removed. Previous behavior can be regained with
- `rng.gen_ascii_chars().take(n).collect()`
-- {IsaacRng, Isaac64Rng, XorShiftRng}::new() have all been removed. These all
- relied on being able to use an OSRng for seeding, but this is no longer
- available in librand (where these types are defined). To retain the same
- functionality, these types now implement the `Rand` trait so they can be
- generated with a random seed from another random number generator. This allows
- the stdlib to use an OSRng to create seeded instances of these RNGs.
-- Rand implementations for `Box<T>` and `@T` were removed. These seemed to be
- pretty rare in the codebase, and it allows for librand to not depend on
- liballoc. Additionally, other pointer types like Rc<T> and Arc<T> were not
- supported.
-- Remove a slew of old deprecated functions
-
-
-## [Rust 0.10] - 2014-04-03
-### Changed
-- replace `Rng.shuffle's` functionality with `.shuffle_mut`
-- bubble up IO errors when creating an OSRng
-
-### Fixed
-- Use `fill()` instead of `read()`
-- Rewrite OsRng in Rust for windows
-
-## [0.10-pre] - 2014-03-02
-### Added
-- Seperate `rand` out of the standard library
diff --git a/rand/COPYRIGHT b/rand/COPYRIGHT
deleted file mode 100644
index 468d907..0000000
--- a/rand/COPYRIGHT
+++ /dev/null
@@ -1,12 +0,0 @@
-Copyrights in the Rand project are retained by their contributors. No
-copyright assignment is required to contribute to the Rand project.
-
-For full authorship information, see the version control history.
-
-Except as otherwise noted (below and/or in individual files), Rand is
-licensed under the Apache License, Version 2.0 <LICENSE-APACHE> or
-<http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-<LICENSE-MIT> or <http://opensource.org/licenses/MIT>, at your option.
-
-The Rand project includes code from the Rust project
-published under these same licenses.
diff --git a/rand/Cargo.toml b/rand/Cargo.toml
deleted file mode 100644
index ef344a6..0000000
--- a/rand/Cargo.toml
+++ /dev/null
@@ -1,90 +0,0 @@
-[package]
-name = "rand"
-version = "0.7.0"
-authors = ["The Rand Project Developers", "The Rust Project Developers"]
-license = "MIT OR Apache-2.0"
-readme = "README.md"
-repository = "https://github.com/rust-random/rand"
-documentation = "https://rust-random.github.io/rand/"
-homepage = "https://crates.io/crates/rand"
-description = """
-Random number generators and other randomness functionality.
-"""
-keywords = ["random", "rng"]
-categories = ["algorithms", "no-std"]
-exclude = ["/utils/*", "/.travis.yml", "/appveyor.yml", ".gitignore"]
-autobenches = true
-edition = "2018"
-
-[badges]
-travis-ci = { repository = "rust-random/rand" }
-appveyor = { repository = "rust-random/rand" }
-
-[features]
-# Meta-features:
-default = ["std"] # without "std" rand uses libcore
-nightly = ["simd_support"] # enables all features requiring nightly rust
-serde1 = [] # does nothing, deprecated
-
-# Optional dependencies:
-std = ["rand_core/std", "rand_chacha/std", "alloc", "getrandom"]
-alloc = ["rand_core/alloc"] # enables Vec and Box support (without std)
-# re-export optional WASM dependencies to avoid breakage:
-wasm-bindgen = ["getrandom_package/wasm-bindgen"]
-stdweb = ["getrandom_package/stdweb"]
-getrandom = ["getrandom_package", "rand_core/getrandom"]
-
-# Configuration:
-simd_support = ["packed_simd"] # enables SIMD support
-small_rng = ["rand_pcg"] # enables SmallRng
-
-[workspace]
-members = [
- "rand_core",
- "rand_distr",
- "rand_jitter",
- "rand_os",
- "rand_isaac",
- "rand_chacha",
- "rand_hc",
- "rand_pcg",
- "rand_xorshift",
- "rand_xoshiro",
- "tests/wasm_bindgen",
-]
-
-[dependencies]
-rand_core = { path = "rand_core", version = "0.5" }
-rand_pcg = { path = "rand_pcg", version = "0.2", optional = true }
-# Do not depend on 'getrandom_package' directly; use the 'getrandom' feature!
-getrandom_package = { version = "0.1.1", package = "getrandom", optional = true }
-log = { version = "0.4", optional = true }
-
-[dependencies.packed_simd]
-# NOTE: so far no version works reliably due to dependence on unstable features
-version = "0.3"
-# git = "https://github.com/rust-lang-nursery/packed_simd"
-optional = true
-features = ["into_bits"]
-
-[target.'cfg(unix)'.dependencies]
-# Used for fork protection (reseeding.rs)
-libc = { version = "0.2.22", default-features = false }
-
-# Emscripten does not support 128-bit integers, which are used by ChaCha code.
-# We work around this by using a different RNG.
-[target.'cfg(not(target_os = "emscripten"))'.dependencies]
-rand_chacha = { path = "rand_chacha", version = "0.2.1", default-features = false }
-[target.'cfg(target_os = "emscripten")'.dependencies]
-rand_hc = { path = "rand_hc", version = "0.2" }
-
-[dev-dependencies]
-rand_pcg = { path = "rand_pcg", version = "0.2" }
-# Only for benches:
-rand_hc = { path = "rand_hc", version = "0.2" }
-rand_xoshiro = { path = "rand_xoshiro", version = "0.3" }
-rand_isaac = { path = "rand_isaac", version = "0.2" }
-rand_xorshift = { path = "rand_xorshift", version = "0.2" }
-
-[package.metadata.docs.rs]
-all-features = true
diff --git a/rand/LICENSE-APACHE b/rand/LICENSE-APACHE
deleted file mode 100644
index 17d7468..0000000
--- a/rand/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
- Apache License
- Version 2.0, January 2004
- https://www.apache.org/licenses/
-
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-
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diff --git a/rand/LICENSE-MIT b/rand/LICENSE-MIT
deleted file mode 100644
index d93b5ba..0000000
--- a/rand/LICENSE-MIT
+++ /dev/null
@@ -1,26 +0,0 @@
-Copyright 2018 Developers of the Rand project
-Copyright (c) 2014 The Rust Project Developers
-
-Permission is hereby granted, free of charge, to any
-person obtaining a copy of this software and associated
-documentation files (the "Software"), to deal in the
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-The above copyright notice and this permission notice
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-TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
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-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
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diff --git a/rand/README.md b/rand/README.md
deleted file mode 100644
index 5acbadb..0000000
--- a/rand/README.md
+++ /dev/null
@@ -1,118 +0,0 @@
-# Rand
-
-[](https://travis-ci.org/rust-random/rand)
-[](https://ci.appveyor.com/project/rust-random/rand)
-[](https://crates.io/crates/rand)
-[](https://rust-random.github.io/book/)
-[](https://rust-random.github.io/rand)
-[](https://docs.rs/rand)
-[](https://github.com/rust-random/rand#rust-version-requirements)
-
-A Rust library for random number generation.
-
-Rand provides utilities to generate random numbers, to convert them to useful
-types and distributions, and some randomness-related algorithms.
-
-The core random number generation traits of Rand live in the [rand_core](
-https://crates.io/crates/rand_core) crate but are also exposed here; RNG
-implementations should prefer to use `rand_core` while most other users should
-depend on `rand`.
-
-Documentation:
-- [The Rust Rand Book](https://rust-random.github.io/book)
-- [API reference (master)](https://rust-random.github.io/rand)
-- [API reference (docs.rs)](https://docs.rs/rand)
-
-
-## Usage
-
-Add this to your `Cargo.toml`:
-
-```toml
-[dependencies]
-rand = "0.7"
-```
-
-To get started using Rand, see [The Book](https://rust-random.github.io/book).
-
-
-## Versions
-
-Rand libs have inter-dependencies and make use of the
-[semver trick](https://github.com/dtolnay/semver-trick/) in order to make traits
-compatible across crate versions. (This is especially important for `RngCore`
-and `SeedableRng`.) A few crate releases are thus compatibility shims,
-depending on the *next* lib version (e.g. `rand_core` versions `0.2.2` and
-`0.3.1`). This means, for example, that `rand_core_0_4_0::SeedableRng` and
-`rand_core_0_3_0::SeedableRng` are distinct, incompatible traits, which can
-cause build errors. Usually, running `cargo update` is enough to fix any issues.
-
-The Rand lib is not yet stable, however we are careful to limit breaking changes
-and warn via deprecation wherever possible. Patch versions never introduce
-breaking changes. The following minor versions are supported:
-
-- Version 0.7 was released in June 2019, moving most non-uniform distributions
- to an external crate, moving `from_entropy` to `SeedableRng`, and many small
- changes and fixes.
-- Version 0.6 was released in November 2018, redesigning the `seq` module,
- moving most PRNGs to external crates, and many small changes.
-- Version 0.5 was released in May 2018, as a major reorganisation
- (introducing `RngCore` and `rand_core`, and deprecating `Rand` and the
- previous distribution traits).
-- Version 0.4 was released in December 2017, but contained almost no breaking
- changes from the 0.3 series.
-
-A detailed [changelog](CHANGELOG.md) is available.
-
-When upgrading to the next minor series (especially 0.4 β 0.5), we recommend
-reading the [Upgrade Guide](https://rust-random.github.io/book/update.html).
-
-### Rust version requirements
-
-Since version 0.7, Rand requires **Rustc version 1.32 or greater**.
-Rand 0.5 requires Rustc 1.22 or greater while versions
-0.4 and 0.3 (since approx. June 2017) require Rustc version 1.15 or
-greater. Subsets of the Rand code may work with older Rust versions, but this
-is not supported.
-
-Travis CI always has a build with a pinned version of Rustc matching the oldest
-supported Rust release. The current policy is that this can be updated in any
-Rand release if required, but the change must be noted in the changelog.
-
-## Crate Features
-
-Rand is built with these features enabled by default:
-
-- `std` enables functionality dependent on the `std` lib
-- `alloc` (implied by `std`) enables functionality requiring an allocator (when using this feature in `no_std`, Rand requires Rustc version 1.36 or greater)
-- `getrandom` (implied by `std`) is an optional dependency providing the code
- behind `rngs::OsRng`
-
-Optionally, the following dependencies can be enabled:
-
-- `log` enables logging via the `log` crate
-- `stdweb` implies `getrandom/stdweb` to enable
- `getrandom` support on `wasm32-unknown-unknown`
-- `wasm-bindgen` implies `getrandom/wasm-bindgen` to enable
- `getrandom` support on `wasm32-unknown-unknown`
-
-Additionally, these features configure Rand:
-
-- `small_rng` enables inclusion of the `SmallRng` PRNG
-- `nightly` enables all experimental features
-- `simd_support` (experimental) enables sampling of SIMD values
- (uniformly random SIMD integers and floats)
-
-Rand supports limited functionality in `no_std` mode (enabled via
-`default-features = false`). In this case, `OsRng` and `from_entropy` are
-unavailable (unless `getrandom` is enabled), large parts of `seq` are
-unavailable (unless `alloc` is enabled), and `thread_rng` and `random` are
-unavailable.
-
-# License
-
-Rand is distributed under the terms of both the MIT license and the
-Apache License (Version 2.0).
-
-See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT), and
-[COPYRIGHT](COPYRIGHT) for details.
diff --git a/rand/appveyor.yml b/rand/appveyor.yml
deleted file mode 100644
index ef0b4bf..0000000
--- a/rand/appveyor.yml
+++ /dev/null
@@ -1,49 +0,0 @@
-environment:
-
- # At the time this was added AppVeyor was having troubles with checking
- # revocation of SSL certificates of sites like static.rust-lang.org and what
- # we think is crates.io. The libcurl HTTP client by default checks for
- # revocation on Windows and according to a mailing list [1] this can be
- # disabled.
- #
- # The `CARGO_HTTP_CHECK_REVOKE` env var here tells cargo to disable SSL
- # revocation checking on Windows in libcurl. Note, though, that rustup, which
- # we're using to download Rust here, also uses libcurl as the default backend.
- # Unlike Cargo, however, rustup doesn't have a mechanism to disable revocation
- # checking. To get rustup working we set `RUSTUP_USE_HYPER` which forces it to
- # use the Hyper instead of libcurl backend. Both Hyper and libcurl use
- # schannel on Windows but it appears that Hyper configures it slightly
- # differently such that revocation checking isn't turned on by default.
- #
- # [1]: https://curl.haxx.se/mail/lib-2016-03/0202.html
- RUSTUP_USE_HYPER: 1
- CARGO_HTTP_CHECK_REVOKE: false
-
- matrix:
- - TARGET: x86_64-pc-windows-msvc
- - TARGET: i686-pc-windows-msvc
-install:
- - appveyor DownloadFile https://win.rustup.rs/ -FileName rustup-init.exe
- - rustup-init.exe -y --default-host %TARGET% --default-toolchain nightly
- - set PATH=%PATH%;C:\Users\appveyor\.cargo\bin
- - rustc -V
- - cargo -V
-
-build: false
-
-test_script:
- - cargo test --tests --no-default-features --features alloc
- # TODO: use --all-features once simd_support is sufficiently stable:
- - cargo test --features=serde1,log
- - cargo test --benches --features=nightly
- - cargo test --examples
- - cargo test --manifest-path rand_core/Cargo.toml
- - cargo test --manifest-path rand_core/Cargo.toml --no-default-features --features=alloc
- - cargo test --manifest-path rand_distr/Cargo.toml
- - cargo test --manifest-path rand_isaac/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_pcg/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xorshift/Cargo.toml --features=serde1
- - cargo test --manifest-path rand_xoshiro/Cargo.toml
- - cargo test --manifest-path rand_chacha/Cargo.toml
- - cargo test --manifest-path rand_hc/Cargo.toml
- - cargo test --manifest-path rand_os/Cargo.toml
diff --git a/rand/benches/generators.rs b/rand/benches/generators.rs
deleted file mode 100644
index 808bb67..0000000
--- a/rand/benches/generators.rs
+++ /dev/null
@@ -1,220 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#![feature(test)]
-#![allow(non_snake_case)]
-
-extern crate test;
-
-const RAND_BENCH_N: u64 = 1000;
-const BYTES_LEN: usize = 1024;
-
-use std::mem::size_of;
-use test::{black_box, Bencher};
-
-use rand::prelude::*;
-use rand::rngs::adapter::ReseedingRng;
-use rand::rngs::{OsRng, mock::StepRng};
-use rand_isaac::{IsaacRng, Isaac64Rng};
-use rand_chacha::{ChaCha20Core, ChaCha8Rng, ChaCha12Rng, ChaCha20Rng};
-use rand_hc::{Hc128Rng};
-use rand_pcg::{Pcg32, Pcg64, Pcg64Mcg};
-use rand_xorshift::XorShiftRng;
-use rand_xoshiro::{Xoshiro256StarStar, Xoshiro256Plus, Xoshiro128StarStar,
- Xoshiro128Plus, Xoroshiro128StarStar, Xoroshiro128Plus, SplitMix64,
- Xoroshiro64StarStar, Xoroshiro64Star};
-
-macro_rules! gen_bytes {
- ($fnn:ident, $gen:expr) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = $gen;
- let mut buf = [0u8; BYTES_LEN];
- b.iter(|| {
- for _ in 0..RAND_BENCH_N {
- rng.fill_bytes(&mut buf);
- black_box(buf);
- }
- });
- b.bytes = BYTES_LEN as u64 * RAND_BENCH_N;
- }
- }
-}
-
-gen_bytes!(gen_bytes_step, StepRng::new(0, 1));
-gen_bytes!(gen_bytes_xorshift, XorShiftRng::from_entropy());
-gen_bytes!(gen_bytes_xoshiro256starstar, Xoshiro256StarStar::from_entropy());
-gen_bytes!(gen_bytes_xoshiro256plus, Xoshiro256Plus::from_entropy());
-gen_bytes!(gen_bytes_xoshiro128starstar, Xoshiro128StarStar::from_entropy());
-gen_bytes!(gen_bytes_xoshiro128plus, Xoshiro128Plus::from_entropy());
-gen_bytes!(gen_bytes_xoroshiro128starstar, Xoroshiro128StarStar::from_entropy());
-gen_bytes!(gen_bytes_xoroshiro128plus, Xoroshiro128Plus::from_entropy());
-gen_bytes!(gen_bytes_xoroshiro64starstar, Xoroshiro64StarStar::from_entropy());
-gen_bytes!(gen_bytes_xoroshiro64star, Xoroshiro64Star::from_entropy());
-gen_bytes!(gen_bytes_splitmix64, SplitMix64::from_entropy());
-gen_bytes!(gen_bytes_pcg32, Pcg32::from_entropy());
-gen_bytes!(gen_bytes_pcg64, Pcg64::from_entropy());
-gen_bytes!(gen_bytes_pcg64mcg, Pcg64Mcg::from_entropy());
-gen_bytes!(gen_bytes_chacha8, ChaCha8Rng::from_entropy());
-gen_bytes!(gen_bytes_chacha12, ChaCha12Rng::from_entropy());
-gen_bytes!(gen_bytes_chacha20, ChaCha20Rng::from_entropy());
-gen_bytes!(gen_bytes_hc128, Hc128Rng::from_entropy());
-gen_bytes!(gen_bytes_isaac, IsaacRng::from_entropy());
-gen_bytes!(gen_bytes_isaac64, Isaac64Rng::from_entropy());
-gen_bytes!(gen_bytes_std, StdRng::from_entropy());
-#[cfg(feature="small_rng")]
-gen_bytes!(gen_bytes_small, SmallRng::from_entropy());
-gen_bytes!(gen_bytes_os, OsRng);
-
-macro_rules! gen_uint {
- ($fnn:ident, $ty:ty, $gen:expr) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = $gen;
- b.iter(|| {
- let mut accum: $ty = 0;
- for _ in 0..RAND_BENCH_N {
- accum = accum.wrapping_add(rng.gen::<$ty>());
- }
- accum
- });
- b.bytes = size_of::<$ty>() as u64 * RAND_BENCH_N;
- }
- }
-}
-
-gen_uint!(gen_u32_step, u32, StepRng::new(0, 1));
-gen_uint!(gen_u32_xorshift, u32, XorShiftRng::from_entropy());
-gen_uint!(gen_u32_xoshiro256starstar, u32, Xoshiro256StarStar::from_entropy());
-gen_uint!(gen_u32_xoshiro256plus, u32, Xoshiro256Plus::from_entropy());
-gen_uint!(gen_u32_xoshiro128starstar, u32, Xoshiro128StarStar::from_entropy());
-gen_uint!(gen_u32_xoshiro128plus, u32, Xoshiro128Plus::from_entropy());
-gen_uint!(gen_u32_xoroshiro128starstar, u32, Xoroshiro128StarStar::from_entropy());
-gen_uint!(gen_u32_xoroshiro128plus, u32, Xoroshiro128Plus::from_entropy());
-gen_uint!(gen_u32_xoroshiro64starstar, u32, Xoroshiro64StarStar::from_entropy());
-gen_uint!(gen_u32_xoroshiro64star, u32, Xoroshiro64Star::from_entropy());
-gen_uint!(gen_u32_splitmix64, u32, SplitMix64::from_entropy());
-gen_uint!(gen_u32_pcg32, u32, Pcg32::from_entropy());
-gen_uint!(gen_u32_pcg64, u32, Pcg64::from_entropy());
-gen_uint!(gen_u32_pcg64mcg, u32, Pcg64Mcg::from_entropy());
-gen_uint!(gen_u32_chacha8, u32, ChaCha8Rng::from_entropy());
-gen_uint!(gen_u32_chacha12, u32, ChaCha12Rng::from_entropy());
-gen_uint!(gen_u32_chacha20, u32, ChaCha20Rng::from_entropy());
-gen_uint!(gen_u32_hc128, u32, Hc128Rng::from_entropy());
-gen_uint!(gen_u32_isaac, u32, IsaacRng::from_entropy());
-gen_uint!(gen_u32_isaac64, u32, Isaac64Rng::from_entropy());
-gen_uint!(gen_u32_std, u32, StdRng::from_entropy());
-#[cfg(feature="small_rng")]
-gen_uint!(gen_u32_small, u32, SmallRng::from_entropy());
-gen_uint!(gen_u32_os, u32, OsRng);
-
-gen_uint!(gen_u64_step, u64, StepRng::new(0, 1));
-gen_uint!(gen_u64_xorshift, u64, XorShiftRng::from_entropy());
-gen_uint!(gen_u64_xoshiro256starstar, u64, Xoshiro256StarStar::from_entropy());
-gen_uint!(gen_u64_xoshiro256plus, u64, Xoshiro256Plus::from_entropy());
-gen_uint!(gen_u64_xoshiro128starstar, u64, Xoshiro128StarStar::from_entropy());
-gen_uint!(gen_u64_xoshiro128plus, u64, Xoshiro128Plus::from_entropy());
-gen_uint!(gen_u64_xoroshiro128starstar, u64, Xoroshiro128StarStar::from_entropy());
-gen_uint!(gen_u64_xoroshiro128plus, u64, Xoroshiro128Plus::from_entropy());
-gen_uint!(gen_u64_xoroshiro64starstar, u64, Xoroshiro64StarStar::from_entropy());
-gen_uint!(gen_u64_xoroshiro64star, u64, Xoroshiro64Star::from_entropy());
-gen_uint!(gen_u64_splitmix64, u64, SplitMix64::from_entropy());
-gen_uint!(gen_u64_pcg32, u64, Pcg32::from_entropy());
-gen_uint!(gen_u64_pcg64, u64, Pcg64::from_entropy());
-gen_uint!(gen_u64_pcg64mcg, u64, Pcg64Mcg::from_entropy());
-gen_uint!(gen_u64_chacha8, u64, ChaCha8Rng::from_entropy());
-gen_uint!(gen_u64_chacha12, u64, ChaCha12Rng::from_entropy());
-gen_uint!(gen_u64_chacha20, u64, ChaCha20Rng::from_entropy());
-gen_uint!(gen_u64_hc128, u64, Hc128Rng::from_entropy());
-gen_uint!(gen_u64_isaac, u64, IsaacRng::from_entropy());
-gen_uint!(gen_u64_isaac64, u64, Isaac64Rng::from_entropy());
-gen_uint!(gen_u64_std, u64, StdRng::from_entropy());
-#[cfg(feature="small_rng")]
-gen_uint!(gen_u64_small, u64, SmallRng::from_entropy());
-gen_uint!(gen_u64_os, u64, OsRng);
-
-macro_rules! init_gen {
- ($fnn:ident, $gen:ident) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = XorShiftRng::from_entropy();
- b.iter(|| {
- let r2 = $gen::from_rng(&mut rng).unwrap();
- r2
- });
- }
- }
-}
-
-init_gen!(init_xorshift, XorShiftRng);
-init_gen!(init_xoshiro256starstar, Xoshiro256StarStar);
-init_gen!(init_xoshiro256plus, Xoshiro256Plus);
-init_gen!(init_xoshiro128starstar, Xoshiro128StarStar);
-init_gen!(init_xoshiro128plus, Xoshiro128Plus);
-init_gen!(init_xoroshiro128starstar, Xoroshiro128StarStar);
-init_gen!(init_xoroshiro128plus, Xoroshiro128Plus);
-init_gen!(init_xoroshiro64starstar, Xoroshiro64StarStar);
-init_gen!(init_xoroshiro64star, Xoroshiro64Star);
-init_gen!(init_splitmix64, SplitMix64);
-init_gen!(init_pcg32, Pcg32);
-init_gen!(init_pcg64, Pcg64);
-init_gen!(init_pcg64mcg, Pcg64Mcg);
-init_gen!(init_hc128, Hc128Rng);
-init_gen!(init_isaac, IsaacRng);
-init_gen!(init_isaac64, Isaac64Rng);
-init_gen!(init_chacha, ChaCha20Rng);
-
-const RESEEDING_BYTES_LEN: usize = 1024 * 1024;
-const RESEEDING_BENCH_N: u64 = 16;
-
-macro_rules! reseeding_bytes {
- ($fnn:ident, $thresh:expr) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = ReseedingRng::new(ChaCha20Core::from_entropy(),
- $thresh * 1024,
- OsRng);
- let mut buf = [0u8; RESEEDING_BYTES_LEN];
- b.iter(|| {
- for _ in 0..RESEEDING_BENCH_N {
- rng.fill_bytes(&mut buf);
- black_box(&buf);
- }
- });
- b.bytes = RESEEDING_BYTES_LEN as u64 * RESEEDING_BENCH_N;
- }
- }
-}
-
-reseeding_bytes!(reseeding_chacha20_4k, 4);
-reseeding_bytes!(reseeding_chacha20_16k, 16);
-reseeding_bytes!(reseeding_chacha20_32k, 32);
-reseeding_bytes!(reseeding_chacha20_64k, 64);
-reseeding_bytes!(reseeding_chacha20_256k, 256);
-reseeding_bytes!(reseeding_chacha20_1M, 1024);
-
-
-macro_rules! threadrng_uint {
- ($fnn:ident, $ty:ty) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = thread_rng();
- b.iter(|| {
- let mut accum: $ty = 0;
- for _ in 0..RAND_BENCH_N {
- accum = accum.wrapping_add(rng.gen::<$ty>());
- }
- accum
- });
- b.bytes = size_of::<$ty>() as u64 * RAND_BENCH_N;
- }
- }
-}
-
-threadrng_uint!(thread_rng_u32, u32);
-threadrng_uint!(thread_rng_u64, u64);
diff --git a/rand/benches/misc.rs b/rand/benches/misc.rs
deleted file mode 100644
index 4098686..0000000
--- a/rand/benches/misc.rs
+++ /dev/null
@@ -1,140 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#![feature(test)]
-
-extern crate test;
-
-const RAND_BENCH_N: u64 = 1000;
-
-use test::Bencher;
-
-use rand::prelude::*;
-use rand::distributions::{Distribution, Standard, Bernoulli};
-use rand_pcg::{Pcg32, Pcg64Mcg};
-
-#[bench]
-fn misc_gen_bool_const(b: &mut Bencher) {
- let mut rng = Pcg32::from_rng(&mut thread_rng()).unwrap();
- b.iter(|| {
- let mut accum = true;
- for _ in 0..crate::RAND_BENCH_N {
- accum ^= rng.gen_bool(0.18);
- }
- accum
- })
-}
-
-#[bench]
-fn misc_gen_bool_var(b: &mut Bencher) {
- let mut rng = Pcg32::from_rng(&mut thread_rng()).unwrap();
- b.iter(|| {
- let mut accum = true;
- let mut p = 0.18;
- for _ in 0..crate::RAND_BENCH_N {
- accum ^= rng.gen_bool(p);
- p += 0.0001;
- }
- accum
- })
-}
-
-#[bench]
-fn misc_gen_ratio_const(b: &mut Bencher) {
- let mut rng = Pcg32::from_rng(&mut thread_rng()).unwrap();
- b.iter(|| {
- let mut accum = true;
- for _ in 0..crate::RAND_BENCH_N {
- accum ^= rng.gen_ratio(2, 3);
- }
- accum
- })
-}
-
-#[bench]
-fn misc_gen_ratio_var(b: &mut Bencher) {
- let mut rng = Pcg32::from_rng(&mut thread_rng()).unwrap();
- b.iter(|| {
- let mut accum = true;
- for i in 2..(crate::RAND_BENCH_N as u32 + 2) {
- accum ^= rng.gen_ratio(i, i + 1);
- }
- accum
- })
-}
-
-#[bench]
-fn misc_bernoulli_const(b: &mut Bencher) {
- let mut rng = Pcg32::from_rng(&mut thread_rng()).unwrap();
- b.iter(|| {
- let d = rand::distributions::Bernoulli::new(0.18).unwrap();
- let mut accum = true;
- for _ in 0..crate::RAND_BENCH_N {
- accum ^= rng.sample(d);
- }
- accum
- })
-}
-
-#[bench]
-fn misc_bernoulli_var(b: &mut Bencher) {
- let mut rng = Pcg32::from_rng(&mut thread_rng()).unwrap();
- b.iter(|| {
- let mut accum = true;
- let mut p = 0.18;
- for _ in 0..crate::RAND_BENCH_N {
- let d = Bernoulli::new(p).unwrap();
- accum ^= rng.sample(d);
- p += 0.0001;
- }
- accum
- })
-}
-
-#[bench]
-fn gen_1k_iter_repeat(b: &mut Bencher) {
- use std::iter;
- let mut rng = Pcg64Mcg::from_rng(&mut thread_rng()).unwrap();
- b.iter(|| {
- let v: Vec<u64> = iter::repeat(()).map(|()| rng.gen()).take(128).collect();
- v
- });
- b.bytes = 1024;
-}
-
-#[bench]
-fn gen_1k_sample_iter(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_rng(&mut thread_rng()).unwrap();
- b.iter(|| {
- let v: Vec<u64> = Standard.sample_iter(&mut rng).take(128).collect();
- v
- });
- b.bytes = 1024;
-}
-
-#[bench]
-fn gen_1k_gen_array(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_rng(&mut thread_rng()).unwrap();
- b.iter(|| {
- // max supported array length is 32!
- let v: [[u64; 32]; 4] = rng.gen();
- v
- });
- b.bytes = 1024;
-}
-
-#[bench]
-fn gen_1k_fill(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_rng(&mut thread_rng()).unwrap();
- let mut buf = [0u64; 128];
- b.iter(|| {
- rng.fill(&mut buf[..]);
- buf
- });
- b.bytes = 1024;
-}
diff --git a/rand/benches/seq.rs b/rand/benches/seq.rs
deleted file mode 100644
index 4c671b8..0000000
--- a/rand/benches/seq.rs
+++ /dev/null
@@ -1,177 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#![feature(test)]
-#![allow(non_snake_case)]
-
-extern crate test;
-
-use test::Bencher;
-
-use rand::prelude::*;
-use rand::seq::*;
-use std::mem::size_of;
-
-// We force use of 32-bit RNG since seq code is optimised for use with 32-bit
-// generators on all platforms.
-use rand_pcg::Pcg32 as SmallRng;
-
-const RAND_BENCH_N: u64 = 1000;
-
-#[bench]
-fn seq_shuffle_100(b: &mut Bencher) {
- let mut rng = SmallRng::from_rng(thread_rng()).unwrap();
- let x : &mut [usize] = &mut [1; 100];
- b.iter(|| {
- x.shuffle(&mut rng);
- x[0]
- })
-}
-
-#[bench]
-fn seq_slice_choose_1_of_1000(b: &mut Bencher) {
- let mut rng = SmallRng::from_rng(thread_rng()).unwrap();
- let x : &mut [usize] = &mut [1; 1000];
- for i in 0..1000 {
- x[i] = i;
- }
- b.iter(|| {
- let mut s = 0;
- for _ in 0..RAND_BENCH_N {
- s += x.choose(&mut rng).unwrap();
- }
- s
- });
- b.bytes = size_of::<usize>() as u64 * crate::RAND_BENCH_N;
-}
-
-macro_rules! seq_slice_choose_multiple {
- ($name:ident, $amount:expr, $length:expr) => {
- #[bench]
- fn $name(b: &mut Bencher) {
- let mut rng = SmallRng::from_rng(thread_rng()).unwrap();
- let x : &[i32] = &[$amount; $length];
- let mut result = [0i32; $amount];
- b.iter(|| {
- // Collect full result to prevent unwanted shortcuts getting
- // first element (in case sample_indices returns an iterator).
- for (slot, sample) in result.iter_mut().zip(
- x.choose_multiple(&mut rng, $amount)) {
- *slot = *sample;
- }
- result[$amount-1]
- })
- }
- }
-}
-
-seq_slice_choose_multiple!(seq_slice_choose_multiple_1_of_1000, 1, 1000);
-seq_slice_choose_multiple!(seq_slice_choose_multiple_950_of_1000, 950, 1000);
-seq_slice_choose_multiple!(seq_slice_choose_multiple_10_of_100, 10, 100);
-seq_slice_choose_multiple!(seq_slice_choose_multiple_90_of_100, 90, 100);
-
-#[bench]
-fn seq_iter_choose_from_1000(b: &mut Bencher) {
- let mut rng = SmallRng::from_rng(thread_rng()).unwrap();
- let x : &mut [usize] = &mut [1; 1000];
- for i in 0..1000 {
- x[i] = i;
- }
- b.iter(|| {
- let mut s = 0;
- for _ in 0..RAND_BENCH_N {
- s += x.iter().choose(&mut rng).unwrap();
- }
- s
- });
- b.bytes = size_of::<usize>() as u64 * crate::RAND_BENCH_N;
-}
-
-#[derive(Clone)]
-struct UnhintedIterator<I: Iterator + Clone> {
- iter: I,
-}
-impl<I: Iterator + Clone> Iterator for UnhintedIterator<I> {
- type Item = I::Item;
- fn next(&mut self) -> Option<Self::Item> {
- self.iter.next()
- }
-}
-
-#[derive(Clone)]
-struct WindowHintedIterator<I: ExactSizeIterator + Iterator + Clone> {
- iter: I,
- window_size: usize,
-}
-impl<I: ExactSizeIterator + Iterator + Clone> Iterator for WindowHintedIterator<I> {
- type Item = I::Item;
- fn next(&mut self) -> Option<Self::Item> {
- self.iter.next()
- }
- fn size_hint(&self) -> (usize, Option<usize>) {
- (std::cmp::min(self.iter.len(), self.window_size), None)
- }
-}
-
-#[bench]
-fn seq_iter_unhinted_choose_from_1000(b: &mut Bencher) {
- let mut rng = SmallRng::from_rng(thread_rng()).unwrap();
- let x : &[usize] = &[1; 1000];
- b.iter(|| {
- UnhintedIterator { iter: x.iter() }.choose(&mut rng).unwrap()
- })
-}
-
-#[bench]
-fn seq_iter_window_hinted_choose_from_1000(b: &mut Bencher) {
- let mut rng = SmallRng::from_rng(thread_rng()).unwrap();
- let x : &[usize] = &[1; 1000];
- b.iter(|| {
- WindowHintedIterator { iter: x.iter(), window_size: 7 }.choose(&mut rng)
- })
-}
-
-#[bench]
-fn seq_iter_choose_multiple_10_of_100(b: &mut Bencher) {
- let mut rng = SmallRng::from_rng(thread_rng()).unwrap();
- let x : &[usize] = &[1; 100];
- b.iter(|| {
- x.iter().cloned().choose_multiple(&mut rng, 10)
- })
-}
-
-#[bench]
-fn seq_iter_choose_multiple_fill_10_of_100(b: &mut Bencher) {
- let mut rng = SmallRng::from_rng(thread_rng()).unwrap();
- let x : &[usize] = &[1; 100];
- let mut buf = [0; 10];
- b.iter(|| {
- x.iter().cloned().choose_multiple_fill(&mut rng, &mut buf)
- })
-}
-
-macro_rules! sample_indices {
- ($name:ident, $fn:ident, $amount:expr, $length:expr) => {
- #[bench]
- fn $name(b: &mut Bencher) {
- let mut rng = SmallRng::from_rng(thread_rng()).unwrap();
- b.iter(|| {
- index::$fn(&mut rng, $length, $amount)
- })
- }
- }
-}
-
-sample_indices!(misc_sample_indices_1_of_1k, sample, 1, 1000);
-sample_indices!(misc_sample_indices_10_of_1k, sample, 10, 1000);
-sample_indices!(misc_sample_indices_100_of_1k, sample, 100, 1000);
-sample_indices!(misc_sample_indices_100_of_1M, sample, 100, 1000_000);
-sample_indices!(misc_sample_indices_100_of_1G, sample, 100, 1000_000_000);
-sample_indices!(misc_sample_indices_200_of_1G, sample, 200, 1000_000_000);
-sample_indices!(misc_sample_indices_400_of_1G, sample, 400, 1000_000_000);
-sample_indices!(misc_sample_indices_600_of_1G, sample, 600, 1000_000_000);
diff --git a/rand/benches/weighted.rs b/rand/benches/weighted.rs
deleted file mode 100644
index 5ddca3f..0000000
--- a/rand/benches/weighted.rs
+++ /dev/null
@@ -1,36 +0,0 @@
-// Copyright 2019 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#![feature(test)]
-
-extern crate test;
-
-use test::Bencher;
-use rand::Rng;
-use rand::distributions::WeightedIndex;
-
-#[bench]
-fn weighted_index_creation(b: &mut Bencher) {
- let mut rng = rand::thread_rng();
- let weights = [1u32, 2, 4, 0, 5, 1, 7, 1, 2, 3, 4, 5, 6, 7];
- b.iter(|| {
- let distr = WeightedIndex::new(weights.to_vec()).unwrap();
- rng.sample(distr)
- })
-}
-
-#[bench]
-fn weighted_index_modification(b: &mut Bencher) {
- let mut rng = rand::thread_rng();
- let weights = [1u32, 2, 3, 0, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7];
- let mut distr = WeightedIndex::new(weights.to_vec()).unwrap();
- b.iter(|| {
- distr.update_weights(&[(2, &4), (5, &1)]).unwrap();
- rng.sample(&distr)
- })
-}
diff --git a/rand/examples/monte-carlo.rs b/rand/examples/monte-carlo.rs
deleted file mode 100644
index 39c779f..0000000
--- a/rand/examples/monte-carlo.rs
+++ /dev/null
@@ -1,48 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013-2018 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! # Monte Carlo estimation of Ο
-//!
-//! Imagine that we have a square with sides of length 2 and a unit circle
-//! (radius = 1), both centered at the origin. The areas are:
-//!
-//! ```text
-//! area of circle = ΟrΒ² = Ο * r * r = Ο
-//! area of square = 2Β² = 4
-//! ```
-//!
-//! The circle is entirely within the square, so if we sample many points
-//! randomly from the square, roughly Ο / 4 of them should be inside the circle.
-//!
-//! We can use the above fact to estimate the value of Ο: pick many points in
-//! the square at random, calculate the fraction that fall within the circle,
-//! and multiply this fraction by 4.
-
-#![cfg(feature = "std")]
-
-use rand::distributions::{Distribution, Uniform};
-
-fn main() {
- let range = Uniform::new(-1.0f64, 1.0);
- let mut rng = rand::thread_rng();
-
- let total = 1_000_000;
- let mut in_circle = 0;
-
- for _ in 0..total {
- let a = range.sample(&mut rng);
- let b = range.sample(&mut rng);
- if a*a + b*b <= 1.0 {
- in_circle += 1;
- }
- }
-
- // prints something close to 3.14159...
- println!("Ο is approximately {}", 4. * (in_circle as f64) / (total as f64));
-}
diff --git a/rand/examples/monty-hall.rs b/rand/examples/monty-hall.rs
deleted file mode 100644
index 9fe5839..0000000
--- a/rand/examples/monty-hall.rs
+++ /dev/null
@@ -1,112 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013-2018 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! ## Monty Hall Problem
-//!
-//! This is a simulation of the [Monty Hall Problem][]:
-//!
-//! > Suppose you're on a game show, and you're given the choice of three doors:
-//! > Behind one door is a car; behind the others, goats. You pick a door, say
-//! > No. 1, and the host, who knows what's behind the doors, opens another
-//! > door, say No. 3, which has a goat. He then says to you, "Do you want to
-//! > pick door No. 2?" Is it to your advantage to switch your choice?
-//!
-//! The rather unintuitive answer is that you will have a 2/3 chance of winning
-//! if you switch and a 1/3 chance of winning if you don't, so it's better to
-//! switch.
-//!
-//! This program will simulate the game show and with large enough simulation
-//! steps it will indeed confirm that it is better to switch.
-//!
-//! [Monty Hall Problem]: https://en.wikipedia.org/wiki/Monty_Hall_problem
-
-#![cfg(feature = "std")]
-
-use rand::distributions::{Distribution, Uniform};
-use rand::Rng;
-
-struct SimulationResult {
- win: bool,
- switch: bool,
-}
-
-// Run a single simulation of the Monty Hall problem.
-fn simulate<R: Rng>(random_door: &Uniform<u32>, rng: &mut R) -> SimulationResult {
- let car = random_door.sample(rng);
-
- // This is our initial choice
- let mut choice = random_door.sample(rng);
-
- // The game host opens a door
- let open = game_host_open(car, choice, rng);
-
- // Shall we switch?
- let switch = rng.gen();
- if switch {
- choice = switch_door(choice, open);
- }
-
- SimulationResult { win: choice == car, switch }
-}
-
-// Returns the door the game host opens given our choice and knowledge of
-// where the car is. The game host will never open the door with the car.
-fn game_host_open<R: Rng>(car: u32, choice: u32, rng: &mut R) -> u32 {
- use rand::seq::SliceRandom;
- *free_doors(&[car, choice]).choose(rng).unwrap()
-}
-
-// Returns the door we switch to, given our current choice and
-// the open door. There will only be one valid door.
-fn switch_door(choice: u32, open: u32) -> u32 {
- free_doors(&[choice, open])[0]
-}
-
-fn free_doors(blocked: &[u32]) -> Vec<u32> {
- (0..3).filter(|x| !blocked.contains(x)).collect()
-}
-
-fn main() {
- // The estimation will be more accurate with more simulations
- let num_simulations = 10000;
-
- let mut rng = rand::thread_rng();
- let random_door = Uniform::new(0u32, 3);
-
- let (mut switch_wins, mut switch_losses) = (0, 0);
- let (mut keep_wins, mut keep_losses) = (0, 0);
-
- println!("Running {} simulations...", num_simulations);
- for _ in 0..num_simulations {
- let result = simulate(&random_door, &mut rng);
-
- match (result.win, result.switch) {
- (true, true) => switch_wins += 1,
- (true, false) => keep_wins += 1,
- (false, true) => switch_losses += 1,
- (false, false) => keep_losses += 1,
- }
- }
-
- let total_switches = switch_wins + switch_losses;
- let total_keeps = keep_wins + keep_losses;
-
- println!("Switched door {} times with {} wins and {} losses",
- total_switches, switch_wins, switch_losses);
-
- println!("Kept our choice {} times with {} wins and {} losses",
- total_keeps, keep_wins, keep_losses);
-
- // With a large number of simulations, the values should converge to
- // 0.667 and 0.333 respectively.
- println!("Estimated chance to win if we switch: {}",
- switch_wins as f32 / total_switches as f32);
- println!("Estimated chance to win if we don't: {}",
- keep_wins as f32 / total_keeps as f32);
-}
diff --git a/rand/rand_chacha/CHANGELOG.md b/rand/rand_chacha/CHANGELOG.md
deleted file mode 100644
index d242f97..0000000
--- a/rand/rand_chacha/CHANGELOG.md
+++ /dev/null
@@ -1,18 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.2.1] - 2019-07-22
-- Force enable the `simd` feature of `c2-chacha` (#845)
-
-## [0.2.0] - 2019-06-06
-- Rewrite based on the much faster `c2-chacha` crate (#789)
-
-## [0.1.1] - 2019-01-04
-- Disable `i128` and `u128` if the `target_os` is `emscripten` (#671: work-around Emscripten limitation)
-- Update readme and doc links
-
-## [0.1.0] - 2018-10-17
-- Pulled out of the Rand crate
diff --git a/rand/rand_chacha/COPYRIGHT b/rand/rand_chacha/COPYRIGHT
deleted file mode 100644
index 468d907..0000000
--- a/rand/rand_chacha/COPYRIGHT
+++ /dev/null
@@ -1,12 +0,0 @@
-Copyrights in the Rand project are retained by their contributors. No
-copyright assignment is required to contribute to the Rand project.
-
-For full authorship information, see the version control history.
-
-Except as otherwise noted (below and/or in individual files), Rand is
-licensed under the Apache License, Version 2.0 <LICENSE-APACHE> or
-<http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-<LICENSE-MIT> or <http://opensource.org/licenses/MIT>, at your option.
-
-The Rand project includes code from the Rust project
-published under these same licenses.
diff --git a/rand/rand_chacha/Cargo.toml b/rand/rand_chacha/Cargo.toml
deleted file mode 100644
index 6a47b86..0000000
--- a/rand/rand_chacha/Cargo.toml
+++ /dev/null
@@ -1,28 +0,0 @@
-[package]
-name = "rand_chacha"
-version = "0.2.1"
-authors = ["The Rand Project Developers", "The Rust Project Developers", "The CryptoCorrosion Contributors"]
-license = "MIT OR Apache-2.0"
-readme = "README.md"
-repository = "https://github.com/rust-random/rand"
-documentation = "https://rust-random.github.io/rand/rand_chacha/"
-homepage = "https://crates.io/crates/rand_chacha"
-description = """
-ChaCha random number generator
-"""
-keywords = ["random", "rng", "chacha"]
-categories = ["algorithms", "no-std"]
-edition = "2018"
-
-[badges]
-travis-ci = { repository = "rust-random/rand" }
-appveyor = { repository = "rust-random/rand" }
-
-[dependencies]
-rand_core = { path = "../rand_core", version = "0.5" }
-c2-chacha = { version = "0.2.2", default-features = false, features = ["simd"] }
-
-[features]
-default = ["std", "simd"]
-std = ["c2-chacha/std"]
-simd = [] # deprecated
diff --git a/rand/rand_chacha/LICENSE-APACHE b/rand/rand_chacha/LICENSE-APACHE
deleted file mode 100644
index 17d7468..0000000
--- a/rand/rand_chacha/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
- Apache License
- Version 2.0, January 2004
- https://www.apache.org/licenses/
-
-TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
-
-1. Definitions.
-
- "License" shall mean the terms and conditions for use, reproduction,
- and distribution as defined by Sections 1 through 9 of this document.
-
- "Licensor" shall mean the copyright owner or entity authorized by
- the copyright owner that is granting the License.
-
- "Legal Entity" shall mean the union of the acting entity and all
- other entities that control, are controlled by, or are under common
- control with that entity. For the purposes of this definition,
- "control" means (i) the power, direct or indirect, to cause the
- direction or management of such entity, whether by contract or
- otherwise, or (ii) ownership of fifty percent (50%) or more of the
- outstanding shares, or (iii) beneficial ownership of such entity.
-
- "You" (or "Your") shall mean an individual or Legal Entity
- exercising permissions granted by this License.
-
- "Source" form shall mean the preferred form for making modifications,
- including but not limited to software source code, documentation
- source, and configuration files.
-
- "Object" form shall mean any form resulting from mechanical
- transformation or translation of a Source form, including but
- not limited to compiled object code, generated documentation,
- and conversions to other media types.
-
- "Work" shall mean the work of authorship, whether in Source or
- Object form, made available under the License, as indicated by a
- copyright notice that is included in or attached to the work
- (an example is provided in the Appendix below).
-
- "Derivative Works" shall mean any work, whether in Source or Object
- form, that is based on (or derived from) the Work and for which the
- editorial revisions, annotations, elaborations, or other modifications
- represent, as a whole, an original work of authorship. For the purposes
- of this License, Derivative Works shall not include works that remain
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- the original version of the Work and any modifications or additions
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- of any other Contributor, and only if You agree to indemnify,
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- incurred by, or claims asserted against, such Contributor by reason
- of your accepting any such warranty or additional liability.
-
-END OF TERMS AND CONDITIONS
-
-APPENDIX: How to apply the Apache License to your work.
-
- To apply the Apache License to your work, attach the following
- boilerplate notice, with the fields enclosed by brackets "[]"
- replaced with your own identifying information. (Don't include
- the brackets!) The text should be enclosed in the appropriate
- comment syntax for the file format. We also recommend that a
- file or class name and description of purpose be included on the
- same "printed page" as the copyright notice for easier
- identification within third-party archives.
-
-Copyright [yyyy] [name of copyright owner]
-
-Licensed 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
-
- https://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.
diff --git a/rand/rand_chacha/LICENSE-MIT b/rand/rand_chacha/LICENSE-MIT
deleted file mode 100644
index d93b5ba..0000000
--- a/rand/rand_chacha/LICENSE-MIT
+++ /dev/null
@@ -1,26 +0,0 @@
-Copyright 2018 Developers of the Rand project
-Copyright (c) 2014 The Rust Project Developers
-
-Permission is hereby granted, free of charge, to any
-person obtaining a copy of this software and associated
-documentation files (the "Software"), to deal in the
-Software without restriction, including without
-limitation the rights to use, copy, modify, merge,
-publish, distribute, sublicense, and/or sell copies of
-the Software, and to permit persons to whom the Software
-is furnished to do so, subject to the following
-conditions:
-
-The above copyright notice and this permission notice
-shall be included in all copies or substantial portions
-of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF
-ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED
-TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
-PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
-SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
-IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-DEALINGS IN THE SOFTWARE.
diff --git a/rand/rand_chacha/README.md b/rand/rand_chacha/README.md
deleted file mode 100644
index 69a0ce7..0000000
--- a/rand/rand_chacha/README.md
+++ /dev/null
@@ -1,49 +0,0 @@
-# rand_chacha
-
-[](https://travis-ci.org/rust-random/rand)
-[](https://ci.appveyor.com/project/rust-random/rand)
-[](https://crates.io/crates/rand_chacha)
-[](https://rust-random.github.io/book/)
-[](https://rust-random.github.io/rand/rand_chacha)
-[](https://docs.rs/rand_chacha)
-[](https://github.com/rust-random/rand#rust-version-requirements)
-
-A cryptographically secure random number generator that uses the ChaCha
-algorithm.
-
-ChaCha is a stream cipher designed by Daniel J. Bernstein[^1], that we use
-as an RNG. It is an improved variant of the Salsa20 cipher family, which was
-selected as one of the "stream ciphers suitable for widespread adoption" by
-eSTREAM[^2].
-
-The RNGs provided by this crate are implemented via the fast stream ciphers of
-the [`c2-chacha`](https://crates.io/crates/c2-chacha) crate.
-
-Links:
-
-- [API documentation (master)](https://rust-random.github.io/rand/rand_chacha)
-- [API documentation (docs.rs)](https://docs.rs/rand_chacha)
-- [Changelog](https://github.com/rust-random/rand/blob/master/rand_chacha/CHANGELOG.md)
-
-[rand]: https://crates.io/crates/rand
-[^1]: D. J. Bernstein, [*ChaCha, a variant of Salsa20*](
- https://cr.yp.to/chacha.html)
-
-[^2]: [eSTREAM: the ECRYPT Stream Cipher Project](
- http://www.ecrypt.eu.org/stream/)
-
-
-## Crate Features
-
-`rand_chacha` is `no_std` compatible when disabling default features; the `std`
-feature can be explicitly required to re-enable `std` support. Using `std`
-allows detection of CPU features and thus better optimisation.
-
-
-# License
-
-`rand_chacha` is distributed under the terms of both the MIT license and the
-Apache License (Version 2.0).
-
-See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT), and
-[COPYRIGHT](COPYRIGHT) for details.
diff --git a/rand/rand_chacha/src/chacha.rs b/rand/rand_chacha/src/chacha.rs
deleted file mode 100644
index b1b89e0..0000000
--- a/rand/rand_chacha/src/chacha.rs
+++ /dev/null
@@ -1,452 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The ChaCha random number generator.
-
-#[cfg(feature = "std")]
-use std as core;
-#[cfg(not(feature = "std"))]
-use core;
-
-use c2_chacha::guts::ChaCha;
-use self::core::fmt;
-use rand_core::block::{BlockRng, BlockRngCore};
-use rand_core::{CryptoRng, Error, RngCore, SeedableRng};
-
-const STREAM_PARAM_NONCE: u32 = 1;
-const STREAM_PARAM_BLOCK: u32 = 0;
-
-pub struct Array64<T>([T; 64]);
-impl<T> Default for Array64<T> where T: Default {
- fn default() -> Self {
- Self([T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(),
- T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(),
- T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(),
- T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(),
- T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(),
- T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(),
- T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(),
- T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default(), T::default()])
- }
-}
-impl<T> AsRef<[T]> for Array64<T> {
- fn as_ref(&self) -> &[T] {
- &self.0
- }
-}
-impl<T> AsMut<[T]> for Array64<T> {
- fn as_mut(&mut self) -> &mut [T] {
- &mut self.0
- }
-}
-impl<T> Clone for Array64<T> where T: Copy + Default {
- fn clone(&self) -> Self {
- let mut new = Self::default();
- new.0.copy_from_slice(&self.0);
- new
- }
-}
-impl<T> fmt::Debug for Array64<T> {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "Array64 {{}}")
- }
-}
-
-macro_rules! chacha_impl {
- ($ChaChaXCore:ident, $ChaChaXRng:ident, $rounds:expr, $doc:expr) => {
- #[doc=$doc]
- #[derive(Clone)]
- pub struct $ChaChaXCore {
- state: ChaCha,
- }
-
- // Custom Debug implementation that does not expose the internal state
- impl fmt::Debug for $ChaChaXCore {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "ChaChaXCore {{}}")
- }
- }
-
- impl BlockRngCore for $ChaChaXCore {
- type Item = u32;
- type Results = Array64<u32>;
- #[inline]
- fn generate(&mut self, r: &mut Self::Results) {
- // Fill slice of words by writing to equivalent slice of bytes, then fixing endianness.
- self.state.refill4($rounds, unsafe {
- &mut *(&mut *r as *mut Array64<u32> as *mut [u8; 256])
- });
- for x in r.as_mut() {
- *x = x.to_le();
- }
- }
- }
-
- impl SeedableRng for $ChaChaXCore {
- type Seed = [u8; 32];
- #[inline]
- fn from_seed(seed: Self::Seed) -> Self {
- $ChaChaXCore { state: ChaCha::new(&seed, &[0u8; 8]) }
- }
- }
-
- /// A cryptographically secure random number generator that uses the ChaCha algorithm.
- ///
- /// ChaCha is a stream cipher designed by Daniel J. Bernstein[^1], that we use as an RNG. It is
- /// an improved variant of the Salsa20 cipher family, which was selected as one of the "stream
- /// ciphers suitable for widespread adoption" by eSTREAM[^2].
- ///
- /// ChaCha uses add-rotate-xor (ARX) operations as its basis. These are safe against timing
- /// attacks, although that is mostly a concern for ciphers and not for RNGs. We provide a SIMD
- /// implementation to support high throughput on a variety of common hardware platforms.
- ///
- /// With the ChaCha algorithm it is possible to choose the number of rounds the core algorithm
- /// should run. The number of rounds is a tradeoff between performance and security, where 8
- /// rounds is the minimum potentially secure configuration, and 20 rounds is widely used as a
- /// conservative choice.
- ///
- /// We use a 64-bit counter and 64-bit stream identifier as in Bernstein's implementation[^1]
- /// except that we use a stream identifier in place of a nonce. A 64-bit counter over 64-byte
- /// (16 word) blocks allows 1 ZiB of output before cycling, and the stream identifier allows
- /// 2<sup>64</sup> unique streams of output per seed. Both counter and stream are initialized
- /// to zero but may be set via the `set_word_pos` and `set_stream` methods.
- ///
- /// The word layout is:
- ///
- /// ```text
- /// constant constant constant constant
- /// seed seed seed seed
- /// seed seed seed seed
- /// counter counter stream_id stream_id
- /// ```
- ///
- /// This implementation uses an output buffer of sixteen `u32` words, and uses
- /// [`BlockRng`] to implement the [`RngCore`] methods.
- ///
- /// [^1]: D. J. Bernstein, [*ChaCha, a variant of Salsa20*](
- /// https://cr.yp.to/chacha.html)
- ///
- /// [^2]: [eSTREAM: the ECRYPT Stream Cipher Project](
- /// http://www.ecrypt.eu.org/stream/)
- #[derive(Clone, Debug)]
- pub struct $ChaChaXRng {
- rng: BlockRng<$ChaChaXCore>,
- }
-
- impl SeedableRng for $ChaChaXRng {
- type Seed = [u8; 32];
- #[inline]
- fn from_seed(seed: Self::Seed) -> Self {
- let core = $ChaChaXCore::from_seed(seed);
- Self {
- rng: BlockRng::new(core),
- }
- }
- }
-
- impl RngCore for $ChaChaXRng {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.rng.next_u32()
- }
- #[inline]
- fn next_u64(&mut self) -> u64 {
- self.rng.next_u64()
- }
- #[inline]
- fn fill_bytes(&mut self, bytes: &mut [u8]) {
- self.rng.fill_bytes(bytes)
- }
- #[inline]
- fn try_fill_bytes(&mut self, bytes: &mut [u8]) -> Result<(), Error> {
- self.rng.try_fill_bytes(bytes)
- }
- }
-
- impl $ChaChaXRng {
- // The buffer is a 4-block window, i.e. it is always at a block-aligned position in the
- // stream but if the stream has been seeked it may not be self-aligned.
-
- /// Get the offset from the start of the stream, in 32-bit words.
- ///
- /// Since the generated blocks are 16 words (2<sup>4</sup>) long and the
- /// counter is 64-bits, the offset is a 68-bit number. Sub-word offsets are
- /// not supported, hence the result can simply be multiplied by 4 to get a
- /// byte-offset.
- #[inline]
- pub fn get_word_pos(&self) -> u128 {
- let mut block = u128::from(self.rng.core.state.get_stream_param(STREAM_PARAM_BLOCK));
- // counter is incremented *after* filling buffer
- block -= 4;
- (block << 4) + self.rng.index() as u128
- }
-
- /// Set the offset from the start of the stream, in 32-bit words.
- ///
- /// As with `get_word_pos`, we use a 68-bit number. Since the generator
- /// simply cycles at the end of its period (1 ZiB), we ignore the upper
- /// 60 bits.
- #[inline]
- pub fn set_word_pos(&mut self, word_offset: u128) {
- let block = (word_offset >> 4) as u64;
- self.rng
- .core
- .state
- .set_stream_param(STREAM_PARAM_BLOCK, block);
- self.rng.generate_and_set((word_offset & 15) as usize);
- }
-
- /// Set the stream number.
- ///
- /// This is initialized to zero; 2<sup>64</sup> unique streams of output
- /// are available per seed/key.
- ///
- /// Note that in order to reproduce ChaCha output with a specific 64-bit
- /// nonce, one can convert that nonce to a `u64` in little-endian fashion
- /// and pass to this function. In theory a 96-bit nonce can be used by
- /// passing the last 64-bits to this function and using the first 32-bits as
- /// the most significant half of the 64-bit counter (which may be set
- /// indirectly via `set_word_pos`), but this is not directly supported.
- #[inline]
- pub fn set_stream(&mut self, stream: u64) {
- self.rng
- .core
- .state
- .set_stream_param(STREAM_PARAM_NONCE, stream);
- if self.rng.index() != 64 {
- let wp = self.get_word_pos();
- self.set_word_pos(wp);
- }
- }
- }
-
- impl CryptoRng for $ChaChaXRng {}
-
- impl From<$ChaChaXCore> for $ChaChaXRng {
- fn from(core: $ChaChaXCore) -> Self {
- $ChaChaXRng {
- rng: BlockRng::new(core),
- }
- }
- }
- }
-}
-
-chacha_impl!(ChaCha20Core, ChaCha20Rng, 10, "ChaCha with 20 rounds");
-chacha_impl!(ChaCha12Core, ChaCha12Rng, 6, "ChaCha with 12 rounds");
-chacha_impl!(ChaCha8Core, ChaCha8Rng, 4, "ChaCha with 8 rounds");
-
-#[cfg(test)]
-mod test {
- use rand_core::{RngCore, SeedableRng};
-
- type ChaChaRng = super::ChaCha20Rng;
-
- #[test]
- fn test_chacha_construction() {
- let seed = [
- 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0,
- 0, 0, 0,
- ];
- let mut rng1 = ChaChaRng::from_seed(seed);
- assert_eq!(rng1.next_u32(), 137206642);
-
- let mut rng2 = ChaChaRng::from_rng(rng1).unwrap();
- assert_eq!(rng2.next_u32(), 1325750369);
- }
-
- #[test]
- fn test_chacha_true_values_a() {
- // Test vectors 1 and 2 from
- // https://tools.ietf.org/html/draft-nir-cfrg-chacha20-poly1305-04
- let seed = [0u8; 32];
- let mut rng = ChaChaRng::from_seed(seed);
-
- let mut results = [0u32; 16];
- for i in results.iter_mut() {
- *i = rng.next_u32();
- }
- let expected = [
- 0xade0b876, 0x903df1a0, 0xe56a5d40, 0x28bd8653, 0xb819d2bd, 0x1aed8da0, 0xccef36a8,
- 0xc70d778b, 0x7c5941da, 0x8d485751, 0x3fe02477, 0x374ad8b8, 0xf4b8436a, 0x1ca11815,
- 0x69b687c3, 0x8665eeb2,
- ];
- assert_eq!(results, expected);
-
- for i in results.iter_mut() {
- *i = rng.next_u32();
- }
- let expected = [
- 0xbee7079f, 0x7a385155, 0x7c97ba98, 0x0d082d73, 0xa0290fcb, 0x6965e348, 0x3e53c612,
- 0xed7aee32, 0x7621b729, 0x434ee69c, 0xb03371d5, 0xd539d874, 0x281fed31, 0x45fb0a51,
- 0x1f0ae1ac, 0x6f4d794b,
- ];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_chacha_true_values_b() {
- // Test vector 3 from
- // https://tools.ietf.org/html/draft-nir-cfrg-chacha20-poly1305-04
- let seed = [
- 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
- 0, 0, 1,
- ];
- let mut rng = ChaChaRng::from_seed(seed);
-
- // Skip block 0
- for _ in 0..16 {
- rng.next_u32();
- }
-
- let mut results = [0u32; 16];
- for i in results.iter_mut() {
- *i = rng.next_u32();
- }
- let expected = [
- 0x2452eb3a, 0x9249f8ec, 0x8d829d9b, 0xddd4ceb1, 0xe8252083, 0x60818b01, 0xf38422b8,
- 0x5aaa49c9, 0xbb00ca8e, 0xda3ba7b4, 0xc4b592d1, 0xfdf2732f, 0x4436274e, 0x2561b3c8,
- 0xebdd4aa6, 0xa0136c00,
- ];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_chacha_true_values_c() {
- // Test vector 4 from
- // https://tools.ietf.org/html/draft-nir-cfrg-chacha20-poly1305-04
- let seed = [
- 0, 0xff, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
- 0, 0, 0, 0,
- ];
- let expected = [
- 0xfb4dd572, 0x4bc42ef1, 0xdf922636, 0x327f1394, 0xa78dea8f, 0x5e269039, 0xa1bebbc1,
- 0xcaf09aae, 0xa25ab213, 0x48a6b46c, 0x1b9d9bcb, 0x092c5be6, 0x546ca624, 0x1bec45d5,
- 0x87f47473, 0x96f0992e,
- ];
- let expected_end = 3 * 16;
- let mut results = [0u32; 16];
-
- // Test block 2 by skipping block 0 and 1
- let mut rng1 = ChaChaRng::from_seed(seed);
- for _ in 0..32 {
- rng1.next_u32();
- }
- for i in results.iter_mut() {
- *i = rng1.next_u32();
- }
- assert_eq!(results, expected);
- assert_eq!(rng1.get_word_pos(), expected_end);
-
- // Test block 2 by using `set_word_pos`
- let mut rng2 = ChaChaRng::from_seed(seed);
- rng2.set_word_pos(2 * 16);
- for i in results.iter_mut() {
- *i = rng2.next_u32();
- }
- assert_eq!(results, expected);
- assert_eq!(rng2.get_word_pos(), expected_end);
-
- // Test skipping behaviour with other types
- let mut buf = [0u8; 32];
- rng2.fill_bytes(&mut buf[..]);
- assert_eq!(rng2.get_word_pos(), expected_end + 8);
- rng2.fill_bytes(&mut buf[0..25]);
- assert_eq!(rng2.get_word_pos(), expected_end + 15);
- rng2.next_u64();
- assert_eq!(rng2.get_word_pos(), expected_end + 17);
- rng2.next_u32();
- rng2.next_u64();
- assert_eq!(rng2.get_word_pos(), expected_end + 20);
- rng2.fill_bytes(&mut buf[0..1]);
- assert_eq!(rng2.get_word_pos(), expected_end + 21);
- }
-
- #[test]
- fn test_chacha_multiple_blocks() {
- let seed = [
- 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 4, 0, 0, 0, 5, 0, 0, 0, 6, 0, 0, 0, 7,
- 0, 0, 0,
- ];
- let mut rng = ChaChaRng::from_seed(seed);
-
- // Store the 17*i-th 32-bit word,
- // i.e., the i-th word of the i-th 16-word block
- let mut results = [0u32; 16];
- for i in results.iter_mut() {
- *i = rng.next_u32();
- for _ in 0..16 {
- rng.next_u32();
- }
- }
- let expected = [
- 0xf225c81a, 0x6ab1be57, 0x04d42951, 0x70858036, 0x49884684, 0x64efec72, 0x4be2d186,
- 0x3615b384, 0x11cfa18e, 0xd3c50049, 0x75c775f6, 0x434c6530, 0x2c5bad8f, 0x898881dc,
- 0x5f1c86d9, 0xc1f8e7f4,
- ];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_chacha_true_bytes() {
- let seed = [0u8; 32];
- let mut rng = ChaChaRng::from_seed(seed);
- let mut results = [0u8; 32];
- rng.fill_bytes(&mut results);
- let expected = [
- 118, 184, 224, 173, 160, 241, 61, 144, 64, 93, 106, 229, 83, 134, 189, 40, 189, 210,
- 25, 184, 160, 141, 237, 26, 168, 54, 239, 204, 139, 119, 13, 199,
- ];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_chacha_nonce() {
- // Test vector 5 from
- // https://tools.ietf.org/html/draft-nir-cfrg-chacha20-poly1305-04
- // Although we do not support setting a nonce, we try it here anyway so
- // we can use this test vector.
- let seed = [0u8; 32];
- let mut rng = ChaChaRng::from_seed(seed);
- // 96-bit nonce in LE order is: 0,0,0,0, 0,0,0,0, 0,0,0,2
- rng.set_stream(2u64 << (24 + 32));
-
- let mut results = [0u32; 16];
- for i in results.iter_mut() {
- *i = rng.next_u32();
- }
- let expected = [
- 0x374dc6c2, 0x3736d58c, 0xb904e24a, 0xcd3f93ef, 0x88228b1a, 0x96a4dfb3, 0x5b76ab72,
- 0xc727ee54, 0x0e0e978a, 0xf3145c95, 0x1b748ea8, 0xf786c297, 0x99c28f5f, 0x628314e8,
- 0x398a19fa, 0x6ded1b53,
- ];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_chacha_clone_streams() {
- let seed = [
- 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 4, 0, 0, 0, 5, 0, 0, 0, 6, 0, 0, 0, 7,
- 0, 0, 0,
- ];
- let mut rng = ChaChaRng::from_seed(seed);
- let mut clone = rng.clone();
- for _ in 0..16 {
- assert_eq!(rng.next_u64(), clone.next_u64());
- }
-
- rng.set_stream(51);
- for _ in 0..7 {
- assert!(rng.next_u32() != clone.next_u32());
- }
- clone.set_stream(51); // switch part way through block
- for _ in 7..16 {
- assert_eq!(rng.next_u32(), clone.next_u32());
- }
- }
-}
diff --git a/rand/rand_chacha/src/lib.rs b/rand/rand_chacha/src/lib.rs
deleted file mode 100644
index e374bdd..0000000
--- a/rand/rand_chacha/src/lib.rs
+++ /dev/null
@@ -1,30 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The ChaCha random number generator.
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
- html_favicon_url = "https://www.rust-lang.org/favicon.ico",
- html_root_url = "https://rust-random.github.io/rand/")]
-
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-#![doc(test(attr(allow(unused_variables), deny(warnings))))]
-
-#![cfg_attr(not(feature = "std"), no_std)]
-
-pub use rand_core;
-
-mod chacha;
-
-pub use crate::chacha::{ChaCha12Core, ChaCha12Rng, ChaCha20Core, ChaCha20Rng, ChaCha8Core, ChaCha8Rng};
-
-/// ChaCha with 20 rounds
-pub type ChaChaRng = ChaCha20Rng;
-/// ChaCha with 20 rounds, low-level interface
-pub type ChaChaCore = ChaCha20Core;
diff --git a/rand/rand_core/CHANGELOG.md b/rand/rand_core/CHANGELOG.md
deleted file mode 100644
index dfdd692..0000000
--- a/rand/rand_core/CHANGELOG.md
+++ /dev/null
@@ -1,58 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.5.1] - 2019-08-28
-- `OsRng` added to `rand_core` (#863)
-- `Error::INTERNAL_START` and `Error::CUSTOM_START` constants (#864)
-- `Error::raw_os_error` method (#864)
-- `Debug` and `Display` formatting for `getrandom` error codes without `std` (#864)
-### Changed
-- `alloc` feature in `no_std` is available since Rust 1.36 (#856)
-- Added `#[inline]` to `Error` conversion methods (#864)
-
-## [0.5.0] - 2019-06-06
-### Changed
-- Enable testing with Miri and fix incorrect pointer usages (#779, #780, #781, #783, #784)
-- Rewrite `Error` type and adjust API (#800)
-- Adjust usage of `#[inline]` for `BlockRng` and `BlockRng64`
-
-## [0.4.0] - 2019-01-24
-### Changed
-- Disable the `std` feature by default (#702)
-
-## [0.3.0] - 2018-09-24
-### Added
-- Add `SeedableRng::seed_from_u64` for convenient seeding. (#537)
-
-## [0.2.1] - 2018-06-08
-### Added
-- References to a `CryptoRng` now also implement `CryptoRng`. (#470)
-
-## [0.2.0] - 2018-05-21
-### Changed
-- Enable the `std` feature by default. (#409)
-- Remove `BlockRng{64}::inner` and `BlockRng::inner_mut`; instead making `core` public
-- Change `BlockRngCore::Results` bound to also require `AsMut<[Self::Item]>`. (#419)
-### Added
-- Add `BlockRng{64}::index` and `BlockRng{64}::generate_and_set`. (#374, #419)
-- Implement `std::io::Read` for RngCore. (#434)
-
-## [0.1.0] - 2018-04-17
-(Split out of the Rand crate, changes here are relative to rand 0.4.2.)
-### Added
-- `RngCore` and `SeedableRng` are now part of `rand_core`. (#288)
-- Add modules to help implementing RNGs `impl` and `le`. (#209, #228)
-- Add `Error` and `ErrorKind`. (#225)
-- Add `CryptoRng` marker trait. (#273)
-- Add `BlockRngCore` trait. (#281)
-- Add `BlockRng` and `BlockRng64` wrappers to help implementations. (#281, #325)
-- Add `RngCore::try_fill_bytes`. (#225)
-### Changed
-- Revise the `SeedableRng` trait. (#233)
-- Remove default implementations for `RngCore::next_u64` and `RngCore::fill_bytes`. (#288)
-
-## [0.0.1] - 2017-09-14 (yanked)
-Experimental version as part of the rand crate refactor.
diff --git a/rand/rand_core/COPYRIGHT b/rand/rand_core/COPYRIGHT
deleted file mode 100644
index 468d907..0000000
--- a/rand/rand_core/COPYRIGHT
+++ /dev/null
@@ -1,12 +0,0 @@
-Copyrights in the Rand project are retained by their contributors. No
-copyright assignment is required to contribute to the Rand project.
-
-For full authorship information, see the version control history.
-
-Except as otherwise noted (below and/or in individual files), Rand is
-licensed under the Apache License, Version 2.0 <LICENSE-APACHE> or
-<http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-<LICENSE-MIT> or <http://opensource.org/licenses/MIT>, at your option.
-
-The Rand project includes code from the Rust project
-published under these same licenses.
diff --git a/rand/rand_core/Cargo.toml b/rand/rand_core/Cargo.toml
deleted file mode 100644
index e52af5f..0000000
--- a/rand/rand_core/Cargo.toml
+++ /dev/null
@@ -1,28 +0,0 @@
-[package]
-name = "rand_core"
-version = "0.5.1"
-authors = ["The Rand Project Developers", "The Rust Project Developers"]
-license = "MIT OR Apache-2.0"
-readme = "README.md"
-repository = "https://github.com/rust-random/rand"
-documentation = "https://rust-random.github.io/rand/rand_core/"
-homepage = "https://crates.io/crates/rand_core"
-description = """
-Core random number generator traits and tools for implementation.
-"""
-keywords = ["random", "rng"]
-categories = ["algorithms", "no-std"]
-edition = "2018"
-
-[badges]
-travis-ci = { repository = "rust-random/rand" }
-appveyor = { repository = "rust-random/rand" }
-
-[features]
-std = ["alloc", "getrandom", "getrandom/std"] # use std library; should be default but for above bug
-alloc = [] # enables Vec and Box support without std
-serde1 = ["serde"] # enables serde for BlockRng wrapper
-
-[dependencies]
-serde = { version = "1", features = ["derive"], optional = true }
-getrandom = { version = "0.1", optional = true }
diff --git a/rand/rand_core/LICENSE-APACHE b/rand/rand_core/LICENSE-APACHE
deleted file mode 100644
index 17d7468..0000000
--- a/rand/rand_core/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
- Apache License
- Version 2.0, January 2004
- https://www.apache.org/licenses/
-
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-
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diff --git a/rand/rand_core/LICENSE-MIT b/rand/rand_core/LICENSE-MIT
deleted file mode 100644
index d93b5ba..0000000
--- a/rand/rand_core/LICENSE-MIT
+++ /dev/null
@@ -1,26 +0,0 @@
-Copyright 2018 Developers of the Rand project
-Copyright (c) 2014 The Rust Project Developers
-
-Permission is hereby granted, free of charge, to any
-person obtaining a copy of this software and associated
-documentation files (the "Software"), to deal in the
-Software without restriction, including without
-limitation the rights to use, copy, modify, merge,
-publish, distribute, sublicense, and/or sell copies of
-the Software, and to permit persons to whom the Software
-is furnished to do so, subject to the following
-conditions:
-
-The above copyright notice and this permission notice
-shall be included in all copies or substantial portions
-of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF
-ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED
-TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
-PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
-SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
-IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-DEALINGS IN THE SOFTWARE.
diff --git a/rand/rand_core/README.md b/rand/rand_core/README.md
deleted file mode 100644
index 467e66f..0000000
--- a/rand/rand_core/README.md
+++ /dev/null
@@ -1,82 +0,0 @@
-# rand_core
-
-[](https://travis-ci.org/rust-random/rand)
-[](https://ci.appveyor.com/project/rust-random/rand)
-[](https://crates.io/crates/rand_core)
-[](https://rust-random.github.io/book/)
-[](https://rust-random.github.io/rand/rand_core)
-[](https://docs.rs/rand_core)
-[](https://github.com/rust-random/rand#rust-version-requirements)
-
-Core traits and error types of the [rand] library, plus tools for implementing
-RNGs.
-
-This crate is intended for use when implementing the core trait, `RngCore`; it
-defines the core traits to be implemented as well as several small functions to
-aid in their implementation and types required for error handling.
-
-The main [rand] crate re-exports most items defined in this crate, along with
-tools to convert the integer samples generated by `RngCore` to many different
-applications (including sampling from restricted ranges, conversion to floating
-point, list permutations and secure initialisation of RNGs). Most users should
-prefer to use the main [rand] crate.
-
-Links:
-
-- [API documentation (master)](https://rust-random.github.io/rand/rand_core)
-- [API documentation (docs.rs)](https://docs.rs/rand_core)
-- [Changelog](https://github.com/rust-random/rand/blob/master/rand_core/CHANGELOG.md)
-
-[rand]: https://crates.io/crates/rand
-
-
-## Functionality
-
-The `rand_core` crate provides:
-
-- base random number generator traits
-- error-reporting types
-- functionality to aid implementation of RNGs
-
-The traits and error types are also available via `rand`.
-
-## Versions
-
-The current version is:
-```
-rand_core = "0.5.0"
-```
-
-Rand libs have inter-dependencies and make use of the
-[semver trick](https://github.com/dtolnay/semver-trick/) in order to make traits
-compatible across crate versions. (This is especially important for `RngCore`
-and `SeedableRng`.) A few crate releases are thus compatibility shims,
-depending on the *next* lib version (e.g. `rand_core` versions `0.2.2` and
-`0.3.1`). This means, for example, that `rand_core_0_4_0::SeedableRng` and
-`rand_core_0_3_0::SeedableRng` are distinct, incompatible traits, which can
-cause build errors. Usually, running `cargo update` is enough to fix any issues.
-
-## Crate Features
-
-`rand_core` supports `no_std` and `alloc`-only configurations, as well as full
-`std` functionality. The differences between `no_std` and full `std` are small,
-comprising `RngCore` support for `Box<R>` types where `R: RngCore`,
-`std::io::Read` support for types supporting `RngCore`, and
-extensions to the `Error` type's functionality.
-
-The `std` feature is *not enabled by default*. This is primarily to avoid build
-problems where one crate implicitly requires `rand_core` with `std` support and
-another crate requires `rand` *without* `std` support. However, the `rand` crate
-continues to enable `std` support by default, both for itself and `rand_core`.
-
-The `serde1` feature can be used to derive `Serialize` and `Deserialize` for RNG
-implementations that use the `BlockRng` or `BlockRng64` wrappers.
-
-
-# License
-
-`rand_core` is distributed under the terms of both the MIT license and the
-Apache License (Version 2.0).
-
-See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT), and
-[COPYRIGHT](COPYRIGHT) for details.
diff --git a/rand/rand_core/src/block.rs b/rand/rand_core/src/block.rs
deleted file mode 100644
index 0ab7458..0000000
--- a/rand/rand_core/src/block.rs
+++ /dev/null
@@ -1,437 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The `BlockRngCore` trait and implementation helpers
-//!
-//! The [`BlockRngCore`] trait exists to assist in the implementation of RNGs
-//! which generate a block of data in a cache instead of returning generated
-//! values directly.
-//!
-//! Usage of this trait is optional, but provides two advantages:
-//! implementations only need to concern themselves with generation of the
-//! block, not the various [`RngCore`] methods (especially [`fill_bytes`], where
-//! the optimal implementations are not trivial), and this allows
-//! `ReseedingRng` (see [`rand`](https://docs.rs/rand) crate) perform periodic
-//! reseeding with very low overhead.
-//!
-//! # Example
-//!
-//! ```norun
-//! use rand_core::block::{BlockRngCore, BlockRng};
-//!
-//! struct MyRngCore;
-//!
-//! impl BlockRngCore for MyRngCore {
-//! type Results = [u32; 16];
-//!
-//! fn generate(&mut self, results: &mut Self::Results) {
-//! unimplemented!()
-//! }
-//! }
-//!
-//! impl SeedableRng for MyRngCore {
-//! type Seed = unimplemented!();
-//! fn from_seed(seed: Self::Seed) -> Self {
-//! unimplemented!()
-//! }
-//! }
-//!
-//! // optionally, also implement CryptoRng for MyRngCore
-//!
-//! // Final RNG.
-//! type MyRng = BlockRng<u32, MyRngCore>;
-//! ```
-//!
-//! [`BlockRngCore`]: crate::block::BlockRngCore
-//! [`fill_bytes`]: RngCore::fill_bytes
-
-use core::convert::AsRef;
-use core::{fmt, ptr};
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use crate::{RngCore, CryptoRng, SeedableRng, Error};
-use crate::impls::{fill_via_u32_chunks, fill_via_u64_chunks};
-
-/// A trait for RNGs which do not generate random numbers individually, but in
-/// blocks (typically `[u32; N]`). This technique is commonly used by
-/// cryptographic RNGs to improve performance.
-///
-/// See the [module][crate::block] documentation for details.
-pub trait BlockRngCore {
- /// Results element type, e.g. `u32`.
- type Item;
-
- /// Results type. This is the 'block' an RNG implementing `BlockRngCore`
- /// generates, which will usually be an array like `[u32; 16]`.
- type Results: AsRef<[Self::Item]> + AsMut<[Self::Item]> + Default;
-
- /// Generate a new block of results.
- fn generate(&mut self, results: &mut Self::Results);
-}
-
-
-/// A wrapper type implementing [`RngCore`] for some type implementing
-/// [`BlockRngCore`] with `u32` array buffer; i.e. this can be used to implement
-/// a full RNG from just a `generate` function.
-///
-/// The `core` field may be accessed directly but the results buffer may not.
-/// PRNG implementations can simply use a type alias
-/// (`pub type MyRng = BlockRng<MyRngCore>;`) but might prefer to use a
-/// wrapper type (`pub struct MyRng(BlockRng<MyRngCore>);`); the latter must
-/// re-implement `RngCore` but hides the implementation details and allows
-/// extra functionality to be defined on the RNG
-/// (e.g. `impl MyRng { fn set_stream(...){...} }`).
-///
-/// `BlockRng` has heavily optimized implementations of the [`RngCore`] methods
-/// reading values from the results buffer, as well as
-/// calling [`BlockRngCore::generate`] directly on the output array when
-/// [`fill_bytes`] / [`try_fill_bytes`] is called on a large array. These methods
-/// also handle the bookkeeping of when to generate a new batch of values.
-///
-/// No whole generated `u32` values are thown away and all values are consumed
-/// in-order. [`next_u32`] simply takes the next available `u32` value.
-/// [`next_u64`] is implemented by combining two `u32` values, least
-/// significant first. [`fill_bytes`] and [`try_fill_bytes`] consume a whole
-/// number of `u32` values, converting each `u32` to a byte slice in
-/// little-endian order. If the requested byte length is not a multiple of 4,
-/// some bytes will be discarded.
-///
-/// See also [`BlockRng64`] which uses `u64` array buffers. Currently there is
-/// no direct support for other buffer types.
-///
-/// For easy initialization `BlockRng` also implements [`SeedableRng`].
-///
-/// [`next_u32`]: RngCore::next_u32
-/// [`next_u64`]: RngCore::next_u64
-/// [`fill_bytes`]: RngCore::fill_bytes
-/// [`try_fill_bytes`]: RngCore::try_fill_bytes
-#[derive(Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct BlockRng<R: BlockRngCore + ?Sized> {
- results: R::Results,
- index: usize,
- /// The *core* part of the RNG, implementing the `generate` function.
- pub core: R,
-}
-
-// Custom Debug implementation that does not expose the contents of `results`.
-impl<R: BlockRngCore + fmt::Debug> fmt::Debug for BlockRng<R> {
- fn fmt(&self, fmt: &mut fmt::Formatter) -> fmt::Result {
- fmt.debug_struct("BlockRng")
- .field("core", &self.core)
- .field("result_len", &self.results.as_ref().len())
- .field("index", &self.index)
- .finish()
- }
-}
-
-impl<R: BlockRngCore> BlockRng<R> {
- /// Create a new `BlockRng` from an existing RNG implementing
- /// `BlockRngCore`. Results will be generated on first use.
- #[inline]
- pub fn new(core: R) -> BlockRng<R>{
- let results_empty = R::Results::default();
- BlockRng {
- core,
- index: results_empty.as_ref().len(),
- results: results_empty,
- }
- }
-
- /// Get the index into the result buffer.
- ///
- /// If this is equal to or larger than the size of the result buffer then
- /// the buffer is "empty" and `generate()` must be called to produce new
- /// results.
- #[inline(always)]
- pub fn index(&self) -> usize {
- self.index
- }
-
- /// Reset the number of available results.
- /// This will force a new set of results to be generated on next use.
- #[inline]
- pub fn reset(&mut self) {
- self.index = self.results.as_ref().len();
- }
-
- /// Generate a new set of results immediately, setting the index to the
- /// given value.
- #[inline]
- pub fn generate_and_set(&mut self, index: usize) {
- assert!(index < self.results.as_ref().len());
- self.core.generate(&mut self.results);
- self.index = index;
- }
-}
-
-impl<R: BlockRngCore<Item=u32>> RngCore for BlockRng<R>
-where <R as BlockRngCore>::Results: AsRef<[u32]> + AsMut<[u32]>
-{
- #[inline]
- fn next_u32(&mut self) -> u32 {
- if self.index >= self.results.as_ref().len() {
- self.generate_and_set(0);
- }
-
- let value = self.results.as_ref()[self.index];
- self.index += 1;
- value
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- let read_u64 = |results: &[u32], index| {
- if cfg!(any(target_endian = "little")) {
- // requires little-endian CPU
- #[allow(clippy::cast_ptr_alignment)] // false positive
- let ptr: *const u64 = results[index..=index+1].as_ptr() as *const u64;
- unsafe { ptr::read_unaligned(ptr) }
- } else {
- let x = u64::from(results[index]);
- let y = u64::from(results[index + 1]);
- (y << 32) | x
- }
- };
-
- let len = self.results.as_ref().len();
-
- let index = self.index;
- if index < len-1 {
- self.index += 2;
- // Read an u64 from the current index
- read_u64(self.results.as_ref(), index)
- } else if index >= len {
- self.generate_and_set(2);
- read_u64(self.results.as_ref(), 0)
- } else {
- let x = u64::from(self.results.as_ref()[len-1]);
- self.generate_and_set(1);
- let y = u64::from(self.results.as_ref()[0]);
- (y << 32) | x
- }
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- let mut read_len = 0;
- while read_len < dest.len() {
- if self.index >= self.results.as_ref().len() {
- self.generate_and_set(0);
- }
- let (consumed_u32, filled_u8) =
- fill_via_u32_chunks(&self.results.as_ref()[self.index..],
- &mut dest[read_len..]);
-
- self.index += consumed_u32;
- read_len += filled_u8;
- }
- }
-
- #[inline(always)]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-impl<R: BlockRngCore + SeedableRng> SeedableRng for BlockRng<R> {
- type Seed = R::Seed;
-
- #[inline(always)]
- fn from_seed(seed: Self::Seed) -> Self {
- Self::new(R::from_seed(seed))
- }
-
- #[inline(always)]
- fn seed_from_u64(seed: u64) -> Self {
- Self::new(R::seed_from_u64(seed))
- }
-
- #[inline(always)]
- fn from_rng<S: RngCore>(rng: S) -> Result<Self, Error> {
- Ok(Self::new(R::from_rng(rng)?))
- }
-}
-
-
-
-/// A wrapper type implementing [`RngCore`] for some type implementing
-/// [`BlockRngCore`] with `u64` array buffer; i.e. this can be used to implement
-/// a full RNG from just a `generate` function.
-///
-/// This is similar to [`BlockRng`], but specialized for algorithms that operate
-/// on `u64` values.
-///
-/// No whole generated `u64` values are thrown away and all values are consumed
-/// in-order. [`next_u64`] simply takes the next available `u64` value.
-/// [`next_u32`] is however a bit special: half of a `u64` is consumed, leaving
-/// the other half in the buffer. If the next function called is [`next_u32`]
-/// then the other half is then consumed, however both [`next_u64`] and
-/// [`fill_bytes`] discard the rest of any half-consumed `u64`s when called.
-///
-/// [`fill_bytes`] and [`try_fill_bytes`] consume a whole number of `u64`
-/// values. If the requested length is not a multiple of 8, some bytes will be
-/// discarded.
-///
-/// [`next_u32`]: RngCore::next_u32
-/// [`next_u64`]: RngCore::next_u64
-/// [`fill_bytes`]: RngCore::fill_bytes
-/// [`try_fill_bytes`]: RngCore::try_fill_bytes
-#[derive(Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct BlockRng64<R: BlockRngCore + ?Sized> {
- results: R::Results,
- index: usize,
- half_used: bool, // true if only half of the previous result is used
- /// The *core* part of the RNG, implementing the `generate` function.
- pub core: R,
-}
-
-// Custom Debug implementation that does not expose the contents of `results`.
-impl<R: BlockRngCore + fmt::Debug> fmt::Debug for BlockRng64<R> {
- fn fmt(&self, fmt: &mut fmt::Formatter) -> fmt::Result {
- fmt.debug_struct("BlockRng64")
- .field("core", &self.core)
- .field("result_len", &self.results.as_ref().len())
- .field("index", &self.index)
- .field("half_used", &self.half_used)
- .finish()
- }
-}
-
-impl<R: BlockRngCore> BlockRng64<R> {
- /// Create a new `BlockRng` from an existing RNG implementing
- /// `BlockRngCore`. Results will be generated on first use.
- #[inline]
- pub fn new(core: R) -> BlockRng64<R>{
- let results_empty = R::Results::default();
- BlockRng64 {
- core,
- index: results_empty.as_ref().len(),
- half_used: false,
- results: results_empty,
- }
- }
-
- /// Get the index into the result buffer.
- ///
- /// If this is equal to or larger than the size of the result buffer then
- /// the buffer is "empty" and `generate()` must be called to produce new
- /// results.
- #[inline(always)]
- pub fn index(&self) -> usize {
- self.index
- }
-
- /// Reset the number of available results.
- /// This will force a new set of results to be generated on next use.
- #[inline]
- pub fn reset(&mut self) {
- self.index = self.results.as_ref().len();
- self.half_used = false;
- }
-
- /// Generate a new set of results immediately, setting the index to the
- /// given value.
- #[inline]
- pub fn generate_and_set(&mut self, index: usize) {
- assert!(index < self.results.as_ref().len());
- self.core.generate(&mut self.results);
- self.index = index;
- self.half_used = false;
- }
-}
-
-impl<R: BlockRngCore<Item=u64>> RngCore for BlockRng64<R>
-where <R as BlockRngCore>::Results: AsRef<[u64]> + AsMut<[u64]>
-{
- #[inline]
- fn next_u32(&mut self) -> u32 {
- let mut index = self.index * 2 - self.half_used as usize;
- if index >= self.results.as_ref().len() * 2 {
- self.core.generate(&mut self.results);
- self.index = 0;
- // `self.half_used` is by definition `false`
- self.half_used = false;
- index = 0;
- }
-
- self.half_used = !self.half_used;
- self.index += self.half_used as usize;
-
- // Index as if this is a u32 slice.
- unsafe {
- let results =
- &*(self.results.as_ref() as *const [u64] as *const [u32]);
- if cfg!(target_endian = "little") {
- *results.get_unchecked(index)
- } else {
- *results.get_unchecked(index ^ 1)
- }
- }
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- if self.index >= self.results.as_ref().len() {
- self.core.generate(&mut self.results);
- self.index = 0;
- }
-
- let value = self.results.as_ref()[self.index];
- self.index += 1;
- self.half_used = false;
- value
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- let mut read_len = 0;
- self.half_used = false;
- while read_len < dest.len() {
- if self.index as usize >= self.results.as_ref().len() {
- self.core.generate(&mut self.results);
- self.index = 0;
- }
-
- let (consumed_u64, filled_u8) =
- fill_via_u64_chunks(&self.results.as_ref()[self.index as usize..],
- &mut dest[read_len..]);
-
- self.index += consumed_u64;
- read_len += filled_u8;
- }
- }
-
- #[inline(always)]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-impl<R: BlockRngCore + SeedableRng> SeedableRng for BlockRng64<R> {
- type Seed = R::Seed;
-
- #[inline(always)]
- fn from_seed(seed: Self::Seed) -> Self {
- Self::new(R::from_seed(seed))
- }
-
- #[inline(always)]
- fn seed_from_u64(seed: u64) -> Self {
- Self::new(R::seed_from_u64(seed))
- }
-
- #[inline(always)]
- fn from_rng<S: RngCore>(rng: S) -> Result<Self, Error> {
- Ok(Self::new(R::from_rng(rng)?))
- }
-}
-
-impl<R: BlockRngCore + CryptoRng> CryptoRng for BlockRng<R> {}
diff --git a/rand/rand_core/src/error.rs b/rand/rand_core/src/error.rs
deleted file mode 100644
index 30b095c..0000000
--- a/rand/rand_core/src/error.rs
+++ /dev/null
@@ -1,190 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Error types
-
-use core::fmt;
-use core::num::NonZeroU32;
-
-
-/// Error type of random number generators
-///
-/// In order to be compatible with `std` and `no_std`, this type has two
-/// possible implementations: with `std` a boxed `Error` trait object is stored,
-/// while with `no_std` we merely store an error code.
-pub struct Error {
- #[cfg(feature="std")]
- inner: Box<dyn std::error::Error + Send + Sync + 'static>,
- #[cfg(not(feature="std"))]
- code: NonZeroU32,
-}
-
-impl Error {
- /// Construct from any type supporting `std::error::Error`
- ///
- /// Available only when configured with `std`.
- ///
- /// See also `From<NonZeroU32>`, which is available with and without `std`.
- #[cfg(feature="std")]
- #[inline]
- pub fn new<E>(err: E) -> Self
- where E: Into<Box<dyn std::error::Error + Send + Sync + 'static>>
- {
- Error { inner: err.into() }
- }
-
- /// Reference the inner error (`std` only)
- ///
- /// When configured with `std`, this is a trivial operation and never
- /// panics. Without `std`, this method is simply unavailable.
- #[cfg(feature="std")]
- #[inline]
- pub fn inner(&self) -> &(dyn std::error::Error + Send + Sync + 'static) {
- &*self.inner
- }
-
- /// Unwrap the inner error (`std` only)
- ///
- /// When configured with `std`, this is a trivial operation and never
- /// panics. Without `std`, this method is simply unavailable.
- #[cfg(feature="std")]
- #[inline]
- pub fn take_inner(self) -> Box<dyn std::error::Error + Send + Sync + 'static> {
- self.inner
- }
-
- /// Codes below this point represent OS Errors (i.e. positive i32 values).
- /// Codes at or above this point, but below [`Error::CUSTOM_START`] are
- /// reserved for use by the `rand` and `getrandom` crates.
- pub const INTERNAL_START: u32 = 1 << 31;
-
- /// Codes at or above this point can be used by users to define their own
- /// custom errors.
- pub const CUSTOM_START: u32 = (1 << 31) + (1 << 30);
-
- /// Extract the raw OS error code (if this error came from the OS)
- ///
- /// This method is identical to `std::io::Error::raw_os_error()`, except
- /// that it works in `no_std` contexts. If this method returns `None`, the
- /// error value can still be formatted via the `Diplay` implementation.
- #[inline]
- pub fn raw_os_error(&self) -> Option<i32> {
- #[cfg(feature="std")] {
- if let Some(e) = self.inner.downcast_ref::<std::io::Error>() {
- return e.raw_os_error();
- }
- }
- match self.code() {
- Some(code) if u32::from(code) < Self::INTERNAL_START =>
- Some(u32::from(code) as i32),
- _ => None,
- }
- }
-
- /// Retrieve the error code, if any.
- ///
- /// If this `Error` was constructed via `From<NonZeroU32>`, then this method
- /// will return this `NonZeroU32` code (for `no_std` this is always the
- /// case). Otherwise, this method will return `None`.
- #[inline]
- pub fn code(&self) -> Option<NonZeroU32> {
- #[cfg(feature="std")] {
- self.inner.downcast_ref::<ErrorCode>().map(|c| c.0)
- }
- #[cfg(not(feature="std"))] {
- Some(self.code)
- }
- }
-}
-
-impl fmt::Debug for Error {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- #[cfg(feature="std")] {
- write!(f, "Error {{ inner: {:?} }}", self.inner)
- }
- #[cfg(all(feature="getrandom", not(feature="std")))] {
- getrandom::Error::from(self.code).fmt(f)
- }
- #[cfg(not(feature="getrandom"))] {
- write!(f, "Error {{ code: {} }}", self.code)
- }
- }
-}
-
-impl fmt::Display for Error {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- #[cfg(feature="std")] {
- write!(f, "{}", self.inner)
- }
- #[cfg(all(feature="getrandom", not(feature="std")))] {
- getrandom::Error::from(self.code).fmt(f)
- }
- #[cfg(not(feature="getrandom"))] {
- write!(f, "error code {}", self.code)
- }
- }
-}
-
-impl From<NonZeroU32> for Error {
- #[inline]
- fn from(code: NonZeroU32) -> Self {
- #[cfg(feature="std")] {
- Error { inner: Box::new(ErrorCode(code)) }
- }
- #[cfg(not(feature="std"))] {
- Error { code }
- }
- }
-}
-
-#[cfg(feature="getrandom")]
-impl From<getrandom::Error> for Error {
- #[inline]
- fn from(error: getrandom::Error) -> Self {
- #[cfg(feature="std")] {
- Error { inner: Box::new(error) }
- }
- #[cfg(not(feature="std"))] {
- Error { code: error.code() }
- }
- }
-}
-
-#[cfg(feature="std")]
-impl std::error::Error for Error {
- #[inline]
- fn source(&self) -> Option<&(dyn std::error::Error + 'static)> {
- self.inner.source()
- }
-}
-
-#[cfg(feature="std")]
-impl From<Error> for std::io::Error {
- #[inline]
- fn from(error: Error) -> Self {
- if let Some(code) = error.raw_os_error() {
- std::io::Error::from_raw_os_error(code)
- } else {
- std::io::Error::new(std::io::ErrorKind::Other, error)
- }
- }
-}
-
-#[cfg(feature="std")]
-#[derive(Debug, Copy, Clone)]
-struct ErrorCode(NonZeroU32);
-
-#[cfg(feature="std")]
-impl fmt::Display for ErrorCode {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "error code {}", self.0)
- }
-}
-
-#[cfg(feature="std")]
-impl std::error::Error for ErrorCode {}
diff --git a/rand/rand_core/src/impls.rs b/rand/rand_core/src/impls.rs
deleted file mode 100644
index dee4ed1..0000000
--- a/rand/rand_core/src/impls.rs
+++ /dev/null
@@ -1,158 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Helper functions for implementing `RngCore` functions.
-//!
-//! For cross-platform reproducibility, these functions all use Little Endian:
-//! least-significant part first. For example, `next_u64_via_u32` takes `u32`
-//! values `x, y`, then outputs `(y << 32) | x`. To implement `next_u32`
-//! from `next_u64` in little-endian order, one should use `next_u64() as u32`.
-//!
-//! Byte-swapping (like the std `to_le` functions) is only needed to convert
-//! to/from byte sequences, and since its purpose is reproducibility,
-//! non-reproducible sources (e.g. `OsRng`) need not bother with it.
-
-use core::ptr::copy_nonoverlapping;
-use core::slice;
-use core::cmp::min;
-use core::mem::size_of;
-use crate::RngCore;
-
-
-/// Implement `next_u64` via `next_u32`, little-endian order.
-pub fn next_u64_via_u32<R: RngCore + ?Sized>(rng: &mut R) -> u64 {
- // Use LE; we explicitly generate one value before the next.
- let x = u64::from(rng.next_u32());
- let y = u64::from(rng.next_u32());
- (y << 32) | x
-}
-
-/// Implement `fill_bytes` via `next_u64` and `next_u32`, little-endian order.
-///
-/// The fastest way to fill a slice is usually to work as long as possible with
-/// integers. That is why this method mostly uses `next_u64`, and only when
-/// there are 4 or less bytes remaining at the end of the slice it uses
-/// `next_u32` once.
-pub fn fill_bytes_via_next<R: RngCore + ?Sized>(rng: &mut R, dest: &mut [u8]) {
- let mut left = dest;
- while left.len() >= 8 {
- let (l, r) = {left}.split_at_mut(8);
- left = r;
- let chunk: [u8; 8] = rng.next_u64().to_le_bytes();
- l.copy_from_slice(&chunk);
- }
- let n = left.len();
- if n > 4 {
- let chunk: [u8; 8] = rng.next_u64().to_le_bytes();
- left.copy_from_slice(&chunk[..n]);
- } else if n > 0 {
- let chunk: [u8; 4] = rng.next_u32().to_le_bytes();
- left.copy_from_slice(&chunk[..n]);
- }
-}
-
-macro_rules! impl_uint_from_fill {
- ($rng:expr, $ty:ty, $N:expr) => ({
- debug_assert!($N == size_of::<$ty>());
-
- let mut int: $ty = 0;
- unsafe {
- let ptr = &mut int as *mut $ty as *mut u8;
- let slice = slice::from_raw_parts_mut(ptr, $N);
- $rng.fill_bytes(slice);
- }
- int
- });
-}
-
-macro_rules! fill_via_chunks {
- ($src:expr, $dst:expr, $ty:ty, $size:expr) => ({
- let chunk_size_u8 = min($src.len() * $size, $dst.len());
- let chunk_size = (chunk_size_u8 + $size - 1) / $size;
- if cfg!(target_endian="little") {
- unsafe {
- copy_nonoverlapping(
- $src.as_ptr() as *const u8,
- $dst.as_mut_ptr(),
- chunk_size_u8);
- }
- } else {
- for (&n, chunk) in $src.iter().zip($dst.chunks_mut($size)) {
- let tmp = n.to_le();
- let src_ptr = &tmp as *const $ty as *const u8;
- unsafe {
- copy_nonoverlapping(src_ptr,
- chunk.as_mut_ptr(),
- chunk.len());
- }
- }
- }
-
- (chunk_size, chunk_size_u8)
- });
-}
-
-/// Implement `fill_bytes` by reading chunks from the output buffer of a block
-/// based RNG.
-///
-/// The return values are `(consumed_u32, filled_u8)`.
-///
-/// `filled_u8` is the number of filled bytes in `dest`, which may be less than
-/// the length of `dest`.
-/// `consumed_u32` is the number of words consumed from `src`, which is the same
-/// as `filled_u8 / 4` rounded up.
-///
-/// # Example
-/// (from `IsaacRng`)
-///
-/// ```ignore
-/// fn fill_bytes(&mut self, dest: &mut [u8]) {
-/// let mut read_len = 0;
-/// while read_len < dest.len() {
-/// if self.index >= self.rsl.len() {
-/// self.isaac();
-/// }
-///
-/// let (consumed_u32, filled_u8) =
-/// impls::fill_via_u32_chunks(&mut self.rsl[self.index..],
-/// &mut dest[read_len..]);
-///
-/// self.index += consumed_u32;
-/// read_len += filled_u8;
-/// }
-/// }
-/// ```
-pub fn fill_via_u32_chunks(src: &[u32], dest: &mut [u8]) -> (usize, usize) {
- fill_via_chunks!(src, dest, u32, 4)
-}
-
-/// Implement `fill_bytes` by reading chunks from the output buffer of a block
-/// based RNG.
-///
-/// The return values are `(consumed_u64, filled_u8)`.
-/// `filled_u8` is the number of filled bytes in `dest`, which may be less than
-/// the length of `dest`.
-/// `consumed_u64` is the number of words consumed from `src`, which is the same
-/// as `filled_u8 / 8` rounded up.
-///
-/// See `fill_via_u32_chunks` for an example.
-pub fn fill_via_u64_chunks(src: &[u64], dest: &mut [u8]) -> (usize, usize) {
- fill_via_chunks!(src, dest, u64, 8)
-}
-
-/// Implement `next_u32` via `fill_bytes`, little-endian order.
-pub fn next_u32_via_fill<R: RngCore + ?Sized>(rng: &mut R) -> u32 {
- impl_uint_from_fill!(rng, u32, 4)
-}
-
-/// Implement `next_u64` via `fill_bytes`, little-endian order.
-pub fn next_u64_via_fill<R: RngCore + ?Sized>(rng: &mut R) -> u64 {
- impl_uint_from_fill!(rng, u64, 8)
-}
-
-// TODO: implement tests for the above
diff --git a/rand/rand_core/src/le.rs b/rand/rand_core/src/le.rs
deleted file mode 100644
index 266651f..0000000
--- a/rand/rand_core/src/le.rs
+++ /dev/null
@@ -1,68 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Little-Endian utilities
-//!
-//! Little-Endian order has been chosen for internal usage; this makes some
-//! useful functions available.
-
-use core::ptr;
-
-macro_rules! read_slice {
- ($src:expr, $dst:expr, $size:expr, $which:ident) => {{
- assert_eq!($src.len(), $size * $dst.len());
-
- unsafe {
- ptr::copy_nonoverlapping(
- $src.as_ptr(),
- $dst.as_mut_ptr() as *mut u8,
- $src.len());
- }
- for v in $dst.iter_mut() {
- *v = v.$which();
- }
- }};
-}
-
-/// Reads unsigned 32 bit integers from `src` into `dst`.
-/// Borrowed from the `byteorder` crate.
-#[inline]
-pub fn read_u32_into(src: &[u8], dst: &mut [u32]) {
- read_slice!(src, dst, 4, to_le);
-}
-
-/// Reads unsigned 64 bit integers from `src` into `dst`.
