Deleted vendor folder

33 files changed, 0 insertions, 7552 deletions

diff --git a/vendor/rand/.cargo-checksum.json b/vendor/rand/.cargo-checksum.json
deleted file mode 100644
index 56e7916..0000000
--- a/vendor/rand/.cargo-checksum.json
+++ /dev/null
@@ -1 +0,0 @@
-{"files":{"CHANGELOG.md":"f5e9c71d4123971f9f6c54eed8837245e6cac4b610c9d23b680fa95538946142","Cargo.toml":"4c770ee471e19f4a453a36d76479f9a530987058b793c735cd7a2bcf937d7edb","LICENSE-APACHE":"a60eea817514531668d7e00765731449fe14d059d3249e0bc93b36de45f759f2","LICENSE-MIT":"6485b8ed310d3f0340bf1ad1f47645069ce4069dcc6bb46c7d5c6faf41de1fdb","README.md":"fb8071c3bc1013107b16ebcb303f31ef614e81440f2d58a46bfb9ff1e311b792","appveyor.yml":"8796156caf7041ef2a43f7a313df21ea639de3f2563b6181bba1096b1c489f1b","benches/bench.rs":"35c4ab609f2a5f5aab6c52c257415258dc0780621b492b5a82bb12d048cab6db","benches/distributions/exponential.rs":"99cb59c013a0b6bb390d34c5649b341fc3b88ea7df0caf2470bdda8798f9fe3d","benches/distributions/gamma.rs":"3533f311e4b55d743c5b01a7eb6529c94fd97726ef6702a6372f914f5f33666b","benches/distributions/mod.rs":"0028f1cb96f61152ed5b49a4fe91227d809ef6d19035592c36032a538af7f95e","benches/distributions/normal.rs":"4e10c18cb583ccb96301ea953c8e0aa9ee3b6662060271d1b8d19ca23364dc6b","benches/generators.rs":"aaa2f1dbfb399df8323d8a5796b92add6210cd5f0f1d916895ffdd81d60f812b","benches/misc.rs":"bd2f7c5a16f0fcb59022d5aeef66ed3c94e89ebf6c06667851dd23d0b1595504","src/distributions/exponential.rs":"103c8412c8a581b71835f1c00e40f6370e7702adf9d499243933a793d132d4e7","src/distributions/gamma.rs":"7a3f85c8daad4e56e334586ddb9fc9d83df3b0699738ed681a6c41e4ed455be9","src/distributions/mod.rs":"7943c4f83721bac816f831cca3b1574b6136932f7b4927aa6101130080ba62c5","src/distributions/normal.rs":"1562b43f80e4d5f83a8deb5af18de5a18dfeeeeda11fefc577da26672b14c949","src/distributions/range.rs":"a72a538d3ec4ed23f8d632aa55fd4793c464f24a5872d04ce8095ddd5db92115","src/distributions/ziggurat_tables.rs":"4eacf94fc352c91c455a6623de6a721e53842e1690f13a5662b6a79c7fbb73de","src/jitter.rs":"befd4b84bf753c107370b5b9498ad49611c220bdae2e4be9ee4398e9fa497042","src/lib.rs":"f9f4d15c2ce67f9ba21261a4bc76599523b930698cee2ae1e37d01f0d2ba834e","src/os.rs":"bbba4481432ae0f19bafb2168af5e7e1a858547ff8a7f8996286ea1b2a951158","src/prng/chacha.rs":"558007276f9c22933d39e5b8e853f4dd9533e823ed66df8dc1f23ad6925b1d51","src/prng/isaac.rs":"a8a2ee8b38d312663308e3bdf03376e342fd91330655f39144e5bba7392b2a8e","src/prng/isaac64.rs":"f28f7596ccab910db265b42671116abb9d2039fa8a421cbc75312bd0e7715d3a","src/prng/mod.rs":"c1a73450f49e819a20942a5b591f84a08ebb5ac33aa0f65b18ac1dc9a19a3084","src/prng/xorshift.rs":"606c308747293652c868b46dc3cad847d0c3717629c04ba75681c887c7634114","src/rand_impls.rs":"e1f27077fc13d5855bb66235f8ccfb216e116337eb38424d9c30c090e112215c","src/read.rs":"bd0eb508a6b659dc578d546fc2f231484aed80c73cfe8c475e0d65c8d699a769","src/reseeding.rs":"a97b86387b87ea1adc5262ddea480fe735c9c2a86762abaace29119022ac9f6e","src/seq.rs":"76dd58af0f580aed2721c393a5c036322186dc7cb3b4abed33436620c7c49288","utils/ziggurat_tables.py":"a9fc0a2fdae9b5c798c238788f94b720c156e13fd96f2356c409aa533191eb94"},"package":"552840b97013b1a26992c11eac34bdd778e464601a4c2054b5f0bff7c6761293"}
\ No newline at end of file
diff --git a/vendor/rand/CHANGELOG.md b/vendor/rand/CHANGELOG.md
deleted file mode 100644
index aa4c293..0000000
--- a/vendor/rand/CHANGELOG.md
+++ /dev/null
@@ -1,277 +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](http://semver.org/spec/v2.0.0.html).
-
-## [0.4.5] - 2019-01-25
-### Platforms
-- Fuchsia: Replaced fuchsia-zircon with fuchsia-cprng
-
-## [0.4.4] - 2019-01-06
-### Added
-- SGX support
-
-## [0.4.3] - 2018-08-16
-### Fixed
-- Use correct syscall number for PowerPC (#589)
-
-## [0.4.2] - 2018-01-05
-### 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`)
-
-## [0.3.18] - 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 inplementaions 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!   2adf5363f88ffe06f6d2ea5c338d1b186d47f4a1
-- 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/vendor/rand/Cargo.toml b/vendor/rand/Cargo.toml
deleted file mode 100644
index 64d240c..0000000
--- a/vendor/rand/Cargo.toml
+++ /dev/null
@@ -1,45 +0,0 @@
-# THIS FILE IS AUTOMATICALLY GENERATED BY CARGO
-#
-# When uploading crates to the registry Cargo will automatically
-# "normalize" Cargo.toml files for maximal compatibility
-# with all versions of Cargo and also rewrite `path` dependencies
-# to registry (e.g. crates.io) dependencies
-#
-# If you believe there's an error in this file please file an
-# issue against the rust-lang/cargo repository. If you're
-# editing this file be aware that the upstream Cargo.toml
-