-/// Borrowed from the `byteorder` crate.
-#[inline]
-pub fn read_u64_into(src: &[u8], dst: &mut [u64]) {
- read_slice!(src, dst, 8, to_le);
-}
-
-#[test]
-fn test_read() {
- let bytes = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16];
-
- let mut buf = [0u32; 4];
- read_u32_into(&bytes, &mut buf);
- assert_eq!(buf[0], 0x04030201);
- assert_eq!(buf[3], 0x100F0E0D);
-
- let mut buf = [0u32; 3];
- read_u32_into(&bytes[1..13], &mut buf); // unaligned
- assert_eq!(buf[0], 0x05040302);
- assert_eq!(buf[2], 0x0D0C0B0A);
-
- let mut buf = [0u64; 2];
- read_u64_into(&bytes, &mut buf);
- assert_eq!(buf[0], 0x0807060504030201);
- assert_eq!(buf[1], 0x100F0E0D0C0B0A09);
-
- let mut buf = [0u64; 1];
- read_u64_into(&bytes[7..15], &mut buf); // unaligned
- assert_eq!(buf[0], 0x0F0E0D0C0B0A0908);
-}
diff --git a/rand/rand_core/src/lib.rs b/rand/rand_core/src/lib.rs
deleted file mode 100644
index d8e0189..0000000
--- a/rand/rand_core/src/lib.rs
+++ /dev/null
@@ -1,492 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2017-2018 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Random number generation traits
-//!
-//! This crate is mainly of interest to crates publishing implementations of
-//! [`RngCore`]. Other users are encouraged to use the [`rand`] crate instead
-//! which re-exports the main traits and error types.
-//!
-//! [`RngCore`] is the core trait implemented by algorithmic pseudo-random number
-//! generators and external random-number sources.
-//!
-//! [`SeedableRng`] is an extension trait for construction from fixed seeds and
-//! other random number generators.
-//!
-//! [`Error`] is provided for error-handling. It is safe to use in `no_std`
-//! environments.
-//!
-//! The [`impls`] and [`le`] sub-modules include a few small functions to assist
-//! implementation of [`RngCore`].
-//!
-//! [`rand`]: https://docs.rs/rand
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
- html_favicon_url = "https://www.rust-lang.org/favicon.ico",
- html_root_url = "https://rust-random.github.io/rand/")]
-
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-#![doc(test(attr(allow(unused_variables), deny(warnings))))]
-
-#![allow(clippy::unreadable_literal)]
-
-#![cfg_attr(not(feature="std"), no_std)]
-
-
-use core::default::Default;
-use core::convert::AsMut;
-use core::ptr::copy_nonoverlapping;
-
-#[cfg(all(feature="alloc", not(feature="std")))] extern crate alloc;
-#[cfg(all(feature="alloc", not(feature="std")))] use alloc::boxed::Box;
-
-pub use error::Error;
-#[cfg(feature="getrandom")] pub use os::OsRng;
-
-
-mod error;
-pub mod block;
-pub mod impls;
-pub mod le;
-#[cfg(feature="getrandom")] mod os;
-
-
-/// The core of a random number generator.
-///
-/// This trait encapsulates the low-level functionality common to all
-/// generators, and is the "back end", to be implemented by generators.
-/// End users should normally use the `Rng` trait from the [`rand`] crate,
-/// which is automatically implemented for every type implementing `RngCore`.
-///
-/// Three different methods for generating random data are provided since the
-/// optimal implementation of each is dependent on the type of generator. There
-/// is no required relationship between the output of each; e.g. many
-/// implementations of [`fill_bytes`] consume a whole number of `u32` or `u64`
-/// values and drop any remaining unused bytes.
-///
-/// The [`try_fill_bytes`] method is a variant of [`fill_bytes`] allowing error
-/// handling; it is not deemed sufficiently useful to add equivalents for
-/// [`next_u32`] or [`next_u64`] since the latter methods are almost always used
-/// with algorithmic generators (PRNGs), which are normally infallible.
-///
-/// Algorithmic generators implementing [`SeedableRng`] should normally have
-/// *portable, reproducible* output, i.e. fix Endianness when converting values
-/// to avoid platform differences, and avoid making any changes which affect
-/// output (except by communicating that the release has breaking changes).
-///
-/// Typically implementators will implement only one of the methods available
-/// in this trait directly, then use the helper functions from the
-/// [`impls`] module to implement the other methods.
-///
-/// It is recommended that implementations also implement:
-///
-/// - `Debug` with a custom implementation which *does not* print any internal
-/// state (at least, [`CryptoRng`]s should not risk leaking state through
-/// `Debug`).
-/// - `Serialize` and `Deserialize` (from Serde), preferably making Serde
-/// support optional at the crate level in PRNG libs.
-/// - `Clone`, if possible.
-/// - *never* implement `Copy` (accidental copies may cause repeated values).
-/// - *do not* implement `Default` for pseudorandom generators, but instead
-/// implement [`SeedableRng`], to guide users towards proper seeding.
-/// External / hardware RNGs can choose to implement `Default`.
-/// - `Eq` and `PartialEq` could be implemented, but are probably not useful.
-///
-/// # Example
-///
-/// A simple example, obviously not generating very *random* output:
-///
-/// ```
-/// #![allow(dead_code)]
-/// use rand_core::{RngCore, Error, impls};
-///
-/// struct CountingRng(u64);
-///
-/// impl RngCore for CountingRng {
-/// fn next_u32(&mut self) -> u32 {
-/// self.next_u64() as u32
-/// }
-///
-/// fn next_u64(&mut self) -> u64 {
-/// self.0 += 1;
-/// self.0
-/// }
-///
-/// fn fill_bytes(&mut self, dest: &mut [u8]) {
-/// impls::fill_bytes_via_next(self, dest)
-/// }
-///
-/// fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
-/// Ok(self.fill_bytes(dest))
-/// }
-/// }
-/// ```
-///
-/// [`rand`]: https://docs.rs/rand
-/// [`try_fill_bytes`]: RngCore::try_fill_bytes
-/// [`fill_bytes`]: RngCore::fill_bytes
-/// [`next_u32`]: RngCore::next_u32
-/// [`next_u64`]: RngCore::next_u64
-pub trait RngCore {
- /// Return the next random `u32`.
- ///
- /// RNGs must implement at least one method from this trait directly. In
- /// the case this method is not implemented directly, it can be implemented
- /// using `self.next_u64() as u32` or via
- /// [`fill_bytes`](impls::next_u32_via_fill).
- fn next_u32(&mut self) -> u32;
-
- /// Return the next random `u64`.
- ///
- /// RNGs must implement at least one method from this trait directly. In
- /// the case this method is not implemented directly, it can be implemented
- /// via [`next_u32`](impls::next_u64_via_u32) or via
- /// [`fill_bytes`](impls::next_u64_via_fill).
- fn next_u64(&mut self) -> u64;
-
- /// Fill `dest` with random data.
- ///
- /// RNGs must implement at least one method from this trait directly. In
- /// the case this method is not implemented directly, it can be implemented
- /// via [`next_u*`](impls::fill_bytes_via_next) or
- /// via [`try_fill_bytes`](RngCore::try_fill_bytes); if this generator can
- /// fail the implementation must choose how best to handle errors here
- /// (e.g. panic with a descriptive message or log a warning and retry a few
- /// times).
- ///
- /// This method should guarantee that `dest` is entirely filled
- /// with new data, and may panic if this is impossible
- /// (e.g. reading past the end of a file that is being used as the
- /// source of randomness).
- fn fill_bytes(&mut self, dest: &mut [u8]);
-
- /// Fill `dest` entirely with random data.
- ///
- /// This is the only method which allows an RNG to report errors while
- /// generating random data thus making this the primary method implemented
- /// by external (true) RNGs (e.g. `OsRng`) which can fail. It may be used
- /// directly to generate keys and to seed (infallible) PRNGs.
- ///
- /// Other than error handling, this method is identical to [`fill_bytes`];
- /// thus this may be implemented using `Ok(self.fill_bytes(dest))` or
- /// `fill_bytes` may be implemented with
- /// `self.try_fill_bytes(dest).unwrap()` or more specific error handling.
- ///
- /// [`fill_bytes`]: RngCore::fill_bytes
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error>;
-}
-
-/// A marker trait used to indicate that an [`RngCore`] or [`BlockRngCore`]
-/// implementation is supposed to be cryptographically secure.
-///
-/// *Cryptographically secure generators*, also known as *CSPRNGs*, should
-/// satisfy an additional properties over other generators: given the first
-/// *k* bits of an algorithm's output
-/// sequence, it should not be possible using polynomial-time algorithms to
-/// predict the next bit with probability significantly greater than 50%.
-///
-/// Some generators may satisfy an additional property, however this is not
-/// required by this trait: if the CSPRNG's state is revealed, it should not be
-/// computationally-feasible to reconstruct output prior to this. Some other
-/// generators allow backwards-computation and are consided *reversible*.
-///
-/// Note that this trait is provided for guidance only and cannot guarantee
-/// suitability for cryptographic applications. In general it should only be
-/// implemented for well-reviewed code implementing well-regarded algorithms.
-///
-/// Note also that use of a `CryptoRng` does not protect against other
-/// weaknesses such as seeding from a weak entropy source or leaking state.
-///
-/// [`BlockRngCore`]: block::BlockRngCore
-pub trait CryptoRng {}
-
-/// A random number generator that can be explicitly seeded.
-///
-/// This trait encapsulates the low-level functionality common to all
-/// pseudo-random number generators (PRNGs, or algorithmic generators).
-///
-/// [`rand`]: https://docs.rs/rand
-pub trait SeedableRng: Sized {
- /// Seed type, which is restricted to types mutably-dereferencable as `u8`
- /// arrays (we recommend `[u8; N]` for some `N`).
- ///
- /// It is recommended to seed PRNGs with a seed of at least circa 100 bits,
- /// which means an array of `[u8; 12]` or greater to avoid picking RNGs with
- /// partially overlapping periods.
- ///
- /// For cryptographic RNG's a seed of 256 bits is recommended, `[u8; 32]`.
- ///
- ///
- /// # Implementing `SeedableRng` for RNGs with large seeds
- ///
- /// Note that the required traits `core::default::Default` and
- /// `core::convert::AsMut<u8>` are not implemented for large arrays
- /// `[u8; N]` with `N` > 32. To be able to implement the traits required by
- /// `SeedableRng` for RNGs with such large seeds, the newtype pattern can be
- /// used:
- ///
- /// ```
- /// use rand_core::SeedableRng;
- ///
- /// const N: usize = 64;
- /// pub struct MyRngSeed(pub [u8; N]);
- /// pub struct MyRng(MyRngSeed);
- ///
- /// impl Default for MyRngSeed {
- /// fn default() -> MyRngSeed {
- /// MyRngSeed([0; N])
- /// }
- /// }
- ///
- /// impl AsMut<[u8]> for MyRngSeed {
- /// fn as_mut(&mut self) -> &mut [u8] {
- /// &mut self.0
- /// }
- /// }
- ///
- /// impl SeedableRng for MyRng {
- /// type Seed = MyRngSeed;
- ///
- /// fn from_seed(seed: MyRngSeed) -> MyRng {
- /// MyRng(seed)
- /// }
- /// }
- /// ```
- type Seed: Sized + Default + AsMut<[u8]>;
-
- /// Create a new PRNG using the given seed.
- ///
- /// PRNG implementations are allowed to assume that bits in the seed are
- /// well distributed. That means usually that the number of one and zero
- /// bits are roughly equal, and values like 0, 1 and (size - 1) are unlikely.
- /// Note that many non-cryptographic PRNGs will show poor quality output
- /// if this is not adhered to. If you wish to seed from simple numbers, use
- /// `seed_from_u64` instead.
- ///
- /// All PRNG implementations should be reproducible unless otherwise noted:
- /// given a fixed `seed`, the same sequence of output should be produced
- /// on all runs, library versions and architectures (e.g. check endianness).
- /// Any "value-breaking" changes to the generator should require bumping at
- /// least the minor version and documentation of the change.
- ///
- /// It is not required that this function yield the same state as a
- /// reference implementation of the PRNG given equivalent seed; if necessary
- /// another constructor replicating behaviour from a reference
- /// implementation can be added.
- ///
- /// PRNG implementations should make sure `from_seed` never panics. In the
- /// case that some special values (like an all zero seed) are not viable
- /// seeds it is preferable to map these to alternative constant value(s),
- /// for example `0xBAD5EEDu32` or `0x0DDB1A5E5BAD5EEDu64` ("odd biases? bad
- /// seed"). This is assuming only a small number of values must be rejected.
- fn from_seed(seed: Self::Seed) -> Self;
-
- /// Create a new PRNG using a `u64` seed.
- ///
- /// This is a convenience-wrapper around `from_seed` to allow construction
- /// of any `SeedableRng` from a simple `u64` value. It is designed such that
- /// low Hamming Weight numbers like 0 and 1 can be used and should still
- /// result in good, independent seeds to the PRNG which is returned.
- ///
- /// This **is not suitable for cryptography**, as should be clear given that
- /// the input size is only 64 bits.
- ///
- /// Implementations for PRNGs *may* provide their own implementations of
- /// this function, but the default implementation should be good enough for
- /// all purposes. *Changing* the implementation of this function should be
- /// considered a value-breaking change.
- fn seed_from_u64(mut state: u64) -> Self {
- // We use PCG32 to generate a u32 sequence, and copy to the seed
- const MUL: u64 = 6364136223846793005;
- const INC: u64 = 11634580027462260723;
-
- let mut seed = Self::Seed::default();
- for chunk in seed.as_mut().chunks_mut(4) {
- // We advance the state first (to get away from the input value,
- // in case it has low Hamming Weight).
- state = state.wrapping_mul(MUL).wrapping_add(INC);
-
- // Use PCG output function with to_le to generate x:
- let xorshifted = (((state >> 18) ^ state) >> 27) as u32;
- let rot = (state >> 59) as u32;
- let x = xorshifted.rotate_right(rot).to_le();
-
- unsafe {
- let p = &x as *const u32 as *const u8;
- copy_nonoverlapping(p, chunk.as_mut_ptr(), chunk.len());
- }
- }
-
- Self::from_seed(seed)
- }
-
- /// Create a new PRNG seeded from another `Rng`.
- ///
- /// This may be useful when needing to rapidly seed many PRNGs from a master
- /// PRNG, and to allow forking of PRNGs. It may be considered deterministic.
- ///
- /// The master PRNG should be at least as high quality as the child PRNGs.
- /// When seeding non-cryptographic child PRNGs, we recommend using a
- /// different algorithm for the master PRNG (ideally a CSPRNG) to avoid
- /// correlations between the child PRNGs. If this is not possible (e.g.
- /// forking using small non-crypto PRNGs) ensure that your PRNG has a good
- /// mixing function on the output or consider use of a hash function with
- /// `from_seed`.
- ///
- /// Note that seeding `XorShiftRng` from another `XorShiftRng` provides an
- /// extreme example of what can go wrong: the new PRNG will be a clone
- /// of the parent.
- ///
- /// PRNG implementations are allowed to assume that a good RNG is provided
- /// for seeding, and that it is cryptographically secure when appropriate.
- /// As of `rand` 0.7 / `rand_core` 0.5, implementations overriding this
- /// method should ensure the implementation satisfies reproducibility
- /// (in prior versions this was not required).
- ///
- /// [`rand`]: https://docs.rs/rand
- /// [`rand_os`]: https://docs.rs/rand_os
- fn from_rng<R: RngCore>(mut rng: R) -> Result<Self, Error> {
- let mut seed = Self::Seed::default();
- rng.try_fill_bytes(seed.as_mut())?;
- Ok(Self::from_seed(seed))
- }
-
- /// Creates a new instance of the RNG seeded via [`getrandom`].
- ///
- /// This method is the recommended way to construct non-deterministic PRNGs
- /// since it is convenient and secure.
- ///
- /// In case the overhead of using [`getrandom`] to seed *many* PRNGs is an
- /// issue, one may prefer to seed from a local PRNG, e.g.
- /// `from_rng(thread_rng()).unwrap()`.
- ///
- /// # Panics
- ///
- /// If [`getrandom`] is unable to provide secure entropy this method will panic.
- ///
- /// [`getrandom`]: https://docs.rs/getrandom
- #[cfg(feature="getrandom")]
- fn from_entropy() -> Self {
- let mut seed = Self::Seed::default();
- if let Err(err) = getrandom::getrandom(seed.as_mut()) {
- panic!("from_entropy failed: {}", err);
- }
- Self::from_seed(seed)
- }
-}
-
-// Implement `RngCore` for references to an `RngCore`.
-// Force inlining all functions, so that it is up to the `RngCore`
-// implementation and the optimizer to decide on inlining.
-impl<'a, R: RngCore + ?Sized> RngCore for &'a mut R {
- #[inline(always)]
- fn next_u32(&mut self) -> u32 {
- (**self).next_u32()
- }
-
- #[inline(always)]
- fn next_u64(&mut self) -> u64 {
- (**self).next_u64()
- }
-
- #[inline(always)]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- (**self).fill_bytes(dest)
- }
-
- #[inline(always)]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- (**self).try_fill_bytes(dest)
- }
-}
-
-// Implement `RngCore` for boxed references to an `RngCore`.
-// Force inlining all functions, so that it is up to the `RngCore`
-// implementation and the optimizer to decide on inlining.
-#[cfg(feature="alloc")]
-impl<R: RngCore + ?Sized> RngCore for Box<R> {
- #[inline(always)]
- fn next_u32(&mut self) -> u32 {
- (**self).next_u32()
- }
-
- #[inline(always)]
- fn next_u64(&mut self) -> u64 {
- (**self).next_u64()
- }
-
- #[inline(always)]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- (**self).fill_bytes(dest)
- }
-
- #[inline(always)]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- (**self).try_fill_bytes(dest)
- }
-}
-
-#[cfg(feature="std")]
-impl std::io::Read for dyn RngCore {
- fn read(&mut self, buf: &mut [u8]) -> Result<usize, std::io::Error> {
- self.try_fill_bytes(buf)?;
- Ok(buf.len())
- }
-}
-
-// Implement `CryptoRng` for references to an `CryptoRng`.
-impl<'a, R: CryptoRng + ?Sized> CryptoRng for &'a mut R {}
-
-// Implement `CryptoRng` for boxed references to an `CryptoRng`.
-#[cfg(feature="alloc")]
-impl<R: CryptoRng + ?Sized> CryptoRng for Box<R> {}
-
-#[cfg(test)]
-mod test {
- use super::*;
-
- #[test]
- fn test_seed_from_u64() {
- struct SeedableNum(u64);
- impl SeedableRng for SeedableNum {
- type Seed = [u8; 8];
- fn from_seed(seed: Self::Seed) -> Self {
- let mut x = [0u64; 1];
- le::read_u64_into(&seed, &mut x);
- SeedableNum(x[0])
- }
- }
-
- const N: usize = 8;
- const SEEDS: [u64; N] = [0u64, 1, 2, 3, 4, 8, 16, -1i64 as u64];
- let mut results = [0u64; N];
- for (i, seed) in SEEDS.iter().enumerate() {
- let SeedableNum(x) = SeedableNum::seed_from_u64(*seed);
- results[i] = x;
- }
-
- for (i1, r1) in results.iter().enumerate() {
- let weight = r1.count_ones();
- // This is the binomial distribution B(64, 0.5), so chance of
- // weight < 20 is binocdf(19, 64, 0.5) = 7.8e-4, and same for
- // weight > 44.
- assert!(weight >= 20 && weight <= 44);
-
- for (i2, r2) in results.iter().enumerate() {
- if i1 == i2 { continue; }
- let diff_weight = (r1 ^ r2).count_ones();
- assert!(diff_weight >= 20);
- }
- }
-
- // value-breakage test:
- assert_eq!(results[0], 5029875928683246316);
- }
-}
diff --git a/rand/rand_core/src/os.rs b/rand/rand_core/src/os.rs
deleted file mode 100644
index fc23a57..0000000
--- a/rand/rand_core/src/os.rs
+++ /dev/null
@@ -1,85 +0,0 @@
-// Copyright 2019 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Interface to the random number generator of the operating system.
-// Note: keep this code in sync with the rand_os crate!
-
-use getrandom::getrandom;
-use crate::{CryptoRng, RngCore, Error, impls};
-
-/// A random number generator that retrieves randomness from from the
-/// operating system.
-///
-/// This is a zero-sized struct. It can be freely constructed with `OsRng`.
-///
-/// The implementation is provided by the [getrandom] crate. Refer to
-/// [getrandom] documentation for details.
-///
-/// This struct is only available when specifying the crate feature `getrandom`
-/// or `std`. When using the `rand` lib, it is also available as `rand::rngs::OsRng`.
-///
-/// # Blocking and error handling
-///
-/// It is possible that when used during early boot the first call to `OsRng`
-/// will block until the system's RNG is initialised. It is also possible
-/// (though highly unlikely) for `OsRng` to fail on some platforms, most
-/// likely due to system mis-configuration.
-///
-/// After the first successful call, it is highly unlikely that failures or
-/// significant delays will occur (although performance should be expected to
-/// be much slower than a user-space PRNG).
-///
-/// # Usage example
-/// ```
-/// use rand_core::{RngCore, OsRng};
-///
-/// let mut key = [0u8; 16];
-/// OsRng.fill_bytes(&mut key);
-/// let random_u64 = OsRng.next_u64();
-/// ```
-///
-/// [getrandom]: https://crates.io/crates/getrandom
-#[derive(Clone, Copy, Debug, Default)]
-pub struct OsRng;
-
-impl CryptoRng for OsRng {}
-
-impl RngCore for OsRng {
- fn next_u32(&mut self) -> u32 {
- impls::next_u32_via_fill(self)
- }
-
- fn next_u64(&mut self) -> u64 {
- impls::next_u64_via_fill(self)
- }
-
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- if let Err(e) = self.try_fill_bytes(dest) {
- panic!("Error: {}", e);
- }
- }
-
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- getrandom(dest)?;
- Ok(())
- }
-}
-
-#[test]
-fn test_os_rng() {
- let x = OsRng.next_u64();
- let y = OsRng.next_u64();
- assert!(x != 0);
- assert!(x != y);
-}
-
-#[test]
-fn test_construction() {
- let mut rng = OsRng::default();
- assert!(rng.next_u64() != 0);
-}
diff --git a/rand/rand_distr/CHANGELOG.md b/rand/rand_distr/CHANGELOG.md
deleted file mode 100644
index 376bb95..0000000
--- a/rand/rand_distr/CHANGELOG.md
+++ /dev/null
@@ -1,21 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.2.1] - 2019-06-29
-- Update dependency to support Rand 0.7
-- Doc link fixes
-
-## [0.2.0] - 2019-06-06
-- Remove `new` constructors for zero-sized types
-- Add Pert distribution
-- Fix undefined behavior in `Poisson`
-- Make all distributions return `Result`s instead of panicking
-- Implement `f32` support for most distributions
-- Rename `UnitSphereSurface` to `UnitSphere`
-- Implement `UnitBall` and `UnitDisc`
-
-## [0.1.0] - 2019-06-06
-Initial release. This is equivalent to the code in `rand` 0.6.5.
diff --git a/rand/rand_distr/COPYRIGHT b/rand/rand_distr/COPYRIGHT
deleted file mode 100644
index 468d907..0000000
--- a/rand/rand_distr/COPYRIGHT
+++ /dev/null
@@ -1,12 +0,0 @@
-Copyrights in the Rand project are retained by their contributors. No
-copyright assignment is required to contribute to the Rand project.
-
-For full authorship information, see the version control history.
-
-Except as otherwise noted (below and/or in individual files), Rand is
-licensed under the Apache License, Version 2.0 <LICENSE-APACHE> or
-<http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-<LICENSE-MIT> or <http://opensource.org/licenses/MIT>, at your option.
-
-The Rand project includes code from the Rust project
-published under these same licenses.
diff --git a/rand/rand_distr/Cargo.toml b/rand/rand_distr/Cargo.toml
deleted file mode 100644
index 315a5b0..0000000
--- a/rand/rand_distr/Cargo.toml
+++ /dev/null
@@ -1,27 +0,0 @@
-[package]
-name = "rand_distr"
-version = "0.2.1"
-authors = ["The Rand Project Developers"]
-license = "MIT OR Apache-2.0"
-readme = "README.md"
-repository = "https://github.com/rust-random/rand"
-documentation = "https://rust-random.github.io/rand/rand_distr/"
-homepage = "https://crates.io/crates/rand_distr"
-description = """
-Sampling from random number distributions
-"""
-keywords = ["random", "rng", "distribution", "probability"]
-categories = ["algorithms"]
-edition = "2018"
-
-[badges]
-travis-ci = { repository = "rust-random/rand" }
-appveyor = { repository = "rust-random/rand" }
-
-[dependencies]
-rand = { path = "..", version = "0.7" }
-
-[dev-dependencies]
-rand_pcg = { version = "0.2", path = "../rand_pcg" }
-# Histogram implementation for testing uniformity
-average = "0.9.2"
diff --git a/rand/rand_distr/LICENSE-APACHE b/rand/rand_distr/LICENSE-APACHE
deleted file mode 100644
index 17d7468..0000000
--- a/rand/rand_distr/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
- Apache License
- Version 2.0, January 2004
- https://www.apache.org/licenses/
-
-TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
-
-1. Definitions.
-
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- by You to the Licensor shall be under the terms and conditions of
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- Notwithstanding the above, nothing herein shall supersede or modify
- the terms of any separate license agreement you may have executed
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diff --git a/rand/rand_distr/LICENSE-MIT b/rand/rand_distr/LICENSE-MIT
deleted file mode 100644
index cf65607..0000000
--- a/rand/rand_distr/LICENSE-MIT
+++ /dev/null
@@ -1,25 +0,0 @@
-Copyright 2018 Developers of the Rand project
-
-Permission is hereby granted, free of charge, to any
-person obtaining a copy of this software and associated
-documentation files (the "Software"), to deal in the
-Software without restriction, including without
-limitation the rights to use, copy, modify, merge,
-publish, distribute, sublicense, and/or sell copies of
-the Software, and to permit persons to whom the Software
-is furnished to do so, subject to the following
-conditions:
-
-The above copyright notice and this permission notice
-shall be included in all copies or substantial portions
-of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF
-ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED
-TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
-PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
-SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
-IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-DEALINGS IN THE SOFTWARE.
diff --git a/rand/rand_distr/README.md b/rand/rand_distr/README.md
deleted file mode 100644
index 68acd2f..0000000
--- a/rand/rand_distr/README.md
+++ /dev/null
@@ -1,42 +0,0 @@
-# rand_distr
-
-[](https://travis-ci.org/rust-random/rand)
-[](https://ci.appveyor.com/project/rust-random/rand)
-[](https://crates.io/crates/rand_distr)
-[[](https://rust-random.github.io/book/)
-[](https://rust-random.github.io/rand/rand_distr)
-[](https://docs.rs/rand_distr)
-[](https://github.com/rust-random/rand#rust-version-requirements)
-
-Implements a full suite of random number distributions sampling routines.
-
-This crate is a super-set of the [rand::distributions] module, including support
-for sampling from Beta, Binomial, Cauchy, ChiSquared, Dirichlet, exponential,
-Fisher F, Gamma, Log-normal, Normal, Pareto, Poisson, StudentT, Triangular and
-Weibull distributions, as well as sampling points from the unit circle and unit
-sphere surface.
-
-It is worth mentioning the [statrs] crate which provides similar functionality
-along with various support functions, including PDF and CDF computation. In
-contrast, this `rand_distr` crate focusses on sampling from distributions.
-
-Unlike most Rand crates, `rand_distr` does not currently support `no_std`.
-
-Links:
-
-- [API documentation (master)](https://rust-random.github.io/rand/rand_distr)
-- [API documentation (docs.rs)](https://docs.rs/rand_distr)
-- [Changelog](CHANGELOG.md)
-- [The Rand project](https://github.com/rust-random/rand)
-
-
-[statrs]: https://github.com/boxtown/statrs
-[rand::distributions]: https://rust-random.github.io/rand/rand/distributions/index.html
-
-## License
-
-`rand_distr` is distributed under the terms of both the MIT license and the
-Apache License (Version 2.0).
-
-See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT), and
-[COPYRIGHT](COPYRIGHT) for details.
diff --git a/rand/rand_distr/benches/distributions.rs b/rand/rand_distr/benches/distributions.rs
deleted file mode 100644
index 63bde36..0000000
--- a/rand/rand_distr/benches/distributions.rs
+++ /dev/null
@@ -1,316 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#![feature(test)]
-
-const RAND_BENCH_N: u64 = 1000;
-
-use std::mem::size_of;
-use std::num::{NonZeroU8, NonZeroU16, NonZeroU32, NonZeroU64, NonZeroU128};
-use test::Bencher;
-use std::time::Duration;
-
-use rand::prelude::*;
-use rand_distr::{*, weighted::WeightedIndex};
-
-// At this time, distributions are optimised for 64-bit platforms.
-use rand_pcg::Pcg64Mcg;
-
-macro_rules! distr_int {
- ($fnn:ident, $ty:ty, $distr:expr) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_entropy();
- let distr = $distr;
-
- b.iter(|| {
- let mut accum = 0 as $ty;
- for _ in 0..RAND_BENCH_N {
- let x: $ty = distr.sample(&mut rng);
- accum = accum.wrapping_add(x);
- }
- accum
- });
- b.bytes = size_of::<$ty>() as u64 * RAND_BENCH_N;
- }
- }
-}
-
-macro_rules! distr_nz_int {
- ($fnn:ident, $tynz:ty, $ty:ty, $distr:expr) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_entropy();
- let distr = $distr;
-
- b.iter(|| {
- let mut accum = 0 as $ty;
- for _ in 0..RAND_BENCH_N {
- let x: $tynz = distr.sample(&mut rng);
- accum = accum.wrapping_add(x.get());
- }
- accum
- });
- b.bytes = size_of::<$ty>() as u64 * RAND_BENCH_N;
- }
- }
-}
-
-macro_rules! distr_float {
- ($fnn:ident, $ty:ty, $distr:expr) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_entropy();
- let distr = $distr;
-
- b.iter(|| {
- let mut accum = 0.0;
- for _ in 0..RAND_BENCH_N {
- let x: $ty = distr.sample(&mut rng);
- accum += x;
- }
- accum
- });
- b.bytes = size_of::<$ty>() as u64 * RAND_BENCH_N;
- }
- }
-}
-
-macro_rules! distr_duration {
- ($fnn:ident, $distr:expr) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_entropy();
- let distr = $distr;
-
- b.iter(|| {
- let mut accum = Duration::new(0, 0);
- for _ in 0..RAND_BENCH_N {
- let x: Duration = distr.sample(&mut rng);
- accum = accum.checked_add(x).unwrap_or(Duration::new(u64::max_value(), 999_999_999));
- }
- accum
- });
- b.bytes = size_of::<Duration>() as u64 * RAND_BENCH_N;
- }
- }
-}
-
-macro_rules! distr {
- ($fnn:ident, $ty:ty, $distr:expr) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_entropy();
- let distr = $distr;
-
- b.iter(|| {
- let mut accum = 0u32;
- for _ in 0..RAND_BENCH_N {
- let x: $ty = distr.sample(&mut rng);
- accum = accum.wrapping_add(x as u32);
- }
- accum
- });
- b.bytes = size_of::<$ty>() as u64 * RAND_BENCH_N;
- }
- }
-}
-
-macro_rules! distr_arr {
- ($fnn:ident, $ty:ty, $distr:expr) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_entropy();
- let distr = $distr;
-
- b.iter(|| {
- let mut accum = 0u32;
- for _ in 0..RAND_BENCH_N {
- let x: $ty = distr.sample(&mut rng);
- accum = accum.wrapping_add(x[0] as u32);
- }
- accum
- });
- b.bytes = size_of::<$ty>() as u64 * RAND_BENCH_N;
- }
- }
-}
-
-// uniform
-distr_int!(distr_uniform_i8, i8, Uniform::new(20i8, 100));
-distr_int!(distr_uniform_i16, i16, Uniform::new(-500i16, 2000));
-distr_int!(distr_uniform_i32, i32, Uniform::new(-200_000_000i32, 800_000_000));
-distr_int!(distr_uniform_i64, i64, Uniform::new(3i64, 123_456_789_123));
-distr_int!(distr_uniform_i128, i128, Uniform::new(-123_456_789_123i128, 123_456_789_123_456_789));
-distr_int!(distr_uniform_usize16, usize, Uniform::new(0usize, 0xb9d7));
-distr_int!(distr_uniform_usize32, usize, Uniform::new(0usize, 0x548c0f43));
-#[cfg(target_pointer_width = "64")]
-distr_int!(distr_uniform_usize64, usize, Uniform::new(0usize, 0x3a42714f2bf927a8));
-distr_int!(distr_uniform_isize, isize, Uniform::new(-1060478432isize, 1858574057));
-
-distr_float!(distr_uniform_f32, f32, Uniform::new(2.26f32, 2.319));
-distr_float!(distr_uniform_f64, f64, Uniform::new(2.26f64, 2.319));
-
-const LARGE_SEC: u64 = u64::max_value() / 1000;
-
-distr_duration!(distr_uniform_duration_largest,
- Uniform::new_inclusive(Duration::new(0, 0), Duration::new(u64::max_value(), 999_999_999))
-);
-distr_duration!(distr_uniform_duration_large,
- Uniform::new(Duration::new(0, 0), Duration::new(LARGE_SEC, 1_000_000_000 / 2))
-);
-distr_duration!(distr_uniform_duration_one,
- Uniform::new(Duration::new(0, 0), Duration::new(1, 0))
-);
-distr_duration!(distr_uniform_duration_variety,
- Uniform::new(Duration::new(10000, 423423), Duration::new(200000, 6969954))
-);
-distr_duration!(distr_uniform_duration_edge,
- Uniform::new_inclusive(Duration::new(LARGE_SEC, 999_999_999), Duration::new(LARGE_SEC + 1, 1))
-);
-
-
-// standard
-distr_int!(distr_standard_i8, i8, Standard);
-distr_int!(distr_standard_i16, i16, Standard);
-distr_int!(distr_standard_i32, i32, Standard);
-distr_int!(distr_standard_i64, i64, Standard);
-distr_int!(distr_standard_i128, i128, Standard);
-distr_nz_int!(distr_standard_nz8, NonZeroU8, u8, Standard);
-distr_nz_int!(distr_standard_nz16, NonZeroU16, u16, Standard);
-distr_nz_int!(distr_standard_nz32, NonZeroU32, u32, Standard);
-distr_nz_int!(distr_standard_nz64, NonZeroU64, u64, Standard);
-distr_nz_int!(distr_standard_nz128, NonZeroU128, u128, Standard);
-
-distr!(distr_standard_bool, bool, Standard);
-distr!(distr_standard_alphanumeric, char, Alphanumeric);
-distr!(distr_standard_codepoint, char, Standard);
-
-distr_float!(distr_standard_f32, f32, Standard);
-distr_float!(distr_standard_f64, f64, Standard);
-distr_float!(distr_open01_f32, f32, Open01);
-distr_float!(distr_open01_f64, f64, Open01);
-distr_float!(distr_openclosed01_f32, f32, OpenClosed01);
-distr_float!(distr_openclosed01_f64, f64, OpenClosed01);
-
-// distributions
-distr_float!(distr_exp, f64, Exp::new(1.23 * 4.56).unwrap());
-distr_float!(distr_normal, f64, Normal::new(-1.23, 4.56).unwrap());
-distr_float!(distr_log_normal, f64, LogNormal::new(-1.23, 4.56).unwrap());
-distr_float!(distr_gamma_large_shape, f64, Gamma::new(10., 1.0).unwrap());
-distr_float!(distr_gamma_small_shape, f64, Gamma::new(0.1, 1.0).unwrap());
-distr_float!(distr_cauchy, f64, Cauchy::new(4.2, 6.9).unwrap());
-distr_float!(distr_triangular, f64, Triangular::new(0., 1., 0.9).unwrap());
-distr_int!(distr_binomial, u64, Binomial::new(20, 0.7).unwrap());
-distr_int!(distr_binomial_small, u64, Binomial::new(1000000, 1e-30).unwrap());
-distr_int!(distr_poisson, u64, Poisson::new(4.0).unwrap());
-distr!(distr_bernoulli, bool, Bernoulli::new(0.18).unwrap());
-distr_arr!(distr_circle, [f64; 2], UnitCircle);
-distr_arr!(distr_sphere, [f64; 3], UnitSphere);
-
-// Weighted
-distr_int!(distr_weighted_i8, usize, WeightedIndex::new(&[1i8, 2, 3, 4, 12, 0, 2, 1]).unwrap());
-distr_int!(distr_weighted_u32, usize, WeightedIndex::new(&[1u32, 2, 3, 4, 12, 0, 2, 1]).unwrap());
-distr_int!(distr_weighted_f64, usize, WeightedIndex::new(&[1.0f64, 0.001, 1.0/3.0, 4.01, 0.0, 3.3, 22.0, 0.001]).unwrap());
-distr_int!(distr_weighted_large_set, usize, WeightedIndex::new((0..10000).rev().chain(1..10001)).unwrap());
-
-distr_int!(distr_weighted_alias_method_i8, usize, weighted::alias_method::WeightedIndex::new(vec![1i8, 2, 3, 4, 12, 0, 2, 1]).unwrap());
-distr_int!(distr_weighted_alias_method_u32, usize, weighted::alias_method::WeightedIndex::new(vec![1u32, 2, 3, 4, 12, 0, 2, 1]).unwrap());
-distr_int!(distr_weighted_alias_method_f64, usize, weighted::alias_method::WeightedIndex::new(vec![1.0f64, 0.001, 1.0/3.0, 4.01, 0.0, 3.3, 22.0, 0.001]).unwrap());
-distr_int!(distr_weighted_alias_method_large_set, usize, weighted::alias_method::WeightedIndex::new((0..10000).rev().chain(1..10001).collect()).unwrap());
-
-// construct and sample from a range
-macro_rules! gen_range_int {
- ($fnn:ident, $ty:ident, $low:expr, $high:expr) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_entropy();
-
- b.iter(|| {
- let mut high = $high;
- let mut accum: $ty = 0;
- for _ in 0..RAND_BENCH_N {
- accum = accum.wrapping_add(rng.gen_range($low, high));
- // force recalculation of range each time
- high = high.wrapping_add(1) & std::$ty::MAX;
- }
- accum
- });
- b.bytes = size_of::<$ty>() as u64 * RAND_BENCH_N;
- }
- }
-}
-
-gen_range_int!(gen_range_i8, i8, -20i8, 100);
-gen_range_int!(gen_range_i16, i16, -500i16, 2000);
-gen_range_int!(gen_range_i32, i32, -200_000_000i32, 800_000_000);
-gen_range_int!(gen_range_i64, i64, 3i64, 123_456_789_123);
-gen_range_int!(gen_range_i128, i128, -12345678901234i128, 123_456_789_123_456_789);
-
-// construct and sample from a floating-point range
-macro_rules! gen_range_float {
- ($fnn:ident, $ty:ident, $low:expr, $high:expr) => {
- #[bench]
- fn $fnn(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_entropy();
-
- b.iter(|| {
- let mut high = $high;
- let mut low = $low;
- let mut accum: $ty = 0.0;
- for _ in 0..RAND_BENCH_N {
- accum += rng.gen_range(low, high);
- // force recalculation of range each time
- low += 0.9;
- high += 1.1;
- }
- accum
- });
- b.bytes = size_of::<$ty>() as u64 * RAND_BENCH_N;
- }
- }
-}
-
-gen_range_float!(gen_range_f32, f32, -20000.0f32, 100000.0);
-gen_range_float!(gen_range_f64, f64, 123.456f64, 7890.12);
-
-#[bench]
-fn dist_iter(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_entropy();
- let distr = Normal::new(-2.71828, 3.14159).unwrap();
- let mut iter = distr.sample_iter(&mut rng);
-
- b.iter(|| {
- let mut accum = 0.0;
- for _ in 0..RAND_BENCH_N {
- accum += iter.next().unwrap();
- }
- accum
- });
- b.bytes = size_of::<f64>() as u64 * RAND_BENCH_N;
-}
-
-macro_rules! sample_binomial {
- ($name:ident, $n:expr, $p:expr) => {
- #[bench]
- fn $name(b: &mut Bencher) {
- let mut rng = Pcg64Mcg::from_rng(&mut thread_rng()).unwrap();
- let (n, p) = ($n, $p);
- b.iter(|| {
- let d = Binomial::new(n, p).unwrap();
- rng.sample(d)
- })
- }
- }
-}
-
-sample_binomial!(misc_binomial_1, 1, 0.9);
-sample_binomial!(misc_binomial_10, 10, 0.9);
-sample_binomial!(misc_binomial_100, 100, 0.99);
-sample_binomial!(misc_binomial_1000, 1000, 0.01);
-sample_binomial!(misc_binomial_1e12, 1000_000_000_000, 0.2);
diff --git a/rand/rand_distr/src/binomial.rs b/rand/rand_distr/src/binomial.rs
deleted file mode 100644
index 0e6bf9a..0000000
--- a/rand/rand_distr/src/binomial.rs
+++ /dev/null
@@ -1,329 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2016-2017 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The binomial distribution.
-
-use rand::Rng;
-use crate::{Distribution, Uniform};
-
-/// The binomial distribution `Binomial(n, p)`.
-///
-/// This distribution has density function:
-/// `f(k) = n!/(k! (n-k)!) p^k (1-p)^(n-k)` for `k >= 0`.
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{Binomial, Distribution};
-///
-/// let bin = Binomial::new(20, 0.3).unwrap();
-/// let v = bin.sample(&mut rand::thread_rng());
-/// println!("{} is from a binomial distribution", v);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Binomial {
- /// Number of trials.
- n: u64,
- /// Probability of success.
- p: f64,
-}
-
-/// Error type returned from `Binomial::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum Error {
- /// `p < 0` or `nan`.
- ProbabilityTooSmall,
- /// `p > 1`.
- ProbabilityTooLarge,
-}
-
-impl Binomial {
- /// Construct a new `Binomial` with the given shape parameters `n` (number
- /// of trials) and `p` (probability of success).
- pub fn new(n: u64, p: f64) -> Result<Binomial, Error> {
- if !(p >= 0.0) {
- return Err(Error::ProbabilityTooSmall);
- }
- if !(p <= 1.0) {
- return Err(Error::ProbabilityTooLarge);
- }
- Ok(Binomial { n, p })
- }
-}
-
-/// Convert a `f64` to an `i64`, panicing on overflow.
-// In the future (Rust 1.34), this might be replaced with `TryFrom`.
-fn f64_to_i64(x: f64) -> i64 {
- assert!(x < (::std::i64::MAX as f64));
- x as i64
-}
-
-impl Distribution<u64> for Binomial {
- #[allow(clippy::many_single_char_names)] // Same names as in the reference.
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u64 {
- // Handle these values directly.
- if self.p == 0.0 {
- return 0;
- } else if self.p == 1.0 {
- return self.n;
- }
-
- // The binomial distribution is symmetrical with respect to p -> 1-p,
- // k -> n-k switch p so that it is less than 0.5 - this allows for lower
- // expected values we will just invert the result at the end
- let p = if self.p <= 0.5 {
- self.p
- } else {
- 1.0 - self.p
- };
-
- let result;
- let q = 1. - p;
-
- // For small n * min(p, 1 - p), the BINV algorithm based on the inverse
- // transformation of the binomial distribution is efficient. Otherwise,
- // the BTPE algorithm is used.
- //
- // Voratas Kachitvichyanukul and Bruce W. Schmeiser. 1988. Binomial
- // random variate generation. Commun. ACM 31, 2 (February 1988),
- // 216-222. http://dx.doi.org/10.1145/42372.42381
-
- // Threshold for prefering the BINV algorithm. The paper suggests 10,
- // Ranlib uses 30, and GSL uses 14.
- const BINV_THRESHOLD: f64 = 10.;
-
- if (self.n as f64) * p < BINV_THRESHOLD &&
- self.n <= (::std::i32::MAX as u64) {
- // Use the BINV algorithm.
- let s = p / q;
- let a = ((self.n + 1) as f64) * s;
- let mut r = q.powi(self.n as i32);
- let mut u: f64 = rng.gen();
- let mut x = 0;
- while u > r as f64 {
- u -= r;
- x += 1;
- r *= a / (x as f64) - s;
- }
- result = x;
- } else {
- // Use the BTPE algorithm.
-
- // Threshold for using the squeeze algorithm. This can be freely
- // chosen based on performance. Ranlib and GSL use 20.
- const SQUEEZE_THRESHOLD: i64 = 20;
-
- // Step 0: Calculate constants as functions of `n` and `p`.
- let n = self.n as f64;
- let np = n * p;
- let npq = np * q;
- let f_m = np + p;
- let m = f64_to_i64(f_m);
- // radius of triangle region, since height=1 also area of region
- let p1 = (2.195 * npq.sqrt() - 4.6 * q).floor() + 0.5;
- // tip of triangle
- let x_m = (m as f64) + 0.5;
- // left edge of triangle
- let x_l = x_m - p1;
- // right edge of triangle
- let x_r = x_m + p1;
- let c = 0.134 + 20.5 / (15.3 + (m as f64));
- // p1 + area of parallelogram region
- let p2 = p1 * (1. + 2. * c);
-
- fn lambda(a: f64) -> f64 {
- a * (1. + 0.5 * a)
- }
-
- let lambda_l = lambda((f_m - x_l) / (f_m - x_l * p));
- let lambda_r = lambda((x_r - f_m) / (x_r * q));
- // p1 + area of left tail
- let p3 = p2 + c / lambda_l;
- // p1 + area of right tail
- let p4 = p3 + c / lambda_r;
-
- // return value
- let mut y: i64;
-
- let gen_u = Uniform::new(0., p4);
- let gen_v = Uniform::new(0., 1.);
-
- loop {
- // Step 1: Generate `u` for selecting the region. If region 1 is
- // selected, generate a triangularly distributed variate.
- let u = gen_u.sample(rng);
- let mut v = gen_v.sample(rng);
- if !(u > p1) {
- y = f64_to_i64(x_m - p1 * v + u);
- break;
- }
-
- if !(u > p2) {
- // Step 2: Region 2, parallelograms. Check if region 2 is
- // used. If so, generate `y`.
- let x = x_l + (u - p1) / c;
- v = v * c + 1.0 - (x - x_m).abs() / p1;
- if v > 1. {
- continue;
- } else {
- y = f64_to_i64(x);
- }
- } else if !(u > p3) {
- // Step 3: Region 3, left exponential tail.
- y = f64_to_i64(x_l + v.ln() / lambda_l);
- if y < 0 {
- continue;
- } else {
- v *= (u - p2) * lambda_l;
- }
- } else {
- // Step 4: Region 4, right exponential tail.
- y = f64_to_i64(x_r - v.ln() / lambda_r);
- if y > 0 && (y as u64) > self.n {
- continue;
- } else {
- v *= (u - p3) * lambda_r;
- }
- }
-
- // Step 5: Acceptance/rejection comparison.
-
- // Step 5.0: Test for appropriate method of evaluating f(y).
- let k = (y - m).abs();
- if !(k > SQUEEZE_THRESHOLD && (k as f64) < 0.5 * npq - 1.) {
- // Step 5.1: Evaluate f(y) via the recursive relationship. Start the
- // search from the mode.
- let s = p / q;
- let a = s * (n + 1.);
- let mut f = 1.0;
- if m < y {
- let mut i = m;
- loop {
- i += 1;
- f *= a / (i as f64) - s;
- if i == y {
- break;
- }
- }
- } else if m > y {
- let mut i = y;
- loop {
- i += 1;
- f /= a / (i as f64) - s;
- if i == m {
- break;
- }
- }
- }
- if v > f {
- continue;
- } else {
- break;
- }
- }
-
- // Step 5.2: Squeezing. Check the value of ln(v) againts upper and
- // lower bound of ln(f(y)).
- let k = k as f64;
- let rho = (k / npq) * ((k * (k / 3. + 0.625) + 1./6.) / npq + 0.5);
- let t = -0.5 * k*k / npq;
- let alpha = v.ln();
- if alpha < t - rho {
- break;
- }
- if alpha > t + rho {
- continue;
- }
-
- // Step 5.3: Final acceptance/rejection test.
- let x1 = (y + 1) as f64;
- let f1 = (m + 1) as f64;
- let z = (f64_to_i64(n) + 1 - m) as f64;
- let w = (f64_to_i64(n) - y + 1) as f64;
-
- fn stirling(a: f64) -> f64 {
- let a2 = a * a;
- (13860. - (462. - (132. - (99. - 140. / a2) / a2) / a2) / a2) / a / 166320.
- }
-
- if alpha > x_m * (f1 / x1).ln()
- + (n - (m as f64) + 0.5) * (z / w).ln()
- + ((y - m) as f64) * (w * p / (x1 * q)).ln()
- // We use the signs from the GSL implementation, which are
- // different than the ones in the reference. According to
- // the GSL authors, the new signs were verified to be
- // correct by one of the original designers of the
- // algorithm.
- + stirling(f1) + stirling(z) - stirling(x1) - stirling(w)
- {
- continue;
- }
-
- break;
- }
- assert!(y >= 0);
- result = y as u64;
- }
-
- // Invert the result for p < 0.5.
- if p != self.p {
- self.n - result
- } else {
- result
- }
- }
-}
-
-#[cfg(test)]
-mod test {
- use rand::Rng;
- use crate::Distribution;
- use super::Binomial;
-
- fn test_binomial_mean_and_variance<R: Rng>(n: u64, p: f64, rng: &mut R) {
- let binomial = Binomial::new(n, p).unwrap();
-
- let expected_mean = n as f64 * p;
- let expected_variance = n as f64 * p * (1.0 - p);
-
- let mut results = [0.0; 1000];
- for i in results.iter_mut() { *i = binomial.sample(rng) as f64; }
-
- let mean = results.iter().sum::<f64>() / results.len() as f64;
- assert!((mean as f64 - expected_mean).abs() < expected_mean / 50.0);
-
- let variance =
- results.iter().map(|x| (x - mean) * (x - mean)).sum::<f64>()
- / results.len() as f64;
- assert!((variance - expected_variance).abs() < expected_variance / 10.0);
- }
-
- #[test]
- fn test_binomial() {
- let mut rng = crate::test::rng(351);
- test_binomial_mean_and_variance(150, 0.1, &mut rng);
- test_binomial_mean_and_variance(70, 0.6, &mut rng);
- test_binomial_mean_and_variance(40, 0.5, &mut rng);
- test_binomial_mean_and_variance(20, 0.7, &mut rng);
- test_binomial_mean_and_variance(20, 0.5, &mut rng);
- }
-
- #[test]
- fn test_binomial_end_points() {
- let mut rng = crate::test::rng(352);
- assert_eq!(rng.sample(Binomial::new(20, 0.0).unwrap()), 0);
- assert_eq!(rng.sample(Binomial::new(20, 1.0).unwrap()), 20);
- }
-
- #[test]
- #[should_panic]
- fn test_binomial_invalid_lambda_neg() {
- Binomial::new(20, -10.0).unwrap();
- }
-}
diff --git a/rand/rand_distr/src/cauchy.rs b/rand/rand_distr/src/cauchy.rs
deleted file mode 100644
index 6b0e7c6..0000000
--- a/rand/rand_distr/src/cauchy.rs
+++ /dev/null
@@ -1,120 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2016-2017 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The Cauchy distribution.
-
-use rand::Rng;
-use crate::{Distribution, Standard};
-use crate::utils::Float;
-
-/// The Cauchy distribution `Cauchy(median, scale)`.
-///
-/// This distribution has a density function:
-/// `f(x) = 1 / (pi * scale * (1 + ((x - median) / scale)^2))`
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{Cauchy, Distribution};
-///
-/// let cau = Cauchy::new(2.0, 5.0).unwrap();
-/// let v = cau.sample(&mut rand::thread_rng());
-/// println!("{} is from a Cauchy(2, 5) distribution", v);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Cauchy<N> {
- median: N,
- scale: N,
-}
-
-/// Error type returned from `Cauchy::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum Error {
- /// `scale <= 0` or `nan`.
- ScaleTooSmall,
-}
-
-impl<N: Float> Cauchy<N>
-where Standard: Distribution<N>
-{
- /// Construct a new `Cauchy` with the given shape parameters
- /// `median` the peak location and `scale` the scale factor.
- pub fn new(median: N, scale: N) -> Result<Cauchy<N>, Error> {
- if !(scale > N::from(0.0)) {
- return Err(Error::ScaleTooSmall);
- }
- Ok(Cauchy {
- median,
- scale
- })
- }
-}
-
-impl<N: Float> Distribution<N> for Cauchy<N>
-where Standard: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- // sample from [0, 1)
- let x = Standard.sample(rng);
- // get standard cauchy random number
- // note that Ο/2 is not exactly representable, even if x=0.5 the result is finite
- let comp_dev = (N::pi() * x).tan();
- // shift and scale according to parameters
- self.median + self.scale * comp_dev
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::Distribution;
- use super::Cauchy;
-
- fn median(mut numbers: &mut [f64]) -> f64 {
- sort(&mut numbers);
- let mid = numbers.len() / 2;
- numbers[mid]
- }
-
- fn sort(numbers: &mut [f64]) {
- numbers.sort_by(|a, b| a.partial_cmp(b).unwrap());
- }
-
- #[test]
- fn test_cauchy_averages() {
- // NOTE: given that the variance and mean are undefined,
- // this test does not have any rigorous statistical meaning.
- let cauchy = Cauchy::new(10.0, 5.0).unwrap();
- let mut rng = crate::test::rng(123);
- let mut numbers: [f64; 1000] = [0.0; 1000];
- let mut sum = 0.0;
- for i in 0..1000 {
- numbers[i] = cauchy.sample(&mut rng);
- sum += numbers[i];
- }
- let median = median(&mut numbers);
- println!("Cauchy median: {}", median);
- assert!((median - 10.0).abs() < 0.4); // not 100% certain, but probable enough
- let mean = sum / 1000.0;
- println!("Cauchy mean: {}", mean);
- // for a Cauchy distribution the mean should not converge
- assert!((mean - 10.0).abs() > 0.4); // not 100% certain, but probable enough
- }
-
- #[test]
- #[should_panic]
- fn test_cauchy_invalid_scale_zero() {
- Cauchy::new(0.0, 0.0).unwrap();
- }
-
- #[test]
- #[should_panic]
- fn test_cauchy_invalid_scale_neg() {
- Cauchy::new(0.0, -10.0).unwrap();
- }
-}
diff --git a/rand/rand_distr/src/dirichlet.rs b/rand/rand_distr/src/dirichlet.rs
deleted file mode 100644
index 71cf73c..0000000
--- a/rand/rand_distr/src/dirichlet.rs
+++ /dev/null
@@ -1,154 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The dirichlet distribution.
-
-use rand::Rng;
-use crate::{Distribution, Gamma, StandardNormal, Exp1, Open01};
-use crate::utils::Float;
-
-/// The dirichelet distribution `Dirichlet(alpha)`.
-///
-/// The Dirichlet distribution is a family of continuous multivariate
-/// probability distributions parameterized by a vector alpha of positive reals.
-/// It is a multivariate generalization of the beta distribution.
-///
-/// # Example
-///
-/// ```
-/// use rand::prelude::*;
-/// use rand_distr::Dirichlet;
-///
-/// let dirichlet = Dirichlet::new(vec![1.0, 2.0, 3.0]).unwrap();
-/// let samples = dirichlet.sample(&mut rand::thread_rng());
-/// println!("{:?} is from a Dirichlet([1.0, 2.0, 3.0]) distribution", samples);
-/// ```
-#[derive(Clone, Debug)]
-pub struct Dirichlet<N> {
- /// Concentration parameters (alpha)
- alpha: Vec<N>,
-}
-
-/// Error type returned from `Dirchlet::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum Error {
- /// `alpha.len() < 2`.
- AlphaTooShort,
- /// `alpha <= 0.0` or `nan`.
- AlphaTooSmall,
- /// `size < 2`.
- SizeTooSmall,
-}
-
-impl<N: Float> Dirichlet<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- /// Construct a new `Dirichlet` with the given alpha parameter `alpha`.
- ///
- /// Requires `alpha.len() >= 2`.
- #[inline]
- pub fn new<V: Into<Vec<N>>>(alpha: V) -> Result<Dirichlet<N>, Error> {
- let a = alpha.into();
- if a.len() < 2 {
- return Err(Error::AlphaTooShort);
- }
- for &ai in &a {
- if !(ai > N::from(0.0)) {
- return Err(Error::AlphaTooSmall);
- }
- }
-
- Ok(Dirichlet { alpha: a })
- }
-
- /// Construct a new `Dirichlet` with the given shape parameter `alpha` and `size`.
- ///
- /// Requires `size >= 2`.
- #[inline]
- pub fn new_with_size(alpha: N, size: usize) -> Result<Dirichlet<N>, Error> {
- if !(alpha > N::from(0.0)) {
- return Err(Error::AlphaTooSmall);
- }
- if size < 2 {
- return Err(Error::SizeTooSmall);
- }
- Ok(Dirichlet {
- alpha: vec![alpha; size],
- })
- }
-}
-
-impl<N: Float> Distribution<Vec<N>> for Dirichlet<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Vec<N> {
- let n = self.alpha.len();
- let mut samples = vec![N::from(0.0); n];
- let mut sum = N::from(0.0);
-
- for (s, &a) in samples.iter_mut().zip(self.alpha.iter()) {
- let g = Gamma::new(a, N::from(1.0)).unwrap();
- *s = g.sample(rng);
- sum += *s;
- }
- let invacc = N::from(1.0) / sum;
- for s in samples.iter_mut() {
- *s *= invacc;
- }
- samples
- }
-}
-
-#[cfg(test)]
-mod test {
- use super::Dirichlet;
- use crate::Distribution;
-
- #[test]
- fn test_dirichlet() {
- let d = Dirichlet::new(vec![1.0, 2.0, 3.0]).unwrap();
- let mut rng = crate::test::rng(221);
- let samples = d.sample(&mut rng);
- let _: Vec<f64> = samples
- .into_iter()
- .map(|x| {
- assert!(x > 0.0);
- x
- })
- .collect();
- }
-
- #[test]
- fn test_dirichlet_with_param() {
- let alpha = 0.5f64;
- let size = 2;
- let d = Dirichlet::new_with_size(alpha, size).unwrap();
- let mut rng = crate::test::rng(221);
- let samples = d.sample(&mut rng);
- let _: Vec<f64> = samples
- .into_iter()
- .map(|x| {
- assert!(x > 0.0);
- x
- })
- .collect();
- }
-
- #[test]
- #[should_panic]
- fn test_dirichlet_invalid_length() {
- Dirichlet::new_with_size(0.5f64, 1).unwrap();
- }
-
- #[test]
- #[should_panic]
- fn test_dirichlet_invalid_alpha() {
- Dirichlet::new_with_size(0.0f64, 2).unwrap();
- }
-}
diff --git a/rand/rand_distr/src/exponential.rs b/rand/rand_distr/src/exponential.rs
deleted file mode 100644
index 8322489..0000000
--- a/rand/rand_distr/src/exponential.rs
+++ /dev/null
@@ -1,145 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The exponential distribution.
-
-use rand::Rng;
-use crate::{ziggurat_tables, Distribution};
-use crate::utils::{ziggurat, Float};
-
-/// Samples floating-point numbers according to the exponential distribution,
-/// with rate parameter `Ξ» = 1`. This is equivalent to `Exp::new(1.0)` or
-/// sampling with `-rng.gen::<f64>().ln()`, but faster.
-///
-/// See `Exp` for the general exponential distribution.
-///
-/// Implemented via the ZIGNOR variant[^1] of the Ziggurat method. The exact
-/// description in the paper was adjusted to use tables for the exponential
-/// distribution rather than normal.
-///
-/// [^1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method to
-/// Generate Normal Random Samples*](
-/// https://www.doornik.com/research/ziggurat.pdf).
-/// Nuffield College, Oxford
-///
-/// # Example
-/// ```
-/// use rand::prelude::*;
-/// use rand_distr::Exp1;
-///
-/// let val: f64 = thread_rng().sample(Exp1);
-/// println!("{}", val);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Exp1;
-
-impl Distribution<f32> for Exp1 {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f32 {
- // TODO: use optimal 32-bit implementation
- let x: f64 = self.sample(rng);
- x as f32
- }
-}
-
-// This could be done via `-rng.gen::<f64>().ln()` but that is slower.
-impl Distribution<f64> for Exp1 {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- #[inline]
- fn pdf(x: f64) -> f64 {
- (-x).exp()
- }
- #[inline]
- fn zero_case<R: Rng + ?Sized>(rng: &mut R, _u: f64) -> f64 {
- ziggurat_tables::ZIG_EXP_R - rng.gen::<f64>().ln()
- }
-
- ziggurat(rng, false,
- &ziggurat_tables::ZIG_EXP_X,
- &ziggurat_tables::ZIG_EXP_F,
- pdf, zero_case)
- }
-}
-
-/// The exponential distribution `Exp(lambda)`.
-///
-/// This distribution has density function: `f(x) = lambda * exp(-lambda * x)`
-/// for `x > 0`.
-///
-/// Note that [`Exp1`](crate::Exp1) is an optimised implementation for `lambda = 1`.
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{Exp, Distribution};
-///
-/// let exp = Exp::new(2.0).unwrap();
-/// let v = exp.sample(&mut rand::thread_rng());
-/// println!("{} is from a Exp(2) distribution", v);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Exp<N> {
- /// `lambda` stored as `1/lambda`, since this is what we scale by.
- lambda_inverse: N
-}
-
-/// Error type returned from `Exp::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum Error {
- /// `lambda <= 0` or `nan`.
- LambdaTooSmall,
-}
-
-impl<N: Float> Exp<N>
-where Exp1: Distribution<N>
-{
- /// Construct a new `Exp` with the given shape parameter
- /// `lambda`.
- #[inline]
- pub fn new(lambda: N) -> Result<Exp<N>, Error> {
- if !(lambda > N::from(0.0)) {
- return Err(Error::LambdaTooSmall);
- }
- Ok(Exp { lambda_inverse: N::from(1.0) / lambda })
- }
-}
-
-impl<N: Float> Distribution<N> for Exp<N>
-where Exp1: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- rng.sample(Exp1) * self.lambda_inverse
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::Distribution;
- use super::Exp;
-
- #[test]
- fn test_exp() {
- let exp = Exp::new(10.0).unwrap();
- let mut rng = crate::test::rng(221);
- for _ in 0..1000 {
- assert!(exp.sample(&mut rng) >= 0.0);
- }
- }
- #[test]
- #[should_panic]
- fn test_exp_invalid_lambda_zero() {
- Exp::new(0.0).unwrap();
- }
- #[test]
- #[should_panic]
- fn test_exp_invalid_lambda_neg() {
- Exp::new(-10.0).unwrap();
- }
-}
diff --git a/rand/rand_distr/src/gamma.rs b/rand/rand_distr/src/gamma.rs
deleted file mode 100644
index 4018361..0000000
--- a/rand/rand_distr/src/gamma.rs
+++ /dev/null
@@ -1,485 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The Gamma and derived distributions.
-
-use self::GammaRepr::*;
-use self::ChiSquaredRepr::*;
-
-use rand::Rng;
-use crate::normal::StandardNormal;
-use crate::{Distribution, Exp1, Exp, Open01};
-use crate::utils::Float;
-
-/// The Gamma distribution `Gamma(shape, scale)` distribution.
-///
-/// The density function of this distribution is
-///
-/// ```text
-/// f(x) = x^(k - 1) * exp(-x / ΞΈ) / (Ξ(k) * ΞΈ^k)
-/// ```
-///
-/// where `Ξ` is the Gamma function, `k` is the shape and `ΞΈ` is the
-/// scale and both `k` and `ΞΈ` are strictly positive.
-///
-/// The algorithm used is that described by Marsaglia & Tsang 2000[^1],
-/// falling back to directly sampling from an Exponential for `shape
-/// == 1`, and using the boosting technique described in that paper for
-/// `shape < 1`.
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{Distribution, Gamma};
-///
-/// let gamma = Gamma::new(2.0, 5.0).unwrap();
-/// let v = gamma.sample(&mut rand::thread_rng());
-/// println!("{} is from a Gamma(2, 5) distribution", v);
-/// ```
-///
-/// [^1]: George Marsaglia and Wai Wan Tsang. 2000. "A Simple Method for
-/// Generating Gamma Variables" *ACM Trans. Math. Softw.* 26, 3
-/// (September 2000), 363-372.
-/// DOI:[10.1145/358407.358414](https://doi.acm.org/10.1145/358407.358414)
-#[derive(Clone, Copy, Debug)]
-pub struct Gamma<N> {
- repr: GammaRepr<N>,
-}
-
-/// Error type returned from `Gamma::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum Error {
- /// `shape <= 0` or `nan`.
- ShapeTooSmall,
- /// `scale <= 0` or `nan`.
- ScaleTooSmall,
- /// `1 / scale == 0`.
- ScaleTooLarge,
-}
-
-#[derive(Clone, Copy, Debug)]
-enum GammaRepr<N> {
- Large(GammaLargeShape<N>),
- One(Exp<N>),
- Small(GammaSmallShape<N>)
-}
-
-// These two helpers could be made public, but saving the
-// match-on-Gamma-enum branch from using them directly (e.g. if one
-// knows that the shape is always > 1) doesn't appear to be much
-// faster.
-
-/// Gamma distribution where the shape parameter is less than 1.
-///
-/// Note, samples from this require a compulsory floating-point `pow`
-/// call, which makes it significantly slower than sampling from a
-/// gamma distribution where the shape parameter is greater than or
-/// equal to 1.
-///
-/// See `Gamma` for sampling from a Gamma distribution with general
-/// shape parameters.
-#[derive(Clone, Copy, Debug)]
-struct GammaSmallShape<N> {
- inv_shape: N,
- large_shape: GammaLargeShape<N>
-}
-
-/// Gamma distribution where the shape parameter is larger than 1.
-///
-/// See `Gamma` for sampling from a Gamma distribution with general
-/// shape parameters.
-#[derive(Clone, Copy, Debug)]
-struct GammaLargeShape<N> {
- scale: N,
- c: N,
- d: N
-}
-
-impl<N: Float> Gamma<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- /// Construct an object representing the `Gamma(shape, scale)`
- /// distribution.
- #[inline]
- pub fn new(shape: N, scale: N) -> Result<Gamma<N>, Error> {
- if !(shape > N::from(0.0)) {
- return Err(Error::ShapeTooSmall);
- }
- if !(scale > N::from(0.0)) {
- return Err(Error::ScaleTooSmall);
- }
-
- let repr = if shape == N::from(1.0) {
- One(Exp::new(N::from(1.0) / scale).map_err(|_| Error::ScaleTooLarge)?)
- } else if shape < N::from(1.0) {
- Small(GammaSmallShape::new_raw(shape, scale))
- } else {
- Large(GammaLargeShape::new_raw(shape, scale))
- };
- Ok(Gamma { repr })
- }
-}
-
-impl<N: Float> GammaSmallShape<N>
-where StandardNormal: Distribution<N>, Open01: Distribution<N>
-{
- fn new_raw(shape: N, scale: N) -> GammaSmallShape<N> {
- GammaSmallShape {
- inv_shape: N::from(1.0) / shape,
- large_shape: GammaLargeShape::new_raw(shape + N::from(1.0), scale)
- }
- }
-}
-
-impl<N: Float> GammaLargeShape<N>
-where StandardNormal: Distribution<N>, Open01: Distribution<N>
-{
- fn new_raw(shape: N, scale: N) -> GammaLargeShape<N> {
- let d = shape - N::from(1. / 3.);
- GammaLargeShape {
- scale,
- c: N::from(1.0) / (N::from(9.) * d).sqrt(),
- d
- }
- }
-}
-
-impl<N: Float> Distribution<N> for Gamma<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- match self.repr {
- Small(ref g) => g.sample(rng),
- One(ref g) => g.sample(rng),
- Large(ref g) => g.sample(rng),
- }
- }
-}
-impl<N: Float> Distribution<N> for GammaSmallShape<N>
-where StandardNormal: Distribution<N>, Open01: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- let u: N = rng.sample(Open01);
-
- self.large_shape.sample(rng) * u.powf(self.inv_shape)
- }
-}
-impl<N: Float> Distribution<N> for GammaLargeShape<N>
-where StandardNormal: Distribution<N>, Open01: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- // Marsaglia & Tsang method, 2000
- loop {
- let x: N = rng.sample(StandardNormal);
- let v_cbrt = N::from(1.0) + self.c * x;
- if v_cbrt <= N::from(0.0) { // a^3 <= 0 iff a <= 0
- continue
- }
-
- let v = v_cbrt * v_cbrt * v_cbrt;
- let u: N = rng.sample(Open01);
-
- let x_sqr = x * x;
- if u < N::from(1.0) - N::from(0.0331) * x_sqr * x_sqr ||
- u.ln() < N::from(0.5) * x_sqr + self.d * (N::from(1.0) - v + v.ln())
- {
- return self.d * v * self.scale
- }
- }
- }
-}
-
-/// The chi-squared distribution `ΟΒ²(k)`, where `k` is the degrees of
-/// freedom.
-///
-/// For `k > 0` integral, this distribution is the sum of the squares
-/// of `k` independent standard normal random variables. For other
-/// `k`, this uses the equivalent characterisation
-/// `ΟΒ²(k) = Gamma(k/2, 2)`.
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{ChiSquared, Distribution};
-///
-/// let chi = ChiSquared::new(11.0).unwrap();
-/// let v = chi.sample(&mut rand::thread_rng());
-/// println!("{} is from a ΟΒ²(11) distribution", v)
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct ChiSquared<N> {
- repr: ChiSquaredRepr<N>,
-}
-
-/// Error type returned from `ChiSquared::new` and `StudentT::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum ChiSquaredError {
- /// `0.5 * k <= 0` or `nan`.
- DoFTooSmall,
-}
-
-#[derive(Clone, Copy, Debug)]
-enum ChiSquaredRepr<N> {
- // k == 1, Gamma(alpha, ..) is particularly slow for alpha < 1,
- // e.g. when alpha = 1/2 as it would be for this case, so special-
- // casing and using the definition of N(0,1)^2 is faster.
- DoFExactlyOne,
- DoFAnythingElse(Gamma<N>),
-}
-
-impl<N: Float> ChiSquared<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- /// Create a new chi-squared distribution with degrees-of-freedom
- /// `k`.
- pub fn new(k: N) -> Result<ChiSquared<N>, ChiSquaredError> {
- let repr = if k == N::from(1.0) {
- DoFExactlyOne
- } else {
- if !(N::from(0.5) * k > N::from(0.0)) {
- return Err(ChiSquaredError::DoFTooSmall);
- }
- DoFAnythingElse(Gamma::new(N::from(0.5) * k, N::from(2.0)).unwrap())
- };
- Ok(ChiSquared { repr })
- }
-}
-impl<N: Float> Distribution<N> for ChiSquared<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- match self.repr {
- DoFExactlyOne => {
- // k == 1 => N(0,1)^2
- let norm: N = rng.sample(StandardNormal);
- norm * norm
- }
- DoFAnythingElse(ref g) => g.sample(rng)
- }
- }
-}
-
-/// The Fisher F distribution `F(m, n)`.
-///
-/// This distribution is equivalent to the ratio of two normalised
-/// chi-squared distributions, that is, `F(m,n) = (ΟΒ²(m)/m) /
-/// (ΟΒ²(n)/n)`.
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{FisherF, Distribution};
-///
-/// let f = FisherF::new(2.0, 32.0).unwrap();
-/// let v = f.sample(&mut rand::thread_rng());
-/// println!("{} is from an F(2, 32) distribution", v)
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct FisherF<N> {
- numer: ChiSquared<N>,
- denom: ChiSquared<N>,
- // denom_dof / numer_dof so that this can just be a straight
- // multiplication, rather than a division.
- dof_ratio: N,
-}
-
-/// Error type returned from `FisherF::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum FisherFError {
- /// `m <= 0` or `nan`.
- MTooSmall,
- /// `n <= 0` or `nan`.
- NTooSmall,
-}
-
-impl<N: Float> FisherF<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- /// Create a new `FisherF` distribution, with the given parameter.
- pub fn new(m: N, n: N) -> Result<FisherF<N>, FisherFError> {
- if !(m > N::from(0.0)) {
- return Err(FisherFError::MTooSmall);
- }
- if !(n > N::from(0.0)) {
- return Err(FisherFError::NTooSmall);
- }
-
- Ok(FisherF {
- numer: ChiSquared::new(m).unwrap(),
- denom: ChiSquared::new(n).unwrap(),
- dof_ratio: n / m
- })
- }
-}
-impl<N: Float> Distribution<N> for FisherF<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- self.numer.sample(rng) / self.denom.sample(rng) * self.dof_ratio
- }
-}
-
-/// The Student t distribution, `t(nu)`, where `nu` is the degrees of
-/// freedom.
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{StudentT, Distribution};
-///
-/// let t = StudentT::new(11.0).unwrap();
-/// let v = t.sample(&mut rand::thread_rng());
-/// println!("{} is from a t(11) distribution", v)
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct StudentT<N> {
- chi: ChiSquared<N>,
- dof: N
-}
-
-impl<N: Float> StudentT<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- /// Create a new Student t distribution with `n` degrees of
- /// freedom.
- pub fn new(n: N) -> Result<StudentT<N>, ChiSquaredError> {
- Ok(StudentT {
- chi: ChiSquared::new(n)?,
- dof: n
- })
- }
-}
-impl<N: Float> Distribution<N> for StudentT<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- let norm: N = rng.sample(StandardNormal);
- norm * (self.dof / self.chi.sample(rng)).sqrt()
- }
-}
-
-/// The Beta distribution with shape parameters `alpha` and `beta`.
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{Distribution, Beta};
-///
-/// let beta = Beta::new(2.0, 5.0).unwrap();
-/// let v = beta.sample(&mut rand::thread_rng());
-/// println!("{} is from a Beta(2, 5) distribution", v);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Beta<N> {
- gamma_a: Gamma<N>,
- gamma_b: Gamma<N>,
-}
-
-/// Error type returned from `Beta::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum BetaError {
- /// `alpha <= 0` or `nan`.
- AlphaTooSmall,
- /// `beta <= 0` or `nan`.
- BetaTooSmall,
-}
-
-impl<N: Float> Beta<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- /// Construct an object representing the `Beta(alpha, beta)`
- /// distribution.
- pub fn new(alpha: N, beta: N) -> Result<Beta<N>, BetaError> {
- Ok(Beta {
- gamma_a: Gamma::new(alpha, N::from(1.))
- .map_err(|_| BetaError::AlphaTooSmall)?,
- gamma_b: Gamma::new(beta, N::from(1.))
- .map_err(|_| BetaError::BetaTooSmall)?,
- })
- }
-}
-
-impl<N: Float> Distribution<N> for Beta<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- let x = self.gamma_a.sample(rng);
- let y = self.gamma_b.sample(rng);
- x / (x + y)
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::Distribution;
- use super::{Beta, ChiSquared, StudentT, FisherF};
-
- #[test]
- fn test_chi_squared_one() {
- let chi = ChiSquared::new(1.0).unwrap();
- let mut rng = crate::test::rng(201);
- for _ in 0..1000 {
- chi.sample(&mut rng);
- }
- }
- #[test]
- fn test_chi_squared_small() {
- let chi = ChiSquared::new(0.5).unwrap();
- let mut rng = crate::test::rng(202);
- for _ in 0..1000 {
- chi.sample(&mut rng);
- }
- }
- #[test]
- fn test_chi_squared_large() {
- let chi = ChiSquared::new(30.0).unwrap();
- let mut rng = crate::test::rng(203);
- for _ in 0..1000 {
- chi.sample(&mut rng);
- }
- }
- #[test]
- #[should_panic]
- fn test_chi_squared_invalid_dof() {
- ChiSquared::new(-1.0).unwrap();
- }
-
- #[test]
- fn test_f() {
- let f = FisherF::new(2.0, 32.0).unwrap();
- let mut rng = crate::test::rng(204);
- for _ in 0..1000 {
- f.sample(&mut rng);
- }
- }
-
- #[test]
- fn test_t() {
- let t = StudentT::new(11.0).unwrap();
- let mut rng = crate::test::rng(205);
- for _ in 0..1000 {
- t.sample(&mut rng);
- }
- }
-
- #[test]
- fn test_beta() {
- let beta = Beta::new(1.0, 2.0).unwrap();
- let mut rng = crate::test::rng(201);
- for _ in 0..1000 {
- beta.sample(&mut rng);
- }
- }
-
- #[test]
- #[should_panic]
- fn test_beta_invalid_dof() {
- Beta::new(0., 0.).unwrap();
- }
-}
diff --git a/rand/rand_distr/src/lib.rs b/rand/rand_distr/src/lib.rs
deleted file mode 100644
index baf65ed..0000000
--- a/rand/rand_distr/src/lib.rs
+++ /dev/null
@@ -1,134 +0,0 @@
-// Copyright 2019 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
- html_favicon_url = "https://www.rust-lang.org/favicon.ico",
- html_root_url = "https://rust-random.github.io/rand/")]
-
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-
-#![allow(clippy::excessive_precision, clippy::float_cmp, clippy::unreadable_literal)]
-#![allow(clippy::neg_cmp_op_on_partial_ord)] // suggested fix too verbose
-
-//! Generating random samples from probability distributions.
-//!
-//! ## Re-exports
-//!
-//! This crate is a super-set of the [`rand::distributions`] module. See the
-//! [`rand::distributions`] module documentation for an overview of the core
-//! [`Distribution`] trait and implementations.
-//!
-//! The following are re-exported:
-//!
-//! - The [`Distribution`] trait and [`DistIter`] helper type
-//! - The [`Standard`], [`Alphanumeric`], [`Uniform`], [`OpenClosed01`], [`Open01`] and [`Bernoulli`] distributions
-//! - The [`weighted`] sub-module
-//!
-//! ## Distributions
-//!
-//! This crate provides the following probability distributions:
-//!
-//! - Related to real-valued quantities that grow linearly
-//! (e.g. errors, offsets):
-//! - [`Normal`] distribution, and [`StandardNormal`] as a primitive
-//! - [`Cauchy`] distribution
-//! - Related to Bernoulli trials (yes/no events, with a given probability):
-//! - [`Binomial`] distribution
-//! - Related to positive real-valued quantities that grow exponentially
-//! (e.g. prices, incomes, populations):
-//! - [`LogNormal`] distribution
-//! - Related to the occurrence of independent events at a given rate:
-//! - [`Pareto`] distribution
-//! - [`Poisson`] distribution
-//! - [`Exp`]onential distribution, and [`Exp1`] as a primitive
-//! - [`Weibull`] distribution
-//! - Gamma and derived distributions:
-//! - [`Gamma`] distribution
-//! - [`ChiSquared`] distribution
-//! - [`StudentT`] distribution
-//! - [`FisherF`] distribution
-//! - Triangular distribution:
-//! - [`Beta`] distribution
-//! - [`Triangular`] distribution
-//! - Multivariate probability distributions
-//! - [`Dirichlet`] distribution
-//! - [`UnitSphere`] distribution
-//! - [`UnitBall`] distribution
-//! - [`UnitCircle`] distribution
-//! - [`UnitDisc`] distribution
-
-pub use rand::distributions::{Distribution, DistIter, Standard,
- Alphanumeric, Uniform, OpenClosed01, Open01, Bernoulli, uniform, weighted};
-
-pub use self::unit_sphere::UnitSphere;
-pub use self::unit_ball::UnitBall;
-pub use self::unit_circle::UnitCircle;
-pub use self::unit_disc::UnitDisc;
-pub use self::gamma::{Gamma, Error as GammaError, ChiSquared, ChiSquaredError,
- FisherF, FisherFError, StudentT, Beta, BetaError};
-pub use self::normal::{Normal, Error as NormalError, LogNormal, StandardNormal};
-pub use self::exponential::{Exp, Error as ExpError, Exp1};
-pub use self::pareto::{Pareto, Error as ParetoError};
-pub use self::pert::{Pert, PertError};
-pub use self::poisson::{Poisson, Error as PoissonError};
-pub use self::binomial::{Binomial, Error as BinomialError};
-pub use self::cauchy::{Cauchy, Error as CauchyError};
-pub use self::dirichlet::{Dirichlet, Error as DirichletError};
-pub use self::triangular::{Triangular, TriangularError};
-pub use self::weibull::{Weibull, Error as WeibullError};
-pub use self::utils::Float;
-
-mod unit_sphere;
-mod unit_ball;
-mod unit_circle;
-mod unit_disc;
-mod gamma;
-mod normal;
-mod exponential;
-mod pareto;
-mod pert;
-mod poisson;
-mod binomial;
-mod cauchy;
-mod dirichlet;
-mod triangular;
-mod weibull;
-mod utils;
-mod ziggurat_tables;
-
-#[cfg(test)]
-mod test {
- // Notes on testing
- //
- // Testing random number distributions correctly is hard. The following
- // testing is desired:
- //
- // - Construction: test initialisation with a few valid parameter sets.
- // - Erroneous usage: test that incorrect usage generates an error.
- // - Vector: test that usage with fixed inputs (including RNG) generates a
- // fixed output sequence on all platforms.
- // - Correctness at fixed points (optional): using a specific mock RNG,
- // check that specific values are sampled (e.g. end-points and median of
- // distribution).
- // - Correctness of PDF (extra): generate a histogram of samples within a
- // certain range, and check this approximates the PDF. These tests are
- // expected to be expensive, and should be behind a feature-gate.
- //
- // TODO: Vector and correctness tests are largely absent so far.
- // NOTE: Some distributions have tests checking only that samples can be
- // generated. This is redundant with vector and correctness tests.
-
- /// Construct a deterministic RNG with the given seed
- pub fn rng(seed: u64) -> impl rand::RngCore {
- // For tests, we want a statistically good, fast, reproducible RNG.
- // PCG32 will do fine, and will be easy to embed if we ever need to.
- const INC: u64 = 11634580027462260723;
- rand_pcg::Pcg32::new(seed, INC)
- }
-}
diff --git a/rand/rand_distr/src/normal.rs b/rand/rand_distr/src/normal.rs
deleted file mode 100644
index 882754f..0000000
--- a/rand/rand_distr/src/normal.rs
+++ /dev/null
@@ -1,219 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The normal and derived distributions.
-
-use rand::Rng;
-use crate::{ziggurat_tables, Distribution, Open01};
-use crate::utils::{ziggurat, Float};
-
-/// Samples floating-point numbers according to the normal distribution
-/// `N(0, 1)` (a.k.a. a standard normal, or Gaussian). This is equivalent to
-/// `Normal::new(0.0, 1.0)` but faster.
-///
-/// See `Normal` for the general normal distribution.
-///
-/// Implemented via the ZIGNOR variant[^1] of the Ziggurat method.
-///
-/// [^1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method to
-/// Generate Normal Random Samples*](
-/// https://www.doornik.com/research/ziggurat.pdf).
-/// Nuffield College, Oxford
-///
-/// # Example
-/// ```
-/// use rand::prelude::*;
-/// use rand_distr::StandardNormal;
-///
-/// let val: f64 = thread_rng().sample(StandardNormal);
-/// println!("{}", val);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct StandardNormal;
-
-impl Distribution<f32> for StandardNormal {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f32 {
- // TODO: use optimal 32-bit implementation
- let x: f64 = self.sample(rng);
- x as f32
- }
-}
-
-impl Distribution<f64> for StandardNormal {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- #[inline]
- fn pdf(x: f64) -> f64 {
- (-x*x/2.0).exp()
- }
- #[inline]
- fn zero_case<R: Rng + ?Sized>(rng: &mut R, u: f64) -> f64 {
- // compute a random number in the tail by hand
-
- // strange initial conditions, because the loop is not
- // do-while, so the condition should be true on the first
- // run, they get overwritten anyway (0 < 1, so these are
- // good).
- let mut x = 1.0f64;
- let mut y = 0.0f64;
-
- while -2.0 * y < x * x {
- let x_: f64 = rng.sample(Open01);
- let y_: f64 = rng.sample(Open01);
-
- x = x_.ln() / ziggurat_tables::ZIG_NORM_R;
- y = y_.ln();
- }
-
- if u < 0.0 { x - ziggurat_tables::ZIG_NORM_R } else { ziggurat_tables::ZIG_NORM_R - x }
- }
-
- ziggurat(rng, true, // this is symmetric
- &ziggurat_tables::ZIG_NORM_X,
- &ziggurat_tables::ZIG_NORM_F,
- pdf, zero_case)
- }
-}
-
-/// The normal distribution `N(mean, std_dev**2)`.
-///
-/// This uses the ZIGNOR variant of the Ziggurat method, see [`StandardNormal`]
-/// for more details.
-///
-/// Note that [`StandardNormal`] is an optimised implementation for mean 0, and
-/// standard deviation 1.
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{Normal, Distribution};
-///
-/// // mean 2, standard deviation 3
-/// let normal = Normal::new(2.0, 3.0).unwrap();
-/// let v = normal.sample(&mut rand::thread_rng());
-/// println!("{} is from a N(2, 9) distribution", v)
-/// ```
-///
-/// [`StandardNormal`]: crate::StandardNormal
-#[derive(Clone, Copy, Debug)]
-pub struct Normal<N> {
- mean: N,
- std_dev: N,
-}
-
-/// Error type returned from `Normal::new` and `LogNormal::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum Error {
- /// `std_dev < 0` or `nan`.
- StdDevTooSmall,
-}
-
-impl<N: Float> Normal<N>
-where StandardNormal: Distribution<N>
-{
- /// Construct a new `Normal` distribution with the given mean and
- /// standard deviation.
- #[inline]
- pub fn new(mean: N, std_dev: N) -> Result<Normal<N>, Error> {
- if !(std_dev >= N::from(0.0)) {
- return Err(Error::StdDevTooSmall);
- }
- Ok(Normal {
- mean,
- std_dev
- })
- }
-}
-
-impl<N: Float> Distribution<N> for Normal<N>
-where StandardNormal: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- let n: N = rng.sample(StandardNormal);
- self.mean + self.std_dev * n
- }
-}
-
-
-/// The log-normal distribution `ln N(mean, std_dev**2)`.
-///
-/// If `X` is log-normal distributed, then `ln(X)` is `N(mean, std_dev**2)`
-/// distributed.
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{LogNormal, Distribution};
-///
-/// // mean 2, standard deviation 3
-/// let log_normal = LogNormal::new(2.0, 3.0).unwrap();
-/// let v = log_normal.sample(&mut rand::thread_rng());
-/// println!("{} is from an ln N(2, 9) distribution", v)
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct LogNormal<N> {
- norm: Normal<N>
-}
-
-impl<N: Float> LogNormal<N>
-where StandardNormal: Distribution<N>
-{
- /// Construct a new `LogNormal` distribution with the given mean
- /// and standard deviation of the logarithm of the distribution.
- #[inline]
- pub fn new(mean: N, std_dev: N) -> Result<LogNormal<N>, Error> {
- if !(std_dev >= N::from(0.0)) {
- return Err(Error::StdDevTooSmall);
- }
- Ok(LogNormal { norm: Normal::new(mean, std_dev).unwrap() })
- }
-}
-
-impl<N: Float> Distribution<N> for LogNormal<N>
-where StandardNormal: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- self.norm.sample(rng).exp()
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::Distribution;
- use super::{Normal, LogNormal};
-
- #[test]
- fn test_normal() {
- let norm = Normal::new(10.0, 10.0).unwrap();
- let mut rng = crate::test::rng(210);
- for _ in 0..1000 {
- norm.sample(&mut rng);
- }
- }
- #[test]
- #[should_panic]
- fn test_normal_invalid_sd() {
- Normal::new(10.0, -1.0).unwrap();
- }
-
-
- #[test]
- fn test_log_normal() {
- let lnorm = LogNormal::new(10.0, 10.0).unwrap();
- let mut rng = crate::test::rng(211);
- for _ in 0..1000 {
- lnorm.sample(&mut rng);
- }
- }
- #[test]
- #[should_panic]
- fn test_log_normal_invalid_sd() {
- LogNormal::new(10.0, -1.0).unwrap();
- }
-}
diff --git a/rand/rand_distr/src/pareto.rs b/rand/rand_distr/src/pareto.rs
deleted file mode 100644
index 33ea382..0000000
--- a/rand/rand_distr/src/pareto.rs
+++ /dev/null
@@ -1,89 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The Pareto distribution.
-
-use rand::Rng;
-use crate::{Distribution, OpenClosed01};
-use crate::utils::Float;
-
-/// Samples floating-point numbers according to the Pareto distribution
-///
-/// # Example
-/// ```
-/// use rand::prelude::*;
-/// use rand_distr::Pareto;
-///
-/// let val: f64 = thread_rng().sample(Pareto::new(1., 2.).unwrap());
-/// println!("{}", val);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Pareto<N> {
- scale: N,
- inv_neg_shape: N,
-}
-
-/// Error type returned from `Pareto::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum Error {
- /// `scale <= 0` or `nan`.
- ScaleTooSmall,
- /// `shape <= 0` or `nan`.
- ShapeTooSmall,
-}
-
-impl<N: Float> Pareto<N>
-where OpenClosed01: Distribution<N>
-{
- /// Construct a new Pareto distribution with given `scale` and `shape`.
- ///
- /// In the literature, `scale` is commonly written as x<sub>m</sub> or k and
- /// `shape` is often written as Ξ±.
- pub fn new(scale: N, shape: N) -> Result<Pareto<N>, Error> {
- if !(scale > N::from(0.0)) {
- return Err(Error::ScaleTooSmall);
- }
- if !(shape > N::from(0.0)) {
- return Err(Error::ShapeTooSmall);
- }
- Ok(Pareto { scale, inv_neg_shape: N::from(-1.0) / shape })
- }
-}
-
-impl<N: Float> Distribution<N> for Pareto<N>
-where OpenClosed01: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- let u: N = OpenClosed01.sample(rng);
- self.scale * u.powf(self.inv_neg_shape)
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::Distribution;
- use super::Pareto;
-
- #[test]
- #[should_panic]
- fn invalid() {
- Pareto::new(0., 0.).unwrap();
- }
-
- #[test]
- fn sample() {
- let scale = 1.0;
- let shape = 2.0;
- let d = Pareto::new(scale, shape).unwrap();
- let mut rng = crate::test::rng(1);
- for _ in 0..1000 {
- let r = d.sample(&mut rng);
- assert!(r >= scale);
- }
- }
-}
diff --git a/rand/rand_distr/src/pert.rs b/rand/rand_distr/src/pert.rs
deleted file mode 100644
index 040cd05..0000000
--- a/rand/rand_distr/src/pert.rs
+++ /dev/null
@@ -1,132 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-//! The PERT distribution.
-
-use rand::Rng;
-use crate::{Distribution, Beta, StandardNormal, Exp1, Open01};
-use crate::utils::Float;
-
-/// The PERT distribution.
-///
-/// Similar to the [`Triangular`] distribution, the PERT distribution is
-/// parameterised by a range and a mode within that range. Unlike the
-/// [`Triangular`] distribution, the probability density function of the PERT
-/// distribution is smooth, with a configurable weighting around the mode.
-///
-/// # Example
-///
-/// ```rust
-/// use rand_distr::{Pert, Distribution};
-///
-/// let d = Pert::new(0., 5., 2.5).unwrap();
-/// let v = d.sample(&mut rand::thread_rng());
-/// println!("{} is from a PERT distribution", v);
-/// ```
-///
-/// [`Triangular`]: crate::Triangular
-#[derive(Clone, Copy, Debug)]
-pub struct Pert<N> {
- min: N,
- range: N,
- beta: Beta<N>,
-}
-
-/// Error type returned from [`Pert`] constructors.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum PertError {
- /// `max < min` or `min` or `max` is NaN.
- RangeTooSmall,
- /// `mode < min` or `mode > max` or `mode` is NaN.
- ModeRange,
- /// `shape < 0` or `shape` is NaN
- ShapeTooSmall,
-}
-
-impl<N: Float> Pert<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- /// Set up the PERT distribution with defined `min`, `max` and `mode`.
- ///
- /// This is equivalent to calling `Pert::new_shape` with `shape == 4.0`.
- #[inline]
- pub fn new(min: N, max: N, mode: N) -> Result<Pert<N>, PertError> {
- Pert::new_with_shape(min, max, mode, N::from(4.))
- }
-
- /// Set up the PERT distribution with defined `min`, `max`, `mode` and
- /// `shape`.
- pub fn new_with_shape(min: N, max: N, mode: N, shape: N) -> Result<Pert<N>, PertError> {
- if !(max > min) {
- return Err(PertError::RangeTooSmall);
- }
- if !(mode >= min && max >= mode) {
- return Err(PertError::ModeRange);
- }
- if !(shape >= N::from(0.)) {
- return Err(PertError::ShapeTooSmall);
- }
-
- let range = max - min;
- let mu = (min + max + shape * mode) / (shape + N::from(2.));
- let v = if mu == mode {
- shape * N::from(0.5) + N::from(1.)
- } else {
- (mu - min) * (N::from(2.) * mode - min - max)
- / ((mode - mu) * (max - min))
- };
- let w = v * (max - mu) / (mu - min);
- let beta = Beta::new(v, w).map_err(|_| PertError::RangeTooSmall)?;
- Ok(Pert{ min, range, beta })
- }
-}
-
-impl<N: Float> Distribution<N> for Pert<N>
-where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
-{
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- self.beta.sample(rng) * self.range + self.min
- }
-}
-
-#[cfg(test)]
-mod test {
- use std::f64;
- use super::*;
-
- #[test]
- fn test_pert() {
- for &(min, max, mode) in &[
- (-1., 1., 0.),
- (1., 2., 1.),
- (5., 25., 25.),
- ] {
- let _distr = Pert::new(min, max, mode).unwrap();
- // TODO: test correctness
- }
-
- for &(min, max, mode) in &[
- (-1., 1., 2.),
- (-1., 1., -2.),
- (2., 1., 1.),
- ] {
- assert!(Pert::new(min, max, mode).is_err());
- }
- }
-
- #[test]
- fn value_stability() {
- let rng = crate::test::rng(860);
- let distr = Pert::new(2., 10., 3.).unwrap(); // mean = 4, var = 12/7
- let seq = distr.sample_iter(rng).take(5).collect::<Vec<f64>>();
- println!("seq: {:?}", seq);
- let expected = vec![4.631484136029422, 3.307201472321789,
- 3.29995019556348, 3.66835483991721, 3.514246139933899];
- assert!(seq == expected);
- }
-}
diff --git a/rand/rand_distr/src/poisson.rs b/rand/rand_distr/src/poisson.rs
deleted file mode 100644
index 4f4a0b7..0000000
--- a/rand/rand_distr/src/poisson.rs
+++ /dev/null
@@ -1,233 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2016-2017 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The Poisson distribution.
-
-use rand::Rng;
-use crate::{Distribution, Cauchy, Standard};
-use crate::utils::Float;
-
-/// The Poisson distribution `Poisson(lambda)`.
-///
-/// This distribution has a density function:
-/// `f(k) = lambda^k * exp(-lambda) / k!` for `k >= 0`.
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{Poisson, Distribution};
-///
-/// let poi = Poisson::new(2.0).unwrap();
-/// let v: u64 = poi.sample(&mut rand::thread_rng());
-/// println!("{} is from a Poisson(2) distribution", v);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Poisson<N> {
- lambda: N,
- // precalculated values
- exp_lambda: N,
- log_lambda: N,
- sqrt_2lambda: N,
- magic_val: N,
-}
-
-/// Error type returned from `Poisson::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum Error {
- /// `lambda <= 0` or `nan`.
- ShapeTooSmall,
-}
-
-impl<N: Float> Poisson<N>
-where Standard: Distribution<N>
-{
- /// Construct a new `Poisson` with the given shape parameter
- /// `lambda`.
- pub fn new(lambda: N) -> Result<Poisson<N>, Error> {
- if !(lambda > N::from(0.0)) {
- return Err(Error::ShapeTooSmall);
- }
- let log_lambda = lambda.ln();
- Ok(Poisson {
- lambda,
- exp_lambda: (-lambda).exp(),
- log_lambda,
- sqrt_2lambda: (N::from(2.0) * lambda).sqrt(),
- magic_val: lambda * log_lambda - (N::from(1.0) + lambda).log_gamma(),
- })
- }
-}
-
-impl<N: Float> Distribution<N> for Poisson<N>
-where Standard: Distribution<N>
-{
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- // using the algorithm from Numerical Recipes in C
-
- // for low expected values use the Knuth method
- if self.lambda < N::from(12.0) {
- let mut result = N::from(0.);
- let mut p = N::from(1.0);
- while p > self.exp_lambda {
- p *= rng.gen::<N>();
- result += N::from(1.);
- }
- result - N::from(1.)
- }
- // high expected values - rejection method
- else {
- // we use the Cauchy distribution as the comparison distribution
- // f(x) ~ 1/(1+x^2)
- let cauchy = Cauchy::new(N::from(0.0), N::from(1.0)).unwrap();
- let mut result;
-
- loop {
- let mut comp_dev;
-
- loop {
- // draw from the Cauchy distribution
- comp_dev = rng.sample(cauchy);
- // shift the peak of the comparison ditribution
- result = self.sqrt_2lambda * comp_dev + self.lambda;
- // repeat the drawing until we are in the range of possible values
- if result >= N::from(0.0) {
- break;
- }
- }
- // now the result is a random variable greater than 0 with Cauchy distribution
- // the result should be an integer value
- result = result.floor();
-
- // this is the ratio of the Poisson distribution to the comparison distribution
- // the magic value scales the distribution function to a range of approximately 0-1
- // since it is not exact, we multiply the ratio by 0.9 to avoid ratios greater than 1
- // this doesn't change the resulting distribution, only increases the rate of failed drawings
- let check = N::from(0.9) * (N::from(1.0) + comp_dev * comp_dev)
- * (result * self.log_lambda - (N::from(1.0) + result).log_gamma() - self.magic_val).exp();
-
- // check with uniform random value - if below the threshold, we are within the target distribution
- if rng.gen::<N>() <= check {
- break;
- }
- }
- result
- }
- }
-}
-
-impl<N: Float> Distribution<u64> for Poisson<N>
-where Standard: Distribution<N>
-{
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u64 {
- let result: N = self.sample(rng);
- result.to_u64().unwrap()
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::Distribution;
- use super::Poisson;
-
- #[test]
- fn test_poisson_10() {
- let poisson = Poisson::new(10.0).unwrap();
- let mut rng = crate::test::rng(123);
- let mut sum_u64 = 0;
- let mut sum_f64 = 0.;
- for _ in 0..1000 {
- let s_u64: u64 = poisson.sample(&mut rng);
- let s_f64: f64 = poisson.sample(&mut rng);
- sum_u64 += s_u64;
- sum_f64 += s_f64;
- }
- let avg_u64 = (sum_u64 as f64) / 1000.0;
- let avg_f64 = sum_f64 / 1000.0;
- println!("Poisson averages: {} (u64) {} (f64)", avg_u64, avg_f64);
- for &avg in &[avg_u64, avg_f64] {
- assert!((avg - 10.0).abs() < 0.5); // not 100% certain, but probable enough
- }
- }
-
- #[test]
- fn test_poisson_15() {
- // Take the 'high expected values' path
- let poisson = Poisson::new(15.0).unwrap();
- let mut rng = crate::test::rng(123);
- let mut sum_u64 = 0;
- let mut sum_f64 = 0.;
- for _ in 0..1000 {
- let s_u64: u64 = poisson.sample(&mut rng);
- let s_f64: f64 = poisson.sample(&mut rng);
- sum_u64 += s_u64;
- sum_f64 += s_f64;
- }
- let avg_u64 = (sum_u64 as f64) / 1000.0;
- let avg_f64 = sum_f64 / 1000.0;
- println!("Poisson average: {} (u64) {} (f64)", avg_u64, avg_f64);
- for &avg in &[avg_u64, avg_f64] {
- assert!((avg - 15.0).abs() < 0.5); // not 100% certain, but probable enough
- }
- }
-
- #[test]
- fn test_poisson_10_f32() {
- let poisson = Poisson::new(10.0f32).unwrap();
- let mut rng = crate::test::rng(123);
- let mut sum_u64 = 0;
- let mut sum_f32 = 0.;
- for _ in 0..1000 {
- let s_u64: u64 = poisson.sample(&mut rng);
- let s_f32: f32 = poisson.sample(&mut rng);
- sum_u64 += s_u64;
- sum_f32 += s_f32;
- }
- let avg_u64 = (sum_u64 as f32) / 1000.0;
- let avg_f32 = sum_f32 / 1000.0;
- println!("Poisson averages: {} (u64) {} (f32)", avg_u64, avg_f32);
- for &avg in &[avg_u64, avg_f32] {
- assert!((avg - 10.0).abs() < 0.5); // not 100% certain, but probable enough
- }
- }
-
- #[test]
- fn test_poisson_15_f32() {
- // Take the 'high expected values' path
- let poisson = Poisson::new(15.0f32).unwrap();
- let mut rng = crate::test::rng(123);
- let mut sum_u64 = 0;
- let mut sum_f32 = 0.;
- for _ in 0..1000 {
- let s_u64: u64 = poisson.sample(&mut rng);
- let s_f32: f32 = poisson.sample(&mut rng);
- sum_u64 += s_u64;
- sum_f32 += s_f32;
- }
- let avg_u64 = (sum_u64 as f32) / 1000.0;
- let avg_f32 = sum_f32 / 1000.0;
- println!("Poisson average: {} (u64) {} (f32)", avg_u64, avg_f32);
- for &avg in &[avg_u64, avg_f32] {
- assert!((avg - 15.0).abs() < 0.5); // not 100% certain, but probable enough
- }
- }
-
- #[test]
- #[should_panic]
- fn test_poisson_invalid_lambda_zero() {
- Poisson::new(0.0).unwrap();
- }
-
- #[test]
- #[should_panic]
- fn test_poisson_invalid_lambda_neg() {
- Poisson::new(-10.0).unwrap();
- }
-}
diff --git a/rand/rand_distr/src/triangular.rs b/rand/rand_distr/src/triangular.rs
deleted file mode 100644
index dd0bbfb..0000000
--- a/rand/rand_distr/src/triangular.rs
+++ /dev/null
@@ -1,125 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-//! The triangular distribution.
-
-use rand::Rng;
-use crate::{Distribution, Standard};
-use crate::utils::Float;
-
-/// The triangular distribution.
-///
-/// A continuous probability distribution parameterised by a range, and a mode
-/// (most likely value) within that range.
-///
-/// The probability density function is triangular. For a similar distribution
-/// with a smooth PDF, see the [`Pert`] distribution.
-///
-/// # Example
-///
-/// ```rust
-/// use rand_distr::{Triangular, Distribution};
-///
-/// let d = Triangular::new(0., 5., 2.5).unwrap();
-/// let v = d.sample(&mut rand::thread_rng());
-/// println!("{} is from a triangular distribution", v);
-/// ```
-///
-/// [`Pert`]: crate::Pert
-#[derive(Clone, Copy, Debug)]
-pub struct Triangular<N> {
- min: N,
- max: N,
- mode: N,
-}
-
-/// Error type returned from [`Triangular::new`].
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum TriangularError {
- /// `max < min` or `min` or `max` is NaN.
- RangeTooSmall,
- /// `mode < min` or `mode > max` or `mode` is NaN.
- ModeRange,
-}
-
-impl<N: Float> Triangular<N>
-where Standard: Distribution<N>
-{
- /// Set up the Triangular distribution with defined `min`, `max` and `mode`.
- #[inline]
- pub fn new(min: N, max: N, mode: N) -> Result<Triangular<N>, TriangularError> {
- if !(max >= min) {
- return Err(TriangularError::RangeTooSmall);
- }
- if !(mode >= min && max >= mode) {
- return Err(TriangularError::ModeRange);
- }
- Ok(Triangular { min, max, mode })
- }
-}
-
-impl<N: Float> Distribution<N> for Triangular<N>
-where Standard: Distribution<N>
-{
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- let f: N = rng.sample(Standard);
- let diff_mode_min = self.mode - self.min;
- let range = self.max - self.min;
- let f_range = f * range;
- if f_range < diff_mode_min {
- self.min + (f_range * diff_mode_min).sqrt()
- } else {
- self.max - ((range - f_range) * (self.max - self.mode)).sqrt()
- }
- }
-}
-
-#[cfg(test)]
-mod test {
- use std::f64;
- use rand::{Rng, rngs::mock};
- use super::*;
-
- #[test]
- fn test_triangular() {
- let mut half_rng = mock::StepRng::new(0x8000_0000_0000_0000, 0);
- assert_eq!(half_rng.gen::<f64>(), 0.5);
- for &(min, max, mode, median) in &[
- (-1., 1., 0., 0.),
- (1., 2., 1., 2. - 0.5f64.sqrt()),
- (5., 25., 25., 5. + 200f64.sqrt()),
- (1e-5, 1e5, 1e-3, 1e5 - 4999999949.5f64.sqrt()),
- (0., 1., 0.9, 0.45f64.sqrt()),
- (-4., -0.5, -2., -4.0 + 3.5f64.sqrt()),
- ] {
- println!("{} {} {} {}", min, max, mode, median);
- let distr = Triangular::new(min, max, mode).unwrap();
- // Test correct value at median:
- assert_eq!(distr.sample(&mut half_rng), median);
- }
-
- for &(min, max, mode) in &[
- (-1., 1., 2.),
- (-1., 1., -2.),
- (2., 1., 1.),
- ] {
- assert!(Triangular::new(min, max, mode).is_err());
- }
- }
-
- #[test]
- fn value_stability() {
- let rng = crate::test::rng(860);
- let distr = Triangular::new(2., 10., 3.).unwrap();
- let seq = distr.sample_iter(rng).take(5).collect::<Vec<f64>>();
- println!("seq: {:?}", seq);
- let expected = vec![5.74373257511361, 7.890059162791258,
- 4.7256280652553455, 2.9474808121184077, 3.058301946314053];
- assert!(seq == expected);
- }
-}
diff --git a/rand/rand_distr/src/unit_ball.rs b/rand/rand_distr/src/unit_ball.rs
deleted file mode 100644
index 9d61627..0000000
--- a/rand/rand_distr/src/unit_ball.rs
+++ /dev/null
@@ -1,69 +0,0 @@
-// Copyright 2019 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-use rand::Rng;
-use crate::{Distribution, Uniform, uniform::SampleUniform};
-use crate::utils::Float;
-
-/// Samples uniformly from the unit ball (surface and interior) in three
-/// dimensions.
-///
-/// Implemented via rejection sampling.
-///
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{UnitBall, Distribution};
-///
-/// let v: [f64; 3] = UnitBall.sample(&mut rand::thread_rng());
-/// println!("{:?} is from the unit ball.", v)
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct UnitBall;
-
-impl<N: Float + SampleUniform> Distribution<[N; 3]> for UnitBall {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> [N; 3] {
- let uniform = Uniform::new(N::from(-1.), N::from(1.));
- let mut x1;
- let mut x2;
- let mut x3;
- loop {
- x1 = uniform.sample(rng);
- x2 = uniform.sample(rng);
- x3 = uniform.sample(rng);
- if x1*x1 + x2*x2 + x3*x3 <= N::from(1.) {
- break;
- }
- }
- [x1, x2, x3]
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::Distribution;
- use super::UnitBall;
-
- #[test]
- fn value_stability() {
- let mut rng = crate::test::rng(2);
- let expected = [
- [0.018035709265959987, -0.4348771383120438, -0.07982762085055706],
- [0.10588569388223945, -0.4734350111375454, -0.7392104908825501],
- [0.11060237642041049, -0.16065642822852677, -0.8444043930440075]
- ];
- let samples: [[f64; 3]; 3] = [
- UnitBall.sample(&mut rng),
- UnitBall.sample(&mut rng),
- UnitBall.sample(&mut rng),
- ];
- assert_eq!(samples, expected);
- }
-}
diff --git a/rand/rand_distr/src/unit_circle.rs b/rand/rand_distr/src/unit_circle.rs
deleted file mode 100644
index 5863a1a..0000000
--- a/rand/rand_distr/src/unit_circle.rs
+++ /dev/null
@@ -1,99 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-use rand::Rng;
-use crate::{Distribution, Uniform, uniform::SampleUniform};
-use crate::utils::Float;
-
-/// Samples uniformly from the edge of the unit circle in two dimensions.
-///
-/// Implemented via a method by von Neumann[^1].
-///
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{UnitCircle, Distribution};
-///
-/// let v: [f64; 2] = UnitCircle.sample(&mut rand::thread_rng());
-/// println!("{:?} is from the unit circle.", v)
-/// ```
-///
-/// [^1]: von Neumann, J. (1951) [*Various Techniques Used in Connection with
-/// Random Digits.*](https://mcnp.lanl.gov/pdf_files/nbs_vonneumann.pdf)
-/// NBS Appl. Math. Ser., No. 12. Washington, DC: U.S. Government Printing
-/// Office, pp. 36-38.
-#[derive(Clone, Copy, Debug)]
-pub struct UnitCircle;
-
-impl<N: Float + SampleUniform> Distribution<[N; 2]> for UnitCircle {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> [N; 2] {
- let uniform = Uniform::new(N::from(-1.), N::from(1.));
- let mut x1;
- let mut x2;
- let mut sum;
- loop {
- x1 = uniform.sample(rng);
- x2 = uniform.sample(rng);
- sum = x1*x1 + x2*x2;
- if sum < N::from(1.) {
- break;
- }
- }
- let diff = x1*x1 - x2*x2;
- [diff / sum, N::from(2.)*x1*x2 / sum]
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::Distribution;
- use super::UnitCircle;
-
- /// Assert that two numbers are almost equal to each other.
- ///
- /// On panic, this macro will print the values of the expressions with their
- /// debug representations.
- macro_rules! assert_almost_eq {
- ($a:expr, $b:expr, $prec:expr) => (
- let diff = ($a - $b).abs();
- if diff > $prec {
- panic!(format!(
- "assertion failed: `abs(left - right) = {:.1e} < {:e}`, \
- (left: `{}`, right: `{}`)",
- diff, $prec, $a, $b));
- }
- );
- }
-
- #[test]
- fn norm() {
- let mut rng = crate::test::rng(1);
- for _ in 0..1000 {
- let x: [f64; 2] = UnitCircle.sample(&mut rng);
- assert_almost_eq!(x[0]*x[0] + x[1]*x[1], 1., 1e-15);
- }
- }
-
- #[test]
- fn value_stability() {
- let mut rng = crate::test::rng(2);
- let expected = [
- [-0.9965658683520504, -0.08280380447614634],
- [-0.9790853270389644, -0.20345004884984505],
- [-0.8449189758898707, 0.5348943112253227],
- ];
- let samples: [[f64; 2]; 3] = [
- UnitCircle.sample(&mut rng),
- UnitCircle.sample(&mut rng),
- UnitCircle.sample(&mut rng),
- ];
- assert_eq!(samples, expected);
- }
-}
diff --git a/rand/rand_distr/src/unit_disc.rs b/rand/rand_distr/src/unit_disc.rs
deleted file mode 100644
index 97abc2f..0000000
--- a/rand/rand_distr/src/unit_disc.rs
+++ /dev/null
@@ -1,66 +0,0 @@
-// Copyright 2019 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-use rand::Rng;
-use crate::{Distribution, Uniform, uniform::SampleUniform};
-use crate::utils::Float;
-
-/// Samples uniformly from the unit disc in two dimensions.
-///
-/// Implemented via rejection sampling.
-///
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{UnitDisc, Distribution};
-///
-/// let v: [f64; 2] = UnitDisc.sample(&mut rand::thread_rng());
-/// println!("{:?} is from the unit Disc.", v)
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct UnitDisc;
-
-impl<N: Float + SampleUniform> Distribution<[N; 2]> for UnitDisc {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> [N; 2] {
- let uniform = Uniform::new(N::from(-1.), N::from(1.));
- let mut x1;
- let mut x2;
- loop {
- x1 = uniform.sample(rng);
- x2 = uniform.sample(rng);
- if x1*x1 + x2*x2 <= N::from(1.) {
- break;
- }
- }
- [x1, x2]
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::Distribution;
- use super::UnitDisc;
-
- #[test]
- fn value_stability() {
- let mut rng = crate::test::rng(2);
- let expected = [
- [0.018035709265959987, -0.4348771383120438],
- [-0.07982762085055706, 0.7765329819820659],
- [0.21450745997299503, 0.7398636984333291]
- ];
- let samples: [[f64; 2]; 3] = [
- UnitDisc.sample(&mut rng),
- UnitDisc.sample(&mut rng),
- UnitDisc.sample(&mut rng),
- ];
- assert_eq!(samples, expected);
- }
-}
diff --git a/rand/rand_distr/src/unit_sphere.rs b/rand/rand_distr/src/unit_sphere.rs
deleted file mode 100644
index 8e0c361..0000000
--- a/rand/rand_distr/src/unit_sphere.rs
+++ /dev/null
@@ -1,94 +0,0 @@
-// Copyright 2018-2019 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-use rand::Rng;
-use crate::{Distribution, Uniform, uniform::SampleUniform};
-use crate::utils::Float;
-
-/// Samples uniformly from the surface of the unit sphere in three dimensions.
-///
-/// Implemented via a method by Marsaglia[^1].
-///
-///
-/// # Example
-///
-/// ```
-/// use rand_distr::{UnitSphere, Distribution};
-///
-/// let v: [f64; 3] = UnitSphere.sample(&mut rand::thread_rng());
-/// println!("{:?} is from the unit sphere surface.", v)
-/// ```
-///
-/// [^1]: Marsaglia, George (1972). [*Choosing a Point from the Surface of a
-/// Sphere.*](https://doi.org/10.1214/aoms/1177692644)
-/// Ann. Math. Statist. 43, no. 2, 645--646.
-#[derive(Clone, Copy, Debug)]
-pub struct UnitSphere;
-
-impl<N: Float + SampleUniform> Distribution<[N; 3]> for UnitSphere {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> [N; 3] {
- let uniform = Uniform::new(N::from(-1.), N::from(1.));
- loop {
- let (x1, x2) = (uniform.sample(rng), uniform.sample(rng));
- let sum = x1*x1 + x2*x2;
- if sum >= N::from(1.) {
- continue;
- }
- let factor = N::from(2.) * (N::from(1.0) - sum).sqrt();
- return [x1 * factor, x2 * factor, N::from(1.) - N::from(2.)*sum];
- }
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::Distribution;
- use super::UnitSphere;
-
- /// Assert that two numbers are almost equal to each other.
- ///
- /// On panic, this macro will print the values of the expressions with their
- /// debug representations.
- macro_rules! assert_almost_eq {
- ($a:expr, $b:expr, $prec:expr) => (
- let diff = ($a - $b).abs();
- if diff > $prec {
- panic!(format!(
- "assertion failed: `abs(left - right) = {:.1e} < {:e}`, \
- (left: `{}`, right: `{}`)",
- diff, $prec, $a, $b));
- }
- );
- }
-
- #[test]
- fn norm() {
- let mut rng = crate::test::rng(1);
- for _ in 0..1000 {
- let x: [f64; 3] = UnitSphere.sample(&mut rng);
- assert_almost_eq!(x[0]*x[0] + x[1]*x[1] + x[2]*x[2], 1., 1e-15);
- }
- }
-
- #[test]
- fn value_stability() {
- let mut rng = crate::test::rng(2);
- let expected = [
- [0.03247542860231647, -0.7830477442152738, 0.6211131755296027],
- [-0.09978440840914075, 0.9706650829833128, -0.21875184231323952],
- [0.2735582468624679, 0.9435374242279655, -0.1868234852870203],
- ];
- let samples: [[f64; 3]; 3] = [
- UnitSphere.sample(&mut rng),
- UnitSphere.sample(&mut rng),
- UnitSphere.sample(&mut rng),
- ];
- assert_eq!(samples, expected);
- }
-}
diff --git a/rand/rand_distr/src/utils.rs b/rand/rand_distr/src/utils.rs
deleted file mode 100644
index 75b3500..0000000
--- a/rand/rand_distr/src/utils.rs
+++ /dev/null
@@ -1,234 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Math helper functions
-
-use rand::Rng;
-use crate::ziggurat_tables;
-use rand::distributions::hidden_export::IntoFloat;
-use core::{cmp, ops};
-
-/// Trait for floating-point scalar types
-///
-/// This allows many distributions to work with `f32` or `f64` parameters and is
-/// potentially extensible. Note however that the `Exp1` and `StandardNormal`
-/// distributions are implemented exclusively for `f32` and `f64`.
-///
-/// The bounds and methods are based purely on internal
-/// requirements, and will change as needed.
-pub trait Float: Copy + Sized + cmp::PartialOrd
- + ops::Neg<Output = Self>
- + ops::Add<Output = Self>
- + ops::Sub<Output = Self>
- + ops::Mul<Output = Self>
- + ops::Div<Output = Self>
- + ops::AddAssign + ops::SubAssign + ops::MulAssign + ops::DivAssign
-{
- /// The constant Ο
- fn pi() -> Self;
- /// Support approximate representation of a f64 value
- fn from(x: f64) -> Self;
- /// Support converting to an unsigned integer.
- fn to_u64(self) -> Option<u64>;
-
- /// Take the absolute value of self
- fn abs(self) -> Self;
- /// Take the largest integer less than or equal to self
- fn floor(self) -> Self;
-
- /// Take the exponential of self
- fn exp(self) -> Self;
- /// Take the natural logarithm of self
- fn ln(self) -> Self;
- /// Take square root of self
- fn sqrt(self) -> Self;
- /// Take self to a floating-point power
- fn powf(self, power: Self) -> Self;
-
- /// Take the tangent of self
- fn tan(self) -> Self;
- /// Take the logarithm of the gamma function of self
- fn log_gamma(self) -> Self;
-}
-
-impl Float for f32 {
- #[inline]
- fn pi() -> Self { core::f32::consts::PI }
- #[inline]
- fn from(x: f64) -> Self { x as f32 }
- #[inline]
- fn to_u64(self) -> Option<u64> {
- if self >= 0. && self <= ::core::u64::MAX as f32 {
- Some(self as u64)
- } else {
- None
- }
- }
-
- #[inline]
- fn abs(self) -> Self { self.abs() }
- #[inline]
- fn floor(self) -> Self { self.floor() }
-
- #[inline]
- fn exp(self) -> Self { self.exp() }
- #[inline]
- fn ln(self) -> Self { self.ln() }
- #[inline]
- fn sqrt(self) -> Self { self.sqrt() }
- #[inline]
- fn powf(self, power: Self) -> Self { self.powf(power) }
-
- #[inline]
- fn tan(self) -> Self { self.tan() }
- #[inline]
- fn log_gamma(self) -> Self {
- let result = log_gamma(self.into());
- assert!(result <= ::core::f32::MAX.into());
- assert!(result >= ::core::f32::MIN.into());
- result as f32
- }
-}
-
-impl Float for f64 {
- #[inline]
- fn pi() -> Self { core::f64::consts::PI }
- #[inline]
- fn from(x: f64) -> Self { x }
- #[inline]
- fn to_u64(self) -> Option<u64> {
- if self >= 0. && self <= ::core::u64::MAX as f64 {
- Some(self as u64)
- } else {
- None
- }
- }
-
- #[inline]
- fn abs(self) -> Self { self.abs() }
- #[inline]
- fn floor(self) -> Self { self.floor() }
-
- #[inline]
- fn exp(self) -> Self { self.exp() }
- #[inline]
- fn ln(self) -> Self { self.ln() }
- #[inline]
- fn sqrt(self) -> Self { self.sqrt() }
- #[inline]
- fn powf(self, power: Self) -> Self { self.powf(power) }
-
- #[inline]
- fn tan(self) -> Self { self.tan() }
- #[inline]
- fn log_gamma(self) -> Self { log_gamma(self) }
-}
-
-/// Calculates ln(gamma(x)) (natural logarithm of the gamma
-/// function) using the Lanczos approximation.
-///
-/// The approximation expresses the gamma function as:
-/// `gamma(z+1) = sqrt(2*pi)*(z+g+0.5)^(z+0.5)*exp(-z-g-0.5)*Ag(z)`
-/// `g` is an arbitrary constant; we use the approximation with `g=5`.
-///
-/// Noting that `gamma(z+1) = z*gamma(z)` and applying `ln` to both sides:
-/// `ln(gamma(z)) = (z+0.5)*ln(z+g+0.5)-(z+g+0.5) + ln(sqrt(2*pi)*Ag(z)/z)`
-///
-/// `Ag(z)` is an infinite series with coefficients that can be calculated
-/// ahead of time - we use just the first 6 terms, which is good enough
-/// for most purposes.
-pub(crate) fn log_gamma(x: f64) -> f64 {
- // precalculated 6 coefficients for the first 6 terms of the series
- let coefficients: [f64; 6] = [
- 76.18009172947146,
- -86.50532032941677,
- 24.01409824083091,
- -1.231739572450155,
- 0.1208650973866179e-2,
- -0.5395239384953e-5,
- ];
-
- // (x+0.5)*ln(x+g+0.5)-(x+g+0.5)
- let tmp = x + 5.5;
- let log = (x + 0.5) * tmp.ln() - tmp;
-
- // the first few terms of the series for Ag(x)
- let mut a = 1.000000000190015;
- let mut denom = x;
- for &coeff in &coefficients {
- denom += 1.0;
- a += coeff / denom;
- }
-
- // get everything together
- // a is Ag(x)
- // 2.5066... is sqrt(2pi)
- log + (2.5066282746310005 * a / x).ln()
-}
-
-/// 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)
-
-// the perf improvement (25-50%) is definitely worth the extra code
-// size from force-inlining.
-#[inline(always)]
-pub(crate) fn ziggurat<R: Rng + ?Sized, P, Z>(
- rng: &mut R,
- symmetric: bool,
- x_tab: ziggurat_tables::ZigTable,
- f_tab: ziggurat_tables::ZigTable,
- mut pdf: P,
- mut zero_case: Z)
- -> f64 where P: FnMut(f64) -> f64, Z: FnMut(&mut R, f64) -> f64 {
- loop {
- // As an optimisation we re-implement the conversion to a f64.
- // From the remaining 12 most significant bits we use 8 to construct `i`.
- // This saves us generating a whole extra random number, while the added
- // precision of using 64 bits for f64 does not buy us much.
- let bits = rng.next_u64();
- let i = bits as usize & 0xff;
-
- let u = if symmetric {
- // Convert to a value in the range [2,4) and substract to get [-1,1)
- // We can't convert to an open range directly, that would require
- // substracting `3.0 - EPSILON`, which is not representable.
- // It is possible with an extra step, but an open range does not
- // seem neccesary for the ziggurat algorithm anyway.
- (bits >> 12).into_float_with_exponent(1) - 3.0
- } else {
- // Convert to a value in the range [1,2) and substract to get (0,1)
- (bits >> 12).into_float_with_exponent(0)
- - (1.0 - std::f64::EPSILON / 2.0)
- };
- let x = u * x_tab[i];
-
- let test_x = if symmetric { x.abs() } else {x};
-
- // algebraically equivalent to |u| < x_tab[i+1]/x_tab[i] (or u < x_tab[i+1]/x_tab[i])
- if test_x < x_tab[i + 1] {
- return x;
- }
- if i == 0 {
- return zero_case(rng, u);
- }
- // algebraically equivalent to f1 + DRanU()*(f0 - f1) < 1
- if f_tab[i + 1] + (f_tab[i] - f_tab[i + 1]) * rng.gen::<f64>() < pdf(x) {
- return x;
- }
- }
-}
diff --git a/rand/rand_distr/src/weibull.rs b/rand/rand_distr/src/weibull.rs
deleted file mode 100644
index ddde380..0000000
--- a/rand/rand_distr/src/weibull.rs
+++ /dev/null
@@ -1,86 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The Weibull distribution.
-
-use rand::Rng;
-use crate::{Distribution, OpenClosed01};
-use crate::utils::Float;
-
-/// Samples floating-point numbers according to the Weibull distribution
-///
-/// # Example
-/// ```
-/// use rand::prelude::*;
-/// use rand_distr::Weibull;
-///
-/// let val: f64 = thread_rng().sample(Weibull::new(1., 10.).unwrap());
-/// println!("{}", val);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Weibull<N> {
- inv_shape: N,
- scale: N,
-}
-
-/// Error type returned from `Weibull::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum Error {
- /// `scale <= 0` or `nan`.
- ScaleTooSmall,
- /// `shape <= 0` or `nan`.
- ShapeTooSmall,
-}
-
-impl<N: Float> Weibull<N>
-where OpenClosed01: Distribution<N>
-{
- /// Construct a new `Weibull` distribution with given `scale` and `shape`.
- pub fn new(scale: N, shape: N) -> Result<Weibull<N>, Error> {
- if !(scale > N::from(0.0)) {
- return Err(Error::ScaleTooSmall);
- }
- if !(shape > N::from(0.0)) {
- return Err(Error::ShapeTooSmall);
- }
- Ok(Weibull { inv_shape: N::from(1.)/shape, scale })
- }
-}
-
-impl<N: Float> Distribution<N> for Weibull<N>
-where OpenClosed01: Distribution<N>
-{
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
- let x: N = rng.sample(OpenClosed01);
- self.scale * (-x.ln()).powf(self.inv_shape)
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::Distribution;
- use super::Weibull;
-
- #[test]
- #[should_panic]
- fn invalid() {
- Weibull::new(0., 0.).unwrap();
- }
-
- #[test]
- fn sample() {
- let scale = 1.0;
- let shape = 2.0;
- let d = Weibull::new(scale, shape).unwrap();
- let mut rng = crate::test::rng(1);
- for _ in 0..1000 {
- let r = d.sample(&mut rng);
- assert!(r >= 0.);
- }
- }
-}
diff --git a/rand/rand_distr/src/ziggurat_tables.rs b/rand/rand_distr/src/ziggurat_tables.rs
deleted file mode 100644
index ca1ce30..0000000
--- a/rand/rand_distr/src/ziggurat_tables.rs
+++ /dev/null
@@ -1,279 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-// Tables for distributions which are sampled using the ziggurat
-// algorithm. Autogenerated by `ziggurat_tables.py`.
-
-pub type ZigTable = &'static [f64; 257];
-pub const ZIG_NORM_R: f64 = 3.654152885361008796;
-pub static ZIG_NORM_X: [f64; 257] =
- [3.910757959537090045, 3.654152885361008796, 3.449278298560964462, 3.320244733839166074,
- 3.224575052047029100, 3.147889289517149969, 3.083526132001233044, 3.027837791768635434,
- 2.978603279880844834, 2.934366867207854224, 2.894121053612348060, 2.857138730872132548,
- 2.822877396825325125, 2.790921174000785765, 2.760944005278822555, 2.732685359042827056,
- 2.705933656121858100, 2.680514643284522158, 2.656283037575502437, 2.633116393630324570,
- 2.610910518487548515, 2.589575986706995181, 2.569035452680536569, 2.549221550323460761,
- 2.530075232158516929, 2.511544441625342294, 2.493583041269680667, 2.476149939669143318,
- 2.459208374333311298, 2.442725318198956774, 2.426670984935725972, 2.411018413899685520,
- 2.395743119780480601, 2.380822795170626005, 2.366237056715818632, 2.351967227377659952,
- 2.337996148795031370, 2.324308018869623016, 2.310888250599850036, 2.297723348901329565,
- 2.284800802722946056, 2.272108990226823888, 2.259637095172217780, 2.247375032945807760,
- 2.235313384928327984, 2.223443340090905718, 2.211756642882544366, 2.200245546609647995,
- 2.188902771624720689, 2.177721467738641614, 2.166695180352645966, 2.155817819875063268,
- 2.145083634046203613, 2.134487182844320152, 2.124023315687815661, 2.113687150684933957,
- 2.103474055713146829, 2.093379631137050279, 2.083399693996551783, 2.073530263516978778,
- 2.063767547809956415, 2.054107931648864849, 2.044547965215732788, 2.035084353727808715,
- 2.025713947862032960, 2.016433734904371722, 2.007240830558684852, 1.998132471356564244,
- 1.989106007615571325, 1.980158896898598364, 1.971288697931769640, 1.962493064942461896,
- 1.953769742382734043, 1.945116560006753925, 1.936531428273758904, 1.928012334050718257,
- 1.919557336591228847, 1.911164563769282232, 1.902832208548446369, 1.894558525668710081,
- 1.886341828534776388, 1.878180486290977669, 1.870072921069236838, 1.862017605397632281,
- 1.854013059758148119, 1.846057850283119750, 1.838150586580728607, 1.830289919680666566,
- 1.822474540091783224, 1.814703175964167636, 1.806974591348693426, 1.799287584547580199,
- 1.791640986550010028, 1.784033659547276329, 1.776464495522344977, 1.768932414909077933,
- 1.761436365316706665, 1.753975320315455111, 1.746548278279492994, 1.739154261283669012,
- 1.731792314050707216, 1.724461502945775715, 1.717160915015540690, 1.709889657069006086,
- 1.702646854797613907, 1.695431651932238548, 1.688243209434858727, 1.681080704722823338,
- 1.673943330923760353, 1.666830296159286684, 1.659740822855789499, 1.652674147080648526,
- 1.645629517902360339, 1.638606196773111146, 1.631603456932422036, 1.624620582830568427,
- 1.617656869570534228, 1.610711622367333673, 1.603784156023583041, 1.596873794420261339,
- 1.589979870021648534, 1.583101723393471438, 1.576238702733332886, 1.569390163412534456,
- 1.562555467528439657, 1.555733983466554893, 1.548925085471535512, 1.542128153226347553,
- 1.535342571438843118, 1.528567729435024614, 1.521803020758293101, 1.515047842773992404,
- 1.508301596278571965, 1.501563685112706548, 1.494833515777718391, 1.488110497054654369,
- 1.481394039625375747, 1.474683555695025516, 1.467978458615230908, 1.461278162507407830,
- 1.454582081885523293, 1.447889631277669675, 1.441200224845798017, 1.434513276002946425,
- 1.427828197027290358, 1.421144398672323117, 1.414461289772464658, 1.407778276843371534,
- 1.401094763676202559, 1.394410150925071257, 1.387723835686884621, 1.381035211072741964,
- 1.374343665770030531, 1.367648583594317957, 1.360949343030101844, 1.354245316759430606,
- 1.347535871177359290, 1.340820365893152122, 1.334098153216083604, 1.327368577624624679,
- 1.320630975217730096, 1.313884673146868964, 1.307128989027353860, 1.300363230327433728,
- 1.293586693733517645, 1.286798664489786415, 1.279998415710333237, 1.273185207661843732,
- 1.266358287014688333, 1.259516886060144225, 1.252660221891297887, 1.245787495544997903,
- 1.238897891102027415, 1.231990574742445110, 1.225064693752808020, 1.218119375481726552,
- 1.211153726239911244, 1.204166830140560140, 1.197157747875585931, 1.190125515422801650,
- 1.183069142678760732, 1.175987612011489825, 1.168879876726833800, 1.161744859441574240,
- 1.154581450355851802, 1.147388505416733873, 1.140164844363995789, 1.132909248648336975,
- 1.125620459211294389, 1.118297174115062909, 1.110938046009249502, 1.103541679420268151,
- 1.096106627847603487, 1.088631390649514197, 1.081114409698889389, 1.073554065787871714,
- 1.065948674757506653, 1.058296483326006454, 1.050595664586207123, 1.042844313139370538,
- 1.035040439828605274, 1.027181966030751292, 1.019266717460529215, 1.011292417434978441,
- 1.003256679539591412, 0.995156999629943084, 0.986990747093846266, 0.978755155288937750,
- 0.970447311058864615, 0.962064143217605250, 0.953602409875572654, 0.945058684462571130,
- 0.936429340280896860, 0.927710533396234771, 0.918898183643734989, 0.909987953490768997,
- 0.900975224455174528, 0.891855070726792376, 0.882622229578910122, 0.873271068082494550,
- 0.863795545546826915, 0.854189171001560554, 0.844444954902423661, 0.834555354079518752,
- 0.824512208745288633, 0.814306670128064347, 0.803929116982664893, 0.793369058833152785,
- 0.782615023299588763, 0.771654424216739354, 0.760473406422083165, 0.749056662009581653,
- 0.737387211425838629, 0.725446140901303549, 0.713212285182022732, 0.700661841097584448,
- 0.687767892786257717, 0.674499822827436479, 0.660822574234205984, 0.646695714884388928,
- 0.632072236375024632, 0.616896989996235545, 0.601104617743940417, 0.584616766093722262,
- 0.567338257040473026, 0.549151702313026790, 0.529909720646495108, 0.509423329585933393,
- 0.487443966121754335, 0.463634336771763245, 0.437518402186662658, 0.408389134588000746,
- 0.375121332850465727, 0.335737519180459465, 0.286174591747260509, 0.215241895913273806,
- 0.000000000000000000];
-pub static ZIG_NORM_F: [f64; 257] =
- [0.000477467764586655, 0.001260285930498598, 0.002609072746106363, 0.004037972593371872,
- 0.005522403299264754, 0.007050875471392110, 0.008616582769422917, 0.010214971439731100,
- 0.011842757857943104, 0.013497450601780807, 0.015177088307982072, 0.016880083152595839,
- 0.018605121275783350, 0.020351096230109354, 0.022117062707379922, 0.023902203305873237,
- 0.025705804008632656, 0.027527235669693315, 0.029365939758230111, 0.031221417192023690,
- 0.033093219458688698, 0.034980941461833073, 0.036884215688691151, 0.038802707404656918,
- 0.040736110656078753, 0.042684144916619378, 0.044646552251446536, 0.046623094902089664,
- 0.048613553216035145, 0.050617723861121788, 0.052635418276973649, 0.054666461325077916,
- 0.056710690106399467, 0.058767952921137984, 0.060838108349751806, 0.062921024437977854,
- 0.065016577971470438, 0.067124653828023989, 0.069245144397250269, 0.071377949059141965,
- 0.073522973714240991, 0.075680130359194964, 0.077849336702372207, 0.080030515814947509,
- 0.082223595813495684, 0.084428509570654661, 0.086645194450867782, 0.088873592068594229,
- 0.091113648066700734, 0.093365311913026619, 0.095628536713353335, 0.097903279039215627,
- 0.100189498769172020, 0.102487158942306270, 0.104796225622867056, 0.107116667775072880,
- 0.109448457147210021, 0.111791568164245583, 0.114145977828255210, 0.116511665626037014,
- 0.118888613443345698, 0.121276805485235437, 0.123676228202051403, 0.126086870220650349,
- 0.128508722280473636, 0.130941777174128166, 0.133386029692162844, 0.135841476571757352,
- 0.138308116449064322, 0.140785949814968309, 0.143274978974047118, 0.145775208006537926,
- 0.148286642733128721, 0.150809290682410169, 0.153343161060837674, 0.155888264725064563,
- 0.158444614156520225, 0.161012223438117663, 0.163591108232982951, 0.166181285765110071,
- 0.168782774801850333, 0.171395595638155623, 0.174019770082499359, 0.176655321444406654,
- 0.179302274523530397, 0.181960655600216487, 0.184630492427504539, 0.187311814224516926,
- 0.190004651671193070, 0.192709036904328807, 0.195425003514885592, 0.198152586546538112,
- 0.200891822495431333, 0.203642749311121501, 0.206405406398679298, 0.209179834621935651,
- 0.211966076307852941, 0.214764175252008499, 0.217574176725178370, 0.220396127481011589,
- 0.223230075764789593, 0.226076071323264877, 0.228934165415577484, 0.231804410825248525,
- 0.234686861873252689, 0.237581574432173676, 0.240488605941449107, 0.243408015423711988,
- 0.246339863502238771, 0.249284212419516704, 0.252241126056943765, 0.255210669955677150,
- 0.258192911338648023, 0.261187919133763713, 0.264195763998317568, 0.267216518344631837,
- 0.270250256366959984, 0.273297054069675804, 0.276356989296781264, 0.279430141762765316,
- 0.282516593084849388, 0.285616426816658109, 0.288729728483353931, 0.291856585618280984,
- 0.294997087801162572, 0.298151326697901342, 0.301319396102034120, 0.304501391977896274,
- 0.307697412505553769, 0.310907558127563710, 0.314131931597630143, 0.317370638031222396,
- 0.320623784958230129, 0.323891482377732021, 0.327173842814958593, 0.330470981380537099,
- 0.333783015832108509, 0.337110066638412809, 0.340452257045945450, 0.343809713148291340,
- 0.347182563958251478, 0.350570941482881204, 0.353974980801569250, 0.357394820147290515,
- 0.360830600991175754, 0.364282468130549597, 0.367750569780596226, 0.371235057669821344,
- 0.374736087139491414, 0.378253817247238111, 0.381788410875031348, 0.385340034841733958,
- 0.388908860020464597, 0.392495061461010764, 0.396098818517547080, 0.399720314981931668,
- 0.403359739222868885, 0.407017284331247953, 0.410693148271983222, 0.414387534042706784,
- 0.418100649839684591, 0.421832709231353298, 0.425583931339900579, 0.429354541031341519,
- 0.433144769114574058, 0.436954852549929273, 0.440785034667769915, 0.444635565397727750,
- 0.448506701509214067, 0.452398706863882505, 0.456311852680773566, 0.460246417814923481,
- 0.464202689050278838, 0.468180961407822172, 0.472181538469883255, 0.476204732721683788,
- 0.480250865911249714, 0.484320269428911598, 0.488413284707712059, 0.492530263646148658,
- 0.496671569054796314, 0.500837575128482149, 0.505028667945828791, 0.509245245998136142,
- 0.513487720749743026, 0.517756517232200619, 0.522052074674794864, 0.526374847174186700,
- 0.530725304406193921, 0.535103932383019565, 0.539511234259544614, 0.543947731192649941,
- 0.548413963257921133, 0.552910490428519918, 0.557437893621486324, 0.561996775817277916,
- 0.566587763258951771, 0.571211506738074970, 0.575868682975210544, 0.580559996103683473,
- 0.585286179266300333, 0.590047996335791969, 0.594846243770991268, 0.599681752622167719,
- 0.604555390700549533, 0.609468064928895381, 0.614420723892076803, 0.619414360609039205,
- 0.624450015550274240, 0.629528779928128279, 0.634651799290960050, 0.639820277456438991,
- 0.645035480824251883, 0.650298743114294586, 0.655611470583224665, 0.660975147780241357,
- 0.666391343912380640, 0.671861719900766374, 0.677388036222513090, 0.682972161648791376,
- 0.688616083008527058, 0.694321916130032579, 0.700091918140490099, 0.705928501336797409,
- 0.711834248882358467, 0.717811932634901395, 0.723864533472881599, 0.729995264565802437,
- 0.736207598131266683, 0.742505296344636245, 0.748892447223726720, 0.755373506511754500,
- 0.761953346841546475, 0.768637315803334831, 0.775431304986138326, 0.782341832659861902,
- 0.789376143571198563, 0.796542330428254619, 0.803849483176389490, 0.811307874318219935,
- 0.818929191609414797, 0.826726833952094231, 0.834716292992930375, 0.842915653118441077,
- 0.851346258465123684, 0.860033621203008636, 0.869008688043793165, 0.878309655816146839,
- 0.887984660763399880, 0.898095921906304051, 0.908726440060562912, 0.919991505048360247,
- 0.932060075968990209, 0.945198953453078028, 0.959879091812415930, 0.977101701282731328,
- 1.000000000000000000];
-pub const ZIG_EXP_R: f64 = 7.697117470131050077;
-pub static ZIG_EXP_X: [f64; 257] =
- [8.697117470131052741, 7.697117470131050077, 6.941033629377212577, 6.478378493832569696,
- 6.144164665772472667, 5.882144315795399869, 5.666410167454033697, 5.482890627526062488,
- 5.323090505754398016, 5.181487281301500047, 5.054288489981304089, 4.938777085901250530,
- 4.832939741025112035, 4.735242996601741083, 4.644491885420085175, 4.559737061707351380,
- 4.480211746528421912, 4.405287693473573185, 4.334443680317273007, 4.267242480277365857,
- 4.203313713735184365, 4.142340865664051464, 4.084051310408297830, 4.028208544647936762,
- 3.974606066673788796, 3.923062500135489739, 3.873417670399509127, 3.825529418522336744,
- 3.779270992411667862, 3.734528894039797375, 3.691201090237418825, 3.649195515760853770,
- 3.608428813128909507, 3.568825265648337020, 3.530315889129343354, 3.492837654774059608,
- 3.456332821132760191, 3.420748357251119920, 3.386035442460300970, 3.352149030900109405,
- 3.319047470970748037, 3.286692171599068679, 3.255047308570449882, 3.224079565286264160,
- 3.193757903212240290, 3.164053358025972873, 3.134938858084440394, 3.106389062339824481,
- 3.078380215254090224, 3.050890016615455114, 3.023897504455676621, 2.997382949516130601,
- 2.971327759921089662, 2.945714394895045718, 2.920526286512740821, 2.895747768600141825,
- 2.871364012015536371, 2.847360965635188812, 2.823725302450035279, 2.800444370250737780,
- 2.777506146439756574, 2.754899196562344610, 2.732612636194700073, 2.710636095867928752,
- 2.688959688741803689, 2.667573980773266573, 2.646469963151809157, 2.625639026797788489,
- 2.605072938740835564, 2.584763820214140750, 2.564704126316905253, 2.544886627111869970,
- 2.525304390037828028, 2.505950763528594027, 2.486819361740209455, 2.467904050297364815,
- 2.449198932978249754, 2.430698339264419694, 2.412396812688870629, 2.394289099921457886,
- 2.376370140536140596, 2.358635057409337321, 2.341079147703034380, 2.323697874390196372,
- 2.306486858283579799, 2.289441870532269441, 2.272558825553154804, 2.255833774367219213,
- 2.239262898312909034, 2.222842503111036816, 2.206569013257663858, 2.190438966723220027,
- 2.174449009937774679, 2.158595893043885994, 2.142876465399842001, 2.127287671317368289,
- 2.111826546019042183, 2.096490211801715020, 2.081275874393225145, 2.066180819490575526,
- 2.051202409468584786, 2.036338080248769611, 2.021585338318926173, 2.006941757894518563,
- 1.992404978213576650, 1.977972700957360441, 1.963642687789548313, 1.949412758007184943,
- 1.935280786297051359, 1.921244700591528076, 1.907302480018387536, 1.893452152939308242,
- 1.879691795072211180, 1.866019527692827973, 1.852433515911175554, 1.838931967018879954,
- 1.825513128903519799, 1.812175288526390649, 1.798916770460290859, 1.785735935484126014,
- 1.772631179231305643, 1.759600930889074766, 1.746643651946074405, 1.733757834985571566,
- 1.720942002521935299, 1.708194705878057773, 1.695514524101537912, 1.682900062917553896,
- 1.670349953716452118, 1.657862852574172763, 1.645437439303723659, 1.633072416535991334,
- 1.620766508828257901, 1.608518461798858379, 1.596327041286483395, 1.584191032532688892,
- 1.572109239386229707, 1.560080483527888084, 1.548103603714513499, 1.536177455041032092,
- 1.524300908219226258, 1.512472848872117082, 1.500692176842816750, 1.488957805516746058,
- 1.477268661156133867, 1.465623682245745352, 1.454021818848793446, 1.442462031972012504,
- 1.430943292938879674, 1.419464582769983219, 1.408024891569535697, 1.396623217917042137,
- 1.385258568263121992, 1.373929956328490576, 1.362636402505086775, 1.351376933258335189,
- 1.340150580529504643, 1.328956381137116560, 1.317793376176324749, 1.306660610415174117,
- 1.295557131686601027, 1.284481990275012642, 1.273434238296241139, 1.262412929069615330,
- 1.251417116480852521, 1.240445854334406572, 1.229498195693849105, 1.218573192208790124,
- 1.207669893426761121, 1.196787346088403092, 1.185924593404202199, 1.175080674310911677,
- 1.164254622705678921, 1.153445466655774743, 1.142652227581672841, 1.131873919411078511,
- 1.121109547701330200, 1.110358108727411031, 1.099618588532597308, 1.088889961938546813,
- 1.078171191511372307, 1.067461226479967662, 1.056759001602551429, 1.046063435977044209,
- 1.035373431790528542, 1.024687873002617211, 1.014005623957096480, 1.003325527915696735,
- 0.992646405507275897, 0.981967053085062602, 0.971286240983903260, 0.960602711668666509,
- 0.949915177764075969, 0.939222319955262286, 0.928522784747210395, 0.917815182070044311,
- 0.907098082715690257, 0.896370015589889935, 0.885629464761751528, 0.874874866291025066,
- 0.864104604811004484, 0.853317009842373353, 0.842510351810368485, 0.831682837734273206,
- 0.820832606554411814, 0.809957724057418282, 0.799056177355487174, 0.788125868869492430,
- 0.777164609759129710, 0.766170112735434672, 0.755139984181982249, 0.744071715500508102,
- 0.732962673584365398, 0.721810090308756203, 0.710611050909655040, 0.699362481103231959,
- 0.688061132773747808, 0.676703568029522584, 0.665286141392677943, 0.653804979847664947,
- 0.642255960424536365, 0.630634684933490286, 0.618936451394876075, 0.607156221620300030,
- 0.595288584291502887, 0.583327712748769489, 0.571267316532588332, 0.559100585511540626,
- 0.546820125163310577, 0.534417881237165604, 0.521885051592135052, 0.509211982443654398,
- 0.496388045518671162, 0.483401491653461857, 0.470239275082169006, 0.456886840931420235,
- 0.443327866073552401, 0.429543940225410703, 0.415514169600356364, 0.401214678896277765,
- 0.386617977941119573, 0.371692145329917234, 0.356399760258393816, 0.340696481064849122,
- 0.324529117016909452, 0.307832954674932158, 0.290527955491230394, 0.272513185478464703,
- 0.253658363385912022, 0.233790483059674731, 0.212671510630966620, 0.189958689622431842,
- 0.165127622564187282, 0.137304980940012589, 0.104838507565818778, 0.063852163815001570,
- 0.000000000000000000];
-pub static ZIG_EXP_F: [f64; 257] =
- [0.000167066692307963, 0.000454134353841497, 0.000967269282327174, 0.001536299780301573,
- 0.002145967743718907, 0.002788798793574076, 0.003460264777836904, 0.004157295120833797,
- 0.004877655983542396, 0.005619642207205489, 0.006381905937319183, 0.007163353183634991,
- 0.007963077438017043, 0.008780314985808977, 0.009614413642502212, 0.010464810181029981,
- 0.011331013597834600, 0.012212592426255378, 0.013109164931254991, 0.014020391403181943,
- 0.014945968011691148, 0.015885621839973156, 0.016839106826039941, 0.017806200410911355,
- 0.018786700744696024, 0.019780424338009740, 0.020787204072578114, 0.021806887504283581,
- 0.022839335406385240, 0.023884420511558174, 0.024942026419731787, 0.026012046645134221,
- 0.027094383780955803, 0.028188948763978646, 0.029295660224637411, 0.030414443910466622,
- 0.031545232172893622, 0.032687963508959555, 0.033842582150874358, 0.035009037697397431,
- 0.036187284781931443, 0.037377282772959382, 0.038578995503074871, 0.039792391023374139,
- 0.041017441380414840, 0.042254122413316254, 0.043502413568888197, 0.044762297732943289,
- 0.046033761076175184, 0.047316792913181561, 0.048611385573379504, 0.049917534282706379,
- 0.051235237055126281, 0.052564494593071685, 0.053905310196046080, 0.055257689676697030,
- 0.056621641283742870, 0.057997175631200659, 0.059384305633420280, 0.060783046445479660,
- 0.062193415408541036, 0.063615431999807376, 0.065049117786753805, 0.066494496385339816,
- 0.067951593421936643, 0.069420436498728783, 0.070901055162371843, 0.072393480875708752,
- 0.073897746992364746, 0.075413888734058410, 0.076941943170480517, 0.078481949201606435,
- 0.080033947542319905, 0.081597980709237419, 0.083174093009632397, 0.084762330532368146,
- 0.086362741140756927, 0.087975374467270231, 0.089600281910032886, 0.091237516631040197,
- 0.092887133556043569, 0.094549189376055873, 0.096223742550432825, 0.097910853311492213,
- 0.099610583670637132, 0.101322997425953631, 0.103048160171257702, 0.104786139306570145,
- 0.106537004050001632, 0.108300825451033755, 0.110077676405185357, 0.111867631670056283,
- 0.113670767882744286, 0.115487163578633506, 0.117316899211555525, 0.119160057175327641,
- 0.121016721826674792, 0.122886979509545108, 0.124770918580830933, 0.126668629437510671,
- 0.128580204545228199, 0.130505738468330773, 0.132445327901387494, 0.134399071702213602,
- 0.136367070926428829, 0.138349428863580176, 0.140346251074862399, 0.142357645432472146,
- 0.144383722160634720, 0.146424593878344889, 0.148480375643866735, 0.150551185001039839,
- 0.152637142027442801, 0.154738369384468027, 0.156854992369365148, 0.158987138969314129,
- 0.161134939917591952, 0.163298528751901734, 0.165478041874935922, 0.167673618617250081,
- 0.169885401302527550, 0.172113535315319977, 0.174358169171353411, 0.176619454590494829,
- 0.178897546572478278, 0.181192603475496261, 0.183504787097767436, 0.185834262762197083,
- 0.188181199404254262, 0.190545769663195363, 0.192928149976771296, 0.195328520679563189,
- 0.197747066105098818, 0.200183974691911210, 0.202639439093708962, 0.205113656293837654,
- 0.207606827724221982, 0.210119159388988230, 0.212650861992978224, 0.215202151075378628,
- 0.217773247148700472, 0.220364375843359439, 0.222975768058120111, 0.225607660116683956,
- 0.228260293930716618, 0.230933917169627356, 0.233628783437433291, 0.236345152457059560,
- 0.239083290262449094, 0.241843469398877131, 0.244625969131892024, 0.247431075665327543,
- 0.250259082368862240, 0.253110290015629402, 0.255985007030415324, 0.258883549749016173,
- 0.261806242689362922, 0.264753418835062149, 0.267725419932044739, 0.270722596799059967,
- 0.273745309652802915, 0.276793928448517301, 0.279868833236972869, 0.282970414538780746,
- 0.286099073737076826, 0.289255223489677693, 0.292439288161892630, 0.295651704281261252,
- 0.298892921015581847, 0.302163400675693528, 0.305463619244590256, 0.308794066934560185,
- 0.312155248774179606, 0.315547685227128949, 0.318971912844957239, 0.322428484956089223,
- 0.325917972393556354, 0.329440964264136438, 0.332998068761809096, 0.336589914028677717,
- 0.340217149066780189, 0.343880444704502575, 0.347580494621637148, 0.351318016437483449,
- 0.355093752866787626, 0.358908472948750001, 0.362762973354817997, 0.366658079781514379,
- 0.370594648435146223, 0.374573567615902381, 0.378595759409581067, 0.382662181496010056,
- 0.386773829084137932, 0.390931736984797384, 0.395136981833290435, 0.399390684475231350,
- 0.403694012530530555, 0.408048183152032673, 0.412454465997161457, 0.416914186433003209,
- 0.421428728997616908, 0.425999541143034677, 0.430628137288459167, 0.435316103215636907,
- 0.440065100842354173, 0.444876873414548846, 0.449753251162755330, 0.454696157474615836,
- 0.459707615642138023, 0.464789756250426511, 0.469944825283960310, 0.475175193037377708,
- 0.480483363930454543, 0.485871987341885248, 0.491343869594032867, 0.496901987241549881,
- 0.502549501841348056, 0.508289776410643213, 0.514126393814748894, 0.520063177368233931,
- 0.526104213983620062, 0.532253880263043655, 0.538516872002862246, 0.544898237672440056,
- 0.551403416540641733, 0.558038282262587892, 0.564809192912400615, 0.571723048664826150,
- 0.578787358602845359, 0.586010318477268366, 0.593400901691733762, 0.600968966365232560,
- 0.608725382079622346, 0.616682180915207878, 0.624852738703666200, 0.633251994214366398,
- 0.641896716427266423, 0.650805833414571433, 0.660000841079000145, 0.669506316731925177,
- 0.679350572264765806, 0.689566496117078431, 0.700192655082788606, 0.711274760805076456,
- 0.722867659593572465, 0.735038092431424039, 0.747868621985195658, 0.761463388849896838,
- 0.775956852040116218, 0.791527636972496285, 0.808421651523009044, 0.826993296643051101,
- 0.847785500623990496, 0.871704332381204705, 0.900469929925747703, 0.938143680862176477,
- 1.000000000000000000];
diff --git a/rand/rand_distr/tests/uniformity.rs b/rand/rand_distr/tests/uniformity.rs
deleted file mode 100644
index d0d9d97..0000000
--- a/rand/rand_distr/tests/uniformity.rs
+++ /dev/null
@@ -1,59 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-use average::Histogram;
-use rand::prelude::*;
-
-const N_BINS: usize = 100;
-const N_SAMPLES: u32 = 1_000_000;
-const TOL: f64 = 1e-3;
-average::define_histogram!(hist, 100);
-use hist::Histogram as Histogram100;
-
-#[test]
-fn unit_sphere() {
- const N_DIM: usize = 3;
- let h = Histogram100::with_const_width(-1., 1.);
- let mut histograms = [h.clone(), h.clone(), h];
- let dist = rand_distr::UnitSphere;
- let mut rng = rand_pcg::Pcg32::from_entropy();
- for _ in 0..N_SAMPLES {
- let v: [f64; 3] = dist.sample(&mut rng);
- for i in 0..N_DIM {
- histograms[i].add(v[i]).map_err(
- |e| { println!("v: {}", v[i]); e }
- ).unwrap();
- }
- }
- for h in &histograms {
- let sum: u64 = h.bins().iter().sum();
- println!("{:?}", h);
- for &b in h.bins() {
- let p = (b as f64) / (sum as f64);
- assert!((p - 1.0 / (N_BINS as f64)).abs() < TOL, "{}", p);
- }
- }
-}
-
-#[test]
-fn unit_circle() {
- use std::f64::consts::PI;
- let mut h = Histogram100::with_const_width(-PI, PI);
- let dist = rand_distr::UnitCircle;
- let mut rng = rand_pcg::Pcg32::from_entropy();
- for _ in 0..N_SAMPLES {
- let v: [f64; 2] = dist.sample(&mut rng);
- h.add(v[0].atan2(v[1])).unwrap();
- }
- let sum: u64 = h.bins().iter().sum();
- println!("{:?}", h);
- for &b in h.bins() {
- let p = (b as f64) / (sum as f64);
- assert!((p - 1.0 / (N_BINS as f64)).abs() < TOL, "{}", p);
- }
-}
diff --git a/rand/rand_hc/CHANGELOG.md b/rand/rand_hc/CHANGELOG.md
deleted file mode 100644
index a629d7d..0000000
--- a/rand/rand_hc/CHANGELOG.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.2.0] - 2019-06-12
-- Bump minor crate version since rand_core bump is a breaking change
-- Switch to Edition 2018
-
-## [0.1.1] - 2019-06-06 - yanked
-- Bump `rand_core` version
-- Adjust usage of `#[inline]`
-
-## [0.1.0] - 2018-10-17
-- Pulled out of the Rand crate
diff --git a/rand/rand_hc/COPYRIGHT b/rand/rand_hc/COPYRIGHT
deleted file mode 100644
index 468d907..0000000
--- a/rand/rand_hc/COPYRIGHT
+++ /dev/null
@@ -1,12 +0,0 @@
-Copyrights in the Rand project are retained by their contributors. No
-copyright assignment is required to contribute to the Rand project.
-
-For full authorship information, see the version control history.
-
-Except as otherwise noted (below and/or in individual files), Rand is
-licensed under the Apache License, Version 2.0 <LICENSE-APACHE> or
-<http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-<LICENSE-MIT> or <http://opensource.org/licenses/MIT>, at your option.
-
-The Rand project includes code from the Rust project
-published under these same licenses.
diff --git a/rand/rand_hc/Cargo.toml b/rand/rand_hc/Cargo.toml
deleted file mode 100644
index 40cea06..0000000
--- a/rand/rand_hc/Cargo.toml
+++ /dev/null
@@ -1,22 +0,0 @@
-[package]
-name = "rand_hc"
-version = "0.2.0"
-authors = ["The Rand Project Developers"]
-license = "MIT OR Apache-2.0"
-readme = "README.md"
-repository = "https://github.com/rust-random/rand"
-documentation = "https://rust-random.github.io/rand/rand_hc/"
-homepage = "https://crates.io/crates/rand_hc"
-description = """
-HC128 random number generator
-"""
-keywords = ["random", "rng", "hc128"]
-categories = ["algorithms", "no-std"]
-edition = "2018"
-
-[badges]
-travis-ci = { repository = "rust-random/rand" }
-appveyor = { repository = "rust-random/rand" }
-
-[dependencies]
-rand_core = { path = "../rand_core", version = "0.5" }
diff --git a/rand/rand_hc/LICENSE-APACHE b/rand/rand_hc/LICENSE-APACHE
deleted file mode 100644
index 17d7468..0000000
--- a/rand/rand_hc/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
- Apache License
- Version 2.0, January 2004
- https://www.apache.org/licenses/
-
-TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
-
-1. Definitions.
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- any Contribution intentionally submitted for inclusion in the Work
- by You to the Licensor shall be under the terms and conditions of
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- Notwithstanding the above, nothing herein shall supersede or modify
- the terms of any separate license agreement you may have executed
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diff --git a/rand/rand_hc/LICENSE-MIT b/rand/rand_hc/LICENSE-MIT
deleted file mode 100644
index cf65607..0000000
--- a/rand/rand_hc/LICENSE-MIT
+++ /dev/null
@@ -1,25 +0,0 @@
-Copyright 2018 Developers of the Rand project
-
-Permission is hereby granted, free of charge, to any
-person obtaining a copy of this software and associated
-documentation files (the "Software"), to deal in the
-Software without restriction, including without
-limitation the rights to use, copy, modify, merge,
-publish, distribute, sublicense, and/or sell copies of
-the Software, and to permit persons to whom the Software
-is furnished to do so, subject to the following
-conditions:
-
-The above copyright notice and this permission notice
-shall be included in all copies or substantial portions
-of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF
-ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED
-TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
-PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
-SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
-IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-DEALINGS IN THE SOFTWARE.
diff --git a/rand/rand_hc/README.md b/rand/rand_hc/README.md
deleted file mode 100644
index 36449c0..0000000
--- a/rand/rand_hc/README.md
+++ /dev/null
@@ -1,45 +0,0 @@
-# rand_hc
-
-[](https://travis-ci.org/rust-random/rand)
-[](https://ci.appveyor.com/project/rust-random/rand)
-[](https://crates.io/crates/rand_hc)
-[[](https://rust-random.github.io/book/)
-[](https://rust-random.github.io/rand/rand_hc)
-[](https://docs.rs/rand_hc)
-[](https://github.com/rust-random/rand#rust-version-requirements)
-
-A cryptographically secure random number generator that uses the HC-128
-algorithm.
-
-HC-128 is a stream cipher designed by Hongjun Wu[^1], that we use as an
-RNG. It is selected as one of the "stream ciphers suitable for widespread
-adoption" by eSTREAM[^2].
-
-Links:
-
-- [API documentation (master)](https://rust-random.github.io/rand/rand_hc)
-- [API documentation (docs.rs)](https://docs.rs/rand_hc)
-- [Changelog](https://github.com/rust-random/rand/blob/master/rand_hc/CHANGELOG.md)
-
-[rand]: https://crates.io/crates/rand
-[^1]: Hongjun Wu (2008). ["The Stream Cipher HC-128"](
- http://www.ecrypt.eu.org/stream/p3ciphers/hc/hc128_p3.pdf).
- *The eSTREAM Finalists*, LNCS 4986, pp. 39β47, Springer-Verlag.
-
-[^2]: [eSTREAM: the ECRYPT Stream Cipher Project](
- http://www.ecrypt.eu.org/stream/)
-
-
-## Crate Features
-
-`rand_hc` is `no_std` compatible. It does not require any functionality
-outside of the `core` lib, thus there are no features to configure.
-
-
-# License
-
-`rand_hc` is distributed under the terms of both the MIT license and the
-Apache License (Version 2.0).
-
-See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT), and
-[COPYRIGHT](COPYRIGHT) for details.
diff --git a/rand/rand_hc/src/hc128.rs b/rand/rand_hc/src/hc128.rs
deleted file mode 100644
index a320f48..0000000
--- a/rand/rand_hc/src/hc128.rs
+++ /dev/null
@@ -1,464 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The HC-128 random number generator.
-
-use core::fmt;
-use rand_core::{CryptoRng, RngCore, SeedableRng, Error, le};
-use rand_core::block::{BlockRngCore, BlockRng};
-
-const SEED_WORDS: usize = 8; // 128 bit key followed by 128 bit iv
-
-/// A cryptographically secure random number generator that uses the HC-128
-/// algorithm.
-///
-/// HC-128 is a stream cipher designed by Hongjun Wu[^1], that we use as an
-/// RNG. It is selected as one of the "stream ciphers suitable for widespread
-/// adoption" by eSTREAM[^2].
-///
-/// HC-128 is an array based RNG. In this it is similar to RC-4 and ISAAC before
-/// it, but those have never been proven cryptographically secure (or have even
-/// been significantly compromised, as in the case of RC-4[^5]).
-///
-/// Because HC-128 works with simple indexing into a large array and with a few
-/// operations that parallelize well, it has very good performance. The size of
-/// the array it needs, 4kb, can however be a disadvantage.
-///
-/// This implementation is not based on the version of HC-128 submitted to the
-/// eSTREAM contest, but on a later version by the author with a few small
-/// improvements from December 15, 2009[^3].
-///
-/// HC-128 has no known weaknesses that are easier to exploit than doing a
-/// brute-force search of 2<sup>128</sup>. A very comprehensive analysis of the
-/// current state of known attacks / weaknesses of HC-128 is given in *Some
-/// Results On Analysis And Implementation Of HC-128 Stream Cipher*[^4].
-///
-/// The average cycle length is expected to be
-/// 2<sup>1024*32+10-1</sup> = 2<sup>32777</sup>.
-/// We support seeding with a 256-bit array, which matches the 128-bit key
-/// concatenated with a 128-bit IV from the stream cipher.
-///
-/// This implementation uses an output buffer of sixteen `u32` words, and uses
-/// [`BlockRng`] to implement the [`RngCore`] methods.
-///
-/// ## References
-/// [^1]: Hongjun Wu (2008). ["The Stream Cipher HC-128"](
-/// http://www.ecrypt.eu.org/stream/p3ciphers/hc/hc128_p3.pdf).
-/// *The eSTREAM Finalists*, LNCS 4986, pp. 39β47, Springer-Verlag.
-///
-/// [^2]: [eSTREAM: the ECRYPT Stream Cipher Project](
-/// http://www.ecrypt.eu.org/stream/)
-///
-/// [^3]: Hongjun Wu, [Stream Ciphers HC-128 and HC-256](
-/// https://www.ntu.edu.sg/home/wuhj/research/hc/index.html)
-///
-/// [^4]: Shashwat Raizada (January 2015),["Some Results On Analysis And
-/// Implementation Of HC-128 Stream Cipher"](
-/// http://library.isical.ac.in:8080/jspui/bitstream/123456789/6636/1/TH431.pdf).
-///
-/// [^5]: Internet Engineering Task Force (February 2015),
-/// ["Prohibiting RC4 Cipher Suites"](https://tools.ietf.org/html/rfc7465).
-#[derive(Clone, Debug)]
-pub struct Hc128Rng(BlockRng<Hc128Core>);
-
-impl RngCore for Hc128Rng {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.0.next_u32()
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- self.0.next_u64()
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- self.0.fill_bytes(dest)
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.0.try_fill_bytes(dest)
- }
-}
-
-impl SeedableRng for Hc128Rng {
- type Seed = <Hc128Core as SeedableRng>::Seed;
-
- #[inline]
- fn from_seed(seed: Self::Seed) -> Self {
- Hc128Rng(BlockRng::<Hc128Core>::from_seed(seed))
- }
-
- #[inline]
- fn from_rng<R: RngCore>(rng: R) -> Result<Self, Error> {
- BlockRng::<Hc128Core>::from_rng(rng).map(Hc128Rng)
- }
-}
-
-impl CryptoRng for Hc128Rng {}
-
-/// The core of `Hc128Rng`, used with `BlockRng`.
-#[derive(Clone)]
-pub struct Hc128Core {
- t: [u32; 1024],
- counter1024: usize,
-}
-
-// Custom Debug implementation that does not expose the internal state
-impl fmt::Debug for Hc128Core {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "Hc128Core {{}}")
- }
-}
-
-impl BlockRngCore for Hc128Core {
- type Item = u32;
- type Results = [u32; 16];
-
- fn generate(&mut self, results: &mut Self::Results) {
- assert!(self.counter1024 % 16 == 0);
-
- let cc = self.counter1024 % 512;
- let dd = (cc + 16) % 512;
- let ee = cc.wrapping_sub(16) % 512;
-
- if self.counter1024 & 512 == 0 {
- // P block
- results[0] = self.step_p(cc+0, cc+1, ee+13, ee+6, ee+4);
- results[1] = self.step_p(cc+1, cc+2, ee+14, ee+7, ee+5);
- results[2] = self.step_p(cc+2, cc+3, ee+15, ee+8, ee+6);
- results[3] = self.step_p(cc+3, cc+4, cc+0, ee+9, ee+7);
- results[4] = self.step_p(cc+4, cc+5, cc+1, ee+10, ee+8);
- results[5] = self.step_p(cc+5, cc+6, cc+2, ee+11, ee+9);
- results[6] = self.step_p(cc+6, cc+7, cc+3, ee+12, ee+10);
- results[7] = self.step_p(cc+7, cc+8, cc+4, ee+13, ee+11);
- results[8] = self.step_p(cc+8, cc+9, cc+5, ee+14, ee+12);
- results[9] = self.step_p(cc+9, cc+10, cc+6, ee+15, ee+13);
- results[10] = self.step_p(cc+10, cc+11, cc+7, cc+0, ee+14);
- results[11] = self.step_p(cc+11, cc+12, cc+8, cc+1, ee+15);
- results[12] = self.step_p(cc+12, cc+13, cc+9, cc+2, cc+0);
- results[13] = self.step_p(cc+13, cc+14, cc+10, cc+3, cc+1);
- results[14] = self.step_p(cc+14, cc+15, cc+11, cc+4, cc+2);
- results[15] = self.step_p(cc+15, dd+0, cc+12, cc+5, cc+3);
- } else {
- // Q block
- results[0] = self.step_q(cc+0, cc+1, ee+13, ee+6, ee+4);
- results[1] = self.step_q(cc+1, cc+2, ee+14, ee+7, ee+5);
- results[2] = self.step_q(cc+2, cc+3, ee+15, ee+8, ee+6);
- results[3] = self.step_q(cc+3, cc+4, cc+0, ee+9, ee+7);
- results[4] = self.step_q(cc+4, cc+5, cc+1, ee+10, ee+8);
- results[5] = self.step_q(cc+5, cc+6, cc+2, ee+11, ee+9);
- results[6] = self.step_q(cc+6, cc+7, cc+3, ee+12, ee+10);
- results[7] = self.step_q(cc+7, cc+8, cc+4, ee+13, ee+11);
- results[8] = self.step_q(cc+8, cc+9, cc+5, ee+14, ee+12);
- results[9] = self.step_q(cc+9, cc+10, cc+6, ee+15, ee+13);
- results[10] = self.step_q(cc+10, cc+11, cc+7, cc+0, ee+14);
- results[11] = self.step_q(cc+11, cc+12, cc+8, cc+1, ee+15);
- results[12] = self.step_q(cc+12, cc+13, cc+9, cc+2, cc+0);
- results[13] = self.step_q(cc+13, cc+14, cc+10, cc+3, cc+1);
- results[14] = self.step_q(cc+14, cc+15, cc+11, cc+4, cc+2);
- results[15] = self.step_q(cc+15, dd+0, cc+12, cc+5, cc+3);
- }
- self.counter1024 = self.counter1024.wrapping_add(16);
- }
-}
-
-impl Hc128Core {
- // One step of HC-128, update P and generate 32 bits keystream
- #[inline(always)]
- fn step_p(&mut self, i: usize, i511: usize, i3: usize, i10: usize, i12: usize)
- -> u32
- {
- let (p, q) = self.t.split_at_mut(512);
- // FIXME: it would be great if we the bounds checks here could be
- // optimized out, and we would not need unsafe.
- // This improves performance by about 7%.
- unsafe {
- let temp0 = p.get_unchecked(i511).rotate_right(23);
- let temp1 = p.get_unchecked(i3).rotate_right(10);
- let temp2 = p.get_unchecked(i10).rotate_right(8);
- *p.get_unchecked_mut(i) = p.get_unchecked(i)
- .wrapping_add(temp2)
- .wrapping_add(temp0 ^ temp1);
- let temp3 = {
- // The h1 function in HC-128
- let a = *p.get_unchecked(i12) as u8;
- let c = (p.get_unchecked(i12) >> 16) as u8;
- q[a as usize].wrapping_add(q[256 + c as usize])
- };
- temp3 ^ p.get_unchecked(i)
- }
- }
-
- // One step of HC-128, update Q and generate 32 bits keystream
- // Similar to `step_p`, but `p` and `q` are swapped, and the rotates are to
- // the left instead of to the right.
- #[inline(always)]
- fn step_q(&mut self, i: usize, i511: usize, i3: usize, i10: usize, i12: usize)
- -> u32
- {
- let (p, q) = self.t.split_at_mut(512);
- unsafe {
- let temp0 = q.get_unchecked(i511).rotate_left(23);
- let temp1 = q.get_unchecked(i3).rotate_left(10);
- let temp2 = q.get_unchecked(i10).rotate_left(8);
- *q.get_unchecked_mut(i) = q.get_unchecked(i)
- .wrapping_add(temp2)
- .wrapping_add(temp0 ^ temp1);
- let temp3 = {
- // The h2 function in HC-128
- let a = *q.get_unchecked(i12) as u8;
- let c = (q.get_unchecked(i12) >> 16) as u8;
- p[a as usize].wrapping_add(p[256 + c as usize])
- };
- temp3 ^ q.get_unchecked(i)
- }
- }
-
- fn sixteen_steps(&mut self) {
- assert!(self.counter1024 % 16 == 0);
-
- let cc = self.counter1024 % 512;
- let dd = (cc + 16) % 512;
- let ee = cc.wrapping_sub(16) % 512;
-
- if self.counter1024 < 512 {
- // P block
- self.t[cc+0] = self.step_p(cc+0, cc+1, ee+13, ee+6, ee+4);
- self.t[cc+1] = self.step_p(cc+1, cc+2, ee+14, ee+7, ee+5);
- self.t[cc+2] = self.step_p(cc+2, cc+3, ee+15, ee+8, ee+6);
- self.t[cc+3] = self.step_p(cc+3, cc+4, cc+0, ee+9, ee+7);
- self.t[cc+4] = self.step_p(cc+4, cc+5, cc+1, ee+10, ee+8);
- self.t[cc+5] = self.step_p(cc+5, cc+6, cc+2, ee+11, ee+9);
- self.t[cc+6] = self.step_p(cc+6, cc+7, cc+3, ee+12, ee+10);
- self.t[cc+7] = self.step_p(cc+7, cc+8, cc+4, ee+13, ee+11);
- self.t[cc+8] = self.step_p(cc+8, cc+9, cc+5, ee+14, ee+12);
- self.t[cc+9] = self.step_p(cc+9, cc+10, cc+6, ee+15, ee+13);
- self.t[cc+10] = self.step_p(cc+10, cc+11, cc+7, cc+0, ee+14);
- self.t[cc+11] = self.step_p(cc+11, cc+12, cc+8, cc+1, ee+15);
- self.t[cc+12] = self.step_p(cc+12, cc+13, cc+9, cc+2, cc+0);
- self.t[cc+13] = self.step_p(cc+13, cc+14, cc+10, cc+3, cc+1);
- self.t[cc+14] = self.step_p(cc+14, cc+15, cc+11, cc+4, cc+2);
- self.t[cc+15] = self.step_p(cc+15, dd+0, cc+12, cc+5, cc+3);
- } else {
- // Q block
- self.t[cc+512+0] = self.step_q(cc+0, cc+1, ee+13, ee+6, ee+4);
- self.t[cc+512+1] = self.step_q(cc+1, cc+2, ee+14, ee+7, ee+5);
- self.t[cc+512+2] = self.step_q(cc+2, cc+3, ee+15, ee+8, ee+6);
- self.t[cc+512+3] = self.step_q(cc+3, cc+4, cc+0, ee+9, ee+7);
- self.t[cc+512+4] = self.step_q(cc+4, cc+5, cc+1, ee+10, ee+8);
- self.t[cc+512+5] = self.step_q(cc+5, cc+6, cc+2, ee+11, ee+9);
- self.t[cc+512+6] = self.step_q(cc+6, cc+7, cc+3, ee+12, ee+10);
- self.t[cc+512+7] = self.step_q(cc+7, cc+8, cc+4, ee+13, ee+11);
- self.t[cc+512+8] = self.step_q(cc+8, cc+9, cc+5, ee+14, ee+12);
- self.t[cc+512+9] = self.step_q(cc+9, cc+10, cc+6, ee+15, ee+13);
- self.t[cc+512+10] = self.step_q(cc+10, cc+11, cc+7, cc+0, ee+14);
- self.t[cc+512+11] = self.step_q(cc+11, cc+12, cc+8, cc+1, ee+15);
- self.t[cc+512+12] = self.step_q(cc+12, cc+13, cc+9, cc+2, cc+0);
- self.t[cc+512+13] = self.step_q(cc+13, cc+14, cc+10, cc+3, cc+1);
- self.t[cc+512+14] = self.step_q(cc+14, cc+15, cc+11, cc+4, cc+2);
- self.t[cc+512+15] = self.step_q(cc+15, dd+0, cc+12, cc+5, cc+3);
- }
- self.counter1024 += 16;
- }
-
- // Initialize an HC-128 random number generator. The seed has to be
- // 256 bits in length (`[u32; 8]`), matching the 128 bit `key` followed by
- // 128 bit `iv` when HC-128 where to be used as a stream cipher.
- #[inline(always)] // single use: SeedableRng::from_seed
- fn init(seed: [u32; SEED_WORDS]) -> Self {
- #[inline]
- fn f1(x: u32) -> u32 {
- x.rotate_right(7) ^ x.rotate_right(18) ^ (x >> 3)
- }
-
- #[inline]
- fn f2(x: u32) -> u32 {
- x.rotate_right(17) ^ x.rotate_right(19) ^ (x >> 10)
- }
-
- let mut t = [0u32; 1024];
-
- // Expand the key and iv into P and Q
- let (key, iv) = seed.split_at(4);
- t[..4].copy_from_slice(key);
- t[4..8].copy_from_slice(key);
- t[8..12].copy_from_slice(iv);
- t[12..16].copy_from_slice(iv);
-
- // Generate the 256 intermediate values W[16] ... W[256+16-1], and
- // copy the last 16 generated values to the start op P.
- for i in 16..256+16 {
- t[i] = f2(t[i-2]).wrapping_add(t[i-7]).wrapping_add(f1(t[i-15]))
- .wrapping_add(t[i-16]).wrapping_add(i as u32);
- }
- {
- let (p1, p2) = t.split_at_mut(256);
- p1[0..16].copy_from_slice(&p2[0..16]);
- }
-
- // Generate both the P and Q tables
- for i in 16..1024 {
- t[i] = f2(t[i-2]).wrapping_add(t[i-7]).wrapping_add(f1(t[i-15]))
- .wrapping_add(t[i-16]).wrapping_add(256 + i as u32);
- }
-
- let mut core = Self { t, counter1024: 0 };
-
- // run the cipher 1024 steps
- for _ in 0..64 { core.sixteen_steps() };
- core.counter1024 = 0;
- core
- }
-}
-
-impl SeedableRng for Hc128Core {
- type Seed = [u8; SEED_WORDS*4];
-
- /// Create an HC-128 random number generator with a seed. The seed has to be
- /// 256 bits in length, matching the 128 bit `key` followed by 128 bit `iv`
- /// when HC-128 where to be used as a stream cipher.
- fn from_seed(seed: Self::Seed) -> Self {
- let mut seed_u32 = [0u32; SEED_WORDS];
- le::read_u32_into(&seed, &mut seed_u32);
- Self::init(seed_u32)
- }
-}
-
-impl CryptoRng for Hc128Core {}
-
-#[cfg(test)]
-mod test {
- use ::rand_core::{RngCore, SeedableRng};
- use super::Hc128Rng;
-
- #[test]
- // Test vector 1 from the paper "The Stream Cipher HC-128"
- fn test_hc128_true_values_a() {
- let seed = [0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0, // key
- 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0]; // iv
- let mut rng = Hc128Rng::from_seed(seed);
-
- let mut results = [0u32; 16];
- for i in results.iter_mut() { *i = rng.next_u32(); }
- let expected = [0x73150082, 0x3bfd03a0, 0xfb2fd77f, 0xaa63af0e,
- 0xde122fc6, 0xa7dc29b6, 0x62a68527, 0x8b75ec68,
- 0x9036db1e, 0x81896005, 0x00ade078, 0x491fbf9a,
- 0x1cdc3013, 0x6c3d6e24, 0x90f664b2, 0x9cd57102];
- assert_eq!(results, expected);
- }
-
- #[test]
- // Test vector 2 from the paper "The Stream Cipher HC-128"
- fn test_hc128_true_values_b() {
- let seed = [0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0, // key
- 1,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0]; // iv
- let mut rng = Hc128Rng::from_seed(seed);
-
- let mut results = [0u32; 16];
- for i in results.iter_mut() { *i = rng.next_u32(); }
- let expected = [0xc01893d5, 0xb7dbe958, 0x8f65ec98, 0x64176604,
- 0x36fc6724, 0xc82c6eec, 0x1b1c38a7, 0xc9b42a95,
- 0x323ef123, 0x0a6a908b, 0xce757b68, 0x9f14f7bb,
- 0xe4cde011, 0xaeb5173f, 0x89608c94, 0xb5cf46ca];
- assert_eq!(results, expected);
- }
-
- #[test]
- // Test vector 3 from the paper "The Stream Cipher HC-128"
- fn test_hc128_true_values_c() {
- let seed = [0x55,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0, // key
- 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0]; // iv
- let mut rng = Hc128Rng::from_seed(seed);
-
- let mut results = [0u32; 16];
- for i in results.iter_mut() { *i = rng.next_u32(); }
- let expected = [0x518251a4, 0x04b4930a, 0xb02af931, 0x0639f032,
- 0xbcb4a47a, 0x5722480b, 0x2bf99f72, 0xcdc0e566,
- 0x310f0c56, 0xd3cc83e8, 0x663db8ef, 0x62dfe07f,
- 0x593e1790, 0xc5ceaa9c, 0xab03806f, 0xc9a6e5a0];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_hc128_true_values_u64() {
- let seed = [0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0, // key
- 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0]; // iv
- let mut rng = Hc128Rng::from_seed(seed);
-
- let mut results = [0u64; 8];
- for i in results.iter_mut() { *i = rng.next_u64(); }
- let expected = [0x3bfd03a073150082, 0xaa63af0efb2fd77f,
- 0xa7dc29b6de122fc6, 0x8b75ec6862a68527,
- 0x818960059036db1e, 0x491fbf9a00ade078,
- 0x6c3d6e241cdc3013, 0x9cd5710290f664b2];
- assert_eq!(results, expected);
-
- // The RNG operates in a P block of 512 results and next a Q block.
- // After skipping 2*800 u32 results we end up somewhere in the Q block
- // of the second round
- for _ in 0..800 { rng.next_u64(); }
-
- for i in results.iter_mut() { *i = rng.next_u64(); }
- let expected = [0xd8c4d6ca84d0fc10, 0xf16a5d91dc66e8e7,
- 0xd800de5bc37a8653, 0x7bae1f88c0dfbb4c,
- 0x3bfe1f374e6d4d14, 0x424b55676be3fa06,
- 0xe3a1e8758cbff579, 0x417f7198c5652bcd];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_hc128_true_values_bytes() {
- let seed = [0x55,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0, // key
- 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0]; // iv
- let mut rng = Hc128Rng::from_seed(seed);
- let expected = [0x31, 0xf9, 0x2a, 0xb0, 0x32, 0xf0, 0x39, 0x06,
- 0x7a, 0xa4, 0xb4, 0xbc, 0x0b, 0x48, 0x22, 0x57,
- 0x72, 0x9f, 0xf9, 0x2b, 0x66, 0xe5, 0xc0, 0xcd,
- 0x56, 0x0c, 0x0f, 0x31, 0xe8, 0x83, 0xcc, 0xd3,
- 0xef, 0xb8, 0x3d, 0x66, 0x7f, 0xe0, 0xdf, 0x62,
- 0x90, 0x17, 0x3e, 0x59, 0x9c, 0xaa, 0xce, 0xc5,
- 0x6f, 0x80, 0x03, 0xab, 0xa0, 0xe5, 0xa6, 0xc9,
- 0x60, 0x95, 0x84, 0x7a, 0xa5, 0x68, 0x5a, 0x84,
- 0xea, 0xd5, 0xf3, 0xea, 0x73, 0xa9, 0xad, 0x01,
- 0x79, 0x7d, 0xbe, 0x9f, 0xea, 0xe3, 0xf9, 0x74,
- 0x0e, 0xda, 0x2f, 0xa0, 0xe4, 0x7b, 0x4b, 0x1b,
- 0xdd, 0x17, 0x69, 0x4a, 0xfe, 0x9f, 0x56, 0x95,
- 0xad, 0x83, 0x6b, 0x9d, 0x60, 0xa1, 0x99, 0x96,
- 0x90, 0x00, 0x66, 0x7f, 0xfa, 0x7e, 0x65, 0xe9,
- 0xac, 0x8b, 0x92, 0x34, 0x77, 0xb4, 0x23, 0xd0,
- 0xb9, 0xab, 0xb1, 0x47, 0x7d, 0x4a, 0x13, 0x0a];
-
- // Pick a somewhat large buffer so we can test filling with the
- // remainder from `state.results`, directly filling the buffer, and
- // filling the remainder of the buffer.
- let mut buffer = [0u8; 16*4*2];
- // Consume a value so that we have a remainder.
- assert!(rng.next_u64() == 0x04b4930a518251a4);
- rng.fill_bytes(&mut buffer);
-
- // [u8; 128] doesn't implement PartialEq
- assert_eq!(buffer.len(), expected.len());
- for (b, e) in buffer.iter().zip(expected.iter()) {
- assert_eq!(b, e);
- }
- }
-
- #[test]
- fn test_hc128_clone() {
- let seed = [0x55,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0, // key
- 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0]; // iv
- let mut rng1 = Hc128Rng::from_seed(seed);
- let mut rng2 = rng1.clone();
- for _ in 0..16 {
- assert_eq!(rng1.next_u32(), rng2.next_u32());
- }
- }
-}
diff --git a/rand/rand_hc/src/lib.rs b/rand/rand_hc/src/lib.rs
deleted file mode 100644
index c1ae665..0000000
--- a/rand/rand_hc/src/lib.rs
+++ /dev/null
@@ -1,23 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The HC128 random number generator.
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
- html_favicon_url = "https://www.rust-lang.org/favicon.ico",
- html_root_url = "https://rust-random.github.io/rand/")]
-
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-#![doc(test(attr(allow(unused_variables), deny(warnings))))]
-
-#![no_std]
-
-mod hc128;
-
-pub use hc128::{Hc128Rng, Hc128Core};
diff --git a/rand/rand_isaac/CHANGELOG.md b/rand/rand_isaac/CHANGELOG.md
deleted file mode 100644
index 0a5591f..0000000
--- a/rand/rand_isaac/CHANGELOG.md
+++ /dev/null
@@ -1,21 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.2.0] - 2019-06-12
-- Bump minor crate version since rand_core bump is a breaking change
-- Switch to Edition 2018
-
-## [0.1.2] - 2019-06-06 - yanked
-- Bump `rand_core` version
-- Remove deprecated code
-- Adjust usage of `#[inline]`
-
-## [0.1.1] - 2018-11-26
-- Fix `rand_core` version requirement
-- Fix doc links
-
-## [0.1.0] - 2018-10-17
-- Pulled out of the Rand crate
diff --git a/rand/rand_isaac/COPYRIGHT b/rand/rand_isaac/COPYRIGHT
deleted file mode 100644
index 468d907..0000000
--- a/rand/rand_isaac/COPYRIGHT
+++ /dev/null
@@ -1,12 +0,0 @@
-Copyrights in the Rand project are retained by their contributors. No
-copyright assignment is required to contribute to the Rand project.
-
-For full authorship information, see the version control history.
-
-Except as otherwise noted (below and/or in individual files), Rand is
-licensed under the Apache License, Version 2.0 <LICENSE-APACHE> or
-<http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-<LICENSE-MIT> or <http://opensource.org/licenses/MIT>, at your option.
-
-The Rand project includes code from the Rust project
-published under these same licenses.
diff --git a/rand/rand_isaac/Cargo.toml b/rand/rand_isaac/Cargo.toml
deleted file mode 100644
index c11c305..0000000
--- a/rand/rand_isaac/Cargo.toml
+++ /dev/null
@@ -1,31 +0,0 @@
-[package]
-name = "rand_isaac"
-version = "0.2.0"
-authors = ["The Rand Project Developers", "The Rust Project Developers"]
-license = "MIT OR Apache-2.0"
-readme = "README.md"
-repository = "https://github.com/rust-random/rand"
-documentation = "https://rust-random.github.io/rand/rand_isaac/"
-homepage = "https://crates.io/crates/rand_isaac"
-description = """
-ISAAC random number generator
-"""
-keywords = ["random", "rng", "isaac"]
-categories = ["algorithms", "no-std"]
-edition = "2018"
-
-[badges]
-travis-ci = { repository = "rust-random/rand" }
-appveyor = { repository = "rust-random/rand" }
-
-[features]
-serde1 = ["serde", "rand_core/serde1"]
-
-[dependencies]
-rand_core = { path = "../rand_core", version = "0.5" }
-serde = { version = "1", features = ["derive"], optional = true }
-
-[dev-dependencies]
-# This is for testing serde, unfortunately we can't specify feature-gated dev
-# deps yet, see: https://github.com/rust-lang/cargo/issues/1596
-bincode = "1"
diff --git a/rand/rand_isaac/LICENSE-APACHE b/rand/rand_isaac/LICENSE-APACHE
deleted file mode 100644
index 17d7468..0000000
--- a/rand/rand_isaac/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
- Apache License
- Version 2.0, January 2004
- https://www.apache.org/licenses/
-
-TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
-
-1. Definitions.
-
- "License" shall mean the terms and conditions for use, reproduction,
- and distribution as defined by Sections 1 through 9 of this document.
-
- "Licensor" shall mean the copyright owner or entity authorized by
- the copyright owner that is granting the License.
-
- "Legal Entity" shall mean the union of the acting entity and all
- other entities that control, are controlled by, or are under common
- control with that entity. For the purposes of this definition,
- "control" means (i) the power, direct or indirect, to cause the
- direction or management of such entity, whether by contract or
- otherwise, or (ii) ownership of fifty percent (50%) or more of the
- outstanding shares, or (iii) beneficial ownership of such entity.
-
- "You" (or "Your") shall mean an individual or Legal Entity
- exercising permissions granted by this License.
-
- "Source" form shall mean the preferred form for making modifications,
- including but not limited to software source code, documentation
- source, and configuration files.
-
- "Object" form shall mean any form resulting from mechanical
- transformation or translation of a Source form, including but
- not limited to compiled object code, generated documentation,
- and conversions to other media types.
-
- "Work" shall mean the work of authorship, whether in Source or
- Object form, made available under the License, as indicated by a
- copyright notice that is included in or attached to the work
- (an example is provided in the Appendix below).
-
- "Derivative Works" shall mean any work, whether in Source or Object
- form, that is based on (or derived from) the Work and for which the
- editorial revisions, annotations, elaborations, or other modifications
- represent, as a whole, an original work of authorship. For the purposes
- of this License, Derivative Works shall not include works that remain
- separable from, or merely link (or bind by name) to the interfaces of,
- the Work and Derivative Works thereof.
-
- "Contribution" shall mean any work of authorship, including
- the original version of the Work and any modifications or additions
- to that Work or Derivative Works thereof, that is intentionally
- submitted to Licensor for inclusion in the Work by the copyright owner
- or by an individual or Legal Entity authorized to submit on behalf of
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- communication on electronic mailing lists, source code control systems,
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- Licensor for the purpose of discussing and improving the Work, but
- excluding communication that is conspicuously marked or otherwise
- designated in writing by the copyright owner as "Not a Contribution."
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- "Contributor" shall mean Licensor and any individual or Legal Entity
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-2. Grant of Copyright License. Subject to the terms and conditions of
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-3. Grant of Patent License. Subject to the terms and conditions of
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diff --git a/rand/rand_isaac/LICENSE-MIT b/rand/rand_isaac/LICENSE-MIT
deleted file mode 100644
index d93b5ba..0000000
--- a/rand/rand_isaac/LICENSE-MIT
+++ /dev/null
@@ -1,26 +0,0 @@
-Copyright 2018 Developers of the Rand project
-Copyright (c) 2014 The Rust Project Developers
-
-Permission is hereby granted, free of charge, to any
-person obtaining a copy of this software and associated
-documentation files (the "Software"), to deal in the
-Software without restriction, including without
-limitation the rights to use, copy, modify, merge,
-publish, distribute, sublicense, and/or sell copies of
-the Software, and to permit persons to whom the Software
-is furnished to do so, subject to the following
-conditions:
-
-The above copyright notice and this permission notice
-shall be included in all copies or substantial portions
-of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF
-ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED
-TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
-PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
-SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
-IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-DEALINGS IN THE SOFTWARE.
diff --git a/rand/rand_isaac/README.md b/rand/rand_isaac/README.md
deleted file mode 100644
index c16c63f..0000000
--- a/rand/rand_isaac/README.md
+++ /dev/null
@@ -1,47 +0,0 @@
-# rand_isaac
-
-[](https://travis-ci.org/rust-random/rand)
-[](https://ci.appveyor.com/project/rust-random/rand)
-[](https://crates.io/crates/rand_isaac)
-[](https://rust-random.github.io/book/)
-[](https://rust-random.github.io/rand/rand_isaac)
-[](https://docs.rs/rand_isaac)
-[](https://github.com/rust-random/rand#rust-version-requirements)
-
-Implements the ISAAC and ISAAC-64 random number generators.
-
-ISAAC stands for "Indirection, Shift, Accumulate, Add, and Count" which are
-the principal bitwise operations employed. It is the most advanced of a
-series of array based random number generator designed by Robert Jenkins
-in 1996[^1][^2].
-
-ISAAC is notably fast and produces excellent quality random numbers for
-non-cryptographic applications.
-
-Links:
-
-- [API documentation (master)](https://rust-random.github.io/rand/rand_isaac)
-- [API documentation (docs.rs)](https://docs.rs/rand_isaac)
-- [Changelog](https://github.com/rust-random/rand/blob/master/rand_isaac/CHANGELOG.md)
-
-[rand]: https://crates.io/crates/rand
-[^1]: Bob Jenkins, [*ISAAC: A fast cryptographic random number generator*](http://burtleburtle.net/bob/rand/isaacafa.html)
-[^2]: Bob Jenkins, [*ISAAC and RC4*](http://burtleburtle.net/bob/rand/isaac.html)
-
-
-## Crate Features
-
-`rand_isaac` is `no_std` compatible. It does not require any functionality
-outside of the `core` lib, thus there are no features to configure.
-
-The `serde1` feature includes implementations of `Serialize` and `Deserialize`
-for the included RNGs.
-
-
-# License
-
-`rand_isaac` is distributed under the terms of both the MIT license and the
-Apache License (Version 2.0).
-
-See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT), and
-[COPYRIGHT](COPYRIGHT) for details.
diff --git a/rand/rand_isaac/src/isaac.rs b/rand/rand_isaac/src/isaac.rs
deleted file mode 100644
index 2caf61a..0000000
--- a/rand/rand_isaac/src/isaac.rs
+++ /dev/null
@@ -1,476 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013-2018 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The ISAAC random number generator.
-
-use core::{fmt, slice};
-use core::num::Wrapping as w;
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core::{RngCore, SeedableRng, Error, le};
-use rand_core::block::{BlockRngCore, BlockRng};
-use crate::isaac_array::IsaacArray;
-
-#[allow(non_camel_case_types)]
-type w32 = w<u32>;
-
-const RAND_SIZE_LEN: usize = 8;
-const RAND_SIZE: usize = 1 << RAND_SIZE_LEN;
-
-/// A random number generator that uses the ISAAC algorithm.
-///
-/// ISAAC stands for "Indirection, Shift, Accumulate, Add, and Count" which are
-/// the principal bitwise operations employed. It is the most advanced of a
-/// series of array based random number generator designed by Robert Jenkins
-/// in 1996[^1][^2].
-///
-/// ISAAC is notably fast and produces excellent quality random numbers for
-/// non-cryptographic applications.
-///
-/// In spite of being designed with cryptographic security in mind, ISAAC hasn't
-/// been stringently cryptanalyzed and thus cryptographers do not not
-/// consensually trust it to be secure. When looking for a secure RNG, prefer
-/// `Hc128Rng` from the [`rand_hc`] crate instead, which, like ISAAC, is an
-/// array-based RNG and one of the stream-ciphers selected the by eSTREAM
-///
-/// In 2006 an improvement to ISAAC was suggested by Jean-Philippe Aumasson,
-/// named ISAAC+[^3]. But because the specification is not complete, because
-/// there is no good implementation, and because the suggested bias may not
-/// exist, it is not implemented here.
-///
-/// ## Overview of the ISAAC algorithm:
-/// (in pseudo-code)
-///
-/// ```text
-/// Input: a, b, c, s[256] // state
-/// Output: r[256] // results
-///
-/// mix(a,i) = a ^ a << 13 if i = 0 mod 4
-/// a ^ a >> 6 if i = 1 mod 4
-/// a ^ a << 2 if i = 2 mod 4
-/// a ^ a >> 16 if i = 3 mod 4
-///
-/// c = c + 1
-/// b = b + c
-///
-/// for i in 0..256 {
-/// x = s_[i]
-/// a = f(a,i) + s[i+128 mod 256]
-/// y = a + b + s[x>>2 mod 256]
-/// s[i] = y
-/// b = x + s[y>>10 mod 256]
-/// r[i] = b
-/// }
-/// ```
-///
-/// Numbers are generated in blocks of 256. This means the function above only
-/// runs once every 256 times you ask for a next random number. In all other
-/// circumstances the last element of the results array is returned.
-///
-/// ISAAC therefore needs a lot of memory, relative to other non-crypto RNGs.
-/// 2 * 256 * 4 = 2 kb to hold the state and results.
-///
-/// This implementation uses [`BlockRng`] to implement the [`RngCore`] methods.
-///
-/// ## References
-/// [^1]: Bob Jenkins, [*ISAAC: A fast cryptographic random number generator*](
-/// http://burtleburtle.net/bob/rand/isaacafa.html)
-///
-/// [^2]: Bob Jenkins, [*ISAAC and RC4*](
-/// http://burtleburtle.net/bob/rand/isaac.html)
-///
-/// [^3]: Jean-Philippe Aumasson, [*On the pseudo-random generator ISAAC*](
-/// https://eprint.iacr.org/2006/438)
-///
-/// [`rand_hc`]: https://docs.rs/rand_hc
-#[derive(Clone, Debug)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct IsaacRng(BlockRng<IsaacCore>);
-
-impl RngCore for IsaacRng {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.0.next_u32()
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- self.0.next_u64()
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- self.0.fill_bytes(dest)
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.0.try_fill_bytes(dest)
- }
-}
-
-impl SeedableRng for IsaacRng {
- type Seed = <IsaacCore as SeedableRng>::Seed;
-
- #[inline]
- fn from_seed(seed: Self::Seed) -> Self {
- IsaacRng(BlockRng::<IsaacCore>::from_seed(seed))
- }
-
- /// Create an ISAAC random number generator using an `u64` as seed.
- /// If `seed == 0` this will produce the same stream of random numbers as
- /// the reference implementation when used unseeded.
- #[inline]
- fn seed_from_u64(seed: u64) -> Self {
- IsaacRng(BlockRng::<IsaacCore>::seed_from_u64(seed))
- }
-
- #[inline]
- fn from_rng<S: RngCore>(rng: S) -> Result<Self, Error> {
- BlockRng::<IsaacCore>::from_rng(rng).map(|rng| IsaacRng(rng))
- }
-}
-
-/// The core of [`IsaacRng`], used with [`BlockRng`].
-#[derive(Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct IsaacCore {
- #[cfg_attr(feature="serde1",serde(with="super::isaac_array::isaac_array_serde"))]
- mem: [w32; RAND_SIZE],
- a: w32,
- b: w32,
- c: w32,
-}
-
-// Custom Debug implementation that does not expose the internal state
-impl fmt::Debug for IsaacCore {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "IsaacCore {{}}")
- }
-}
-
-impl BlockRngCore for IsaacCore {
- type Item = u32;
- type Results = IsaacArray<Self::Item>;
-
- /// Refills the output buffer, `results`. See also the pseudocode desciption
- /// of the algorithm in the `IsaacRng` documentation.
- ///
- /// Optimisations used (similar to the reference implementation):
- ///
- /// - The loop is unrolled 4 times, once for every constant of mix().
- /// - The contents of the main loop are moved to a function `rngstep`, to
- /// reduce code duplication.
- /// - We use local variables for a and b, which helps with optimisations.
- /// - We split the main loop in two, one that operates over 0..128 and one
- /// over 128..256. This way we can optimise out the addition and modulus
- /// from `s[i+128 mod 256]`.
- /// - We maintain one index `i` and add `m` or `m2` as base (m2 for the
- /// `s[i+128 mod 256]`), relying on the optimizer to turn it into pointer
- /// arithmetic.
- /// - We fill `results` backwards. The reference implementation reads values
- /// from `results` in reverse. We read them in the normal direction, to
- /// make `fill_bytes` a memcopy. To maintain compatibility we fill in
- /// reverse.
- fn generate(&mut self, results: &mut IsaacArray<Self::Item>) {
- self.c += w(1);
- // abbreviations
- let mut a = self.a;
- let mut b = self.b + self.c;
- const MIDPOINT: usize = RAND_SIZE / 2;
-
- #[inline]
- fn ind(mem:&[w32; RAND_SIZE], v: w32, amount: usize) -> w32 {
- let index = (v >> amount).0 as usize % RAND_SIZE;
- mem[index]
- }
-
- #[inline]
- fn rngstep(mem: &mut [w32; RAND_SIZE],
- results: &mut [u32; RAND_SIZE],
- mix: w32,
- a: &mut w32,
- b: &mut w32,
- base: usize,
- m: usize,
- m2: usize) {
- let x = mem[base + m];
- *a = mix + mem[base + m2];
- let y = *a + *b + ind(&mem, x, 2);
- mem[base + m] = y;
- *b = x + ind(&mem, y, 2 + RAND_SIZE_LEN);
- results[RAND_SIZE - 1 - base - m] = (*b).0;
- }
-
- let mut m = 0;
- let mut m2 = MIDPOINT;
- for i in (0..MIDPOINT/4).map(|i| i * 4) {
- rngstep(&mut self.mem, results, a ^ (a << 13), &mut a, &mut b, i + 0, m, m2);
- rngstep(&mut self.mem, results, a ^ (a >> 6 ), &mut a, &mut b, i + 1, m, m2);
- rngstep(&mut self.mem, results, a ^ (a << 2 ), &mut a, &mut b, i + 2, m, m2);
- rngstep(&mut self.mem, results, a ^ (a >> 16), &mut a, &mut b, i + 3, m, m2);
- }
-
- m = MIDPOINT;
- m2 = 0;
- for i in (0..MIDPOINT/4).map(|i| i * 4) {
- rngstep(&mut self.mem, results, a ^ (a << 13), &mut a, &mut b, i + 0, m, m2);
- rngstep(&mut self.mem, results, a ^ (a >> 6 ), &mut a, &mut b, i + 1, m, m2);
- rngstep(&mut self.mem, results, a ^ (a << 2 ), &mut a, &mut b, i + 2, m, m2);
- rngstep(&mut self.mem, results, a ^ (a >> 16), &mut a, &mut b, i + 3, m, m2);
- }
-
- self.a = a;
- self.b = b;
- }
-}
-
-impl IsaacCore {
- /// Create a new ISAAC random number generator.
- ///
- /// The author Bob Jenkins describes how to best initialize ISAAC here:
- /// <https://rt.cpan.org/Public/Bug/Display.html?id=64324>
- /// The answer is included here just in case:
- ///
- /// "No, you don't need a full 8192 bits of seed data. Normal key sizes will
- /// do fine, and they should have their expected strength (eg a 40-bit key
- /// will take as much time to brute force as 40-bit keys usually will). You
- /// could fill the remainder with 0, but set the last array element to the
- /// length of the key provided (to distinguish keys that differ only by
- /// different amounts of 0 padding). You do still need to call `randinit()`
- /// to make sure the initial state isn't uniform-looking."
- /// "After publishing ISAAC, I wanted to limit the key to half the size of
- /// `r[]`, and repeat it twice. That would have made it hard to provide a
- /// key that sets the whole internal state to anything convenient. But I'd
- /// already published it."
- ///
- /// And his answer to the question "For my code, would repeating the key
- /// over and over to fill 256 integers be a better solution than
- /// zero-filling, or would they essentially be the same?":
- /// "If the seed is under 32 bytes, they're essentially the same, otherwise
- /// repeating the seed would be stronger. randinit() takes a chunk of 32
- /// bytes, mixes it, and combines that with the next 32 bytes, et cetera.
- /// Then loops over all the elements the same way a second time."
- #[inline]
- fn init(mut mem: [w32; RAND_SIZE], rounds: u32) -> Self {
- fn mix(a: &mut w32, b: &mut w32, c: &mut w32, d: &mut w32,
- e: &mut w32, f: &mut w32, g: &mut w32, h: &mut w32) {
- *a ^= *b << 11; *d += *a; *b += *c;
- *b ^= *c >> 2; *e += *b; *c += *d;
- *c ^= *d << 8; *f += *c; *d += *e;
- *d ^= *e >> 16; *g += *d; *e += *f;
- *e ^= *f << 10; *h += *e; *f += *g;
- *f ^= *g >> 4; *a += *f; *g += *h;
- *g ^= *h << 8; *b += *g; *h += *a;
- *h ^= *a >> 9; *c += *h; *a += *b;
- }
-
- // These numbers are the result of initializing a...h with the
- // fractional part of the golden ratio in binary (0x9e3779b9)
- // and applying mix() 4 times.
- let mut a = w(0x1367df5a);
- let mut b = w(0x95d90059);
- let mut c = w(0xc3163e4b);
- let mut d = w(0x0f421ad8);
- let mut e = w(0xd92a4a78);
- let mut f = w(0xa51a3c49);
- let mut g = w(0xc4efea1b);
- let mut h = w(0x30609119);
-
- // Normally this should do two passes, to make all of the seed effect
- // all of `mem`
- for _ in 0..rounds {
- for i in (0..RAND_SIZE/8).map(|i| i * 8) {
- a += mem[i ]; b += mem[i+1];
- c += mem[i+2]; d += mem[i+3];
- e += mem[i+4]; f += mem[i+5];
- g += mem[i+6]; h += mem[i+7];
- mix(&mut a, &mut b, &mut c, &mut d,
- &mut e, &mut f, &mut g, &mut h);
- mem[i ] = a; mem[i+1] = b;
- mem[i+2] = c; mem[i+3] = d;
- mem[i+4] = e; mem[i+5] = f;
- mem[i+6] = g; mem[i+7] = h;
- }
- }
-
- Self { mem, a: w(0), b: w(0), c: w(0) }
- }
-}
-
-impl SeedableRng for IsaacCore {
- type Seed = [u8; 32];
-
- fn from_seed(seed: Self::Seed) -> Self {
- let mut seed_u32 = [0u32; 8];
- le::read_u32_into(&seed, &mut seed_u32);
- // Convert the seed to `Wrapping<u32>` and zero-extend to `RAND_SIZE`.
- let mut seed_extended = [w(0); RAND_SIZE];
- for (x, y) in seed_extended.iter_mut().zip(seed_u32.iter()) {
- *x = w(*y);
- }
- Self::init(seed_extended, 2)
- }
-
- /// Create an ISAAC random number generator using an `u64` as seed.
- /// If `seed == 0` this will produce the same stream of random numbers as
- /// the reference implementation when used unseeded.
- fn seed_from_u64(seed: u64) -> Self {
- let mut key = [w(0); RAND_SIZE];
- key[0] = w(seed as u32);
- key[1] = w((seed >> 32) as u32);
- // Initialize with only one pass.
- // A second pass does not improve the quality here, because all of the
- // seed was already available in the first round.
- // Not doing the second pass has the small advantage that if
- // `seed == 0` this method produces exactly the same state as the
- // reference implementation when used unseeded.
- Self::init(key, 1)
- }
-
- fn from_rng<R: RngCore>(mut rng: R) -> Result<Self, Error> {
- // Custom `from_rng` implementation that fills a seed with the same size
- // as the entire state.
- let mut seed = [w(0u32); RAND_SIZE];
- unsafe {
- let ptr = seed.as_mut_ptr() as *mut u8;
-
- let slice = slice::from_raw_parts_mut(ptr, RAND_SIZE * 4);
- rng.try_fill_bytes(slice)?;
- }
- for i in seed.iter_mut() {
- *i = w(i.0.to_le());
- }
-
- Ok(Self::init(seed, 2))
- }
-}
-
-#[cfg(test)]
-mod test {
- use rand_core::{RngCore, SeedableRng};
- use super::IsaacRng;
-
- #[test]
- fn test_isaac_construction() {
- // Test that various construction techniques produce a working RNG.
- let seed = [1,0,0,0, 23,0,0,0, 200,1,0,0, 210,30,0,0,
- 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0];
- let mut rng1 = IsaacRng::from_seed(seed);
- assert_eq!(rng1.next_u32(), 2869442790);
-
- let mut rng2 = IsaacRng::from_rng(rng1).unwrap();
- assert_eq!(rng2.next_u32(), 3094074039);
- }
-
- #[test]
- fn test_isaac_true_values_32() {
- let seed = [1,0,0,0, 23,0,0,0, 200,1,0,0, 210,30,0,0,
- 57,48,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0];
- let mut rng1 = IsaacRng::from_seed(seed);
- let mut results = [0u32; 10];
- for i in results.iter_mut() { *i = rng1.next_u32(); }
- let expected = [
- 2558573138, 873787463, 263499565, 2103644246, 3595684709,
- 4203127393, 264982119, 2765226902, 2737944514, 3900253796];
- assert_eq!(results, expected);
-
- let seed = [57,48,0,0, 50,9,1,0, 49,212,0,0, 148,38,0,0,
- 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0];
- let mut rng2 = IsaacRng::from_seed(seed);
- // skip forward to the 10000th number
- for _ in 0..10000 { rng2.next_u32(); }
-
- for i in results.iter_mut() { *i = rng2.next_u32(); }
- let expected = [
- 3676831399, 3183332890, 2834741178, 3854698763, 2717568474,
- 1576568959, 3507990155, 179069555, 141456972, 2478885421];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_isaac_true_values_64() {
- // As above, using little-endian versions of above values
- let seed = [1,0,0,0, 23,0,0,0, 200,1,0,0, 210,30,0,0,
- 57,48,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0];
- let mut rng = IsaacRng::from_seed(seed);
- let mut results = [0u64; 5];
- for i in results.iter_mut() { *i = rng.next_u64(); }
- let expected = [
- 3752888579798383186, 9035083239252078381,18052294697452424037,
- 11876559110374379111, 16751462502657800130];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_isaac_true_bytes() {
- let seed = [1,0,0,0, 23,0,0,0, 200,1,0,0, 210,30,0,0,
- 57,48,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0];
- let mut rng = IsaacRng::from_seed(seed);
- let mut results = [0u8; 32];
- rng.fill_bytes(&mut results);
- // Same as first values in test_isaac_true_values as bytes in LE order
- let expected = [82, 186, 128, 152, 71, 240, 20, 52,
- 45, 175, 180, 15, 86, 16, 99, 125,
- 101, 203, 81, 214, 97, 162, 134, 250,
- 103, 78, 203, 15, 150, 3, 210, 164];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_isaac_new_uninitialized() {
- // Compare the results from initializing `IsaacRng` with
- // `seed_from_u64(0)`, to make sure it is the same as the reference
- // implementation when used uninitialized.
- // Note: We only test the first 16 integers, not the full 256 of the
- // first block.
- let mut rng = IsaacRng::seed_from_u64(0);
- let mut results = [0u32; 16];
- for i in results.iter_mut() { *i = rng.next_u32(); }
- let expected: [u32; 16] = [
- 0x71D71FD2, 0xB54ADAE7, 0xD4788559, 0xC36129FA,
- 0x21DC1EA9, 0x3CB879CA, 0xD83B237F, 0xFA3CE5BD,
- 0x8D048509, 0xD82E9489, 0xDB452848, 0xCA20E846,
- 0x500F972E, 0x0EEFF940, 0x00D6B993, 0xBC12C17F];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_isaac_clone() {
- let seed = [1,0,0,0, 23,0,0,0, 200,1,0,0, 210,30,0,0,
- 57,48,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0];
- let mut rng1 = IsaacRng::from_seed(seed);
- let mut rng2 = rng1.clone();
- for _ in 0..16 {
- assert_eq!(rng1.next_u32(), rng2.next_u32());
- }
- }
-
- #[test]
- #[cfg(feature="serde1")]
- fn test_isaac_serde() {
- use bincode;
- use std::io::{BufWriter, BufReader};
-
- let seed = [1,0,0,0, 23,0,0,0, 200,1,0,0, 210,30,0,0,
- 57,48,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0];
- let mut rng = IsaacRng::from_seed(seed);
-
- let buf: Vec<u8> = Vec::new();
- let mut buf = BufWriter::new(buf);
- bincode::serialize_into(&mut buf, &rng).expect("Could not serialize");
-
- let buf = buf.into_inner().unwrap();
- let mut read = BufReader::new(&buf[..]);
- let mut deserialized: IsaacRng = bincode::deserialize_from(&mut read).expect("Could not deserialize");
-
- for _ in 0..300 { // more than the 256 buffered results
- assert_eq!(rng.next_u32(), deserialized.next_u32());
- }
- }
-}
diff --git a/rand/rand_isaac/src/isaac64.rs b/rand/rand_isaac/src/isaac64.rs
deleted file mode 100644
index 7d4b88c..0000000
--- a/rand/rand_isaac/src/isaac64.rs
+++ /dev/null
@@ -1,466 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013-2018 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The ISAAC-64 random number generator.
-
-use core::{fmt, slice};
-use core::num::Wrapping as w;
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core::{RngCore, SeedableRng, Error, le};
-use rand_core::block::{BlockRngCore, BlockRng64};
-use crate::isaac_array::IsaacArray;
-
-#[allow(non_camel_case_types)]
-type w64 = w<u64>;
-
-const RAND_SIZE_LEN: usize = 8;
-const RAND_SIZE: usize = 1 << RAND_SIZE_LEN;
-
-/// A random number generator that uses ISAAC-64, the 64-bit variant of the
-/// ISAAC algorithm.
-///
-/// ISAAC stands for "Indirection, Shift, Accumulate, Add, and Count" which are
-/// the principal bitwise operations employed. It is the most advanced of a
-/// series of array based random number generator designed by Robert Jenkins
-/// in 1996[^1].
-///
-/// ISAAC-64 is mostly similar to ISAAC. Because it operates on 64-bit integers
-/// instead of 32-bit, it uses twice as much memory to hold its state and
-/// results. Also it uses different constants for shifts and indirect indexing,
-/// optimized to give good results for 64bit arithmetic.
-///
-/// ISAAC-64 is notably fast and produces excellent quality random numbers for
-/// non-cryptographic applications.
-///
-/// In spite of being designed with cryptographic security in mind, ISAAC hasn't
-/// been stringently cryptanalyzed and thus cryptographers do not not
-/// consensually trust it to be secure. When looking for a secure RNG, prefer
-/// `Hc128Rng` from the [`rand_hc`] crate instead, which, like ISAAC, is an
-/// array-based RNG and one of the stream-ciphers selected the by eSTREAM
-///
-/// ## Overview of the ISAAC-64 algorithm:
-/// (in pseudo-code)
-///
-/// ```text
-/// Input: a, b, c, s[256] // state
-/// Output: r[256] // results
-///
-/// mix(a,i) = !(a ^ a << 21) if i = 0 mod 4
-/// a ^ a >> 5 if i = 1 mod 4
-/// a ^ a << 12 if i = 2 mod 4
-/// a ^ a >> 33 if i = 3 mod 4
-///
-/// c = c + 1
-/// b = b + c
-///
-/// for i in 0..256 {
-/// x = s_[i]
-/// a = mix(a,i) + s[i+128 mod 256]
-/// y = a + b + s[x>>3 mod 256]
-/// s[i] = y
-/// b = x + s[y>>11 mod 256]
-/// r[i] = b
-/// }
-/// ```
-///
-/// This implementation uses [`BlockRng64`] to implement the [`RngCore`] methods.
-///
-/// See for more information the documentation of [`IsaacRng`].
-///
-/// [^1]: Bob Jenkins, [*ISAAC and RC4*](
-/// http://burtleburtle.net/bob/rand/isaac.html)
-///
-/// [`IsaacRng`]: crate::isaac::IsaacRng
-/// [`rand_hc`]: https://docs.rs/rand_hc
-/// [`BlockRng64`]: rand_core::block::BlockRng64
-#[derive(Clone, Debug)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Isaac64Rng(BlockRng64<Isaac64Core>);
-
-impl RngCore for Isaac64Rng {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.0.next_u32()
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- self.0.next_u64()
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- self.0.fill_bytes(dest)
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.0.try_fill_bytes(dest)
- }
-}
-
-impl SeedableRng for Isaac64Rng {
- type Seed = <Isaac64Core as SeedableRng>::Seed;
-
- #[inline]
- fn from_seed(seed: Self::Seed) -> Self {
- Isaac64Rng(BlockRng64::<Isaac64Core>::from_seed(seed))
- }
-
- /// Create an ISAAC random number generator using an `u64` as seed.
- /// If `seed == 0` this will produce the same stream of random numbers as
- /// the reference implementation when used unseeded.
- #[inline]
- fn seed_from_u64(seed: u64) -> Self {
- Isaac64Rng(BlockRng64::<Isaac64Core>::seed_from_u64(seed))
- }
-
- #[inline]
- fn from_rng<S: RngCore>(rng: S) -> Result<Self, Error> {
- BlockRng64::<Isaac64Core>::from_rng(rng).map(|rng| Isaac64Rng(rng))
- }
-}
-
-/// The core of `Isaac64Rng`, used with `BlockRng`.
-#[derive(Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Isaac64Core {
- #[cfg_attr(feature="serde1",serde(with="super::isaac_array::isaac_array_serde"))]
- mem: [w64; RAND_SIZE],
- a: w64,
- b: w64,
- c: w64,
-}
-
-// Custom Debug implementation that does not expose the internal state
-impl fmt::Debug for Isaac64Core {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "Isaac64Core {{}}")
- }
-}
-
-impl BlockRngCore for Isaac64Core {
- type Item = u64;
- type Results = IsaacArray<Self::Item>;
-
- /// Refills the output buffer, `results`. See also the pseudocode desciption
- /// of the algorithm in the `Isaac64Rng` documentation.
- ///
- /// Optimisations used (similar to the reference implementation):
- ///
- /// - The loop is unrolled 4 times, once for every constant of mix().
- /// - The contents of the main loop are moved to a function `rngstep`, to
- /// reduce code duplication.
- /// - We use local variables for a and b, which helps with optimisations.
- /// - We split the main loop in two, one that operates over 0..128 and one
- /// over 128..256. This way we can optimise out the addition and modulus
- /// from `s[i+128 mod 256]`.
- /// - We maintain one index `i` and add `m` or `m2` as base (m2 for the
- /// `s[i+128 mod 256]`), relying on the optimizer to turn it into pointer
- /// arithmetic.
- /// - We fill `results` backwards. The reference implementation reads values
- /// from `results` in reverse. We read them in the normal direction, to
- /// make `fill_bytes` a memcopy. To maintain compatibility we fill in
- /// reverse.
- fn generate(&mut self, results: &mut IsaacArray<Self::Item>) {
- self.c += w(1);
- // abbreviations
- let mut a = self.a;
- let mut b = self.b + self.c;
- const MIDPOINT: usize = RAND_SIZE / 2;
-
- #[inline]
- fn ind(mem:&[w64; RAND_SIZE], v: w64, amount: usize) -> w64 {
- let index = (v >> amount).0 as usize % RAND_SIZE;
- mem[index]
- }
-
- #[inline]
- fn rngstep(mem: &mut [w64; RAND_SIZE],
- results: &mut [u64; RAND_SIZE],
- mix: w64,
- a: &mut w64,
- b: &mut w64,
- base: usize,
- m: usize,
- m2: usize) {
- let x = mem[base + m];
- *a = mix + mem[base + m2];
- let y = *a + *b + ind(&mem, x, 3);
- mem[base + m] = y;
- *b = x + ind(&mem, y, 3 + RAND_SIZE_LEN);
- results[RAND_SIZE - 1 - base - m] = (*b).0;
- }
-
- let mut m = 0;
- let mut m2 = MIDPOINT;
- for i in (0..MIDPOINT/4).map(|i| i * 4) {
- rngstep(&mut self.mem, results, !(a ^ (a << 21)), &mut a, &mut b, i + 0, m, m2);
- rngstep(&mut self.mem, results, a ^ (a >> 5 ), &mut a, &mut b, i + 1, m, m2);
- rngstep(&mut self.mem, results, a ^ (a << 12), &mut a, &mut b, i + 2, m, m2);
- rngstep(&mut self.mem, results, a ^ (a >> 33), &mut a, &mut b, i + 3, m, m2);
- }
-
- m = MIDPOINT;
- m2 = 0;
- for i in (0..MIDPOINT/4).map(|i| i * 4) {
- rngstep(&mut self.mem, results, !(a ^ (a << 21)), &mut a, &mut b, i + 0, m, m2);
- rngstep(&mut self.mem, results, a ^ (a >> 5 ), &mut a, &mut b, i + 1, m, m2);
- rngstep(&mut self.mem, results, a ^ (a << 12), &mut a, &mut b, i + 2, m, m2);
- rngstep(&mut self.mem, results, a ^ (a >> 33), &mut a, &mut b, i + 3, m, m2);
- }
-
- self.a = a;
- self.b = b;
- }
-}
-
-impl Isaac64Core {
- /// Create a new ISAAC-64 random number generator.
- fn init(mut mem: [w64; RAND_SIZE], rounds: u32) -> Self {
- fn mix(a: &mut w64, b: &mut w64, c: &mut w64, d: &mut w64,
- e: &mut w64, f: &mut w64, g: &mut w64, h: &mut w64) {
- *a -= *e; *f ^= *h >> 9; *h += *a;
- *b -= *f; *g ^= *a << 9; *a += *b;
- *c -= *g; *h ^= *b >> 23; *b += *c;
- *d -= *h; *a ^= *c << 15; *c += *d;
- *e -= *a; *b ^= *d >> 14; *d += *e;
- *f -= *b; *c ^= *e << 20; *e += *f;
- *g -= *c; *d ^= *f >> 17; *f += *g;
- *h -= *d; *e ^= *g << 14; *g += *h;
- }
-
- // These numbers are the result of initializing a...h with the
- // fractional part of the golden ratio in binary (0x9e3779b97f4a7c13)
- // and applying mix() 4 times.
- let mut a = w(0x647c4677a2884b7c);
- let mut b = w(0xb9f8b322c73ac862);
- let mut c = w(0x8c0ea5053d4712a0);
- let mut d = w(0xb29b2e824a595524);
- let mut e = w(0x82f053db8355e0ce);
- let mut f = w(0x48fe4a0fa5a09315);
- let mut g = w(0xae985bf2cbfc89ed);
- let mut h = w(0x98f5704f6c44c0ab);
-
- // Normally this should do two passes, to make all of the seed effect
- // all of `mem`
- for _ in 0..rounds {
- for i in (0..RAND_SIZE/8).map(|i| i * 8) {
- a += mem[i ]; b += mem[i+1];
- c += mem[i+2]; d += mem[i+3];
- e += mem[i+4]; f += mem[i+5];
- g += mem[i+6]; h += mem[i+7];
- mix(&mut a, &mut b, &mut c, &mut d,
- &mut e, &mut f, &mut g, &mut h);
- mem[i ] = a; mem[i+1] = b;
- mem[i+2] = c; mem[i+3] = d;
- mem[i+4] = e; mem[i+5] = f;
- mem[i+6] = g; mem[i+7] = h;
- }
- }
-
- Self { mem, a: w(0), b: w(0), c: w(0) }
- }
-}
-
-impl SeedableRng for Isaac64Core {
- type Seed = [u8; 32];
-
- fn from_seed(seed: Self::Seed) -> Self {
- let mut seed_u64 = [0u64; 4];
- le::read_u64_into(&seed, &mut seed_u64);
- // Convert the seed to `Wrapping<u64>` and zero-extend to `RAND_SIZE`.
- let mut seed_extended = [w(0); RAND_SIZE];
- for (x, y) in seed_extended.iter_mut().zip(seed_u64.iter()) {
- *x = w(*y);
- }
- Self::init(seed_extended, 2)
- }
-
- fn seed_from_u64(seed: u64) -> Self {
- let mut key = [w(0); RAND_SIZE];
- key[0] = w(seed);
- // Initialize with only one pass.
- // A second pass does not improve the quality here, because all of the
- // seed was already available in the first round.
- // Not doing the second pass has the small advantage that if
- // `seed == 0` this method produces exactly the same state as the
- // reference implementation when used unseeded.
- Self::init(key, 1)
- }
-
- fn from_rng<R: RngCore>(mut rng: R) -> Result<Self, Error> {
- // Custom `from_rng` implementation that fills a seed with the same size
- // as the entire state.
- let mut seed = [w(0u64); RAND_SIZE];
- unsafe {
- let ptr = seed.as_mut_ptr() as *mut u8;
- let slice = slice::from_raw_parts_mut(ptr, RAND_SIZE * 8);
- rng.try_fill_bytes(slice)?;
- }
- for i in seed.iter_mut() {
- *i = w(i.0.to_le());
- }
-
- Ok(Self::init(seed, 2))
- }
-}
-
-#[cfg(test)]
-mod test {
- use rand_core::{RngCore, SeedableRng};
- use super::Isaac64Rng;
-
- #[test]
- fn test_isaac64_construction() {
- // Test that various construction techniques produce a working RNG.
- let seed = [1,0,0,0, 23,0,0,0, 200,1,0,0, 210,30,0,0,
- 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0];
- let mut rng1 = Isaac64Rng::from_seed(seed);
- assert_eq!(rng1.next_u64(), 14964555543728284049);
-
- let mut rng2 = Isaac64Rng::from_rng(rng1).unwrap();
- assert_eq!(rng2.next_u64(), 919595328260451758);
- }
-
- #[test]
- fn test_isaac64_true_values_64() {
- let seed = [1,0,0,0, 0,0,0,0, 23,0,0,0, 0,0,0,0,
- 200,1,0,0, 0,0,0,0, 210,30,0,0, 0,0,0,0];
- let mut rng1 = Isaac64Rng::from_seed(seed);
- let mut results = [0u64; 10];
- for i in results.iter_mut() { *i = rng1.next_u64(); }
- let expected = [
- 15071495833797886820, 7720185633435529318,
- 10836773366498097981, 5414053799617603544,
- 12890513357046278984, 17001051845652595546,
- 9240803642279356310, 12558996012687158051,
- 14673053937227185542, 1677046725350116783];
- assert_eq!(results, expected);
-
- let seed = [57,48,0,0, 0,0,0,0, 50,9,1,0, 0,0,0,0,
- 49,212,0,0, 0,0,0,0, 148,38,0,0, 0,0,0,0];
- let mut rng2 = Isaac64Rng::from_seed(seed);
- // skip forward to the 10000th number
- for _ in 0..10000 { rng2.next_u64(); }
-
- for i in results.iter_mut() { *i = rng2.next_u64(); }
- let expected = [
- 18143823860592706164, 8491801882678285927, 2699425367717515619,
- 17196852593171130876, 2606123525235546165, 15790932315217671084,
- 596345674630742204, 9947027391921273664, 11788097613744130851,
- 10391409374914919106];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_isaac64_true_values_32() {
- let seed = [1,0,0,0, 0,0,0,0, 23,0,0,0, 0,0,0,0,
- 200,1,0,0, 0,0,0,0, 210,30,0,0, 0,0,0,0];
- let mut rng = Isaac64Rng::from_seed(seed);
- let mut results = [0u32; 12];
- for i in results.iter_mut() { *i = rng.next_u32(); }
- // Subset of above values, as an LE u32 sequence
- let expected = [
- 3477963620, 3509106075,
- 687845478, 1797495790,
- 227048253, 2523132918,
- 4044335064, 1260557630,
- 4079741768, 3001306521,
- 69157722, 3958365844];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_isaac64_true_values_mixed() {
- let seed = [1,0,0,0, 0,0,0,0, 23,0,0,0, 0,0,0,0,
- 200,1,0,0, 0,0,0,0, 210,30,0,0, 0,0,0,0];
- let mut rng = Isaac64Rng::from_seed(seed);
- // Test alternating between `next_u64` and `next_u32` works as expected.
- // Values are the same as `test_isaac64_true_values` and
- // `test_isaac64_true_values_32`.
- assert_eq!(rng.next_u64(), 15071495833797886820);
- assert_eq!(rng.next_u32(), 687845478);
- assert_eq!(rng.next_u32(), 1797495790);
- assert_eq!(rng.next_u64(), 10836773366498097981);
- assert_eq!(rng.next_u32(), 4044335064);
- // Skip one u32
- assert_eq!(rng.next_u64(), 12890513357046278984);
- assert_eq!(rng.next_u32(), 69157722);
- }
-
- #[test]
- fn test_isaac64_true_bytes() {
- let seed = [1,0,0,0, 0,0,0,0, 23,0,0,0, 0,0,0,0,
- 200,1,0,0, 0,0,0,0, 210,30,0,0, 0,0,0,0];
- let mut rng = Isaac64Rng::from_seed(seed);
- let mut results = [0u8; 32];
- rng.fill_bytes(&mut results);
- // Same as first values in test_isaac64_true_values as bytes in LE order
- let expected = [100, 131, 77, 207, 155, 181, 40, 209,
- 102, 176, 255, 40, 238, 155, 35, 107,
- 61, 123, 136, 13, 246, 243, 99, 150,
- 216, 167, 15, 241, 62, 149, 34, 75];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_isaac64_new_uninitialized() {
- // Compare the results from initializing `IsaacRng` with
- // `seed_from_u64(0)`, to make sure it is the same as the reference
- // implementation when used uninitialized.
- // Note: We only test the first 16 integers, not the full 256 of the
- // first block.
- let mut rng = Isaac64Rng::seed_from_u64(0);
- let mut results = [0u64; 16];
- for i in results.iter_mut() { *i = rng.next_u64(); }
- let expected: [u64; 16] = [
- 0xF67DFBA498E4937C, 0x84A5066A9204F380, 0xFEE34BD5F5514DBB,
- 0x4D1664739B8F80D6, 0x8607459AB52A14AA, 0x0E78BC5A98529E49,
- 0xFE5332822AD13777, 0x556C27525E33D01A, 0x08643CA615F3149F,
- 0xD0771FAF3CB04714, 0x30E86F68A37B008D, 0x3074EBC0488A3ADF,
- 0x270645EA7A2790BC, 0x5601A0A8D3763C6A, 0x2F83071F53F325DD,
- 0xB9090F3D42D2D2EA];
- assert_eq!(results, expected);
- }
-
- #[test]
- fn test_isaac64_clone() {
- let seed = [1,0,0,0, 0,0,0,0, 23,0,0,0, 0,0,0,0,
- 200,1,0,0, 0,0,0,0, 210,30,0,0, 0,0,0,0];
- let mut rng1 = Isaac64Rng::from_seed(seed);
- let mut rng2 = rng1.clone();
- for _ in 0..16 {
- assert_eq!(rng1.next_u64(), rng2.next_u64());
- }
- }
-
- #[test]
- #[cfg(feature="serde1")]
- fn test_isaac64_serde() {
- use bincode;
- use std::io::{BufWriter, BufReader};
-
- let seed = [1,0,0,0, 23,0,0,0, 200,1,0,0, 210,30,0,0,
- 57,48,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0];
- let mut rng = Isaac64Rng::from_seed(seed);
-
- let buf: Vec<u8> = Vec::new();
- let mut buf = BufWriter::new(buf);
- bincode::serialize_into(&mut buf, &rng).expect("Could not serialize");
-
- let buf = buf.into_inner().unwrap();
- let mut read = BufReader::new(&buf[..]);
- let mut deserialized: Isaac64Rng = bincode::deserialize_from(&mut read).expect("Could not deserialize");
-
- for _ in 0..300 { // more than the 256 buffered results
- assert_eq!(rng.next_u64(), deserialized.next_u64());
- }
- }
-}
diff --git a/rand/rand_isaac/src/isaac_array.rs b/rand/rand_isaac/src/isaac_array.rs
deleted file mode 100644
index cbe4a59..0000000
--- a/rand/rand_isaac/src/isaac_array.rs
+++ /dev/null
@@ -1,136 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2017-2018 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! ISAAC helper functions for 256-element arrays.
-
-// Terrible workaround because arrays with more than 32 elements do not
-// implement `AsRef`, `Default`, `Serialize`, `Deserialize`, or any other
-// traits for that matter.
-
-#[cfg(feature="serde")] use serde::{Serialize, Deserialize};
-
-const RAND_SIZE_LEN: usize = 8;
-const RAND_SIZE: usize = 1 << RAND_SIZE_LEN;
-
-
-#[derive(Copy, Clone)]
-#[allow(missing_debug_implementations)]
-#[cfg_attr(feature="serde", derive(Serialize, Deserialize))]
-pub struct IsaacArray<T> {
- #[cfg_attr(feature="serde",serde(with="isaac_array_serde"))]
- #[cfg_attr(feature="serde", serde(bound(
- serialize = "T: Serialize",
- deserialize = "T: Deserialize<'de> + Copy + Default")))]
- inner: [T; RAND_SIZE]
-}
-
-impl<T> ::core::convert::AsRef<[T]> for IsaacArray<T> {
- #[inline(always)]
- fn as_ref(&self) -> &[T] {
- &self.inner[..]
- }
-}
-
-impl<T> ::core::convert::AsMut<[T]> for IsaacArray<T> {
- #[inline(always)]
- fn as_mut(&mut self) -> &mut [T] {
- &mut self.inner[..]
- }
-}
-
-impl<T> ::core::ops::Deref for IsaacArray<T> {
- type Target = [T; RAND_SIZE];
- #[inline(always)]
- fn deref(&self) -> &Self::Target {
- &self.inner
- }
-}
-
-impl<T> ::core::ops::DerefMut for IsaacArray<T> {
- #[inline(always)]
- fn deref_mut(&mut self) -> &mut [T; RAND_SIZE] {
- &mut self.inner
- }
-}
-
-impl<T> ::core::default::Default for IsaacArray<T> where T: Copy + Default {
- fn default() -> IsaacArray<T> {
- IsaacArray { inner: [T::default(); RAND_SIZE] }
- }
-}
-
-
-#[cfg(feature="serde")]
-pub(super) mod isaac_array_serde {
- const RAND_SIZE_LEN: usize = 8;
- const RAND_SIZE: usize = 1 << RAND_SIZE_LEN;
-
- use serde::{Deserialize, Deserializer, Serialize, Serializer};
- use serde::de::{Visitor,SeqAccess};
- use serde::de;
-
- use core::fmt;
-
- pub fn serialize<T, S>(arr: &[T;RAND_SIZE], ser: S) -> Result<S::Ok, S::Error>
- where
- T: Serialize,
- S: Serializer
- {
- use serde::ser::SerializeTuple;
-
- let mut seq = ser.serialize_tuple(RAND_SIZE)?;
-
- for e in arr.iter() {
- seq.serialize_element(&e)?;
- }
-
- seq.end()
- }
-
- #[inline]
- pub fn deserialize<'de, T, D>(de: D) -> Result<[T;RAND_SIZE], D::Error>
- where
- T: Deserialize<'de>+Default+Copy,
- D: Deserializer<'de>,
- {
- use core::marker::PhantomData;
- struct ArrayVisitor<T> {
- _pd: PhantomData<T>,
- };
- impl<'de,T> Visitor<'de> for ArrayVisitor<T>
- where
- T: Deserialize<'de>+Default+Copy
- {
- type Value = [T; RAND_SIZE];
-
- fn expecting(&self, formatter: &mut fmt::Formatter) -> fmt::Result {
- formatter.write_str("Isaac state array")
- }
-
- #[inline]
- fn visit_seq<A>(self, mut seq: A) -> Result<[T; RAND_SIZE], A::Error>
- where
- A: SeqAccess<'de>,
- {
- let mut out = [Default::default();RAND_SIZE];
-
- for i in 0..RAND_SIZE {
- match seq.next_element()? {
- Some(val) => out[i] = val,
- None => return Err(de::Error::invalid_length(i, &self)),
- };
- }
-
- Ok(out)
- }
- }
-
- de.deserialize_tuple(RAND_SIZE, ArrayVisitor{_pd: PhantomData})
- }
-}
diff --git a/rand/rand_isaac/src/lib.rs b/rand/rand_isaac/src/lib.rs
deleted file mode 100644
index 84cdf21..0000000
--- a/rand/rand_isaac/src/lib.rs
+++ /dev/null
@@ -1,27 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The ISAAC and ISAAC-64 random number generators.
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
- html_favicon_url = "https://www.rust-lang.org/favicon.ico",
- html_root_url = "https://rust-random.github.io/rand/")]
-
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-#![doc(test(attr(allow(unused_variables), deny(warnings))))]
-
-#![cfg_attr(not(all(feature="serde", test)), no_std)]
-
-pub mod isaac;
-pub mod isaac64;
-
-mod isaac_array;
-
-pub use self::isaac::IsaacRng;
-pub use self::isaac64::Isaac64Rng;
diff --git a/rand/rand_jitter/CHANGELOG.md b/rand/rand_jitter/CHANGELOG.md
deleted file mode 100644
index 9f4bb7e..0000000
--- a/rand/rand_jitter/CHANGELOG.md
+++ /dev/null
@@ -1,32 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.2.1] - 2019-08-16
-### Changed
-- `TimerError` changed to `repr(u32)` (#864)
-- `TimerError` enum values all increased by `1<<30` to match new `rand_core::Error` range (#864)
-
-## [0.2.0] - 2019-06-06
-- Bump `rand_core` version
-- Support new `Error` type in `rand_core` 0.5
-- Remove CryptoRng trait bound (#699, #814)
-- Enable doc-testing of README
-
-## [0.1.4] - 2019-05-02
-- Change error conversion code to partially fix #738
-
-## [0.1.3] - 2019-02-05
-- Use libc in `no_std` mode to fix #723
-
-## [0.1.2] - 2019-01-31
-- Fix for older rustc compilers on Windows (#722)
-
-## [0.1.1] - 2019-01-29
-- Fix for older rustc compilers on Mac OSX / iOS (#720)
-- Misc. doc fixes
-
-## [0.1.0] - 2019-01-24
-Initial release.
diff --git a/rand/rand_jitter/COPYRIGHT b/rand/rand_jitter/COPYRIGHT
deleted file mode 100644
index 468d907..0000000
--- a/rand/rand_jitter/COPYRIGHT
+++ /dev/null
@@ -1,12 +0,0 @@
-Copyrights in the Rand project are retained by their contributors. No
-copyright assignment is required to contribute to the Rand project.
-
-For full authorship information, see the version control history.
-
-Except as otherwise noted (below and/or in individual files), Rand is
-licensed under the Apache License, Version 2.0 <LICENSE-APACHE> or
-<http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-<LICENSE-MIT> or <http://opensource.org/licenses/MIT>, at your option.
-
-The Rand project includes code from the Rust project
-published under these same licenses.
diff --git a/rand/rand_jitter/Cargo.toml b/rand/rand_jitter/Cargo.toml
deleted file mode 100644
index 5b7e3c3..0000000
--- a/rand/rand_jitter/Cargo.toml
+++ /dev/null
@@ -1,30 +0,0 @@
-[package]
-name = "rand_jitter"
-version = "0.2.1"
-authors = ["The Rand Project Developers"]
-license = "MIT OR Apache-2.0"
-readme = "README.md"
-repository = "https://github.com/rust-random/rand"
-documentation = "https://docs.rs/rand_jitter"
-description = "Random number generator based on timing jitter"
-keywords = ["random", "rng", "os"]
-edition = "2018"
-
-[badges]
-travis-ci = { repository = "rust-random/rand" }
-appveyor = { repository = "rust-random/rand" }
-
-[dependencies]
-rand_core = { path = "../rand_core", version = "0.5" }
-log = { version = "0.4", optional = true }
-
-[target.'cfg(any(target_os = "macos", target_os = "ios"))'.dependencies]
-# We don't need the 'use_std' feature and depending on it causes
-# issues due to: https://github.com/rust-lang/cargo/issues/1197
-libc = { version = "0.2", default_features = false }
-
-[target.'cfg(target_os = "windows")'.dependencies]
-winapi = { version = "0.3", features = ["profileapi"] }
-
-[features]
-std = ["rand_core/std"]
diff --git a/rand/rand_jitter/LICENSE-APACHE b/rand/rand_jitter/LICENSE-APACHE
deleted file mode 100644
index 17d7468..0000000
--- a/rand/rand_jitter/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
- Apache License
- Version 2.0, January 2004
- https://www.apache.org/licenses/
-
-TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
-
-1. Definitions.
-
- "License" shall mean the terms and conditions for use, reproduction,
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- "Work" shall mean the work of authorship, whether in Source or
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-5. Submission of Contributions. Unless You explicitly state otherwise,
- any Contribution intentionally submitted for inclusion in the Work
- by You to the Licensor shall be under the terms and conditions of
- this License, without any additional terms or conditions.
- Notwithstanding the above, nothing herein shall supersede or modify
- the terms of any separate license agreement you may have executed
- with Licensor regarding such Contributions.
-
-6. Trademarks. This License does not grant permission to use the trade
- names, trademarks, service marks, or product names of the Licensor,
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-
-7. Disclaimer of Warranty. Unless required by applicable law or
- agreed to in writing, Licensor provides the Work (and each
- Contributor provides its Contributions) on an "AS IS" BASIS,
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-8. Limitation of Liability. In no event and under no legal theory,
- whether in tort (including negligence), contract, or otherwise,
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-
-APPENDIX: How to apply the Apache License to your work.
-
- To apply the Apache License to your work, attach the following
- boilerplate notice, with the fields enclosed by brackets "[]"
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- https://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
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diff --git a/rand/rand_jitter/LICENSE-MIT b/rand/rand_jitter/LICENSE-MIT
deleted file mode 100644
index d93b5ba..0000000
--- a/rand/rand_jitter/LICENSE-MIT
+++ /dev/null
@@ -1,26 +0,0 @@
-Copyright 2018 Developers of the Rand project
-Copyright (c) 2014 The Rust Project Developers
-
-Permission is hereby granted, free of charge, to any
-person obtaining a copy of this software and associated
-documentation files (the "Software"), to deal in the
-Software without restriction, including without
-limitation the rights to use, copy, modify, merge,
-publish, distribute, sublicense, and/or sell copies of
-the Software, and to permit persons to whom the Software
-is furnished to do so, subject to the following
-conditions:
-
-The above copyright notice and this permission notice
-shall be included in all copies or substantial portions
-of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF
-ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED
-TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
-PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
-SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
-IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-DEALINGS IN THE SOFTWARE.
diff --git a/rand/rand_jitter/README.md b/rand/rand_jitter/README.md
deleted file mode 100644
index 2091d6c..0000000
--- a/rand/rand_jitter/README.md
+++ /dev/null
@@ -1,119 +0,0 @@
-# rand_jitter
-[](https://travis-ci.org/rust-random/rand)
-[](https://ci.appveyor.com/project/rust-random/rand)
-[](https://crates.io/crates/rand_jitter)
-[](https://rust-random.github.io/book/)
-[](https://rust-random.github.io/rand/rand_jitter)
-[](https://docs.rs/rand_jitter)
-[](https://github.com/rust-random/rand#rust-version-requirements)
-
-Non-physical true random number generator based on timing jitter.
-
-Note that this RNG is not suited for use cases where cryptographic security is
-required (also see [this
-discussion](https://github.com/rust-random/rand/issues/699)).
-
-This crate depends on [rand_core](https://crates.io/crates/rand_core) and is
-part of the [Rand project](https://github.com/rust-random/rand).
-
-This crate aims to support all of Rust's `std` platforms with a system-provided
-entropy source. Unlike other Rand crates, this crate does not support `no_std`
-(handling this gracefully is a current discussion topic).
-
-Links:
-
-- [API documentation (master)](https://rust-random.github.io/rand/rand_jitter)
-- [API documentation (docs.rs)](https://docs.rs/rand_jitter)
-- [Changelog](https://github.com/rust-random/rand/blob/master/rand_jitter/CHANGELOG.md)
-
-## Features
-
-This crate has optional `std` support which is *disabled by default*;
-this feature is required to provide the `JitterRng::new` function;
-without `std` support a timer must be supplied via `JitterRng::new_with_timer`.
-
-## Quality testing
-
-`JitterRng::new()` has build-in, but limited, quality testing, however
-before using `JitterRng` on untested hardware, or after changes that could
-effect how the code is optimized (such as a new LLVM version), it is
-recommend to run the much more stringent
-[NIST SP 800-90B Entropy Estimation Suite](https://github.com/usnistgov/SP800-90B_EntropyAssessment).
-
-Use the following code using `timer_stats` to collect the data:
-
-```rust,no_run
-use rand_jitter::JitterRng;
-
-use std::error::Error;
-use std::fs::File;
-use std::io::Write;
-
-fn get_nstime() -> u64 {
- use std::time::{SystemTime, UNIX_EPOCH};
-
- let dur = SystemTime::now().duration_since(UNIX_EPOCH).unwrap();
- // The correct way to calculate the current time is
- // `dur.as_secs() * 1_000_000_000 + dur.subsec_nanos() as u64`
- // But this is faster, and the difference in terms of entropy is
- // negligible (log2(10^9) == 29.9).
- dur.as_secs() << 30 | dur.subsec_nanos() as u64
-}
-
-fn main() -> Result<(), Box<dyn Error>> {
- let mut rng = JitterRng::new_with_timer(get_nstime);
-
- // 1_000_000 results are required for the
- // NIST SP 800-90B Entropy Estimation Suite
- const ROUNDS: usize = 1_000_000;
- let mut deltas_variable: Vec<u8> = Vec::with_capacity(ROUNDS);
- let mut deltas_minimal: Vec<u8> = Vec::with_capacity(ROUNDS);
-
- for _ in 0..ROUNDS {
- deltas_variable.push(rng.timer_stats(true) as u8);
- deltas_minimal.push(rng.timer_stats(false) as u8);
- }
-
- // Write out after the statistics collection loop, to not disturb the
- // test results.
- File::create("jitter_rng_var.bin")?.write(&deltas_variable)?;
- File::create("jitter_rng_min.bin")?.write(&deltas_minimal)?;
- Ok(())
-}
-```
-
-This will produce two files: `jitter_rng_var.bin` and `jitter_rng_min.bin`.
-Run the Entropy Estimation Suite in three configurations, as outlined below.
-Every run has two steps. One step to produce an estimation, another to
-validate the estimation.
-
-1. Estimate the expected amount of entropy that is at least available with
- each round of the entropy collector. This number should be greater than
- the amount estimated with `64 / test_timer()`.
- ```sh
- python noniid_main.py -v jitter_rng_var.bin 8
- restart.py -v jitter_rng_var.bin 8 <min-entropy>
- ```
-2. Estimate the expected amount of entropy that is available in the last 4
- bits of the timer delta after running noice sources. Note that a value of
- `3.70` is the minimum estimated entropy for true randomness.
- ```sh
- python noniid_main.py -v -u 4 jitter_rng_var.bin 4
- restart.py -v -u 4 jitter_rng_var.bin 4 <min-entropy>
- ```
-3. Estimate the expected amount of entropy that is available to the entropy
- collector if both noise sources only run their minimal number of times.
- This measures the absolute worst-case, and gives a lower bound for the
- available entropy.
- ```sh
- python noniid_main.py -v -u 4 jitter_rng_min.bin 4
- restart.py -v -u 4 jitter_rng_min.bin 4 <min-entropy>
- ```
-
-## License
-
-`rand_jitter` is distributed under the terms of both the MIT license and the
-Apache License (Version 2.0).
-
-See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT), and
-[COPYRIGHT](COPYRIGHT) for details.
diff --git a/rand/rand_jitter/benches/mod.rs b/rand/rand_jitter/benches/mod.rs
deleted file mode 100644
index bf7c8a2..0000000
--- a/rand/rand_jitter/benches/mod.rs
+++ /dev/null
@@ -1,17 +0,0 @@
-#![feature(test)]
-#![cfg(std)]
-
-use test::Bencher;
-use rand_jitter::rand_core::RngCore;
-
-#[bench]
-fn bench_add_two(b: &mut Bencher) {
- let mut rng = rand_jitter::JitterRng::new().unwrap();
- let mut buf = [0u8; 1024];
- b.iter(|| {
- rng.fill_bytes(&mut buf[..]);
- test::black_box(&buf);
- });
- b.bytes = buf.len() as u64;
-}
-
diff --git a/rand/rand_jitter/src/error.rs b/rand/rand_jitter/src/error.rs
deleted file mode 100644
index b54fffa..0000000
--- a/rand/rand_jitter/src/error.rs
+++ /dev/null
@@ -1,77 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013-2015 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-use rand_core::Error;
-use core::fmt;
-
-/// Base code for all `JitterRng` errors
-const ERROR_BASE: u32 = 0xAE53_0400;
-
-/// An error that can occur when [`JitterRng::test_timer`] fails.
-///
-/// All variants have a value of 0xAE530400 = 2924676096 plus a small
-/// increment (1 through 5).
-///
-/// [`JitterRng::test_timer`]: crate::JitterRng::test_timer
-#[derive(Debug, Clone, PartialEq, Eq)]
-#[repr(u32)]
-pub enum TimerError {
- /// No timer available.
- NoTimer = ERROR_BASE + 1,
- /// Timer too coarse to use as an entropy source.
- CoarseTimer = ERROR_BASE + 2,
- /// Timer is not monotonically increasing.
- NotMonotonic = ERROR_BASE + 3,
- /// Variations of deltas of time too small.
- TinyVariantions = ERROR_BASE + 4,
- /// Too many stuck results (indicating no added entropy).
- TooManyStuck = ERROR_BASE + 5,
- #[doc(hidden)]
- __Nonexhaustive,
-}
-
-impl TimerError {
- fn description(&self) -> &'static str {
- match *self {
- TimerError::NoTimer => "no timer available",
- TimerError::CoarseTimer => "coarse timer",
- TimerError::NotMonotonic => "timer not monotonic",
- TimerError::TinyVariantions => "time delta variations too small",
- TimerError::TooManyStuck => "too many stuck results",
- TimerError::__Nonexhaustive => unreachable!(),
- }
- }
-}
-
-impl fmt::Display for TimerError {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "{}", self.description())
- }
-}
-
-#[cfg(feature = "std")]
-impl ::std::error::Error for TimerError {
- fn description(&self) -> &str {
- self.description()
- }
-}
-
-impl From<TimerError> for Error {
- fn from(err: TimerError) -> Error {
- // Timer check is already quite permissive of failures so we don't
- // expect false-positive failures, i.e. any error is irrecoverable.
- #[cfg(feature = "std")] {
- Error::new(err)
- }
- #[cfg(not(feature = "std"))] {
- Error::from(core::num::NonZeroU32::new(err as u32).unwrap())
- }
- }
-}
-
diff --git a/rand/rand_jitter/src/lib.rs b/rand/rand_jitter/src/lib.rs
deleted file mode 100644
index 49c53e6..0000000
--- a/rand/rand_jitter/src/lib.rs
+++ /dev/null
@@ -1,750 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-//
-// Based on jitterentropy-library, http://www.chronox.de/jent.html.
-// Copyright Stephan Mueller <smueller@chronox.de>, 2014 - 2017.
-//
-// With permission from Stephan Mueller to relicense the Rust translation under
-// the MIT license.
-
-//! Non-physical true random number generator based on timing jitter.
-//!
-//! Note that this RNG is not suited for use cases where cryptographic security is
-//! required (also see this [discussion]).
-//!
-//! This is a true random number generator, as opposed to pseudo-random
-//! generators. Random numbers generated by `JitterRng` can be seen as fresh
-//! entropy. A consequence is that it is orders of magnitude slower than `OsRng`
-//! and PRNGs (about 10<sup>3</sup>..10<sup>6</sup> slower).
-//!
-//! There are very few situations where using this RNG is appropriate. Only very
-//! few applications require true entropy. A normal PRNG can be statistically
-//! indistinguishable, and a cryptographic PRNG should also be as impossible to
-//! predict.
-//!
-//! `JitterRng` can be used without the standard library, but not conveniently,
-//! you must provide a high-precision timer and carefully have to follow the
-//! instructions of [`JitterRng::new_with_timer`].
-//!
-//! This implementation is based on [Jitterentropy] version 2.1.0.
-//!
-//! Note: There is no accurate timer available on WASM platforms, to help
-//! prevent fingerprinting or timing side-channel attacks. Therefore
-//! [`JitterRng::new()`] is not available on WASM. It is also unavailable
-//! with disabled `std` feature.
-//!
-//! [Jitterentropy]: http://www.chronox.de/jent.html
-//! [discussion]: https://github.com/rust-random/rand/issues/699
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
- html_favicon_url = "https://www.rust-lang.org/favicon.ico",
- html_root_url = "https://rust-random.github.io/rand/")]
-
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-#![doc(test(attr(allow(unused_variables), deny(warnings))))]
-
-// Note: the C implementation of `Jitterentropy` relies on being compiled
-// without optimizations. This implementation goes through lengths to make the
-// compiler not optimize out code which does influence timing jitter, but is
-// technically dead code.
-#![no_std]
-#[cfg(feature = "std")]
-extern crate std;
-
-pub use rand_core;
-
-// Coming from https://crates.io/crates/doc-comment
-#[cfg(test)]
-macro_rules! doc_comment {
- ($x:expr) => {
- #[doc = $x]
- extern {}
- };
-}
-
-#[cfg(test)]
-doc_comment!(include_str!("../README.md"));
-
-#[allow(unused)]
-macro_rules! trace { ($($x:tt)*) => (
- #[cfg(feature = "log")] {
- log::trace!($($x)*)
- }
-) }
-#[allow(unused)]
-macro_rules! debug { ($($x:tt)*) => (
- #[cfg(feature = "log")] {
- log::debug!($($x)*)
- }
-) }
-#[allow(unused)]
-macro_rules! info { ($($x:tt)*) => (
- #[cfg(feature = "log")] {
- log::info!($($x)*)
- }
-) }
-#[allow(unused)]
-macro_rules! warn { ($($x:tt)*) => (
- #[cfg(feature = "log")] {
- log::warn!($($x)*)
- }
-) }
-#[allow(unused)]
-macro_rules! error { ($($x:tt)*) => (
- #[cfg(feature = "log")] {
- log::error!($($x)*)
- }
-) }
-
-#[cfg(feature = "std")]
-mod platform;
-mod error;
-
-use rand_core::{RngCore, Error, impls};
-pub use crate::error::TimerError;
-
-use core::{fmt, mem, ptr};
-#[cfg(feature = "std")]
-use std::sync::atomic::{AtomicUsize, Ordering};
-
-const MEMORY_BLOCKS: usize = 64;
-const MEMORY_BLOCKSIZE: usize = 32;
-const MEMORY_SIZE: usize = MEMORY_BLOCKS * MEMORY_BLOCKSIZE;
-
-/// A true random number generator based on jitter in the CPU execution time,
-/// and jitter in memory access time.
-///
-/// Note that this RNG is not suitable for use cases where cryptographic
-/// security is required.
-pub struct JitterRng {
- data: u64, // Actual random number
- // Number of rounds to run the entropy collector per 64 bits
- rounds: u8,
- // Timer used by `measure_jitter`
- timer: fn() -> u64,
- // Memory for the Memory Access noise source
- mem_prev_index: u16,
- // Make `next_u32` not waste 32 bits
- data_half_used: bool,
-}
-
-// Note: `JitterRng` maintains a small 64-bit entropy pool. With every
-// `generate` 64 new bits should be integrated in the pool. If a round of
-// `generate` were to collect less than the expected 64 bit, then the returned
-// value, and the new state of the entropy pool, would be in some way related to
-// the initial state. It is therefore better if the initial state of the entropy
-// pool is different on each call to `generate`. This has a few implications:
-// - `generate` should be called once before using `JitterRng` to produce the
-// first usable value (this is done by default in `new`);
-// - We do not zero the entropy pool after generating a result. The reference
-// implementation also does not support zeroing, but recommends generating a
-// new value without using it if you want to protect a previously generated
-// 'secret' value from someone inspecting the memory;
-// - Implementing `Clone` seems acceptable, as it would not cause the systematic
-// bias a constant might cause. Only instead of one value that could be
-// potentially related to the same initial state, there are now two.
-
-// Entropy collector state.
-// These values are not necessary to preserve across runs.
-struct EcState {
- // Previous time stamp to determine the timer delta
- prev_time: u64,
- // Deltas used for the stuck test
- last_delta: i32,
- last_delta2: i32,
- // Memory for the Memory Access noise source
- mem: [u8; MEMORY_SIZE],
-}
-
-impl EcState {
- // Stuck test by checking the:
- // - 1st derivation of the jitter measurement (time delta)
- // - 2nd derivation of the jitter measurement (delta of time deltas)
- // - 3rd derivation of the jitter measurement (delta of delta of time
- // deltas)
- //
- // All values must always be non-zero.
- // This test is a heuristic to see whether the last measurement holds
- // entropy.
- fn stuck(&mut self, current_delta: i32) -> bool {
- let delta2 = self.last_delta - current_delta;
- let delta3 = delta2 - self.last_delta2;
-
- self.last_delta = current_delta;
- self.last_delta2 = delta2;
-
- current_delta == 0 || delta2 == 0 || delta3 == 0
- }
-}
-
-// Custom Debug implementation that does not expose the internal state
-impl fmt::Debug for JitterRng {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "JitterRng {{}}")
- }
-}
-
-impl Clone for JitterRng {
- fn clone(&self) -> JitterRng {
- JitterRng {
- data: self.data,
- rounds: self.rounds,
- timer: self.timer,
- mem_prev_index: self.mem_prev_index,
- // The 32 bits that may still be unused from the previous round are
- // for the original to use, not for the clone.
- data_half_used: false,
- }
- }
-}
-
-// Initialise to zero; must be positive
-#[cfg(all(feature = "std", not(target_arch = "wasm32")))]
-static JITTER_ROUNDS: AtomicUsize = AtomicUsize::new(0);
-
-impl JitterRng {
- /// Create a new `JitterRng`. Makes use of `std::time` for a timer, or a
- /// platform-specific function with higher accuracy if necessary and
- /// available.
- ///
- /// During initialization CPU execution timing jitter is measured a few
- /// hundred times. If this does not pass basic quality tests, an error is
- /// returned. The test result is cached to make subsequent calls faster.
- #[cfg(all(feature = "std", not(target_arch = "wasm32")))]
- pub fn new() -> Result<JitterRng, TimerError> {
- if cfg!(target_arch = "wasm32") {
- return Err(TimerError::NoTimer);
- }
- let mut state = JitterRng::new_with_timer(platform::get_nstime);
- let mut rounds = JITTER_ROUNDS.load(Ordering::Relaxed) as u8;
- if rounds == 0 {
- // No result yet: run test.
- // This allows the timer test to run multiple times; we don't care.
- rounds = state.test_timer()?;
- JITTER_ROUNDS.store(rounds as usize, Ordering::Relaxed);
- info!("JitterRng: using {} rounds per u64 output", rounds);
- }
- state.set_rounds(rounds);
-
- // Fill `data` with a non-zero value.
- state.gen_entropy();
- Ok(state)
- }
-
- /// Create a new `JitterRng`.
- /// A custom timer can be supplied, making it possible to use `JitterRng` in
- /// `no_std` environments.
- ///
- /// The timer must have nanosecond precision.
- ///
- /// This method is more low-level than `new()`. It is the responsibility of
- /// the caller to run [`test_timer`] before using any numbers generated with
- /// `JitterRng`, and optionally call [`set_rounds`]. Also it is important to
- /// consume at least one `u64` before using the first result to initialize
- /// the entropy collection pool.
- ///
- /// # Example
- ///
- /// ```
- /// # use rand_jitter::rand_core::{RngCore, Error};
- /// use rand_jitter::JitterRng;
- ///
- /// # fn try_inner() -> Result<(), Error> {
- /// fn get_nstime() -> u64 {
- /// use std::time::{SystemTime, UNIX_EPOCH};
- ///
- /// let dur = SystemTime::now().duration_since(UNIX_EPOCH).unwrap();
- /// // The correct way to calculate the current time is
- /// // `dur.as_secs() * 1_000_000_000 + dur.subsec_nanos() as u64`
- /// // But this is faster, and the difference in terms of entropy is
- /// // negligible (log2(10^9) == 29.9).
- /// dur.as_secs() << 30 | dur.subsec_nanos() as u64
- /// }
- ///
- /// let mut rng = JitterRng::new_with_timer(get_nstime);
- /// let rounds = rng.test_timer()?;
- /// rng.set_rounds(rounds); // optional
- /// let _ = rng.next_u64();
- ///
- /// // Ready for use
- /// let v: u64 = rng.next_u64();
- /// # Ok(())
- /// # }
- ///
- /// # let _ = try_inner();
- /// ```
- ///
- /// [`test_timer`]: JitterRng::test_timer
- /// [`set_rounds`]: JitterRng::set_rounds
- pub fn new_with_timer(timer: fn() -> u64) -> JitterRng {
- JitterRng {
- data: 0,
- rounds: 64,
- timer,
- mem_prev_index: 0,
- data_half_used: false,
- }
- }
-
- /// Configures how many rounds are used to generate each 64-bit value.
- /// This must be greater than zero, and has a big impact on performance
- /// and output quality.
- ///
- /// [`new_with_timer`] conservatively uses 64 rounds, but often less rounds
- /// can be used. The `test_timer()` function returns the minimum number of
- /// rounds required for full strength (platform dependent), so one may use
- /// `rng.set_rounds(rng.test_timer()?);` or cache the value.
- ///
- /// [`new_with_timer`]: JitterRng::new_with_timer
- pub fn set_rounds(&mut self, rounds: u8) {
- assert!(rounds > 0);
- self.rounds = rounds;
- }
-
- // Calculate a random loop count used for the next round of an entropy
- // collection, based on bits from a fresh value from the timer.
- //
- // The timer is folded to produce a number that contains at most `n_bits`
- // bits.
- //
- // Note: A constant should be added to the resulting random loop count to
- // prevent loops that run 0 times.
- #[inline(never)]
- fn random_loop_cnt(&mut self, n_bits: u32) -> u32 {
- let mut rounds = 0;
-
- let mut time = (self.timer)();
- // Mix with the current state of the random number balance the random
- // loop counter a bit more.
- time ^= self.data;
-
- // We fold the time value as much as possible to ensure that as many
- // bits of the time stamp are included as possible.
- let folds = (64 + n_bits - 1) / n_bits;
- let mask = (1 << n_bits) - 1;
- for _ in 0..folds {
- rounds ^= time & mask;
- time >>= n_bits;
- }
-
- rounds as u32
- }
-
- // CPU jitter noise source
- // Noise source based on the CPU execution time jitter
- //
- // This function injects the individual bits of the time value into the
- // entropy pool using an LFSR.
- //
- // The code is deliberately inefficient with respect to the bit shifting.
- // This function not only acts as folding operation, but this function's
- // execution is used to measure the CPU execution time jitter. Any change to
- // the loop in this function implies that careful retesting must be done.
- #[inline(never)]
- fn lfsr_time(&mut self, time: u64, var_rounds: bool) {
- fn lfsr(mut data: u64, time: u64) -> u64{
- for i in 1..65 {
- let mut tmp = time << (64 - i);
- tmp >>= 64 - 1;
-
- // Fibonacci LSFR with polynomial of
- // x^64 + x^61 + x^56 + x^31 + x^28 + x^23 + 1 which is
- // primitive according to
- // http://poincare.matf.bg.ac.rs/~ezivkovm/publications/primpol1.pdf
- // (the shift values are the polynomial values minus one
- // due to counting bits from 0 to 63). As the current
- // position is always the LSB, the polynomial only needs
- // to shift data in from the left without wrap.
- data ^= tmp;
- data ^= (data >> 63) & 1;
- data ^= (data >> 60) & 1;
- data ^= (data >> 55) & 1;
- data ^= (data >> 30) & 1;
- data ^= (data >> 27) & 1;
- data ^= (data >> 22) & 1;
- data = data.rotate_left(1);
- }
- data
- }
-
- // Note: in the reference implementation only the last round effects
- // `self.data`, all the other results are ignored. To make sure the
- // other rounds are not optimised out, we first run all but the last
- // round on a throw-away value instead of the real `self.data`.
- let mut lfsr_loop_cnt = 0;
- if var_rounds { lfsr_loop_cnt = self.random_loop_cnt(4) };
-
- let mut throw_away: u64 = 0;
- for _ in 0..lfsr_loop_cnt {
- throw_away = lfsr(throw_away, time);
- }
- black_box(throw_away);
-
- self.data = lfsr(self.data, time);
- }
-
- // Memory Access noise source
- // This is a noise source based on variations in memory access times
- //
- // This function performs memory accesses which will add to the timing
- // variations due to an unknown amount of CPU wait states that need to be
- // added when accessing memory. The memory size should be larger than the L1
- // caches as outlined in the documentation and the associated testing.
- //
- // The L1 cache has a very high bandwidth, albeit its access rate is usually
- // slower than accessing CPU registers. Therefore, L1 accesses only add
- // minimal variations as the CPU has hardly to wait. Starting with L2,
- // significant variations are added because L2 typically does not belong to
- // the CPU any more and therefore a wider range of CPU wait states is
- // necessary for accesses. L3 and real memory accesses have even a wider
- // range of wait states. However, to reliably access either L3 or memory,
- // the `self.mem` memory must be quite large which is usually not desirable.
- #[inline(never)]
- fn memaccess(&mut self, mem: &mut [u8; MEMORY_SIZE], var_rounds: bool) {
- let mut acc_loop_cnt = 128;
- if var_rounds { acc_loop_cnt += self.random_loop_cnt(4) };
-
- let mut index = self.mem_prev_index as usize;
- for _ in 0..acc_loop_cnt {
- // Addition of memblocksize - 1 to index with wrap around logic to
- // ensure that every memory location is hit evenly.
- // The modulus also allows the compiler to remove the indexing
- // bounds check.
- index = (index + MEMORY_BLOCKSIZE - 1) % MEMORY_SIZE;
-
- // memory access: just add 1 to one byte
- // memory access implies read from and write to memory location
- mem[index] = mem[index].wrapping_add(1);
- }
- self.mem_prev_index = index as u16;
- }
-
- // This is the heart of the entropy generation: calculate time deltas and
- // use the CPU jitter in the time deltas. The jitter is injected into the
- // entropy pool.
- //
- // Ensure that `ec.prev_time` is primed before using the output of this
- // function. This can be done by calling this function and not using its
- // result.
- fn measure_jitter(&mut self, ec: &mut EcState) -> Option<()> {
- // Invoke one noise source before time measurement to add variations
- self.memaccess(&mut ec.mem, true);
-
- // Get time stamp and calculate time delta to previous
- // invocation to measure the timing variations
- let time = (self.timer)();
- // Note: wrapping_sub combined with a cast to `i64` generates a correct
- // delta, even in the unlikely case this is a timer that is not strictly
- // monotonic.
- let current_delta = time.wrapping_sub(ec.prev_time) as i64 as i32;
- ec.prev_time = time;
-
- // Call the next noise source which also injects the data
- self.lfsr_time(current_delta as u64, true);
-
- // Check whether we have a stuck measurement (i.e. does the last
- // measurement holds entropy?).
- if ec.stuck(current_delta) { return None };
-
- // Rotate the data buffer by a prime number (any odd number would
- // do) to ensure that every bit position of the input time stamp
- // has an even chance of being merged with a bit position in the
- // entropy pool. We do not use one here as the adjacent bits in
- // successive time deltas may have some form of dependency. The
- // chosen value of 7 implies that the low 7 bits of the next
- // time delta value is concatenated with the current time delta.
- self.data = self.data.rotate_left(7);
-
- Some(())
- }
-
- // Shuffle the pool a bit by mixing some value with a bijective function
- // (XOR) into the pool.
- //
- // The function generates a mixer value that depends on the bits set and
- // the location of the set bits in the random number generated by the
- // entropy source. Therefore, based on the generated random number, this
- // mixer value can have 2^64 different values. That mixer value is
- // initialized with the first two SHA-1 constants. After obtaining the
- // mixer value, it is XORed into the random number.
- //
- // The mixer value is not assumed to contain any entropy. But due to the
- // XOR operation, it can also not destroy any entropy present in the
- // entropy pool.
- #[inline(never)]
- fn stir_pool(&mut self) {
- // This constant is derived from the first two 32 bit initialization
- // vectors of SHA-1 as defined in FIPS 180-4 section 5.3.1
- // The order does not really matter as we do not rely on the specific
- // numbers. We just pick the SHA-1 constants as they have a good mix of
- // bit set and unset.
- const CONSTANT: u64 = 0x67452301efcdab89;
-
- // The start value of the mixer variable is derived from the third
- // and fourth 32 bit initialization vector of SHA-1 as defined in
- // FIPS 180-4 section 5.3.1
- let mut mixer = 0x98badcfe10325476;
-
- // This is a constant time function to prevent leaking timing
- // information about the random number.
- // The normal code is:
- // ```
- // for i in 0..64 {
- // if ((self.data >> i) & 1) == 1 { mixer ^= CONSTANT; }
- // }
- // ```
- // This is a bit fragile, as LLVM really wants to use branches here, and
- // we rely on it to not recognise the opportunity.
- for i in 0..64 {
- let apply = (self.data >> i) & 1;
- let mask = !apply.wrapping_sub(1);
- mixer ^= CONSTANT & mask;
- mixer = mixer.rotate_left(1);
- }
-
- self.data ^= mixer;
- }
-
- fn gen_entropy(&mut self) -> u64 {
- trace!("JitterRng: collecting entropy");
-
- // Prime `ec.prev_time`, and run the noice sources to make sure the
- // first loop round collects the expected entropy.
- let mut ec = EcState {
- prev_time: (self.timer)(),
- last_delta: 0,
- last_delta2: 0,
- mem: [0; MEMORY_SIZE],
- };
- let _ = self.measure_jitter(&mut ec);
-
- for _ in 0..self.rounds {
- // If a stuck measurement is received, repeat measurement
- // Note: we do not guard against an infinite loop, that would mean
- // the timer suddenly became broken.
- while self.measure_jitter(&mut ec).is_none() {}
- }
-
- // Do a single read from `self.mem` to make sure the Memory Access noise
- // source is not optimised out.
- black_box(ec.mem[0]);
-
- self.stir_pool();
- self.data
- }
-
- /// Basic quality tests on the timer, by measuring CPU timing jitter a few
- /// hundred times.
- ///
- /// If successful, this will return the estimated number of rounds necessary
- /// to collect 64 bits of entropy. Otherwise a [`TimerError`] with the cause
- /// of the failure will be returned.
- pub fn test_timer(&mut self) -> Result<u8, TimerError> {
- debug!("JitterRng: testing timer ...");
- // We could add a check for system capabilities such as `clock_getres`
- // or check for `CONFIG_X86_TSC`, but it does not make much sense as the
- // following sanity checks verify that we have a high-resolution timer.
-
- let mut delta_sum = 0;
- let mut old_delta = 0;
-
- let mut time_backwards = 0;
- let mut count_mod = 0;
- let mut count_stuck = 0;
-
- let mut ec = EcState {
- prev_time: (self.timer)(),
- last_delta: 0,
- last_delta2: 0,
- mem: [0; MEMORY_SIZE],
- };
-
- // TESTLOOPCOUNT needs some loops to identify edge systems.
- // 100 is definitely too little.
- const TESTLOOPCOUNT: u64 = 300;
- const CLEARCACHE: u64 = 100;
-
- for i in 0..(CLEARCACHE + TESTLOOPCOUNT) {
- // Measure time delta of core entropy collection logic
- let time = (self.timer)();
- self.memaccess(&mut ec.mem, true);
- self.lfsr_time(time, true);
- let time2 = (self.timer)();
-
- // Test whether timer works
- if time == 0 || time2 == 0 {
- return Err(TimerError::NoTimer);
- }
- let delta = time2.wrapping_sub(time) as i64 as i32;
-
- // Test whether timer is fine grained enough to provide delta even
- // when called shortly after each other -- this implies that we also
- // have a high resolution timer
- if delta == 0 {
- return Err(TimerError::CoarseTimer);
- }
-
- // Up to here we did not modify any variable that will be
- // evaluated later, but we already performed some work. Thus we
- // already have had an impact on the caches, branch prediction,
- // etc. with the goal to clear it to get the worst case
- // measurements.
- if i < CLEARCACHE { continue; }
-
- if ec.stuck(delta) { count_stuck += 1; }
-
- // Test whether we have an increasing timer.
- if !(time2 > time) { time_backwards += 1; }
-
- // Count the number of times the counter increases in steps of 100ns
- // or greater.
- if (delta % 100) == 0 { count_mod += 1; }
-
- // Ensure that we have a varying delta timer which is necessary for
- // the calculation of entropy -- perform this check only after the
- // first loop is executed as we need to prime the old_delta value
- delta_sum += (delta - old_delta).abs() as u64;
- old_delta = delta;
- }
-
- // Do a single read from `self.mem` to make sure the Memory Access noise
- // source is not optimised out.
- black_box(ec.mem[0]);
-
- // We allow the time to run backwards for up to three times.
- // This can happen if the clock is being adjusted by NTP operations.
- // If such an operation just happens to interfere with our test, it
- // should not fail. The value of 3 should cover the NTP case being
- // performed during our test run.
- if time_backwards > 3 {
- return Err(TimerError::NotMonotonic);
- }
-
- // Test that the available amount of entropy per round does not get to
- // low. We expect 1 bit of entropy per round as a reasonable minimum
- // (although less is possible, it means the collector loop has to run
- // much more often).
- // `assert!(delta_average >= log2(1))`
- // `assert!(delta_sum / TESTLOOPCOUNT >= 1)`
- // `assert!(delta_sum >= TESTLOOPCOUNT)`
- if delta_sum < TESTLOOPCOUNT {
- return Err(TimerError::TinyVariantions);
- }
-
- // Ensure that we have variations in the time stamp below 100 for at
- // least 10% of all checks -- on some platforms, the counter increments
- // in multiples of 100, but not always
- if count_mod > (TESTLOOPCOUNT * 9 / 10) {
- return Err(TimerError::CoarseTimer);
- }
-
- // If we have more than 90% stuck results, then this Jitter RNG is
- // likely to not work well.
- if count_stuck > (TESTLOOPCOUNT * 9 / 10) {
- return Err(TimerError::TooManyStuck);
- }
-
- // Estimate the number of `measure_jitter` rounds necessary for 64 bits
- // of entropy.
- //
- // We don't try very hard to come up with a good estimate of the
- // available bits of entropy per round here for two reasons:
- // 1. Simple estimates of the available bits (like Shannon entropy) are
- // too optimistic.
- // 2. Unless we want to waste a lot of time during intialization, there
- // only a small number of samples are available.
- //
- // Therefore we use a very simple and conservative estimate:
- // `let bits_of_entropy = log2(delta_average) / 2`.
- //
- // The number of rounds `measure_jitter` should run to collect 64 bits
- // of entropy is `64 / bits_of_entropy`.
- let delta_average = delta_sum / TESTLOOPCOUNT;
-
- if delta_average >= 16 {
- let log2 = 64 - delta_average.leading_zeros();
- // Do something similar to roundup(64/(log2/2)):
- Ok( ((64u32 * 2 + log2 - 1) / log2) as u8)
- } else {
- // For values < 16 the rounding error becomes too large, use a
- // lookup table.
- // Values 0 and 1 are invalid, and filtered out by the
- // `delta_sum < TESTLOOPCOUNT` test above.
- let log2_lookup = [0, 0, 128, 81, 64, 56, 50, 46,
- 43, 41, 39, 38, 36, 35, 34, 33];
- Ok(log2_lookup[delta_average as usize])
- }
- }
-
- /// Statistical test: return the timer delta of one normal run of the
- /// `JitterRng` entropy collector.
- ///
- /// Setting `var_rounds` to `true` will execute the memory access and the
- /// CPU jitter noice sources a variable amount of times (just like a real
- /// `JitterRng` round).
- ///
- /// Setting `var_rounds` to `false` will execute the noice sources the
- /// minimal number of times. This can be used to measure the minimum amount
- /// of entropy one round of the entropy collector can collect in the worst
- /// case.
- ///
- /// See this crate's README on how to use `timer_stats` to test the quality
- /// of `JitterRng`.
- pub fn timer_stats(&mut self, var_rounds: bool) -> i64 {
- let mut mem = [0; MEMORY_SIZE];
-
- let time = (self.timer)();
- self.memaccess(&mut mem, var_rounds);
- self.lfsr_time(time, var_rounds);
- let time2 = (self.timer)();
- time2.wrapping_sub(time) as i64
- }
-}
-
-// A function that is opaque to the optimizer to assist in avoiding dead-code
-// elimination. Taken from `bencher`.
-fn black_box<T>(dummy: T) -> T {
- unsafe {
- let ret = ptr::read_volatile(&dummy);
- mem::forget(dummy);
- ret
- }
-}
-
-impl RngCore for JitterRng {
- fn next_u32(&mut self) -> u32 {
- // We want to use both parts of the generated entropy
- if self.data_half_used {
- self.data_half_used = false;
- (self.data >> 32) as u32
- } else {
- self.data = self.next_u64();
- self.data_half_used = true;
- self.data as u32
- }
- }
-
- fn next_u64(&mut self) -> u64 {
- self.data_half_used = false;
- self.gen_entropy()
- }
-
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- // Fill using `next_u32`. This is faster for filling small slices (four
- // bytes or less), while the overhead is negligible.
- //
- // This is done especially for wrappers that implement `next_u32`
- // themselves via `fill_bytes`.
- impls::fill_bytes_via_next(self, dest)
- }
-
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- Ok(self.fill_bytes(dest))
- }
-}
diff --git a/rand/rand_jitter/src/platform.rs b/rand/rand_jitter/src/platform.rs
deleted file mode 100644
index 8e3d0fb..0000000
--- a/rand/rand_jitter/src/platform.rs
+++ /dev/null
@@ -1,44 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013-2015 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(not(any(target_os = "macos", target_os = "ios", target_os = "windows")))]
-pub fn get_nstime() -> u64 {
- use std::time::{SystemTime, UNIX_EPOCH};
-
- let dur = SystemTime::now().duration_since(UNIX_EPOCH).unwrap();
- // The correct way to calculate the current time is
- // `dur.as_secs() * 1_000_000_000 + dur.subsec_nanos() as u64`
- // But this is faster, and the difference in terms of entropy is
- // negligible (log2(10^9) == 29.9).
- dur.as_secs() << 30 | dur.subsec_nanos() as u64
-}
-
-#[cfg(any(target_os = "macos", target_os = "ios"))]
-pub fn get_nstime() -> u64 {
- use libc;
-
- // On Mac OS and iOS std::time::SystemTime only has 1000ns resolution.
- // We use `mach_absolute_time` instead. This provides a CPU dependent
- // unit, to get real nanoseconds the result should by multiplied by
- // numer/denom from `mach_timebase_info`.
- // But we are not interested in the exact nanoseconds, just entropy. So
- // we use the raw result.
- unsafe { libc::mach_absolute_time() }
-}
-
-#[cfg(target_os = "windows")]
-pub fn get_nstime() -> u64 {
- use winapi;
-
- unsafe {
- let mut t = super::mem::zeroed();
- winapi::um::profileapi::QueryPerformanceCounter(&mut t);
- *t.QuadPart() as u64
- }
-}
diff --git a/rand/rand_jitter/tests/mod.rs b/rand/rand_jitter/tests/mod.rs
deleted file mode 100644
index 961dc27..0000000
--- a/rand/rand_jitter/tests/mod.rs
+++ /dev/null
@@ -1,28 +0,0 @@
-use rand_jitter::JitterRng;
-#[cfg(feature = "std")]
-use rand_core::RngCore;
-
-#[cfg(feature = "std")]
-#[test]
-fn test_jitter_init() {
- // Because this is a debug build, measurements here are not representive
- // of the final release build.
- // Don't fail this test if initializing `JitterRng` fails because of a
- // bad timer (the timer from the standard library may not have enough
- // accuracy on all platforms).
- match JitterRng::new() {
- Ok(ref mut rng) => {
- // false positives are possible, but extremely unlikely
- assert!(rng.next_u32() | rng.next_u32() != 0);
- },
- Err(_) => {},
- }
-}
-
-#[test]
-fn test_jitter_bad_timer() {
- fn bad_timer() -> u64 { 0 }
- let mut rng = JitterRng::new_with_timer(bad_timer);
- assert!(rng.test_timer().is_err());
-}
-
diff --git a/rand/rand_os/CHANGELOG.md b/rand/rand_os/CHANGELOG.md
deleted file mode 100644
index b0c6549..0000000
--- a/rand/rand_os/CHANGELOG.md
+++ /dev/null
@@ -1,35 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.2.2] - 2019-09-02
-### Changed
-- `OsRng` added to `rand_core`, rendering this crate deprecated (#863)
-
-## [0.2.1] - 2019-08-08
-### Fixed
-- Fix `no_std` support.
-
-## [0.2.0] - 2019-06-06
-### Changed
-- Minimum Supported Rust Version has changed to 1.32.
-- Replaced implementation with a backwards-compatible shim around
-[getrandom](https://crates.io/crates/getrandom).
-
-## [0.1.3] - 2019-03-05
-### Fixed
-- Fix support for Illumos (#730)
-- Fix deprecation warnings from atomic init (#739)
-
-## [0.1.2] - 2019-01-28
-### Changed
-- Fuchsia: Replaced fuchsia-zircon with fuchsia-cprng
-
-## [0.1.1] - 2019-01-08
-### Added
-- Add support for x86_64-fortanix-unknown-sgx target (#670)
-
-## [0.1.0] - 2019-01-04
-Initial release.
diff --git a/rand/rand_os/COPYRIGHT b/rand/rand_os/COPYRIGHT
deleted file mode 100644
index 468d907..0000000
--- a/rand/rand_os/COPYRIGHT
+++ /dev/null
@@ -1,12 +0,0 @@
-Copyrights in the Rand project are retained by their contributors. No
-copyright assignment is required to contribute to the Rand project.
-
-For full authorship information, see the version control history.
-
-Except as otherwise noted (below and/or in individual files), Rand is
-licensed under the Apache License, Version 2.0 <LICENSE-APACHE> or
-<http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-<LICENSE-MIT> or <http://opensource.org/licenses/MIT>, at your option.
-
-The Rand project includes code from the Rust project
-published under these same licenses.
diff --git a/rand/rand_os/Cargo.toml b/rand/rand_os/Cargo.toml
deleted file mode 100644
index c8010e2..0000000
--- a/rand/rand_os/Cargo.toml
+++ /dev/null
@@ -1,26 +0,0 @@
-[package]
-name = "rand_os"
-version = "0.2.2"
-authors = ["The Rand Project Developers"]
-license = "MIT OR Apache-2.0"
-readme = "README.md"
-repository = "https://github.com/rust-random/rand"
-documentation = "https://docs.rs/rand_os"
-homepage = "https://crates.io/crates/rand_os"
-description = "OS backed Random Number Generator"
-keywords = ["random", "rng", "os"]
-edition = "2018"
-
-[badges]
-travis-ci = { repository = "rust-random/rand" }
-appveyor = { repository = "rust-random/rand" }
-
-[features]
-log = ["getrandom/log"]
-# re-export optional WASM dependencies to avoid breakage:
-wasm-bindgen = ["getrandom/wasm-bindgen"]
-stdweb = ["getrandom/stdweb"]
-
-[dependencies]
-rand_core = { path = "../rand_core", version = "0.5", features = ["getrandom"] }
-getrandom = "0.1.1"
diff --git a/rand/rand_os/LICENSE-APACHE b/rand/rand_os/LICENSE-APACHE
deleted file mode 100644
index 17d7468..0000000
--- a/rand/rand_os/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
- Apache License
- Version 2.0, January 2004
- https://www.apache.org/licenses/
-
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-
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-
-Copyright [yyyy] [name of copyright owner]
-
-Licensed 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
-
- https://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.
diff --git a/rand/rand_os/LICENSE-MIT b/rand/rand_os/LICENSE-MIT
deleted file mode 100644
index d93b5ba..0000000
--- a/rand/rand_os/LICENSE-MIT
+++ /dev/null
@@ -1,26 +0,0 @@
-Copyright 2018 Developers of the Rand project
-Copyright (c) 2014 The Rust Project Developers
-
-Permission is hereby granted, free of charge, to any
-person obtaining a copy of this software and associated
-documentation files (the "Software"), to deal in the
-Software without restriction, including without
-limitation the rights to use, copy, modify, merge,
-publish, distribute, sublicense, and/or sell copies of
-the Software, and to permit persons to whom the Software
-is furnished to do so, subject to the following
-conditions:
-
-The above copyright notice and this permission notice
-shall be included in all copies or substantial portions
-of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF
-ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED
-TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
-PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
-SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
-IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-DEALINGS IN THE SOFTWARE.
diff --git a/rand/rand_os/README.md b/rand/rand_os/README.md
deleted file mode 100644
index 7b68b35..0000000
--- a/rand/rand_os/README.md
+++ /dev/null
@@ -1,35 +0,0 @@
-# rand_os
-
-[](https://travis-ci.org/rust-random/rand)
-[](https://ci.appveyor.com/project/rust-random/rand)
-[](https://crates.io/crates/rand_os)
-[](https://rust-random.github.io/book/)
-[](https://rust-random.github.io/rand/rand_os)
-[](https://docs.rs/rand_os)
-[](https://github.com/rust-random/rand#rust-version-requirements)
-
-A random number generator that retrieves randomness straight from the
-operating system.
-
-**This crate is deprecated:** `OsRng` is available in `rand_core` since version 0.5.1.
-
-This crate provides `OsRng` as a shim around
-[getrandom](https://crates.io/crates/getrandom)
-implementing `RngCore` from [rand_core](https://crates.io/crates/rand_core).
-
-Note: the `rand` crate provides an equivalent `OsRng`; the two implementations
-are equivalent, though distinct types.
-
-Links:
-
-- [API documentation (master)](https://rust-random.github.io/rand/rand_os)
-- [API documentation (docs.rs)](https://docs.rs/rand_os)
-- [Changelog](https://github.com/rust-random/rand/blob/master/rand_os/CHANGELOG.md)
-
-## License
-
-`rand_os` is distributed under the terms of both the MIT license and the
-Apache License (Version 2.0).
-
-See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT), and
-[COPYRIGHT](COPYRIGHT) for details.
diff --git a/rand/rand_os/src/lib.rs b/rand/rand_os/src/lib.rs
deleted file mode 100644
index abfdf79..0000000
--- a/rand/rand_os/src/lib.rs
+++ /dev/null
@@ -1,106 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013-2015 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Interface to the random number generator of the operating system.
-// Note: keep this code in sync with the rand::rngs::os module!
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
- html_favicon_url = "https://www.rust-lang.org/favicon.ico",
- html_root_url = "https://rust-random.github.io/rand/")]
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-#![doc(test(attr(allow(unused_variables), deny(warnings))))]
-
-#![no_std] // but see getrandom crate
-
-#![deprecated(since="0.2.2", note="OsRng is now provided by rand_core and rand")]
-
-pub use rand_core; // re-export
-
-use getrandom::getrandom;
-use rand_core::{CryptoRng, RngCore, Error, impls};
-
-/// A random number generator that retrieves randomness from from the
-/// operating system.
-///
-/// This is a zero-sized struct. It can be freely constructed with `OsRng`.
-///
-/// The implementation is provided by the [getrandom] crate. Refer to
-/// [getrandom] documentation for details.
-///
-/// # Blocking and error handling
-///
-/// It is possible that when used during early boot the first call to `OsRng`
-/// will block until the system's RNG is initialised. It is also possible
-/// (though highly unlikely) for `OsRng` to fail on some platforms, most
-/// likely due to system mis-configuration.
-///
-/// After the first successful call, it is highly unlikely that failures or
-/// significant delays will occur (although performance should be expected to
-/// be much slower than a user-space PRNG).
-///
-/// # Usage example
-/// ```
-/// #![allow(deprecated)]
-/// use rand_os::rand_core::RngCore;
-/// use rand_os::OsRng;
-///
-/// let mut key = [0u8; 16];
-/// OsRng.fill_bytes(&mut key);
-/// let random_u64 = OsRng.next_u64();
-/// ```
-///
-/// [getrandom]: https://crates.io/crates/getrandom
-#[derive(Clone, Copy, Debug, Default)]
-pub struct OsRng;
-
-impl OsRng {
- /// Create a new `OsRng`.
- #[deprecated(since="0.2.0", note="replace OsRng::new().unwrap() with just OsRng")]
- pub fn new() -> Result<OsRng, Error> {
- Ok(OsRng)
- }
-}
-
-impl CryptoRng for OsRng {}
-
-impl RngCore for OsRng {
- fn next_u32(&mut self) -> u32 {
- impls::next_u32_via_fill(self)
- }
-
- fn next_u64(&mut self) -> u64 {
- impls::next_u64_via_fill(self)
- }
-
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- if let Err(e) = self.try_fill_bytes(dest) {
- panic!("Error: {}", e);
- }
- }
-
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- getrandom(dest)?;
- Ok(())
- }
-}
-
-#[test]
-fn test_os_rng() {
- let x = OsRng.next_u64();
- let y = OsRng.next_u64();
- assert!(x != 0);
- assert!(x != y);
-}
-
-#[test]
-fn test_construction() {
- let mut rng = OsRng::default();
- assert!(rng.next_u64() != 0);
-}
diff --git a/rand/rand_pcg/CHANGELOG.md b/rand/rand_pcg/CHANGELOG.md
deleted file mode 100644
index a9b82fd..0000000
--- a/rand/rand_pcg/CHANGELOG.md
+++ /dev/null
@@ -1,24 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.2.0] - 2019-06-12
-- Add `Lcg128Xsl64` aka `Pcg64`
-- Bump minor crate version since rand_core bump is a breaking change
-- Switch to Edition 2018
-
-## [0.1.2] - 2019-02-23
-- require `bincode` 1.1.2 for i128 auto-detection
-- make `bincode` a dev-dependency again #663
-- clean up tests and Serde support
-
-## [0.1.1] - 2018-10-04
-- make `bincode` an explicit dependency when using Serde
-
-## [0.1.0] - 2018-10-04
-Initial release, including:
-
-- `Lcg64Xsh32` aka `Pcg32`
-- `Mcg128Xsl64` aka `Pcg64Mcg`
diff --git a/rand/rand_pcg/COPYRIGHT b/rand/rand_pcg/COPYRIGHT
deleted file mode 100644
index 468d907..0000000
--- a/rand/rand_pcg/COPYRIGHT
+++ /dev/null
@@ -1,12 +0,0 @@
-Copyrights in the Rand project are retained by their contributors. No
-copyright assignment is required to contribute to the Rand project.
-
-For full authorship information, see the version control history.
-
-Except as otherwise noted (below and/or in individual files), Rand is
-licensed under the Apache License, Version 2.0 <LICENSE-APACHE> or
-<http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-<LICENSE-MIT> or <http://opensource.org/licenses/MIT>, at your option.
-
-The Rand project includes code from the Rust project
-published under these same licenses.
diff --git a/rand/rand_pcg/Cargo.toml b/rand/rand_pcg/Cargo.toml
deleted file mode 100644
index e2aa157..0000000
--- a/rand/rand_pcg/Cargo.toml
+++ /dev/null
@@ -1,32 +0,0 @@
-[package]
-name = "rand_pcg"
-version = "0.2.0"
-authors = ["The Rand Project Developers"]
-license = "MIT OR Apache-2.0"
-readme = "README.md"
-repository = "https://github.com/rust-random/rand"
-documentation = "https://rust-random.github.io/rand/rand_pcg/"
-homepage = "https://crates.io/crates/rand_pcg"
-description = """
-Selected PCG random number generators
-"""
-keywords = ["random", "rng", "pcg"]
-categories = ["algorithms", "no-std"]
-edition = "2018"
-
-[badges]
-travis-ci = { repository = "rust-random/rand" }
-appveyor = { repository = "rust-random/rand" }
-
-[features]
-serde1 = ["serde"]
-
-[dependencies]
-rand_core = { path = "../rand_core", version = "0.5" }
-serde = { version = "1", features = ["derive"], optional = true }
-
-[dev-dependencies]
-# This is for testing serde, unfortunately we can't specify feature-gated dev
-# deps yet, see: https://github.com/rust-lang/cargo/issues/1596
-# We require at least 1.1.2 for i128 auto-detection
-bincode = { version = "1.1.2" }
diff --git a/rand/rand_pcg/LICENSE-APACHE b/rand/rand_pcg/LICENSE-APACHE
deleted file mode 100644
index 17d7468..0000000
--- a/rand/rand_pcg/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
- Apache License
- Version 2.0, January 2004
- https://www.apache.org/licenses/
-
-TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
-
-1. Definitions.
-
- "License" shall mean the terms and conditions for use, reproduction,
- and distribution as defined by Sections 1 through 9 of this document.
-
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- the copyright owner that is granting the License.
-
- "Legal Entity" shall mean the union of the acting entity and all
- other entities that control, are controlled by, or are under common
- control with that entity. For the purposes of this definition,
- "control" means (i) the power, direct or indirect, to cause the
- direction or management of such entity, whether by contract or
- otherwise, or (ii) ownership of fifty percent (50%) or more of the
- outstanding shares, or (iii) beneficial ownership of such entity.
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-5. Submission of Contributions. Unless You explicitly state otherwise,
- any Contribution intentionally submitted for inclusion in the Work
- by You to the Licensor shall be under the terms and conditions of
- this License, without any additional terms or conditions.
- Notwithstanding the above, nothing herein shall supersede or modify
- the terms of any separate license agreement you may have executed
- with Licensor regarding such Contributions.
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-6. Trademarks. This License does not grant permission to use the trade
- names, trademarks, service marks, or product names of the Licensor,
- except as required for reasonable and customary use in describing the
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-
-7. Disclaimer of Warranty. Unless required by applicable law or
- agreed to in writing, Licensor provides the Work (and each
- Contributor provides its Contributions) on an "AS IS" BASIS,
- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
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- PARTICULAR PURPOSE. You are solely responsible for determining the
- appropriateness of using or redistributing the Work and assume any
- risks associated with Your exercise of permissions under this License.
-
-8. Limitation of Liability. In no event and under no legal theory,
- whether in tort (including negligence), contract, or otherwise,
- unless required by applicable law (such as deliberate and grossly
- negligent acts) or agreed to in writing, shall any Contributor be
- liable to You for damages, including any direct, indirect, special,
- incidental, or consequential damages of any character arising as a
- result of this License or out of the use or inability to use the
- Work (including but not limited to damages for loss of goodwill,
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-APPENDIX: How to apply the Apache License to your work.
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- To apply the Apache License to your work, attach the following
- boilerplate notice, with the fields enclosed by brackets "[]"
- replaced with your own identifying information. (Don't include
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- comment syntax for the file format. We also recommend that a
- file or class name and description of purpose be included on the
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-Copyright [yyyy] [name of copyright owner]
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-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
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-
- https://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
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-See the License for the specific language governing permissions and
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diff --git a/rand/rand_pcg/LICENSE-MIT b/rand/rand_pcg/LICENSE-MIT
deleted file mode 100644
index d46f058..0000000
--- a/rand/rand_pcg/LICENSE-MIT
+++ /dev/null
@@ -1,26 +0,0 @@
-Copyright (c) 2014-2017 Melissa O'Neill and PCG Project contributors
-Copyright 2018 Developers of the Rand project
-
-Permission is hereby granted, free of charge, to any
-person obtaining a copy of this software and associated
-documentation files (the "Software"), to deal in the
-Software without restriction, including without
-limitation the rights to use, copy, modify, merge,
-publish, distribute, sublicense, and/or sell copies of
-the Software, and to permit persons to whom the Software
-is furnished to do so, subject to the following
-conditions:
-
-The above copyright notice and this permission notice
-shall be included in all copies or substantial portions
-of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF
-ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED
-TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
-PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
-SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
-IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-DEALINGS IN THE SOFTWARE.
diff --git a/rand/rand_pcg/README.md b/rand/rand_pcg/README.md
deleted file mode 100644
index fe47f2d..0000000
--- a/rand/rand_pcg/README.md
+++ /dev/null
@@ -1,43 +0,0 @@
-# rand_pcg
-
-[](https://travis-ci.org/rust-random/rand)
-[](https://ci.appveyor.com/project/rust-random/rand)
-[](https://crates.io/crates/rand_pcg)
-[[](https://rust-random.github.io/book/)
-[](https://rust-random.github.io/rand/rand_pcg)
-[](https://docs.rs/rand_pcg)
-[](https://github.com/rust-random/rand#rust-version-requirements)
-
-Implements a selection of PCG random number generators.
-
-> PCG is a family of simple fast space-efficient statistically good algorithms
-> for random number generation. [Melissa O'Neill, Harvey Mudd College, 2014].
-
-The PCG algorithms are not suitable for cryptographic uses, but perform well
-in statistical tests, use little memory and are fairly fast.
-See the [pcg-random website](http://www.pcg-random.org/).
-
-This crate depends on [rand_core](https://crates.io/crates/rand_core) and is
-part of the [Rand project](https://github.com/rust-random/rand).
-
-Links:
-
-- [API documentation (master)](https://rust-random.github.io/rand/rand_pcg)
-- [API documentation (docs.rs)](https://docs.rs/rand_pcg)
-- [Changelog](https://github.com/rust-random/rand/blob/master/rand_pcg/CHANGELOG.md)
-
-
-## Crate Features
-
-`rand_pcg` is `no_std` compatible by default.
-
-The `serde1` feature includes implementations of `Serialize` and `Deserialize`
-for the included RNGs.
-
-## License
-
-`rand_pcg` is distributed under the terms of both the MIT license and the
-Apache License (Version 2.0).
-
-See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT), and
-[COPYRIGHT](COPYRIGHT) for details.
diff --git a/rand/rand_pcg/src/lib.rs b/rand/rand_pcg/src/lib.rs
deleted file mode 100644
index 22ba4a0..0000000
--- a/rand/rand_pcg/src/lib.rs
+++ /dev/null
@@ -1,49 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The PCG random number generators.
-//!
-//! This is a native Rust implementation of a small selection of PCG generators.
-//! The primary goal of this crate is simple, minimal, well-tested code; in
-//! other words it is explicitly not a goal to re-implement all of PCG.
-//!
-//! This crate provides:
-//!
-//! - `Pcg32` aka `Lcg64Xsh32`, officially known as `pcg32`, a general
-//! purpose RNG. This is a good choice on both 32-bit and 64-bit CPUs
-//! (for 32-bit output).
-//! - `Pcg64` aka `Lcg128Xsl64`, officially known as `pcg64`, a general
-//! purpose RNG. This is a good choice on 64-bit CPUs.
-//! - `Pcg64Mcg` aka `Mcg128Xsl64`, officially known as `pcg64_fast`,
-//! a general purpose RNG using 128-bit multiplications. This has poor
-//! performance on 32-bit CPUs but is a good choice on 64-bit CPUs for
-//! both 32-bit and 64-bit output.
-//!
-//! Both of these use 16 bytes of state and 128-bit seeds, and are considered
-//! value-stable (i.e. any change affecting the output given a fixed seed would
-//! be considered a breaking change to the crate).
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
- html_favicon_url = "https://www.rust-lang.org/favicon.ico",
- html_root_url = "https://rust-random.github.io/rand/")]
-
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-
-#![allow(clippy::unreadable_literal)]
-
-#![no_std]
-
-mod pcg64;
-#[cfg(not(target_os = "emscripten"))] mod pcg128;
-
-pub use self::pcg64::{Pcg32, Lcg64Xsh32};
-#[cfg(not(target_os = "emscripten"))] pub use self::pcg128::{
- Pcg64, Lcg128Xsl64,
- Pcg64Mcg, Mcg128Xsl64,
-};
diff --git a/rand/rand_pcg/src/pcg128.rs b/rand/rand_pcg/src/pcg128.rs
deleted file mode 100644
index 311a41b..0000000
--- a/rand/rand_pcg/src/pcg128.rs
+++ /dev/null
@@ -1,225 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2017 Paul Dicker.
-// Copyright 2014-2017 Melissa O'Neill and PCG Project contributors
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! PCG random number generators
-
-// This is the default multiplier used by PCG for 64-bit state.
-const MULTIPLIER: u128 = 0x2360_ED05_1FC6_5DA4_4385_DF64_9FCC_F645;
-
-use core::fmt;
-use rand_core::{RngCore, SeedableRng, Error, le};
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-
-/// A PCG random number generator (XSL RR 128/64 (LCG) variant).
-///
-/// Permuted Congruential Generator with 128-bit state, internal Linear
-/// Congruential Generator, and 64-bit output via "xorshift low (bits),
-/// random rotation" output function.
-///
-/// This is a 128-bit LCG with explicitly chosen stream with the PCG-XSL-RR
-/// output function. This combination is the standard `pcg64`.
-///
-/// Despite the name, this implementation uses 32 bytes (256 bit) space
-/// comprising 128 bits of state and 128 bits stream selector. These are both
-/// set by `SeedableRng`, using a 256-bit seed.
-#[derive(Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize,Deserialize))]
-pub struct Lcg128Xsl64 {
- state: u128,
- increment: u128,
-}
-
-/// `Lcg128Xsl64` is also officially known as `pcg64`.
-pub type Pcg64 = Lcg128Xsl64;
-
-impl Lcg128Xsl64 {
- /// Construct an instance compatible with PCG seed and stream.
- ///
- /// Note that PCG specifies default values for both parameters:
- ///
- /// - `state = 0xcafef00dd15ea5e5`
- /// - `stream = 0xa02bdbf7bb3c0a7ac28fa16a64abf96`
- pub fn new(state: u128, stream: u128) -> Self {
- // The increment must be odd, hence we discard one bit:
- let increment = (stream << 1) | 1;
- Lcg128Xsl64::from_state_incr(state, increment)
- }
-
- #[inline]
- fn from_state_incr(state: u128, increment: u128) -> Self {
- let mut pcg = Lcg128Xsl64 { state, increment };
- // Move away from inital value:
- pcg.state = pcg.state.wrapping_add(pcg.increment);
- pcg.step();
- pcg
- }
-
- #[inline]
- fn step(&mut self) {
- // prepare the LCG for the next round
- self.state = self.state
- .wrapping_mul(MULTIPLIER)
- .wrapping_add(self.increment);
- }
-}
-
-// Custom Debug implementation that does not expose the internal state
-impl fmt::Debug for Lcg128Xsl64 {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "Lcg128Xsl64 {{}}")
- }
-}
-
-/// We use a single 255-bit seed to initialise the state and select a stream.
-/// One `seed` bit (lowest bit of `seed[8]`) is ignored.
-impl SeedableRng for Lcg128Xsl64 {
- type Seed = [u8; 32];
-
- fn from_seed(seed: Self::Seed) -> Self {
- let mut seed_u64 = [0u64; 4];
- le::read_u64_into(&seed, &mut seed_u64);
- let state = u128::from(seed_u64[0]) | (u128::from(seed_u64[1]) << 64);
- let incr = u128::from(seed_u64[2]) | (u128::from(seed_u64[3]) << 64);
-
- // The increment must be odd, hence we discard one bit:
- Lcg128Xsl64::from_state_incr(state, incr | 1)
- }
-}
-
-impl RngCore for Lcg128Xsl64 {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.next_u64() as u32
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- self.step();
- output_xsl_rr(self.state)
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_impl(self, dest)
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-
-/// A PCG random number generator (XSL 128/64 (MCG) variant).
-///
-/// Permuted Congruential Generator with 128-bit state, internal Multiplicative
-/// Congruential Generator, and 64-bit output via "xorshift low (bits),
-/// random rotation" output function.
-///
-/// This is a 128-bit MCG with the PCG-XSL-RR output function, also known as
-/// `pcg64_fast`.
-/// Note that compared to the standard `pcg64` (128-bit LCG with PCG-XSL-RR
-/// output function), this RNG is faster, also has a long cycle, and still has
-/// good performance on statistical tests.
-#[derive(Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize,Deserialize))]
-pub struct Mcg128Xsl64 {
- state: u128,
-}
-
-/// A friendly name for `Mcg128Xsl64` (also known as `pcg64_fast`).
-pub type Pcg64Mcg = Mcg128Xsl64;
-
-impl Mcg128Xsl64 {
- /// Construct an instance compatible with PCG seed.
- ///
- /// Note that PCG specifies a default value for the parameter:
- ///
- /// - `state = 0xcafef00dd15ea5e5`
- pub fn new(state: u128) -> Self {
- // Force low bit to 1, as in C version (C++ uses `state | 3` instead).
- Mcg128Xsl64 { state: state | 1 }
- }
-}
-
-// Custom Debug implementation that does not expose the internal state
-impl fmt::Debug for Mcg128Xsl64 {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "Mcg128Xsl64 {{}}")
- }
-}
-
-/// We use a single 126-bit seed to initialise the state and select a stream.
-/// Two `seed` bits (lowest order of last byte) are ignored.
-impl SeedableRng for Mcg128Xsl64 {
- type Seed = [u8; 16];
-
- fn from_seed(seed: Self::Seed) -> Self {
- // Read as if a little-endian u128 value:
- let mut seed_u64 = [0u64; 2];
- le::read_u64_into(&seed, &mut seed_u64);
- let state = u128::from(seed_u64[0]) |
- u128::from(seed_u64[1]) << 64;
- Mcg128Xsl64::new(state)
- }
-}
-
-impl RngCore for Mcg128Xsl64 {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.next_u64() as u32
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- self.state = self.state.wrapping_mul(MULTIPLIER);
- output_xsl_rr(self.state)
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_impl(self, dest)
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-#[inline(always)]
-fn output_xsl_rr(state: u128) -> u64 {
- // Output function XSL RR ("xorshift low (bits), random rotation")
- // Constants are for 128-bit state, 64-bit output
- const XSHIFT: u32 = 64; // (128 - 64 + 64) / 2
- const ROTATE: u32 = 122; // 128 - 6
-
- let rot = (state >> ROTATE) as u32;
- let xsl = ((state >> XSHIFT) as u64) ^ (state as u64);
- xsl.rotate_right(rot)
-}
-
-#[inline(always)]
-fn fill_bytes_impl<R: RngCore + ?Sized>(rng: &mut R, dest: &mut [u8]) {
- let mut left = dest;
- while left.len() >= 8 {
- let (l, r) = {left}.split_at_mut(8);
- left = r;
- let chunk: [u8; 8] = rng.next_u64().to_le_bytes();
- l.copy_from_slice(&chunk);
- }
- let n = left.len();
- if n > 0 {
- let chunk: [u8; 8] = rng.next_u64().to_le_bytes();
- left.copy_from_slice(&chunk[..n]);
- }
-}
diff --git a/rand/rand_pcg/src/pcg64.rs b/rand/rand_pcg/src/pcg64.rs
deleted file mode 100644
index fadc6dc..0000000
--- a/rand/rand_pcg/src/pcg64.rs
+++ /dev/null
@@ -1,127 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2017 Paul Dicker.
-// Copyright 2014-2017 Melissa O'Neill and PCG Project contributors
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! PCG random number generators
-
-use core::fmt;
-use rand_core::{RngCore, SeedableRng, Error, le, impls};
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-
-// This is the default multiplier used by PCG for 64-bit state.
-const MULTIPLIER: u64 = 6364136223846793005;
-
-/// A PCG random number generator (XSH RR 64/32 (LCG) variant).
-///
-/// Permuted Congruential Generator with 64-bit state, internal Linear
-/// Congruential Generator, and 32-bit output via "xorshift high (bits),
-/// random rotation" output function.
-///
-/// This is a 64-bit LCG with explicitly chosen stream with the PCG-XSH-RR
-/// output function. This combination is the standard `pcg32`.
-///
-/// Despite the name, this implementation uses 16 bytes (128 bit) space
-/// comprising 64 bits of state and 64 bits stream selector. These are both set
-/// by `SeedableRng`, using a 128-bit seed.
-#[derive(Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize,Deserialize))]
-pub struct Lcg64Xsh32 {
- state: u64,
- increment: u64,
-}
-
-/// `Lcg64Xsh32` is also officially known as `pcg32`.
-pub type Pcg32 = Lcg64Xsh32;
-
-impl Lcg64Xsh32 {
- /// Construct an instance compatible with PCG seed and stream.
- ///
- /// Note that PCG specifies default values for both parameters:
- ///
- /// - `state = 0xcafef00dd15ea5e5`
- /// - `stream = 0xa02bdbf7bb3c0a7`
- // Note: stream is 1442695040888963407u64 >> 1
- pub fn new(state: u64, stream: u64) -> Self {
- // The increment must be odd, hence we discard one bit:
- let increment = (stream << 1) | 1;
- Lcg64Xsh32::from_state_incr(state, increment)
- }
-
- #[inline]
- fn from_state_incr(state: u64, increment: u64) -> Self {
- let mut pcg = Lcg64Xsh32 { state, increment };
- // Move away from inital value:
- pcg.state = pcg.state.wrapping_add(pcg.increment);
- pcg.step();
- pcg
- }
-
- #[inline]
- fn step(&mut self) {
- // prepare the LCG for the next round
- self.state = self.state
- .wrapping_mul(MULTIPLIER)
- .wrapping_add(self.increment);
- }
-}
-
-// Custom Debug implementation that does not expose the internal state
-impl fmt::Debug for Lcg64Xsh32 {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "Lcg64Xsh32 {{}}")
- }
-}
-
-/// We use a single 127-bit seed to initialise the state and select a stream.
-/// One `seed` bit (lowest bit of `seed[8]`) is ignored.
-impl SeedableRng for Lcg64Xsh32 {
- type Seed = [u8; 16];
-
- fn from_seed(seed: Self::Seed) -> Self {
- let mut seed_u64 = [0u64; 2];
- le::read_u64_into(&seed, &mut seed_u64);
-
- // The increment must be odd, hence we discard one bit:
- Lcg64Xsh32::from_state_incr(seed_u64[0], seed_u64[1] | 1)
- }
-}
-
-impl RngCore for Lcg64Xsh32 {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- let state = self.state;
- self.step();
-
- // Output function XSH RR: xorshift high (bits), followed by a random rotate
- // Constants are for 64-bit state, 32-bit output
- const ROTATE: u32 = 59; // 64 - 5
- const XSHIFT: u32 = 18; // (5 + 32) / 2
- const SPARE: u32 = 27; // 64 - 32 - 5
-
- let rot = (state >> ROTATE) as u32;
- let xsh = (((state >> XSHIFT) ^ state) >> SPARE) as u32;
- xsh.rotate_right(rot)
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- impls::next_u64_via_u32(self)
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- impls::fill_bytes_via_next(self, dest)
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
diff --git a/rand/rand_pcg/tests/lcg128xsl64.rs b/rand/rand_pcg/tests/lcg128xsl64.rs
deleted file mode 100644
index efc72ff..0000000
--- a/rand/rand_pcg/tests/lcg128xsl64.rs
+++ /dev/null
@@ -1,55 +0,0 @@
-use rand_core::{RngCore, SeedableRng};
-use rand_pcg::{Lcg128Xsl64, Pcg64};
-
-#[test]
-fn test_lcg128xsl64_construction() {
- // Test that various construction techniques produce a working RNG.
- let seed = [1,2,3,4, 5,6,7,8, 9,10,11,12, 13,14,15,16,
- 17,18,19,20, 21,22,23,24, 25,26,27,28, 29,30,31,32];
- let mut rng1 = Lcg128Xsl64::from_seed(seed);
- assert_eq!(rng1.next_u64(), 8740028313290271629);
-
- let mut rng2 = Lcg128Xsl64::from_rng(&mut rng1).unwrap();
- assert_eq!(rng2.next_u64(), 1922280315005786345);
-
- let mut rng3 = Lcg128Xsl64::seed_from_u64(0);
- assert_eq!(rng3.next_u64(), 2354861276966075475);
-
- // This is the same as Lcg128Xsl64, so we only have a single test:
- let mut rng4 = Pcg64::seed_from_u64(0);
- assert_eq!(rng4.next_u64(), 2354861276966075475);
-}
-
-#[test]
-fn test_lcg128xsl64_true_values() {
- // Numbers copied from official test suite (C version).
- let mut rng = Lcg128Xsl64::new(42, 54);
-
- let mut results = [0u64; 6];
- for i in results.iter_mut() { *i = rng.next_u64(); }
- let expected: [u64; 6] = [0x86b1da1d72062b68, 0x1304aa46c9853d39,
- 0xa3670e9e0dd50358, 0xf9090e529a7dae00, 0xc85b9fd837996f2c, 0x606121f8e3919196];
- assert_eq!(results, expected);
-}
-
-#[cfg(feature="serde1")]
-#[test]
-fn test_lcg128xsl64_serde() {
- use bincode;
- use std::io::{BufWriter, BufReader};
-
- let mut rng = Lcg128Xsl64::seed_from_u64(0);
-
- let buf: Vec<u8> = Vec::new();
- let mut buf = BufWriter::new(buf);
- bincode::serialize_into(&mut buf, &rng).expect("Could not serialize");
-
- let buf = buf.into_inner().unwrap();
- let mut read = BufReader::new(&buf[..]);
- let mut deserialized: Lcg128Xsl64 = bincode::deserialize_from(&mut read)
- .expect("Could not deserialize");
-
- for _ in 0..16 {
- assert_eq!(rng.next_u64(), deserialized.next_u64());
- }
-}
diff --git a/rand/rand_pcg/tests/lcg64xsh32.rs b/rand/rand_pcg/tests/lcg64xsh32.rs
deleted file mode 100644
index e05bcc1..0000000
--- a/rand/rand_pcg/tests/lcg64xsh32.rs
+++ /dev/null
@@ -1,54 +0,0 @@
-use rand_core::{RngCore, SeedableRng};
-use rand_pcg::{Lcg64Xsh32, Pcg32};
-
-#[test]
-fn test_lcg64xsh32_construction() {
- // Test that various construction techniques produce a working RNG.
- let seed = [1,2,3,4, 5,6,7,8, 9,10,11,12, 13,14,15,16];
- let mut rng1 = Lcg64Xsh32::from_seed(seed);
- assert_eq!(rng1.next_u64(), 1204678643940597513);
-
- let mut rng2 = Lcg64Xsh32::from_rng(&mut rng1).unwrap();
- assert_eq!(rng2.next_u64(), 12384929573776311845);
-
- let mut rng3 = Lcg64Xsh32::seed_from_u64(0);
- assert_eq!(rng3.next_u64(), 18195738587432868099);
-
- // This is the same as Lcg64Xsh32, so we only have a single test:
- let mut rng4 = Pcg32::seed_from_u64(0);
- assert_eq!(rng4.next_u64(), 18195738587432868099);
-}
-
-#[test]
-fn test_lcg64xsh32_true_values() {
- // Numbers copied from official test suite.
- let mut rng = Lcg64Xsh32::new(42, 54);
-
- let mut results = [0u32; 6];
- for i in results.iter_mut() { *i = rng.next_u32(); }
- let expected: [u32; 6] = [0xa15c02b7, 0x7b47f409, 0xba1d3330,
- 0x83d2f293, 0xbfa4784b, 0xcbed606e];
- assert_eq!(results, expected);
-}
-
-#[cfg(feature="serde1")]
-#[test]
-fn test_lcg64xsh32_serde() {
- use bincode;
- use std::io::{BufWriter, BufReader};
-
- let mut rng = Lcg64Xsh32::seed_from_u64(0);
-
- let buf: Vec<u8> = Vec::new();
- let mut buf = BufWriter::new(buf);
- bincode::serialize_into(&mut buf, &rng).expect("Could not serialize");
-
- let buf = buf.into_inner().unwrap();
- let mut read = BufReader::new(&buf[..]);
- let mut deserialized: Lcg64Xsh32 = bincode::deserialize_from(&mut read)
- .expect("Could not deserialize");
-
- for _ in 0..16 {
- assert_eq!(rng.next_u64(), deserialized.next_u64());
- }
-}
diff --git a/rand/rand_pcg/tests/mcg128xsl64.rs b/rand/rand_pcg/tests/mcg128xsl64.rs
deleted file mode 100644
index d58fa75..0000000
--- a/rand/rand_pcg/tests/mcg128xsl64.rs
+++ /dev/null
@@ -1,54 +0,0 @@
-use rand_core::{RngCore, SeedableRng};
-use rand_pcg::{Mcg128Xsl64, Pcg64Mcg};
-
-#[test]
-fn test_mcg128xsl64_construction() {
- // Test that various construction techniques produce a working RNG.
- let seed = [1,2,3,4, 5,6,7,8, 9,10,11,12, 13,14,15,16];
- let mut rng1 = Mcg128Xsl64::from_seed(seed);
- assert_eq!(rng1.next_u64(), 7071994460355047496);
-
- let mut rng2 = Mcg128Xsl64::from_rng(&mut rng1).unwrap();
- assert_eq!(rng2.next_u64(), 12300796107712034932);
-
- let mut rng3 = Mcg128Xsl64::seed_from_u64(0);
- assert_eq!(rng3.next_u64(), 6198063878555692194);
-
- // This is the same as Mcg128Xsl64, so we only have a single test:
- let mut rng4 = Pcg64Mcg::seed_from_u64(0);
- assert_eq!(rng4.next_u64(), 6198063878555692194);
-}
-
-#[test]
-fn test_mcg128xsl64_true_values() {
- // Numbers copied from official test suite (C version).
- let mut rng = Mcg128Xsl64::new(42);
-
- let mut results = [0u64; 6];
- for i in results.iter_mut() { *i = rng.next_u64(); }
- let expected: [u64; 6] = [0x63b4a3a813ce700a, 0x382954200617ab24,
- 0xa7fd85ae3fe950ce, 0xd715286aa2887737, 0x60c92fee2e59f32c, 0x84c4e96beff30017];
- assert_eq!(results, expected);
-}
-
-#[cfg(feature="serde1")]
-#[test]
-fn test_mcg128xsl64_serde() {
- use bincode;
- use std::io::{BufWriter, BufReader};
-
- let mut rng = Mcg128Xsl64::seed_from_u64(0);
-
- let buf: Vec<u8> = Vec::new();
- let mut buf = BufWriter::new(buf);
- bincode::serialize_into(&mut buf, &rng).expect("Could not serialize");
-
- let buf = buf.into_inner().unwrap();
- let mut read = BufReader::new(&buf[..]);
- let mut deserialized: Mcg128Xsl64 = bincode::deserialize_from(&mut read)
- .expect("Could not deserialize");
-
- for _ in 0..16 {
- assert_eq!(rng.next_u64(), deserialized.next_u64());
- }
-}
diff --git a/rand/rand_xorshift/CHANGELOG.md b/rand/rand_xorshift/CHANGELOG.md
deleted file mode 100644
index ce3098a..0000000
--- a/rand/rand_xorshift/CHANGELOG.md
+++ /dev/null
@@ -1,19 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.2.0] - 2019-06-12
-- Bump minor crate version since rand_core bump is a breaking change
-- Switch to Edition 2018
-
-## [0.1.2] - 2019-06-06 - yanked
-- Bump `rand_core` version
-- Make XorShiftRng::from_rng portable by enforcing Endianness (#815)
-
-## [0.1.1] - 2019-01-04
-- Reorganise code and tests; tweak doc
-
-## [0.1.0] - 2018-07-16
-- Pulled out of the Rand crate
diff --git a/rand/rand_xorshift/COPYRIGHT b/rand/rand_xorshift/COPYRIGHT
deleted file mode 100644
index 468d907..0000000
--- a/rand/rand_xorshift/COPYRIGHT
+++ /dev/null
@@ -1,12 +0,0 @@
-Copyrights in the Rand project are retained by their contributors. No
-copyright assignment is required to contribute to the Rand project.
-
-For full authorship information, see the version control history.
-
-Except as otherwise noted (below and/or in individual files), Rand is
-licensed under the Apache License, Version 2.0 <LICENSE-APACHE> or
-<http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-<LICENSE-MIT> or <http://opensource.org/licenses/MIT>, at your option.
-
-The Rand project includes code from the Rust project
-published under these same licenses.
diff --git a/rand/rand_xorshift/Cargo.toml b/rand/rand_xorshift/Cargo.toml
deleted file mode 100644
index 9cb257b..0000000
--- a/rand/rand_xorshift/Cargo.toml
+++ /dev/null
@@ -1,31 +0,0 @@
-[package]
-name = "rand_xorshift"
-version = "0.2.0"
-authors = ["The Rand Project Developers", "The Rust Project Developers"]
-license = "MIT OR Apache-2.0"
-readme = "README.md"
-repository = "https://github.com/rust-random/rand"
-documentation = "https://rust-random.github.io/rand/rand_xorshift/"
-homepage = "https://crates.io/crates/rand_xorshift"
-description = """
-Xorshift random number generator
-"""
-keywords = ["random", "rng", "xorshift"]
-categories = ["algorithms", "no-std"]
-edition = "2018"
-
-[badges]
-travis-ci = { repository = "rust-random/rand" }
-appveyor = { repository = "rust-random/rand" }
-
-[features]
-serde1 = ["serde"]
-
-[dependencies]
-rand_core = { path = "../rand_core", version = "0.5" }
-serde = { version = "1", features = ["derive"], optional = true }
-
-[dev-dependencies]
-# This is for testing serde, unfortunately we can't specify feature-gated dev
-# deps yet, see: https://github.com/rust-lang/cargo/issues/1596
-bincode = "1"
diff --git a/rand/rand_xorshift/LICENSE-APACHE b/rand/rand_xorshift/LICENSE-APACHE
deleted file mode 100644
index 17d7468..0000000
--- a/rand/rand_xorshift/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
- Apache License
- Version 2.0, January 2004
- https://www.apache.org/licenses/
-
-TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
-
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diff --git a/rand/rand_xorshift/LICENSE-MIT b/rand/rand_xorshift/LICENSE-MIT
deleted file mode 100644
index d93b5ba..0000000
--- a/rand/rand_xorshift/LICENSE-MIT
+++ /dev/null
@@ -1,26 +0,0 @@
-Copyright 2018 Developers of the Rand project
-Copyright (c) 2014 The Rust Project Developers
-
-Permission is hereby granted, free of charge, to any
-person obtaining a copy of this software and associated
-documentation files (the "Software"), to deal in the
-Software without restriction, including without
-limitation the rights to use, copy, modify, merge,
-publish, distribute, sublicense, and/or sell copies of
-the Software, and to permit persons to whom the Software
-is furnished to do so, subject to the following
-conditions:
-
-The above copyright notice and this permission notice
-shall be included in all copies or substantial portions
-of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF
-ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED
-TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
-PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
-SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
-IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-DEALINGS IN THE SOFTWARE.
diff --git a/rand/rand_xorshift/README.md b/rand/rand_xorshift/README.md
deleted file mode 100644
index 57de284..0000000
--- a/rand/rand_xorshift/README.md
+++ /dev/null
@@ -1,45 +0,0 @@
-# rand_xorshift
-
-[](https://travis-ci.org/rust-random/rand)
-[](https://ci.appveyor.com/project/rust-random/rand)
-[](https://crates.io/crates/rand_xorshift)
-[](https://rust-random.github.io/book/)
-[](https://rust-random.github.io/rand/rand_xorshift)
-[](https://docs.rs/rand_xorshift)
-[](https://github.com/rust-random/rand#rust-version-requirements)
-
-Implements the Xorshift random number generator.
-
-The Xorshift[^1] algorithm is not suitable for cryptographic purposes
-but is very fast. If you do not know for sure that it fits your
-requirements, use a more secure one such as `StdRng` or `OsRng`.
-
-[^1]: Marsaglia, George (July 2003).
- ["Xorshift RNGs"](https://www.jstatsoft.org/v08/i14/paper).
- *Journal of Statistical Software*. Vol. 8 (Issue 14).
-
-Links:
-
-- [API documentation (master)](https://rust-random.github.io/rand/rand_xorshift)
-- [API documentation (docs.rs)](https://docs.rs/rand_xorshift)
-- [Changelog](https://github.com/rust-random/rand/blob/master/rand_xorshift/CHANGELOG.md)
-
-[rand]: https://crates.io/crates/rand
-
-
-## Crate Features
-
-`rand_xorshift` is `no_std` compatible. It does not require any functionality
-outside of the `core` lib, thus there are no features to configure.
-
-The `serde1` feature includes implementations of `Serialize` and `Deserialize`
-for the included RNGs.
-
-
-## License
-
-`rand_xorshift` is distributed under the terms of both the MIT license and the
-Apache License (Version 2.0).
-
-See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT), and
-[COPYRIGHT](COPYRIGHT) for details.
diff --git a/rand/rand_xorshift/src/lib.rs b/rand/rand_xorshift/src/lib.rs
deleted file mode 100644
index b9fef23..0000000
--- a/rand/rand_xorshift/src/lib.rs
+++ /dev/null
@@ -1,117 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The xorshift random number generator.
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
- html_favicon_url = "https://www.rust-lang.org/favicon.ico",
- html_root_url = "https://rust-random.github.io/rand/")]
-
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-
-#![no_std]
-
-use core::num::Wrapping as w;
-use core::fmt;
-use rand_core::{RngCore, SeedableRng, Error, impls, le};
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-
-/// An Xorshift random number generator.
-///
-/// The Xorshift[^1] algorithm is not suitable for cryptographic purposes
-/// but is very fast. If you do not know for sure that it fits your
-/// requirements, use a more secure one such as `StdRng` or `OsRng`.
-///
-/// [^1]: Marsaglia, George (July 2003).
-/// ["Xorshift RNGs"](https://www.jstatsoft.org/v08/i14/paper).
-/// *Journal of Statistical Software*. Vol. 8 (Issue 14).
-#[derive(Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize,Deserialize))]
-pub struct XorShiftRng {
- x: w<u32>,
- y: w<u32>,
- z: w<u32>,
- w: w<u32>,
-}
-
-// Custom Debug implementation that does not expose the internal state
-impl fmt::Debug for XorShiftRng {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "XorShiftRng {{}}")
- }
-}
-
-impl RngCore for XorShiftRng {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- let x = self.x;
- let t = x ^ (x << 11);
- self.x = self.y;
- self.y = self.z;
- self.z = self.w;
- let w_ = self.w;
- self.w = w_ ^ (w_ >> 19) ^ (t ^ (t >> 8));
- self.w.0
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- impls::next_u64_via_u32(self)
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- impls::fill_bytes_via_next(self, dest)
- }
-
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-impl SeedableRng for XorShiftRng {
- type Seed = [u8; 16];
-
- fn from_seed(seed: Self::Seed) -> Self {
- let mut seed_u32 = [0u32; 4];
- le::read_u32_into(&seed, &mut seed_u32);
-
- // Xorshift cannot be seeded with 0 and we cannot return an Error, but
- // also do not wish to panic (because a random seed can legitimately be
- // 0); our only option is therefore to use a preset value.
- if seed_u32.iter().all(|&x| x == 0) {
- seed_u32 = [0xBAD_5EED, 0xBAD_5EED, 0xBAD_5EED, 0xBAD_5EED];
- }
-
- XorShiftRng {
- x: w(seed_u32[0]),
- y: w(seed_u32[1]),
- z: w(seed_u32[2]),
- w: w(seed_u32[3]),
- }
- }
-
- fn from_rng<R: RngCore>(mut rng: R) -> Result<Self, Error> {
- let mut b = [0u8; 16];
- loop {
- rng.try_fill_bytes(&mut b[..])?;
- if !b.iter().all(|&x| x == 0) {
- break;
- }
- }
-
- Ok(XorShiftRng {
- x: w(u32::from_le_bytes([b[0], b[1], b[2], b[3]])),
- y: w(u32::from_le_bytes([b[4], b[5], b[6], b[7]])),
- z: w(u32::from_le_bytes([b[8], b[9], b[10], b[11]])),
- w: w(u32::from_le_bytes([b[12], b[13], b[14], b[15]])),
- })
- }
-}
diff --git a/rand/rand_xorshift/tests/mod.rs b/rand/rand_xorshift/tests/mod.rs
deleted file mode 100644
index 7ecdeae..0000000
--- a/rand/rand_xorshift/tests/mod.rs
+++ /dev/null
@@ -1,89 +0,0 @@
-use rand_core::{RngCore, SeedableRng};
-use rand_xorshift::XorShiftRng;
-
-#[test]
-fn test_xorshift_construction() {
- // Test that various construction techniques produce a working RNG.
- let seed = [1,2,3,4, 5,6,7,8, 9,10,11,12, 13,14,15,16];
- let mut rng1 = XorShiftRng::from_seed(seed);
- assert_eq!(rng1.next_u64(), 4325440999699518727);
-
- let mut rng2 = XorShiftRng::from_rng(&mut rng1).unwrap();
- // Yes, this makes rng2 a clone of rng1!
- assert_eq!(rng1.next_u64(), 15614385950550801700);
- assert_eq!(rng2.next_u64(), 15614385950550801700);
-}
-
-#[test]
-fn test_xorshift_true_values() {
- let seed = [16,15,14,13, 12,11,10,9, 8,7,6,5, 4,3,2,1];
- let mut rng = XorShiftRng::from_seed(seed);
-
- let mut results = [0u32; 9];
- for i in results.iter_mut() { *i = rng.next_u32(); }
- let expected: [u32; 9] = [
- 2081028795, 620940381, 269070770, 16943764, 854422573, 29242889,
- 1550291885, 1227154591, 271695242];
- assert_eq!(results, expected);
-
- let mut results = [0u64; 9];
- for i in results.iter_mut() { *i = rng.next_u64(); }
- let expected: [u64; 9] = [
- 9247529084182843387, 8321512596129439293, 14104136531997710878,
- 6848554330849612046, 343577296533772213, 17828467390962600268,
- 9847333257685787782, 7717352744383350108, 1133407547287910111];
- assert_eq!(results, expected);
-
- let mut results = [0u8; 32];
- rng.fill_bytes(&mut results);
- let expected = [102, 57, 212, 16, 233, 130, 49, 183,
- 158, 187, 44, 203, 63, 149, 45, 17,
- 117, 129, 131, 160, 70, 121, 158, 155,
- 224, 209, 192, 53, 10, 62, 57, 72];
- assert_eq!(results, expected);
-}
-
-#[test]
-fn test_xorshift_zero_seed() {
- // Xorshift does not work with an all zero seed.
- // Assert it does not panic.
- let seed = [0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0];
- let mut rng = XorShiftRng::from_seed(seed);
- let a = rng.next_u64();
- let b = rng.next_u64();
- assert!(a != 0);
- assert!(b != a);
-}
-
-#[test]
-fn test_xorshift_clone() {
- let seed = [1,2,3,4, 5,5,7,8, 8,7,6,5, 4,3,2,1];
- let mut rng1 = XorShiftRng::from_seed(seed);
- let mut rng2 = rng1.clone();
- for _ in 0..16 {
- assert_eq!(rng1.next_u64(), rng2.next_u64());
- }
-}
-
-#[cfg(feature="serde1")]
-#[test]
-fn test_xorshift_serde() {
- use bincode;
- use std::io::{BufWriter, BufReader};
-
- let seed = [1,2,3,4, 5,6,7,8, 9,10,11,12, 13,14,15,16];
- let mut rng = XorShiftRng::from_seed(seed);
-
- let buf: Vec<u8> = Vec::new();
- let mut buf = BufWriter::new(buf);
- bincode::serialize_into(&mut buf, &rng).expect("Could not serialize");
-
- let buf = buf.into_inner().unwrap();
- let mut read = BufReader::new(&buf[..]);
- let mut deserialized: XorShiftRng = bincode::deserialize_from(&mut read)
- .expect("Could not deserialize");
-
- for _ in 0..16 {
- assert_eq!(rng.next_u64(), deserialized.next_u64());
- }
-}
diff --git a/rand/rand_xoshiro/CHANGELOG.md b/rand/rand_xoshiro/CHANGELOG.md
deleted file mode 100644
index 56cb9c2..0000000
--- a/rand/rand_xoshiro/CHANGELOG.md
+++ /dev/null
@@ -1,24 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.3.1] - 2019-08-06
-- Drop `byteorder`-dependency in favor of `stdlib`-implementation.
-
-## [0.3.0] - 2019-06-12
-- Bump minor crate version since rand_core bump is a breaking change
-- Switch to Edition 2018
-
-## [0.2.1] - 2019-06-06 - yanked
-- Bump `rand_core` version
-- Document crate features in README
-
-## [0.2.0] - 2019-05-28
-- Fix `seed_from_u64(0)` for `Xoroshiro64StarStar` and `Xoroshiro64Star`. This
- breaks value stability for these generators if initialized with `seed_from_u64`.
-- Implement Serde support.
-
-## [0.1.0] - 2019-01-04
-Initial release.
diff --git a/rand/rand_xoshiro/COPYRIGHT b/rand/rand_xoshiro/COPYRIGHT
deleted file mode 100644
index 468d907..0000000
--- a/rand/rand_xoshiro/COPYRIGHT
+++ /dev/null
@@ -1,12 +0,0 @@
-Copyrights in the Rand project are retained by their contributors. No
-copyright assignment is required to contribute to the Rand project.
-
-For full authorship information, see the version control history.
-
-Except as otherwise noted (below and/or in individual files), Rand is
-licensed under the Apache License, Version 2.0 <LICENSE-APACHE> or
-<http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-<LICENSE-MIT> or <http://opensource.org/licenses/MIT>, at your option.
-
-The Rand project includes code from the Rust project
-published under these same licenses.
diff --git a/rand/rand_xoshiro/Cargo.toml b/rand/rand_xoshiro/Cargo.toml
deleted file mode 100644
index 128c213..0000000
--- a/rand/rand_xoshiro/Cargo.toml
+++ /dev/null
@@ -1,25 +0,0 @@
-[package]
-name = "rand_xoshiro"
-version = "0.3.1" # NB: When modifying, also modify html_root_url in lib.rs
-authors = ["The Rand Project Developers"]
-license = "MIT OR Apache-2.0"
-readme = "README.md"
-repository = "https://github.com/rust-random/rand"
-documentation = "https://docs.rs/rand_xoshiro"
-homepage = "https://crates.io/crates/rand_xoshiro"
-description = "Xoshiro, xoroshiro and splitmix64 random number generators"
-keywords = ["random", "rng"]
-categories = ["algorithms"]
-edition = "2018"
-
-[features]
-serde1 = ["serde"]
-
-[dependencies]
-rand_core = { path = "../rand_core", version = "0.5" }
-serde = { version = "1", features = ["derive"], optional=true }
-
-[dev-dependencies]
-# This is for testing serde, unfortunately we can't specify feature-gated dev
-# deps yet, see: https://github.com/rust-lang/cargo/issues/1596
-bincode = { version = "1" }
diff --git a/rand/rand_xoshiro/LICENSE-APACHE b/rand/rand_xoshiro/LICENSE-APACHE
deleted file mode 100644
index 16fe87b..0000000
--- a/rand/rand_xoshiro/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
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diff --git a/rand/rand_xoshiro/LICENSE-MIT b/rand/rand_xoshiro/LICENSE-MIT
deleted file mode 100644
index a5e040c..0000000
--- a/rand/rand_xoshiro/LICENSE-MIT
+++ /dev/null
@@ -1,25 +0,0 @@
-Copyright (c) 2018 Developers of the Rand project
-
-Permission is hereby granted, free of charge, to any
-person obtaining a copy of this software and associated
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-publish, distribute, sublicense, and/or sell copies of
-the Software, and to permit persons to whom the Software
-is furnished to do so, subject to the following
-conditions:
-
-The above copyright notice and this permission notice
-shall be included in all copies or substantial portions
-of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF
-ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED
-TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
-PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
-SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR
-IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-DEALINGS IN THE SOFTWARE.
diff --git a/rand/rand_xoshiro/README.md b/rand/rand_xoshiro/README.md
deleted file mode 100644
index 1c02992..0000000
--- a/rand/rand_xoshiro/README.md
+++ /dev/null
@@ -1,34 +0,0 @@
-# rand_xoshiro
-
-[](https://travis-ci.org/rust-random/rand)
-[](https://ci.appveyor.com/project/rust-random/rand)
-[](https://crates.io/crates/rand_xoshiro)
-[](https://rust-random.github.io/book/)
-[](https://rust-random.github.io/rand/rand_xoshiro)
-[](https://docs.rs/rand_xoshiro)
-[](https://github.com/rust-random/rand#rust-version-requirements)
-
-Rust implementation of the [xoshiro, xoroshiro and splitmix64](http://xoshiro.di.unimi.it) random number generators.
-
-This crate depends on [rand_core](https://crates.io/crates/rand_core) and is
-part of the [Rand project](https://github.com/rust-random/rand).
-
-Links:
-
-- [API documentation (master)](https://rust-random.github.io/rand/rand_xoshiro)
-- [API documentation (docs.rs)](https://docs.rs/rand_xoshiro)
-- [Changelog](https://github.com/rust-random/rand/blob/master/rand_xoshiro/CHANGELOG.md)
-
-## Crate Features
-
-`rand_xoshiro` is no_std compatible by default.
-
-The `serde1` feature includes implementations of `Serialize` and `Deserialize` for the included RNGs.
-
-## License
-
-`rand_xoshiro` is distributed under the terms of both the MIT license and the
-Apache License (Version 2.0).
-
-See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT), and
-[COPYRIGHT](COPYRIGHT) for details.
diff --git a/rand/rand_xoshiro/src/common.rs b/rand/rand_xoshiro/src/common.rs
deleted file mode 100644
index b188dd6..0000000
--- a/rand/rand_xoshiro/src/common.rs
+++ /dev/null
@@ -1,243 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-/// Initialize a RNG from a `u64` seed using `SplitMix64`.
-macro_rules! from_splitmix {
- ($seed:expr) => { {
- let mut rng = crate::SplitMix64::seed_from_u64($seed);
- Self::from_rng(&mut rng).unwrap()
- } }
-}
-
-/// Apply the ** scrambler used by some RNGs from the xoshiro family.
-macro_rules! starstar_u64 {
- ($x:expr) => {
- $x.wrapping_mul(5).rotate_left(7).wrapping_mul(9)
- }
-}
-
-/// Apply the ** scrambler used by some RNGs from the xoshiro family.
-macro_rules! starstar_u32 {
- ($x:expr) => {
- $x.wrapping_mul(0x9E3779BB).rotate_left(5).wrapping_mul(5)
- }
-}
-
-/// Implement a jump function for an RNG from the xoshiro family.
-macro_rules! impl_jump {
- (u32, $self:expr, [$j0:expr, $j1:expr]) => {
- const JUMP: [u32; 2] = [$j0, $j1];
- let mut s0 = 0;
- let mut s1 = 0;
- for j in &JUMP {
- for b in 0..32 {
- if (j & 1 << b) != 0 {
- s0 ^= $self.s0;
- s1 ^= $self.s1;
- }
- $self.next_u32();
- }
- }
- $self.s0 = s0;
- $self.s1 = s1;
- };
- (u64, $self:expr, [$j0:expr, $j1:expr]) => {
- const JUMP: [u64; 2] = [$j0, $j1];
- let mut s0 = 0;
- let mut s1 = 0;
- for j in &JUMP {
- for b in 0..64 {
- if (j & 1 << b) != 0 {
- s0 ^= $self.s0;
- s1 ^= $self.s1;
- }
- $self.next_u64();
- }
- }
- $self.s0 = s0;
- $self.s1 = s1;
- };
- (u32, $self:expr, [$j0:expr, $j1:expr, $j2:expr, $j3:expr]) => {
- const JUMP: [u32; 4] = [$j0, $j1, $j2, $j3];
- let mut s0 = 0;
- let mut s1 = 0;
- let mut s2 = 0;
- let mut s3 = 0;
- for j in &JUMP {
- for b in 0..32 {
- if (j & 1 << b) != 0 {
- s0 ^= $self.s[0];
- s1 ^= $self.s[1];
- s2 ^= $self.s[2];
- s3 ^= $self.s[3];
- }
- $self.next_u32();
- }
- }
- $self.s[0] = s0;
- $self.s[1] = s1;
- $self.s[2] = s2;
- $self.s[3] = s3;
- };
- (u64, $self:expr, [$j0:expr, $j1:expr, $j2:expr, $j3:expr]) => {
- const JUMP: [u64; 4] = [$j0, $j1, $j2, $j3];
- let mut s0 = 0;
- let mut s1 = 0;
- let mut s2 = 0;
- let mut s3 = 0;
- for j in &JUMP {
- for b in 0..64 {
- if (j & 1 << b) != 0 {
- s0 ^= $self.s[0];
- s1 ^= $self.s[1];
- s2 ^= $self.s[2];
- s3 ^= $self.s[3];
- }
- $self.next_u64();
- }
- }
- $self.s[0] = s0;
- $self.s[1] = s1;
- $self.s[2] = s2;
- $self.s[3] = s3;
- };
- (u64, $self:expr, [$j0:expr, $j1:expr, $j2:expr, $j3:expr,
- $j4:expr, $j5:expr, $j6:expr, $j7:expr]) => {
- const JUMP: [u64; 8] = [$j0, $j1, $j2, $j3, $j4, $j5, $j6, $j7];
- let mut s = [0; 8];
- for j in &JUMP {
- for b in 0..64 {
- if (j & 1 << b) != 0 {
- s[0] ^= $self.s[0];
- s[1] ^= $self.s[1];
- s[2] ^= $self.s[2];
- s[3] ^= $self.s[3];
- s[4] ^= $self.s[4];
- s[5] ^= $self.s[5];
- s[6] ^= $self.s[6];
- s[7] ^= $self.s[7];
- }
- $self.next_u64();
- }
- }
- $self.s = s;
- };
-}
-
-/// Implement the xoroshiro iteration.
-macro_rules! impl_xoroshiro_u32 {
- ($self:expr) => {
- $self.s1 ^= $self.s0;
- $self.s0 = $self.s0.rotate_left(26) ^ $self.s1 ^ ($self.s1 << 9);
- $self.s1 = $self.s1.rotate_left(13);
- }
-}
-
-/// Implement the xoroshiro iteration.
-macro_rules! impl_xoroshiro_u64 {
- ($self:expr) => {
- $self.s1 ^= $self.s0;
- $self.s0 = $self.s0.rotate_left(24) ^ $self.s1 ^ ($self.s1 << 16);
- $self.s1 = $self.s1.rotate_left(37);
- }
-}
-
-/// Implement the xoshiro iteration for `u32` output.
-macro_rules! impl_xoshiro_u32 {
- ($self:expr) => {
- let t = $self.s[1] << 9;
-
- $self.s[2] ^= $self.s[0];
- $self.s[3] ^= $self.s[1];
- $self.s[1] ^= $self.s[2];
- $self.s[0] ^= $self.s[3];
-
- $self.s[2] ^= t;
-
- $self.s[3] = $self.s[3].rotate_left(11);
- }
-}
-
-/// Implement the xoshiro iteration for `u64` output.
-macro_rules! impl_xoshiro_u64 {
- ($self:expr) => {
- let t = $self.s[1] << 17;
-
- $self.s[2] ^= $self.s[0];
- $self.s[3] ^= $self.s[1];
- $self.s[1] ^= $self.s[2];
- $self.s[0] ^= $self.s[3];
-
- $self.s[2] ^= t;
-
- $self.s[3] = $self.s[3].rotate_left(45);
- }
-}
-
-/// Implement the large-state xoshiro iteration.
-macro_rules! impl_xoshiro_large {
- ($self:expr) => {
- let t = $self.s[1] << 11;
-
- $self.s[2] ^= $self.s[0];
- $self.s[5] ^= $self.s[1];
- $self.s[1] ^= $self.s[2];
- $self.s[7] ^= $self.s[3];
- $self.s[3] ^= $self.s[4];
- $self.s[4] ^= $self.s[5];
- $self.s[0] ^= $self.s[6];
- $self.s[6] ^= $self.s[7];
-
- $self.s[6] ^= t;
-
- $self.s[7] = $self.s[7].rotate_left(21);
- }
-}
-
-/// Map an all-zero seed to a different one.
-macro_rules! deal_with_zero_seed {
- ($seed:expr, $Self:ident) => {
- if $seed.iter().all(|&x| x == 0) {
- return $Self::seed_from_u64(0);
- }
- }
-}
-
-/// 512-bit seed for a generator.
-///
-/// This wrapper is necessary, because some traits required for a seed are not
-/// implemented on large arrays.
-#[derive(Clone)]
-pub struct Seed512(pub [u8; 64]);
-
-use core;
-impl Seed512 {
- /// Return an iterator over the seed.
- pub fn iter(&self) -> core::slice::Iter<u8> {
- self.0.iter()
- }
-}
-
-impl core::fmt::Debug for Seed512 {
- fn fmt(&self, f: &mut core::fmt::Formatter) -> core::fmt::Result {
- self.0[..].fmt(f)
- }
-}
-
-impl Default for Seed512 {
- fn default() -> Seed512 {
- Seed512([0; 64])
- }
-}
-
-impl AsMut<[u8]> for Seed512 {
- fn as_mut(&mut self) -> &mut [u8] {
- &mut self.0
- }
-}
-
diff --git a/rand/rand_xoshiro/src/lib.rs b/rand/rand_xoshiro/src/lib.rs
deleted file mode 100644
index 3047e92..0000000
--- a/rand/rand_xoshiro/src/lib.rs
+++ /dev/null
@@ -1,94 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! This crate implements the [xoshiro] family of pseudorandom number generators
-//! designed by David Blackman and Sebastiano Vigna. They feature high
-//! perfomance and a small state and superseed the previous xorshift-based
-//! generators. However, they are no cryptographically secure and their output
-//! can be predicted by observing a few samples.
-//!
-//! The following generators are implemented:
-//!
-//! # 64-bit generators
-//! - [`Xoshiro256StarStar`]: Recommended for all purposes. Excellent speed and
-//! a state space (256 bits) large enough for any parallel application.
-//! - [`Xoshiro256Plus`]: Recommended for generating 64-bit floating-point
-//! numbers. About 15% faster than `Xoshiro256StarStar`, but has a [low linear
-//! complexity] in the lowest bits (which are discarded when generating
-//! floats), making it fail linearity tests. This is unlikely to have any
-//! impact in practise.
-//! - [`Xoroshiro128StarStar`]: An alternative to `Xoshiro256StarStar`, having
-//! the same speed but using half the state. Only suited for low-scale parallel
-//! applications.
-//! - [`Xoroshiro128Plus`]: An alternative to `Xoshiro256Plus`, having the same
-//! speed but using half the state. Only suited for low-scale parallel
-//! applications. Has a [low linear complexity] in the lowest bits (which are
-//! discarded when generating floats), making it fail linearity tests. This is
-//! unlikely to have any impact in practise.
-//! - [`Xoshiro512StarStar`]: An alternative to `Xoshiro256StarStar` with more
-//! state and the same speed.
-//! - [`Xoshiro512Plus`]: An alternative to `Xoshiro512Plus` with more
-//! state and the same speed. Has a [low linear complexity] in the lowest bits
-//! (which are discarded when generating floats), making it fail linearity
-//! tests. This is unlikely to have any impact in practise.
-//! - [`SplitMix64`]: Recommended for initializing generators of the xoshiro
-//! familiy from a 64-bit seed. Used for implementing `seed_from_u64`.
-//!
-//! # 32-bit generators
-//! - [`Xoshiro128StarStar`]: Recommended for all purposes. Excellent speed.
-//! - [`Xoshiro128Plus`]: Recommended for generating 32-bit floating-point
-//! numbers. Faster than `Xoshiro128StarStar`, but has a [low linear
-//! complexity] in the lowest bits (which are discarded when generating
-//! floats), making it fail linearity tests. This is unlikely to have any
-//! impact in practise.
-//! - [`Xoroshiro64StarStar`]: An alternative to `Xoshiro128StarStar`, having
-//! the same speed but using half the state.
-//! - [`Xoroshiro64Star`]: An alternative to `Xoshiro128Plus`, having the
-//! same speed but using half the state. Has a [low linear complexity] in the
-//! lowest bits (which are discarded when generating floats), making it fail
-//! linearity tests. This is unlikely to have any impact in practise.
-//!
-//! [xoshiro]: http://xoshiro.di.unimi.it/
-//! [low linear complexity]: http://xoshiro.di.unimi.it/lowcomp.php
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
- html_favicon_url = "https://www.rust-lang.org/favicon.ico",
- html_root_url = "https://docs.rs/rand_xoshiro/0.3.1")]
-
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-#![allow(clippy::unreadable_literal)]
-#![no_std]
-
-#[macro_use]
-mod common;
-mod splitmix64;
-mod xoshiro128starstar;
-mod xoshiro128plus;
-mod xoshiro256starstar;
-mod xoshiro256plus;
-mod xoshiro512starstar;
-mod xoshiro512plus;
-mod xoroshiro128plus;
-mod xoroshiro128starstar;
-mod xoroshiro64starstar;
-mod xoroshiro64star;
-
-pub use rand_core;
-pub use splitmix64::SplitMix64;
-pub use xoshiro128starstar::Xoshiro128StarStar;
-pub use xoshiro128plus::Xoshiro128Plus;
-pub use xoshiro256starstar::Xoshiro256StarStar;
-pub use xoshiro256plus::Xoshiro256Plus;
-pub use common::Seed512;
-pub use xoshiro512starstar::Xoshiro512StarStar;
-pub use xoshiro512plus::Xoshiro512Plus;
-pub use xoroshiro128plus::Xoroshiro128Plus;
-pub use xoroshiro128starstar::Xoroshiro128StarStar;
-pub use xoroshiro64starstar::Xoroshiro64StarStar;
-pub use xoroshiro64star::Xoroshiro64Star;
diff --git a/rand/rand_xoshiro/src/splitmix64.rs b/rand/rand_xoshiro/src/splitmix64.rs
deleted file mode 100644
index 3a41450..0000000
--- a/rand/rand_xoshiro/src/splitmix64.rs
+++ /dev/null
@@ -1,149 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core::le::read_u64_into;
-use rand_core::impls::fill_bytes_via_next;
-use rand_core::{RngCore, SeedableRng, Error};
-
-/// A splitmix64 random number generator.
-///
-/// The splitmix algorithm is not suitable for cryptographic purposes, but is
-/// very fast and has a 64 bit state.
-///
-/// The algorithm used here is translated from [the `splitmix64.c`
-/// reference source code](http://xoshiro.di.unimi.it/splitmix64.c) by
-/// Sebastiano Vigna. For `next_u32`, a more efficient mixing function taken
-/// from [`dsiutils`](http://dsiutils.di.unimi.it/) is used.
-#[allow(missing_copy_implementations)]
-#[derive(Debug, Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct SplitMix64 {
- x: u64,
-}
-
-const PHI: u64 = 0x9e3779b97f4a7c15;
-
-impl RngCore for SplitMix64 {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.x = self.x.wrapping_add(PHI);
- let mut z = self.x;
- // David Stafford's
- // (http://zimbry.blogspot.com/2011/09/better-bit-mixing-improving-on.html)
- // "Mix4" variant of the 64-bit finalizer in Austin Appleby's
- // MurmurHash3 algorithm.
- z = (z ^ (z >> 33)).wrapping_mul(0x62A9D9ED799705F5);
- z = (z ^ (z >> 28)).wrapping_mul(0xCB24D0A5C88C35B3);
- (z >> 32) as u32
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- self.x = self.x.wrapping_add(PHI);
- let mut z = self.x;
- z = (z ^ (z >> 30)).wrapping_mul(0xbf58476d1ce4e5b9);
- z = (z ^ (z >> 27)).wrapping_mul(0x94d049bb133111eb);
- z ^ (z >> 31)
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-impl SeedableRng for SplitMix64 {
- type Seed = [u8; 8];
-
- /// Create a new `SplitMix64`.
- fn from_seed(seed: [u8; 8]) -> SplitMix64 {
- let mut state = [0; 1];
- read_u64_into(&seed, &mut state);
- SplitMix64 {
- x: state[0],
- }
- }
-
- /// Seed a `SplitMix64` from a `u64`.
- fn seed_from_u64(seed: u64) -> SplitMix64 {
- SplitMix64::from_seed(seed.to_le_bytes())
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn reference() {
- let mut rng = SplitMix64::seed_from_u64(1477776061723855037);
- // These values were produced with the reference implementation:
- // http://xoshiro.di.unimi.it/splitmix64.c
- let expected : [u64 ; 50]= [
- 1985237415132408290, 2979275885539914483, 13511426838097143398,
- 8488337342461049707, 15141737807933549159, 17093170987380407015,
- 16389528042912955399, 13177319091862933652, 10841969400225389492,
- 17094824097954834098, 3336622647361835228, 9678412372263018368,
- 11111587619974030187, 7882215801036322410, 5709234165213761869,
- 7799681907651786826, 4616320717312661886, 4251077652075509767,
- 7836757050122171900, 5054003328188417616, 12919285918354108358,
- 16477564761813870717, 5124667218451240549, 18099554314556827626,
- 7603784838804469118, 6358551455431362471, 3037176434532249502,
- 3217550417701719149, 9958699920490216947, 5965803675992506258,
- 12000828378049868312, 12720568162811471118, 245696019213873792,
- 8351371993958923852, 14378754021282935786, 5655432093647472106,
- 5508031680350692005, 8515198786865082103, 6287793597487164412,
- 14963046237722101617, 3630795823534910476, 8422285279403485710,
- 10554287778700714153, 10871906555720704584, 8659066966120258468,
- 9420238805069527062, 10338115333623340156, 13514802760105037173,
- 14635952304031724449, 15419692541594102413,
- ];
- for &e in expected.iter() {
- assert_eq!(rng.next_u64(), e);
- }
- }
-
- #[test]
- fn next_u32() {
- let mut rng = SplitMix64::seed_from_u64(10);
- // These values were produced with the reference implementation:
- // http://dsiutils.di.unimi.it/dsiutils-2.5.1-src.tar.gz
- let expected : [u32 ; 100]= [
- 3930361779, 4016923089, 4113052479, 925926767, 1755287528,
- 802865554, 954171070, 3724185978, 173676273, 1414488795, 12664133,
- 1784889697, 1303817078, 261610523, 941280008, 2571813643,
- 2954453492, 378291111, 2546873158, 3923319175, 645257028,
- 3881821278, 2681538690, 3037029984, 1999958137, 1853970361,
- 2989951788, 2126166628, 839962987, 3989679659, 3656977858,
- 684284364, 1673258011, 170979192, 3037622326, 1600748179,
- 1780764218, 1141430714, 4139736875, 3336905707, 2262051600,
- 3830850262, 2430765325, 1073032139, 1668888979, 2716938970,
- 4102420032, 40305196, 386350562, 2754480591, 622869439, 2129598760,
- 2306038241, 4218338739, 412298926, 3453855056, 3061469690,
- 4284292697, 994843708, 1591016681, 414726151, 1238182607, 18073498,
- 1237631493, 351884714, 2347486264, 2488990876, 802846256, 645670443,
- 957607012, 3126589776, 1966356370, 3036485766, 868696717,
- 2808613630, 2070968151, 1025536863, 1743949425, 466212687,
- 2994327271, 209776458, 1246125124, 3344380309, 2203947859,
- 968313105, 2805485302, 197484837, 3472483632, 3931823935,
- 3288490351, 4165666529, 3671080416, 689542830, 1272555356,
- 1039141475, 3984640460, 4142959054, 2252788890, 2459379590,
- 991872507,
- ];
- for &e in expected.iter() {
- assert_eq!(rng.next_u32(), e);
- }
- }
-}
diff --git a/rand/rand_xoshiro/src/xoroshiro128plus.rs b/rand/rand_xoshiro/src/xoroshiro128plus.rs
deleted file mode 100644
index a7b4ebc..0000000
--- a/rand/rand_xoshiro/src/xoroshiro128plus.rs
+++ /dev/null
@@ -1,130 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core;
-use rand_core::le::read_u64_into;
-use rand_core::impls::fill_bytes_via_next;
-use rand_core::{RngCore, SeedableRng};
-
-/// A xoroshiro128+ random number generator.
-///
-/// The xoroshiro128+ algorithm is not suitable for cryptographic purposes, but
-/// is very fast and has good statistical properties, besides a low linear
-/// complexity in the lowest bits.
-///
-/// The algorithm used here is translated from [the `xoroshiro128plus.c`
-/// reference source code](http://xoshiro.di.unimi.it/xoroshiro128plus.c) by
-/// David Blackman and Sebastiano Vigna.
-#[allow(missing_copy_implementations)]
-#[derive(Debug, Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Xoroshiro128Plus {
- s0: u64,
- s1: u64,
-}
-
-impl Xoroshiro128Plus {
- /// Jump forward, equivalently to 2^64 calls to `next_u64()`.
- ///
- /// This can be used to generate 2^64 non-overlapping subsequences for
- /// parallel computations.
- ///
- /// ```
- /// use rand_xoshiro::rand_core::SeedableRng;
- /// use rand_xoshiro::Xoroshiro128Plus;
- ///
- /// let rng1 = Xoroshiro128Plus::seed_from_u64(0);
- /// let mut rng2 = rng1.clone();
- /// rng2.jump();
- /// let mut rng3 = rng2.clone();
- /// rng3.jump();
- /// ```
- pub fn jump(&mut self) {
- impl_jump!(u64, self, [0xdf900294d8f554a5, 0x170865df4b3201fc]);
- }
-
- /// Jump forward, equivalently to 2^96 calls to `next_u64()`.
- ///
- /// This can be used to generate 2^32 starting points, from each of which
- /// `jump()` will generate 2^32 non-overlapping subsequences for parallel
- /// distributed computations.
- pub fn long_jump(&mut self) {
- impl_jump!(u64, self, [0xd2a98b26625eee7b, 0xdddf9b1090aa7ac1]);
- }
-}
-
-impl RngCore for Xoroshiro128Plus {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- // The two lowest bits have some linear dependencies, so we use the
- // upper bits instead.
- (self.next_u64() >> 32) as u32
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- let r = self.s0.wrapping_add(self.s1);
- impl_xoroshiro_u64!(self);
- r
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), rand_core::Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-impl SeedableRng for Xoroshiro128Plus {
- type Seed = [u8; 16];
-
- /// Create a new `Xoroshiro128Plus`. If `seed` is entirely 0, it will be
- /// mapped to a different seed.
- fn from_seed(seed: [u8; 16]) -> Xoroshiro128Plus {
- deal_with_zero_seed!(seed, Self);
- let mut s = [0; 2];
- read_u64_into(&seed, &mut s);
-
- Xoroshiro128Plus {
- s0: s[0],
- s1: s[1],
- }
- }
-
- /// Seed a `Xoroshiro128Plus` from a `u64` using `SplitMix64`.
- fn seed_from_u64(seed: u64) -> Xoroshiro128Plus {
- from_splitmix!(seed)
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn reference() {
- let mut rng = Xoroshiro128Plus::from_seed(
- [1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0]);
- // These values were produced with the reference implementation:
- // http://xoshiro.di.unimi.it/xoshiro128starstar.c
- let expected = [
- 3, 412333834243, 2360170716294286339, 9295852285959843169,
- 2797080929874688578, 6019711933173041966, 3076529664176959358,
- 3521761819100106140, 7493067640054542992, 920801338098114767,
- ];
- for &e in &expected {
- assert_eq!(rng.next_u64(), e);
- }
- }
-}
diff --git a/rand/rand_xoshiro/src/xoroshiro128starstar.rs b/rand/rand_xoshiro/src/xoroshiro128starstar.rs
deleted file mode 100644
index 21823f5..0000000
--- a/rand/rand_xoshiro/src/xoroshiro128starstar.rs
+++ /dev/null
@@ -1,127 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core;
-use rand_core::le::read_u64_into;
-use rand_core::impls::fill_bytes_via_next;
-use rand_core::{RngCore, SeedableRng};
-
-/// A xoroshiro128** random number generator.
-///
-/// The xoroshiro128** algorithm is not suitable for cryptographic purposes, but
-/// is very fast and has excellent statistical properties.
-///
-/// The algorithm used here is translated from [the `xoroshiro128starstar.c`
-/// reference source code](http://xoshiro.di.unimi.it/xoroshiro128starstar.c) by
-/// David Blackman and Sebastiano Vigna.
-#[allow(missing_copy_implementations)]
-#[derive(Debug, Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Xoroshiro128StarStar {
- s0: u64,
- s1: u64,
-}
-
-impl Xoroshiro128StarStar {
- /// Jump forward, equivalently to 2^64 calls to `next_u64()`.
- ///
- /// This can be used to generate 2^64 non-overlapping subsequences for
- /// parallel computations.
- ///
- /// ```
- /// use rand_xoshiro::rand_core::SeedableRng;
- /// use rand_xoshiro::Xoroshiro128StarStar;
- ///
- /// let rng1 = Xoroshiro128StarStar::seed_from_u64(0);
- /// let mut rng2 = rng1.clone();
- /// rng2.jump();
- /// let mut rng3 = rng2.clone();
- /// rng3.jump();
- /// ```
- pub fn jump(&mut self) {
- impl_jump!(u64, self, [0xdf900294d8f554a5, 0x170865df4b3201fc]);
- }
-
- /// Jump forward, equivalently to 2^96 calls to `next_u64()`.
- ///
- /// This can be used to generate 2^32 starting points, from each of which
- /// `jump()` will generate 2^32 non-overlapping subsequences for parallel
- /// distributed computations.
- pub fn long_jump(&mut self) {
- impl_jump!(u64, self, [0xd2a98b26625eee7b, 0xdddf9b1090aa7ac1]);
- }
-}
-
-impl RngCore for Xoroshiro128StarStar {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.next_u64() as u32
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- let r = starstar_u64!(self.s0);
- impl_xoroshiro_u64!(self);
- r
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), rand_core::Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-impl SeedableRng for Xoroshiro128StarStar {
- type Seed = [u8; 16];
-
- /// Create a new `Xoroshiro128StarStar`. If `seed` is entirely 0, it will be
- /// mapped to a different seed.
- fn from_seed(seed: [u8; 16]) -> Xoroshiro128StarStar {
- deal_with_zero_seed!(seed, Self);
- let mut s = [0; 2];
- read_u64_into(&seed, &mut s);
-
- Xoroshiro128StarStar {
- s0: s[0],
- s1: s[1],
- }
- }
-
- /// Seed a `Xoroshiro128StarStar` from a `u64` using `SplitMix64`.
- fn seed_from_u64(seed: u64) -> Xoroshiro128StarStar {
- from_splitmix!(seed)
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn reference() {
- let mut rng = Xoroshiro128StarStar::from_seed(
- [1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0]);
- // These values were produced with the reference implementation:
- // http://xoshiro.di.unimi.it/xoshiro128starstar.c
- let expected = [
- 5760, 97769243520, 9706862127477703552, 9223447511460779954,
- 8358291023205304566, 15695619998649302768, 8517900938696309774,
- 16586480348202605369, 6959129367028440372, 16822147227405758281,
- ];
- for &e in &expected {
- assert_eq!(rng.next_u64(), e);
- }
- }
-}
diff --git a/rand/rand_xoshiro/src/xoroshiro64star.rs b/rand/rand_xoshiro/src/xoroshiro64star.rs
deleted file mode 100644
index 6bb708a..0000000
--- a/rand/rand_xoshiro/src/xoroshiro64star.rs
+++ /dev/null
@@ -1,102 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core;
-use rand_core::le::read_u32_into;
-use rand_core::impls::{fill_bytes_via_next, next_u64_via_u32};
-use rand_core::{RngCore, SeedableRng};
-
-/// A xoroshiro64* random number generator.
-///
-/// The xoroshiro64* algorithm is not suitable for cryptographic purposes, but
-/// is very fast and has good statistical properties, besides a low linear
-/// complexity in the lowest bits.
-///
-/// The algorithm used here is translated from [the `xoroshiro64star.c`
-/// reference source code](http://xoshiro.di.unimi.it/xoroshiro64star.c) by
-/// David Blackman and Sebastiano Vigna.
-#[allow(missing_copy_implementations)]
-#[derive(Debug, Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Xoroshiro64Star {
- s0: u32,
- s1: u32,
-}
-
-impl RngCore for Xoroshiro64Star {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- let r = self.s0.wrapping_mul(0x9E3779BB);
- impl_xoroshiro_u32!(self);
- r
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- next_u64_via_u32(self)
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), rand_core::Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-impl SeedableRng for Xoroshiro64Star {
- type Seed = [u8; 8];
-
- /// Create a new `Xoroshiro64Star`. If `seed` is entirely 0, it will be
- /// mapped to a different seed.
- fn from_seed(seed: [u8; 8]) -> Xoroshiro64Star {
- deal_with_zero_seed!(seed, Self);
- let mut s = [0; 2];
- read_u32_into(&seed, &mut s);
-
- Xoroshiro64Star {
- s0: s[0],
- s1: s[1],
- }
- }
-
- /// Seed a `Xoroshiro64Star` from a `u64` using `SplitMix64`.
- fn seed_from_u64(seed: u64) -> Xoroshiro64Star {
- from_splitmix!(seed)
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn reference() {
- let mut rng = Xoroshiro64Star::from_seed([1, 0, 0, 0, 2, 0, 0, 0]);
- // These values were produced with the reference implementation:
- // http://xoshiro.di.unimi.it/xoshiro64star.c
- let expected = [
- 2654435771, 327208753, 4063491769, 4259754937, 261922412, 168123673,
- 552743735, 1672597395, 1031040050, 2755315674,
- ];
- for &e in &expected {
- assert_eq!(rng.next_u32(), e);
- }
- }
-
- #[test]
- fn zero_seed() {
- let mut rng = Xoroshiro64Star::seed_from_u64(0);
- assert_ne!(rng.next_u64(), 0);
- }
-}
diff --git a/rand/rand_xoshiro/src/xoroshiro64starstar.rs b/rand/rand_xoshiro/src/xoroshiro64starstar.rs
deleted file mode 100644
index 8e1aea1..0000000
--- a/rand/rand_xoshiro/src/xoroshiro64starstar.rs
+++ /dev/null
@@ -1,101 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core;
-use rand_core::le::read_u32_into;
-use rand_core::impls::{fill_bytes_via_next, next_u64_via_u32};
-use rand_core::{RngCore, SeedableRng};
-
-/// A xoroshiro64** random number generator.
-///
-/// The xoshiro64** algorithm is not suitable for cryptographic purposes, but
-/// is very fast and has excellent statistical properties.
-///
-/// The algorithm used here is translated from [the `xoroshiro64starstar.c`
-/// reference source code](http://xoshiro.di.unimi.it/xoroshiro64starstar.c) by
-/// David Blackman and Sebastiano Vigna.
-#[allow(missing_copy_implementations)]
-#[derive(Debug, Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Xoroshiro64StarStar {
- s0: u32,
- s1: u32,
-}
-
-impl RngCore for Xoroshiro64StarStar {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- let r = starstar_u32!(self.s0);
- impl_xoroshiro_u32!(self);
- r
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- next_u64_via_u32(self)
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), rand_core::Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-impl SeedableRng for Xoroshiro64StarStar {
- type Seed = [u8; 8];
-
- /// Create a new `Xoroshiro64StarStar`. If `seed` is entirely 0, it will be
- /// mapped to a different seed.
- fn from_seed(seed: [u8; 8]) -> Xoroshiro64StarStar {
- deal_with_zero_seed!(seed, Self);
- let mut s = [0; 2];
- read_u32_into(&seed, &mut s);
-
- Xoroshiro64StarStar {
- s0: s[0],
- s1: s[1],
- }
- }
-
- /// Seed a `Xoroshiro64StarStar` from a `u64` using `SplitMix64`.
- fn seed_from_u64(seed: u64) -> Xoroshiro64StarStar {
- from_splitmix!(seed)
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn reference() {
- let mut rng = Xoroshiro64StarStar::from_seed([1, 0, 0, 0, 2, 0, 0, 0]);
- // These values were produced with the reference implementation:
- // http://xoshiro.di.unimi.it/xoshiro64starstar.c
- let expected = [
- 3802928447, 813792938, 1618621494, 2955957307, 3252880261,
- 1129983909, 2539651700, 1327610908, 1757650787, 2763843748,
- ];
- for &e in &expected {
- assert_eq!(rng.next_u32(), e);
- }
- }
-
- #[test]
- fn zero_seed() {
- let mut rng = Xoroshiro64StarStar::seed_from_u64(0);
- assert_ne!(rng.next_u64(), 0);
- }
-}
diff --git a/rand/rand_xoshiro/src/xoshiro128plus.rs b/rand/rand_xoshiro/src/xoshiro128plus.rs
deleted file mode 100644
index 7cbd612..0000000
--- a/rand/rand_xoshiro/src/xoshiro128plus.rs
+++ /dev/null
@@ -1,112 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core::impls::{next_u64_via_u32, fill_bytes_via_next};
-use rand_core::le::read_u32_into;
-use rand_core::{SeedableRng, RngCore, Error};
-
-/// A xoshiro128+ random number generator.
-///
-/// The xoshiro128+ algorithm is not suitable for cryptographic purposes, but
-/// is very fast and has good statistical properties, besides a low linear
-/// complexity in the lowest bits.
-///
-/// The algorithm used here is translated from [the `xoshiro128starstar.c`
-/// reference source code](http://xoshiro.di.unimi.it/xoshiro128starstar.c) by
-/// David Blackman and Sebastiano Vigna.
-#[derive(Debug, Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Xoshiro128Plus {
- s: [u32; 4],
-}
-
-impl Xoshiro128Plus {
- /// Jump forward, equivalently to 2^64 calls to `next_u32()`.
- ///
- /// This can be used to generate 2^64 non-overlapping subsequences for
- /// parallel computations.
- ///
- /// ```
- /// use rand_xoshiro::rand_core::SeedableRng;
- /// use rand_xoshiro::Xoroshiro128StarStar;
- ///
- /// let rng1 = Xoroshiro128StarStar::seed_from_u64(0);
- /// let mut rng2 = rng1.clone();
- /// rng2.jump();
- /// let mut rng3 = rng2.clone();
- /// rng3.jump();
- /// ```
- pub fn jump(&mut self) {
- impl_jump!(u32, self, [0x8764000b, 0xf542d2d3, 0x6fa035c3, 0x77f2db5b]);
- }
-}
-
-impl SeedableRng for Xoshiro128Plus {
- type Seed = [u8; 16];
-
- /// Create a new `Xoshiro128Plus`. If `seed` is entirely 0, it will be
- /// mapped to a different seed.
- #[inline]
- fn from_seed(seed: [u8; 16]) -> Xoshiro128Plus {
- deal_with_zero_seed!(seed, Self);
- let mut state = [0; 4];
- read_u32_into(&seed, &mut state);
- Xoshiro128Plus { s: state }
- }
-
- /// Seed a `Xoshiro128Plus` from a `u64` using `SplitMix64`.
- fn seed_from_u64(seed: u64) -> Xoshiro128Plus {
- from_splitmix!(seed)
- }
-}
-
-impl RngCore for Xoshiro128Plus {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- let result_plus = self.s[0].wrapping_add(self.s[3]);
- impl_xoshiro_u32!(self);
- result_plus
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- next_u64_via_u32(self)
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn reference() {
- let mut rng = Xoshiro128Plus::from_seed(
- [1, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 4, 0, 0, 0]);
- // These values were produced with the reference implementation:
- // http://xoshiro.di.unimi.it/xoshiro128plus.c
- let expected = [
- 5, 12295, 25178119, 27286542, 39879690, 1140358681, 3276312097,
- 4110231701, 399823256, 2144435200,
- ];
- for &e in &expected {
- assert_eq!(rng.next_u32(), e);
- }
- }
-}
diff --git a/rand/rand_xoshiro/src/xoshiro128starstar.rs b/rand/rand_xoshiro/src/xoshiro128starstar.rs
deleted file mode 100644
index 7af1e50..0000000
--- a/rand/rand_xoshiro/src/xoshiro128starstar.rs
+++ /dev/null
@@ -1,111 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core::impls::{next_u64_via_u32, fill_bytes_via_next};
-use rand_core::le::read_u32_into;
-use rand_core::{SeedableRng, RngCore, Error};
-
-/// A xoshiro128** random number generator.
-///
-/// The xoshiro128** algorithm is not suitable for cryptographic purposes, but
-/// is very fast and has excellent statistical properties.
-///
-/// The algorithm used here is translated from [the `xoshiro128starstar.c`
-/// reference source code](http://xoshiro.di.unimi.it/xoshiro128starstar.c) by
-/// David Blackman and Sebastiano Vigna.
-#[derive(Debug, Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Xoshiro128StarStar {
- s: [u32; 4],
-}
-
-impl Xoshiro128StarStar {
- /// Jump forward, equivalently to 2^64 calls to `next_u32()`.
- ///
- /// This can be used to generate 2^64 non-overlapping subsequences for
- /// parallel computations.
- ///
- /// ```
- /// use rand_xoshiro::rand_core::SeedableRng;
- /// use rand_xoshiro::Xoroshiro128StarStar;
- ///
- /// let rng1 = Xoroshiro128StarStar::seed_from_u64(0);
- /// let mut rng2 = rng1.clone();
- /// rng2.jump();
- /// let mut rng3 = rng2.clone();
- /// rng3.jump();
- /// ```
- pub fn jump(&mut self) {
- impl_jump!(u32, self, [0x8764000b, 0xf542d2d3, 0x6fa035c3, 0x77f2db5b]);
- }
-}
-
-impl SeedableRng for Xoshiro128StarStar {
- type Seed = [u8; 16];
-
- /// Create a new `Xoshiro128StarStar`. If `seed` is entirely 0, it will be
- /// mapped to a different seed.
- #[inline]
- fn from_seed(seed: [u8; 16]) -> Xoshiro128StarStar {
- deal_with_zero_seed!(seed, Self);
- let mut state = [0; 4];
- read_u32_into(&seed, &mut state);
- Xoshiro128StarStar { s: state }
- }
-
- /// Seed a `Xoshiro128StarStar` from a `u64` using `SplitMix64`.
- fn seed_from_u64(seed: u64) -> Xoshiro128StarStar {
- from_splitmix!(seed)
- }
-}
-
-impl RngCore for Xoshiro128StarStar {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- let result_starstar = starstar_u64!(self.s[0]);
- impl_xoshiro_u32!(self);
- result_starstar
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- next_u64_via_u32(self)
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn reference() {
- let mut rng = Xoshiro128StarStar::from_seed(
- [1, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 4, 0, 0, 0]);
- // These values were produced with the reference implementation:
- // http://xoshiro.di.unimi.it/xoshiro128starstar.c
- let expected = [
- 5760, 40320, 70819200, 3297914139, 2480851620, 1792823698,
- 4118739149, 1251203317, 1581886583, 1721184582,
- ];
- for &e in &expected {
- assert_eq!(rng.next_u32(), e);
- }
- }
-}
diff --git a/rand/rand_xoshiro/src/xoshiro256plus.rs b/rand/rand_xoshiro/src/xoshiro256plus.rs
deleted file mode 100644
index 396f588..0000000
--- a/rand/rand_xoshiro/src/xoshiro256plus.rs
+++ /dev/null
@@ -1,131 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core::impls::fill_bytes_via_next;
-use rand_core::le::read_u64_into;
-use rand_core::{SeedableRng, RngCore, Error};
-
-/// A xoshiro256+ random number generator.
-///
-/// The xoshiro256+ algorithm is not suitable for cryptographic purposes, but
-/// is very fast and has good statistical properties, besides a low linear
-/// complexity in the lowest bits.
-///
-/// The algorithm used here is translated from [the `xoshiro256plus.c`
-/// reference source code](http://xoshiro.di.unimi.it/xoshiro256plus.c) by
-/// David Blackman and Sebastiano Vigna.
-#[derive(Debug, Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Xoshiro256Plus {
- s: [u64; 4],
-}
-
-impl Xoshiro256Plus {
- /// Jump forward, equivalently to 2^128 calls to `next_u64()`.
- ///
- /// This can be used to generate 2^128 non-overlapping subsequences for
- /// parallel computations.
- ///
- /// ```
- /// use rand_xoshiro::rand_core::SeedableRng;
- /// use rand_xoshiro::Xoshiro256Plus;
- ///
- /// let rng1 = Xoshiro256Plus::seed_from_u64(0);
- /// let mut rng2 = rng1.clone();
- /// rng2.jump();
- /// let mut rng3 = rng2.clone();
- /// rng3.jump();
- /// ```
- pub fn jump(&mut self) {
- impl_jump!(u64, self, [
- 0x180ec6d33cfd0aba, 0xd5a61266f0c9392c,
- 0xa9582618e03fc9aa, 0x39abdc4529b1661c
- ]);
- }
-
- /// Jump forward, equivalently to 2^192 calls to `next_u64()`.
- ///
- /// This can be used to generate 2^64 starting points, from each of which
- /// `jump()` will generate 2^64 non-overlapping subsequences for parallel
- /// distributed computations.
- pub fn long_jump(&mut self) {
- impl_jump!(u64, self, [
- 0x76e15d3efefdcbbf, 0xc5004e441c522fb3,
- 0x77710069854ee241, 0x39109bb02acbe635
- ]);
- }
-}
-
-impl SeedableRng for Xoshiro256Plus {
- type Seed = [u8; 32];
-
- /// Create a new `Xoshiro256Plus`. If `seed` is entirely 0, it will be
- /// mapped to a different seed.
- #[inline]
- fn from_seed(seed: [u8; 32]) -> Xoshiro256Plus {
- deal_with_zero_seed!(seed, Self);
- let mut state = [0; 4];
- read_u64_into(&seed, &mut state);
- Xoshiro256Plus { s: state }
- }
-
- /// Seed a `Xoshiro256Plus` from a `u64` using `SplitMix64`.
- fn seed_from_u64(seed: u64) -> Xoshiro256Plus {
- from_splitmix!(seed)
- }
-}
-
-impl RngCore for Xoshiro256Plus {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- // The lowest bits have some linear dependencies, so we use the
- // upper bits instead.
- (self.next_u64() >> 32) as u32
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- let result_plus = self.s[0].wrapping_add(self.s[3]);
- impl_xoshiro_u64!(self);
- result_plus
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn reference() {
- let mut rng = Xoshiro256Plus::from_seed(
- [1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0,
- 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0]);
- // These values were produced with the reference implementation:
- // http://xoshiro.di.unimi.it/xoshiro256plus.c
- let expected = [
- 5, 211106232532999, 211106635186183, 9223759065350669058,
- 9250833439874351877, 13862484359527728515, 2346507365006083650,
- 1168864526675804870, 34095955243042024, 3466914240207415127,
- ];
- for &e in &expected {
- assert_eq!(rng.next_u64(), e);
- }
- }
-}
diff --git a/rand/rand_xoshiro/src/xoshiro256starstar.rs b/rand/rand_xoshiro/src/xoshiro256starstar.rs
deleted file mode 100644
index 2cc2029..0000000
--- a/rand/rand_xoshiro/src/xoshiro256starstar.rs
+++ /dev/null
@@ -1,128 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core::impls::fill_bytes_via_next;
-use rand_core::le::read_u64_into;
-use rand_core::{SeedableRng, RngCore, Error};
-
-/// A xoshiro256** random number generator.
-///
-/// The xoshiro256** algorithm is not suitable for cryptographic purposes, but
-/// is very fast and has excellent statistical properties.
-///
-/// The algorithm used here is translated from [the `xoshiro256starstar.c`
-/// reference source code](http://xoshiro.di.unimi.it/xoshiro256starstar.c) by
-/// David Blackman and Sebastiano Vigna.
-#[derive(Debug, Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Xoshiro256StarStar {
- s: [u64; 4],
-}
-
-impl Xoshiro256StarStar {
- /// Jump forward, equivalently to 2^128 calls to `next_u64()`.
- ///
- /// This can be used to generate 2^128 non-overlapping subsequences for
- /// parallel computations.
- ///
- /// ```
- /// use rand_xoshiro::rand_core::SeedableRng;
- /// use rand_xoshiro::Xoshiro256StarStar;
- ///
- /// let rng1 = Xoshiro256StarStar::seed_from_u64(0);
- /// let mut rng2 = rng1.clone();
- /// rng2.jump();
- /// let mut rng3 = rng2.clone();
- /// rng3.jump();
- /// ```
- pub fn jump(&mut self) {
- impl_jump!(u64, self, [
- 0x180ec6d33cfd0aba, 0xd5a61266f0c9392c,
- 0xa9582618e03fc9aa, 0x39abdc4529b1661c
- ]);
- }
-
- /// Jump forward, equivalently to 2^192 calls to `next_u64()`.
- ///
- /// This can be used to generate 2^64 starting points, from each of which
- /// `jump()` will generate 2^64 non-overlapping subsequences for parallel
- /// distributed computations.
- pub fn long_jump(&mut self) {
- impl_jump!(u64, self, [
- 0x76e15d3efefdcbbf, 0xc5004e441c522fb3,
- 0x77710069854ee241, 0x39109bb02acbe635
- ]);
- }
-}
-
-impl SeedableRng for Xoshiro256StarStar {
- type Seed = [u8; 32];
-
- /// Create a new `Xoshiro256StarStar`. If `seed` is entirely 0, it will be
- /// mapped to a different seed.
- #[inline]
- fn from_seed(seed: [u8; 32]) -> Xoshiro256StarStar {
- deal_with_zero_seed!(seed, Self);
- let mut state = [0; 4];
- read_u64_into(&seed, &mut state);
- Xoshiro256StarStar { s: state }
- }
-
- /// Seed a `Xoshiro256StarStar` from a `u64` using `SplitMix64`.
- fn seed_from_u64(seed: u64) -> Xoshiro256StarStar {
- from_splitmix!(seed)
- }
-}
-
-impl RngCore for Xoshiro256StarStar {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.next_u64() as u32
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- let result_starstar = starstar_u64!(self.s[1]);
- impl_xoshiro_u64!(self);
- result_starstar
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn reference() {
- let mut rng = Xoshiro256StarStar::from_seed(
- [1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0,
- 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0]);
- // These values were produced with the reference implementation:
- // http://xoshiro.di.unimi.it/xoshiro128starstar.c
- let expected = [
- 11520, 0, 1509978240, 1215971899390074240, 1216172134540287360,
- 607988272756665600, 16172922978634559625, 8476171486693032832,
- 10595114339597558777, 2904607092377533576,
- ];
- for &e in &expected {
- assert_eq!(rng.next_u64(), e);
- }
- }
-}
diff --git a/rand/rand_xoshiro/src/xoshiro512plus.rs b/rand/rand_xoshiro/src/xoshiro512plus.rs
deleted file mode 100644
index 4b589f2..0000000
--- a/rand/rand_xoshiro/src/xoshiro512plus.rs
+++ /dev/null
@@ -1,122 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core::impls::fill_bytes_via_next;
-use rand_core::le::read_u64_into;
-use rand_core::{SeedableRng, RngCore, Error};
-
-use crate::Seed512;
-
-/// A xoshiro512+ random number generator.
-///
-/// The xoshiro512+ algorithm is not suitable for cryptographic purposes, but
-/// is very fast and has good statistical properties, besides a low linear
-/// complexity in the lowest bits.
-///
-/// The algorithm used here is translated from [the `xoshiro512plus.c`
-/// reference source code](http://xoshiro.di.unimi.it/xoshiro512plus.c) by
-/// David Blackman and Sebastiano Vigna.
-#[derive(Debug, Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Xoshiro512Plus {
- s: [u64; 8],
-}
-
-impl Xoshiro512Plus {
- /// Jump forward, equivalently to 2^256 calls to `next_u64()`.
- ///
- /// This can be used to generate 2^256 non-overlapping subsequences for
- /// parallel computations.
- ///
- /// ```
- /// use rand_xoshiro::rand_core::SeedableRng;
- /// use rand_xoshiro::Xoshiro512Plus;
- ///
- /// let rng1 = Xoshiro512Plus::seed_from_u64(0);
- /// let mut rng2 = rng1.clone();
- /// rng2.jump();
- /// let mut rng3 = rng2.clone();
- /// rng3.jump();
- /// ```
- pub fn jump(&mut self) {
- impl_jump!(u64, self, [
- 0x33ed89b6e7a353f9, 0x760083d7955323be, 0x2837f2fbb5f22fae,
- 0x4b8c5674d309511c, 0xb11ac47a7ba28c25, 0xf1be7667092bcc1c,
- 0x53851efdb6df0aaf, 0x1ebbc8b23eaf25db
- ]);
- }
-}
-
-impl SeedableRng for Xoshiro512Plus {
- type Seed = Seed512;
-
- /// Create a new `Xoshiro512Plus`. If `seed` is entirely 0, it will be
- /// mapped to a different seed.
- #[inline]
- fn from_seed(seed: Seed512) -> Xoshiro512Plus {
- deal_with_zero_seed!(seed, Self);
- let mut state = [0; 8];
- read_u64_into(&seed.0, &mut state);
- Xoshiro512Plus { s: state }
- }
-
- /// Seed a `Xoshiro512Plus` from a `u64` using `SplitMix64`.
- fn seed_from_u64(seed: u64) -> Xoshiro512Plus {
- from_splitmix!(seed)
- }
-}
-
-impl RngCore for Xoshiro512Plus {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.next_u64() as u32
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- let result_plus = self.s[0].wrapping_add(self.s[2]);
- impl_xoshiro_large!(self);
- result_plus
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn reference() {
- let mut rng = Xoshiro512Plus::from_seed(Seed512(
- [1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0,
- 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0,
- 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0,
- 7, 0, 0, 0, 0, 0, 0, 0, 8, 0, 0, 0, 0, 0, 0, 0]));
- // These values were produced with the reference implementation:
- // http://xoshiro.di.unimi.it/xoshiro512plus.c
- let expected = [
- 4, 8, 4113, 25169936, 52776585412635, 57174648719367,
- 9223482039571869716, 9331471677901559830, 9340533895746033672,
- 14078399799840753678,
- ];
- for &e in &expected {
- assert_eq!(rng.next_u64(), e);
- }
- }
-}
diff --git a/rand/rand_xoshiro/src/xoshiro512starstar.rs b/rand/rand_xoshiro/src/xoshiro512starstar.rs
deleted file mode 100644
index 2db9ac1..0000000
--- a/rand/rand_xoshiro/src/xoshiro512starstar.rs
+++ /dev/null
@@ -1,122 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#[cfg(feature="serde1")] use serde::{Serialize, Deserialize};
-use rand_core::impls::fill_bytes_via_next;
-use rand_core::le::read_u64_into;
-use rand_core::{SeedableRng, RngCore, Error};
-
-use crate::Seed512;
-
-/// A xoshiro512** random number generator.
-///
-/// The xoshiro512** algorithm is not suitable for cryptographic purposes, but
-/// is very fast and has excellent statistical properties.
-///
-/// The algorithm used here is translated from [the `xoshiro512starstar.c`
-/// reference source code](http://xoshiro.di.unimi.it/xoshiro512starstar.c) by
-/// David Blackman and Sebastiano Vigna.
-#[derive(Debug, Clone)]
-#[cfg_attr(feature="serde1", derive(Serialize, Deserialize))]
-pub struct Xoshiro512StarStar {
- s: [u64; 8],
-}
-
-impl Xoshiro512StarStar {
- /// Jump forward, equivalently to 2^256 calls to `next_u64()`.
- ///
- /// This can be used to generate 2^256 non-overlapping subsequences for
- /// parallel computations.
- ///
- /// ```
- /// use rand_xoshiro::rand_core::SeedableRng;
- /// use rand_xoshiro::Xoshiro512StarStar;
- ///
- /// let rng1 = Xoshiro512StarStar::seed_from_u64(0);
- /// let mut rng2 = rng1.clone();
- /// rng2.jump();
- /// let mut rng3 = rng2.clone();
- /// rng3.jump();
- /// ```
- pub fn jump(&mut self) {
- impl_jump!(u64, self, [
- 0x33ed89b6e7a353f9, 0x760083d7955323be, 0x2837f2fbb5f22fae,
- 0x4b8c5674d309511c, 0xb11ac47a7ba28c25, 0xf1be7667092bcc1c,
- 0x53851efdb6df0aaf, 0x1ebbc8b23eaf25db
- ]);
- }
-}
-
-
-impl SeedableRng for Xoshiro512StarStar {
- type Seed = Seed512;
-
- /// Create a new `Xoshiro512StarStar`. If `seed` is entirely 0, it will be
- /// mapped to a different seed.
- #[inline]
- fn from_seed(seed: Seed512) -> Xoshiro512StarStar {
- deal_with_zero_seed!(seed, Self);
- let mut state = [0; 8];
- read_u64_into(&seed.0, &mut state);
- Xoshiro512StarStar { s: state }
- }
-
- /// Seed a `Xoshiro512StarStar` from a `u64` using `SplitMix64`.
- fn seed_from_u64(seed: u64) -> Xoshiro512StarStar {
- from_splitmix!(seed)
- }
-}
-
-impl RngCore for Xoshiro512StarStar {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.next_u64() as u32
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- let result_starstar = starstar_u64!(self.s[1]);
- impl_xoshiro_large!(self);
- result_starstar
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn reference() {
- let mut rng = Xoshiro512StarStar::from_seed(Seed512(
- [1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0,
- 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0,
- 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0,
- 7, 0, 0, 0, 0, 0, 0, 0, 8, 0, 0, 0, 0, 0, 0, 0]));
- // These values were produced with the reference implementation:
- // http://xoshiro.di.unimi.it/xoshiro512starstar.c
- let expected = [
- 11520, 0, 23040, 23667840, 144955163520, 303992986974289920,
- 25332796375735680, 296904390158016, 13911081092387501979,
- 15304787717237593024,
- ];
- for &e in &expected {
- assert_eq!(rng.next_u64(), e);
- }
- }
-}
diff --git a/rand/rand_xoshiro/tests/serde.rs b/rand/rand_xoshiro/tests/serde.rs
deleted file mode 100644
index ee23a1d..0000000
--- a/rand/rand_xoshiro/tests/serde.rs
+++ /dev/null
@@ -1,83 +0,0 @@
-#![cfg(feature="serde1")]
-
-use rand_core::{RngCore, SeedableRng};
-use rand_xoshiro::{SplitMix64, Xoroshiro64StarStar, Xoroshiro64Star,
- Xoroshiro128Plus, Xoroshiro128StarStar, Xoshiro128StarStar, Xoshiro128Plus,
- Xoshiro256StarStar, Xoshiro256Plus, Xoshiro512StarStar, Xoshiro512Plus};
-
-macro_rules! serde_rng {
- ($rng:ident) => {
- use bincode;
- use std::io::{BufWriter, BufReader};
-
- let mut rng = $rng::seed_from_u64(0);
-
- let buf: Vec<u8> = Vec::new();
- let mut buf = BufWriter::new(buf);
- bincode::serialize_into(&mut buf, &rng).expect("Could not serialize");
-
- let buf = buf.into_inner().unwrap();
- let mut read = BufReader::new(&buf[..]);
- let mut deserialized: $rng = bincode::deserialize_from(&mut read)
- .expect("Could not deserialize");
-
- for _ in 0..16 {
- assert_eq!(rng.next_u64(), deserialized.next_u64());
- }
- }
-}
-
-#[test]
-fn test_splitmix64() {
- serde_rng!(SplitMix64);
-}
-
-#[test]
-fn test_xoroshiro64starstar() {
- serde_rng!(Xoroshiro64StarStar);
-}
-
-#[test]
-fn test_xoroshiro64star() {
- serde_rng!(Xoroshiro64Star);
-}
-
-#[test]
-fn test_xoroshiro128plus() {
- serde_rng!(Xoroshiro128Plus);
-}
-
-#[test]
-fn test_xoroshiro128starstar() {
- serde_rng!(Xoroshiro128StarStar);
-}
-
-#[test]
-fn test_xoshiro128starstar() {
- serde_rng!(Xoshiro128StarStar);
-}
-
-#[test]
-fn test_xoshiro128plus() {
- serde_rng!(Xoshiro128Plus);
-}
-
-#[test]
-fn test_xoshiro256starstar() {
- serde_rng!(Xoshiro256StarStar);
-}
-
-#[test]
-fn test_xoshiro256plus() {
- serde_rng!(Xoshiro256Plus);
-}
-
-#[test]
-fn test_xoshiro512starstar() {
- serde_rng!(Xoshiro512StarStar);
-}
-
-#[test]
-fn test_xoshiro512plus() {
- serde_rng!(Xoshiro512Plus);
-}
diff --git a/rand/rustfmt.toml b/rand/rustfmt.toml
deleted file mode 100644
index 6b2aba3..0000000
--- a/rand/rustfmt.toml
+++ /dev/null
@@ -1,30 +0,0 @@
-# This rustfmt file is added for configuration, but in practice much of our
-# code is hand-formatted, frequently with more readable results.
-
-# Comments:
-normalize_comments = true
-wrap_comments = false
-format_doc_comments = true
-comment_width = 90 # small excess is okay but prefer 80
-
-# Arguments:
-use_small_heuristics = "max"
-fn_args_density = "compressed"
-fn_single_line = false
-overflow_delimited_expr = true
-where_single_line = true
-
-# enum_discrim_align_threshold = 20
-# struct_field_align_threshold = 20
-
-# Compatibility:
-edition = "2018" # we require compatibility back to 1.32.0
-
-# Misc:
-blank_lines_upper_bound = 2
-reorder_impl_items = true
-# report_todo = "Unnumbered"
-# report_fixme = "Unnumbered"
-
-# Ignored files:
-ignore = []
diff --git a/rand/src/distributions/bernoulli.rs b/rand/src/distributions/bernoulli.rs
deleted file mode 100644
index eadd056..0000000
--- a/rand/src/distributions/bernoulli.rs
+++ /dev/null
@@ -1,166 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The Bernoulli distribution.
-
-use crate::Rng;
-use crate::distributions::Distribution;
-
-/// The Bernoulli distribution.
-///
-/// This is a special case of the Binomial distribution where `n = 1`.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::{Bernoulli, Distribution};
-///
-/// let d = Bernoulli::new(0.3).unwrap();
-/// let v = d.sample(&mut rand::thread_rng());
-/// println!("{} is from a Bernoulli distribution", v);
-/// ```
-///
-/// # Precision
-///
-/// This `Bernoulli` distribution uses 64 bits from the RNG (a `u64`),
-/// so only probabilities that are multiples of 2<sup>-64</sup> can be
-/// represented.
-#[derive(Clone, Copy, Debug)]
-pub struct Bernoulli {
- /// Probability of success, relative to the maximal integer.
- p_int: u64,
-}
-
-// To sample from the Bernoulli distribution we use a method that compares a
-// random `u64` value `v < (p * 2^64)`.
-//
-// If `p == 1.0`, the integer `v` to compare against can not represented as a
-// `u64`. We manually set it to `u64::MAX` instead (2^64 - 1 instead of 2^64).
-// Note that value of `p < 1.0` can never result in `u64::MAX`, because an
-// `f64` only has 53 bits of precision, and the next largest value of `p` will
-// result in `2^64 - 2048`.
-//
-// Also there is a 100% theoretical concern: if someone consistenly wants to
-// generate `true` using the Bernoulli distribution (i.e. by using a probability
-// of `1.0`), just using `u64::MAX` is not enough. On average it would return
-// false once every 2^64 iterations. Some people apparently care about this
-// case.
-//
-// That is why we special-case `u64::MAX` to always return `true`, without using
-// the RNG, and pay the performance price for all uses that *are* reasonable.
-// Luckily, if `new()` and `sample` are close, the compiler can optimize out the
-// extra check.
-const ALWAYS_TRUE: u64 = ::core::u64::MAX;
-
-// This is just `2.0.powi(64)`, but written this way because it is not available
-// in `no_std` mode.
-const SCALE: f64 = 2.0 * (1u64 << 63) as f64;
-
-/// Error type returned from `Bernoulli::new`.
-#[derive(Clone, Copy, Debug, PartialEq, Eq)]
-pub enum BernoulliError {
- /// `p < 0` or `p > 1`.
- InvalidProbability,
-}
-
-impl Bernoulli {
- /// Construct a new `Bernoulli` with the given probability of success `p`.
- ///
- /// # Precision
- ///
- /// For `p = 1.0`, the resulting distribution will always generate true.
- /// For `p = 0.0`, the resulting distribution will always generate false.
- ///
- /// This method is accurate for any input `p` in the range `[0, 1]` which is
- /// a multiple of 2<sup>-64</sup>. (Note that not all multiples of
- /// 2<sup>-64</sup> in `[0, 1]` can be represented as a `f64`.)
- #[inline]
- pub fn new(p: f64) -> Result<Bernoulli, BernoulliError> {
- if p < 0.0 || p >= 1.0 {
- if p == 1.0 { return Ok(Bernoulli { p_int: ALWAYS_TRUE }) }
- return Err(BernoulliError::InvalidProbability);
- }
- Ok(Bernoulli { p_int: (p * SCALE) as u64 })
- }
-
- /// Construct a new `Bernoulli` with the probability of success of
- /// `numerator`-in-`denominator`. I.e. `new_ratio(2, 3)` will return
- /// a `Bernoulli` with a 2-in-3 chance, or about 67%, of returning `true`.
- ///
- /// If `numerator == denominator` then the returned `Bernoulli` will always
- /// return `true`. If `numerator == 0` it will always return `false`.
- #[inline]
- pub fn from_ratio(numerator: u32, denominator: u32) -> Result<Bernoulli, BernoulliError> {
- if numerator > denominator {
- return Err(BernoulliError::InvalidProbability);
- }
- if numerator == denominator {
- return Ok(Bernoulli { p_int: ALWAYS_TRUE })
- }
- let p_int = ((f64::from(numerator) / f64::from(denominator)) * SCALE) as u64;
- Ok(Bernoulli { p_int })
- }
-}
-
-impl Distribution<bool> for Bernoulli {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> bool {
- // Make sure to always return true for p = 1.0.
- if self.p_int == ALWAYS_TRUE { return true; }
- let v: u64 = rng.gen();
- v < self.p_int
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::Rng;
- use crate::distributions::Distribution;
- use super::Bernoulli;
-
- #[test]
- fn test_trivial() {
- let mut r = crate::test::rng(1);
- let always_false = Bernoulli::new(0.0).unwrap();
- let always_true = Bernoulli::new(1.0).unwrap();
- for _ in 0..5 {
- assert_eq!(r.sample::<bool, _>(&always_false), false);
- assert_eq!(r.sample::<bool, _>(&always_true), true);
- assert_eq!(Distribution::<bool>::sample(&always_false, &mut r), false);
- assert_eq!(Distribution::<bool>::sample(&always_true, &mut r), true);
- }
- }
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_average() {
- const P: f64 = 0.3;
- const NUM: u32 = 3;
- const DENOM: u32 = 10;
- let d1 = Bernoulli::new(P).unwrap();
- let d2 = Bernoulli::from_ratio(NUM, DENOM).unwrap();
- const N: u32 = 100_000;
-
- let mut sum1: u32 = 0;
- let mut sum2: u32 = 0;
- let mut rng = crate::test::rng(2);
- for _ in 0..N {
- if d1.sample(&mut rng) {
- sum1 += 1;
- }
- if d2.sample(&mut rng) {
- sum2 += 1;
- }
- }
- let avg1 = (sum1 as f64) / (N as f64);
- assert!((avg1 - P).abs() < 5e-3);
-
- let avg2 = (sum2 as f64) / (N as f64);
- assert!((avg2 - (NUM as f64)/(DENOM as f64)).abs() < 5e-3);
- }
-}
diff --git a/rand/src/distributions/binomial.rs b/rand/src/distributions/binomial.rs
deleted file mode 100644
index 8fc290a..0000000
--- a/rand/src/distributions/binomial.rs
+++ /dev/null
@@ -1,313 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2016-2017 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The binomial distribution.
-#![allow(deprecated)]
-#![allow(clippy::all)]
-
-use crate::Rng;
-use crate::distributions::{Distribution, Uniform};
-
-/// The binomial distribution `Binomial(n, p)`.
-///
-/// This distribution has density function:
-/// `f(k) = n!/(k! (n-k)!) p^k (1-p)^(n-k)` for `k >= 0`.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Binomial {
- /// Number of trials.
- n: u64,
- /// Probability of success.
- p: f64,
-}
-
-impl Binomial {
- /// Construct a new `Binomial` with the given shape parameters `n` (number
- /// of trials) and `p` (probability of success).
- ///
- /// Panics if `p < 0` or `p > 1`.
- pub fn new(n: u64, p: f64) -> Binomial {
- assert!(p >= 0.0, "Binomial::new called with p < 0");
- assert!(p <= 1.0, "Binomial::new called with p > 1");
- Binomial { n, p }
- }
-}
-
-/// Convert a `f64` to an `i64`, panicing on overflow.
-// In the future (Rust 1.34), this might be replaced with `TryFrom`.
-fn f64_to_i64(x: f64) -> i64 {
- assert!(x < (::std::i64::MAX as f64));
- x as i64
-}
-
-impl Distribution<u64> for Binomial {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u64 {
- // Handle these values directly.
- if self.p == 0.0 {
- return 0;
- } else if self.p == 1.0 {
- return self.n;
- }
-
- // The binomial distribution is symmetrical with respect to p -> 1-p,
- // k -> n-k switch p so that it is less than 0.5 - this allows for lower
- // expected values we will just invert the result at the end
- let p = if self.p <= 0.5 {
- self.p
- } else {
- 1.0 - self.p
- };
-
- let result;
- let q = 1. - p;
-
- // For small n * min(p, 1 - p), the BINV algorithm based on the inverse
- // transformation of the binomial distribution is efficient. Otherwise,
- // the BTPE algorithm is used.
- //
- // Voratas Kachitvichyanukul and Bruce W. Schmeiser. 1988. Binomial
- // random variate generation. Commun. ACM 31, 2 (February 1988),
- // 216-222. http://dx.doi.org/10.1145/42372.42381
-
- // Threshold for prefering the BINV algorithm. The paper suggests 10,
- // Ranlib uses 30, and GSL uses 14.
- const BINV_THRESHOLD: f64 = 10.;
-
- if (self.n as f64) * p < BINV_THRESHOLD &&
- self.n <= (::std::i32::MAX as u64) {
- // Use the BINV algorithm.
- let s = p / q;
- let a = ((self.n + 1) as f64) * s;
- let mut r = q.powi(self.n as i32);
- let mut u: f64 = rng.gen();
- let mut x = 0;
- while u > r as f64 {
- u -= r;
- x += 1;
- r *= a / (x as f64) - s;
- }
- result = x;
- } else {
- // Use the BTPE algorithm.
-
- // Threshold for using the squeeze algorithm. This can be freely
- // chosen based on performance. Ranlib and GSL use 20.
- const SQUEEZE_THRESHOLD: i64 = 20;
-
- // Step 0: Calculate constants as functions of `n` and `p`.
- let n = self.n as f64;
- let np = n * p;
- let npq = np * q;
- let f_m = np + p;
- let m = f64_to_i64(f_m);
- // radius of triangle region, since height=1 also area of region
- let p1 = (2.195 * npq.sqrt() - 4.6 * q).floor() + 0.5;
- // tip of triangle
- let x_m = (m as f64) + 0.5;
- // left edge of triangle
- let x_l = x_m - p1;
- // right edge of triangle
- let x_r = x_m + p1;
- let c = 0.134 + 20.5 / (15.3 + (m as f64));
- // p1 + area of parallelogram region
- let p2 = p1 * (1. + 2. * c);
-
- fn lambda(a: f64) -> f64 {
- a * (1. + 0.5 * a)
- }
-
- let lambda_l = lambda((f_m - x_l) / (f_m - x_l * p));
- let lambda_r = lambda((x_r - f_m) / (x_r * q));
- // p1 + area of left tail
- let p3 = p2 + c / lambda_l;
- // p1 + area of right tail
- let p4 = p3 + c / lambda_r;
-
- // return value
- let mut y: i64;
-
- let gen_u = Uniform::new(0., p4);
- let gen_v = Uniform::new(0., 1.);
-
- loop {
- // Step 1: Generate `u` for selecting the region. If region 1 is
- // selected, generate a triangularly distributed variate.
- let u = gen_u.sample(rng);
- let mut v = gen_v.sample(rng);
- if !(u > p1) {
- y = f64_to_i64(x_m - p1 * v + u);
- break;
- }
-
- if !(u > p2) {
- // Step 2: Region 2, parallelograms. Check if region 2 is
- // used. If so, generate `y`.
- let x = x_l + (u - p1) / c;
- v = v * c + 1.0 - (x - x_m).abs() / p1;
- if v > 1. {
- continue;
- } else {
- y = f64_to_i64(x);
- }
- } else if !(u > p3) {
- // Step 3: Region 3, left exponential tail.
- y = f64_to_i64(x_l + v.ln() / lambda_l);
- if y < 0 {
- continue;
- } else {
- v *= (u - p2) * lambda_l;
- }
- } else {
- // Step 4: Region 4, right exponential tail.
- y = f64_to_i64(x_r - v.ln() / lambda_r);
- if y > 0 && (y as u64) > self.n {
- continue;
- } else {
- v *= (u - p3) * lambda_r;
- }
- }
-
- // Step 5: Acceptance/rejection comparison.
-
- // Step 5.0: Test for appropriate method of evaluating f(y).
- let k = (y - m).abs();
- if !(k > SQUEEZE_THRESHOLD && (k as f64) < 0.5 * npq - 1.) {
- // Step 5.1: Evaluate f(y) via the recursive relationship. Start the
- // search from the mode.
- let s = p / q;
- let a = s * (n + 1.);
- let mut f = 1.0;
- if m < y {
- let mut i = m;
- loop {
- i += 1;
- f *= a / (i as f64) - s;
- if i == y {
- break;
- }
- }
- } else if m > y {
- let mut i = y;
- loop {
- i += 1;
- f /= a / (i as f64) - s;
- if i == m {
- break;
- }
- }
- }
- if v > f {
- continue;
- } else {
- break;
- }
- }
-
- // Step 5.2: Squeezing. Check the value of ln(v) againts upper and
- // lower bound of ln(f(y)).
- let k = k as f64;
- let rho = (k / npq) * ((k * (k / 3. + 0.625) + 1./6.) / npq + 0.5);
- let t = -0.5 * k*k / npq;
- let alpha = v.ln();
- if alpha < t - rho {
- break;
- }
- if alpha > t + rho {
- continue;
- }
-
- // Step 5.3: Final acceptance/rejection test.
- let x1 = (y + 1) as f64;
- let f1 = (m + 1) as f64;
- let z = (f64_to_i64(n) + 1 - m) as f64;
- let w = (f64_to_i64(n) - y + 1) as f64;
-
- fn stirling(a: f64) -> f64 {
- let a2 = a * a;
- (13860. - (462. - (132. - (99. - 140. / a2) / a2) / a2) / a2) / a / 166320.
- }
-
- if alpha > x_m * (f1 / x1).ln()
- + (n - (m as f64) + 0.5) * (z / w).ln()
- + ((y - m) as f64) * (w * p / (x1 * q)).ln()
- // We use the signs from the GSL implementation, which are
- // different than the ones in the reference. According to
- // the GSL authors, the new signs were verified to be
- // correct by one of the original designers of the
- // algorithm.
- + stirling(f1) + stirling(z) - stirling(x1) - stirling(w)
- {
- continue;
- }
-
- break;
- }
- assert!(y >= 0);
- result = y as u64;
- }
-
- // Invert the result for p < 0.5.
- if p != self.p {
- self.n - result
- } else {
- result
- }
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::Rng;
- use crate::distributions::Distribution;
- use super::Binomial;
-
- fn test_binomial_mean_and_variance<R: Rng>(n: u64, p: f64, rng: &mut R) {
- let binomial = Binomial::new(n, p);
-
- let expected_mean = n as f64 * p;
- let expected_variance = n as f64 * p * (1.0 - p);
-
- let mut results = [0.0; 1000];
- for i in results.iter_mut() { *i = binomial.sample(rng) as f64; }
-
- let mean = results.iter().sum::<f64>() / results.len() as f64;
- assert!((mean as f64 - expected_mean).abs() < expected_mean / 50.0,
- "mean: {}, expected_mean: {}", mean, expected_mean);
-
- let variance =
- results.iter().map(|x| (x - mean) * (x - mean)).sum::<f64>()
- / results.len() as f64;
- assert!((variance - expected_variance).abs() < expected_variance / 10.0,
- "variance: {}, expected_variance: {}", variance, expected_variance);
- }
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_binomial() {
- let mut rng = crate::test::rng(351);
- test_binomial_mean_and_variance(150, 0.1, &mut rng);
- test_binomial_mean_and_variance(70, 0.6, &mut rng);
- test_binomial_mean_and_variance(40, 0.5, &mut rng);
- test_binomial_mean_and_variance(20, 0.7, &mut rng);
- test_binomial_mean_and_variance(20, 0.5, &mut rng);
- }
-
- #[test]
- fn test_binomial_end_points() {
- let mut rng = crate::test::rng(352);
- assert_eq!(rng.sample(Binomial::new(20, 0.0)), 0);
- assert_eq!(rng.sample(Binomial::new(20, 1.0)), 20);
- }
-
- #[test]
- #[should_panic]
- fn test_binomial_invalid_lambda_neg() {
- Binomial::new(20, -10.0);
- }
-}
diff --git a/rand/src/distributions/cauchy.rs b/rand/src/distributions/cauchy.rs
deleted file mode 100644
index 0a5d149..0000000
--- a/rand/src/distributions/cauchy.rs
+++ /dev/null
@@ -1,103 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2016-2017 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The Cauchy distribution.
-#![allow(deprecated)]
-#![allow(clippy::all)]
-
-use crate::Rng;
-use crate::distributions::Distribution;
-use std::f64::consts::PI;
-
-/// The Cauchy distribution `Cauchy(median, scale)`.
-///
-/// This distribution has a density function:
-/// `f(x) = 1 / (pi * scale * (1 + ((x - median) / scale)^2))`
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Cauchy {
- median: f64,
- scale: f64
-}
-
-impl Cauchy {
- /// Construct a new `Cauchy` with the given shape parameters
- /// `median` the peak location and `scale` the scale factor.
- /// Panics if `scale <= 0`.
- pub fn new(median: f64, scale: f64) -> Cauchy {
- assert!(scale > 0.0, "Cauchy::new called with scale factor <= 0");
- Cauchy {
- median,
- scale
- }
- }
-}
-
-impl Distribution<f64> for Cauchy {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- // sample from [0, 1)
- let x = rng.gen::<f64>();
- // get standard cauchy random number
- // note that Ο/2 is not exactly representable, even if x=0.5 the result is finite
- let comp_dev = (PI * x).tan();
- // shift and scale according to parameters
- let result = self.median + self.scale * comp_dev;
- result
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::distributions::Distribution;
- use super::Cauchy;
-
- fn median(mut numbers: &mut [f64]) -> f64 {
- sort(&mut numbers);
- let mid = numbers.len() / 2;
- numbers[mid]
- }
-
- fn sort(numbers: &mut [f64]) {
- numbers.sort_by(|a, b| a.partial_cmp(b).unwrap());
- }
-
- #[test]
- #[cfg(not(miri))] // Miri doesn't support transcendental functions
- fn test_cauchy_averages() {
- // NOTE: given that the variance and mean are undefined,
- // this test does not have any rigorous statistical meaning.
- let cauchy = Cauchy::new(10.0, 5.0);
- let mut rng = crate::test::rng(123);
- let mut numbers: [f64; 1000] = [0.0; 1000];
- let mut sum = 0.0;
- for i in 0..1000 {
- numbers[i] = cauchy.sample(&mut rng);
- sum += numbers[i];
- }
- let median = median(&mut numbers);
- println!("Cauchy median: {}", median);
- assert!((median - 10.0).abs() < 0.4); // not 100% certain, but probable enough
- let mean = sum / 1000.0;
- println!("Cauchy mean: {}", mean);
- // for a Cauchy distribution the mean should not converge
- assert!((mean - 10.0).abs() > 0.4); // not 100% certain, but probable enough
- }
-
- #[test]
- #[should_panic]
- fn test_cauchy_invalid_scale_zero() {
- Cauchy::new(0.0, 0.0);
- }
-
- #[test]
- #[should_panic]
- fn test_cauchy_invalid_scale_neg() {
- Cauchy::new(0.0, -10.0);
- }
-}
diff --git a/rand/src/distributions/dirichlet.rs b/rand/src/distributions/dirichlet.rs
deleted file mode 100644
index 1ce01fd..0000000
--- a/rand/src/distributions/dirichlet.rs
+++ /dev/null
@@ -1,128 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The dirichlet distribution.
-#![allow(deprecated)]
-#![allow(clippy::all)]
-
-use crate::Rng;
-use crate::distributions::Distribution;
-use crate::distributions::gamma::Gamma;
-
-/// The dirichelet distribution `Dirichlet(alpha)`.
-///
-/// The Dirichlet distribution is a family of continuous multivariate
-/// probability distributions parameterized by a vector alpha of positive reals.
-/// It is a multivariate generalization of the beta distribution.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Debug)]
-pub struct Dirichlet {
- /// Concentration parameters (alpha)
- alpha: Vec<f64>,
-}
-
-impl Dirichlet {
- /// Construct a new `Dirichlet` with the given alpha parameter `alpha`.
- ///
- /// # Panics
- /// - if `alpha.len() < 2`
- ///
- #[inline]
- pub fn new<V: Into<Vec<f64>>>(alpha: V) -> Dirichlet {
- let a = alpha.into();
- assert!(a.len() > 1);
- for i in 0..a.len() {
- assert!(a[i] > 0.0);
- }
-
- Dirichlet { alpha: a }
- }
-
- /// Construct a new `Dirichlet` with the given shape parameter `alpha` and `size`.
- ///
- /// # Panics
- /// - if `alpha <= 0.0`
- /// - if `size < 2`
- ///
- #[inline]
- pub fn new_with_param(alpha: f64, size: usize) -> Dirichlet {
- assert!(alpha > 0.0);
- assert!(size > 1);
- Dirichlet {
- alpha: vec![alpha; size],
- }
- }
-}
-
-impl Distribution<Vec<f64>> for Dirichlet {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Vec<f64> {
- let n = self.alpha.len();
- let mut samples = vec![0.0f64; n];
- let mut sum = 0.0f64;
-
- for i in 0..n {
- let g = Gamma::new(self.alpha[i], 1.0);
- samples[i] = g.sample(rng);
- sum += samples[i];
- }
- let invacc = 1.0 / sum;
- for i in 0..n {
- samples[i] *= invacc;
- }
- samples
- }
-}
-
-#[cfg(test)]
-mod test {
- use super::Dirichlet;
- use crate::distributions::Distribution;
-
- #[test]
- fn test_dirichlet() {
- let d = Dirichlet::new(vec![1.0, 2.0, 3.0]);
- let mut rng = crate::test::rng(221);
- let samples = d.sample(&mut rng);
- let _: Vec<f64> = samples
- .into_iter()
- .map(|x| {
- assert!(x > 0.0);
- x
- })
- .collect();
- }
-
- #[test]
- fn test_dirichlet_with_param() {
- let alpha = 0.5f64;
- let size = 2;
- let d = Dirichlet::new_with_param(alpha, size);
- let mut rng = crate::test::rng(221);
- let samples = d.sample(&mut rng);
- let _: Vec<f64> = samples
- .into_iter()
- .map(|x| {
- assert!(x > 0.0);
- x
- })
- .collect();
- }
-
- #[test]
- #[should_panic]
- fn test_dirichlet_invalid_length() {
- Dirichlet::new_with_param(0.5f64, 1);
- }
-
- #[test]
- #[should_panic]
- fn test_dirichlet_invalid_alpha() {
- Dirichlet::new_with_param(0.0f64, 2);
- }
-}
diff --git a/rand/src/distributions/exponential.rs b/rand/src/distributions/exponential.rs
deleted file mode 100644
index 0278248..0000000
--- a/rand/src/distributions/exponential.rs
+++ /dev/null
@@ -1,108 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The exponential distribution.
-#![allow(deprecated)]
-
-use crate::{Rng};
-use crate::distributions::{ziggurat_tables, Distribution};
-use crate::distributions::utils::ziggurat;
-
-/// Samples floating-point numbers according to the exponential distribution,
-/// with rate parameter `Ξ» = 1`. This is equivalent to `Exp::new(1.0)` or
-/// sampling with `-rng.gen::<f64>().ln()`, but faster.
-///
-/// See `Exp` for the general exponential distribution.
-///
-/// Implemented via the ZIGNOR variant[^1] of the Ziggurat method. The exact
-/// description in the paper was adjusted to use tables for the exponential
-/// distribution rather than normal.
-///
-/// [^1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method to
-/// Generate Normal Random Samples*](
-/// https://www.doornik.com/research/ziggurat.pdf).
-/// Nuffield College, Oxford
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Exp1;
-
-// This could be done via `-rng.gen::<f64>().ln()` but that is slower.
-impl Distribution<f64> for Exp1 {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- #[inline]
- fn pdf(x: f64) -> f64 {
- (-x).exp()
- }
- #[inline]
- fn zero_case<R: Rng + ?Sized>(rng: &mut R, _u: f64) -> f64 {
- ziggurat_tables::ZIG_EXP_R - rng.gen::<f64>().ln()
- }
-
- ziggurat(rng, false,
- &ziggurat_tables::ZIG_EXP_X,
- &ziggurat_tables::ZIG_EXP_F,
- pdf, zero_case)
- }
-}
-
-/// The exponential distribution `Exp(lambda)`.
-///
-/// This distribution has density function: `f(x) = lambda * exp(-lambda * x)`
-/// for `x > 0`.
-///
-/// Note that [`Exp1`](crate::distributions::Exp1) is an optimised implementation for `lambda = 1`.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Exp {
- /// `lambda` stored as `1/lambda`, since this is what we scale by.
- lambda_inverse: f64
-}
-
-impl Exp {
- /// Construct a new `Exp` with the given shape parameter
- /// `lambda`. Panics if `lambda <= 0`.
- #[inline]
- pub fn new(lambda: f64) -> Exp {
- assert!(lambda > 0.0, "Exp::new called with `lambda` <= 0");
- Exp { lambda_inverse: 1.0 / lambda }
- }
-}
-
-impl Distribution<f64> for Exp {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- let n: f64 = rng.sample(Exp1);
- n * self.lambda_inverse
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::distributions::Distribution;
- use super::Exp;
-
- #[test]
- fn test_exp() {
- let exp = Exp::new(10.0);
- let mut rng = crate::test::rng(221);
- for _ in 0..1000 {
- assert!(exp.sample(&mut rng) >= 0.0);
- }
- }
- #[test]
- #[should_panic]
- fn test_exp_invalid_lambda_zero() {
- Exp::new(0.0);
- }
- #[test]
- #[should_panic]
- fn test_exp_invalid_lambda_neg() {
- Exp::new(-10.0);
- }
-}
diff --git a/rand/src/distributions/float.rs b/rand/src/distributions/float.rs
deleted file mode 100644
index bda523a..0000000
--- a/rand/src/distributions/float.rs
+++ /dev/null
@@ -1,259 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Basic floating-point number distributions
-
-use core::mem;
-use crate::Rng;
-use crate::distributions::{Distribution, Standard};
-use crate::distributions::utils::FloatSIMDUtils;
-#[cfg(feature="simd_support")]
-use packed_simd::*;
-
-/// A distribution to sample floating point numbers uniformly in the half-open
-/// interval `(0, 1]`, i.e. including 1 but not 0.
-///
-/// All values that can be generated are of the form `n * Ξ΅/2`. For `f32`
-/// the 23 most significant random bits of a `u32` are used and for `f64` the
-/// 53 most significant bits of a `u64` are used. The conversion uses the
-/// multiplicative method.
-///
-/// See also: [`Standard`] which samples from `[0, 1)`, [`Open01`]
-/// which samples from `(0, 1)` and [`Uniform`] which samples from arbitrary
-/// ranges.
-///
-/// # Example
-/// ```
-/// use rand::{thread_rng, Rng};
-/// use rand::distributions::OpenClosed01;
-///
-/// let val: f32 = thread_rng().sample(OpenClosed01);
-/// println!("f32 from (0, 1): {}", val);
-/// ```
-///
-/// [`Standard`]: crate::distributions::Standard
-/// [`Open01`]: crate::distributions::Open01
-/// [`Uniform`]: crate::distributions::uniform::Uniform
-#[derive(Clone, Copy, Debug)]
-pub struct OpenClosed01;
-
-/// A distribution to sample floating point numbers uniformly in the open
-/// interval `(0, 1)`, i.e. not including either endpoint.
-///
-/// All values that can be generated are of the form `n * Ξ΅ + Ξ΅/2`. For `f32`
-/// the 22 most significant random bits of an `u32` are used, for `f64` 52 from
-/// an `u64`. The conversion uses a transmute-based method.
-///
-/// See also: [`Standard`] which samples from `[0, 1)`, [`OpenClosed01`]
-/// which samples from `(0, 1]` and [`Uniform`] which samples from arbitrary
-/// ranges.
-///
-/// # Example
-/// ```
-/// use rand::{thread_rng, Rng};
-/// use rand::distributions::Open01;
-///
-/// let val: f32 = thread_rng().sample(Open01);
-/// println!("f32 from (0, 1): {}", val);
-/// ```
-///
-/// [`Standard`]: crate::distributions::Standard
-/// [`OpenClosed01`]: crate::distributions::OpenClosed01
-/// [`Uniform`]: crate::distributions::uniform::Uniform
-#[derive(Clone, Copy, Debug)]
-pub struct Open01;
-
-
-// This trait is needed by both this lib and rand_distr hence is a hidden export
-#[doc(hidden)]
-pub trait IntoFloat {
- type F;
-
- /// Helper method to combine the fraction and a contant exponent into a
- /// float.
- ///
- /// Only the least significant bits of `self` may be set, 23 for `f32` and
- /// 52 for `f64`.
- /// The resulting value will fall in a range that depends on the exponent.
- /// As an example the range with exponent 0 will be
- /// [2<sup>0</sup>..2<sup>1</sup>), which is [1..2).
- fn into_float_with_exponent(self, exponent: i32) -> Self::F;
-}
-
-macro_rules! float_impls {
- ($ty:ident, $uty:ident, $f_scalar:ident, $u_scalar:ty,
- $fraction_bits:expr, $exponent_bias:expr) => {
- impl IntoFloat for $uty {
- type F = $ty;
- #[inline(always)]
- fn into_float_with_exponent(self, exponent: i32) -> $ty {
- // The exponent is encoded using an offset-binary representation
- let exponent_bits: $u_scalar =
- (($exponent_bias + exponent) as $u_scalar) << $fraction_bits;
- $ty::from_bits(self | exponent_bits)
- }
- }
-
- impl Distribution<$ty> for Standard {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> $ty {
- // Multiply-based method; 24/53 random bits; [0, 1) interval.
- // We use the most significant bits because for simple RNGs
- // those are usually more random.
- let float_size = mem::size_of::<$f_scalar>() as u32 * 8;
- let precision = $fraction_bits + 1;
- let scale = 1.0 / ((1 as $u_scalar << precision) as $f_scalar);
-
- let value: $uty = rng.gen();
- let value = value >> (float_size - precision);
- scale * $ty::cast_from_int(value)
- }
- }
-
- impl Distribution<$ty> for OpenClosed01 {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> $ty {
- // Multiply-based method; 24/53 random bits; (0, 1] interval.
- // We use the most significant bits because for simple RNGs
- // those are usually more random.
- let float_size = mem::size_of::<$f_scalar>() as u32 * 8;
- let precision = $fraction_bits + 1;
- let scale = 1.0 / ((1 as $u_scalar << precision) as $f_scalar);
-
- let value: $uty = rng.gen();
- let value = value >> (float_size - precision);
- // Add 1 to shift up; will not overflow because of right-shift:
- scale * $ty::cast_from_int(value + 1)
- }
- }
-
- impl Distribution<$ty> for Open01 {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> $ty {
- // Transmute-based method; 23/52 random bits; (0, 1) interval.
- // We use the most significant bits because for simple RNGs
- // those are usually more random.
- use core::$f_scalar::EPSILON;
- let float_size = mem::size_of::<$f_scalar>() as u32 * 8;
-
- let value: $uty = rng.gen();
- let fraction = value >> (float_size - $fraction_bits);
- fraction.into_float_with_exponent(0) - (1.0 - EPSILON / 2.0)
- }
- }
- }
-}
-
-float_impls! { f32, u32, f32, u32, 23, 127 }
-float_impls! { f64, u64, f64, u64, 52, 1023 }
-
-#[cfg(feature="simd_support")]
-float_impls! { f32x2, u32x2, f32, u32, 23, 127 }
-#[cfg(feature="simd_support")]
-float_impls! { f32x4, u32x4, f32, u32, 23, 127 }
-#[cfg(feature="simd_support")]
-float_impls! { f32x8, u32x8, f32, u32, 23, 127 }
-#[cfg(feature="simd_support")]
-float_impls! { f32x16, u32x16, f32, u32, 23, 127 }
-
-#[cfg(feature="simd_support")]
-float_impls! { f64x2, u64x2, f64, u64, 52, 1023 }
-#[cfg(feature="simd_support")]
-float_impls! { f64x4, u64x4, f64, u64, 52, 1023 }
-#[cfg(feature="simd_support")]
-float_impls! { f64x8, u64x8, f64, u64, 52, 1023 }
-
-
-#[cfg(test)]
-mod tests {
- use crate::Rng;
- use crate::distributions::{Open01, OpenClosed01};
- use crate::rngs::mock::StepRng;
- #[cfg(feature="simd_support")]
- use packed_simd::*;
-
- const EPSILON32: f32 = ::core::f32::EPSILON;
- const EPSILON64: f64 = ::core::f64::EPSILON;
-
- macro_rules! test_f32 {
- ($fnn:ident, $ty:ident, $ZERO:expr, $EPSILON:expr) => {
- #[test]
- fn $fnn() {
- // Standard
- let mut zeros = StepRng::new(0, 0);
- assert_eq!(zeros.gen::<$ty>(), $ZERO);
- let mut one = StepRng::new(1 << 8 | 1 << (8 + 32), 0);
- assert_eq!(one.gen::<$ty>(), $EPSILON / 2.0);
- let mut max = StepRng::new(!0, 0);
- assert_eq!(max.gen::<$ty>(), 1.0 - $EPSILON / 2.0);
-
- // OpenClosed01
- let mut zeros = StepRng::new(0, 0);
- assert_eq!(zeros.sample::<$ty, _>(OpenClosed01),
- 0.0 + $EPSILON / 2.0);
- let mut one = StepRng::new(1 << 8 | 1 << (8 + 32), 0);
- assert_eq!(one.sample::<$ty, _>(OpenClosed01), $EPSILON);
- let mut max = StepRng::new(!0, 0);
- assert_eq!(max.sample::<$ty, _>(OpenClosed01), $ZERO + 1.0);
-
- // Open01
- let mut zeros = StepRng::new(0, 0);
- assert_eq!(zeros.sample::<$ty, _>(Open01), 0.0 + $EPSILON / 2.0);
- let mut one = StepRng::new(1 << 9 | 1 << (9 + 32), 0);
- assert_eq!(one.sample::<$ty, _>(Open01), $EPSILON / 2.0 * 3.0);
- let mut max = StepRng::new(!0, 0);
- assert_eq!(max.sample::<$ty, _>(Open01), 1.0 - $EPSILON / 2.0);
- }
- }
- }
- test_f32! { f32_edge_cases, f32, 0.0, EPSILON32 }
- #[cfg(feature="simd_support")]
- test_f32! { f32x2_edge_cases, f32x2, f32x2::splat(0.0), f32x2::splat(EPSILON32) }
- #[cfg(feature="simd_support")]
- test_f32! { f32x4_edge_cases, f32x4, f32x4::splat(0.0), f32x4::splat(EPSILON32) }
- #[cfg(feature="simd_support")]
- test_f32! { f32x8_edge_cases, f32x8, f32x8::splat(0.0), f32x8::splat(EPSILON32) }
- #[cfg(feature="simd_support")]
- test_f32! { f32x16_edge_cases, f32x16, f32x16::splat(0.0), f32x16::splat(EPSILON32) }
-
- macro_rules! test_f64 {
- ($fnn:ident, $ty:ident, $ZERO:expr, $EPSILON:expr) => {
- #[test]
- fn $fnn() {
- // Standard
- let mut zeros = StepRng::new(0, 0);
- assert_eq!(zeros.gen::<$ty>(), $ZERO);
- let mut one = StepRng::new(1 << 11, 0);
- assert_eq!(one.gen::<$ty>(), $EPSILON / 2.0);
- let mut max = StepRng::new(!0, 0);
- assert_eq!(max.gen::<$ty>(), 1.0 - $EPSILON / 2.0);
-
- // OpenClosed01
- let mut zeros = StepRng::new(0, 0);
- assert_eq!(zeros.sample::<$ty, _>(OpenClosed01),
- 0.0 + $EPSILON / 2.0);
- let mut one = StepRng::new(1 << 11, 0);
- assert_eq!(one.sample::<$ty, _>(OpenClosed01), $EPSILON);
- let mut max = StepRng::new(!0, 0);
- assert_eq!(max.sample::<$ty, _>(OpenClosed01), $ZERO + 1.0);
-
- // Open01
- let mut zeros = StepRng::new(0, 0);
- assert_eq!(zeros.sample::<$ty, _>(Open01), 0.0 + $EPSILON / 2.0);
- let mut one = StepRng::new(1 << 12, 0);
- assert_eq!(one.sample::<$ty, _>(Open01), $EPSILON / 2.0 * 3.0);
- let mut max = StepRng::new(!0, 0);
- assert_eq!(max.sample::<$ty, _>(Open01), 1.0 - $EPSILON / 2.0);
- }
- }
- }
- test_f64! { f64_edge_cases, f64, 0.0, EPSILON64 }
- #[cfg(feature="simd_support")]
- test_f64! { f64x2_edge_cases, f64x2, f64x2::splat(0.0), f64x2::splat(EPSILON64) }
- #[cfg(feature="simd_support")]
- test_f64! { f64x4_edge_cases, f64x4, f64x4::splat(0.0), f64x4::splat(EPSILON64) }
- #[cfg(feature="simd_support")]
- test_f64! { f64x8_edge_cases, f64x8, f64x8::splat(0.0), f64x8::splat(EPSILON64) }
-}
diff --git a/rand/src/distributions/gamma.rs b/rand/src/distributions/gamma.rs
deleted file mode 100644
index b5a97f5..0000000
--- a/rand/src/distributions/gamma.rs
+++ /dev/null
@@ -1,371 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The Gamma and derived distributions.
-#![allow(deprecated)]
-
-use self::GammaRepr::*;
-use self::ChiSquaredRepr::*;
-
-use crate::Rng;
-use crate::distributions::normal::StandardNormal;
-use crate::distributions::{Distribution, Exp, Open01};
-
-/// The Gamma distribution `Gamma(shape, scale)` distribution.
-///
-/// The density function of this distribution is
-///
-/// ```text
-/// f(x) = x^(k - 1) * exp(-x / ΞΈ) / (Ξ(k) * ΞΈ^k)
-/// ```
-///
-/// where `Ξ` is the Gamma function, `k` is the shape and `ΞΈ` is the
-/// scale and both `k` and `ΞΈ` are strictly positive.
-///
-/// The algorithm used is that described by Marsaglia & Tsang 2000[^1],
-/// falling back to directly sampling from an Exponential for `shape
-/// == 1`, and using the boosting technique described in that paper for
-/// `shape < 1`.
-///
-/// [^1]: George Marsaglia and Wai Wan Tsang. 2000. "A Simple Method for
-/// Generating Gamma Variables" *ACM Trans. Math. Softw.* 26, 3
-/// (September 2000), 363-372.
-/// DOI:[10.1145/358407.358414](https://doi.acm.org/10.1145/358407.358414)
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Gamma {
- repr: GammaRepr,
-}
-
-#[derive(Clone, Copy, Debug)]
-enum GammaRepr {
- Large(GammaLargeShape),
- One(Exp),
- Small(GammaSmallShape)
-}
-
-// These two helpers could be made public, but saving the
-// match-on-Gamma-enum branch from using them directly (e.g. if one
-// knows that the shape is always > 1) doesn't appear to be much
-// faster.
-
-/// Gamma distribution where the shape parameter is less than 1.
-///
-/// Note, samples from this require a compulsory floating-point `pow`
-/// call, which makes it significantly slower than sampling from a
-/// gamma distribution where the shape parameter is greater than or
-/// equal to 1.
-///
-/// See `Gamma` for sampling from a Gamma distribution with general
-/// shape parameters.
-#[derive(Clone, Copy, Debug)]
-struct GammaSmallShape {
- inv_shape: f64,
- large_shape: GammaLargeShape
-}
-
-/// Gamma distribution where the shape parameter is larger than 1.
-///
-/// See `Gamma` for sampling from a Gamma distribution with general
-/// shape parameters.
-#[derive(Clone, Copy, Debug)]
-struct GammaLargeShape {
- scale: f64,
- c: f64,
- d: f64
-}
-
-impl Gamma {
- /// Construct an object representing the `Gamma(shape, scale)`
- /// distribution.
- ///
- /// Panics if `shape <= 0` or `scale <= 0`.
- #[inline]
- pub fn new(shape: f64, scale: f64) -> Gamma {
- assert!(shape > 0.0, "Gamma::new called with shape <= 0");
- assert!(scale > 0.0, "Gamma::new called with scale <= 0");
-
- let repr = if shape == 1.0 {
- One(Exp::new(1.0 / scale))
- } else if shape < 1.0 {
- Small(GammaSmallShape::new_raw(shape, scale))
- } else {
- Large(GammaLargeShape::new_raw(shape, scale))
- };
- Gamma { repr }
- }
-}
-
-impl GammaSmallShape {
- fn new_raw(shape: f64, scale: f64) -> GammaSmallShape {
- GammaSmallShape {
- inv_shape: 1. / shape,
- large_shape: GammaLargeShape::new_raw(shape + 1.0, scale)
- }
- }
-}
-
-impl GammaLargeShape {
- fn new_raw(shape: f64, scale: f64) -> GammaLargeShape {
- let d = shape - 1. / 3.;
- GammaLargeShape {
- scale,
- c: 1. / (9. * d).sqrt(),
- d
- }
- }
-}
-
-impl Distribution<f64> for Gamma {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- match self.repr {
- Small(ref g) => g.sample(rng),
- One(ref g) => g.sample(rng),
- Large(ref g) => g.sample(rng),
- }
- }
-}
-impl Distribution<f64> for GammaSmallShape {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- let u: f64 = rng.sample(Open01);
-
- self.large_shape.sample(rng) * u.powf(self.inv_shape)
- }
-}
-impl Distribution<f64> for GammaLargeShape {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- loop {
- let x = rng.sample(StandardNormal);
- let v_cbrt = 1.0 + self.c * x;
- if v_cbrt <= 0.0 { // a^3 <= 0 iff a <= 0
- continue
- }
-
- let v = v_cbrt * v_cbrt * v_cbrt;
- let u: f64 = rng.sample(Open01);
-
- let x_sqr = x * x;
- if u < 1.0 - 0.0331 * x_sqr * x_sqr ||
- u.ln() < 0.5 * x_sqr + self.d * (1.0 - v + v.ln()) {
- return self.d * v * self.scale
- }
- }
- }
-}
-
-/// The chi-squared distribution `ΟΒ²(k)`, where `k` is the degrees of
-/// freedom.
-///
-/// For `k > 0` integral, this distribution is the sum of the squares
-/// of `k` independent standard normal random variables. For other
-/// `k`, this uses the equivalent characterisation
-/// `ΟΒ²(k) = Gamma(k/2, 2)`.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct ChiSquared {
- repr: ChiSquaredRepr,
-}
-
-#[derive(Clone, Copy, Debug)]
-enum ChiSquaredRepr {
- // k == 1, Gamma(alpha, ..) is particularly slow for alpha < 1,
- // e.g. when alpha = 1/2 as it would be for this case, so special-
- // casing and using the definition of N(0,1)^2 is faster.
- DoFExactlyOne,
- DoFAnythingElse(Gamma),
-}
-
-impl ChiSquared {
- /// Create a new chi-squared distribution with degrees-of-freedom
- /// `k`. Panics if `k < 0`.
- pub fn new(k: f64) -> ChiSquared {
- let repr = if k == 1.0 {
- DoFExactlyOne
- } else {
- assert!(k > 0.0, "ChiSquared::new called with `k` < 0");
- DoFAnythingElse(Gamma::new(0.5 * k, 2.0))
- };
- ChiSquared { repr }
- }
-}
-impl Distribution<f64> for ChiSquared {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- match self.repr {
- DoFExactlyOne => {
- // k == 1 => N(0,1)^2
- let norm = rng.sample(StandardNormal);
- norm * norm
- }
- DoFAnythingElse(ref g) => g.sample(rng)
- }
- }
-}
-
-/// The Fisher F distribution `F(m, n)`.
-///
-/// This distribution is equivalent to the ratio of two normalised
-/// chi-squared distributions, that is, `F(m,n) = (ΟΒ²(m)/m) /
-/// (ΟΒ²(n)/n)`.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct FisherF {
- numer: ChiSquared,
- denom: ChiSquared,
- // denom_dof / numer_dof so that this can just be a straight
- // multiplication, rather than a division.
- dof_ratio: f64,
-}
-
-impl FisherF {
- /// Create a new `FisherF` distribution, with the given
- /// parameter. Panics if either `m` or `n` are not positive.
- pub fn new(m: f64, n: f64) -> FisherF {
- assert!(m > 0.0, "FisherF::new called with `m < 0`");
- assert!(n > 0.0, "FisherF::new called with `n < 0`");
-
- FisherF {
- numer: ChiSquared::new(m),
- denom: ChiSquared::new(n),
- dof_ratio: n / m
- }
- }
-}
-impl Distribution<f64> for FisherF {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- self.numer.sample(rng) / self.denom.sample(rng) * self.dof_ratio
- }
-}
-
-/// The Student t distribution, `t(nu)`, where `nu` is the degrees of
-/// freedom.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct StudentT {
- chi: ChiSquared,
- dof: f64
-}
-
-impl StudentT {
- /// Create a new Student t distribution with `n` degrees of
- /// freedom. Panics if `n <= 0`.
- pub fn new(n: f64) -> StudentT {
- assert!(n > 0.0, "StudentT::new called with `n <= 0`");
- StudentT {
- chi: ChiSquared::new(n),
- dof: n
- }
- }
-}
-impl Distribution<f64> for StudentT {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- let norm = rng.sample(StandardNormal);
- norm * (self.dof / self.chi.sample(rng)).sqrt()
- }
-}
-
-/// The Beta distribution with shape parameters `alpha` and `beta`.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Beta {
- gamma_a: Gamma,
- gamma_b: Gamma,
-}
-
-impl Beta {
- /// Construct an object representing the `Beta(alpha, beta)`
- /// distribution.
- ///
- /// Panics if `shape <= 0` or `scale <= 0`.
- pub fn new(alpha: f64, beta: f64) -> Beta {
- assert!((alpha > 0.) & (beta > 0.));
- Beta {
- gamma_a: Gamma::new(alpha, 1.),
- gamma_b: Gamma::new(beta, 1.),
- }
- }
-}
-
-impl Distribution<f64> for Beta {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- let x = self.gamma_a.sample(rng);
- let y = self.gamma_b.sample(rng);
- x / (x + y)
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::distributions::Distribution;
- use super::{Beta, ChiSquared, StudentT, FisherF};
-
- const N: u32 = 100;
-
- #[test]
- fn test_chi_squared_one() {
- let chi = ChiSquared::new(1.0);
- let mut rng = crate::test::rng(201);
- for _ in 0..N {
- chi.sample(&mut rng);
- }
- }
- #[test]
- fn test_chi_squared_small() {
- let chi = ChiSquared::new(0.5);
- let mut rng = crate::test::rng(202);
- for _ in 0..N {
- chi.sample(&mut rng);
- }
- }
- #[test]
- fn test_chi_squared_large() {
- let chi = ChiSquared::new(30.0);
- let mut rng = crate::test::rng(203);
- for _ in 0..N {
- chi.sample(&mut rng);
- }
- }
- #[test]
- #[should_panic]
- fn test_chi_squared_invalid_dof() {
- ChiSquared::new(-1.0);
- }
-
- #[test]
- fn test_f() {
- let f = FisherF::new(2.0, 32.0);
- let mut rng = crate::test::rng(204);
- for _ in 0..N {
- f.sample(&mut rng);
- }
- }
-
- #[test]
- fn test_t() {
- let t = StudentT::new(11.0);
- let mut rng = crate::test::rng(205);
- for _ in 0..N {
- t.sample(&mut rng);
- }
- }
-
- #[test]
- fn test_beta() {
- let beta = Beta::new(1.0, 2.0);
- let mut rng = crate::test::rng(201);
- for _ in 0..N {
- beta.sample(&mut rng);
- }
- }
-
- #[test]
- #[should_panic]
- fn test_beta_invalid_dof() {
- Beta::new(0., 0.);
- }
-}
diff --git a/rand/src/distributions/integer.rs b/rand/src/distributions/integer.rs
deleted file mode 100644
index 5238339..0000000
--- a/rand/src/distributions/integer.rs
+++ /dev/null
@@ -1,184 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The implementations of the `Standard` distribution for integer types.
-
-use crate::{Rng};
-use crate::distributions::{Distribution, Standard};
-use core::num::{NonZeroU8, NonZeroU16, NonZeroU32, NonZeroU64, NonZeroUsize};
-#[cfg(not(target_os = "emscripten"))] use core::num::NonZeroU128;
-#[cfg(feature="simd_support")]
-use packed_simd::*;
-#[cfg(all(target_arch = "x86", feature="nightly"))]
-use core::arch::x86::*;
-#[cfg(all(target_arch = "x86_64", feature="nightly"))]
-use core::arch::x86_64::*;
-
-impl Distribution<u8> for Standard {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u8 {
- rng.next_u32() as u8
- }
-}
-
-impl Distribution<u16> for Standard {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u16 {
- rng.next_u32() as u16
- }
-}
-
-impl Distribution<u32> for Standard {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u32 {
- rng.next_u32()
- }
-}
-
-impl Distribution<u64> for Standard {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u64 {
- rng.next_u64()
- }
-}
-
-#[cfg(not(target_os = "emscripten"))]
-impl Distribution<u128> for Standard {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u128 {
- // Use LE; we explicitly generate one value before the next.
- let x = u128::from(rng.next_u64());
- let y = u128::from(rng.next_u64());
- (y << 64) | x
- }
-}
-
-impl Distribution<usize> for Standard {
- #[inline]
- #[cfg(any(target_pointer_width = "32", target_pointer_width = "16"))]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> usize {
- rng.next_u32() as usize
- }
-
- #[inline]
- #[cfg(target_pointer_width = "64")]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> usize {
- rng.next_u64() as usize
- }
-}
-
-macro_rules! impl_int_from_uint {
- ($ty:ty, $uty:ty) => {
- impl Distribution<$ty> for Standard {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> $ty {
- rng.gen::<$uty>() as $ty
- }
- }
- }
-}
-
-impl_int_from_uint! { i8, u8 }
-impl_int_from_uint! { i16, u16 }
-impl_int_from_uint! { i32, u32 }
-impl_int_from_uint! { i64, u64 }
-#[cfg(not(target_os = "emscripten"))] impl_int_from_uint! { i128, u128 }
-impl_int_from_uint! { isize, usize }
-
-macro_rules! impl_nzint {
- ($ty:ty, $new:path) => {
- impl Distribution<$ty> for Standard {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> $ty {
- loop {
- if let Some(nz) = $new(rng.gen()) {
- break nz;
- }
- }
- }
- }
- }
-}
-
-impl_nzint!(NonZeroU8, NonZeroU8::new);
-impl_nzint!(NonZeroU16, NonZeroU16::new);
-impl_nzint!(NonZeroU32, NonZeroU32::new);
-impl_nzint!(NonZeroU64, NonZeroU64::new);
-#[cfg(not(target_os = "emscripten"))] impl_nzint!(NonZeroU128, NonZeroU128::new);
-impl_nzint!(NonZeroUsize, NonZeroUsize::new);
-
-#[cfg(feature="simd_support")]
-macro_rules! simd_impl {
- ($(($intrinsic:ident, $vec:ty),)+) => {$(
- impl Distribution<$intrinsic> for Standard {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> $intrinsic {
- $intrinsic::from_bits(rng.gen::<$vec>())
- }
- }
- )+};
-
- ($bits:expr,) => {};
- ($bits:expr, $ty:ty, $($ty_more:ty,)*) => {
- simd_impl!($bits, $($ty_more,)*);
-
- impl Distribution<$ty> for Standard {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> $ty {
- let mut vec: $ty = Default::default();
- unsafe {
- let ptr = &mut vec;
- let b_ptr = &mut *(ptr as *mut $ty as *mut [u8; $bits/8]);
- rng.fill_bytes(b_ptr);
- }
- vec.to_le()
- }
- }
- };
-}
-
-#[cfg(feature="simd_support")]
-simd_impl!(16, u8x2, i8x2,);
-#[cfg(feature="simd_support")]
-simd_impl!(32, u8x4, i8x4, u16x2, i16x2,);
-#[cfg(feature="simd_support")]
-simd_impl!(64, u8x8, i8x8, u16x4, i16x4, u32x2, i32x2,);
-#[cfg(feature="simd_support")]
-simd_impl!(128, u8x16, i8x16, u16x8, i16x8, u32x4, i32x4, u64x2, i64x2,);
-#[cfg(feature="simd_support")]
-simd_impl!(256, u8x32, i8x32, u16x16, i16x16, u32x8, i32x8, u64x4, i64x4,);
-#[cfg(feature="simd_support")]
-simd_impl!(512, u8x64, i8x64, u16x32, i16x32, u32x16, i32x16, u64x8, i64x8,);
-#[cfg(all(feature="simd_support", feature="nightly", any(target_arch="x86", target_arch="x86_64")))]
-simd_impl!((__m64, u8x8), (__m128i, u8x16), (__m256i, u8x32),);
-
-#[cfg(test)]
-mod tests {
- use crate::Rng;
- use crate::distributions::{Standard};
-
- #[test]
- fn test_integers() {
- let mut rng = crate::test::rng(806);
-
- rng.sample::<isize, _>(Standard);
- rng.sample::<i8, _>(Standard);
- rng.sample::<i16, _>(Standard);
- rng.sample::<i32, _>(Standard);
- rng.sample::<i64, _>(Standard);
- #[cfg(not(target_os = "emscripten"))]
- rng.sample::<i128, _>(Standard);
-
- rng.sample::<usize, _>(Standard);
- rng.sample::<u8, _>(Standard);
- rng.sample::<u16, _>(Standard);
- rng.sample::<u32, _>(Standard);
- rng.sample::<u64, _>(Standard);
- #[cfg(not(target_os = "emscripten"))]
- rng.sample::<u128, _>(Standard);
- }
-}
diff --git a/rand/src/distributions/mod.rs b/rand/src/distributions/mod.rs
deleted file mode 100644
index 02ece6f..0000000
--- a/rand/src/distributions/mod.rs
+++ /dev/null
@@ -1,381 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013-2017 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Generating random samples from probability distributions
-//!
-//! This module is the home of the [`Distribution`] trait and several of its
-//! implementations. It is the workhorse behind some of the convenient
-//! functionality of the [`Rng`] trait, e.g. [`Rng::gen`], [`Rng::gen_range`] and
-//! of course [`Rng::sample`].
-//!
-//! Abstractly, a [probability distribution] describes the probability of
-//! occurance of each value in its sample space.
-//!
-//! More concretely, an implementation of `Distribution<T>` for type `X` is an
-//! algorithm for choosing values from the sample space (a subset of `T`)
-//! according to the distribution `X` represents, using an external source of
-//! randomness (an RNG supplied to the `sample` function).
-//!
-//! A type `X` may implement `Distribution<T>` for multiple types `T`.
-//! Any type implementing [`Distribution`] is stateless (i.e. immutable),
-//! but it may have internal parameters set at construction time (for example,
-//! [`Uniform`] allows specification of its sample space as a range within `T`).
-//!
-//!
-//! # The `Standard` distribution
-//!
-//! The [`Standard`] distribution is important to mention. This is the
-//! distribution used by [`Rng::gen()`] and represents the "default" way to
-//! produce a random value for many different types, including most primitive
-//! types, tuples, arrays, and a few derived types. See the documentation of
-//! [`Standard`] for more details.
-//!
-//! Implementing `Distribution<T>` for [`Standard`] for user types `T` makes it
-//! possible to generate type `T` with [`Rng::gen()`], and by extension also
-//! with the [`random()`] function.
-//!
-//! ## Random characters
-//!
-//! [`Alphanumeric`] is a simple distribution to sample random letters and
-//! numbers of the `char` type; in contrast [`Standard`] may sample any valid
-//! `char`.
-//!
-//!
-//! # Uniform numeric ranges
-//!
-//! The [`Uniform`] distribution is more flexible than [`Standard`], but also
-//! more specialised: it supports fewer target types, but allows the sample
-//! space to be specified as an arbitrary range within its target type `T`.
-//! Both [`Standard`] and [`Uniform`] are in some sense uniform distributions.
-//!
-//! Values may be sampled from this distribution using [`Rng::gen_range`] or
-//! by creating a distribution object with [`Uniform::new`],
-//! [`Uniform::new_inclusive`] or `From<Range>`. When the range limits are not
-//! known at compile time it is typically faster to reuse an existing
-//! distribution object than to call [`Rng::gen_range`].
-//!
-//! User types `T` may also implement `Distribution<T>` for [`Uniform`],
-//! although this is less straightforward than for [`Standard`] (see the
-//! documentation in the [`uniform`] module. Doing so enables generation of
-//! values of type `T` with [`Rng::gen_range`].
-//!
-//! ## Open and half-open ranges
-//!
-//! There are surprisingly many ways to uniformly generate random floats. A
-//! range between 0 and 1 is standard, but the exact bounds (open vs closed)
-//! and accuracy differ. In addition to the [`Standard`] distribution Rand offers
-//! [`Open01`] and [`OpenClosed01`]. See "Floating point implementation" section of
-//! [`Standard`] documentation for more details.
-//!
-//! # Non-uniform sampling
-//!
-//! Sampling a simple true/false outcome with a given probability has a name:
-//! the [`Bernoulli`] distribution (this is used by [`Rng::gen_bool`]).
-//!
-//! For weighted sampling from a sequence of discrete values, use the
-//! [`weighted`] module.
-//!
-//! This crate no longer includes other non-uniform distributions; instead
-//! it is recommended that you use either [`rand_distr`] or [`statrs`].
-//!
-//!
-//! [probability distribution]: https://en.wikipedia.org/wiki/Probability_distribution
-//! [`rand_distr`]: https://crates.io/crates/rand_distr
-//! [`statrs`]: https://crates.io/crates/statrs
-
-//! [`Alphanumeric`]: distributions::Alphanumeric
-//! [`Bernoulli`]: distributions::Bernoulli
-//! [`Open01`]: distributions::Open01
-//! [`OpenClosed01`]: distributions::OpenClosed01
-//! [`Standard`]: distributions::Standard
-//! [`Uniform`]: distributions::Uniform
-//! [`Uniform::new`]: distributions::Uniform::new
-//! [`Uniform::new_inclusive`]: distributions::Uniform::new_inclusive
-//! [`weighted`]: distributions::weighted
-//! [`rand_distr`]: https://crates.io/crates/rand_distr
-//! [`statrs`]: https://crates.io/crates/statrs
-
-use core::iter;
-use crate::Rng;
-
-pub use self::other::Alphanumeric;
-#[doc(inline)] pub use self::uniform::Uniform;
-pub use self::float::{OpenClosed01, Open01};
-pub use self::bernoulli::{Bernoulli, BernoulliError};
-#[cfg(feature="alloc")] pub use self::weighted::{WeightedIndex, WeightedError};
-
-// The following are all deprecated after being moved to rand_distr
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::unit_sphere::UnitSphereSurface;
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::unit_circle::UnitCircle;
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::gamma::{Gamma, ChiSquared, FisherF,
- StudentT, Beta};
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::normal::{Normal, LogNormal, StandardNormal};
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::exponential::{Exp, Exp1};
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::pareto::Pareto;
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::poisson::Poisson;
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::binomial::Binomial;
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::cauchy::Cauchy;
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::dirichlet::Dirichlet;
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::triangular::Triangular;
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::weibull::Weibull;
-
-pub mod uniform;
-mod bernoulli;
-#[cfg(feature="alloc")] pub mod weighted;
-#[cfg(feature="std")] mod unit_sphere;
-#[cfg(feature="std")] mod unit_circle;
-#[cfg(feature="std")] mod gamma;
-#[cfg(feature="std")] mod normal;
-#[cfg(feature="std")] mod exponential;
-#[cfg(feature="std")] mod pareto;
-#[cfg(feature="std")] mod poisson;
-#[cfg(feature="std")] mod binomial;
-#[cfg(feature="std")] mod cauchy;
-#[cfg(feature="std")] mod dirichlet;
-#[cfg(feature="std")] mod triangular;
-#[cfg(feature="std")] mod weibull;
-
-mod float;
-#[doc(hidden)] pub mod hidden_export {
- pub use super::float::IntoFloat; // used by rand_distr
-}
-mod integer;
-mod other;
-mod utils;
-#[cfg(feature="std")] mod ziggurat_tables;
-
-/// Types (distributions) that can be used to create a random instance of `T`.
-///
-/// It is possible to sample from a distribution through both the
-/// `Distribution` and [`Rng`] traits, via `distr.sample(&mut rng)` and
-/// `rng.sample(distr)`. They also both offer the [`sample_iter`] method, which
-/// produces an iterator that samples from the distribution.
-///
-/// All implementations are expected to be immutable; this has the significant
-/// advantage of not needing to consider thread safety, and for most
-/// distributions efficient state-less sampling algorithms are available.
-///
-/// [`sample_iter`]: Distribution::method.sample_iter
-pub trait Distribution<T> {
- /// Generate a random value of `T`, using `rng` as the source of randomness.
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> T;
-
- /// Create an iterator that generates random values of `T`, using `rng` as
- /// the source of randomness.
- ///
- /// Note that this function takes `self` by value. This works since
- /// `Distribution<T>` is impl'd for `&D` where `D: Distribution<T>`,
- /// however borrowing is not automatic hence `distr.sample_iter(...)` may
- /// need to be replaced with `(&distr).sample_iter(...)` to borrow or
- /// `(&*distr).sample_iter(...)` to reborrow an existing reference.
- ///
- /// # Example
- ///
- /// ```
- /// use rand::thread_rng;
- /// use rand::distributions::{Distribution, Alphanumeric, Uniform, Standard};
- ///
- /// let rng = thread_rng();
- ///
- /// // Vec of 16 x f32:
- /// let v: Vec<f32> = Standard.sample_iter(rng).take(16).collect();
- ///
- /// // String:
- /// let s: String = Alphanumeric.sample_iter(rng).take(7).collect();
- ///
- /// // Dice-rolling:
- /// let die_range = Uniform::new_inclusive(1, 6);
- /// let mut roll_die = die_range.sample_iter(rng);
- /// while roll_die.next().unwrap() != 6 {
- /// println!("Not a 6; rolling again!");
- /// }
- /// ```
- fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T>
- where R: Rng, Self: Sized
- {
- DistIter {
- distr: self,
- rng,
- phantom: ::core::marker::PhantomData,
- }
- }
-}
-
-impl<'a, T, D: Distribution<T>> Distribution<T> for &'a D {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> T {
- (*self).sample(rng)
- }
-}
-
-
-/// An iterator that generates random values of `T` with distribution `D`,
-/// using `R` as the source of randomness.
-///
-/// This `struct` is created by the [`sample_iter`] method on [`Distribution`].
-/// See its documentation for more.
-///
-/// [`sample_iter`]: Distribution::sample_iter
-#[derive(Debug)]
-pub struct DistIter<D, R, T> {
- distr: D,
- rng: R,
- phantom: ::core::marker::PhantomData<T>,
-}
-
-impl<D, R, T> Iterator for DistIter<D, R, T>
- where D: Distribution<T>, R: Rng
-{
- type Item = T;
-
- #[inline(always)]
- fn next(&mut self) -> Option<T> {
- // Here, self.rng may be a reference, but we must take &mut anyway.
- // Even if sample could take an R: Rng by value, we would need to do this
- // since Rng is not copyable and we cannot enforce that this is "reborrowable".
- Some(self.distr.sample(&mut self.rng))
- }
-
- fn size_hint(&self) -> (usize, Option<usize>) {
- (usize::max_value(), None)
- }
-}
-
-impl<D, R, T> iter::FusedIterator for DistIter<D, R, T>
- where D: Distribution<T>, R: Rng {}
-
-#[cfg(features = "nightly")]
-impl<D, R, T> iter::TrustedLen for DistIter<D, R, T>
- where D: Distribution<T>, R: Rng {}
-
-
-/// A generic random value distribution, implemented for many primitive types.
-/// Usually generates values with a numerically uniform distribution, and with a
-/// range appropriate to the type.
-///
-/// ## Provided implementations
-///
-/// Assuming the provided `Rng` is well-behaved, these implementations
-/// generate values with the following ranges and distributions:
-///
-/// * Integers (`i32`, `u32`, `isize`, `usize`, etc.): Uniformly distributed
-/// over all values of the type.
-/// * `char`: Uniformly distributed over all Unicode scalar values, i.e. all
-/// code points in the range `0...0x10_FFFF`, except for the range
-/// `0xD800...0xDFFF` (the surrogate code points). This includes
-/// unassigned/reserved code points.
-/// * `bool`: Generates `false` or `true`, each with probability 0.5.
-/// * Floating point types (`f32` and `f64`): Uniformly distributed in the
-/// half-open range `[0, 1)`. See notes below.
-/// * Wrapping integers (`Wrapping<T>`), besides the type identical to their
-/// normal integer variants.
-///
-/// The `Standard` distribution also supports generation of the following
-/// compound types where all component types are supported:
-///
-/// * Tuples (up to 12 elements): each element is generated sequentially.
-/// * Arrays (up to 32 elements): each element is generated sequentially;
-/// see also [`Rng::fill`] which supports arbitrary array length for integer
-/// types and tends to be faster for `u32` and smaller types.
-/// * `Option<T>` first generates a `bool`, and if true generates and returns
-/// `Some(value)` where `value: T`, otherwise returning `None`.
-///
-/// ## Custom implementations
-///
-/// The [`Standard`] distribution may be implemented for user types as follows:
-///
-/// ```
-/// # #![allow(dead_code)]
-/// use rand::Rng;
-/// use rand::distributions::{Distribution, Standard};
-///
-/// struct MyF32 {
-/// x: f32,
-/// }
-///
-/// impl Distribution<MyF32> for Standard {
-/// fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> MyF32 {
-/// MyF32 { x: rng.gen() }
-/// }
-/// }
-/// ```
-///
-/// ## Example usage
-/// ```
-/// use rand::prelude::*;
-/// use rand::distributions::Standard;
-///
-/// let val: f32 = StdRng::from_entropy().sample(Standard);
-/// println!("f32 from [0, 1): {}", val);
-/// ```
-///
-/// # Floating point implementation
-/// The floating point implementations for `Standard` generate a random value in
-/// the half-open interval `[0, 1)`, i.e. including 0 but not 1.
-///
-/// All values that can be generated are of the form `n * Ξ΅/2`. For `f32`
-/// the 23 most significant random bits of a `u32` are used and for `f64` the
-/// 53 most significant bits of a `u64` are used. The conversion uses the
-/// multiplicative method: `(rng.gen::<$uty>() >> N) as $ty * (Ξ΅/2)`.
-///
-/// See also: [`Open01`] which samples from `(0, 1)`, [`OpenClosed01`] which
-/// samples from `(0, 1]` and `Rng::gen_range(0, 1)` which also samples from
-/// `[0, 1)`. Note that `Open01` and `gen_range` (which uses [`Uniform`]) use
-/// transmute-based methods which yield 1 bit less precision but may perform
-/// faster on some architectures (on modern Intel CPUs all methods have
-/// approximately equal performance).
-///
-/// [`Uniform`]: uniform::Uniform
-#[derive(Clone, Copy, Debug)]
-pub struct Standard;
-
-
-#[cfg(all(test, feature = "std"))]
-mod tests {
- use crate::Rng;
- use super::{Distribution, Uniform};
-
- #[test]
- fn test_distributions_iter() {
- use crate::distributions::Open01;
- let mut rng = crate::test::rng(210);
- let distr = Open01;
- let results: Vec<f32> = distr.sample_iter(&mut rng).take(100).collect();
- println!("{:?}", results);
- }
-
- #[test]
- fn test_make_an_iter() {
- fn ten_dice_rolls_other_than_five<'a, R: Rng>(rng: &'a mut R) -> impl Iterator<Item = i32> + 'a {
- Uniform::new_inclusive(1, 6)
- .sample_iter(rng)
- .filter(|x| *x != 5)
- .take(10)
- }
-
- let mut rng = crate::test::rng(211);
- let mut count = 0;
- for val in ten_dice_rolls_other_than_five(&mut rng) {
- assert!(val >= 1 && val <= 6 && val != 5);
- count += 1;
- }
- assert_eq!(count, 10);
- }
-}
diff --git a/rand/src/distributions/normal.rs b/rand/src/distributions/normal.rs
deleted file mode 100644
index 7808baf..0000000
--- a/rand/src/distributions/normal.rs
+++ /dev/null
@@ -1,170 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The normal and derived distributions.
-#![allow(deprecated)]
-
-use crate::Rng;
-use crate::distributions::{ziggurat_tables, Distribution, Open01};
-use crate::distributions::utils::ziggurat;
-
-/// Samples floating-point numbers according to the normal distribution
-/// `N(0, 1)` (a.k.a. a standard normal, or Gaussian). This is equivalent to
-/// `Normal::new(0.0, 1.0)` but faster.
-///
-/// See `Normal` for the general normal distribution.
-///
-/// Implemented via the ZIGNOR variant[^1] of the Ziggurat method.
-///
-/// [^1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method to
-/// Generate Normal Random Samples*](
-/// https://www.doornik.com/research/ziggurat.pdf).
-/// Nuffield College, Oxford
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct StandardNormal;
-
-impl Distribution<f64> for StandardNormal {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- #[inline]
- fn pdf(x: f64) -> f64 {
- (-x*x/2.0).exp()
- }
- #[inline]
- fn zero_case<R: Rng + ?Sized>(rng: &mut R, u: f64) -> f64 {
- // compute a random number in the tail by hand
-
- // strange initial conditions, because the loop is not
- // do-while, so the condition should be true on the first
- // run, they get overwritten anyway (0 < 1, so these are
- // good).
- let mut x = 1.0f64;
- let mut y = 0.0f64;
-
- while -2.0 * y < x * x {
- let x_: f64 = rng.sample(Open01);
- let y_: f64 = rng.sample(Open01);
-
- x = x_.ln() / ziggurat_tables::ZIG_NORM_R;
- y = y_.ln();
- }
-
- if u < 0.0 { x - ziggurat_tables::ZIG_NORM_R } else { ziggurat_tables::ZIG_NORM_R - x }
- }
-
- ziggurat(rng, true, // this is symmetric
- &ziggurat_tables::ZIG_NORM_X,
- &ziggurat_tables::ZIG_NORM_F,
- pdf, zero_case)
- }
-}
-
-/// The normal distribution `N(mean, std_dev**2)`.
-///
-/// This uses the ZIGNOR variant of the Ziggurat method, see [`StandardNormal`]
-/// for more details.
-///
-/// Note that [`StandardNormal`] is an optimised implementation for mean 0, and
-/// standard deviation 1.
-///
-/// [`StandardNormal`]: crate::distributions::StandardNormal
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Normal {
- mean: f64,
- std_dev: f64,
-}
-
-impl Normal {
- /// Construct a new `Normal` distribution with the given mean and
- /// standard deviation.
- ///
- /// # Panics
- ///
- /// Panics if `std_dev < 0`.
- #[inline]
- pub fn new(mean: f64, std_dev: f64) -> Normal {
- assert!(std_dev >= 0.0, "Normal::new called with `std_dev` < 0");
- Normal {
- mean,
- std_dev
- }
- }
-}
-impl Distribution<f64> for Normal {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- let n = rng.sample(StandardNormal);
- self.mean + self.std_dev * n
- }
-}
-
-
-/// The log-normal distribution `ln N(mean, std_dev**2)`.
-///
-/// If `X` is log-normal distributed, then `ln(X)` is `N(mean, std_dev**2)`
-/// distributed.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct LogNormal {
- norm: Normal
-}
-
-impl LogNormal {
- /// Construct a new `LogNormal` distribution with the given mean
- /// and standard deviation.
- ///
- /// # Panics
- ///
- /// Panics if `std_dev < 0`.
- #[inline]
- pub fn new(mean: f64, std_dev: f64) -> LogNormal {
- assert!(std_dev >= 0.0, "LogNormal::new called with `std_dev` < 0");
- LogNormal { norm: Normal::new(mean, std_dev) }
- }
-}
-impl Distribution<f64> for LogNormal {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- self.norm.sample(rng).exp()
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::distributions::Distribution;
- use super::{Normal, LogNormal};
-
- #[test]
- fn test_normal() {
- let norm = Normal::new(10.0, 10.0);
- let mut rng = crate::test::rng(210);
- for _ in 0..1000 {
- norm.sample(&mut rng);
- }
- }
- #[test]
- #[should_panic]
- fn test_normal_invalid_sd() {
- Normal::new(10.0, -1.0);
- }
-
-
- #[test]
- fn test_log_normal() {
- let lnorm = LogNormal::new(10.0, 10.0);
- let mut rng = crate::test::rng(211);
- for _ in 0..1000 {
- lnorm.sample(&mut rng);
- }
- }
- #[test]
- #[should_panic]
- fn test_log_normal_invalid_sd() {
- LogNormal::new(10.0, -1.0);
- }
-}
diff --git a/rand/src/distributions/other.rs b/rand/src/distributions/other.rs
deleted file mode 100644
index 6ec0473..0000000
--- a/rand/src/distributions/other.rs
+++ /dev/null
@@ -1,220 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The implementations of the `Standard` distribution for other built-in types.
-
-use core::char;
-use core::num::Wrapping;
-
-use crate::Rng;
-use crate::distributions::{Distribution, Standard, Uniform};
-
-// ----- Sampling distributions -----
-
-/// Sample a `char`, uniformly distributed over ASCII letters and numbers:
-/// a-z, A-Z and 0-9.
-///
-/// # Example
-///
-/// ```
-/// use std::iter;
-/// use rand::{Rng, thread_rng};
-/// use rand::distributions::Alphanumeric;
-///
-/// let mut rng = thread_rng();
-/// let chars: String = iter::repeat(())
-/// .map(|()| rng.sample(Alphanumeric))
-/// .take(7)
-/// .collect();
-/// println!("Random chars: {}", chars);
-/// ```
-#[derive(Debug)]
-pub struct Alphanumeric;
-
-
-// ----- Implementations of distributions -----
-
-impl Distribution<char> for Standard {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> char {
- // A valid `char` is either in the interval `[0, 0xD800)` or
- // `(0xDFFF, 0x11_0000)`. All `char`s must therefore be in
- // `[0, 0x11_0000)` but not in the "gap" `[0xD800, 0xDFFF]` which is
- // reserved for surrogates. This is the size of that gap.
- const GAP_SIZE: u32 = 0xDFFF - 0xD800 + 1;
-
- // Uniform::new(0, 0x11_0000 - GAP_SIZE) can also be used but it
- // seemed slower.
- let range = Uniform::new(GAP_SIZE, 0x11_0000);
-
- let mut n = range.sample(rng);
- if n <= 0xDFFF {
- n -= GAP_SIZE;
- }
- unsafe { char::from_u32_unchecked(n) }
- }
-}
-
-impl Distribution<char> for Alphanumeric {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> char {
- const RANGE: u32 = 26 + 26 + 10;
- const GEN_ASCII_STR_CHARSET: &[u8] =
- b"ABCDEFGHIJKLMNOPQRSTUVWXYZ\
- abcdefghijklmnopqrstuvwxyz\
- 0123456789";
- // We can pick from 62 characters. This is so close to a power of 2, 64,
- // that we can do better than `Uniform`. Use a simple bitshift and
- // rejection sampling. We do not use a bitmask, because for small RNGs
- // the most significant bits are usually of higher quality.
- loop {
- let var = rng.next_u32() >> (32 - 6);
- if var < RANGE {
- return GEN_ASCII_STR_CHARSET[var as usize] as char
- }
- }
- }
-}
-
-impl Distribution<bool> for Standard {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> bool {
- // We can compare against an arbitrary bit of an u32 to get a bool.
- // Because the least significant bits of a lower quality RNG can have
- // simple patterns, we compare against the most significant bit. This is
- // easiest done using a sign test.
- (rng.next_u32() as i32) < 0
- }
-}
-
-macro_rules! tuple_impl {
- // use variables to indicate the arity of the tuple
- ($($tyvar:ident),* ) => {
- // the trailing commas are for the 1 tuple
- impl< $( $tyvar ),* >
- Distribution<( $( $tyvar ),* , )>
- for Standard
- where $( Standard: Distribution<$tyvar> ),*
- {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> ( $( $tyvar ),* , ) {
- (
- // use the $tyvar's to get the appropriate number of
- // repeats (they're not actually needed)
- $(
- _rng.gen::<$tyvar>()
- ),*
- ,
- )
- }
- }
- }
-}
-
-impl Distribution<()> for Standard {
- #[allow(clippy::unused_unit)]
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, _: &mut R) -> () { () }
-}
-tuple_impl!{A}
-tuple_impl!{A, B}
-tuple_impl!{A, B, C}
-tuple_impl!{A, B, C, D}
-tuple_impl!{A, B, C, D, E}
-tuple_impl!{A, B, C, D, E, F}
-tuple_impl!{A, B, C, D, E, F, G}
-tuple_impl!{A, B, C, D, E, F, G, H}
-tuple_impl!{A, B, C, D, E, F, G, H, I}
-tuple_impl!{A, B, C, D, E, F, G, H, I, J}
-tuple_impl!{A, B, C, D, E, F, G, H, I, J, K}
-tuple_impl!{A, B, C, D, E, F, G, H, I, J, K, L}
-
-macro_rules! array_impl {
- // recursive, given at least one type parameter:
- {$n:expr, $t:ident, $($ts:ident,)*} => {
- array_impl!{($n - 1), $($ts,)*}
-
- impl<T> Distribution<[T; $n]> for Standard where Standard: Distribution<T> {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> [T; $n] {
- [_rng.gen::<$t>(), $(_rng.gen::<$ts>()),*]
- }
- }
- };
- // empty case:
- {$n:expr,} => {
- impl<T> Distribution<[T; $n]> for Standard {
- fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> [T; $n] { [] }
- }
- };
-}
-
-array_impl!{32, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T,}
-
-impl<T> Distribution<Option<T>> for Standard where Standard: Distribution<T> {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Option<T> {
- // UFCS is needed here: https://github.com/rust-lang/rust/issues/24066
- if rng.gen::<bool>() {
- Some(rng.gen())
- } else {
- None
- }
- }
-}
-
-impl<T> Distribution<Wrapping<T>> for Standard where Standard: Distribution<T> {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Wrapping<T> {
- Wrapping(rng.gen())
- }
-}
-
-
-#[cfg(test)]
-mod tests {
- use crate::{Rng, RngCore, Standard};
- use crate::distributions::Alphanumeric;
- #[cfg(all(not(feature="std"), feature="alloc"))] use alloc::string::String;
-
- #[test]
- fn test_misc() {
- let rng: &mut dyn RngCore = &mut crate::test::rng(820);
-
- rng.sample::<char, _>(Standard);
- rng.sample::<bool, _>(Standard);
- }
-
- #[cfg(feature="alloc")]
- #[test]
- fn test_chars() {
- use core::iter;
- let mut rng = crate::test::rng(805);
-
- // Test by generating a relatively large number of chars, so we also
- // take the rejection sampling path.
- let word: String = iter::repeat(())
- .map(|()| rng.gen::<char>()).take(1000).collect();
- assert!(word.len() != 0);
- }
-
- #[test]
- fn test_alphanumeric() {
- let mut rng = crate::test::rng(806);
-
- // Test by generating a relatively large number of chars, so we also
- // take the rejection sampling path.
- let mut incorrect = false;
- for _ in 0..100 {
- let c = rng.sample(Alphanumeric);
- incorrect |= !((c >= '0' && c <= '9') ||
- (c >= 'A' && c <= 'Z') ||
- (c >= 'a' && c <= 'z') );
- }
- assert!(incorrect == false);
- }
-}
diff --git a/rand/src/distributions/pareto.rs b/rand/src/distributions/pareto.rs
deleted file mode 100644
index edc9122..0000000
--- a/rand/src/distributions/pareto.rs
+++ /dev/null
@@ -1,67 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The Pareto distribution.
-#![allow(deprecated)]
-
-use crate::Rng;
-use crate::distributions::{Distribution, OpenClosed01};
-
-/// Samples floating-point numbers according to the Pareto distribution
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Pareto {
- scale: f64,
- inv_neg_shape: f64,
-}
-
-impl Pareto {
- /// Construct a new Pareto distribution with given `scale` and `shape`.
- ///
- /// In the literature, `scale` is commonly written as x<sub>m</sub> or k and
- /// `shape` is often written as Ξ±.
- ///
- /// # Panics
- ///
- /// `scale` and `shape` have to be non-zero and positive.
- pub fn new(scale: f64, shape: f64) -> Pareto {
- assert!((scale > 0.) & (shape > 0.));
- Pareto { scale, inv_neg_shape: -1.0 / shape }
- }
-}
-
-impl Distribution<f64> for Pareto {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- let u: f64 = rng.sample(OpenClosed01);
- self.scale * u.powf(self.inv_neg_shape)
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::distributions::Distribution;
- use super::Pareto;
-
- #[test]
- #[should_panic]
- fn invalid() {
- Pareto::new(0., 0.);
- }
-
- #[test]
- fn sample() {
- let scale = 1.0;
- let shape = 2.0;
- let d = Pareto::new(scale, shape);
- let mut rng = crate::test::rng(1);
- for _ in 0..1000 {
- let r = d.sample(&mut rng);
- assert!(r >= scale);
- }
- }
-}
diff --git a/rand/src/distributions/poisson.rs b/rand/src/distributions/poisson.rs
deleted file mode 100644
index 9fd6e99..0000000
--- a/rand/src/distributions/poisson.rs
+++ /dev/null
@@ -1,151 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2016-2017 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The Poisson distribution.
-#![allow(deprecated)]
-
-use crate::Rng;
-use crate::distributions::{Distribution, Cauchy};
-use crate::distributions::utils::log_gamma;
-
-/// The Poisson distribution `Poisson(lambda)`.
-///
-/// This distribution has a density function:
-/// `f(k) = lambda^k * exp(-lambda) / k!` for `k >= 0`.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Poisson {
- lambda: f64,
- // precalculated values
- exp_lambda: f64,
- log_lambda: f64,
- sqrt_2lambda: f64,
- magic_val: f64,
-}
-
-impl Poisson {
- /// Construct a new `Poisson` with the given shape parameter
- /// `lambda`. Panics if `lambda <= 0`.
- pub fn new(lambda: f64) -> Poisson {
- assert!(lambda > 0.0, "Poisson::new called with lambda <= 0");
- let log_lambda = lambda.ln();
- Poisson {
- lambda,
- exp_lambda: (-lambda).exp(),
- log_lambda,
- sqrt_2lambda: (2.0 * lambda).sqrt(),
- magic_val: lambda * log_lambda - log_gamma(1.0 + lambda),
- }
- }
-}
-
-impl Distribution<u64> for Poisson {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u64 {
- // using the algorithm from Numerical Recipes in C
-
- // for low expected values use the Knuth method
- if self.lambda < 12.0 {
- let mut result = 0;
- let mut p = 1.0;
- while p > self.exp_lambda {
- p *= rng.gen::<f64>();
- result += 1;
- }
- result - 1
- }
- // high expected values - rejection method
- else {
- let mut int_result: u64;
-
- // we use the Cauchy distribution as the comparison distribution
- // f(x) ~ 1/(1+x^2)
- let cauchy = Cauchy::new(0.0, 1.0);
-
- loop {
- let mut result;
- let mut comp_dev;
-
- loop {
- // draw from the Cauchy distribution
- comp_dev = rng.sample(cauchy);
- // shift the peak of the comparison ditribution
- result = self.sqrt_2lambda * comp_dev + self.lambda;
- // repeat the drawing until we are in the range of possible values
- if result >= 0.0 {
- break;
- }
- }
- // now the result is a random variable greater than 0 with Cauchy distribution
- // the result should be an integer value
- result = result.floor();
- int_result = result as u64;
-
- // this is the ratio of the Poisson distribution to the comparison distribution
- // the magic value scales the distribution function to a range of approximately 0-1
- // since it is not exact, we multiply the ratio by 0.9 to avoid ratios greater than 1
- // this doesn't change the resulting distribution, only increases the rate of failed drawings
- let check = 0.9 * (1.0 + comp_dev * comp_dev)
- * (result * self.log_lambda - log_gamma(1.0 + result) - self.magic_val).exp();
-
- // check with uniform random value - if below the threshold, we are within the target distribution
- if rng.gen::<f64>() <= check {
- break;
- }
- }
- int_result
- }
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::distributions::Distribution;
- use super::Poisson;
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_poisson_10() {
- let poisson = Poisson::new(10.0);
- let mut rng = crate::test::rng(123);
- let mut sum = 0;
- for _ in 0..1000 {
- sum += poisson.sample(&mut rng);
- }
- let avg = (sum as f64) / 1000.0;
- println!("Poisson average: {}", avg);
- assert!((avg - 10.0).abs() < 0.5); // not 100% certain, but probable enough
- }
-
- #[test]
- #[cfg(not(miri))] // Miri doesn't support transcendental functions
- fn test_poisson_15() {
- // Take the 'high expected values' path
- let poisson = Poisson::new(15.0);
- let mut rng = crate::test::rng(123);
- let mut sum = 0;
- for _ in 0..1000 {
- sum += poisson.sample(&mut rng);
- }
- let avg = (sum as f64) / 1000.0;
- println!("Poisson average: {}", avg);
- assert!((avg - 15.0).abs() < 0.5); // not 100% certain, but probable enough
- }
-
- #[test]
- #[should_panic]
- fn test_poisson_invalid_lambda_zero() {
- Poisson::new(0.0);
- }
-
- #[test]
- #[should_panic]
- fn test_poisson_invalid_lambda_neg() {
- Poisson::new(-10.0);
- }
-}
diff --git a/rand/src/distributions/triangular.rs b/rand/src/distributions/triangular.rs
deleted file mode 100644
index 3e8f8b0..0000000
--- a/rand/src/distributions/triangular.rs
+++ /dev/null
@@ -1,79 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The triangular distribution.
-#![allow(deprecated)]
-
-use crate::Rng;
-use crate::distributions::{Distribution, Standard};
-
-/// The triangular distribution.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Triangular {
- min: f64,
- max: f64,
- mode: f64,
-}
-
-impl Triangular {
- /// Construct a new `Triangular` with minimum `min`, maximum `max` and mode
- /// `mode`.
- ///
- /// # Panics
- ///
- /// If `max < mode`, `mode < max` or `max == min`.
- ///
- #[inline]
- pub fn new(min: f64, max: f64, mode: f64) -> Triangular {
- assert!(max >= mode);
- assert!(mode >= min);
- assert!(max != min);
- Triangular { min, max, mode }
- }
-}
-
-impl Distribution<f64> for Triangular {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- let f: f64 = rng.sample(Standard);
- let diff_mode_min = self.mode - self.min;
- let diff_max_min = self.max - self.min;
- if f * diff_max_min < diff_mode_min {
- self.min + (f * diff_max_min * diff_mode_min).sqrt()
- } else {
- self.max - ((1. - f) * diff_max_min * (self.max - self.mode)).sqrt()
- }
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::distributions::Distribution;
- use super::Triangular;
-
- #[test]
- fn test_new() {
- for &(min, max, mode) in &[
- (-1., 1., 0.), (1., 2., 1.), (5., 25., 25.), (1e-5, 1e5, 1e-3),
- (0., 1., 0.9), (-4., -0.5, -2.), (-13.039, 8.41, 1.17),
- ] {
- println!("{} {} {}", min, max, mode);
- let _ = Triangular::new(min, max, mode);
- }
- }
-
- #[test]
- fn test_sample() {
- let norm = Triangular::new(0., 1., 0.5);
- let mut rng = crate::test::rng(1);
- for _ in 0..1000 {
- norm.sample(&mut rng);
- }
- }
-}
diff --git a/rand/src/distributions/uniform.rs b/rand/src/distributions/uniform.rs
deleted file mode 100644
index 8c90f4e..0000000
--- a/rand/src/distributions/uniform.rs
+++ /dev/null
@@ -1,1270 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2017 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! A distribution uniformly sampling numbers within a given range.
-//!
-//! [`Uniform`] is the standard distribution to sample uniformly from a range;
-//! e.g. `Uniform::new_inclusive(1, 6)` can sample integers from 1 to 6, like a
-//! standard die. [`Rng::gen_range`] supports any type supported by
-//! [`Uniform`].
-//!
-//! This distribution is provided with support for several primitive types
-//! (all integer and floating-point types) as well as [`std::time::Duration`],
-//! and supports extension to user-defined types via a type-specific *back-end*
-//! implementation.
-//!
-//! The types [`UniformInt`], [`UniformFloat`] and [`UniformDuration`] are the
-//! back-ends supporting sampling from primitive integer and floating-point
-//! ranges as well as from [`std::time::Duration`]; these types do not normally
-//! need to be used directly (unless implementing a derived back-end).
-//!
-//! # Example usage
-//!
-//! ```
-//! use rand::{Rng, thread_rng};
-//! use rand::distributions::Uniform;
-//!
-//! let mut rng = thread_rng();
-//! let side = Uniform::new(-10.0, 10.0);
-//!
-//! // sample between 1 and 10 points
-//! for _ in 0..rng.gen_range(1, 11) {
-//! // sample a point from the square with sides -10 - 10 in two dimensions
-//! let (x, y) = (rng.sample(side), rng.sample(side));
-//! println!("Point: {}, {}", x, y);
-//! }
-//! ```
-//!
-//! # Extending `Uniform` to support a custom type
-//!
-//! To extend [`Uniform`] to support your own types, write a back-end which
-//! implements the [`UniformSampler`] trait, then implement the [`SampleUniform`]
-//! helper trait to "register" your back-end. See the `MyF32` example below.
-//!
-//! At a minimum, the back-end needs to store any parameters needed for sampling
-//! (e.g. the target range) and implement `new`, `new_inclusive` and `sample`.
-//! Those methods should include an assert to check the range is valid (i.e.
-//! `low < high`). The example below merely wraps another back-end.
-//!
-//! The `new`, `new_inclusive` and `sample_single` functions use arguments of
-//! type SampleBorrow<X> in order to support passing in values by reference or
-//! by value. In the implementation of these functions, you can choose to
-//! simply use the reference returned by [`SampleBorrow::borrow`], or you can choose
-//! to copy or clone the value, whatever is appropriate for your type.
-//!
-//! ```
-//! use rand::prelude::*;
-//! use rand::distributions::uniform::{Uniform, SampleUniform,
-//! UniformSampler, UniformFloat, SampleBorrow};
-//!
-//! struct MyF32(f32);
-//!
-//! #[derive(Clone, Copy, Debug)]
-//! struct UniformMyF32 {
-//! inner: UniformFloat<f32>,
-//! }
-//!
-//! impl UniformSampler for UniformMyF32 {
-//! type X = MyF32;
-//! fn new<B1, B2>(low: B1, high: B2) -> Self
-//! where B1: SampleBorrow<Self::X> + Sized,
-//! B2: SampleBorrow<Self::X> + Sized
-//! {
-//! UniformMyF32 {
-//! inner: UniformFloat::<f32>::new(low.borrow().0, high.borrow().0),
-//! }
-//! }
-//! fn new_inclusive<B1, B2>(low: B1, high: B2) -> Self
-//! where B1: SampleBorrow<Self::X> + Sized,
-//! B2: SampleBorrow<Self::X> + Sized
-//! {
-//! UniformSampler::new(low, high)
-//! }
-//! fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Self::X {
-//! MyF32(self.inner.sample(rng))
-//! }
-//! }
-//!
-//! impl SampleUniform for MyF32 {
-//! type Sampler = UniformMyF32;
-//! }
-//!
-//! let (low, high) = (MyF32(17.0f32), MyF32(22.0f32));
-//! let uniform = Uniform::new(low, high);
-//! let x = uniform.sample(&mut thread_rng());
-//! ```
-//!
-//! [`SampleUniform`]: crate::distributions::uniform::SampleUniform
-//! [`UniformSampler`]: crate::distributions::uniform::UniformSampler
-//! [`UniformInt`]: crate::distributions::uniform::UniformInt
-//! [`UniformFloat`]: crate::distributions::uniform::UniformFloat
-//! [`UniformDuration`]: crate::distributions::uniform::UniformDuration
-//! [`SampleBorrow::borrow`]: crate::distributions::uniform::SampleBorrow::borrow
-
-#[cfg(feature = "std")]
-use std::time::Duration;
-#[cfg(not(feature = "std"))]
-use core::time::Duration;
-
-use crate::Rng;
-use crate::distributions::Distribution;
-use crate::distributions::float::IntoFloat;
-use crate::distributions::utils::{WideningMultiply, FloatSIMDUtils, FloatAsSIMD, BoolAsSIMD};
-
-#[cfg(not(feature = "std"))]
-#[allow(unused_imports)] // rustc doesn't detect that this is actually used
-use crate::distributions::utils::Float;
-
-
-#[cfg(feature="simd_support")]
-use packed_simd::*;
-
-/// Sample values uniformly between two bounds.
-///
-/// [`Uniform::new`] and [`Uniform::new_inclusive`] construct a uniform
-/// distribution sampling from the given range; these functions may do extra
-/// work up front to make sampling of multiple values faster.
-///
-/// When sampling from a constant range, many calculations can happen at
-/// compile-time and all methods should be fast; for floating-point ranges and
-/// the full range of integer types this should have comparable performance to
-/// the `Standard` distribution.
-///
-/// Steps are taken to avoid bias which might be present in naive
-/// implementations; for example `rng.gen::<u8>() % 170` samples from the range
-/// `[0, 169]` but is twice as likely to select numbers less than 85 than other
-/// values. Further, the implementations here give more weight to the high-bits
-/// generated by the RNG than the low bits, since with some RNGs the low-bits
-/// are of lower quality than the high bits.
-///
-/// Implementations must sample in `[low, high)` range for
-/// `Uniform::new(low, high)`, i.e., excluding `high`. In particular care must
-/// be taken to ensure that rounding never results values `< low` or `>= high`.
-///
-/// # Example
-///
-/// ```
-/// use rand::distributions::{Distribution, Uniform};
-///
-/// fn main() {
-/// let between = Uniform::from(10..10000);
-/// let mut rng = rand::thread_rng();
-/// let mut sum = 0;
-/// for _ in 0..1000 {
-/// sum += between.sample(&mut rng);
-/// }
-/// println!("{}", sum);
-/// }
-/// ```
-///
-/// [`new`]: Uniform::new
-/// [`new_inclusive`]: Uniform::new_inclusive
-#[derive(Clone, Copy, Debug)]
-pub struct Uniform<X: SampleUniform> {
- inner: X::Sampler,
-}
-
-impl<X: SampleUniform> Uniform<X> {
- /// Create a new `Uniform` instance which samples uniformly from the half
- /// open range `[low, high)` (excluding `high`). Panics if `low >= high`.
- pub fn new<B1, B2>(low: B1, high: B2) -> Uniform<X>
- where B1: SampleBorrow<X> + Sized,
- B2: SampleBorrow<X> + Sized
- {
- Uniform { inner: X::Sampler::new(low, high) }
- }
-
- /// Create a new `Uniform` instance which samples uniformly from the closed
- /// range `[low, high]` (inclusive). Panics if `low > high`.
- pub fn new_inclusive<B1, B2>(low: B1, high: B2) -> Uniform<X>
- where B1: SampleBorrow<X> + Sized,
- B2: SampleBorrow<X> + Sized
- {
- Uniform { inner: X::Sampler::new_inclusive(low, high) }
- }
-}
-
-impl<X: SampleUniform> Distribution<X> for Uniform<X> {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> X {
- self.inner.sample(rng)
- }
-}
-
-/// Helper trait for creating objects using the correct implementation of
-/// [`UniformSampler`] for the sampling type.
-///
-/// See the [module documentation] on how to implement [`Uniform`] range
-/// sampling for a custom type.
-///
-/// [module documentation]: crate::distributions::uniform
-pub trait SampleUniform: Sized {
- /// The `UniformSampler` implementation supporting type `X`.
- type Sampler: UniformSampler<X = Self>;
-}
-
-/// Helper trait handling actual uniform sampling.
-///
-/// See the [module documentation] on how to implement [`Uniform`] range
-/// sampling for a custom type.
-///
-/// Implementation of [`sample_single`] is optional, and is only useful when
-/// the implementation can be faster than `Self::new(low, high).sample(rng)`.
-///
-/// [module documentation]: crate::distributions::uniform
-/// [`sample_single`]: UniformSampler::sample_single
-pub trait UniformSampler: Sized {
- /// The type sampled by this implementation.
- type X;
-
- /// Construct self, with inclusive lower bound and exclusive upper bound
- /// `[low, high)`.
- ///
- /// Usually users should not call this directly but instead use
- /// `Uniform::new`, which asserts that `low < high` before calling this.
- fn new<B1, B2>(low: B1, high: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized;
-
- /// Construct self, with inclusive bounds `[low, high]`.
- ///
- /// Usually users should not call this directly but instead use
- /// `Uniform::new_inclusive`, which asserts that `low <= high` before
- /// calling this.
- fn new_inclusive<B1, B2>(low: B1, high: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized;
-
- /// Sample a value.
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Self::X;
-
- /// Sample a single value uniformly from a range with inclusive lower bound
- /// and exclusive upper bound `[low, high)`.
- ///
- /// By default this is implemented using
- /// `UniformSampler::new(low, high).sample(rng)`. However, for some types
- /// more optimal implementations for single usage may be provided via this
- /// method (which is the case for integers and floats).
- /// Results may not be identical.
- fn sample_single<R: Rng + ?Sized, B1, B2>(low: B1, high: B2, rng: &mut R)
- -> Self::X
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- let uniform: Self = UniformSampler::new(low, high);
- uniform.sample(rng)
- }
-}
-
-impl<X: SampleUniform> From<::core::ops::Range<X>> for Uniform<X> {
- fn from(r: ::core::ops::Range<X>) -> Uniform<X> {
- Uniform::new(r.start, r.end)
- }
-}
-
-impl<X: SampleUniform> From<::core::ops::RangeInclusive<X>> for Uniform<X> {
- fn from(r: ::core::ops::RangeInclusive<X>) -> Uniform<X> {
- Uniform::new_inclusive(r.start(), r.end())
- }
-}
-
-/// Helper trait similar to [`Borrow`] but implemented
-/// only for SampleUniform and references to SampleUniform in
-/// order to resolve ambiguity issues.
-///
-/// [`Borrow`]: std::borrow::Borrow
-pub trait SampleBorrow<Borrowed> {
- /// Immutably borrows from an owned value. See [`Borrow::borrow`]
- ///
- /// [`Borrow::borrow`]: std::borrow::Borrow::borrow
- fn borrow(&self) -> &Borrowed;
-}
-impl<Borrowed> SampleBorrow<Borrowed> for Borrowed where Borrowed: SampleUniform {
- #[inline(always)]
- fn borrow(&self) -> &Borrowed { self }
-}
-impl<'a, Borrowed> SampleBorrow<Borrowed> for &'a Borrowed where Borrowed: SampleUniform {
- #[inline(always)]
- fn borrow(&self) -> &Borrowed { *self }
-}
-
-////////////////////////////////////////////////////////////////////////////////
-
-// What follows are all back-ends.
-
-
-/// The back-end implementing [`UniformSampler`] for integer types.
-///
-/// Unless you are implementing [`UniformSampler`] for your own type, this type
-/// should not be used directly, use [`Uniform`] instead.
-///
-/// # Implementation notes
-///
-/// For simplicity, we use the same generic struct `UniformInt<X>` for all
-/// integer types `X`. This gives us only one field type, `X`; to store unsigned
-/// values of this size, we take use the fact that these conversions are no-ops.
-///
-/// For a closed range, the number of possible numbers we should generate is
-/// `range = (high - low + 1)`. To avoid bias, we must ensure that the size of
-/// our sample space, `zone`, is a multiple of `range`; other values must be
-/// rejected (by replacing with a new random sample).
-///
-/// As a special case, we use `range = 0` to represent the full range of the
-/// result type (i.e. for `new_inclusive($ty::MIN, $ty::MAX)`).
-///
-/// The optimum `zone` is the largest product of `range` which fits in our
-/// (unsigned) target type. We calculate this by calculating how many numbers we
-/// must reject: `reject = (MAX + 1) % range = (MAX - range + 1) % range`. Any (large)
-/// product of `range` will suffice, thus in `sample_single` we multiply by a
-/// power of 2 via bit-shifting (faster but may cause more rejections).
-///
-/// The smallest integer PRNGs generate is `u32`. For 8- and 16-bit outputs we
-/// use `u32` for our `zone` and samples (because it's not slower and because
-/// it reduces the chance of having to reject a sample). In this case we cannot
-/// store `zone` in the target type since it is too large, however we know
-/// `ints_to_reject < range <= $unsigned::MAX`.
-///
-/// An alternative to using a modulus is widening multiply: After a widening
-/// multiply by `range`, the result is in the high word. Then comparing the low
-/// word against `zone` makes sure our distribution is uniform.
-#[derive(Clone, Copy, Debug)]
-pub struct UniformInt<X> {
- low: X,
- range: X,
- z: X, // either ints_to_reject or zone depending on implementation
-}
-
-macro_rules! uniform_int_impl {
- ($ty:ty, $unsigned:ident, $u_large:ident) => {
- impl SampleUniform for $ty {
- type Sampler = UniformInt<$ty>;
- }
-
- impl UniformSampler for UniformInt<$ty> {
- // We play free and fast with unsigned vs signed here
- // (when $ty is signed), but that's fine, since the
- // contract of this macro is for $ty and $unsigned to be
- // "bit-equal", so casting between them is a no-op.
-
- type X = $ty;
-
- #[inline] // if the range is constant, this helps LLVM to do the
- // calculations at compile-time.
- fn new<B1, B2>(low_b: B1, high_b: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- let low = *low_b.borrow();
- let high = *high_b.borrow();
- assert!(low < high, "Uniform::new called with `low >= high`");
- UniformSampler::new_inclusive(low, high - 1)
- }
-
- #[inline] // if the range is constant, this helps LLVM to do the
- // calculations at compile-time.
- fn new_inclusive<B1, B2>(low_b: B1, high_b: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- let low = *low_b.borrow();
- let high = *high_b.borrow();
- assert!(low <= high,
- "Uniform::new_inclusive called with `low > high`");
- let unsigned_max = ::core::$u_large::MAX;
-
- let range = high.wrapping_sub(low).wrapping_add(1) as $unsigned;
- let ints_to_reject =
- if range > 0 {
- let range = $u_large::from(range);
- (unsigned_max - range + 1) % range
- } else {
- 0
- };
-
- UniformInt {
- low: low,
- // These are really $unsigned values, but store as $ty:
- range: range as $ty,
- z: ints_to_reject as $unsigned as $ty
- }
- }
-
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Self::X {
- let range = self.range as $unsigned as $u_large;
- if range > 0 {
- let unsigned_max = ::core::$u_large::MAX;
- let zone = unsigned_max - (self.z as $unsigned as $u_large);
- loop {
- let v: $u_large = rng.gen();
- let (hi, lo) = v.wmul(range);
- if lo <= zone {
- return self.low.wrapping_add(hi as $ty);
- }
- }
- } else {
- // Sample from the entire integer range.
- rng.gen()
- }
- }
-
- fn sample_single<R: Rng + ?Sized, B1, B2>(low_b: B1, high_b: B2, rng: &mut R)
- -> Self::X
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- let low = *low_b.borrow();
- let high = *high_b.borrow();
- assert!(low < high,
- "UniformSampler::sample_single: low >= high");
- let range = high.wrapping_sub(low) as $unsigned as $u_large;
- let zone =
- if ::core::$unsigned::MAX <= ::core::u16::MAX as $unsigned {
- // Using a modulus is faster than the approximation for
- // i8 and i16. I suppose we trade the cost of one
- // modulus for near-perfect branch prediction.
- let unsigned_max: $u_large = ::core::$u_large::MAX;
- let ints_to_reject = (unsigned_max - range + 1) % range;
- unsigned_max - ints_to_reject
- } else {
- // conservative but fast approximation. `- 1` is necessary to allow the
- // same comparison without bias.
- (range << range.leading_zeros()).wrapping_sub(1)
- };
-
- loop {
- let v: $u_large = rng.gen();
- let (hi, lo) = v.wmul(range);
- if lo <= zone {
- return low.wrapping_add(hi as $ty);
- }
- }
- }
- }
- }
-}
-
-uniform_int_impl! { i8, u8, u32 }
-uniform_int_impl! { i16, u16, u32 }
-uniform_int_impl! { i32, u32, u32 }
-uniform_int_impl! { i64, u64, u64 }
-#[cfg(not(target_os = "emscripten"))]
-uniform_int_impl! { i128, u128, u128 }
-uniform_int_impl! { isize, usize, usize }
-uniform_int_impl! { u8, u8, u32 }
-uniform_int_impl! { u16, u16, u32 }
-uniform_int_impl! { u32, u32, u32 }
-uniform_int_impl! { u64, u64, u64 }
-uniform_int_impl! { usize, usize, usize }
-#[cfg(not(target_os = "emscripten"))]
-uniform_int_impl! { u128, u128, u128 }
-
-#[cfg(all(feature = "simd_support", feature = "nightly"))]
-macro_rules! uniform_simd_int_impl {
- ($ty:ident, $unsigned:ident, $u_scalar:ident) => {
- // The "pick the largest zone that can fit in an `u32`" optimization
- // is less useful here. Multiple lanes complicate things, we don't
- // know the PRNG's minimal output size, and casting to a larger vector
- // is generally a bad idea for SIMD performance. The user can still
- // implement it manually.
-
- // TODO: look into `Uniform::<u32x4>::new(0u32, 100)` functionality
- // perhaps `impl SampleUniform for $u_scalar`?
- impl SampleUniform for $ty {
- type Sampler = UniformInt<$ty>;
- }
-
- impl UniformSampler for UniformInt<$ty> {
- type X = $ty;
-
- #[inline] // if the range is constant, this helps LLVM to do the
- // calculations at compile-time.
- fn new<B1, B2>(low_b: B1, high_b: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- let low = *low_b.borrow();
- let high = *high_b.borrow();
- assert!(low.lt(high).all(), "Uniform::new called with `low >= high`");
- UniformSampler::new_inclusive(low, high - 1)
- }
-
- #[inline] // if the range is constant, this helps LLVM to do the
- // calculations at compile-time.
- fn new_inclusive<B1, B2>(low_b: B1, high_b: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- let low = *low_b.borrow();
- let high = *high_b.borrow();
- assert!(low.le(high).all(),
- "Uniform::new_inclusive called with `low > high`");
- let unsigned_max = ::core::$u_scalar::MAX;
-
- // NOTE: these may need to be replaced with explicitly
- // wrapping operations if `packed_simd` changes
- let range: $unsigned = ((high - low) + 1).cast();
- // `% 0` will panic at runtime.
- let not_full_range = range.gt($unsigned::splat(0));
- // replacing 0 with `unsigned_max` allows a faster `select`
- // with bitwise OR
- let modulo = not_full_range.select(range, $unsigned::splat(unsigned_max));
- // wrapping addition
- let ints_to_reject = (unsigned_max - range + 1) % modulo;
- // When `range` is 0, `lo` of `v.wmul(range)` will always be
- // zero which means only one sample is needed.
- let zone = unsigned_max - ints_to_reject;
-
- UniformInt {
- low: low,
- // These are really $unsigned values, but store as $ty:
- range: range.cast(),
- z: zone.cast(),
- }
- }
-
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Self::X {
- let range: $unsigned = self.range.cast();
- let zone: $unsigned = self.z.cast();
-
- // This might seem very slow, generating a whole new
- // SIMD vector for every sample rejection. For most uses
- // though, the chance of rejection is small and provides good
- // general performance. With multiple lanes, that chance is
- // multiplied. To mitigate this, we replace only the lanes of
- // the vector which fail, iteratively reducing the chance of
- // rejection. The replacement method does however add a little
- // overhead. Benchmarking or calculating probabilities might
- // reveal contexts where this replacement method is slower.
- let mut v: $unsigned = rng.gen();
- loop {
- let (hi, lo) = v.wmul(range);
- let mask = lo.le(zone);
- if mask.all() {
- let hi: $ty = hi.cast();
- // wrapping addition
- let result = self.low + hi;
- // `select` here compiles to a blend operation
- // When `range.eq(0).none()` the compare and blend
- // operations are avoided.
- let v: $ty = v.cast();
- return range.gt($unsigned::splat(0)).select(result, v);
- }
- // Replace only the failing lanes
- v = mask.select(v, rng.gen());
- }
- }
- }
- };
-
- // bulk implementation
- ($(($unsigned:ident, $signed:ident),)+ $u_scalar:ident) => {
- $(
- uniform_simd_int_impl!($unsigned, $unsigned, $u_scalar);
- uniform_simd_int_impl!($signed, $unsigned, $u_scalar);
- )+
- };
-}
-
-#[cfg(all(feature = "simd_support", feature = "nightly"))]
-uniform_simd_int_impl! {
- (u64x2, i64x2),
- (u64x4, i64x4),
- (u64x8, i64x8),
- u64
-}
-
-#[cfg(all(feature = "simd_support", feature = "nightly"))]
-uniform_simd_int_impl! {
- (u32x2, i32x2),
- (u32x4, i32x4),
- (u32x8, i32x8),
- (u32x16, i32x16),
- u32
-}
-
-#[cfg(all(feature = "simd_support", feature = "nightly"))]
-uniform_simd_int_impl! {
- (u16x2, i16x2),
- (u16x4, i16x4),
- (u16x8, i16x8),
- (u16x16, i16x16),
- (u16x32, i16x32),
- u16
-}
-
-#[cfg(all(feature = "simd_support", feature = "nightly"))]
-uniform_simd_int_impl! {
- (u8x2, i8x2),
- (u8x4, i8x4),
- (u8x8, i8x8),
- (u8x16, i8x16),
- (u8x32, i8x32),
- (u8x64, i8x64),
- u8
-}
-
-
-/// The back-end implementing [`UniformSampler`] for floating-point types.
-///
-/// Unless you are implementing [`UniformSampler`] for your own type, this type
-/// should not be used directly, use [`Uniform`] instead.
-///
-/// # Implementation notes
-///
-/// Instead of generating a float in the `[0, 1)` range using [`Standard`], the
-/// `UniformFloat` implementation converts the output of an PRNG itself. This
-/// way one or two steps can be optimized out.
-///
-/// The floats are first converted to a value in the `[1, 2)` interval using a
-/// transmute-based method, and then mapped to the expected range with a
-/// multiply and addition. Values produced this way have what equals 22 bits of
-/// random digits for an `f32`, and 52 for an `f64`.
-///
-/// [`new`]: UniformSampler::new
-/// [`new_inclusive`]: UniformSampler::new_inclusive
-/// [`Standard`]: crate::distributions::Standard
-#[derive(Clone, Copy, Debug)]
-pub struct UniformFloat<X> {
- low: X,
- scale: X,
-}
-
-macro_rules! uniform_float_impl {
- ($ty:ty, $uty:ident, $f_scalar:ident, $u_scalar:ident, $bits_to_discard:expr) => {
- impl SampleUniform for $ty {
- type Sampler = UniformFloat<$ty>;
- }
-
- impl UniformSampler for UniformFloat<$ty> {
- type X = $ty;
-
- fn new<B1, B2>(low_b: B1, high_b: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- let low = *low_b.borrow();
- let high = *high_b.borrow();
- assert!(low.all_lt(high),
- "Uniform::new called with `low >= high`");
- assert!(low.all_finite() && high.all_finite(),
- "Uniform::new called with non-finite boundaries");
- let max_rand = <$ty>::splat((::core::$u_scalar::MAX >> $bits_to_discard)
- .into_float_with_exponent(0) - 1.0);
-
- let mut scale = high - low;
-
- loop {
- let mask = (scale * max_rand + low).ge_mask(high);
- if mask.none() {
- break;
- }
- scale = scale.decrease_masked(mask);
- }
-
- debug_assert!(<$ty>::splat(0.0).all_le(scale));
-
- UniformFloat { low, scale }
- }
-
- fn new_inclusive<B1, B2>(low_b: B1, high_b: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- let low = *low_b.borrow();
- let high = *high_b.borrow();
- assert!(low.all_le(high),
- "Uniform::new_inclusive called with `low > high`");
- assert!(low.all_finite() && high.all_finite(),
- "Uniform::new_inclusive called with non-finite boundaries");
- let max_rand = <$ty>::splat((::core::$u_scalar::MAX >> $bits_to_discard)
- .into_float_with_exponent(0) - 1.0);
-
- let mut scale = (high - low) / max_rand;
-
- loop {
- let mask = (scale * max_rand + low).gt_mask(high);
- if mask.none() {
- break;
- }
- scale = scale.decrease_masked(mask);
- }
-
- debug_assert!(<$ty>::splat(0.0).all_le(scale));
-
- UniformFloat { low, scale }
- }
-
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Self::X {
- // Generate a value in the range [1, 2)
- let value1_2 = (rng.gen::<$uty>() >> $bits_to_discard)
- .into_float_with_exponent(0);
-
- // Get a value in the range [0, 1) in order to avoid
- // overflowing into infinity when multiplying with scale
- let value0_1 = value1_2 - 1.0;
-
- // We don't use `f64::mul_add`, because it is not available with
- // `no_std`. Furthermore, it is slower for some targets (but
- // faster for others). However, the order of multiplication and
- // addition is important, because on some platforms (e.g. ARM)
- // it will be optimized to a single (non-FMA) instruction.
- value0_1 * self.scale + self.low
- }
-
- #[inline]
- fn sample_single<R: Rng + ?Sized, B1, B2>(low_b: B1, high_b: B2, rng: &mut R)
- -> Self::X
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- let low = *low_b.borrow();
- let high = *high_b.borrow();
- assert!(low.all_lt(high),
- "UniformSampler::sample_single: low >= high");
- let mut scale = high - low;
-
- loop {
- // Generate a value in the range [1, 2)
- let value1_2 = (rng.gen::<$uty>() >> $bits_to_discard)
- .into_float_with_exponent(0);
-
- // Get a value in the range [0, 1) in order to avoid
- // overflowing into infinity when multiplying with scale
- let value0_1 = value1_2 - 1.0;
-
- // Doing multiply before addition allows some architectures
- // to use a single instruction.
- let res = value0_1 * scale + low;
-
- debug_assert!(low.all_le(res) || !scale.all_finite());
- if res.all_lt(high) {
- return res;
- }
-
- // This handles a number of edge cases.
- // * `low` or `high` is NaN. In this case `scale` and
- // `res` are going to end up as NaN.
- // * `low` is negative infinity and `high` is finite.
- // `scale` is going to be infinite and `res` will be
- // NaN.
- // * `high` is positive infinity and `low` is finite.
- // `scale` is going to be infinite and `res` will
- // be infinite or NaN (if value0_1 is 0).
- // * `low` is negative infinity and `high` is positive
- // infinity. `scale` will be infinite and `res` will
- // be NaN.
- // * `low` and `high` are finite, but `high - low`
- // overflows to infinite. `scale` will be infinite
- // and `res` will be infinite or NaN (if value0_1 is 0).
- // So if `high` or `low` are non-finite, we are guaranteed
- // to fail the `res < high` check above and end up here.
- //
- // While we technically should check for non-finite `low`
- // and `high` before entering the loop, by doing the checks
- // here instead, we allow the common case to avoid these
- // checks. But we are still guaranteed that if `low` or
- // `high` are non-finite we'll end up here and can do the
- // appropriate checks.
- //
- // Likewise `high - low` overflowing to infinity is also
- // rare, so handle it here after the common case.
- let mask = !scale.finite_mask();
- if mask.any() {
- assert!(low.all_finite() && high.all_finite(),
- "Uniform::sample_single: low and high must be finite");
- scale = scale.decrease_masked(mask);
- }
- }
- }
- }
- }
-}
-
-uniform_float_impl! { f32, u32, f32, u32, 32 - 23 }
-uniform_float_impl! { f64, u64, f64, u64, 64 - 52 }
-
-#[cfg(feature="simd_support")]
-uniform_float_impl! { f32x2, u32x2, f32, u32, 32 - 23 }
-#[cfg(feature="simd_support")]
-uniform_float_impl! { f32x4, u32x4, f32, u32, 32 - 23 }
-#[cfg(feature="simd_support")]
-uniform_float_impl! { f32x8, u32x8, f32, u32, 32 - 23 }
-#[cfg(feature="simd_support")]
-uniform_float_impl! { f32x16, u32x16, f32, u32, 32 - 23 }
-
-#[cfg(feature="simd_support")]
-uniform_float_impl! { f64x2, u64x2, f64, u64, 64 - 52 }
-#[cfg(feature="simd_support")]
-uniform_float_impl! { f64x4, u64x4, f64, u64, 64 - 52 }
-#[cfg(feature="simd_support")]
-uniform_float_impl! { f64x8, u64x8, f64, u64, 64 - 52 }
-
-
-
-/// The back-end implementing [`UniformSampler`] for `Duration`.
-///
-/// Unless you are implementing [`UniformSampler`] for your own types, this type
-/// should not be used directly, use [`Uniform`] instead.
-#[derive(Clone, Copy, Debug)]
-pub struct UniformDuration {
- mode: UniformDurationMode,
- offset: u32,
-}
-
-#[derive(Debug, Copy, Clone)]
-enum UniformDurationMode {
- Small {
- secs: u64,
- nanos: Uniform<u32>,
- },
- Medium {
- nanos: Uniform<u64>,
- },
- Large {
- max_secs: u64,
- max_nanos: u32,
- secs: Uniform<u64>,
- }
-}
-
-impl SampleUniform for Duration {
- type Sampler = UniformDuration;
-}
-
-impl UniformSampler for UniformDuration {
- type X = Duration;
-
- #[inline]
- fn new<B1, B2>(low_b: B1, high_b: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- let low = *low_b.borrow();
- let high = *high_b.borrow();
- assert!(low < high, "Uniform::new called with `low >= high`");
- UniformDuration::new_inclusive(low, high - Duration::new(0, 1))
- }
-
- #[inline]
- fn new_inclusive<B1, B2>(low_b: B1, high_b: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- let low = *low_b.borrow();
- let high = *high_b.borrow();
- assert!(low <= high, "Uniform::new_inclusive called with `low > high`");
-
- let low_s = low.as_secs();
- let low_n = low.subsec_nanos();
- let mut high_s = high.as_secs();
- let mut high_n = high.subsec_nanos();
-
- if high_n < low_n {
- high_s -= 1;
- high_n += 1_000_000_000;
- }
-
- let mode = if low_s == high_s {
- UniformDurationMode::Small {
- secs: low_s,
- nanos: Uniform::new_inclusive(low_n, high_n),
- }
- } else {
- let max = high_s
- .checked_mul(1_000_000_000)
- .and_then(|n| n.checked_add(u64::from(high_n)));
-
- if let Some(higher_bound) = max {
- let lower_bound = low_s * 1_000_000_000 + u64::from(low_n);
- UniformDurationMode::Medium {
- nanos: Uniform::new_inclusive(lower_bound, higher_bound),
- }
- } else {
- // An offset is applied to simplify generation of nanoseconds
- let max_nanos = high_n - low_n;
- UniformDurationMode::Large {
- max_secs: high_s,
- max_nanos,
- secs: Uniform::new_inclusive(low_s, high_s),
- }
- }
- };
- UniformDuration {
- mode,
- offset: low_n,
- }
- }
-
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Duration {
- match self.mode {
- UniformDurationMode::Small { secs, nanos } => {
- let n = nanos.sample(rng);
- Duration::new(secs, n)
- }
- UniformDurationMode::Medium { nanos } => {
- let nanos = nanos.sample(rng);
- Duration::new(nanos / 1_000_000_000, (nanos % 1_000_000_000) as u32)
- }
- UniformDurationMode::Large { max_secs, max_nanos, secs } => {
- // constant folding means this is at least as fast as `gen_range`
- let nano_range = Uniform::new(0, 1_000_000_000);
- loop {
- let s = secs.sample(rng);
- let n = nano_range.sample(rng);
- if !(s == max_secs && n > max_nanos) {
- let sum = n + self.offset;
- break Duration::new(s, sum);
- }
- }
- }
- }
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::Rng;
- use crate::rngs::mock::StepRng;
- use crate::distributions::uniform::Uniform;
- use crate::distributions::utils::FloatAsSIMD;
- #[cfg(feature="simd_support")] use packed_simd::*;
-
- #[should_panic]
- #[test]
- fn test_uniform_bad_limits_equal_int() {
- Uniform::new(10, 10);
- }
-
- #[test]
- fn test_uniform_good_limits_equal_int() {
- let mut rng = crate::test::rng(804);
- let dist = Uniform::new_inclusive(10, 10);
- for _ in 0..20 {
- assert_eq!(rng.sample(dist), 10);
- }
- }
-
- #[should_panic]
- #[test]
- fn test_uniform_bad_limits_flipped_int() {
- Uniform::new(10, 5);
- }
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_integers() {
- use core::{i8, i16, i32, i64, isize};
- use core::{u8, u16, u32, u64, usize};
- #[cfg(not(target_os = "emscripten"))]
- use core::{i128, u128};
-
- let mut rng = crate::test::rng(251);
- macro_rules! t {
- ($ty:ident, $v:expr, $le:expr, $lt:expr) => {{
- for &(low, high) in $v.iter() {
- let my_uniform = Uniform::new(low, high);
- for _ in 0..1000 {
- let v: $ty = rng.sample(my_uniform);
- assert!($le(low, v) && $lt(v, high));
- }
-
- let my_uniform = Uniform::new_inclusive(low, high);
- for _ in 0..1000 {
- let v: $ty = rng.sample(my_uniform);
- assert!($le(low, v) && $le(v, high));
- }
-
- let my_uniform = Uniform::new(&low, high);
- for _ in 0..1000 {
- let v: $ty = rng.sample(my_uniform);
- assert!($le(low, v) && $lt(v, high));
- }
-
- let my_uniform = Uniform::new_inclusive(&low, &high);
- for _ in 0..1000 {
- let v: $ty = rng.sample(my_uniform);
- assert!($le(low, v) && $le(v, high));
- }
-
- for _ in 0..1000 {
- let v: $ty = rng.gen_range(low, high);
- assert!($le(low, v) && $lt(v, high));
- }
- }
- }};
-
- // scalar bulk
- ($($ty:ident),*) => {{
- $(t!(
- $ty,
- [(0, 10), (10, 127), ($ty::MIN, $ty::MAX)],
- |x, y| x <= y,
- |x, y| x < y
- );)*
- }};
-
- // simd bulk
- ($($ty:ident),* => $scalar:ident) => {{
- $(t!(
- $ty,
- [
- ($ty::splat(0), $ty::splat(10)),
- ($ty::splat(10), $ty::splat(127)),
- ($ty::splat($scalar::MIN), $ty::splat($scalar::MAX)),
- ],
- |x: $ty, y| x.le(y).all(),
- |x: $ty, y| x.lt(y).all()
- );)*
- }};
- }
- t!(i8, i16, i32, i64, isize,
- u8, u16, u32, u64, usize);
- #[cfg(not(target_os = "emscripten"))]
- t!(i128, u128);
-
- #[cfg(all(feature = "simd_support", feature = "nightly"))]
- {
- t!(u8x2, u8x4, u8x8, u8x16, u8x32, u8x64 => u8);
- t!(i8x2, i8x4, i8x8, i8x16, i8x32, i8x64 => i8);
- t!(u16x2, u16x4, u16x8, u16x16, u16x32 => u16);
- t!(i16x2, i16x4, i16x8, i16x16, i16x32 => i16);
- t!(u32x2, u32x4, u32x8, u32x16 => u32);
- t!(i32x2, i32x4, i32x8, i32x16 => i32);
- t!(u64x2, u64x4, u64x8 => u64);
- t!(i64x2, i64x4, i64x8 => i64);
- }
- }
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_floats() {
- let mut rng = crate::test::rng(252);
- let mut zero_rng = StepRng::new(0, 0);
- let mut max_rng = StepRng::new(0xffff_ffff_ffff_ffff, 0);
- macro_rules! t {
- ($ty:ty, $f_scalar:ident, $bits_shifted:expr) => {{
- let v: &[($f_scalar, $f_scalar)]=
- &[(0.0, 100.0),
- (-1e35, -1e25),
- (1e-35, 1e-25),
- (-1e35, 1e35),
- (<$f_scalar>::from_bits(0), <$f_scalar>::from_bits(3)),
- (-<$f_scalar>::from_bits(10), -<$f_scalar>::from_bits(1)),
- (-<$f_scalar>::from_bits(5), 0.0),
- (-<$f_scalar>::from_bits(7), -0.0),
- (10.0, ::core::$f_scalar::MAX),
- (-100.0, ::core::$f_scalar::MAX),
- (-::core::$f_scalar::MAX / 5.0, ::core::$f_scalar::MAX),
- (-::core::$f_scalar::MAX, ::core::$f_scalar::MAX / 5.0),
- (-::core::$f_scalar::MAX * 0.8, ::core::$f_scalar::MAX * 0.7),
- (-::core::$f_scalar::MAX, ::core::$f_scalar::MAX),
- ];
- for &(low_scalar, high_scalar) in v.iter() {
- for lane in 0..<$ty>::lanes() {
- let low = <$ty>::splat(0.0 as $f_scalar).replace(lane, low_scalar);
- let high = <$ty>::splat(1.0 as $f_scalar).replace(lane, high_scalar);
- let my_uniform = Uniform::new(low, high);
- let my_incl_uniform = Uniform::new_inclusive(low, high);
- for _ in 0..100 {
- let v = rng.sample(my_uniform).extract(lane);
- assert!(low_scalar <= v && v < high_scalar);
- let v = rng.sample(my_incl_uniform).extract(lane);
- assert!(low_scalar <= v && v <= high_scalar);
- let v = rng.gen_range(low, high).extract(lane);
- assert!(low_scalar <= v && v < high_scalar);
- }
-
- assert_eq!(rng.sample(Uniform::new_inclusive(low, low)).extract(lane), low_scalar);
-
- assert_eq!(zero_rng.sample(my_uniform).extract(lane), low_scalar);
- assert_eq!(zero_rng.sample(my_incl_uniform).extract(lane), low_scalar);
- assert_eq!(zero_rng.gen_range(low, high).extract(lane), low_scalar);
- assert!(max_rng.sample(my_uniform).extract(lane) < high_scalar);
- assert!(max_rng.sample(my_incl_uniform).extract(lane) <= high_scalar);
-
- // Don't run this test for really tiny differences between high and low
- // since for those rounding might result in selecting high for a very
- // long time.
- if (high_scalar - low_scalar) > 0.0001 {
- let mut lowering_max_rng =
- StepRng::new(0xffff_ffff_ffff_ffff,
- (-1i64 << $bits_shifted) as u64);
- assert!(lowering_max_rng.gen_range(low, high).extract(lane) < high_scalar);
- }
- }
- }
-
- assert_eq!(rng.sample(Uniform::new_inclusive(::core::$f_scalar::MAX,
- ::core::$f_scalar::MAX)),
- ::core::$f_scalar::MAX);
- assert_eq!(rng.sample(Uniform::new_inclusive(-::core::$f_scalar::MAX,
- -::core::$f_scalar::MAX)),
- -::core::$f_scalar::MAX);
- }}
- }
-
- t!(f32, f32, 32 - 23);
- t!(f64, f64, 64 - 52);
- #[cfg(feature="simd_support")]
- {
- t!(f32x2, f32, 32 - 23);
- t!(f32x4, f32, 32 - 23);
- t!(f32x8, f32, 32 - 23);
- t!(f32x16, f32, 32 - 23);
- t!(f64x2, f64, 64 - 52);
- t!(f64x4, f64, 64 - 52);
- t!(f64x8, f64, 64 - 52);
- }
- }
-
- #[test]
- #[cfg(all(feature="std",
- not(target_arch = "wasm32"),
- not(target_arch = "asmjs")))]
- #[cfg(not(miri))] // Miri does not support catching panics
- fn test_float_assertions() {
- use std::panic::catch_unwind;
- use super::SampleUniform;
- fn range<T: SampleUniform>(low: T, high: T) {
- let mut rng = crate::test::rng(253);
- rng.gen_range(low, high);
- }
-
- macro_rules! t {
- ($ty:ident, $f_scalar:ident) => {{
- let v: &[($f_scalar, $f_scalar)] =
- &[(::std::$f_scalar::NAN, 0.0),
- (1.0, ::std::$f_scalar::NAN),
- (::std::$f_scalar::NAN, ::std::$f_scalar::NAN),
- (1.0, 0.5),
- (::std::$f_scalar::MAX, -::std::$f_scalar::MAX),
- (::std::$f_scalar::INFINITY, ::std::$f_scalar::INFINITY),
- (::std::$f_scalar::NEG_INFINITY, ::std::$f_scalar::NEG_INFINITY),
- (::std::$f_scalar::NEG_INFINITY, 5.0),
- (5.0, ::std::$f_scalar::INFINITY),
- (::std::$f_scalar::NAN, ::std::$f_scalar::INFINITY),
- (::std::$f_scalar::NEG_INFINITY, ::std::$f_scalar::NAN),
- (::std::$f_scalar::NEG_INFINITY, ::std::$f_scalar::INFINITY),
- ];
- for &(low_scalar, high_scalar) in v.iter() {
- for lane in 0..<$ty>::lanes() {
- let low = <$ty>::splat(0.0 as $f_scalar).replace(lane, low_scalar);
- let high = <$ty>::splat(1.0 as $f_scalar).replace(lane, high_scalar);
- assert!(catch_unwind(|| range(low, high)).is_err());
- assert!(catch_unwind(|| Uniform::new(low, high)).is_err());
- assert!(catch_unwind(|| Uniform::new_inclusive(low, high)).is_err());
- assert!(catch_unwind(|| range(low, low)).is_err());
- assert!(catch_unwind(|| Uniform::new(low, low)).is_err());
- }
- }
- }}
- }
-
- t!(f32, f32);
- t!(f64, f64);
- #[cfg(feature="simd_support")]
- {
- t!(f32x2, f32);
- t!(f32x4, f32);
- t!(f32x8, f32);
- t!(f32x16, f32);
- t!(f64x2, f64);
- t!(f64x4, f64);
- t!(f64x8, f64);
- }
- }
-
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_durations() {
- #[cfg(feature = "std")]
- use std::time::Duration;
- #[cfg(not(feature = "std"))]
- use core::time::Duration;
-
- let mut rng = crate::test::rng(253);
-
- let v = &[(Duration::new(10, 50000), Duration::new(100, 1234)),
- (Duration::new(0, 100), Duration::new(1, 50)),
- (Duration::new(0, 0), Duration::new(u64::max_value(), 999_999_999))];
- for &(low, high) in v.iter() {
- let my_uniform = Uniform::new(low, high);
- for _ in 0..1000 {
- let v = rng.sample(my_uniform);
- assert!(low <= v && v < high);
- }
- }
- }
-
- #[test]
- fn test_custom_uniform() {
- use crate::distributions::uniform::{UniformSampler, UniformFloat, SampleUniform, SampleBorrow};
- #[derive(Clone, Copy, PartialEq, PartialOrd)]
- struct MyF32 {
- x: f32,
- }
- #[derive(Clone, Copy, Debug)]
- struct UniformMyF32 {
- inner: UniformFloat<f32>,
- }
- impl UniformSampler for UniformMyF32 {
- type X = MyF32;
- fn new<B1, B2>(low: B1, high: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- UniformMyF32 {
- inner: UniformFloat::<f32>::new(low.borrow().x, high.borrow().x),
- }
- }
- fn new_inclusive<B1, B2>(low: B1, high: B2) -> Self
- where B1: SampleBorrow<Self::X> + Sized,
- B2: SampleBorrow<Self::X> + Sized
- {
- UniformSampler::new(low, high)
- }
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Self::X {
- MyF32 { x: self.inner.sample(rng) }
- }
- }
- impl SampleUniform for MyF32 {
- type Sampler = UniformMyF32;
- }
-
- let (low, high) = (MyF32{ x: 17.0f32 }, MyF32{ x: 22.0f32 });
- let uniform = Uniform::new(low, high);
- let mut rng = crate::test::rng(804);
- for _ in 0..100 {
- let x: MyF32 = rng.sample(uniform);
- assert!(low <= x && x < high);
- }
- }
-
- #[test]
- fn test_uniform_from_std_range() {
- let r = Uniform::from(2u32..7);
- assert_eq!(r.inner.low, 2);
- assert_eq!(r.inner.range, 5);
- let r = Uniform::from(2.0f64..7.0);
- assert_eq!(r.inner.low, 2.0);
- assert_eq!(r.inner.scale, 5.0);
- }
-
- #[test]
- fn test_uniform_from_std_range_inclusive() {
- let r = Uniform::from(2u32..=6);
- assert_eq!(r.inner.low, 2);
- assert_eq!(r.inner.range, 5);
- let r = Uniform::from(2.0f64..=7.0);
- assert_eq!(r.inner.low, 2.0);
- assert!(r.inner.scale > 5.0);
- assert!(r.inner.scale < 5.0 + 1e-14);
- }
-}
diff --git a/rand/src/distributions/unit_circle.rs b/rand/src/distributions/unit_circle.rs
deleted file mode 100644
index 56e75b6..0000000
--- a/rand/src/distributions/unit_circle.rs
+++ /dev/null
@@ -1,101 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#![allow(deprecated)]
-#![allow(clippy::all)]
-
-use crate::Rng;
-use crate::distributions::{Distribution, Uniform};
-
-/// Samples uniformly from the edge of the unit circle in two dimensions.
-///
-/// Implemented via a method by von Neumann[^1].
-///
-/// [^1]: von Neumann, J. (1951) [*Various Techniques Used in Connection with
-/// Random Digits.*](https://mcnp.lanl.gov/pdf_files/nbs_vonneumann.pdf)
-/// NBS Appl. Math. Ser., No. 12. Washington, DC: U.S. Government Printing
-/// Office, pp. 36-38.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct UnitCircle;
-
-impl UnitCircle {
- /// Construct a new `UnitCircle` distribution.
- #[inline]
- pub fn new() -> UnitCircle {
- UnitCircle
- }
-}
-
-impl Distribution<[f64; 2]> for UnitCircle {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> [f64; 2] {
- let uniform = Uniform::new(-1., 1.);
- let mut x1;
- let mut x2;
- let mut sum;
- loop {
- x1 = uniform.sample(rng);
- x2 = uniform.sample(rng);
- sum = x1*x1 + x2*x2;
- if sum < 1. {
- break;
- }
- }
- let diff = x1*x1 - x2*x2;
- [diff / sum, 2.*x1*x2 / sum]
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::distributions::Distribution;
- use super::UnitCircle;
-
- /// Assert that two numbers are almost equal to each other.
- ///
- /// On panic, this macro will print the values of the expressions with their
- /// debug representations.
- macro_rules! assert_almost_eq {
- ($a:expr, $b:expr, $prec:expr) => (
- let diff = ($a - $b).abs();
- if diff > $prec {
- panic!(format!(
- "assertion failed: `abs(left - right) = {:.1e} < {:e}`, \
- (left: `{}`, right: `{}`)",
- diff, $prec, $a, $b));
- }
- );
- }
-
- #[test]
- fn norm() {
- let mut rng = crate::test::rng(1);
- let dist = UnitCircle::new();
- for _ in 0..1000 {
- let x = dist.sample(&mut rng);
- assert_almost_eq!(x[0]*x[0] + x[1]*x[1], 1., 1e-15);
- }
- }
-
- #[test]
- fn value_stability() {
- let mut rng = crate::test::rng(2);
- let expected = [
- [-0.9965658683520504, -0.08280380447614634],
- [-0.9790853270389644, -0.20345004884984505],
- [-0.8449189758898707, 0.5348943112253227],
- ];
- let samples = [
- UnitCircle.sample(&mut rng),
- UnitCircle.sample(&mut rng),
- UnitCircle.sample(&mut rng),
- ];
- assert_eq!(samples, expected);
- }
-}
diff --git a/rand/src/distributions/unit_sphere.rs b/rand/src/distributions/unit_sphere.rs
deleted file mode 100644
index 188f48c..0000000
--- a/rand/src/distributions/unit_sphere.rs
+++ /dev/null
@@ -1,96 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-#![allow(deprecated)]
-#![allow(clippy::all)]
-
-use crate::Rng;
-use crate::distributions::{Distribution, Uniform};
-
-/// Samples uniformly from the surface of the unit sphere in three dimensions.
-///
-/// Implemented via a method by Marsaglia[^1].
-///
-/// [^1]: Marsaglia, George (1972). [*Choosing a Point from the Surface of a
-/// Sphere.*](https://doi.org/10.1214/aoms/1177692644)
-/// Ann. Math. Statist. 43, no. 2, 645--646.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct UnitSphereSurface;
-
-impl UnitSphereSurface {
- /// Construct a new `UnitSphereSurface` distribution.
- #[inline]
- pub fn new() -> UnitSphereSurface {
- UnitSphereSurface
- }
-}
-
-impl Distribution<[f64; 3]> for UnitSphereSurface {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> [f64; 3] {
- let uniform = Uniform::new(-1., 1.);
- loop {
- let (x1, x2) = (uniform.sample(rng), uniform.sample(rng));
- let sum = x1*x1 + x2*x2;
- if sum >= 1. {
- continue;
- }
- let factor = 2. * (1.0_f64 - sum).sqrt();
- return [x1 * factor, x2 * factor, 1. - 2.*sum];
- }
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::distributions::Distribution;
- use super::UnitSphereSurface;
-
- /// Assert that two numbers are almost equal to each other.
- ///
- /// On panic, this macro will print the values of the expressions with their
- /// debug representations.
- macro_rules! assert_almost_eq {
- ($a:expr, $b:expr, $prec:expr) => (
- let diff = ($a - $b).abs();
- if diff > $prec {
- panic!(format!(
- "assertion failed: `abs(left - right) = {:.1e} < {:e}`, \
- (left: `{}`, right: `{}`)",
- diff, $prec, $a, $b));
- }
- );
- }
-
- #[test]
- fn norm() {
- let mut rng = crate::test::rng(1);
- let dist = UnitSphereSurface::new();
- for _ in 0..1000 {
- let x = dist.sample(&mut rng);
- assert_almost_eq!(x[0]*x[0] + x[1]*x[1] + x[2]*x[2], 1., 1e-15);
- }
- }
-
- #[test]
- fn value_stability() {
- let mut rng = crate::test::rng(2);
- let expected = [
- [0.03247542860231647, -0.7830477442152738, 0.6211131755296027],
- [-0.09978440840914075, 0.9706650829833128, -0.21875184231323952],
- [0.2735582468624679, 0.9435374242279655, -0.1868234852870203],
- ];
- let samples = [
- UnitSphereSurface.sample(&mut rng),
- UnitSphereSurface.sample(&mut rng),
- UnitSphereSurface.sample(&mut rng),
- ];
- assert_eq!(samples, expected);
- }
-}
diff --git a/rand/src/distributions/utils.rs b/rand/src/distributions/utils.rs
deleted file mode 100644
index 3af4e86..0000000
--- a/rand/src/distributions/utils.rs
+++ /dev/null
@@ -1,488 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Math helper functions
-
-#[cfg(feature="simd_support")]
-use packed_simd::*;
-#[cfg(feature="std")]
-use crate::distributions::ziggurat_tables;
-#[cfg(feature="std")]
-use crate::Rng;
-
-
-pub trait WideningMultiply<RHS = Self> {
- type Output;
-
- fn wmul(self, x: RHS) -> Self::Output;
-}
-
-macro_rules! wmul_impl {
- ($ty:ty, $wide:ty, $shift:expr) => {
- impl WideningMultiply for $ty {
- type Output = ($ty, $ty);
-
- #[inline(always)]
- fn wmul(self, x: $ty) -> Self::Output {
- let tmp = (self as $wide) * (x as $wide);
- ((tmp >> $shift) as $ty, tmp as $ty)
- }
- }
- };
-
- // simd bulk implementation
- ($(($ty:ident, $wide:ident),)+, $shift:expr) => {
- $(
- impl WideningMultiply for $ty {
- type Output = ($ty, $ty);
-
- #[inline(always)]
- fn wmul(self, x: $ty) -> Self::Output {
- // For supported vectors, this should compile to a couple
- // supported multiply & swizzle instructions (no actual
- // casting).
- // TODO: optimize
- let y: $wide = self.cast();
- let x: $wide = x.cast();
- let tmp = y * x;
- let hi: $ty = (tmp >> $shift).cast();
- let lo: $ty = tmp.cast();
- (hi, lo)
- }
- }
- )+
- };
-}
-wmul_impl! { u8, u16, 8 }
-wmul_impl! { u16, u32, 16 }
-wmul_impl! { u32, u64, 32 }
-#[cfg(not(target_os = "emscripten"))]
-wmul_impl! { u64, u128, 64 }
-
-// This code is a translation of the __mulddi3 function in LLVM's
-// compiler-rt. It is an optimised variant of the common method
-// `(a + b) * (c + d) = ac + ad + bc + bd`.
-//
-// For some reason LLVM can optimise the C version very well, but
-// keeps shuffling registers in this Rust translation.
-macro_rules! wmul_impl_large {
- ($ty:ty, $half:expr) => {
- impl WideningMultiply for $ty {
- type Output = ($ty, $ty);
-
- #[inline(always)]
- fn wmul(self, b: $ty) -> Self::Output {
- const LOWER_MASK: $ty = !0 >> $half;
- let mut low = (self & LOWER_MASK).wrapping_mul(b & LOWER_MASK);
- let mut t = low >> $half;
- low &= LOWER_MASK;
- t += (self >> $half).wrapping_mul(b & LOWER_MASK);
- low += (t & LOWER_MASK) << $half;
- let mut high = t >> $half;
- t = low >> $half;
- low &= LOWER_MASK;
- t += (b >> $half).wrapping_mul(self & LOWER_MASK);
- low += (t & LOWER_MASK) << $half;
- high += t >> $half;
- high += (self >> $half).wrapping_mul(b >> $half);
-
- (high, low)
- }
- }
- };
-
- // simd bulk implementation
- (($($ty:ty,)+) $scalar:ty, $half:expr) => {
- $(
- impl WideningMultiply for $ty {
- type Output = ($ty, $ty);
-
- #[inline(always)]
- fn wmul(self, b: $ty) -> Self::Output {
- // needs wrapping multiplication
- const LOWER_MASK: $scalar = !0 >> $half;
- let mut low = (self & LOWER_MASK) * (b & LOWER_MASK);
- let mut t = low >> $half;
- low &= LOWER_MASK;
- t += (self >> $half) * (b & LOWER_MASK);
- low += (t & LOWER_MASK) << $half;
- let mut high = t >> $half;
- t = low >> $half;
- low &= LOWER_MASK;
- t += (b >> $half) * (self & LOWER_MASK);
- low += (t & LOWER_MASK) << $half;
- high += t >> $half;
- high += (self >> $half) * (b >> $half);
-
- (high, low)
- }
- }
- )+
- };
-}
-#[cfg(target_os = "emscripten")]
-wmul_impl_large! { u64, 32 }
-#[cfg(not(target_os = "emscripten"))]
-wmul_impl_large! { u128, 64 }
-
-macro_rules! wmul_impl_usize {
- ($ty:ty) => {
- impl WideningMultiply for usize {
- type Output = (usize, usize);
-
- #[inline(always)]
- fn wmul(self, x: usize) -> Self::Output {
- let (high, low) = (self as $ty).wmul(x as $ty);
- (high as usize, low as usize)
- }
- }
- }
-}
-#[cfg(target_pointer_width = "32")]
-wmul_impl_usize! { u32 }
-#[cfg(target_pointer_width = "64")]
-wmul_impl_usize! { u64 }
-
-#[cfg(all(feature = "simd_support", feature = "nightly"))]
-mod simd_wmul {
- #[cfg(target_arch = "x86")]
- use core::arch::x86::*;
- #[cfg(target_arch = "x86_64")]
- use core::arch::x86_64::*;
- use super::*;
-
- wmul_impl! {
- (u8x2, u16x2),
- (u8x4, u16x4),
- (u8x8, u16x8),
- (u8x16, u16x16),
- (u8x32, u16x32),,
- 8
- }
-
- wmul_impl! { (u16x2, u32x2),, 16 }
- #[cfg(not(target_feature = "sse2"))]
- wmul_impl! { (u16x4, u32x4),, 16 }
- #[cfg(not(target_feature = "sse4.2"))]
- wmul_impl! { (u16x8, u32x8),, 16 }
- #[cfg(not(target_feature = "avx2"))]
- wmul_impl! { (u16x16, u32x16),, 16 }
-
- // 16-bit lane widths allow use of the x86 `mulhi` instructions, which
- // means `wmul` can be implemented with only two instructions.
- #[allow(unused_macros)]
- macro_rules! wmul_impl_16 {
- ($ty:ident, $intrinsic:ident, $mulhi:ident, $mullo:ident) => {
- impl WideningMultiply for $ty {
- type Output = ($ty, $ty);
-
- #[inline(always)]
- fn wmul(self, x: $ty) -> Self::Output {
- let b = $intrinsic::from_bits(x);
- let a = $intrinsic::from_bits(self);
- let hi = $ty::from_bits(unsafe { $mulhi(a, b) });
- let lo = $ty::from_bits(unsafe { $mullo(a, b) });
- (hi, lo)
- }
- }
- };
- }
-
- #[cfg(target_feature = "sse2")]
- wmul_impl_16! { u16x4, __m64, _mm_mulhi_pu16, _mm_mullo_pi16 }
- #[cfg(target_feature = "sse4.2")]
- wmul_impl_16! { u16x8, __m128i, _mm_mulhi_epu16, _mm_mullo_epi16 }
- #[cfg(target_feature = "avx2")]
- wmul_impl_16! { u16x16, __m256i, _mm256_mulhi_epu16, _mm256_mullo_epi16 }
- // FIXME: there are no `__m512i` types in stdsimd yet, so `wmul::<u16x32>`
- // cannot use the same implementation.
-
- wmul_impl! {
- (u32x2, u64x2),
- (u32x4, u64x4),
- (u32x8, u64x8),,
- 32
- }
-
- // TODO: optimize, this seems to seriously slow things down
- wmul_impl_large! { (u8x64,) u8, 4 }
- wmul_impl_large! { (u16x32,) u16, 8 }
- wmul_impl_large! { (u32x16,) u32, 16 }
- wmul_impl_large! { (u64x2, u64x4, u64x8,) u64, 32 }
-}
-#[cfg(all(feature = "simd_support", feature = "nightly"))]
-pub use self::simd_wmul::*;
-
-
-/// Helper trait when dealing with scalar and SIMD floating point types.
-pub(crate) trait FloatSIMDUtils {
- // `PartialOrd` for vectors compares lexicographically. We want to compare all
- // the individual SIMD lanes instead, and get the combined result over all
- // lanes. This is possible using something like `a.lt(b).all()`, but we
- // implement it as a trait so we can write the same code for `f32` and `f64`.
- // Only the comparison functions we need are implemented.
- fn all_lt(self, other: Self) -> bool;
- fn all_le(self, other: Self) -> bool;
- fn all_finite(self) -> bool;
-
- type Mask;
- fn finite_mask(self) -> Self::Mask;
- fn gt_mask(self, other: Self) -> Self::Mask;
- fn ge_mask(self, other: Self) -> Self::Mask;
-
- // Decrease all lanes where the mask is `true` to the next lower value
- // representable by the floating-point type. At least one of the lanes
- // must be set.
- fn decrease_masked(self, mask: Self::Mask) -> Self;
-
- // Convert from int value. Conversion is done while retaining the numerical
- // value, not by retaining the binary representation.
- type UInt;
- fn cast_from_int(i: Self::UInt) -> Self;
-}
-
-/// Implement functions available in std builds but missing from core primitives
-#[cfg(not(std))]
-pub(crate) trait Float : Sized {
- fn is_nan(self) -> bool;
- fn is_infinite(self) -> bool;
- fn is_finite(self) -> bool;
-}
-
-/// Implement functions on f32/f64 to give them APIs similar to SIMD types
-pub(crate) trait FloatAsSIMD : Sized {
- #[inline(always)]
- fn lanes() -> usize { 1 }
- #[inline(always)]
- fn splat(scalar: Self) -> Self { scalar }
- #[inline(always)]
- fn extract(self, index: usize) -> Self { debug_assert_eq!(index, 0); self }
- #[inline(always)]
- fn replace(self, index: usize, new_value: Self) -> Self { debug_assert_eq!(index, 0); new_value }
-}
-
-pub(crate) trait BoolAsSIMD : Sized {
- fn any(self) -> bool;
- fn all(self) -> bool;
- fn none(self) -> bool;
-}
-
-impl BoolAsSIMD for bool {
- #[inline(always)]
- fn any(self) -> bool { self }
- #[inline(always)]
- fn all(self) -> bool { self }
- #[inline(always)]
- fn none(self) -> bool { !self }
-}
-
-macro_rules! scalar_float_impl {
- ($ty:ident, $uty:ident) => {
- #[cfg(not(std))]
- impl Float for $ty {
- #[inline]
- fn is_nan(self) -> bool {
- self != self
- }
-
- #[inline]
- fn is_infinite(self) -> bool {
- self == ::core::$ty::INFINITY || self == ::core::$ty::NEG_INFINITY
- }
-
- #[inline]
- fn is_finite(self) -> bool {
- !(self.is_nan() || self.is_infinite())
- }
- }
-
- impl FloatSIMDUtils for $ty {
- type Mask = bool;
- #[inline(always)]
- fn all_lt(self, other: Self) -> bool { self < other }
- #[inline(always)]
- fn all_le(self, other: Self) -> bool { self <= other }
- #[inline(always)]
- fn all_finite(self) -> bool { self.is_finite() }
- #[inline(always)]
- fn finite_mask(self) -> Self::Mask { self.is_finite() }
- #[inline(always)]
- fn gt_mask(self, other: Self) -> Self::Mask { self > other }
- #[inline(always)]
- fn ge_mask(self, other: Self) -> Self::Mask { self >= other }
- #[inline(always)]
- fn decrease_masked(self, mask: Self::Mask) -> Self {
- debug_assert!(mask, "At least one lane must be set");
- <$ty>::from_bits(self.to_bits() - 1)
- }
- type UInt = $uty;
- fn cast_from_int(i: Self::UInt) -> Self { i as $ty }
- }
-
- impl FloatAsSIMD for $ty {}
- }
-}
-
-scalar_float_impl!(f32, u32);
-scalar_float_impl!(f64, u64);
-
-
-#[cfg(feature="simd_support")]
-macro_rules! simd_impl {
- ($ty:ident, $f_scalar:ident, $mty:ident, $uty:ident) => {
- impl FloatSIMDUtils for $ty {
- type Mask = $mty;
- #[inline(always)]
- fn all_lt(self, other: Self) -> bool { self.lt(other).all() }
- #[inline(always)]
- fn all_le(self, other: Self) -> bool { self.le(other).all() }
- #[inline(always)]
- fn all_finite(self) -> bool { self.finite_mask().all() }
- #[inline(always)]
- fn finite_mask(self) -> Self::Mask {
- // This can possibly be done faster by checking bit patterns
- let neg_inf = $ty::splat(::core::$f_scalar::NEG_INFINITY);
- let pos_inf = $ty::splat(::core::$f_scalar::INFINITY);
- self.gt(neg_inf) & self.lt(pos_inf)
- }
- #[inline(always)]
- fn gt_mask(self, other: Self) -> Self::Mask { self.gt(other) }
- #[inline(always)]
- fn ge_mask(self, other: Self) -> Self::Mask { self.ge(other) }
- #[inline(always)]
- fn decrease_masked(self, mask: Self::Mask) -> Self {
- // Casting a mask into ints will produce all bits set for
- // true, and 0 for false. Adding that to the binary
- // representation of a float means subtracting one from
- // the binary representation, resulting in the next lower
- // value representable by $ty. This works even when the
- // current value is infinity.
- debug_assert!(mask.any(), "At least one lane must be set");
- <$ty>::from_bits(<$uty>::from_bits(self) + <$uty>::from_bits(mask))
- }
- type UInt = $uty;
- #[inline]
- fn cast_from_int(i: Self::UInt) -> Self { i.cast() }
- }
- }
-}
-
-#[cfg(feature="simd_support")] simd_impl! { f32x2, f32, m32x2, u32x2 }
-#[cfg(feature="simd_support")] simd_impl! { f32x4, f32, m32x4, u32x4 }
-#[cfg(feature="simd_support")] simd_impl! { f32x8, f32, m32x8, u32x8 }
-#[cfg(feature="simd_support")] simd_impl! { f32x16, f32, m32x16, u32x16 }
-#[cfg(feature="simd_support")] simd_impl! { f64x2, f64, m64x2, u64x2 }
-#[cfg(feature="simd_support")] simd_impl! { f64x4, f64, m64x4, u64x4 }
-#[cfg(feature="simd_support")] simd_impl! { f64x8, f64, m64x8, u64x8 }
-
-/// Calculates ln(gamma(x)) (natural logarithm of the gamma
-/// function) using the Lanczos approximation.
-///
-/// The approximation expresses the gamma function as:
-/// `gamma(z+1) = sqrt(2*pi)*(z+g+0.5)^(z+0.5)*exp(-z-g-0.5)*Ag(z)`
-/// `g` is an arbitrary constant; we use the approximation with `g=5`.
-///
-/// Noting that `gamma(z+1) = z*gamma(z)` and applying `ln` to both sides:
-/// `ln(gamma(z)) = (z+0.5)*ln(z+g+0.5)-(z+g+0.5) + ln(sqrt(2*pi)*Ag(z)/z)`
-///
-/// `Ag(z)` is an infinite series with coefficients that can be calculated
-/// ahead of time - we use just the first 6 terms, which is good enough
-/// for most purposes.
-#[cfg(feature="std")]
-pub fn log_gamma(x: f64) -> f64 {
- // precalculated 6 coefficients for the first 6 terms of the series
- let coefficients: [f64; 6] = [
- 76.18009172947146,
- -86.50532032941677,
- 24.01409824083091,
- -1.231739572450155,
- 0.1208650973866179e-2,
- -0.5395239384953e-5,
- ];
-
- // (x+0.5)*ln(x+g+0.5)-(x+g+0.5)
- let tmp = x + 5.5;
- let log = (x + 0.5) * tmp.ln() - tmp;
-
- // the first few terms of the series for Ag(x)
- let mut a = 1.000000000190015;
- let mut denom = x;
- for coeff in &coefficients {
- denom += 1.0;
- a += coeff / denom;
- }
-
- // get everything together
- // a is Ag(x)
- // 2.5066... is sqrt(2pi)
- log + (2.5066282746310005 * a / x).ln()
-}
-
-/// 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)
-
-// the perf improvement (25-50%) is definitely worth the extra code
-// size from force-inlining.
-#[cfg(feature="std")]
-#[inline(always)]
-pub fn ziggurat<R: Rng + ?Sized, P, Z>(
- rng: &mut R,
- symmetric: bool,
- x_tab: ziggurat_tables::ZigTable,
- f_tab: ziggurat_tables::ZigTable,
- mut pdf: P,
- mut zero_case: Z)
- -> f64 where P: FnMut(f64) -> f64, Z: FnMut(&mut R, f64) -> f64 {
- use crate::distributions::float::IntoFloat;
- loop {
- // As an optimisation we re-implement the conversion to a f64.
- // From the remaining 12 most significant bits we use 8 to construct `i`.
- // This saves us generating a whole extra random number, while the added
- // precision of using 64 bits for f64 does not buy us much.
- let bits = rng.next_u64();
- let i = bits as usize & 0xff;
-
- let u = if symmetric {
- // Convert to a value in the range [2,4) and substract to get [-1,1)
- // We can't convert to an open range directly, that would require
- // substracting `3.0 - EPSILON`, which is not representable.
- // It is possible with an extra step, but an open range does not
- // seem neccesary for the ziggurat algorithm anyway.
- (bits >> 12).into_float_with_exponent(1) - 3.0
- } else {
- // Convert to a value in the range [1,2) and substract to get (0,1)
- (bits >> 12).into_float_with_exponent(0)
- - (1.0 - ::core::f64::EPSILON / 2.0)
- };
- let x = u * x_tab[i];
-
- let test_x = if symmetric { x.abs() } else {x};
-
- // algebraically equivalent to |u| < x_tab[i+1]/x_tab[i] (or u < x_tab[i+1]/x_tab[i])
- if test_x < x_tab[i + 1] {
- return x;
- }
- if i == 0 {
- return zero_case(rng, u);
- }
- // algebraically equivalent to f1 + DRanU()*(f0 - f1) < 1
- if f_tab[i + 1] + (f_tab[i] - f_tab[i + 1]) * rng.gen::<f64>() < pdf(x) {
- return x;
- }
- }
-}
diff --git a/rand/src/distributions/weibull.rs b/rand/src/distributions/weibull.rs
deleted file mode 100644
index 483714f..0000000
--- a/rand/src/distributions/weibull.rs
+++ /dev/null
@@ -1,64 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The Weibull distribution.
-#![allow(deprecated)]
-
-use crate::Rng;
-use crate::distributions::{Distribution, OpenClosed01};
-
-/// Samples floating-point numbers according to the Weibull distribution
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Weibull {
- inv_shape: f64,
- scale: f64,
-}
-
-impl Weibull {
- /// Construct a new `Weibull` distribution with given `scale` and `shape`.
- ///
- /// # Panics
- ///
- /// `scale` and `shape` have to be non-zero and positive.
- pub fn new(scale: f64, shape: f64) -> Weibull {
- assert!((scale > 0.) & (shape > 0.));
- Weibull { inv_shape: 1./shape, scale }
- }
-}
-
-impl Distribution<f64> for Weibull {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- let x: f64 = rng.sample(OpenClosed01);
- self.scale * (-x.ln()).powf(self.inv_shape)
- }
-}
-
-#[cfg(test)]
-mod tests {
- use crate::distributions::Distribution;
- use super::Weibull;
-
- #[test]
- #[should_panic]
- fn invalid() {
- Weibull::new(0., 0.);
- }
-
- #[test]
- fn sample() {
- let scale = 1.0;
- let shape = 2.0;
- let d = Weibull::new(scale, shape);
- let mut rng = crate::test::rng(1);
- for _ in 0..1000 {
- let r = d.sample(&mut rng);
- assert!(r >= 0.);
- }
- }
-}
diff --git a/rand/src/distributions/weighted/alias_method.rs b/rand/src/distributions/weighted/alias_method.rs
deleted file mode 100644
index bdd4ba0..0000000
--- a/rand/src/distributions/weighted/alias_method.rs
+++ /dev/null
@@ -1,499 +0,0 @@
-//! This module contains an implementation of alias method for sampling random
-//! indices with probabilities proportional to a collection of weights.
-
-use super::WeightedError;
-#[cfg(not(feature = "std"))]
-use crate::alloc::vec::Vec;
-#[cfg(not(feature = "std"))]
-use crate::alloc::vec;
-use core::fmt;
-use core::iter::Sum;
-use core::ops::{Add, AddAssign, Div, DivAssign, Mul, MulAssign, Sub, SubAssign};
-use crate::distributions::uniform::SampleUniform;
-use crate::distributions::Distribution;
-use crate::distributions::Uniform;
-use crate::Rng;
-
-/// A distribution using weighted sampling to pick a discretely selected item.
-///
-/// Sampling a [`WeightedIndex<W>`] distribution returns the index of a randomly
-/// selected element from the vector used to create the [`WeightedIndex<W>`].
-/// The chance of a given element being picked is proportional to the value of
-/// the element. The weights can have any type `W` for which a implementation of
-/// [`Weight`] exists.
-///
-/// # Performance
-///
-/// Given that `n` is the number of items in the vector used to create an
-/// [`WeightedIndex<W>`], [`WeightedIndex<W>`] will require `O(n)` amount of
-/// memory. More specifically it takes up some constant amount of memory plus
-/// the vector used to create it and a [`Vec<u32>`] with capacity `n`.
-///
-/// Time complexity for the creation of a [`WeightedIndex<W>`] is `O(n)`.
-/// Sampling is `O(1)`, it makes a call to [`Uniform<u32>::sample`] and a call
-/// to [`Uniform<W>::sample`].
-///
-/// # Example
-///
-/// ```
-/// use rand::distributions::weighted::alias_method::WeightedIndex;
-/// use rand::prelude::*;
-///
-/// let choices = vec!['a', 'b', 'c'];
-/// let weights = vec![2, 1, 1];
-/// let dist = WeightedIndex::new(weights).unwrap();
-/// let mut rng = thread_rng();
-/// for _ in 0..100 {
-/// // 50% chance to print 'a', 25% chance to print 'b', 25% chance to print 'c'
-/// println!("{}", choices[dist.sample(&mut rng)]);
-/// }
-///
-/// let items = [('a', 0), ('b', 3), ('c', 7)];
-/// let dist2 = WeightedIndex::new(items.iter().map(|item| item.1).collect()).unwrap();
-/// for _ in 0..100 {
-/// // 0% chance to print 'a', 30% chance to print 'b', 70% chance to print 'c'
-/// println!("{}", items[dist2.sample(&mut rng)].0);
-/// }
-/// ```
-///
-/// [`WeightedIndex<W>`]: crate::distributions::weighted::alias_method::WeightedIndex
-/// [`Weight`]: crate::distributions::weighted::alias_method::Weight
-/// [`Vec<u32>`]: Vec
-/// [`Uniform<u32>::sample`]: Distribution::sample
-/// [`Uniform<W>::sample`]: Distribution::sample
-pub struct WeightedIndex<W: Weight> {
- aliases: Vec<u32>,
- no_alias_odds: Vec<W>,
- uniform_index: Uniform<u32>,
- uniform_within_weight_sum: Uniform<W>,
-}
-
-impl<W: Weight> WeightedIndex<W> {
- /// Creates a new [`WeightedIndex`].
- ///
- /// Returns an error if:
- /// - The vector is empty.
- /// - The vector is longer than `u32::MAX`.
- /// - For any weight `w`: `w < 0` or `w > max` where `max = W::MAX /
- /// weights.len()`.
- /// - The sum of weights is zero.
- pub fn new(weights: Vec<W>) -> Result<Self, WeightedError> {
- let n = weights.len();
- if n == 0 {
- return Err(WeightedError::NoItem);
- } else if n > ::core::u32::MAX as usize {
- return Err(WeightedError::TooMany);
- }
- let n = n as u32;
-
- let max_weight_size = W::try_from_u32_lossy(n)
- .map(|n| W::MAX / n)
- .unwrap_or(W::ZERO);
- if !weights
- .iter()
- .all(|&w| W::ZERO <= w && w <= max_weight_size)
- {
- return Err(WeightedError::InvalidWeight);
- }
-
- // The sum of weights will represent 100% of no alias odds.
- let weight_sum = Weight::sum(weights.as_slice());
- // Prevent floating point overflow due to rounding errors.
- let weight_sum = if weight_sum > W::MAX {
- W::MAX
- } else {
- weight_sum
- };
- if weight_sum == W::ZERO {
- return Err(WeightedError::AllWeightsZero);
- }
-
- // `weight_sum` would have been zero if `try_from_lossy` causes an error here.
- let n_converted = W::try_from_u32_lossy(n).unwrap();
-
- let mut no_alias_odds = weights;
- for odds in no_alias_odds.iter_mut() {
- *odds *= n_converted;
- // Prevent floating point overflow due to rounding errors.
- *odds = if *odds > W::MAX { W::MAX } else { *odds };
- }
-
- /// This struct is designed to contain three data structures at once,
- /// sharing the same memory. More precisely it contains two linked lists
- /// and an alias map, which will be the output of this method. To keep
- /// the three data structures from getting in each other's way, it must
- /// be ensured that a single index is only ever in one of them at the
- /// same time.
- struct Aliases {
- aliases: Vec<u32>,
- smalls_head: u32,
- bigs_head: u32,
- }
-
- impl Aliases {
- fn new(size: u32) -> Self {
- Aliases {
- aliases: vec![0; size as usize],
- smalls_head: ::core::u32::MAX,
- bigs_head: ::core::u32::MAX,
- }
- }
-
- fn push_small(&mut self, idx: u32) {
- self.aliases[idx as usize] = self.smalls_head;
- self.smalls_head = idx;
- }
-
- fn push_big(&mut self, idx: u32) {
- self.aliases[idx as usize] = self.bigs_head;
- self.bigs_head = idx;
- }
-
- fn pop_small(&mut self) -> u32 {
- let popped = self.smalls_head;
- self.smalls_head = self.aliases[popped as usize];
- popped
- }
-
- fn pop_big(&mut self) -> u32 {
- let popped = self.bigs_head;
- self.bigs_head = self.aliases[popped as usize];
- popped
- }
-
- fn smalls_is_empty(&self) -> bool {
- self.smalls_head == ::core::u32::MAX
- }
-
- fn bigs_is_empty(&self) -> bool {
- self.bigs_head == ::core::u32::MAX
- }
-
- fn set_alias(&mut self, idx: u32, alias: u32) {
- self.aliases[idx as usize] = alias;
- }
- }
-
- let mut aliases = Aliases::new(n);
-
- // Split indices into those with small weights and those with big weights.
- for (index, &odds) in no_alias_odds.iter().enumerate() {
- if odds < weight_sum {
- aliases.push_small(index as u32);
- } else {
- aliases.push_big(index as u32);
- }
- }
-
- // Build the alias map by finding an alias with big weight for each index with
- // small weight.
- while !aliases.smalls_is_empty() && !aliases.bigs_is_empty() {
- let s = aliases.pop_small();
- let b = aliases.pop_big();
-
- aliases.set_alias(s, b);
- no_alias_odds[b as usize] = no_alias_odds[b as usize]
- - weight_sum
- + no_alias_odds[s as usize];
-
- if no_alias_odds[b as usize] < weight_sum {
- aliases.push_small(b);
- } else {
- aliases.push_big(b);
- }
- }
-
- // The remaining indices should have no alias odds of about 100%. This is due to
- // numeric accuracy. Otherwise they would be exactly 100%.
- while !aliases.smalls_is_empty() {
- no_alias_odds[aliases.pop_small() as usize] = weight_sum;
- }
- while !aliases.bigs_is_empty() {
- no_alias_odds[aliases.pop_big() as usize] = weight_sum;
- }
-
- // Prepare distributions for sampling. Creating them beforehand improves
- // sampling performance.
- let uniform_index = Uniform::new(0, n);
- let uniform_within_weight_sum = Uniform::new(W::ZERO, weight_sum);
-
- Ok(Self {
- aliases: aliases.aliases,
- no_alias_odds,
- uniform_index,
- uniform_within_weight_sum,
- })
- }
-}
-
-impl<W: Weight> Distribution<usize> for WeightedIndex<W> {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> usize {
- let candidate = rng.sample(self.uniform_index);
- if rng.sample(&self.uniform_within_weight_sum) < self.no_alias_odds[candidate as usize] {
- candidate as usize
- } else {
- self.aliases[candidate as usize] as usize
- }
- }
-}
-
-impl<W: Weight> fmt::Debug for WeightedIndex<W>
-where
- W: fmt::Debug,
- Uniform<W>: fmt::Debug,
-{
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- f.debug_struct("WeightedIndex")
- .field("aliases", &self.aliases)
- .field("no_alias_odds", &self.no_alias_odds)
- .field("uniform_index", &self.uniform_index)
- .field("uniform_within_weight_sum", &self.uniform_within_weight_sum)
- .finish()
- }
-}
-
-impl<W: Weight> Clone for WeightedIndex<W>
-where
- Uniform<W>: Clone,
-{
- fn clone(&self) -> Self {
- Self {
- aliases: self.aliases.clone(),
- no_alias_odds: self.no_alias_odds.clone(),
- uniform_index: self.uniform_index.clone(),
- uniform_within_weight_sum: self.uniform_within_weight_sum.clone(),
- }
- }
-}
-
-/// Trait that must be implemented for weights, that are used with
-/// [`WeightedIndex`]. Currently no guarantees on the correctness of
-/// [`WeightedIndex`] are given for custom implementations of this trait.
-pub trait Weight:
- Sized
- + Copy
- + SampleUniform
- + PartialOrd
- + Add<Output = Self>
- + AddAssign
- + Sub<Output = Self>
- + SubAssign
- + Mul<Output = Self>
- + MulAssign
- + Div<Output = Self>
- + DivAssign
- + Sum
-{
- /// Maximum number representable by `Self`.
- const MAX: Self;
-
- /// Element of `Self` equivalent to 0.
- const ZERO: Self;
-
- /// Produce an instance of `Self` from a `u32` value, or return `None` if
- /// out of range. Loss of precision (where `Self` is a floating point type)
- /// is acceptable.
- fn try_from_u32_lossy(n: u32) -> Option<Self>;
-
- /// Sums all values in slice `values`.
- fn sum(values: &[Self]) -> Self {
- values.iter().map(|x| *x).sum()
- }
-}
-
-macro_rules! impl_weight_for_float {
- ($T: ident) => {
- impl Weight for $T {
- const MAX: Self = ::core::$T::MAX;
- const ZERO: Self = 0.0;
-
- fn try_from_u32_lossy(n: u32) -> Option<Self> {
- Some(n as $T)
- }
-
- fn sum(values: &[Self]) -> Self {
- pairwise_sum(values)
- }
- }
- };
-}
-
-/// In comparison to naive accumulation, the pairwise sum algorithm reduces
-/// rounding errors when there are many floating point values.
-fn pairwise_sum<T: Weight>(values: &[T]) -> T {
- if values.len() <= 32 {
- values.iter().map(|x| *x).sum()
- } else {
- let mid = values.len() / 2;
- let (a, b) = values.split_at(mid);
- pairwise_sum(a) + pairwise_sum(b)
- }
-}
-
-macro_rules! impl_weight_for_int {
- ($T: ident) => {
- impl Weight for $T {
- const MAX: Self = ::core::$T::MAX;
- const ZERO: Self = 0;
-
- fn try_from_u32_lossy(n: u32) -> Option<Self> {
- let n_converted = n as Self;
- if n_converted >= Self::ZERO && n_converted as u32 == n {
- Some(n_converted)
- } else {
- None
- }
- }
- }
- };
-}
-
-impl_weight_for_float!(f64);
-impl_weight_for_float!(f32);
-impl_weight_for_int!(usize);
-#[cfg(not(target_os = "emscripten"))]
-impl_weight_for_int!(u128);
-impl_weight_for_int!(u64);
-impl_weight_for_int!(u32);
-impl_weight_for_int!(u16);
-impl_weight_for_int!(u8);
-impl_weight_for_int!(isize);
-#[cfg(not(target_os = "emscripten"))]
-impl_weight_for_int!(i128);
-impl_weight_for_int!(i64);
-impl_weight_for_int!(i32);
-impl_weight_for_int!(i16);
-impl_weight_for_int!(i8);
-
-#[cfg(test)]
-mod test {
- use super::*;
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_weighted_index_f32() {
- test_weighted_index(f32::into);
-
- // Floating point special cases
- assert_eq!(
- WeightedIndex::new(vec![::core::f32::INFINITY]).unwrap_err(),
- WeightedError::InvalidWeight
- );
- assert_eq!(
- WeightedIndex::new(vec![-0_f32]).unwrap_err(),
- WeightedError::AllWeightsZero
- );
- assert_eq!(
- WeightedIndex::new(vec![-1_f32]).unwrap_err(),
- WeightedError::InvalidWeight
- );
- assert_eq!(
- WeightedIndex::new(vec![-::core::f32::INFINITY]).unwrap_err(),
- WeightedError::InvalidWeight
- );
- assert_eq!(
- WeightedIndex::new(vec![::core::f32::NAN]).unwrap_err(),
- WeightedError::InvalidWeight
- );
- }
-
- #[cfg(not(target_os = "emscripten"))]
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_weighted_index_u128() {
- test_weighted_index(|x: u128| x as f64);
- }
-
- #[cfg(all(rustc_1_26, not(target_os = "emscripten")))]
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_weighted_index_i128() {
- test_weighted_index(|x: i128| x as f64);
-
- // Signed integer special cases
- assert_eq!(
- WeightedIndex::new(vec![-1_i128]).unwrap_err(),
- WeightedError::InvalidWeight
- );
- assert_eq!(
- WeightedIndex::new(vec![::core::i128::MIN]).unwrap_err(),
- WeightedError::InvalidWeight
- );
- }
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_weighted_index_u8() {
- test_weighted_index(u8::into);
- }
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_weighted_index_i8() {
- test_weighted_index(i8::into);
-
- // Signed integer special cases
- assert_eq!(
- WeightedIndex::new(vec![-1_i8]).unwrap_err(),
- WeightedError::InvalidWeight
- );
- assert_eq!(
- WeightedIndex::new(vec![::core::i8::MIN]).unwrap_err(),
- WeightedError::InvalidWeight
- );
- }
-
- fn test_weighted_index<W: Weight, F: Fn(W) -> f64>(w_to_f64: F)
- where
- WeightedIndex<W>: fmt::Debug,
- {
- const NUM_WEIGHTS: u32 = 10;
- const ZERO_WEIGHT_INDEX: u32 = 3;
- const NUM_SAMPLES: u32 = 15000;
- let mut rng = crate::test::rng(0x9c9fa0b0580a7031);
-
- let weights = {
- let mut weights = Vec::with_capacity(NUM_WEIGHTS as usize);
- let random_weight_distribution = crate::distributions::Uniform::new_inclusive(
- W::ZERO,
- W::MAX / W::try_from_u32_lossy(NUM_WEIGHTS).unwrap(),
- );
- for _ in 0..NUM_WEIGHTS {
- weights.push(rng.sample(&random_weight_distribution));
- }
- weights[ZERO_WEIGHT_INDEX as usize] = W::ZERO;
- weights
- };
- let weight_sum = weights.iter().map(|w| *w).sum::<W>();
- let expected_counts = weights
- .iter()
- .map(|&w| w_to_f64(w) / w_to_f64(weight_sum) * NUM_SAMPLES as f64)
- .collect::<Vec<f64>>();
- let weight_distribution = WeightedIndex::new(weights).unwrap();
-
- let mut counts = vec![0; NUM_WEIGHTS as usize];
- for _ in 0..NUM_SAMPLES {
- counts[rng.sample(&weight_distribution)] += 1;
- }
-
- assert_eq!(counts[ZERO_WEIGHT_INDEX as usize], 0);
- for (count, expected_count) in counts.into_iter().zip(expected_counts) {
- let difference = (count as f64 - expected_count).abs();
- let max_allowed_difference = NUM_SAMPLES as f64 / NUM_WEIGHTS as f64 * 0.1;
- assert!(difference <= max_allowed_difference);
- }
-
- assert_eq!(
- WeightedIndex::<W>::new(vec![]).unwrap_err(),
- WeightedError::NoItem
- );
- assert_eq!(
- WeightedIndex::new(vec![W::ZERO]).unwrap_err(),
- WeightedError::AllWeightsZero
- );
- assert_eq!(
- WeightedIndex::new(vec![W::MAX, W::MAX]).unwrap_err(),
- WeightedError::InvalidWeight
- );
- }
-}
diff --git a/rand/src/distributions/weighted/mod.rs b/rand/src/distributions/weighted/mod.rs
deleted file mode 100644
index 2711637..0000000
--- a/rand/src/distributions/weighted/mod.rs
+++ /dev/null
@@ -1,363 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Weighted index sampling
-//!
-//! This module provides two implementations for sampling indices:
-//!
-//! * [`WeightedIndex`] allows `O(log N)` sampling
-//! * [`alias_method::WeightedIndex`] allows `O(1)` sampling, but with
-//! much greater set-up cost
-//!
-//! [`alias_method::WeightedIndex`]: alias_method/struct.WeightedIndex.html
-
-pub mod alias_method;
-
-use crate::Rng;
-use crate::distributions::Distribution;
-use crate::distributions::uniform::{UniformSampler, SampleUniform, SampleBorrow};
-use core::cmp::PartialOrd;
-use core::fmt;
-
-// Note that this whole module is only imported if feature="alloc" is enabled.
-#[cfg(not(feature="std"))] use crate::alloc::vec::Vec;
-
-/// A distribution using weighted sampling to pick a discretely selected
-/// item.
-///
-/// Sampling a `WeightedIndex` distribution returns the index of a randomly
-/// selected element from the iterator used when the `WeightedIndex` was
-/// created. The chance of a given element being picked is proportional to the
-/// value of the element. The weights can use any type `X` for which an
-/// implementation of [`Uniform<X>`] exists.
-///
-/// # Performance
-///
-/// A `WeightedIndex<X>` contains a `Vec<X>` and a [`Uniform<X>`] and so its
-/// size is the sum of the size of those objects, possibly plus some alignment.
-///
-/// Creating a `WeightedIndex<X>` will allocate enough space to hold `N - 1`
-/// weights of type `X`, where `N` is the number of weights. However, since
-/// `Vec` doesn't guarantee a particular growth strategy, additional memory
-/// might be allocated but not used. Since the `WeightedIndex` object also
-/// contains, this might cause additional allocations, though for primitive
-/// types, ['Uniform<X>`] doesn't allocate any memory.
-///
-/// Time complexity of sampling from `WeightedIndex` is `O(log N)` where
-/// `N` is the number of weights.
-///
-/// Sampling from `WeightedIndex` will result in a single call to
-/// `Uniform<X>::sample` (method of the [`Distribution`] trait), which typically
-/// will request a single value from the underlying [`RngCore`], though the
-/// exact number depends on the implementaiton of `Uniform<X>::sample`.
-///
-/// # Example
-///
-/// ```
-/// use rand::prelude::*;
-/// use rand::distributions::WeightedIndex;
-///
-/// let choices = ['a', 'b', 'c'];
-/// let weights = [2, 1, 1];
-/// let dist = WeightedIndex::new(&weights).unwrap();
-/// let mut rng = thread_rng();
-/// for _ in 0..100 {
-/// // 50% chance to print 'a', 25% chance to print 'b', 25% chance to print 'c'
-/// println!("{}", choices[dist.sample(&mut rng)]);
-/// }
-///
-/// let items = [('a', 0), ('b', 3), ('c', 7)];
-/// let dist2 = WeightedIndex::new(items.iter().map(|item| item.1)).unwrap();
-/// for _ in 0..100 {
-/// // 0% chance to print 'a', 30% chance to print 'b', 70% chance to print 'c'
-/// println!("{}", items[dist2.sample(&mut rng)].0);
-/// }
-/// ```
-///
-/// [`Uniform<X>`]: crate::distributions::uniform::Uniform
-/// [`RngCore`]: crate::RngCore
-#[derive(Debug, Clone)]
-pub struct WeightedIndex<X: SampleUniform + PartialOrd> {
- cumulative_weights: Vec<X>,
- total_weight: X,
- weight_distribution: X::Sampler,
-}
-
-impl<X: SampleUniform + PartialOrd> WeightedIndex<X> {
- /// Creates a new a `WeightedIndex` [`Distribution`] using the values
- /// in `weights`. The weights can use any type `X` for which an
- /// implementation of [`Uniform<X>`] exists.
- ///
- /// Returns an error if the iterator is empty, if any weight is `< 0`, or
- /// if its total value is 0.
- ///
- /// [`Uniform<X>`]: crate::distributions::uniform::Uniform
- pub fn new<I>(weights: I) -> Result<WeightedIndex<X>, WeightedError>
- where I: IntoIterator,
- I::Item: SampleBorrow<X>,
- X: for<'a> ::core::ops::AddAssign<&'a X> +
- Clone +
- Default {
- let mut iter = weights.into_iter();
- let mut total_weight: X = iter.next()
- .ok_or(WeightedError::NoItem)?
- .borrow()
- .clone();
-
- let zero = <X as Default>::default();
- if total_weight < zero {
- return Err(WeightedError::InvalidWeight);
- }
-
- let mut weights = Vec::<X>::with_capacity(iter.size_hint().0);
- for w in iter {
- if *w.borrow() < zero {
- return Err(WeightedError::InvalidWeight);
- }
- weights.push(total_weight.clone());
- total_weight += w.borrow();
- }
-
- if total_weight == zero {
- return Err(WeightedError::AllWeightsZero);
- }
- let distr = X::Sampler::new(zero, total_weight.clone());
-
- Ok(WeightedIndex { cumulative_weights: weights, total_weight, weight_distribution: distr })
- }
-
- /// Update a subset of weights, without changing the number of weights.
- ///
- /// `new_weights` must be sorted by the index.
- ///
- /// Using this method instead of `new` might be more efficient if only a small number of
- /// weights is modified. No allocations are performed, unless the weight type `X` uses
- /// allocation internally.
- ///
- /// In case of error, `self` is not modified.
- pub fn update_weights(&mut self, new_weights: &[(usize, &X)]) -> Result<(), WeightedError>
- where X: for<'a> ::core::ops::AddAssign<&'a X> +
- for<'a> ::core::ops::SubAssign<&'a X> +
- Clone +
- Default {
- if new_weights.is_empty() {
- return Ok(());
- }
-
- let zero = <X as Default>::default();
-
- let mut total_weight = self.total_weight.clone();
-
- // Check for errors first, so we don't modify `self` in case something
- // goes wrong.
- let mut prev_i = None;
- for &(i, w) in new_weights {
- if let Some(old_i) = prev_i {
- if old_i >= i {
- return Err(WeightedError::InvalidWeight);
- }
- }
- if *w < zero {
- return Err(WeightedError::InvalidWeight);
- }
- if i >= self.cumulative_weights.len() + 1 {
- return Err(WeightedError::TooMany);
- }
-
- let mut old_w = if i < self.cumulative_weights.len() {
- self.cumulative_weights[i].clone()
- } else {
- self.total_weight.clone()
- };
- if i > 0 {
- old_w -= &self.cumulative_weights[i - 1];
- }
-
- total_weight -= &old_w;
- total_weight += w;
- prev_i = Some(i);
- }
- if total_weight == zero {
- return Err(WeightedError::AllWeightsZero);
- }
-
- // Update the weights. Because we checked all the preconditions in the
- // previous loop, this should never panic.
- let mut iter = new_weights.iter();
-
- let mut prev_weight = zero.clone();
- let mut next_new_weight = iter.next();
- let &(first_new_index, _) = next_new_weight.unwrap();
- let mut cumulative_weight = if first_new_index > 0 {
- self.cumulative_weights[first_new_index - 1].clone()
- } else {
- zero.clone()
- };
- for i in first_new_index..self.cumulative_weights.len() {
- match next_new_weight {
- Some(&(j, w)) if i == j => {
- cumulative_weight += w;
- next_new_weight = iter.next();
- },
- _ => {
- let mut tmp = self.cumulative_weights[i].clone();
- tmp -= &prev_weight; // We know this is positive.
- cumulative_weight += &tmp;
- }
- }
- prev_weight = cumulative_weight.clone();
- core::mem::swap(&mut prev_weight, &mut self.cumulative_weights[i]);
- }
-
- self.total_weight = total_weight;
- self.weight_distribution = X::Sampler::new(zero, self.total_weight.clone());
-
- Ok(())
- }
-}
-
-impl<X> Distribution<usize> for WeightedIndex<X> where
- X: SampleUniform + PartialOrd {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> usize {
- use ::core::cmp::Ordering;
- let chosen_weight = self.weight_distribution.sample(rng);
- // Find the first item which has a weight *higher* than the chosen weight.
- self.cumulative_weights.binary_search_by(
- |w| if *w <= chosen_weight { Ordering::Less } else { Ordering::Greater }).unwrap_err()
- }
-}
-
-#[cfg(test)]
-mod test {
- use super::*;
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_weightedindex() {
- let mut r = crate::test::rng(700);
- const N_REPS: u32 = 5000;
- let weights = [1u32, 2, 3, 0, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7];
- let total_weight = weights.iter().sum::<u32>() as f32;
-
- let verify = |result: [i32; 14]| {
- for (i, count) in result.iter().enumerate() {
- let exp = (weights[i] * N_REPS) as f32 / total_weight;
- let mut err = (*count as f32 - exp).abs();
- if err != 0.0 {
- err /= exp;
- }
- assert!(err <= 0.25);
- }
- };
-
- // WeightedIndex from vec
- let mut chosen = [0i32; 14];
- let distr = WeightedIndex::new(weights.to_vec()).unwrap();
- for _ in 0..N_REPS {
- chosen[distr.sample(&mut r)] += 1;
- }
- verify(chosen);
-
- // WeightedIndex from slice
- chosen = [0i32; 14];
- let distr = WeightedIndex::new(&weights[..]).unwrap();
- for _ in 0..N_REPS {
- chosen[distr.sample(&mut r)] += 1;
- }
- verify(chosen);
-
- // WeightedIndex from iterator
- chosen = [0i32; 14];
- let distr = WeightedIndex::new(weights.iter()).unwrap();
- for _ in 0..N_REPS {
- chosen[distr.sample(&mut r)] += 1;
- }
- verify(chosen);
-
- for _ in 0..5 {
- assert_eq!(WeightedIndex::new(&[0, 1]).unwrap().sample(&mut r), 1);
- assert_eq!(WeightedIndex::new(&[1, 0]).unwrap().sample(&mut r), 0);
- assert_eq!(WeightedIndex::new(&[0, 0, 0, 0, 10, 0]).unwrap().sample(&mut r), 4);
- }
-
- assert_eq!(WeightedIndex::new(&[10][0..0]).unwrap_err(), WeightedError::NoItem);
- assert_eq!(WeightedIndex::new(&[0]).unwrap_err(), WeightedError::AllWeightsZero);
- assert_eq!(WeightedIndex::new(&[10, 20, -1, 30]).unwrap_err(), WeightedError::InvalidWeight);
- assert_eq!(WeightedIndex::new(&[-10, 20, 1, 30]).unwrap_err(), WeightedError::InvalidWeight);
- assert_eq!(WeightedIndex::new(&[-10]).unwrap_err(), WeightedError::InvalidWeight);
- }
-
- #[test]
- fn test_update_weights() {
- let data = [
- (&[10u32, 2, 3, 4][..],
- &[(1, &100), (2, &4)][..], // positive change
- &[10, 100, 4, 4][..]),
- (&[1u32, 2, 3, 0, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7][..],
- &[(2, &1), (5, &1), (13, &100)][..], // negative change and last element
- &[1u32, 2, 1, 0, 5, 1, 7, 1, 2, 3, 4, 5, 6, 100][..]),
- ];
-
- for (weights, update, expected_weights) in data.into_iter() {
- let total_weight = weights.iter().sum::<u32>();
- let mut distr = WeightedIndex::new(weights.to_vec()).unwrap();
- assert_eq!(distr.total_weight, total_weight);
-
- distr.update_weights(update).unwrap();
- let expected_total_weight = expected_weights.iter().sum::<u32>();
- let expected_distr = WeightedIndex::new(expected_weights.to_vec()).unwrap();
- assert_eq!(distr.total_weight, expected_total_weight);
- assert_eq!(distr.total_weight, expected_distr.total_weight);
- assert_eq!(distr.cumulative_weights, expected_distr.cumulative_weights);
- }
- }
-}
-
-/// Error type returned from `WeightedIndex::new`.
-#[derive(Debug, Clone, Copy, PartialEq, Eq)]
-pub enum WeightedError {
- /// The provided weight collection contains no items.
- NoItem,
-
- /// A weight is either less than zero, greater than the supported maximum or
- /// otherwise invalid.
- InvalidWeight,
-
- /// All items in the provided weight collection are zero.
- AllWeightsZero,
-
- /// Too many weights are provided (length greater than `u32::MAX`)
- TooMany,
-}
-
-impl WeightedError {
- fn msg(&self) -> &str {
- match *self {
- WeightedError::NoItem => "No weights provided.",
- WeightedError::InvalidWeight => "A weight is invalid.",
- WeightedError::AllWeightsZero => "All weights are zero.",
- WeightedError::TooMany => "Too many weights (hit u32::MAX)",
- }
- }
-}
-
-#[cfg(feature="std")]
-impl ::std::error::Error for WeightedError {
- fn description(&self) -> &str {
- self.msg()
- }
- fn cause(&self) -> Option<&dyn (::std::error::Error)> {
- None
- }
-}
-
-impl fmt::Display for WeightedError {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "{}", self.msg())
- }
-}
diff --git a/rand/src/distributions/ziggurat_tables.rs b/rand/src/distributions/ziggurat_tables.rs
deleted file mode 100644
index ca1ce30..0000000
--- a/rand/src/distributions/ziggurat_tables.rs
+++ /dev/null
@@ -1,279 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-// Tables for distributions which are sampled using the ziggurat
-// algorithm. Autogenerated by `ziggurat_tables.py`.
-
-pub type ZigTable = &'static [f64; 257];
-pub const ZIG_NORM_R: f64 = 3.654152885361008796;
-pub static ZIG_NORM_X: [f64; 257] =
- [3.910757959537090045, 3.654152885361008796, 3.449278298560964462, 3.320244733839166074,
- 3.224575052047029100, 3.147889289517149969, 3.083526132001233044, 3.027837791768635434,
- 2.978603279880844834, 2.934366867207854224, 2.894121053612348060, 2.857138730872132548,
- 2.822877396825325125, 2.790921174000785765, 2.760944005278822555, 2.732685359042827056,
- 2.705933656121858100, 2.680514643284522158, 2.656283037575502437, 2.633116393630324570,
- 2.610910518487548515, 2.589575986706995181, 2.569035452680536569, 2.549221550323460761,
- 2.530075232158516929, 2.511544441625342294, 2.493583041269680667, 2.476149939669143318,
- 2.459208374333311298, 2.442725318198956774, 2.426670984935725972, 2.411018413899685520,
- 2.395743119780480601, 2.380822795170626005, 2.366237056715818632, 2.351967227377659952,
- 2.337996148795031370, 2.324308018869623016, 2.310888250599850036, 2.297723348901329565,
- 2.284800802722946056, 2.272108990226823888, 2.259637095172217780, 2.247375032945807760,
- 2.235313384928327984, 2.223443340090905718, 2.211756642882544366, 2.200245546609647995,
- 2.188902771624720689, 2.177721467738641614, 2.166695180352645966, 2.155817819875063268,
- 2.145083634046203613, 2.134487182844320152, 2.124023315687815661, 2.113687150684933957,
- 2.103474055713146829, 2.093379631137050279, 2.083399693996551783, 2.073530263516978778,
- 2.063767547809956415, 2.054107931648864849, 2.044547965215732788, 2.035084353727808715,
- 2.025713947862032960, 2.016433734904371722, 2.007240830558684852, 1.998132471356564244,
- 1.989106007615571325, 1.980158896898598364, 1.971288697931769640, 1.962493064942461896,
- 1.953769742382734043, 1.945116560006753925, 1.936531428273758904, 1.928012334050718257,
- 1.919557336591228847, 1.911164563769282232, 1.902832208548446369, 1.894558525668710081,
- 1.886341828534776388, 1.878180486290977669, 1.870072921069236838, 1.862017605397632281,
- 1.854013059758148119, 1.846057850283119750, 1.838150586580728607, 1.830289919680666566,
- 1.822474540091783224, 1.814703175964167636, 1.806974591348693426, 1.799287584547580199,
- 1.791640986550010028, 1.784033659547276329, 1.776464495522344977, 1.768932414909077933,
- 1.761436365316706665, 1.753975320315455111, 1.746548278279492994, 1.739154261283669012,
- 1.731792314050707216, 1.724461502945775715, 1.717160915015540690, 1.709889657069006086,
- 1.702646854797613907, 1.695431651932238548, 1.688243209434858727, 1.681080704722823338,
- 1.673943330923760353, 1.666830296159286684, 1.659740822855789499, 1.652674147080648526,
- 1.645629517902360339, 1.638606196773111146, 1.631603456932422036, 1.624620582830568427,
- 1.617656869570534228, 1.610711622367333673, 1.603784156023583041, 1.596873794420261339,
- 1.589979870021648534, 1.583101723393471438, 1.576238702733332886, 1.569390163412534456,
- 1.562555467528439657, 1.555733983466554893, 1.548925085471535512, 1.542128153226347553,
- 1.535342571438843118, 1.528567729435024614, 1.521803020758293101, 1.515047842773992404,
- 1.508301596278571965, 1.501563685112706548, 1.494833515777718391, 1.488110497054654369,
- 1.481394039625375747, 1.474683555695025516, 1.467978458615230908, 1.461278162507407830,
- 1.454582081885523293, 1.447889631277669675, 1.441200224845798017, 1.434513276002946425,
- 1.427828197027290358, 1.421144398672323117, 1.414461289772464658, 1.407778276843371534,
- 1.401094763676202559, 1.394410150925071257, 1.387723835686884621, 1.381035211072741964,
- 1.374343665770030531, 1.367648583594317957, 1.360949343030101844, 1.354245316759430606,
- 1.347535871177359290, 1.340820365893152122, 1.334098153216083604, 1.327368577624624679,
- 1.320630975217730096, 1.313884673146868964, 1.307128989027353860, 1.300363230327433728,
- 1.293586693733517645, 1.286798664489786415, 1.279998415710333237, 1.273185207661843732,
- 1.266358287014688333, 1.259516886060144225, 1.252660221891297887, 1.245787495544997903,
- 1.238897891102027415, 1.231990574742445110, 1.225064693752808020, 1.218119375481726552,
- 1.211153726239911244, 1.204166830140560140, 1.197157747875585931, 1.190125515422801650,
- 1.183069142678760732, 1.175987612011489825, 1.168879876726833800, 1.161744859441574240,
- 1.154581450355851802, 1.147388505416733873, 1.140164844363995789, 1.132909248648336975,
- 1.125620459211294389, 1.118297174115062909, 1.110938046009249502, 1.103541679420268151,
- 1.096106627847603487, 1.088631390649514197, 1.081114409698889389, 1.073554065787871714,
- 1.065948674757506653, 1.058296483326006454, 1.050595664586207123, 1.042844313139370538,
- 1.035040439828605274, 1.027181966030751292, 1.019266717460529215, 1.011292417434978441,
- 1.003256679539591412, 0.995156999629943084, 0.986990747093846266, 0.978755155288937750,
- 0.970447311058864615, 0.962064143217605250, 0.953602409875572654, 0.945058684462571130,
- 0.936429340280896860, 0.927710533396234771, 0.918898183643734989, 0.909987953490768997,
- 0.900975224455174528, 0.891855070726792376, 0.882622229578910122, 0.873271068082494550,
- 0.863795545546826915, 0.854189171001560554, 0.844444954902423661, 0.834555354079518752,
- 0.824512208745288633, 0.814306670128064347, 0.803929116982664893, 0.793369058833152785,
- 0.782615023299588763, 0.771654424216739354, 0.760473406422083165, 0.749056662009581653,
- 0.737387211425838629, 0.725446140901303549, 0.713212285182022732, 0.700661841097584448,
- 0.687767892786257717, 0.674499822827436479, 0.660822574234205984, 0.646695714884388928,
- 0.632072236375024632, 0.616896989996235545, 0.601104617743940417, 0.584616766093722262,
- 0.567338257040473026, 0.549151702313026790, 0.529909720646495108, 0.509423329585933393,
- 0.487443966121754335, 0.463634336771763245, 0.437518402186662658, 0.408389134588000746,
- 0.375121332850465727, 0.335737519180459465, 0.286174591747260509, 0.215241895913273806,
- 0.000000000000000000];
-pub static ZIG_NORM_F: [f64; 257] =
- [0.000477467764586655, 0.001260285930498598, 0.002609072746106363, 0.004037972593371872,
- 0.005522403299264754, 0.007050875471392110, 0.008616582769422917, 0.010214971439731100,
- 0.011842757857943104, 0.013497450601780807, 0.015177088307982072, 0.016880083152595839,
- 0.018605121275783350, 0.020351096230109354, 0.022117062707379922, 0.023902203305873237,
- 0.025705804008632656, 0.027527235669693315, 0.029365939758230111, 0.031221417192023690,
- 0.033093219458688698, 0.034980941461833073, 0.036884215688691151, 0.038802707404656918,
- 0.040736110656078753, 0.042684144916619378, 0.044646552251446536, 0.046623094902089664,
- 0.048613553216035145, 0.050617723861121788, 0.052635418276973649, 0.054666461325077916,
- 0.056710690106399467, 0.058767952921137984, 0.060838108349751806, 0.062921024437977854,
- 0.065016577971470438, 0.067124653828023989, 0.069245144397250269, 0.071377949059141965,
- 0.073522973714240991, 0.075680130359194964, 0.077849336702372207, 0.080030515814947509,
- 0.082223595813495684, 0.084428509570654661, 0.086645194450867782, 0.088873592068594229,
- 0.091113648066700734, 0.093365311913026619, 0.095628536713353335, 0.097903279039215627,
- 0.100189498769172020, 0.102487158942306270, 0.104796225622867056, 0.107116667775072880,
- 0.109448457147210021, 0.111791568164245583, 0.114145977828255210, 0.116511665626037014,
- 0.118888613443345698, 0.121276805485235437, 0.123676228202051403, 0.126086870220650349,
- 0.128508722280473636, 0.130941777174128166, 0.133386029692162844, 0.135841476571757352,
- 0.138308116449064322, 0.140785949814968309, 0.143274978974047118, 0.145775208006537926,
- 0.148286642733128721, 0.150809290682410169, 0.153343161060837674, 0.155888264725064563,
- 0.158444614156520225, 0.161012223438117663, 0.163591108232982951, 0.166181285765110071,
- 0.168782774801850333, 0.171395595638155623, 0.174019770082499359, 0.176655321444406654,
- 0.179302274523530397, 0.181960655600216487, 0.184630492427504539, 0.187311814224516926,
- 0.190004651671193070, 0.192709036904328807, 0.195425003514885592, 0.198152586546538112,
- 0.200891822495431333, 0.203642749311121501, 0.206405406398679298, 0.209179834621935651,
- 0.211966076307852941, 0.214764175252008499, 0.217574176725178370, 0.220396127481011589,
- 0.223230075764789593, 0.226076071323264877, 0.228934165415577484, 0.231804410825248525,
- 0.234686861873252689, 0.237581574432173676, 0.240488605941449107, 0.243408015423711988,
- 0.246339863502238771, 0.249284212419516704, 0.252241126056943765, 0.255210669955677150,
- 0.258192911338648023, 0.261187919133763713, 0.264195763998317568, 0.267216518344631837,
- 0.270250256366959984, 0.273297054069675804, 0.276356989296781264, 0.279430141762765316,
- 0.282516593084849388, 0.285616426816658109, 0.288729728483353931, 0.291856585618280984,
- 0.294997087801162572, 0.298151326697901342, 0.301319396102034120, 0.304501391977896274,
- 0.307697412505553769, 0.310907558127563710, 0.314131931597630143, 0.317370638031222396,
- 0.320623784958230129, 0.323891482377732021, 0.327173842814958593, 0.330470981380537099,
- 0.333783015832108509, 0.337110066638412809, 0.340452257045945450, 0.343809713148291340,
- 0.347182563958251478, 0.350570941482881204, 0.353974980801569250, 0.357394820147290515,
- 0.360830600991175754, 0.364282468130549597, 0.367750569780596226, 0.371235057669821344,
- 0.374736087139491414, 0.378253817247238111, 0.381788410875031348, 0.385340034841733958,
- 0.388908860020464597, 0.392495061461010764, 0.396098818517547080, 0.399720314981931668,
- 0.403359739222868885, 0.407017284331247953, 0.410693148271983222, 0.414387534042706784,
- 0.418100649839684591, 0.421832709231353298, 0.425583931339900579, 0.429354541031341519,
- 0.433144769114574058, 0.436954852549929273, 0.440785034667769915, 0.444635565397727750,
- 0.448506701509214067, 0.452398706863882505, 0.456311852680773566, 0.460246417814923481,
- 0.464202689050278838, 0.468180961407822172, 0.472181538469883255, 0.476204732721683788,
- 0.480250865911249714, 0.484320269428911598, 0.488413284707712059, 0.492530263646148658,
- 0.496671569054796314, 0.500837575128482149, 0.505028667945828791, 0.509245245998136142,
- 0.513487720749743026, 0.517756517232200619, 0.522052074674794864, 0.526374847174186700,
- 0.530725304406193921, 0.535103932383019565, 0.539511234259544614, 0.543947731192649941,
- 0.548413963257921133, 0.552910490428519918, 0.557437893621486324, 0.561996775817277916,
- 0.566587763258951771, 0.571211506738074970, 0.575868682975210544, 0.580559996103683473,
- 0.585286179266300333, 0.590047996335791969, 0.594846243770991268, 0.599681752622167719,
- 0.604555390700549533, 0.609468064928895381, 0.614420723892076803, 0.619414360609039205,
- 0.624450015550274240, 0.629528779928128279, 0.634651799290960050, 0.639820277456438991,
- 0.645035480824251883, 0.650298743114294586, 0.655611470583224665, 0.660975147780241357,
- 0.666391343912380640, 0.671861719900766374, 0.677388036222513090, 0.682972161648791376,
- 0.688616083008527058, 0.694321916130032579, 0.700091918140490099, 0.705928501336797409,
- 0.711834248882358467, 0.717811932634901395, 0.723864533472881599, 0.729995264565802437,
- 0.736207598131266683, 0.742505296344636245, 0.748892447223726720, 0.755373506511754500,
- 0.761953346841546475, 0.768637315803334831, 0.775431304986138326, 0.782341832659861902,
- 0.789376143571198563, 0.796542330428254619, 0.803849483176389490, 0.811307874318219935,
- 0.818929191609414797, 0.826726833952094231, 0.834716292992930375, 0.842915653118441077,
- 0.851346258465123684, 0.860033621203008636, 0.869008688043793165, 0.878309655816146839,
- 0.887984660763399880, 0.898095921906304051, 0.908726440060562912, 0.919991505048360247,
- 0.932060075968990209, 0.945198953453078028, 0.959879091812415930, 0.977101701282731328,
- 1.000000000000000000];
-pub const ZIG_EXP_R: f64 = 7.697117470131050077;
-pub static ZIG_EXP_X: [f64; 257] =
- [8.697117470131052741, 7.697117470131050077, 6.941033629377212577, 6.478378493832569696,
- 6.144164665772472667, 5.882144315795399869, 5.666410167454033697, 5.482890627526062488,
- 5.323090505754398016, 5.181487281301500047, 5.054288489981304089, 4.938777085901250530,
- 4.832939741025112035, 4.735242996601741083, 4.644491885420085175, 4.559737061707351380,
- 4.480211746528421912, 4.405287693473573185, 4.334443680317273007, 4.267242480277365857,
- 4.203313713735184365, 4.142340865664051464, 4.084051310408297830, 4.028208544647936762,
- 3.974606066673788796, 3.923062500135489739, 3.873417670399509127, 3.825529418522336744,
- 3.779270992411667862, 3.734528894039797375, 3.691201090237418825, 3.649195515760853770,
- 3.608428813128909507, 3.568825265648337020, 3.530315889129343354, 3.492837654774059608,
- 3.456332821132760191, 3.420748357251119920, 3.386035442460300970, 3.352149030900109405,
- 3.319047470970748037, 3.286692171599068679, 3.255047308570449882, 3.224079565286264160,
- 3.193757903212240290, 3.164053358025972873, 3.134938858084440394, 3.106389062339824481,
- 3.078380215254090224, 3.050890016615455114, 3.023897504455676621, 2.997382949516130601,
- 2.971327759921089662, 2.945714394895045718, 2.920526286512740821, 2.895747768600141825,
- 2.871364012015536371, 2.847360965635188812, 2.823725302450035279, 2.800444370250737780,
- 2.777506146439756574, 2.754899196562344610, 2.732612636194700073, 2.710636095867928752,
- 2.688959688741803689, 2.667573980773266573, 2.646469963151809157, 2.625639026797788489,
- 2.605072938740835564, 2.584763820214140750, 2.564704126316905253, 2.544886627111869970,
- 2.525304390037828028, 2.505950763528594027, 2.486819361740209455, 2.467904050297364815,
- 2.449198932978249754, 2.430698339264419694, 2.412396812688870629, 2.394289099921457886,
- 2.376370140536140596, 2.358635057409337321, 2.341079147703034380, 2.323697874390196372,
- 2.306486858283579799, 2.289441870532269441, 2.272558825553154804, 2.255833774367219213,
- 2.239262898312909034, 2.222842503111036816, 2.206569013257663858, 2.190438966723220027,
- 2.174449009937774679, 2.158595893043885994, 2.142876465399842001, 2.127287671317368289,
- 2.111826546019042183, 2.096490211801715020, 2.081275874393225145, 2.066180819490575526,
- 2.051202409468584786, 2.036338080248769611, 2.021585338318926173, 2.006941757894518563,
- 1.992404978213576650, 1.977972700957360441, 1.963642687789548313, 1.949412758007184943,
- 1.935280786297051359, 1.921244700591528076, 1.907302480018387536, 1.893452152939308242,
- 1.879691795072211180, 1.866019527692827973, 1.852433515911175554, 1.838931967018879954,
- 1.825513128903519799, 1.812175288526390649, 1.798916770460290859, 1.785735935484126014,
- 1.772631179231305643, 1.759600930889074766, 1.746643651946074405, 1.733757834985571566,
- 1.720942002521935299, 1.708194705878057773, 1.695514524101537912, 1.682900062917553896,
- 1.670349953716452118, 1.657862852574172763, 1.645437439303723659, 1.633072416535991334,
- 1.620766508828257901, 1.608518461798858379, 1.596327041286483395, 1.584191032532688892,
- 1.572109239386229707, 1.560080483527888084, 1.548103603714513499, 1.536177455041032092,
- 1.524300908219226258, 1.512472848872117082, 1.500692176842816750, 1.488957805516746058,
- 1.477268661156133867, 1.465623682245745352, 1.454021818848793446, 1.442462031972012504,
- 1.430943292938879674, 1.419464582769983219, 1.408024891569535697, 1.396623217917042137,
- 1.385258568263121992, 1.373929956328490576, 1.362636402505086775, 1.351376933258335189,
- 1.340150580529504643, 1.328956381137116560, 1.317793376176324749, 1.306660610415174117,
- 1.295557131686601027, 1.284481990275012642, 1.273434238296241139, 1.262412929069615330,
- 1.251417116480852521, 1.240445854334406572, 1.229498195693849105, 1.218573192208790124,
- 1.207669893426761121, 1.196787346088403092, 1.185924593404202199, 1.175080674310911677,
- 1.164254622705678921, 1.153445466655774743, 1.142652227581672841, 1.131873919411078511,
- 1.121109547701330200, 1.110358108727411031, 1.099618588532597308, 1.088889961938546813,
- 1.078171191511372307, 1.067461226479967662, 1.056759001602551429, 1.046063435977044209,
- 1.035373431790528542, 1.024687873002617211, 1.014005623957096480, 1.003325527915696735,
- 0.992646405507275897, 0.981967053085062602, 0.971286240983903260, 0.960602711668666509,
- 0.949915177764075969, 0.939222319955262286, 0.928522784747210395, 0.917815182070044311,
- 0.907098082715690257, 0.896370015589889935, 0.885629464761751528, 0.874874866291025066,
- 0.864104604811004484, 0.853317009842373353, 0.842510351810368485, 0.831682837734273206,
- 0.820832606554411814, 0.809957724057418282, 0.799056177355487174, 0.788125868869492430,
- 0.777164609759129710, 0.766170112735434672, 0.755139984181982249, 0.744071715500508102,
- 0.732962673584365398, 0.721810090308756203, 0.710611050909655040, 0.699362481103231959,
- 0.688061132773747808, 0.676703568029522584, 0.665286141392677943, 0.653804979847664947,
- 0.642255960424536365, 0.630634684933490286, 0.618936451394876075, 0.607156221620300030,
- 0.595288584291502887, 0.583327712748769489, 0.571267316532588332, 0.559100585511540626,
- 0.546820125163310577, 0.534417881237165604, 0.521885051592135052, 0.509211982443654398,
- 0.496388045518671162, 0.483401491653461857, 0.470239275082169006, 0.456886840931420235,
- 0.443327866073552401, 0.429543940225410703, 0.415514169600356364, 0.401214678896277765,
- 0.386617977941119573, 0.371692145329917234, 0.356399760258393816, 0.340696481064849122,
- 0.324529117016909452, 0.307832954674932158, 0.290527955491230394, 0.272513185478464703,
- 0.253658363385912022, 0.233790483059674731, 0.212671510630966620, 0.189958689622431842,
- 0.165127622564187282, 0.137304980940012589, 0.104838507565818778, 0.063852163815001570,
- 0.000000000000000000];
-pub static ZIG_EXP_F: [f64; 257] =
- [0.000167066692307963, 0.000454134353841497, 0.000967269282327174, 0.001536299780301573,
- 0.002145967743718907, 0.002788798793574076, 0.003460264777836904, 0.004157295120833797,
- 0.004877655983542396, 0.005619642207205489, 0.006381905937319183, 0.007163353183634991,
- 0.007963077438017043, 0.008780314985808977, 0.009614413642502212, 0.010464810181029981,
- 0.011331013597834600, 0.012212592426255378, 0.013109164931254991, 0.014020391403181943,
- 0.014945968011691148, 0.015885621839973156, 0.016839106826039941, 0.017806200410911355,
- 0.018786700744696024, 0.019780424338009740, 0.020787204072578114, 0.021806887504283581,
- 0.022839335406385240, 0.023884420511558174, 0.024942026419731787, 0.026012046645134221,
- 0.027094383780955803, 0.028188948763978646, 0.029295660224637411, 0.030414443910466622,
- 0.031545232172893622, 0.032687963508959555, 0.033842582150874358, 0.035009037697397431,
- 0.036187284781931443, 0.037377282772959382, 0.038578995503074871, 0.039792391023374139,
- 0.041017441380414840, 0.042254122413316254, 0.043502413568888197, 0.044762297732943289,
- 0.046033761076175184, 0.047316792913181561, 0.048611385573379504, 0.049917534282706379,
- 0.051235237055126281, 0.052564494593071685, 0.053905310196046080, 0.055257689676697030,
- 0.056621641283742870, 0.057997175631200659, 0.059384305633420280, 0.060783046445479660,
- 0.062193415408541036, 0.063615431999807376, 0.065049117786753805, 0.066494496385339816,
- 0.067951593421936643, 0.069420436498728783, 0.070901055162371843, 0.072393480875708752,
- 0.073897746992364746, 0.075413888734058410, 0.076941943170480517, 0.078481949201606435,
- 0.080033947542319905, 0.081597980709237419, 0.083174093009632397, 0.084762330532368146,
- 0.086362741140756927, 0.087975374467270231, 0.089600281910032886, 0.091237516631040197,
- 0.092887133556043569, 0.094549189376055873, 0.096223742550432825, 0.097910853311492213,
- 0.099610583670637132, 0.101322997425953631, 0.103048160171257702, 0.104786139306570145,
- 0.106537004050001632, 0.108300825451033755, 0.110077676405185357, 0.111867631670056283,
- 0.113670767882744286, 0.115487163578633506, 0.117316899211555525, 0.119160057175327641,
- 0.121016721826674792, 0.122886979509545108, 0.124770918580830933, 0.126668629437510671,
- 0.128580204545228199, 0.130505738468330773, 0.132445327901387494, 0.134399071702213602,
- 0.136367070926428829, 0.138349428863580176, 0.140346251074862399, 0.142357645432472146,
- 0.144383722160634720, 0.146424593878344889, 0.148480375643866735, 0.150551185001039839,
- 0.152637142027442801, 0.154738369384468027, 0.156854992369365148, 0.158987138969314129,
- 0.161134939917591952, 0.163298528751901734, 0.165478041874935922, 0.167673618617250081,
- 0.169885401302527550, 0.172113535315319977, 0.174358169171353411, 0.176619454590494829,
- 0.178897546572478278, 0.181192603475496261, 0.183504787097767436, 0.185834262762197083,
- 0.188181199404254262, 0.190545769663195363, 0.192928149976771296, 0.195328520679563189,
- 0.197747066105098818, 0.200183974691911210, 0.202639439093708962, 0.205113656293837654,
- 0.207606827724221982, 0.210119159388988230, 0.212650861992978224, 0.215202151075378628,
- 0.217773247148700472, 0.220364375843359439, 0.222975768058120111, 0.225607660116683956,
- 0.228260293930716618, 0.230933917169627356, 0.233628783437433291, 0.236345152457059560,
- 0.239083290262449094, 0.241843469398877131, 0.244625969131892024, 0.247431075665327543,
- 0.250259082368862240, 0.253110290015629402, 0.255985007030415324, 0.258883549749016173,
- 0.261806242689362922, 0.264753418835062149, 0.267725419932044739, 0.270722596799059967,
- 0.273745309652802915, 0.276793928448517301, 0.279868833236972869, 0.282970414538780746,
- 0.286099073737076826, 0.289255223489677693, 0.292439288161892630, 0.295651704281261252,
- 0.298892921015581847, 0.302163400675693528, 0.305463619244590256, 0.308794066934560185,
- 0.312155248774179606, 0.315547685227128949, 0.318971912844957239, 0.322428484956089223,
- 0.325917972393556354, 0.329440964264136438, 0.332998068761809096, 0.336589914028677717,
- 0.340217149066780189, 0.343880444704502575, 0.347580494621637148, 0.351318016437483449,
- 0.355093752866787626, 0.358908472948750001, 0.362762973354817997, 0.366658079781514379,
- 0.370594648435146223, 0.374573567615902381, 0.378595759409581067, 0.382662181496010056,
- 0.386773829084137932, 0.390931736984797384, 0.395136981833290435, 0.399390684475231350,
- 0.403694012530530555, 0.408048183152032673, 0.412454465997161457, 0.416914186433003209,
- 0.421428728997616908, 0.425999541143034677, 0.430628137288459167, 0.435316103215636907,
- 0.440065100842354173, 0.444876873414548846, 0.449753251162755330, 0.454696157474615836,
- 0.459707615642138023, 0.464789756250426511, 0.469944825283960310, 0.475175193037377708,
- 0.480483363930454543, 0.485871987341885248, 0.491343869594032867, 0.496901987241549881,
- 0.502549501841348056, 0.508289776410643213, 0.514126393814748894, 0.520063177368233931,
- 0.526104213983620062, 0.532253880263043655, 0.538516872002862246, 0.544898237672440056,
- 0.551403416540641733, 0.558038282262587892, 0.564809192912400615, 0.571723048664826150,
- 0.578787358602845359, 0.586010318477268366, 0.593400901691733762, 0.600968966365232560,
- 0.608725382079622346, 0.616682180915207878, 0.624852738703666200, 0.633251994214366398,
- 0.641896716427266423, 0.650805833414571433, 0.660000841079000145, 0.669506316731925177,
- 0.679350572264765806, 0.689566496117078431, 0.700192655082788606, 0.711274760805076456,
- 0.722867659593572465, 0.735038092431424039, 0.747868621985195658, 0.761463388849896838,
- 0.775956852040116218, 0.791527636972496285, 0.808421651523009044, 0.826993296643051101,
- 0.847785500623990496, 0.871704332381204705, 0.900469929925747703, 0.938143680862176477,
- 1.000000000000000000];
diff --git a/rand/src/lib.rs b/rand/src/lib.rs
deleted file mode 100644
index b4167c3..0000000
--- a/rand/src/lib.rs
+++ /dev/null
@@ -1,720 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013-2017 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Utilities for random number generation
-//!
-//! Rand provides utilities to generate random numbers, to convert them to
-//! useful types and distributions, and some randomness-related algorithms.
-//!
-//! # Quick Start
-//!
-//! To get you started quickly, the easiest and highest-level way to get
-//! a random value is to use [`random()`]; alternatively you can use
-//! [`thread_rng()`]. The [`Rng`] trait provides a useful API on all RNGs, while
-//! the [`distributions`] and [`seq`] modules provide further
-//! functionality on top of RNGs.
-//!
-//! ```
-//! use rand::prelude::*;
-//!
-//! if rand::random() { // generates a boolean
-//! // Try printing a random unicode code point (probably a bad idea)!
-//! println!("char: {}", rand::random::<char>());
-//! }
-//!
-//! let mut rng = rand::thread_rng();
-//! let y: f64 = rng.gen(); // generates a float between 0 and 1
-//!
-//! let mut nums: Vec<i32> = (1..100).collect();
-//! nums.shuffle(&mut rng);
-//! ```
-//!
-//! # The Book
-//!
-//! For the user guide and futher documentation, please read
-//! [The Rust Rand Book](https://rust-random.github.io/book).
-
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
- html_favicon_url = "https://www.rust-lang.org/favicon.ico",
- html_root_url = "https://rust-random.github.io/rand/")]
-
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-#![doc(test(attr(allow(unused_variables), deny(warnings))))]
-
-#![cfg_attr(not(feature="std"), no_std)]
-#![cfg_attr(all(feature="simd_support", feature="nightly"), feature(stdsimd))]
-
-#![allow(clippy::excessive_precision, clippy::unreadable_literal, clippy::float_cmp)]
-
-#[cfg(all(feature="alloc", not(feature="std")))]
-extern crate alloc;
-
-#[cfg(feature = "getrandom")]
-use getrandom_package as getrandom;
-
-#[allow(unused)]
-macro_rules! trace { ($($x:tt)*) => (
- #[cfg(feature = "log")] {
- log::trace!($($x)*)
- }
-) }
-#[allow(unused)]
-macro_rules! debug { ($($x:tt)*) => (
- #[cfg(feature = "log")] {
- log::debug!($($x)*)
- }
-) }
-#[allow(unused)]
-macro_rules! info { ($($x:tt)*) => (
- #[cfg(feature = "log")] {
- log::info!($($x)*)
- }
-) }
-#[allow(unused)]
-macro_rules! warn { ($($x:tt)*) => (
- #[cfg(feature = "log")] {
- log::warn!($($x)*)
- }
-) }
-#[allow(unused)]
-macro_rules! error { ($($x:tt)*) => (
- #[cfg(feature = "log")] {
- log::error!($($x)*)
- }
-) }
-
-// Re-exports from rand_core
-pub use rand_core::{RngCore, CryptoRng, SeedableRng, Error};
-
-// Public exports
-#[cfg(feature="std")] pub use crate::rngs::thread::thread_rng;
-
-// Public modules
-pub mod distributions;
-pub mod prelude;
-pub mod rngs;
-pub mod seq;
-
-
-use core::{mem, slice};
-use core::num::Wrapping;
-use crate::distributions::{Distribution, Standard};
-use crate::distributions::uniform::{SampleUniform, UniformSampler, SampleBorrow};
-
-/// An automatically-implemented extension trait on [`RngCore`] providing high-level
-/// generic methods for sampling values and other convenience methods.
-///
-/// This is the primary trait to use when generating random values.
-///
-/// # Generic usage
-///
-/// The basic pattern is `fn foo<R: Rng + ?Sized>(rng: &mut R)`. Some
-/// things are worth noting here:
-///
-/// - Since `Rng: RngCore` and every `RngCore` implements `Rng`, it makes no
-/// difference whether we use `R: Rng` or `R: RngCore`.
-/// - The `+ ?Sized` un-bounding allows functions to be called directly on
-/// type-erased references; i.e. `foo(r)` where `r: &mut RngCore`. Without
-/// this it would be necessary to write `foo(&mut r)`.
-///
-/// An alternative pattern is possible: `fn foo<R: Rng>(rng: R)`. This has some
-/// trade-offs. It allows the argument to be consumed directly without a `&mut`
-/// (which is how `from_rng(thread_rng())` works); also it still works directly
-/// on references (including type-erased references). Unfortunately within the
-/// function `foo` it is not known whether `rng` is a reference type or not,
-/// hence many uses of `rng` require an extra reference, either explicitly
-/// (`distr.sample(&mut rng)`) or implicitly (`rng.gen()`); one may hope the
-/// optimiser can remove redundant references later.
-///
-/// Example:
-///
-/// ```
-/// # use rand::thread_rng;
-/// use rand::Rng;
-///
-/// fn foo<R: Rng + ?Sized>(rng: &mut R) -> f32 {
-/// rng.gen()
-/// }
-///
-/// # let v = foo(&mut thread_rng());
-/// ```
-pub trait Rng: RngCore {
- /// Return a random value supporting the [`Standard`] distribution.
- ///
- /// # Example
- ///
- /// ```
- /// use rand::{thread_rng, Rng};
- ///
- /// let mut rng = thread_rng();
- /// let x: u32 = rng.gen();
- /// println!("{}", x);
- /// println!("{:?}", rng.gen::<(f64, bool)>());
- /// ```
- ///
- /// # Arrays and tuples
- ///
- /// The `rng.gen()` method is able to generate arrays (up to 32 elements)
- /// and tuples (up to 12 elements), so long as all element types can be
- /// generated.
- ///
- /// For arrays of integers, especially for those with small element types
- /// (< 64 bit), it will likely be faster to instead use [`Rng::fill`].
- ///
- /// ```
- /// use rand::{thread_rng, Rng};
- ///
- /// let mut rng = thread_rng();
- /// let tuple: (u8, i32, char) = rng.gen(); // arbitrary tuple support
- ///
- /// let arr1: [f32; 32] = rng.gen(); // array construction
- /// let mut arr2 = [0u8; 128];
- /// rng.fill(&mut arr2); // array fill
- /// ```
- ///
- /// [`Standard`]: distributions::Standard
- #[inline]
- fn gen<T>(&mut self) -> T
- where Standard: Distribution<T> {
- Standard.sample(self)
- }
-
- /// Generate a random value in the range [`low`, `high`), i.e. inclusive of
- /// `low` and exclusive of `high`.
- ///
- /// This function is optimised for the case that only a single sample is
- /// made from the given range. See also the [`Uniform`] distribution
- /// type which may be faster if sampling from the same range repeatedly.
- ///
- /// # Panics
- ///
- /// Panics if `low >= high`.
- ///
- /// # Example
- ///
- /// ```
- /// use rand::{thread_rng, Rng};
- ///
- /// let mut rng = thread_rng();
- /// let n: u32 = rng.gen_range(0, 10);
- /// println!("{}", n);
- /// let m: f64 = rng.gen_range(-40.0f64, 1.3e5f64);
- /// println!("{}", m);
- /// ```
- ///
- /// [`Uniform`]: distributions::uniform::Uniform
- fn gen_range<T: SampleUniform, B1, B2>(&mut self, low: B1, high: B2) -> T
- where
- B1: SampleBorrow<T> + Sized,
- B2: SampleBorrow<T> + Sized,
- {
- T::Sampler::sample_single(low, high, self)
- }
-
- /// Sample a new value, using the given distribution.
- ///
- /// ### Example
- ///
- /// ```
- /// use rand::{thread_rng, Rng};
- /// use rand::distributions::Uniform;
- ///
- /// let mut rng = thread_rng();
- /// let x = rng.sample(Uniform::new(10u32, 15));
- /// // Type annotation requires two types, the type and distribution; the
- /// // distribution can be inferred.
- /// let y = rng.sample::<u16, _>(Uniform::new(10, 15));
- /// ```
- fn sample<T, D: Distribution<T>>(&mut self, distr: D) -> T {
- distr.sample(self)
- }
-
- /// Create an iterator that generates values using the given distribution.
- ///
- /// Note that this function takes its arguments by value. This works since
- /// `(&mut R): Rng where R: Rng` and
- /// `(&D): Distribution where D: Distribution`,
- /// however borrowing is not automatic hence `rng.sample_iter(...)` may
- /// need to be replaced with `(&mut rng).sample_iter(...)`.
- ///
- /// # Example
- ///
- /// ```
- /// use rand::{thread_rng, Rng};
- /// use rand::distributions::{Alphanumeric, Uniform, Standard};
- ///
- /// let rng = thread_rng();
- ///
- /// // Vec of 16 x f32:
- /// let v: Vec<f32> = rng.sample_iter(Standard).take(16).collect();
- ///
- /// // String:
- /// let s: String = rng.sample_iter(Alphanumeric).take(7).collect();
- ///
- /// // Combined values
- /// println!("{:?}", rng.sample_iter(Standard).take(5)
- /// .collect::<Vec<(f64, bool)>>());
- ///
- /// // Dice-rolling:
- /// let die_range = Uniform::new_inclusive(1, 6);
- /// let mut roll_die = rng.sample_iter(die_range);
- /// while roll_die.next().unwrap() != 6 {
- /// println!("Not a 6; rolling again!");
- /// }
- /// ```
- fn sample_iter<T, D>(self, distr: D) -> distributions::DistIter<D, Self, T>
- where D: Distribution<T>, Self: Sized {
- distr.sample_iter(self)
- }
-
- /// Fill `dest` entirely with random bytes (uniform value distribution),
- /// where `dest` is any type supporting [`AsByteSliceMut`], namely slices
- /// and arrays over primitive integer types (`i8`, `i16`, `u32`, etc.).
- ///
- /// On big-endian platforms this performs byte-swapping to ensure
- /// portability of results from reproducible generators.
- ///
- /// This uses [`fill_bytes`] internally which may handle some RNG errors
- /// implicitly (e.g. waiting if the OS generator is not ready), but panics
- /// on other errors. See also [`try_fill`] which returns errors.
- ///
- /// # Example
- ///
- /// ```
- /// use rand::{thread_rng, Rng};
- ///
- /// let mut arr = [0i8; 20];
- /// thread_rng().fill(&mut arr[..]);
- /// ```
- ///
- /// [`fill_bytes`]: RngCore::fill_bytes
- /// [`try_fill`]: Rng::try_fill
- fn fill<T: AsByteSliceMut + ?Sized>(&mut self, dest: &mut T) {
- self.fill_bytes(dest.as_byte_slice_mut());
- dest.to_le();
- }
-
- /// Fill `dest` entirely with random bytes (uniform value distribution),
- /// where `dest` is any type supporting [`AsByteSliceMut`], namely slices
- /// and arrays over primitive integer types (`i8`, `i16`, `u32`, etc.).
- ///
- /// On big-endian platforms this performs byte-swapping to ensure
- /// portability of results from reproducible generators.
- ///
- /// This is identical to [`fill`] except that it uses [`try_fill_bytes`]
- /// internally and forwards RNG errors.
- ///
- /// # Example
- ///
- /// ```
- /// # use rand::Error;
- /// use rand::{thread_rng, Rng};
- ///
- /// # fn try_inner() -> Result<(), Error> {
- /// let mut arr = [0u64; 4];
- /// thread_rng().try_fill(&mut arr[..])?;
- /// # Ok(())
- /// # }
- ///
- /// # try_inner().unwrap()
- /// ```
- ///
- /// [`try_fill_bytes`]: RngCore::try_fill_bytes
- /// [`fill`]: Rng::fill
- fn try_fill<T: AsByteSliceMut + ?Sized>(&mut self, dest: &mut T) -> Result<(), Error> {
- self.try_fill_bytes(dest.as_byte_slice_mut())?;
- dest.to_le();
- Ok(())
- }
-
- /// Return a bool with a probability `p` of being true.
- ///
- /// See also the [`Bernoulli`] distribution, which may be faster if
- /// sampling from the same probability repeatedly.
- ///
- /// # Example
- ///
- /// ```
- /// use rand::{thread_rng, Rng};
- ///
- /// let mut rng = thread_rng();
- /// println!("{}", rng.gen_bool(1.0 / 3.0));
- /// ```
- ///
- /// # Panics
- ///
- /// If `p < 0` or `p > 1`.
- ///
- /// [`Bernoulli`]: distributions::bernoulli::Bernoulli
- #[inline]
- fn gen_bool(&mut self, p: f64) -> bool {
- let d = distributions::Bernoulli::new(p).unwrap();
- self.sample(d)
- }
-
- /// Return a bool with a probability of `numerator/denominator` of being
- /// true. I.e. `gen_ratio(2, 3)` has chance of 2 in 3, or about 67%, of
- /// returning true. If `numerator == denominator`, then the returned value
- /// is guaranteed to be `true`. If `numerator == 0`, then the returned
- /// value is guaranteed to be `false`.
- ///
- /// See also the [`Bernoulli`] distribution, which may be faster if
- /// sampling from the same `numerator` and `denominator` repeatedly.
- ///
- /// # Panics
- ///
- /// If `denominator == 0` or `numerator > denominator`.
- ///
- /// # Example
- ///
- /// ```
- /// use rand::{thread_rng, Rng};
- ///
- /// let mut rng = thread_rng();
- /// println!("{}", rng.gen_ratio(2, 3));
- /// ```
- ///
- /// [`Bernoulli`]: distributions::bernoulli::Bernoulli
- #[inline]
- fn gen_ratio(&mut self, numerator: u32, denominator: u32) -> bool {
- let d = distributions::Bernoulli::from_ratio(numerator, denominator).unwrap();
- self.sample(d)
- }
-}
-
-impl<R: RngCore + ?Sized> Rng for R {}
-
-/// Trait for casting types to byte slices
-///
-/// This is used by the [`Rng::fill`] and [`Rng::try_fill`] methods.
-pub trait AsByteSliceMut {
- /// Return a mutable reference to self as a byte slice
- fn as_byte_slice_mut(&mut self) -> &mut [u8];
-
- /// Call `to_le` on each element (i.e. byte-swap on Big Endian platforms).
- fn to_le(&mut self);
-}
-
-impl AsByteSliceMut for [u8] {
- fn as_byte_slice_mut(&mut self) -> &mut [u8] {
- self
- }
-
- fn to_le(&mut self) {}
-}
-
-macro_rules! impl_as_byte_slice {
- () => {};
- ($t:ty) => {
- impl AsByteSliceMut for [$t] {
- fn as_byte_slice_mut(&mut self) -> &mut [u8] {
- if self.len() == 0 {
- unsafe {
- // must not use null pointer
- slice::from_raw_parts_mut(0x1 as *mut u8, 0)
- }
- } else {
- unsafe {
- slice::from_raw_parts_mut(self.as_mut_ptr()
- as *mut u8,
- self.len() * mem::size_of::<$t>()
- )
- }
- }
- }
-
- fn to_le(&mut self) {
- for x in self {
- *x = x.to_le();
- }
- }
- }
-
- impl AsByteSliceMut for [Wrapping<$t>] {
- fn as_byte_slice_mut(&mut self) -> &mut [u8] {
- if self.len() == 0 {
- unsafe {
- // must not use null pointer
- slice::from_raw_parts_mut(0x1 as *mut u8, 0)
- }
- } else {
- unsafe {
- slice::from_raw_parts_mut(self.as_mut_ptr()
- as *mut u8,
- self.len() * mem::size_of::<$t>()
- )
- }
- }
- }
-
- fn to_le(&mut self) {
- for x in self {
- *x = Wrapping(x.0.to_le());
- }
- }
- }
- };
- ($t:ty, $($tt:ty,)*) => {
- impl_as_byte_slice!($t);
- // TODO: this could replace above impl once Rust #32463 is fixed
- // impl_as_byte_slice!(Wrapping<$t>);
- impl_as_byte_slice!($($tt,)*);
- }
-}
-
-impl_as_byte_slice!(u16, u32, u64, usize,);
-#[cfg(not(target_os = "emscripten"))] impl_as_byte_slice!(u128);
-impl_as_byte_slice!(i8, i16, i32, i64, isize,);
-#[cfg(not(target_os = "emscripten"))] impl_as_byte_slice!(i128);
-
-macro_rules! impl_as_byte_slice_arrays {
- ($n:expr,) => {};
- ($n:expr, $N:ident) => {
- impl<T> AsByteSliceMut for [T; $n] where [T]: AsByteSliceMut {
- fn as_byte_slice_mut(&mut self) -> &mut [u8] {
- self[..].as_byte_slice_mut()
- }
-
- fn to_le(&mut self) {
- self[..].to_le()
- }
- }
- };
- ($n:expr, $N:ident, $($NN:ident,)*) => {
- impl_as_byte_slice_arrays!($n, $N);
- impl_as_byte_slice_arrays!($n - 1, $($NN,)*);
- };
- (!div $n:expr,) => {};
- (!div $n:expr, $N:ident, $($NN:ident,)*) => {
- impl_as_byte_slice_arrays!($n, $N);
- impl_as_byte_slice_arrays!(!div $n / 2, $($NN,)*);
- };
-}
-impl_as_byte_slice_arrays!(32, N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,);
-impl_as_byte_slice_arrays!(!div 4096, N,N,N,N,N,N,N,);
-
-/// Generates a random value using the thread-local random number generator.
-///
-/// This is simply a shortcut for `thread_rng().gen()`. See [`thread_rng`] for
-/// documentation of the entropy source and [`Standard`] for documentation of
-/// distributions and type-specific generation.
-///
-/// # Examples
-///
-/// ```
-/// let x = rand::random::<u8>();
-/// println!("{}", x);
-///
-/// let y = rand::random::<f64>();
-/// println!("{}", y);
-///
-/// if rand::random() { // generates a boolean
-/// println!("Better lucky than good!");
-/// }
-/// ```
-///
-/// If you're calling `random()` in a loop, caching the generator as in the
-/// following example can increase performance.
-///
-/// ```
-/// use rand::Rng;
-///
-/// let mut v = vec![1, 2, 3];
-///
-/// for x in v.iter_mut() {
-/// *x = rand::random()
-/// }
-///
-/// // can be made faster by caching thread_rng
-///
-/// let mut rng = rand::thread_rng();
-///
-/// for x in v.iter_mut() {
-/// *x = rng.gen();
-/// }
-/// ```
-///
-/// [`Standard`]: distributions::Standard
-#[cfg(feature="std")]
-#[inline]
-pub fn random<T>() -> T
-where Standard: Distribution<T> {
- thread_rng().gen()
-}
-
-#[cfg(test)]
-mod test {
- use crate::rngs::mock::StepRng;
- use super::*;
- #[cfg(all(not(feature="std"), feature="alloc"))] use alloc::boxed::Box;
-
- /// Construct a deterministic RNG with the given seed
- pub fn rng(seed: u64) -> impl RngCore {
- // For tests, we want a statistically good, fast, reproducible RNG.
- // PCG32 will do fine, and will be easy to embed if we ever need to.
- const INC: u64 = 11634580027462260723;
- rand_pcg::Pcg32::new(seed, INC)
- }
-
- #[test]
- fn test_fill_bytes_default() {
- let mut r = StepRng::new(0x11_22_33_44_55_66_77_88, 0);
-
- // check every remainder mod 8, both in small and big vectors.
- let lengths = [0, 1, 2, 3, 4, 5, 6, 7,
- 80, 81, 82, 83, 84, 85, 86, 87];
- for &n in lengths.iter() {
- let mut buffer = [0u8; 87];
- let v = &mut buffer[0..n];
- r.fill_bytes(v);
-
- // use this to get nicer error messages.
- for (i, &byte) in v.iter().enumerate() {
- if byte == 0 {
- panic!("byte {} of {} is zero", i, n)
- }
- }
- }
- }
-
- #[test]
- fn test_fill() {
- let x = 9041086907909331047; // a random u64
- let mut rng = StepRng::new(x, 0);
-
- // Convert to byte sequence and back to u64; byte-swap twice if BE.
- let mut array = [0u64; 2];
- rng.fill(&mut array[..]);
- assert_eq!(array, [x, x]);
- assert_eq!(rng.next_u64(), x);
-
- // Convert to bytes then u32 in LE order
- let mut array = [0u32; 2];
- rng.fill(&mut array[..]);
- assert_eq!(array, [x as u32, (x >> 32) as u32]);
- assert_eq!(rng.next_u32(), x as u32);
-
- // Check equivalence using wrapped arrays
- let mut warray = [Wrapping(0u32); 2];
- rng.fill(&mut warray[..]);
- assert_eq!(array[0], warray[0].0);
- assert_eq!(array[1], warray[1].0);
- }
-
- #[test]
- fn test_fill_empty() {
- let mut array = [0u32; 0];
- let mut rng = StepRng::new(0, 1);
- rng.fill(&mut array);
- rng.fill(&mut array[..]);
- }
-
- #[test]
- fn test_gen_range() {
- let mut r = rng(101);
- for _ in 0..1000 {
- let a = r.gen_range(-4711, 17);
- assert!(a >= -4711 && a < 17);
- let a = r.gen_range(-3i8, 42);
- assert!(a >= -3i8 && a < 42i8);
- let a = r.gen_range(&10u16, 99);
- assert!(a >= 10u16 && a < 99u16);
- let a = r.gen_range(-100i32, &2000);
- assert!(a >= -100i32 && a < 2000i32);
- let a = r.gen_range(&12u32, &24u32);
- assert!(a >= 12u32 && a < 24u32);
-
- assert_eq!(r.gen_range(0u32, 1), 0u32);
- assert_eq!(r.gen_range(-12i64, -11), -12i64);
- assert_eq!(r.gen_range(3_000_000, 3_000_001), 3_000_000);
- }
- }
-
- #[test]
- #[should_panic]
- fn test_gen_range_panic_int() {
- let mut r = rng(102);
- r.gen_range(5, -2);
- }
-
- #[test]
- #[should_panic]
- fn test_gen_range_panic_usize() {
- let mut r = rng(103);
- r.gen_range(5, 2);
- }
-
- #[test]
- fn test_gen_bool() {
- let mut r = rng(105);
- for _ in 0..5 {
- assert_eq!(r.gen_bool(0.0), false);
- assert_eq!(r.gen_bool(1.0), true);
- }
- }
-
- #[test]
- fn test_rng_trait_object() {
- use crate::distributions::{Distribution, Standard};
- let mut rng = rng(109);
- let mut r = &mut rng as &mut dyn RngCore;
- r.next_u32();
- r.gen::<i32>();
- assert_eq!(r.gen_range(0, 1), 0);
- let _c: u8 = Standard.sample(&mut r);
- }
-
- #[test]
- #[cfg(feature="alloc")]
- fn test_rng_boxed_trait() {
- use crate::distributions::{Distribution, Standard};
- let rng = rng(110);
- let mut r = Box::new(rng) as Box<dyn RngCore>;
- r.next_u32();
- r.gen::<i32>();
- assert_eq!(r.gen_range(0, 1), 0);
- let _c: u8 = Standard.sample(&mut r);
- }
-
- #[test]
- #[cfg(feature="std")]
- fn test_random() {
- // not sure how to test this aside from just getting some values
- let _n : usize = random();
- let _f : f32 = random();
- let _o : Option<Option<i8>> = random();
- let _many : ((),
- (usize,
- isize,
- Option<(u32, (bool,))>),
- (u8, i8, u16, i16, u32, i32, u64, i64),
- (f32, (f64, (f64,)))) = random();
- }
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_gen_ratio_average() {
- const NUM: u32 = 3;
- const DENOM: u32 = 10;
- const N: u32 = 100_000;
-
- let mut sum: u32 = 0;
- let mut rng = rng(111);
- for _ in 0..N {
- if rng.gen_ratio(NUM, DENOM) {
- sum += 1;
- }
- }
- // Have Binomial(N, NUM/DENOM) distribution
- let expected = (NUM * N) / DENOM; // exact integer
- assert!(((sum - expected) as i32).abs() < 500);
- }
-}
diff --git a/rand/src/prelude.rs b/rand/src/prelude.rs
deleted file mode 100644
index 3c386e8..0000000
--- a/rand/src/prelude.rs
+++ /dev/null
@@ -1,28 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Convenience re-export of common members
-//!
-//! Like the standard library's prelude, this module simplifies importing of
-//! common items. Unlike the standard prelude, the contents of this module must
-//! be imported manually:
-//!
-//! ```
-//! use rand::prelude::*;
-//! # let mut r = StdRng::from_rng(thread_rng()).unwrap();
-//! # let _: f32 = r.gen();
-//! ```
-
-#[doc(no_inline)] pub use crate::distributions::Distribution;
-#[doc(no_inline)] pub use crate::rngs::StdRng;
-#[cfg(feature="small_rng")]
-#[doc(no_inline)] pub use crate::rngs::SmallRng;
-#[doc(no_inline)] #[cfg(feature="std")] pub use crate::rngs::ThreadRng;
-#[doc(no_inline)] pub use crate::{Rng, RngCore, CryptoRng, SeedableRng};
-#[doc(no_inline)] #[cfg(feature="std")] pub use crate::{random, thread_rng};
-#[doc(no_inline)] pub use crate::seq::{SliceRandom, IteratorRandom};
diff --git a/rand/src/rngs/adapter/mod.rs b/rand/src/rngs/adapter/mod.rs
deleted file mode 100644
index 659ff26..0000000
--- a/rand/src/rngs/adapter/mod.rs
+++ /dev/null
@@ -1,15 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Wrappers / adapters forming RNGs
-
-#[cfg(feature="std")] mod read;
-mod reseeding;
-
-#[cfg(feature="std")] pub use self::read::{ReadRng, ReadError};
-pub use self::reseeding::ReseedingRng;
diff --git a/rand/src/rngs/adapter/read.rs b/rand/src/rngs/adapter/read.rs
deleted file mode 100644
index 901462e..0000000
--- a/rand/src/rngs/adapter/read.rs
+++ /dev/null
@@ -1,148 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! A wrapper around any Read to treat it as an RNG.
-
-use std::io::Read;
-use std::fmt;
-
-use rand_core::{RngCore, Error, impls};
-
-
-/// An RNG that reads random bytes straight from any type supporting
-/// [`std::io::Read`], for example files.
-///
-/// This will work best with an infinite reader, but that is not required.
-///
-/// This can be used with `/dev/urandom` on Unix but it is recommended to use
-/// [`OsRng`] instead.
-///
-/// # Panics
-///
-/// `ReadRng` uses [`std::io::Read::read_exact`], which retries on interrupts.
-/// All other errors from the underlying reader, including when it does not
-/// have enough data, will only be reported through [`try_fill_bytes`].
-/// The other [`RngCore`] methods will panic in case of an error.
-///
-/// # Example
-///
-/// ```
-/// use rand::Rng;
-/// use rand::rngs::adapter::ReadRng;
-///
-/// let data = vec![1, 2, 3, 4, 5, 6, 7, 8];
-/// let mut rng = ReadRng::new(&data[..]);
-/// println!("{:x}", rng.gen::<u32>());
-/// ```
-///
-/// [`OsRng`]: crate::rngs::OsRng
-/// [`try_fill_bytes`]: RngCore::try_fill_bytes
-#[derive(Debug)]
-pub struct ReadRng<R> {
- reader: R
-}
-
-impl<R: Read> ReadRng<R> {
- /// Create a new `ReadRng` from a `Read`.
- pub fn new(r: R) -> ReadRng<R> {
- ReadRng {
- reader: r
- }
- }
-}
-
-impl<R: Read> RngCore for ReadRng<R> {
- fn next_u32(&mut self) -> u32 {
- impls::next_u32_via_fill(self)
- }
-
- fn next_u64(&mut self) -> u64 {
- impls::next_u64_via_fill(self)
- }
-
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- self.try_fill_bytes(dest).unwrap_or_else(|err|
- panic!("reading random bytes from Read implementation failed; error: {}", err));
- }
-
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- if dest.is_empty() { return Ok(()); }
- // Use `std::io::read_exact`, which retries on `ErrorKind::Interrupted`.
- self.reader.read_exact(dest).map_err(|e| Error::new(ReadError(e)))
- }
-}
-
-/// `ReadRng` error type
-#[derive(Debug)]
-pub struct ReadError(std::io::Error);
-
-impl fmt::Display for ReadError {
- fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
- write!(f, "ReadError: {}", self.0)
- }
-}
-
-impl std::error::Error for ReadError {
- fn source(&self) -> Option<&(dyn std::error::Error + 'static)> {
- Some(&self.0)
- }
-}
-
-
-#[cfg(test)]
-mod test {
- use super::ReadRng;
- use crate::RngCore;
-
- #[test]
- fn test_reader_rng_u64() {
- // transmute from the target to avoid endianness concerns.
- let v = vec![0u8, 0, 0, 0, 0, 0, 0, 1,
- 0 , 0, 0, 0, 0, 0, 0, 2,
- 0, 0, 0, 0, 0, 0, 0, 3];
- let mut rng = ReadRng::new(&v[..]);
-
- assert_eq!(rng.next_u64(), 1_u64.to_be());
- assert_eq!(rng.next_u64(), 2_u64.to_be());
- assert_eq!(rng.next_u64(), 3_u64.to_be());
- }
-
- #[test]
- fn test_reader_rng_u32() {
- let v = vec![0u8, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 3];
- let mut rng = ReadRng::new(&v[..]);
-
- assert_eq!(rng.next_u32(), 1_u32.to_be());
- assert_eq!(rng.next_u32(), 2_u32.to_be());
- assert_eq!(rng.next_u32(), 3_u32.to_be());
- }
-
- #[test]
- fn test_reader_rng_fill_bytes() {
- let v = [1u8, 2, 3, 4, 5, 6, 7, 8];
- let mut w = [0u8; 8];
-
- let mut rng = ReadRng::new(&v[..]);
- rng.fill_bytes(&mut w);
-
- assert!(v == w);
- }
-
- #[test]
- fn test_reader_rng_insufficient_bytes() {
- let v = [1u8, 2, 3, 4, 5, 6, 7, 8];
- let mut w = [0u8; 9];
-
- let mut rng = ReadRng::new(&v[..]);
-
- let result = rng.try_fill_bytes(&mut w);
- assert!(result.is_err());
- println!("Error: {}", result.unwrap_err());
- }
-}
diff --git a/rand/src/rngs/adapter/reseeding.rs b/rand/src/rngs/adapter/reseeding.rs
deleted file mode 100644
index ec88efe..0000000
--- a/rand/src/rngs/adapter/reseeding.rs
+++ /dev/null
@@ -1,357 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! A wrapper around another PRNG that reseeds it after it
-//! generates a certain number of random bytes.
-
-use core::mem::size_of;
-
-use rand_core::{RngCore, CryptoRng, SeedableRng, Error};
-use rand_core::block::{BlockRngCore, BlockRng};
-
-/// A wrapper around any PRNG that implements [`BlockRngCore`], that adds the
-/// ability to reseed it.
-///
-/// `ReseedingRng` reseeds the underlying PRNG in the following cases:
-///
-/// - On a manual call to [`reseed()`].
-/// - After `clone()`, the clone will be reseeded on first use.
-/// - After a process is forked, the RNG in the child process is reseeded within
-/// the next few generated values, depending on the block size of the
-/// underlying PRNG. For ChaCha and Hc128 this is a maximum of
-/// 15 `u32` values before reseeding.
-/// - After the PRNG has generated a configurable number of random bytes.
-///
-/// # When should reseeding after a fixed number of generated bytes be used?
-///
-/// Reseeding after a fixed number of generated bytes is never strictly
-/// *necessary*. Cryptographic PRNGs don't have a limited number of bytes they
-/// can output, or at least not a limit reachable in any practical way. There is
-/// no such thing as 'running out of entropy'.
-///
-/// Occasionally reseeding can be seen as some form of 'security in depth'. Even
-/// if in the future a cryptographic weakness is found in the CSPRNG being used,
-/// or a flaw in the implementation, occasionally reseeding should make
-/// exploiting it much more difficult or even impossible.
-///
-/// Use [`ReseedingRng::new`] with a `threshold` of `0` to disable reseeding
-/// after a fixed number of generated bytes.
-///
-/// # Error handling
-///
-/// Although unlikely, reseeding the wrapped PRNG can fail. `ReseedingRng` will
-/// never panic but try to handle the error intelligently through some
-/// combination of retrying and delaying reseeding until later.
-/// If handling the source error fails `ReseedingRng` will continue generating
-/// data from the wrapped PRNG without reseeding.
-///
-/// Manually calling [`reseed()`] will not have this retry or delay logic, but
-/// reports the error.
-///
-/// # Example
-///
-/// ```
-/// use rand::prelude::*;
-/// use rand_chacha::ChaCha20Core; // Internal part of ChaChaRng that
-/// // implements BlockRngCore
-/// use rand::rngs::OsRng;
-/// use rand::rngs::adapter::ReseedingRng;
-///
-/// let prng = ChaCha20Core::from_entropy();
-/// let mut reseeding_rng = ReseedingRng::new(prng, 0, OsRng);
-///
-/// println!("{}", reseeding_rng.gen::<u64>());
-///
-/// let mut cloned_rng = reseeding_rng.clone();
-/// assert!(reseeding_rng.gen::<u64>() != cloned_rng.gen::<u64>());
-/// ```
-///
-/// [`BlockRngCore`]: rand_core::block::BlockRngCore
-/// [`ReseedingRng::new`]: ReseedingRng::new
-/// [`reseed()`]: ReseedingRng::reseed
-#[derive(Debug)]
-pub struct ReseedingRng<R, Rsdr>(BlockRng<ReseedingCore<R, Rsdr>>)
-where R: BlockRngCore + SeedableRng,
- Rsdr: RngCore;
-
-impl<R, Rsdr> ReseedingRng<R, Rsdr>
-where R: BlockRngCore + SeedableRng,
- Rsdr: RngCore
-{
- /// Create a new `ReseedingRng` from an existing PRNG, combined with a RNG
- /// to use as reseeder.
- ///
- /// `threshold` sets the number of generated bytes after which to reseed the
- /// PRNG. Set it to zero to never reseed based on the number of generated
- /// values.
- pub fn new(rng: R, threshold: u64, reseeder: Rsdr) -> Self {
- ReseedingRng(BlockRng::new(ReseedingCore::new(rng, threshold, reseeder)))
- }
-
- /// Reseed the internal PRNG.
- pub fn reseed(&mut self) -> Result<(), Error> {
- self.0.core.reseed()
- }
-}
-
-// TODO: this should be implemented for any type where the inner type
-// implements RngCore, but we can't specify that because ReseedingCore is private
-impl<R, Rsdr: RngCore> RngCore for ReseedingRng<R, Rsdr>
-where R: BlockRngCore<Item = u32> + SeedableRng,
- <R as BlockRngCore>::Results: AsRef<[u32]> + AsMut<[u32]>
-{
- #[inline(always)]
- fn next_u32(&mut self) -> u32 {
- self.0.next_u32()
- }
-
- #[inline(always)]
- fn next_u64(&mut self) -> u64 {
- self.0.next_u64()
- }
-
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- self.0.fill_bytes(dest)
- }
-
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.0.try_fill_bytes(dest)
- }
-}
-
-impl<R, Rsdr> Clone for ReseedingRng<R, Rsdr>
-where R: BlockRngCore + SeedableRng + Clone,
- Rsdr: RngCore + Clone
-{
- fn clone(&self) -> ReseedingRng<R, Rsdr> {
- // Recreating `BlockRng` seems easier than cloning it and resetting
- // the index.
- ReseedingRng(BlockRng::new(self.0.core.clone()))
- }
-}
-
-impl<R, Rsdr> CryptoRng for ReseedingRng<R, Rsdr>
-where R: BlockRngCore + SeedableRng + CryptoRng,
- Rsdr: RngCore + CryptoRng {}
-
-#[derive(Debug)]
-struct ReseedingCore<R, Rsdr> {
- inner: R,
- reseeder: Rsdr,
- threshold: i64,
- bytes_until_reseed: i64,
- fork_counter: usize,
-}
-
-impl<R, Rsdr> BlockRngCore for ReseedingCore<R, Rsdr>
-where R: BlockRngCore + SeedableRng,
- Rsdr: RngCore
-{
- type Item = <R as BlockRngCore>::Item;
- type Results = <R as BlockRngCore>::Results;
-
- fn generate(&mut self, results: &mut Self::Results) {
- let global_fork_counter = fork::get_fork_counter();
- if self.bytes_until_reseed <= 0 ||
- self.is_forked(global_fork_counter) {
- // We get better performance by not calling only `reseed` here
- // and continuing with the rest of the function, but by directly
- // returning from a non-inlined function.
- return self.reseed_and_generate(results, global_fork_counter);
- }
- let num_bytes = results.as_ref().len() * size_of::<Self::Item>();
- self.bytes_until_reseed -= num_bytes as i64;
- self.inner.generate(results);
- }
-}
-
-impl<R, Rsdr> ReseedingCore<R, Rsdr>
-where R: BlockRngCore + SeedableRng,
- Rsdr: RngCore
-{
- /// Create a new `ReseedingCore`.
- fn new(rng: R, threshold: u64, reseeder: Rsdr) -> Self {
- use ::core::i64::MAX;
- fork::register_fork_handler();
-
- // Because generating more values than `i64::MAX` takes centuries on
- // current hardware, we just clamp to that value.
- // Also we set a threshold of 0, which indicates no limit, to that
- // value.
- let threshold =
- if threshold == 0 { MAX }
- else if threshold <= MAX as u64 { threshold as i64 }
- else { MAX };
-
- ReseedingCore {
- inner: rng,
- reseeder,
- threshold: threshold as i64,
- bytes_until_reseed: threshold as i64,
- fork_counter: 0,
- }
- }
-
- /// Reseed the internal PRNG.
- fn reseed(&mut self) -> Result<(), Error> {
- R::from_rng(&mut self.reseeder).map(|result| {
- self.bytes_until_reseed = self.threshold;
- self.inner = result
- })
- }
-
- fn is_forked(&self, global_fork_counter: usize) -> bool {
- // In theory, on 32-bit platforms, it is possible for
- // `global_fork_counter` to wrap around after ~4e9 forks.
- //
- // This check will detect a fork in the normal case where
- // `fork_counter < global_fork_counter`, and also when the difference
- // between both is greater than `isize::MAX` (wrapped around).
- //
- // It will still fail to detect a fork if there have been more than
- // `isize::MAX` forks, without any reseed in between. Seems unlikely
- // enough.
- (self.fork_counter.wrapping_sub(global_fork_counter) as isize) < 0
- }
-
- #[inline(never)]
- fn reseed_and_generate(&mut self,
- results: &mut <Self as BlockRngCore>::Results,
- global_fork_counter: usize)
- {
- #![allow(clippy::if_same_then_else)] // false positive
- if self.is_forked(global_fork_counter) {
- info!("Fork detected, reseeding RNG");
- } else {
- trace!("Reseeding RNG (periodic reseed)");
- }
-
- let num_bytes =
- results.as_ref().len() * size_of::<<R as BlockRngCore>::Item>();
-
- if let Err(e) = self.reseed() {
- warn!("Reseeding RNG failed: {}", e);
- let _ = e;
- }
- self.fork_counter = global_fork_counter;
-
- self.bytes_until_reseed = self.threshold - num_bytes as i64;
- self.inner.generate(results);
- }
-}
-
-impl<R, Rsdr> Clone for ReseedingCore<R, Rsdr>
-where R: BlockRngCore + SeedableRng + Clone,
- Rsdr: RngCore + Clone
-{
- fn clone(&self) -> ReseedingCore<R, Rsdr> {
- ReseedingCore {
- inner: self.inner.clone(),
- reseeder: self.reseeder.clone(),
- threshold: self.threshold,
- bytes_until_reseed: 0, // reseed clone on first use
- fork_counter: self.fork_counter,
- }
- }
-}
-
-impl<R, Rsdr> CryptoRng for ReseedingCore<R, Rsdr>
-where R: BlockRngCore + SeedableRng + CryptoRng,
- Rsdr: RngCore + CryptoRng {}
-
-
-#[cfg(all(unix, not(target_os="emscripten")))]
-mod fork {
- use core::sync::atomic::{AtomicUsize, AtomicBool, Ordering};
- #[allow(deprecated)] // Required for compatibility with Rust < 1.24.
- use core::sync::atomic::{ATOMIC_USIZE_INIT, ATOMIC_BOOL_INIT};
-
- // Fork protection
- //
- // We implement fork protection on Unix using `pthread_atfork`.
- // When the process is forked, we increment `RESEEDING_RNG_FORK_COUNTER`.
- // Every `ReseedingRng` stores the last known value of the static in
- // `fork_counter`. If the cached `fork_counter` is less than
- // `RESEEDING_RNG_FORK_COUNTER`, it is time to reseed this RNG.
- //
- // If reseeding fails, we don't deal with this by setting a delay, but just
- // don't update `fork_counter`, so a reseed is attempted as soon as
- // possible.
-
- #[allow(deprecated)]
- static RESEEDING_RNG_FORK_COUNTER: AtomicUsize = ATOMIC_USIZE_INIT;
-
- pub fn get_fork_counter() -> usize {
- RESEEDING_RNG_FORK_COUNTER.load(Ordering::Relaxed)
- }
-
- #[allow(deprecated)]
- static FORK_HANDLER_REGISTERED: AtomicBool = ATOMIC_BOOL_INIT;
-
- extern fn fork_handler() {
- // Note: fetch_add is defined to wrap on overflow
- // (which is what we want).
- RESEEDING_RNG_FORK_COUNTER.fetch_add(1, Ordering::Relaxed);
- }
-
- pub fn register_fork_handler() {
- if !FORK_HANDLER_REGISTERED.load(Ordering::Relaxed) {
- unsafe { libc::pthread_atfork(None, None, Some(fork_handler)) };
- FORK_HANDLER_REGISTERED.store(true, Ordering::Relaxed);
- }
- }
-}
-
-#[cfg(not(all(unix, not(target_os="emscripten"))))]
-mod fork {
- pub fn get_fork_counter() -> usize { 0 }
- pub fn register_fork_handler() {}
-}
-
-
-#[cfg(test)]
-mod test {
- use crate::{Rng, SeedableRng};
- use crate::rngs::std::Core;
- use crate::rngs::mock::StepRng;
- use super::ReseedingRng;
-
- #[test]
- fn test_reseeding() {
- let mut zero = StepRng::new(0, 0);
- let rng = Core::from_rng(&mut zero).unwrap();
- let thresh = 1; // reseed every time the buffer is exhausted
- let mut reseeding = ReseedingRng::new(rng, thresh, zero);
-
- // RNG buffer size is [u32; 64]
- // Debug is only implemented up to length 32 so use two arrays
- let mut buf = ([0u32; 32], [0u32; 32]);
- reseeding.fill(&mut buf.0);
- reseeding.fill(&mut buf.1);
- let seq = buf;
- for _ in 0..10 {
- reseeding.fill(&mut buf.0);
- reseeding.fill(&mut buf.1);
- assert_eq!(buf, seq);
- }
- }
-
- #[test]
- fn test_clone_reseeding() {
- let mut zero = StepRng::new(0, 0);
- let rng = Core::from_rng(&mut zero).unwrap();
- let mut rng1 = ReseedingRng::new(rng, 32*4, zero);
-
- let first: u32 = rng1.gen();
- for _ in 0..10 { let _ = rng1.gen::<u32>(); }
-
- let mut rng2 = rng1.clone();
- assert_eq!(first, rng2.gen::<u32>());
- }
-}
diff --git a/rand/src/rngs/entropy.rs b/rand/src/rngs/entropy.rs
deleted file mode 100644
index 1ed59ab..0000000
--- a/rand/src/rngs/entropy.rs
+++ /dev/null
@@ -1,76 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Entropy generator, or wrapper around external generators
-
-#![allow(deprecated)] // whole module is deprecated
-
-use rand_core::{RngCore, CryptoRng, Error};
-use crate::rngs::OsRng;
-
-/// An interface returning random data from external source(s), provided
-/// specifically for securely seeding algorithmic generators (PRNGs).
-///
-/// This is deprecated. It is suggested you use [`rngs::OsRng`] instead.
-///
-/// [`rngs::OsRng`]: crate::rngs::OsRng
-#[derive(Debug)]
-#[deprecated(since="0.7.0", note="use rngs::OsRng instead")]
-pub struct EntropyRng {
- source: OsRng,
-}
-
-impl EntropyRng {
- /// Create a new `EntropyRng`.
- ///
- /// This method will do no system calls or other initialization routines,
- /// those are done on first use. This is done to make `new` infallible,
- /// and `try_fill_bytes` the only place to report errors.
- pub fn new() -> Self {
- EntropyRng { source: OsRng }
- }
-}
-
-impl Default for EntropyRng {
- fn default() -> Self {
- EntropyRng::new()
- }
-}
-
-impl RngCore for EntropyRng {
- fn next_u32(&mut self) -> u32 {
- self.source.next_u32()
- }
-
- fn next_u64(&mut self) -> u64 {
- self.source.next_u64()
- }
-
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- self.source.fill_bytes(dest)
- }
-
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.source.try_fill_bytes(dest)
- }
-}
-
-impl CryptoRng for EntropyRng {}
-
-
-#[cfg(test)]
-mod test {
- use super::*;
-
- #[test]
- fn test_entropy() {
- let mut rng = EntropyRng::new();
- let n = (rng.next_u32() ^ rng.next_u32()).count_ones();
- assert!(n >= 2); // p(failure) approx 1e-7
- }
-}
diff --git a/rand/src/rngs/mock.rs b/rand/src/rngs/mock.rs
deleted file mode 100644
index b4081da..0000000
--- a/rand/src/rngs/mock.rs
+++ /dev/null
@@ -1,64 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Mock random number generator
-
-use rand_core::{RngCore, Error, impls};
-
-/// A simple implementation of `RngCore` for testing purposes.
-///
-/// This generates an arithmetic sequence (i.e. adds a constant each step)
-/// over a `u64` number, using wrapping arithmetic. If the increment is 0
-/// the generator yields a constant.
-///
-/// ```
-/// use rand::Rng;
-/// use rand::rngs::mock::StepRng;
-///
-/// let mut my_rng = StepRng::new(2, 1);
-/// let sample: [u64; 3] = my_rng.gen();
-/// assert_eq!(sample, [2, 3, 4]);
-/// ```
-#[derive(Debug, Clone)]
-pub struct StepRng {
- v: u64,
- a: u64,
-}
-
-impl StepRng {
- /// Create a `StepRng`, yielding an arithmetic sequence starting with
- /// `initial` and incremented by `increment` each time.
- pub fn new(initial: u64, increment: u64) -> Self {
- StepRng { v: initial, a: increment }
- }
-}
-
-impl RngCore for StepRng {
- #[inline]
- fn next_u32(&mut self) -> u32 {
- self.next_u64() as u32
- }
-
- #[inline]
- fn next_u64(&mut self) -> u64 {
- let result = self.v;
- self.v = self.v.wrapping_add(self.a);
- result
- }
-
- #[inline]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- impls::fill_bytes_via_next(self, dest);
- }
-
- #[inline]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.fill_bytes(dest);
- Ok(())
- }
-}
diff --git a/rand/src/rngs/mod.rs b/rand/src/rngs/mod.rs
deleted file mode 100644
index abf3243..0000000
--- a/rand/src/rngs/mod.rs
+++ /dev/null
@@ -1,119 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Random number generators and adapters
-//!
-//! ## Background: Random number generators (RNGs)
-//!
-//! Computers cannot produce random numbers from nowhere. We classify
-//! random number generators as follows:
-//!
-//! - "True" random number generators (TRNGs) use hard-to-predict data sources
-//! (e.g. the high-resolution parts of event timings and sensor jitter) to
-//! harvest random bit-sequences, apply algorithms to remove bias and
-//! estimate available entropy, then combine these bits into a byte-sequence
-//! or an entropy pool. This job is usually done by the operating system or
-//! a hardware generator (HRNG).
-//! - "Pseudo"-random number generators (PRNGs) use algorithms to transform a
-//! seed into a sequence of pseudo-random numbers. These generators can be
-//! fast and produce well-distributed unpredictable random numbers (or not).
-//! They are usually deterministic: given algorithm and seed, the output
-//! sequence can be reproduced. They have finite period and eventually loop;
-//! with many algorithms this period is fixed and can be proven sufficiently
-//! long, while others are chaotic and the period depends on the seed.
-//! - "Cryptographically secure" pseudo-random number generators (CSPRNGs)
-//! are the sub-set of PRNGs which are secure. Security of the generator
-//! relies both on hiding the internal state and using a strong algorithm.
-//!
-//! ## Traits and functionality
-//!
-//! All RNGs implement the [`RngCore`] trait, as a consequence of which the
-//! [`Rng`] extension trait is automatically implemented. Secure RNGs may
-//! additionally implement the [`CryptoRng`] trait.
-//!
-//! All PRNGs require a seed to produce their random number sequence. The
-//! [`SeedableRng`] trait provides three ways of constructing PRNGs:
-//!
-//! - `from_seed` accepts a type specific to the PRNG
-//! - `from_rng` allows a PRNG to be seeded from any other RNG
-//! - `seed_from_u64` allows any PRNG to be seeded from a `u64` insecurely
-//! - `from_entropy` securely seeds a PRNG from fresh entropy
-//!
-//! Use the [`rand_core`] crate when implementing your own RNGs.
-//!
-//! ## Our generators
-//!
-//! This crate provides several random number generators:
-//!
-//! - [`OsRng`] is an interface to the operating system's random number
-//! source. Typically the operating system uses a CSPRNG with entropy
-//! provided by a TRNG and some type of on-going re-seeding.
-//! - [`ThreadRng`], provided by the [`thread_rng`] function, is a handle to a
-//! thread-local CSPRNG with periodic seeding from [`OsRng`]. Because this
-//! is local, it is typically much faster than [`OsRng`]. It should be
-//! secure, though the paranoid may prefer [`OsRng`].
-//! - [`StdRng`] is a CSPRNG chosen for good performance and trust of security
-//! (based on reviews, maturity and usage). The current algorithm is ChaCha20,
-//! which is well established and rigorously analysed.
-//! [`StdRng`] provides the algorithm used by [`ThreadRng`] but without
-//! periodic reseeding.
-//! - [`SmallRng`] is an **insecure** PRNG designed to be fast, simple, require
-//! little memory, and have good output quality.
-//!
-//! The algorithms selected for [`StdRng`] and [`SmallRng`] may change in any
-//! release and may be platform-dependent, therefore they should be considered
-//! **not reproducible**.
-//!
-//! ## Additional generators
-//!
-//! **TRNGs**: The [`rdrand`] crate provides an interface to the RDRAND and
-//! RDSEED instructions available in modern Intel and AMD CPUs.
-//! The [`rand_jitter`] crate provides a user-space implementation of
-//! entropy harvesting from CPU timer jitter, but is very slow and has
-//! [security issues](https://github.com/rust-random/rand/issues/699).
-//!
-//! **PRNGs**: Several companion crates are available, providing individual or
-//! families of PRNG algorithms. These provide the implementations behind
-//! [`StdRng`] and [`SmallRng`] but can also be used directly, indeed *should*
-//! be used directly when **reproducibility** matters.
-//! Some suggestions are: [`rand_chacha`], [`rand_pcg`], [`rand_xoshiro`].
-//! A full list can be found by searching for crates with the [`rng` tag].
-//!
-//! [`SmallRng`]: rngs::SmallRng
-//! [`StdRng`]: rngs::StdRng
-//! [`OsRng`]: rngs::OsRng
-//! [`ThreadRng`]: rngs::ThreadRng
-//! [`mock::StepRng`]: rngs::mock::StepRng
-//! [`adapter::ReadRng`]: rngs::adapter::ReadRng
-//! [`adapter::ReseedingRng`]: rngs::adapter::ReseedingRng
-//! [`rdrand`]: https://crates.io/crates/rdrand
-//! [`rand_jitter`]: https://crates.io/crates/rand_jitter
-//! [`rand_chacha`]: https://crates.io/crates/rand_chacha
-//! [`rand_pcg`]: https://crates.io/crates/rand_pcg
-//! [`rand_xoshiro`]: https://crates.io/crates/rand_xoshiro
-//! [`rng` tag]: https://crates.io/keywords/rng
-
-pub mod adapter;
-
-#[cfg(feature="std")] mod entropy;
-pub mod mock; // Public so we don't export `StepRng` directly, making it a bit
- // more clear it is intended for testing.
-#[cfg(feature="small_rng")]
-mod small;
-mod std;
-#[cfg(feature="std")] pub(crate) mod thread;
-
-#[allow(deprecated)]
-#[cfg(feature="std")] pub use self::entropy::EntropyRng;
-
-#[cfg(feature="small_rng")]
-pub use self::small::SmallRng;
-pub use self::std::StdRng;
-#[cfg(feature="std")] pub use self::thread::ThreadRng;
-
-#[cfg(feature="getrandom")] pub use rand_core::OsRng;
diff --git a/rand/src/rngs/small.rs b/rand/src/rngs/small.rs
deleted file mode 100644
index 6571363..0000000
--- a/rand/src/rngs/small.rs
+++ /dev/null
@@ -1,115 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! A small fast RNG
-
-use rand_core::{RngCore, SeedableRng, Error};
-
-#[cfg(all(not(target_os = "emscripten"), target_pointer_width = "64"))]
-type Rng = rand_pcg::Pcg64Mcg;
-#[cfg(not(all(not(target_os = "emscripten"), target_pointer_width = "64")))]
-type Rng = rand_pcg::Pcg32;
-
-/// A small-state, fast non-crypto PRNG
-///
-/// `SmallRng` may be a good choice when a PRNG with small state, cheap
-/// initialization, good statistical quality and good performance are required.
-/// It is **not** a good choice when security against prediction or
-/// reproducibility are important.
-///
-/// This PRNG is **feature-gated**: to use, you must enable the crate feature
-/// `small_rng`.
-///
-/// The algorithm is deterministic but should not be considered reproducible
-/// due to dependence on platform and possible replacement in future
-/// library versions. For a reproducible generator, use a named PRNG from an
-/// external crate, e.g. [rand_pcg] or [rand_chacha].
-/// Refer also to [The Book](https://rust-random.github.io/book/guide-rngs.html).
-///
-/// The PRNG algorithm in `SmallRng` is chosen to be
-/// efficient on the current platform, without consideration for cryptography
-/// or security. The size of its state is much smaller than [`StdRng`].
-/// The current algorithm is [`Pcg64Mcg`](rand_pcg::Pcg64Mcg) on 64-bit
-/// platforms and [`Pcg32`](rand_pcg::Pcg32) on 32-bit platforms. Both are
-/// implemented by the [rand_pcg] crate.
-///
-/// # Examples
-///
-/// Initializing `SmallRng` with a random seed can be done using [`SeedableRng::from_entropy`]:
-///
-/// ```
-/// use rand::{Rng, SeedableRng};
-/// use rand::rngs::SmallRng;
-///
-/// // Create small, cheap to initialize and fast RNG with a random seed.
-/// // The randomness is supplied by the operating system.
-/// let mut small_rng = SmallRng::from_entropy();
-/// # let v: u32 = small_rng.gen();
-/// ```
-///
-/// When initializing a lot of `SmallRng`'s, using [`thread_rng`] can be more
-/// efficient:
-///
-/// ```
-/// use std::iter;
-/// use rand::{SeedableRng, thread_rng};
-/// use rand::rngs::SmallRng;
-///
-/// // Create a big, expensive to initialize and slower, but unpredictable RNG.
-/// // This is cached and done only once per thread.
-/// let mut thread_rng = thread_rng();
-/// // Create small, cheap to initialize and fast RNGs with random seeds.
-/// // One can generally assume this won't fail.
-/// let rngs: Vec<SmallRng> = iter::repeat(())
-/// .map(|()| SmallRng::from_rng(&mut thread_rng).unwrap())
-/// .take(10)
-/// .collect();
-/// ```
-///
-/// [`StdRng`]: crate::rngs::StdRng
-/// [`thread_rng`]: crate::thread_rng
-/// [rand_chacha]: https://crates.io/crates/rand_chacha
-/// [rand_pcg]: https://crates.io/crates/rand_pcg
-#[derive(Clone, Debug)]
-pub struct SmallRng(Rng);
-
-impl RngCore for SmallRng {
- #[inline(always)]
- fn next_u32(&mut self) -> u32 {
- self.0.next_u32()
- }
-
- #[inline(always)]
- fn next_u64(&mut self) -> u64 {
- self.0.next_u64()
- }
-
- #[inline(always)]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- self.0.fill_bytes(dest);
- }
-
- #[inline(always)]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.0.try_fill_bytes(dest)
- }
-}
-
-impl SeedableRng for SmallRng {
- type Seed = <Rng as SeedableRng>::Seed;
-
- #[inline(always)]
- fn from_seed(seed: Self::Seed) -> Self {
- SmallRng(Rng::from_seed(seed))
- }
-
- #[inline(always)]
- fn from_rng<R: RngCore>(rng: R) -> Result<Self, Error> {
- Rng::from_rng(rng).map(SmallRng)
- }
-}
diff --git a/rand/src/rngs/std.rs b/rand/src/rngs/std.rs
deleted file mode 100644
index 22e08ae..0000000
--- a/rand/src/rngs/std.rs
+++ /dev/null
@@ -1,100 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The standard RNG
-
-use crate::{RngCore, CryptoRng, Error, SeedableRng};
-
-#[cfg(target_os = "emscripten")] pub(crate) use rand_hc::Hc128Core as Core;
-#[cfg(not(target_os = "emscripten"))] pub(crate) use rand_chacha::ChaCha20Core as Core;
-#[cfg(target_os = "emscripten")] use rand_hc::Hc128Rng as Rng;
-#[cfg(not(target_os = "emscripten"))] use rand_chacha::ChaCha20Rng as Rng;
-
-/// The standard RNG. The PRNG algorithm in `StdRng` is chosen to be efficient
-/// on the current platform, to be statistically strong and unpredictable
-/// (meaning a cryptographically secure PRNG).
-///
-/// The current algorithm used is the ChaCha block cipher with either 20 or 12
-/// rounds (see the `stdrng_*` feature flags, documented in the README).
-/// This may change as new evidence of cipher security and performance
-/// becomes available.
-///
-/// The algorithm is deterministic but should not be considered reproducible
-/// due to dependence on configuration and possible replacement in future
-/// library versions. For a secure reproducible generator, we recommend use of
-/// the [rand_chacha] crate directly.
-///
-/// [rand_chacha]: https://crates.io/crates/rand_chacha
-#[derive(Clone, Debug)]
-pub struct StdRng(Rng);
-
-impl RngCore for StdRng {
- #[inline(always)]
- fn next_u32(&mut self) -> u32 {
- self.0.next_u32()
- }
-
- #[inline(always)]
- fn next_u64(&mut self) -> u64 {
- self.0.next_u64()
- }
-
- #[inline(always)]
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- self.0.fill_bytes(dest);
- }
-
- #[inline(always)]
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- self.0.try_fill_bytes(dest)
- }
-}
-
-impl SeedableRng for StdRng {
- type Seed = <Rng as SeedableRng>::Seed;
-
- #[inline(always)]
- fn from_seed(seed: Self::Seed) -> Self {
- StdRng(Rng::from_seed(seed))
- }
-
- #[inline(always)]
- fn from_rng<R: RngCore>(rng: R) -> Result<Self, Error> {
- Rng::from_rng(rng).map(StdRng)
- }
-}
-
-impl CryptoRng for StdRng {}
-
-
-#[cfg(test)]
-mod test {
- use crate::{RngCore, SeedableRng};
- use crate::rngs::StdRng;
-
- #[test]
- fn test_stdrng_construction() {
- // Test value-stability of StdRng. This is expected to break any time
- // the algorithm is changed.
- let seed = [1,0,0,0, 23,0,0,0, 200,1,0,0, 210,30,0,0,
- 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0];
-
- #[cfg(any(feature="stdrng_strong", not(feature="stdrng_fast")))]
- let target = [3950704604716924505, 5573172343717151650];
- #[cfg(all(not(feature="stdrng_strong"), feature="stdrng_fast"))]
- let target = [10719222850664546238, 14064965282130556830];
-
- let mut rng0 = StdRng::from_seed(seed);
- let x0 = rng0.next_u64();
-
- let mut rng1 = StdRng::from_rng(rng0).unwrap();
- let x1 = rng1.next_u64();
-
- assert_eq!([x0, x1], target);
- }
-}
diff --git a/rand/src/rngs/thread.rs b/rand/src/rngs/thread.rs
deleted file mode 100644
index 2006f41..0000000
--- a/rand/src/rngs/thread.rs
+++ /dev/null
@@ -1,124 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Thread-local random number generator
-
-use std::cell::UnsafeCell;
-use std::ptr::NonNull;
-
-use crate::{RngCore, CryptoRng, SeedableRng, Error};
-use crate::rngs::adapter::ReseedingRng;
-use crate::rngs::OsRng;
-use super::std::Core;
-
-// Rationale for using `UnsafeCell` in `ThreadRng`:
-//
-// Previously we used a `RefCell`, with an overhead of ~15%. There will only
-// ever be one mutable reference to the interior of the `UnsafeCell`, because
-// we only have such a reference inside `next_u32`, `next_u64`, etc. Within a
-// single thread (which is the definition of `ThreadRng`), there will only ever
-// be one of these methods active at a time.
-//
-// A possible scenario where there could be multiple mutable references is if
-// `ThreadRng` is used inside `next_u32` and co. But the implementation is
-// completely under our control. We just have to ensure none of them use
-// `ThreadRng` internally, which is nonsensical anyway. We should also never run
-// `ThreadRng` in destructors of its implementation, which is also nonsensical.
-
-
-// Number of generated bytes after which to reseed `ThreadRng`.
-// According to benchmarks, reseeding has a noticable impact with thresholds
-// of 32 kB and less. We choose 64 kB to avoid significant overhead.
-const THREAD_RNG_RESEED_THRESHOLD: u64 = 1024 * 64;
-
-/// The type returned by [`thread_rng`], essentially just a reference to the
-/// PRNG in thread-local memory.
-///
-/// `ThreadRng` uses the same PRNG as [`StdRng`] for security and performance.
-/// As hinted by the name, the generator is thread-local. `ThreadRng` is a
-/// handle to this generator and thus supports `Copy`, but not `Send` or `Sync`.
-///
-/// Unlike `StdRng`, `ThreadRng` uses the [`ReseedingRng`] wrapper to reseed
-/// the PRNG from fresh entropy every 64 kiB of random data.
-/// [`OsRng`] is used to provide seed data.
-///
-/// Note that the reseeding is done as an extra precaution against side-channel
-/// attacks and mis-use (e.g. if somehow weak entropy were supplied initially).
-/// The PRNG algorithms used are assumed to be secure.
-///
-/// [`ReseedingRng`]: crate::rngs::adapter::ReseedingRng
-/// [`StdRng`]: crate::rngs::StdRng
-#[derive(Copy, Clone, Debug)]
-pub struct ThreadRng {
- // inner raw pointer implies type is neither Send nor Sync
- rng: NonNull<ReseedingRng<Core, OsRng>>,
-}
-
-thread_local!(
- static THREAD_RNG_KEY: UnsafeCell<ReseedingRng<Core, OsRng>> = {
- let r = Core::from_rng(OsRng).unwrap_or_else(|err|
- panic!("could not initialize thread_rng: {}", err));
- let rng = ReseedingRng::new(r,
- THREAD_RNG_RESEED_THRESHOLD,
- OsRng);
- UnsafeCell::new(rng)
- }
-);
-
-/// Retrieve the lazily-initialized thread-local random number generator,
-/// seeded by the system. Intended to be used in method chaining style,
-/// e.g. `thread_rng().gen::<i32>()`, or cached locally, e.g.
-/// `let mut rng = thread_rng();`. Invoked by the `Default` trait, making
-/// `ThreadRng::default()` equivalent.
-///
-/// For more information see [`ThreadRng`].
-pub fn thread_rng() -> ThreadRng {
- let raw = THREAD_RNG_KEY.with(|t| t.get());
- let nn = NonNull::new(raw).unwrap();
- ThreadRng { rng: nn }
-}
-
-impl Default for ThreadRng {
- fn default() -> ThreadRng {
- crate::prelude::thread_rng()
- }
-}
-
-impl RngCore for ThreadRng {
- #[inline(always)]
- fn next_u32(&mut self) -> u32 {
- unsafe { self.rng.as_mut().next_u32() }
- }
-
- #[inline(always)]
- fn next_u64(&mut self) -> u64 {
- unsafe { self.rng.as_mut().next_u64() }
- }
-
- fn fill_bytes(&mut self, dest: &mut [u8]) {
- unsafe { self.rng.as_mut().fill_bytes(dest) }
- }
-
- fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
- unsafe { self.rng.as_mut().try_fill_bytes(dest) }
- }
-}
-
-impl CryptoRng for ThreadRng {}
-
-
-#[cfg(test)]
-mod test {
- #[test]
- fn test_thread_rng() {
- use crate::Rng;
- let mut r = crate::thread_rng();
- r.gen::<i32>();
- assert_eq!(r.gen_range(0, 1), 0);
- }
-}
diff --git a/rand/src/seq/index.rs b/rand/src/seq/index.rs
deleted file mode 100644
index 22a5733..0000000
--- a/rand/src/seq/index.rs
+++ /dev/null
@@ -1,409 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Low-level API for sampling indices
-
-#[cfg(feature="alloc")] use core::slice;
-
-#[cfg(feature="std")] use std::vec;
-#[cfg(all(feature="alloc", not(feature="std")))] use crate::alloc::vec::{self, Vec};
-// BTreeMap is not as fast in tests, but better than nothing.
-#[cfg(feature="std")] use std::collections::{HashSet};
-#[cfg(all(feature="alloc", not(feature="std")))] use crate::alloc::collections::BTreeSet;
-
-#[cfg(feature="alloc")] use crate::distributions::{Distribution, Uniform, uniform::SampleUniform};
-use crate::Rng;
-
-/// A vector of indices.
-///
-/// Multiple internal representations are possible.
-#[derive(Clone, Debug)]
-pub enum IndexVec {
- #[doc(hidden)] U32(Vec<u32>),
- #[doc(hidden)] USize(Vec<usize>),
-}
-
-impl IndexVec {
- /// Returns the number of indices
- #[inline]
- pub fn len(&self) -> usize {
- match *self {
- IndexVec::U32(ref v) => v.len(),
- IndexVec::USize(ref v) => v.len(),
- }
- }
-
- /// Returns `true` if the length is 0.
- #[inline]
- pub fn is_empty(&self) -> bool {
- match *self {
- IndexVec::U32(ref v) => v.is_empty(),
- IndexVec::USize(ref v) => v.is_empty(),
- }
- }
-
- /// Return the value at the given `index`.
- ///
- /// (Note: we cannot implement [`std::ops::Index`] because of lifetime
- /// restrictions.)
- #[inline]
- pub fn index(&self, index: usize) -> usize {
- match *self {
- IndexVec::U32(ref v) => v[index] as usize,
- IndexVec::USize(ref v) => v[index],
- }
- }
-
- /// Return result as a `Vec<usize>`. Conversion may or may not be trivial.
- #[inline]
- pub fn into_vec(self) -> Vec<usize> {
- match self {
- IndexVec::U32(v) => v.into_iter().map(|i| i as usize).collect(),
- IndexVec::USize(v) => v,
- }
- }
-
- /// Iterate over the indices as a sequence of `usize` values
- #[inline]
- pub fn iter(&self) -> IndexVecIter<'_> {
- match *self {
- IndexVec::U32(ref v) => IndexVecIter::U32(v.iter()),
- IndexVec::USize(ref v) => IndexVecIter::USize(v.iter()),
- }
- }
-
- /// Convert into an iterator over the indices as a sequence of `usize` values
- #[inline]
- pub fn into_iter(self) -> IndexVecIntoIter {
- match self {
- IndexVec::U32(v) => IndexVecIntoIter::U32(v.into_iter()),
- IndexVec::USize(v) => IndexVecIntoIter::USize(v.into_iter()),
- }
- }
-}
-
-impl PartialEq for IndexVec {
- fn eq(&self, other: &IndexVec) -> bool {
- use self::IndexVec::*;
- match (self, other) {
- (&U32(ref v1), &U32(ref v2)) => v1 == v2,
- (&USize(ref v1), &USize(ref v2)) => v1 == v2,
- (&U32(ref v1), &USize(ref v2)) => (v1.len() == v2.len())
- && (v1.iter().zip(v2.iter()).all(|(x, y)| *x as usize == *y)),
- (&USize(ref v1), &U32(ref v2)) => (v1.len() == v2.len())
- && (v1.iter().zip(v2.iter()).all(|(x, y)| *x == *y as usize)),
- }
- }
-}
-
-impl From<Vec<u32>> for IndexVec {
- #[inline]
- fn from(v: Vec<u32>) -> Self {
- IndexVec::U32(v)
- }
-}
-
-impl From<Vec<usize>> for IndexVec {
- #[inline]
- fn from(v: Vec<usize>) -> Self {
- IndexVec::USize(v)
- }
-}
-
-/// Return type of `IndexVec::iter`.
-#[derive(Debug)]
-pub enum IndexVecIter<'a> {
- #[doc(hidden)] U32(slice::Iter<'a, u32>),
- #[doc(hidden)] USize(slice::Iter<'a, usize>),
-}
-
-impl<'a> Iterator for IndexVecIter<'a> {
- type Item = usize;
- #[inline]
- fn next(&mut self) -> Option<usize> {
- use self::IndexVecIter::*;
- match *self {
- U32(ref mut iter) => iter.next().map(|i| *i as usize),
- USize(ref mut iter) => iter.next().cloned(),
- }
- }
-
- #[inline]
- fn size_hint(&self) -> (usize, Option<usize>) {
- match *self {
- IndexVecIter::U32(ref v) => v.size_hint(),
- IndexVecIter::USize(ref v) => v.size_hint(),
- }
- }
-}
-
-impl<'a> ExactSizeIterator for IndexVecIter<'a> {}
-
-/// Return type of `IndexVec::into_iter`.
-#[derive(Clone, Debug)]
-pub enum IndexVecIntoIter {
- #[doc(hidden)] U32(vec::IntoIter<u32>),
- #[doc(hidden)] USize(vec::IntoIter<usize>),
-}
-
-impl Iterator for IndexVecIntoIter {
- type Item = usize;
-
- #[inline]
- fn next(&mut self) -> Option<Self::Item> {
- use self::IndexVecIntoIter::*;
- match *self {
- U32(ref mut v) => v.next().map(|i| i as usize),
- USize(ref mut v) => v.next(),
- }
- }
-
- #[inline]
- fn size_hint(&self) -> (usize, Option<usize>) {
- use self::IndexVecIntoIter::*;
- match *self {
- U32(ref v) => v.size_hint(),
- USize(ref v) => v.size_hint(),
- }
- }
-}
-
-impl ExactSizeIterator for IndexVecIntoIter {}
-
-
-/// Randomly sample exactly `amount` distinct indices from `0..length`, and
-/// return them in random order (fully shuffled).
-///
-/// This method is used internally by the slice sampling methods, but it can
-/// sometimes be useful to have the indices themselves so this is provided as
-/// an alternative.
-///
-/// The implementation used is not specified; we automatically select the
-/// fastest available algorithm for the `length` and `amount` parameters
-/// (based on detailed profiling on an Intel Haswell CPU). Roughly speaking,
-/// complexity is `O(amount)`, except that when `amount` is small, performance
-/// is closer to `O(amount^2)`, and when `length` is close to `amount` then
-/// `O(length)`.
-///
-/// Note that performance is significantly better over `u32` indices than over
-/// `u64` indices. Because of this we hide the underlying type behind an
-/// abstraction, `IndexVec`.
-///
-/// If an allocation-free `no_std` function is required, it is suggested
-/// to adapt the internal `sample_floyd` implementation.
-///
-/// Panics if `amount > length`.
-pub fn sample<R>(rng: &mut R, length: usize, amount: usize) -> IndexVec
-where R: Rng + ?Sized {
- if amount > length {
- panic!("`amount` of samples must be less than or equal to `length`");
- }
- if length > (::core::u32::MAX as usize) {
- // We never want to use inplace here, but could use floyd's alg
- // Lazy version: always use the cache alg.
- return sample_rejection(rng, length, amount);
- }
- let amount = amount as u32;
- let length = length as u32;
-
- // Choice of algorithm here depends on both length and amount. See:
- // https://github.com/rust-random/rand/pull/479
- // We do some calculations with f32. Accuracy is not very important.
-
- if amount < 163 {
- const C: [[f32; 2]; 2] = [[1.6, 8.0/45.0], [10.0, 70.0/9.0]];
- let j = if length < 500_000 { 0 } else { 1 };
- let amount_fp = amount as f32;
- let m4 = C[0][j] * amount_fp;
- // Short-cut: when amount < 12, floyd's is always faster
- if amount > 11 && (length as f32) < (C[1][j] + m4) * amount_fp {
- sample_inplace(rng, length, amount)
- } else {
- sample_floyd(rng, length, amount)
- }
- } else {
- const C: [f32; 2] = [270.0, 330.0/9.0];
- let j = if length < 500_000 { 0 } else { 1 };
- if (length as f32) < C[j] * (amount as f32) {
- sample_inplace(rng, length, amount)
- } else {
- sample_rejection(rng, length, amount)
- }
- }
-}
-
-/// Randomly sample exactly `amount` indices from `0..length`, using Floyd's
-/// combination algorithm.
-///
-/// The output values are fully shuffled. (Overhead is under 50%.)
-///
-/// This implementation uses `O(amount)` memory and `O(amount^2)` time.
-fn sample_floyd<R>(rng: &mut R, length: u32, amount: u32) -> IndexVec
-where R: Rng + ?Sized {
- // For small amount we use Floyd's fully-shuffled variant. For larger
- // amounts this is slow due to Vec::insert performance, so we shuffle
- // afterwards. Benchmarks show little overhead from extra logic.
- let floyd_shuffle = amount < 50;
-
- debug_assert!(amount <= length);
- let mut indices = Vec::with_capacity(amount as usize);
- for j in length - amount .. length {
- let t = rng.gen_range(0, j + 1);
- if floyd_shuffle {
- if let Some(pos) = indices.iter().position(|&x| x == t) {
- indices.insert(pos, j);
- continue;
- }
- } else if indices.contains(&t) {
- indices.push(j);
- continue;
- }
- indices.push(t);
- }
- if !floyd_shuffle {
- // Reimplement SliceRandom::shuffle with smaller indices
- for i in (1..amount).rev() {
- // invariant: elements with index > i have been locked in place.
- indices.swap(i as usize, rng.gen_range(0, i + 1) as usize);
- }
- }
- IndexVec::from(indices)
-}
-
-/// Randomly sample exactly `amount` indices from `0..length`, using an inplace
-/// partial Fisher-Yates method.
-/// Sample an amount of indices using an inplace partial fisher yates method.
-///
-/// This allocates the entire `length` of indices and randomizes only the first `amount`.
-/// It then truncates to `amount` and returns.
-///
-/// This method is not appropriate for large `length` and potentially uses a lot
-/// of memory; because of this we only implement for `u32` index (which improves
-/// performance in all cases).
-///
-/// Set-up is `O(length)` time and memory and shuffling is `O(amount)` time.
-fn sample_inplace<R>(rng: &mut R, length: u32, amount: u32) -> IndexVec
-where R: Rng + ?Sized {
- debug_assert!(amount <= length);
- let mut indices: Vec<u32> = Vec::with_capacity(length as usize);
- indices.extend(0..length);
- for i in 0..amount {
- let j: u32 = rng.gen_range(i, length);
- indices.swap(i as usize, j as usize);
- }
- indices.truncate(amount as usize);
- debug_assert_eq!(indices.len(), amount as usize);
- IndexVec::from(indices)
-}
-
-trait UInt: Copy + PartialOrd + Ord + PartialEq + Eq + SampleUniform + core::hash::Hash {
- fn zero() -> Self;
- fn as_usize(self) -> usize;
-}
-impl UInt for u32 {
- #[inline] fn zero() -> Self { 0 }
- #[inline] fn as_usize(self) -> usize { self as usize }
-}
-impl UInt for usize {
- #[inline] fn zero() -> Self { 0 }
- #[inline] fn as_usize(self) -> usize { self }
-}
-
-/// Randomly sample exactly `amount` indices from `0..length`, using rejection
-/// sampling.
-///
-/// Since `amount <<< length` there is a low chance of a random sample in
-/// `0..length` being a duplicate. We test for duplicates and resample where
-/// necessary. The algorithm is `O(amount)` time and memory.
-///
-/// This function is generic over X primarily so that results are value-stable
-/// over 32-bit and 64-bit platforms.
-fn sample_rejection<X: UInt, R>(rng: &mut R, length: X, amount: X) -> IndexVec
-where R: Rng + ?Sized, IndexVec: From<Vec<X>> {
- debug_assert!(amount < length);
- #[cfg(feature="std")] let mut cache = HashSet::with_capacity(amount.as_usize());
- #[cfg(not(feature="std"))] let mut cache = BTreeSet::new();
- let distr = Uniform::new(X::zero(), length);
- let mut indices = Vec::with_capacity(amount.as_usize());
- for _ in 0..amount.as_usize() {
- let mut pos = distr.sample(rng);
- while !cache.insert(pos) {
- pos = distr.sample(rng);
- }
- indices.push(pos);
- }
-
- debug_assert_eq!(indices.len(), amount.as_usize());
- IndexVec::from(indices)
-}
-
-#[cfg(test)]
-mod test {
- #[cfg(feature="std")] use std::vec;
- #[cfg(all(feature="alloc", not(feature="std")))] use crate::alloc::vec;
- use super::*;
-
- #[test]
- fn test_sample_boundaries() {
- let mut r = crate::test::rng(404);
-
- assert_eq!(sample_inplace(&mut r, 0, 0).len(), 0);
- assert_eq!(sample_inplace(&mut r, 1, 0).len(), 0);
- assert_eq!(sample_inplace(&mut r, 1, 1).into_vec(), vec![0]);
-
- assert_eq!(sample_rejection(&mut r, 1u32, 0).len(), 0);
-
- assert_eq!(sample_floyd(&mut r, 0, 0).len(), 0);
- assert_eq!(sample_floyd(&mut r, 1, 0).len(), 0);
- assert_eq!(sample_floyd(&mut r, 1, 1).into_vec(), vec![0]);
-
- // These algorithms should be fast with big numbers. Test average.
- let sum: usize = sample_rejection(&mut r, 1 << 25, 10u32)
- .into_iter().sum();
- assert!(1 << 25 < sum && sum < (1 << 25) * 25);
-
- let sum: usize = sample_floyd(&mut r, 1 << 25, 10)
- .into_iter().sum();
- assert!(1 << 25 < sum && sum < (1 << 25) * 25);
- }
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_sample_alg() {
- let seed_rng = crate::test::rng;
-
- // We can't test which algorithm is used directly, but Floyd's alg
- // should produce different results from the others. (Also, `inplace`
- // and `cached` currently use different sizes thus produce different results.)
-
- // A small length and relatively large amount should use inplace
- let (length, amount): (usize, usize) = (100, 50);
- let v1 = sample(&mut seed_rng(420), length, amount);
- let v2 = sample_inplace(&mut seed_rng(420), length as u32, amount as u32);
- assert!(v1.iter().all(|e| e < length));
- assert_eq!(v1, v2);
-
- // Test Floyd's alg does produce different results
- let v3 = sample_floyd(&mut seed_rng(420), length as u32, amount as u32);
- assert!(v1 != v3);
-
- // A large length and small amount should use Floyd
- let (length, amount): (usize, usize) = (1<<20, 50);
- let v1 = sample(&mut seed_rng(421), length, amount);
- let v2 = sample_floyd(&mut seed_rng(421), length as u32, amount as u32);
- assert!(v1.iter().all(|e| e < length));
- assert_eq!(v1, v2);
-
- // A large length and larger amount should use cache
- let (length, amount): (usize, usize) = (1<<20, 600);
- let v1 = sample(&mut seed_rng(422), length, amount);
- let v2 = sample_rejection(&mut seed_rng(422), length as u32, amount as u32);
- assert!(v1.iter().all(|e| e < length));
- assert_eq!(v1, v2);
- }
-}
diff --git a/rand/src/seq/mod.rs b/rand/src/seq/mod.rs
deleted file mode 100644
index cec9bb1..0000000
--- a/rand/src/seq/mod.rs
+++ /dev/null
@@ -1,791 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Sequence-related functionality
-//!
-//! This module provides:
-//!
-//! * [`seq::SliceRandom`] slice sampling and mutation
-//! * [`seq::IteratorRandom`] iterator sampling
-//! * [`seq::index::sample`] low-level API to choose multiple indices from
-//! `0..length`
-//!
-//! Also see:
-//!
-//! * [`distributions::weighted`] module which provides implementations of
-//! weighted index sampling.
-//!
-//! In order to make results reproducible across 32-64 bit architectures, all
-//! `usize` indices are sampled as a `u32` where possible (also providing a
-//! small performance boost in some cases).
-
-
-#[cfg(feature="alloc")] pub mod index;
-
-#[cfg(feature="alloc")] use core::ops::Index;
-
-#[cfg(all(feature="alloc", not(feature="std")))] use crate::alloc::vec::Vec;
-
-use crate::Rng;
-#[cfg(feature="alloc")] use crate::distributions::WeightedError;
-#[cfg(feature="alloc")] use crate::distributions::uniform::{SampleUniform, SampleBorrow};
-
-/// Extension trait on slices, providing random mutation and sampling methods.
-///
-/// This trait is implemented on all `[T]` slice types, providing several
-/// methods for choosing and shuffling elements. You must `use` this trait:
-///
-/// ```
-/// use rand::seq::SliceRandom;
-///
-/// fn main() {
-/// let mut rng = rand::thread_rng();
-/// let mut bytes = "Hello, random!".to_string().into_bytes();
-/// bytes.shuffle(&mut rng);
-/// let str = String::from_utf8(bytes).unwrap();
-/// println!("{}", str);
-/// }
-/// ```
-/// Example output (non-deterministic):
-/// ```none
-/// l,nmroHado !le
-/// ```
-pub trait SliceRandom {
- /// The element type.
- type Item;
-
- /// Returns a reference to one random element of the slice, or `None` if the
- /// slice is empty.
- ///
- /// For slices, complexity is `O(1)`.
- ///
- /// # Example
- ///
- /// ```
- /// use rand::thread_rng;
- /// use rand::seq::SliceRandom;
- ///
- /// let choices = [1, 2, 4, 8, 16, 32];
- /// let mut rng = thread_rng();
- /// println!("{:?}", choices.choose(&mut rng));
- /// assert_eq!(choices[..0].choose(&mut rng), None);
- /// ```
- fn choose<R>(&self, rng: &mut R) -> Option<&Self::Item>
- where R: Rng + ?Sized;
-
- /// Returns a mutable reference to one random element of the slice, or
- /// `None` if the slice is empty.
- ///
- /// For slices, complexity is `O(1)`.
- fn choose_mut<R>(&mut self, rng: &mut R) -> Option<&mut Self::Item>
- where R: Rng + ?Sized;
-
- /// Chooses `amount` elements from the slice at random, without repetition,
- /// and in random order. The returned iterator is appropriate both for
- /// collection into a `Vec` and filling an existing buffer (see example).
- ///
- /// In case this API is not sufficiently flexible, use [`index::sample`].
- ///
- /// For slices, complexity is the same as [`index::sample`].
- ///
- /// # Example
- /// ```
- /// use rand::seq::SliceRandom;
- ///
- /// let mut rng = &mut rand::thread_rng();
- /// let sample = "Hello, audience!".as_bytes();
- ///
- /// // collect the results into a vector:
- /// let v: Vec<u8> = sample.choose_multiple(&mut rng, 3).cloned().collect();
- ///
- /// // store in a buffer:
- /// let mut buf = [0u8; 5];
- /// for (b, slot) in sample.choose_multiple(&mut rng, buf.len()).zip(buf.iter_mut()) {
- /// *slot = *b;
- /// }
- /// ```
- #[cfg(feature = "alloc")]
- fn choose_multiple<R>(&self, rng: &mut R, amount: usize) -> SliceChooseIter<Self, Self::Item>
- where R: Rng + ?Sized;
-
- /// Similar to [`choose`], but where the likelihood of each outcome may be
- /// specified.
- ///
- /// The specified function `weight` maps each item `x` to a relative
- /// likelihood `weight(x)`. The probability of each item being selected is
- /// therefore `weight(x) / s`, where `s` is the sum of all `weight(x)`.
- ///
- /// For slices of length `n`, complexity is `O(n)`.
- /// See also [`choose_weighted_mut`], [`distributions::weighted`].
- ///
- /// # Example
- ///
- /// ```
- /// use rand::prelude::*;
- ///
- /// let choices = [('a', 2), ('b', 1), ('c', 1)];
- /// let mut rng = thread_rng();
- /// // 50% chance to print 'a', 25% chance to print 'b', 25% chance to print 'c'
- /// println!("{:?}", choices.choose_weighted(&mut rng, |item| item.1).unwrap().0);
- /// ```
- /// [`choose`]: SliceRandom::choose
- /// [`choose_weighted_mut`]: SliceRandom::choose_weighted_mut
- /// [`distributions::weighted`]: crate::distributions::weighted
- #[cfg(feature = "alloc")]
- fn choose_weighted<R, F, B, X>(
- &self, rng: &mut R, weight: F,
- ) -> Result<&Self::Item, WeightedError>
- where
- R: Rng + ?Sized,
- F: Fn(&Self::Item) -> B,
- B: SampleBorrow<X>,
- X: SampleUniform
- + for<'a> ::core::ops::AddAssign<&'a X>
- + ::core::cmp::PartialOrd<X>
- + Clone
- + Default;
-
- /// Similar to [`choose_mut`], but where the likelihood of each outcome may
- /// be specified.
- ///
- /// The specified function `weight` maps each item `x` to a relative
- /// likelihood `weight(x)`. The probability of each item being selected is
- /// therefore `weight(x) / s`, where `s` is the sum of all `weight(x)`.
- ///
- /// For slices of length `n`, complexity is `O(n)`.
- /// See also [`choose_weighted`], [`distributions::weighted`].
- ///
- /// [`choose_mut`]: SliceRandom::choose_mut
- /// [`choose_weighted`]: SliceRandom::choose_weighted
- /// [`distributions::weighted`]: crate::distributions::weighted
- #[cfg(feature = "alloc")]
- fn choose_weighted_mut<R, F, B, X>(
- &mut self, rng: &mut R, weight: F,
- ) -> Result<&mut Self::Item, WeightedError>
- where
- R: Rng + ?Sized,
- F: Fn(&Self::Item) -> B,
- B: SampleBorrow<X>,
- X: SampleUniform
- + for<'a> ::core::ops::AddAssign<&'a X>
- + ::core::cmp::PartialOrd<X>
- + Clone
- + Default;
-
- /// Shuffle a mutable slice in place.
- ///
- /// For slices of length `n`, complexity is `O(n)`.
- ///
- /// # Example
- ///
- /// ```
- /// use rand::seq::SliceRandom;
- /// use rand::thread_rng;
- ///
- /// let mut rng = thread_rng();
- /// let mut y = [1, 2, 3, 4, 5];
- /// println!("Unshuffled: {:?}", y);
- /// y.shuffle(&mut rng);
- /// println!("Shuffled: {:?}", y);
- /// ```
- fn shuffle<R>(&mut self, rng: &mut R)
- where R: Rng + ?Sized;
-
- /// Shuffle a slice in place, but exit early.
- ///
- /// Returns two mutable slices from the source slice. The first contains
- /// `amount` elements randomly permuted. The second has the remaining
- /// elements that are not fully shuffled.
- ///
- /// This is an efficient method to select `amount` elements at random from
- /// the slice, provided the slice may be mutated.
- ///
- /// If you only need to choose elements randomly and `amount > self.len()/2`
- /// then you may improve performance by taking
- /// `amount = values.len() - amount` and using only the second slice.
- ///
- /// If `amount` is greater than the number of elements in the slice, this
- /// will perform a full shuffle.
- ///
- /// For slices, complexity is `O(m)` where `m = amount`.
- fn partial_shuffle<R>(
- &mut self, rng: &mut R, amount: usize,
- ) -> (&mut [Self::Item], &mut [Self::Item])
- where R: Rng + ?Sized;
-}
-
-/// Extension trait on iterators, providing random sampling methods.
-///
-/// This trait is implemented on all sized iterators, providing methods for
-/// choosing one or more elements. You must `use` this trait:
-///
-/// ```
-/// use rand::seq::IteratorRandom;
-///
-/// fn main() {
-/// let mut rng = rand::thread_rng();
-///
-/// let faces = "πππππ π’";
-/// println!("I am {}!", faces.chars().choose(&mut rng).unwrap());
-/// }
-/// ```
-/// Example output (non-deterministic):
-/// ```none
-/// I am π!
-/// ```
-pub trait IteratorRandom: Iterator + Sized {
- /// Choose one element at random from the iterator.
- ///
- /// Returns `None` if and only if the iterator is empty.
- ///
- /// This method uses [`Iterator::size_hint`] for optimisation. With an
- /// accurate hint and where [`Iterator::nth`] is a constant-time operation
- /// this method can offer `O(1)` performance. Where no size hint is
- /// available, complexity is `O(n)` where `n` is the iterator length.
- /// Partial hints (where `lower > 0`) also improve performance.
- ///
- /// For slices, prefer [`SliceRandom::choose`] which guarantees `O(1)`
- /// performance.
- fn choose<R>(mut self, rng: &mut R) -> Option<Self::Item>
- where R: Rng + ?Sized {
- let (mut lower, mut upper) = self.size_hint();
- let mut consumed = 0;
- let mut result = None;
-
- if upper == Some(lower) {
- return if lower == 0 { None } else { self.nth(gen_index(rng, lower)) };
- }
-
- // Continue until the iterator is exhausted
- loop {
- if lower > 1 {
- let ix = gen_index(rng, lower + consumed);
- let skip = if ix < lower {
- result = self.nth(ix);
- lower - (ix + 1)
- } else {
- lower
- };
- if upper == Some(lower) {
- return result;
- }
- consumed += lower;
- if skip > 0 {
- self.nth(skip - 1);
- }
- } else {
- let elem = self.next();
- if elem.is_none() {
- return result;
- }
- consumed += 1;
- let denom = consumed as f64; // accurate to 2^53 elements
- if rng.gen_bool(1.0 / denom) {
- result = elem;
- }
- }
-
- let hint = self.size_hint();
- lower = hint.0;
- upper = hint.1;
- }
- }
-
- /// Collects values at random from the iterator into a supplied buffer
- /// until that buffer is filled.
- ///
- /// Although the elements are selected randomly, the order of elements in
- /// the buffer is neither stable nor fully random. If random ordering is
- /// desired, shuffle the result.
- ///
- /// Returns the number of elements added to the buffer. This equals the length
- /// of the buffer unless the iterator contains insufficient elements, in which
- /// case this equals the number of elements available.
- ///
- /// Complexity is `O(n)` where `n` is the length of the iterator.
- /// For slices, prefer [`SliceRandom::choose_multiple`].
- fn choose_multiple_fill<R>(mut self, rng: &mut R, buf: &mut [Self::Item]) -> usize
- where R: Rng + ?Sized {
- let amount = buf.len();
- let mut len = 0;
- while len < amount {
- if let Some(elem) = self.next() {
- buf[len] = elem;
- len += 1;
- } else {
- // Iterator exhausted; stop early
- return len;
- }
- }
-
- // Continue, since the iterator was not exhausted
- for (i, elem) in self.enumerate() {
- let k = gen_index(rng, i + 1 + amount);
- if let Some(slot) = buf.get_mut(k) {
- *slot = elem;
- }
- }
- len
- }
-
- /// Collects `amount` values at random from the iterator into a vector.
- ///
- /// This is equivalent to `choose_multiple_fill` except for the result type.
- ///
- /// Although the elements are selected randomly, the order of elements in
- /// the buffer is neither stable nor fully random. If random ordering is
- /// desired, shuffle the result.
- ///
- /// The length of the returned vector equals `amount` unless the iterator
- /// contains insufficient elements, in which case it equals the number of
- /// elements available.
- ///
- /// Complexity is `O(n)` where `n` is the length of the iterator.
- /// For slices, prefer [`SliceRandom::choose_multiple`].
- #[cfg(feature = "alloc")]
- fn choose_multiple<R>(mut self, rng: &mut R, amount: usize) -> Vec<Self::Item>
- where R: Rng + ?Sized {
- let mut reservoir = Vec::with_capacity(amount);
- reservoir.extend(self.by_ref().take(amount));
-
- // Continue unless the iterator was exhausted
- //
- // note: this prevents iterators that "restart" from causing problems.
- // If the iterator stops once, then so do we.
- if reservoir.len() == amount {
- for (i, elem) in self.enumerate() {
- let k = gen_index(rng, i + 1 + amount);
- if let Some(slot) = reservoir.get_mut(k) {
- *slot = elem;
- }
- }
- } else {
- // Don't hang onto extra memory. There is a corner case where
- // `amount` was much less than `self.len()`.
- reservoir.shrink_to_fit();
- }
- reservoir
- }
-}
-
-
-impl<T> SliceRandom for [T] {
- type Item = T;
-
- fn choose<R>(&self, rng: &mut R) -> Option<&Self::Item>
- where R: Rng + ?Sized {
- if self.is_empty() {
- None
- } else {
- Some(&self[gen_index(rng, self.len())])
- }
- }
-
- fn choose_mut<R>(&mut self, rng: &mut R) -> Option<&mut Self::Item>
- where R: Rng + ?Sized {
- if self.is_empty() {
- None
- } else {
- let len = self.len();
- Some(&mut self[gen_index(rng, len)])
- }
- }
-
- #[cfg(feature = "alloc")]
- fn choose_multiple<R>(&self, rng: &mut R, amount: usize) -> SliceChooseIter<Self, Self::Item>
- where R: Rng + ?Sized {
- let amount = ::core::cmp::min(amount, self.len());
- SliceChooseIter {
- slice: self,
- _phantom: Default::default(),
- indices: index::sample(rng, self.len(), amount).into_iter(),
- }
- }
-
- #[cfg(feature = "alloc")]
- fn choose_weighted<R, F, B, X>(
- &self, rng: &mut R, weight: F,
- ) -> Result<&Self::Item, WeightedError>
- where
- R: Rng + ?Sized,
- F: Fn(&Self::Item) -> B,
- B: SampleBorrow<X>,
- X: SampleUniform
- + for<'a> ::core::ops::AddAssign<&'a X>
- + ::core::cmp::PartialOrd<X>
- + Clone
- + Default,
- {
- use crate::distributions::{Distribution, WeightedIndex};
- let distr = WeightedIndex::new(self.iter().map(weight))?;
- Ok(&self[distr.sample(rng)])
- }
-
- #[cfg(feature = "alloc")]
- fn choose_weighted_mut<R, F, B, X>(
- &mut self, rng: &mut R, weight: F,
- ) -> Result<&mut Self::Item, WeightedError>
- where
- R: Rng + ?Sized,
- F: Fn(&Self::Item) -> B,
- B: SampleBorrow<X>,
- X: SampleUniform
- + for<'a> ::core::ops::AddAssign<&'a X>
- + ::core::cmp::PartialOrd<X>
- + Clone
- + Default,
- {
- use crate::distributions::{Distribution, WeightedIndex};
- let distr = WeightedIndex::new(self.iter().map(weight))?;
- Ok(&mut self[distr.sample(rng)])
- }
-
- fn shuffle<R>(&mut self, rng: &mut R)
- where R: Rng + ?Sized {
- for i in (1..self.len()).rev() {
- // invariant: elements with index > i have been locked in place.
- self.swap(i, gen_index(rng, i + 1));
- }
- }
-
- fn partial_shuffle<R>(
- &mut self, rng: &mut R, amount: usize,
- ) -> (&mut [Self::Item], &mut [Self::Item])
- where R: Rng + ?Sized {
- // This applies Durstenfeld's algorithm for the
- // [FisherβYates shuffle](https://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle#The_modern_algorithm)
- // for an unbiased permutation, but exits early after choosing `amount`
- // elements.
-
- let len = self.len();
- let end = if amount >= len { 0 } else { len - amount };
-
- for i in (end..len).rev() {
- // invariant: elements with index > i have been locked in place.
- self.swap(i, gen_index(rng, i + 1));
- }
- let r = self.split_at_mut(end);
- (r.1, r.0)
- }
-}
-
-impl<I> IteratorRandom for I where I: Iterator + Sized {}
-
-
-/// An iterator over multiple slice elements.
-///
-/// This struct is created by
-/// [`SliceRandom::choose_multiple`](trait.SliceRandom.html#tymethod.choose_multiple).
-#[cfg(feature = "alloc")]
-#[derive(Debug)]
-pub struct SliceChooseIter<'a, S: ?Sized + 'a, T: 'a> {
- slice: &'a S,
- _phantom: ::core::marker::PhantomData<T>,
- indices: index::IndexVecIntoIter,
-}
-
-#[cfg(feature = "alloc")]
-impl<'a, S: Index<usize, Output = T> + ?Sized + 'a, T: 'a> Iterator for SliceChooseIter<'a, S, T> {
- type Item = &'a T;
-
- fn next(&mut self) -> Option<Self::Item> {
- // TODO: investigate using SliceIndex::get_unchecked when stable
- self.indices.next().map(|i| &self.slice[i as usize])
- }
-
- fn size_hint(&self) -> (usize, Option<usize>) {
- (self.indices.len(), Some(self.indices.len()))
- }
-}
-
-#[cfg(feature = "alloc")]
-impl<'a, S: Index<usize, Output = T> + ?Sized + 'a, T: 'a> ExactSizeIterator
- for SliceChooseIter<'a, S, T>
-{
- fn len(&self) -> usize {
- self.indices.len()
- }
-}
-
-
-// Sample a number uniformly between 0 and `ubound`. Uses 32-bit sampling where
-// possible, primarily in order to produce the same output on 32-bit and 64-bit
-// platforms.
-#[inline]
-fn gen_index<R: Rng + ?Sized>(rng: &mut R, ubound: usize) -> usize {
- if ubound <= (core::u32::MAX as usize) {
- rng.gen_range(0, ubound as u32) as usize
- } else {
- rng.gen_range(0, ubound)
- }
-}
-
-
-#[cfg(test)]
-mod test {
- use super::*;
- #[cfg(feature = "alloc")] use crate::Rng;
- #[cfg(all(feature="alloc", not(feature="std")))]
- use alloc::vec::Vec;
-
- #[test]
- fn test_slice_choose() {
- let mut r = crate::test::rng(107);
- let chars = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n'];
- let mut chosen = [0i32; 14];
- // The below all use a binomial distribution with n=1000, p=1/14.
- // binocdf(40, 1000, 1/14) ~= 2e-5; 1-binocdf(106, ..) ~= 2e-5
- for _ in 0..1000 {
- let picked = *chars.choose(&mut r).unwrap();
- chosen[(picked as usize) - ('a' as usize)] += 1;
- }
- for count in chosen.iter() {
- assert!(40 < *count && *count < 106);
- }
-
- chosen.iter_mut().for_each(|x| *x = 0);
- for _ in 0..1000 {
- *chosen.choose_mut(&mut r).unwrap() += 1;
- }
- for count in chosen.iter() {
- assert!(40 < *count && *count < 106);
- }
-
- let mut v: [isize; 0] = [];
- assert_eq!(v.choose(&mut r), None);
- assert_eq!(v.choose_mut(&mut r), None);
- }
-
- #[derive(Clone)]
- struct UnhintedIterator<I: Iterator + Clone> {
- iter: I,
- }
- impl<I: Iterator + Clone> Iterator for UnhintedIterator<I> {
- type Item = I::Item;
- fn next(&mut self) -> Option<Self::Item> {
- self.iter.next()
- }
- }
-
- #[derive(Clone)]
- struct ChunkHintedIterator<I: ExactSizeIterator + Iterator + Clone> {
- iter: I,
- chunk_remaining: usize,
- chunk_size: usize,
- hint_total_size: bool,
- }
- impl<I: ExactSizeIterator + Iterator + Clone> Iterator for ChunkHintedIterator<I> {
- type Item = I::Item;
- fn next(&mut self) -> Option<Self::Item> {
- if self.chunk_remaining == 0 {
- self.chunk_remaining = ::core::cmp::min(self.chunk_size,
- self.iter.len());
- }
- self.chunk_remaining = self.chunk_remaining.saturating_sub(1);
-
- self.iter.next()
- }
- fn size_hint(&self) -> (usize, Option<usize>) {
- (self.chunk_remaining,
- if self.hint_total_size { Some(self.iter.len()) } else { None })
- }
- }
-
- #[derive(Clone)]
- struct WindowHintedIterator<I: ExactSizeIterator + Iterator + Clone> {
- iter: I,
- window_size: usize,
- hint_total_size: bool,
- }
- impl<I: ExactSizeIterator + Iterator + Clone> Iterator for WindowHintedIterator<I> {
- type Item = I::Item;
- fn next(&mut self) -> Option<Self::Item> {
- self.iter.next()
- }
- fn size_hint(&self) -> (usize, Option<usize>) {
- (::core::cmp::min(self.iter.len(), self.window_size),
- if self.hint_total_size { Some(self.iter.len()) } else { None })
- }
- }
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_iterator_choose() {
- let r = &mut crate::test::rng(109);
- fn test_iter<R: Rng + ?Sized, Iter: Iterator<Item=usize> + Clone>(r: &mut R, iter: Iter) {
- let mut chosen = [0i32; 9];
- for _ in 0..1000 {
- let picked = iter.clone().choose(r).unwrap();
- chosen[picked] += 1;
- }
- for count in chosen.iter() {
- // Samples should follow Binomial(1000, 1/9)
- // Octave: binopdf(x, 1000, 1/9) gives the prob of *count == x
- // Note: have seen 153, which is unlikely but not impossible.
- assert!(72 < *count && *count < 154, "count not close to 1000/9: {}", count);
- }
- }
-
- test_iter(r, 0..9);
- test_iter(r, [0, 1, 2, 3, 4, 5, 6, 7, 8].iter().cloned());
- #[cfg(feature = "alloc")]
- test_iter(r, (0..9).collect::<Vec<_>>().into_iter());
- test_iter(r, UnhintedIterator { iter: 0..9 });
- test_iter(r, ChunkHintedIterator { iter: 0..9, chunk_size: 4, chunk_remaining: 4, hint_total_size: false });
- test_iter(r, ChunkHintedIterator { iter: 0..9, chunk_size: 4, chunk_remaining: 4, hint_total_size: true });
- test_iter(r, WindowHintedIterator { iter: 0..9, window_size: 2, hint_total_size: false });
- test_iter(r, WindowHintedIterator { iter: 0..9, window_size: 2, hint_total_size: true });
-
- assert_eq!((0..0).choose(r), None);
- assert_eq!(UnhintedIterator{ iter: 0..0 }.choose(r), None);
- }
-
- #[test]
- #[cfg(not(miri))] // Miri is too slow
- fn test_shuffle() {
- let mut r = crate::test::rng(108);
- let empty: &mut [isize] = &mut [];
- empty.shuffle(&mut r);
- let mut one = [1];
- one.shuffle(&mut r);
- let b: &[_] = &[1];
- assert_eq!(one, b);
-
- let mut two = [1, 2];
- two.shuffle(&mut r);
- assert!(two == [1, 2] || two == [2, 1]);
-
- fn move_last(slice: &mut [usize], pos: usize) {
- // use slice[pos..].rotate_left(1); once we can use that
- let last_val = slice[pos];
- for i in pos..slice.len() - 1 {
- slice[i] = slice[i + 1];
- }
- *slice.last_mut().unwrap() = last_val;
- }
- let mut counts = [0i32; 24];
- for _ in 0..10000 {
- let mut arr: [usize; 4] = [0, 1, 2, 3];
- arr.shuffle(&mut r);
- let mut permutation = 0usize;
- let mut pos_value = counts.len();
- for i in 0..4 {
- pos_value /= 4 - i;
- let pos = arr.iter().position(|&x| x == i).unwrap();
- assert!(pos < (4 - i));
- permutation += pos * pos_value;
- move_last(&mut arr, pos);
- assert_eq!(arr[3], i);
- }
- for i in 0..4 {
- assert_eq!(arr[i], i);
- }
- counts[permutation] += 1;
- }
- for count in counts.iter() {
- // Binomial(10000, 1/24) with average 416.667
- // Octave: binocdf(n, 10000, 1/24)
- // 99.9% chance samples lie within this range:
- assert!(352 <= *count && *count <= 483, "count: {}", count);
- }
- }
-
- #[test]
- fn test_partial_shuffle() {
- let mut r = crate::test::rng(118);
-
- let mut empty: [u32; 0] = [];
- let res = empty.partial_shuffle(&mut r, 10);
- assert_eq!((res.0.len(), res.1.len()), (0, 0));
-
- let mut v = [1, 2, 3, 4, 5];
- let res = v.partial_shuffle(&mut r, 2);
- assert_eq!((res.0.len(), res.1.len()), (2, 3));
- assert!(res.0[0] != res.0[1]);
- // First elements are only modified if selected, so at least one isn't modified:
- assert!(res.1[0] == 1 || res.1[1] == 2 || res.1[2] == 3);
- }
-
- #[test]
- #[cfg(feature = "alloc")]
- fn test_sample_iter() {
- let min_val = 1;
- let max_val = 100;
-
- let mut r = crate::test::rng(401);
- let vals = (min_val..max_val).collect::<Vec<i32>>();
- let small_sample = vals.iter().choose_multiple(&mut r, 5);
- let large_sample = vals.iter().choose_multiple(&mut r, vals.len() + 5);
-
- assert_eq!(small_sample.len(), 5);
- assert_eq!(large_sample.len(), vals.len());
- // no randomization happens when amount >= len
- assert_eq!(large_sample, vals.iter().collect::<Vec<_>>());
-
- assert!(small_sample.iter().all(|e| {
- **e >= min_val && **e <= max_val
- }));
- }
-
- #[test]
- #[cfg(feature = "alloc")]
- #[cfg(not(miri))] // Miri is too slow
- fn test_weighted() {
- let mut r = crate::test::rng(406);
- const N_REPS: u32 = 3000;
- let weights = [1u32, 2, 3, 0, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7];
- let total_weight = weights.iter().sum::<u32>() as f32;
-
- let verify = |result: [i32; 14]| {
- for (i, count) in result.iter().enumerate() {
- let exp = (weights[i] * N_REPS) as f32 / total_weight;
- let mut err = (*count as f32 - exp).abs();
- if err != 0.0 {
- err /= exp;
- }
- assert!(err <= 0.25);
- }
- };
-
- // choose_weighted
- fn get_weight<T>(item: &(u32, T)) -> u32 {
- item.0
- }
- let mut chosen = [0i32; 14];
- let mut items = [(0u32, 0usize); 14]; // (weight, index)
- for (i, item) in items.iter_mut().enumerate() {
- *item = (weights[i], i);
- }
- for _ in 0..N_REPS {
- let item = items.choose_weighted(&mut r, get_weight).unwrap();
- chosen[item.1] += 1;
- }
- verify(chosen);
-
- // choose_weighted_mut
- let mut items = [(0u32, 0i32); 14]; // (weight, count)
- for (i, item) in items.iter_mut().enumerate() {
- *item = (weights[i], 0);
- }
- for _ in 0..N_REPS {
- items.choose_weighted_mut(&mut r, get_weight).unwrap().1 += 1;
- }
- for (ch, item) in chosen.iter_mut().zip(items.iter()) {
- *ch = item.1;
- }
- verify(chosen);
-
- // Check error cases
- let empty_slice = &mut [10][0..0];
- assert_eq!(empty_slice.choose_weighted(&mut r, |_| 1), Err(WeightedError::NoItem));
- assert_eq!(empty_slice.choose_weighted_mut(&mut r, |_| 1), Err(WeightedError::NoItem));
- assert_eq!(['x'].choose_weighted_mut(&mut r, |_| 0), Err(WeightedError::AllWeightsZero));
- assert_eq!([0, -1].choose_weighted_mut(&mut r, |x| *x), Err(WeightedError::InvalidWeight));
- assert_eq!([-1, 0].choose_weighted_mut(&mut r, |x| *x), Err(WeightedError::InvalidWeight));
- }
-}
diff --git a/rand/tests/wasm_bindgen/Cargo.toml b/rand/tests/wasm_bindgen/Cargo.toml
deleted file mode 100644
index e83c174..0000000
--- a/rand/tests/wasm_bindgen/Cargo.toml
+++ /dev/null
@@ -1,16 +0,0 @@
-[package]
-name = "rand_wasm_bindgen_test"
-description = "Minimal crate to test that rand can be build for web assembly target"
-version = "0.1.0"
-authors = ["The Rand Project Developers"]
-publish = false
-license = "MIT OR Apache-2.0"
-edition = "2018"
-
-[lib]
-crate-type = ["cdylib"]
-
-[dependencies]
-rand = { path = "../..", features = ["wasm-bindgen"] }
-wasm-bindgen = "0.2"
-wasm-bindgen-test = "0.2"
diff --git a/rand/tests/wasm_bindgen/js/index.js b/rand/tests/wasm_bindgen/js/index.js
deleted file mode 100644
index a02fb59..0000000
--- a/rand/tests/wasm_bindgen/js/index.js
+++ /dev/null
@@ -1,7 +0,0 @@
-'use strict';
-
-const rand_wasm_bindgen_test = require('./rand_wasm_bindgen_test');
-
-console.log(rand_wasm_bindgen_test.generate_from_entropy());
-console.log(rand_wasm_bindgen_test.generate_from_os_rand());
-console.log(rand_wasm_bindgen_test.generate_from_seed());
diff --git a/rand/tests/wasm_bindgen/src/lib.rs b/rand/tests/wasm_bindgen/src/lib.rs
deleted file mode 100644
index 9af0b9e..0000000
--- a/rand/tests/wasm_bindgen/src/lib.rs
+++ /dev/null
@@ -1,49 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-// Crate to test WASM with the `wasm-bindgen` lib.
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png")]
-
-use rand::rngs::{OsRng, StdRng};
-use rand::{Rng, SeedableRng};
-use wasm_bindgen::prelude::*;
-
-#[wasm_bindgen]
-pub fn generate_from_seed(seed: u32) -> i32 {
- StdRng::seed_from_u64(seed as u64).gen()
-}
-
-#[wasm_bindgen]
-pub fn generate_from_os_rand() -> i32 {
- OsRng.gen()
-}
-
-#[wasm_bindgen]
-pub fn generate_from_entropy() -> i32 {
- StdRng::from_entropy().gen()
-}
-
-pub mod tests {
- use wasm_bindgen_test::*;
-
- #[wasm_bindgen_test]
- fn generate_from_seed() {
- let _ = super::generate_from_seed(42);
- }
-
- #[wasm_bindgen_test]
- fn generate_from_os_rand() {
- let _ = super::generate_from_os_rand();
- }
-
- #[wasm_bindgen_test]
- fn generate_from_entropy() {
- let _ = super::generate_from_entropy();
- }
-}
diff --git a/rand/utils/ci/install.sh b/rand/utils/ci/install.sh
deleted file mode 100644
index 8e636e1..0000000
--- a/rand/utils/ci/install.sh
+++ /dev/null
@@ -1,49 +0,0 @@
-# From https://github.com/japaric/trust
-
-set -ex
-
-main() {
- local target=
- if [ $TRAVIS_OS_NAME = linux ]; then
- target=x86_64-unknown-linux-musl
- sort=sort
- else
- target=x86_64-apple-darwin
- sort=gsort # for `sort --sort-version`, from brew's coreutils.
- fi
-
- # Builds for iOS are done on OSX, but require the specific target to be
- # installed.
- case $TARGET in
- aarch64-apple-ios)
- rustup target install aarch64-apple-ios
- ;;
- armv7-apple-ios)
- rustup target install armv7-apple-ios
- ;;
- armv7s-apple-ios)
- rustup target install armv7s-apple-ios
- ;;
- i386-apple-ios)
- rustup target install i386-apple-ios
- ;;
- x86_64-apple-ios)
- rustup target install x86_64-apple-ios
- ;;
- esac
-
- # This fetches latest stable release
- local tag=$(git ls-remote --tags --refs --exit-code https://github.com/japaric/cross \
- | cut -d/ -f3 \
- | grep -E '^v[0.1.0-9.]+$' \
- | $sort --version-sort \
- | tail -n1)
- curl -LSfs https://japaric.github.io/trust/install.sh | \
- sh -s -- \
- --force \
- --git japaric/cross \
- --tag $tag \
- --target $target
-}
-
-main
diff --git a/rand/utils/ci/install_cargo_web.sh b/rand/utils/ci/install_cargo_web.sh
deleted file mode 100755
index b35f069..0000000
--- a/rand/utils/ci/install_cargo_web.sh
+++ /dev/null
@@ -1,15 +0,0 @@
-#!/bin/bash
-
-set -euo pipefail
-IFS=$'\n\t'
-
-CARGO_WEB_RELEASE=$(curl -L -s -H 'Accept: application/json' https://github.com/koute/cargo-web/releases/latest)
-CARGO_WEB_VERSION=$(echo $CARGO_WEB_RELEASE | sed -e 's/.*"tag_name":"\([^"]*\)".*/\1/')
-CARGO_WEB_URL="https://github.com/koute/cargo-web/releases/download/$CARGO_WEB_VERSION/cargo-web-x86_64-unknown-linux-gnu.gz"
-
-echo "Downloading cargo-web from: $CARGO_WEB_URL"
-curl -L $CARGO_WEB_URL | gzip -d > cargo-web
-chmod +x cargo-web
-
-mkdir -p ~/.cargo/bin
-mv cargo-web ~/.cargo/bin
diff --git a/rand/utils/ci/miri.sh b/rand/utils/ci/miri.sh
deleted file mode 100644
index 209adf2..0000000
--- a/rand/utils/ci/miri.sh
+++ /dev/null
@@ -1,23 +0,0 @@
-set -ex
-
-MIRI_NIGHTLY=nightly-$(curl -s https://rust-lang.github.io/rustup-components-history/x86_64-unknown-linux-gnu/miri)
-echo "Installing latest nightly with Miri: $MIRI_NIGHTLY"
-rustup default "$MIRI_NIGHTLY"
-
-rustup component add miri
-cargo miri setup
-
-cargo miri test --no-default-features -- -- -Zunstable-options --exclude-should-panic
-cargo miri test --features=log -- -- -Zunstable-options --exclude-should-panic
-cargo miri test --manifest-path rand_core/Cargo.toml
-cargo miri test --manifest-path rand_core/Cargo.toml --features=serde1
-cargo miri test --manifest-path rand_core/Cargo.toml --no-default-features
-#cargo miri test --manifest-path rand_distr/Cargo.toml # no unsafe and lots of slow tests
-cargo miri test --manifest-path rand_isaac/Cargo.toml --features=serde1
-cargo miri test --manifest-path rand_pcg/Cargo.toml --features=serde1
-cargo miri test --manifest-path rand_xorshift/Cargo.toml --features=serde1
-cargo miri test --manifest-path rand_xoshiro/Cargo.toml --features=serde1
-cargo miri test --manifest-path rand_chacha/Cargo.toml --no-default-features
-cargo miri test --manifest-path rand_hc/Cargo.toml
-cargo miri test --manifest-path rand_jitter/Cargo.toml
-cargo miri test --manifest-path rand_os/Cargo.toml
diff --git a/rand/utils/ci/script.sh b/rand/utils/ci/script.sh
deleted file mode 100644
index 852a850..0000000
--- a/rand/utils/ci/script.sh
+++ /dev/null
@@ -1,27 +0,0 @@
-# Derived from https://github.com/japaric/trust
-
-set -ex
-
-main() {
- cross test --target $TARGET --tests --no-default-features
- # TODO: add simd_support feature:
- cross test --target $TARGET --features=log
- cross test --target $TARGET --examples
- cross test --target $TARGET --manifest-path rand_core/Cargo.toml
- cross test --target $TARGET --manifest-path rand_core/Cargo.toml --features=serde1
- cross test --target $TARGET --manifest-path rand_core/Cargo.toml --no-default-features
- cross test --target $TARGET --manifest-path rand_distr/Cargo.toml
- cross test --target $TARGET --manifest-path rand_isaac/Cargo.toml --features=serde1
- cross test --target $TARGET --manifest-path rand_pcg/Cargo.toml --features=serde1
- cross test --target $TARGET --manifest-path rand_xorshift/Cargo.toml --features=serde1
- cross test --target $TARGET --manifest-path rand_xoshiro/Cargo.toml --features=serde1
- cross test --target $TARGET --manifest-path rand_chacha/Cargo.toml
- cross test --target $TARGET --manifest-path rand_hc/Cargo.toml
- cross test --target $TARGET --manifest-path rand_os/Cargo.toml
- cross test --target $TARGET --manifest-path rand_jitter/Cargo.toml
-}
-
-# we don't run the "test phase" when doing deploys
-if [ -z $TRAVIS_TAG ]; then
- main
-fi
diff --git a/rand/utils/ziggurat_tables.py b/rand/utils/ziggurat_tables.py
deleted file mode 100755
index 88cfdab..0000000
--- a/rand/utils/ziggurat_tables.py
+++ /dev/null
@@ -1,125 +0,0 @@
-#!/usr/bin/env python
-#
-# Copyright 2018 Developers of the Rand project.
-# Copyright 2013 The Rust Project Developers.
-#
-# Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-# https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-# <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-# option. This file may not be copied, modified, or distributed
-# except according to those terms.
-
-# This creates the tables used for distributions implemented using the
-# ziggurat algorithm in `rand::distributions;`. They are
-# (basically) the tables as used in the ZIGNOR variant (Doornik 2005).
-# They are changed rarely, so the generated file should be checked in
-# to git.
-#
-# It creates 3 tables: X as in the paper, F which is f(x_i), and
-# F_DIFF which is f(x_i) - f(x_{i-1}). The latter two are just cached
-# values which is not done in that paper (but is done in other
-# variants). Note that the adZigR table is unnecessary because of
-# algebra.
-#
-# It is designed to be compatible with Python 2 and 3.
-
-from math import exp, sqrt, log, floor
-import random
-
-# The order should match the return value of `tables`
-TABLE_NAMES = ['X', 'F']
-
-# The actual length of the table is 1 more, to stop
-# index-out-of-bounds errors. This should match the bitwise operation
-# to find `i` in `zigurrat` in `libstd/rand/mod.rs`. Also the *_R and
-# *_V constants below depend on this value.
-TABLE_LEN = 256
-
-# equivalent to `zigNorInit` in Doornik2005, but generalised to any
-# distribution. r = dR, v = dV, f = probability density function,
-# f_inv = inverse of f
-def tables(r, v, f, f_inv):
- # compute the x_i
- xvec = [0]*(TABLE_LEN+1)
-
- xvec[0] = v / f(r)
- xvec[1] = r
-
- for i in range(2, TABLE_LEN):
- last = xvec[i-1]
- xvec[i] = f_inv(v / last + f(last))
-
- # cache the f's
- fvec = [0]*(TABLE_LEN+1)
- for i in range(TABLE_LEN+1):
- fvec[i] = f(xvec[i])
-
- return xvec, fvec
-
-# Distributions
-# N(0, 1)
-def norm_f(x):
- return exp(-x*x/2.0)
-def norm_f_inv(y):
- return sqrt(-2.0*log(y))
-
-NORM_R = 3.6541528853610088
-NORM_V = 0.00492867323399
-
-NORM = tables(NORM_R, NORM_V,
- norm_f, norm_f_inv)
-
-# Exp(1)
-def exp_f(x):
- return exp(-x)
-def exp_f_inv(y):
- return -log(y)
-
-EXP_R = 7.69711747013104972
-EXP_V = 0.0039496598225815571993
-
-EXP = tables(EXP_R, EXP_V,
- exp_f, exp_f_inv)
-
-
-# Output the tables/constants/types
-
-def render_static(name, type, value):
- # no space or
- return 'pub static %s: %s =%s;\n' % (name, type, value)
-
-# static `name`: [`type`, .. `len(values)`] =
-# [values[0], ..., values[3],
-# values[4], ..., values[7],
-# ... ];
-def render_table(name, values):
- rows = []
- # 4 values on each row
- for i in range(0, len(values), 4):
- row = values[i:i+4]
- rows.append(', '.join('%.18f' % f for f in row))
-
- rendered = '\n [%s]' % ',\n '.join(rows)
- return render_static(name, '[f64, .. %d]' % len(values), rendered)
-
-
-with open('ziggurat_tables.rs', 'w') as f:
- f.write('''// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-// Tables for distributions which are sampled using the ziggurat
-// algorithm. Autogenerated by `ziggurat_tables.py`.
-
-pub type ZigTable = &\'static [f64, .. %d];
-''' % (TABLE_LEN + 1))
- for name, tables, r in [('NORM', NORM, NORM_R),
- ('EXP', EXP, EXP_R)]:
- f.write(render_static('ZIG_%s_R' % name, 'f64', ' %.18f' % r))
- for (tabname, table) in zip(TABLE_NAMES, tables):
- f.write(render_table('ZIG_%s_%s' % (name, tabname), table))
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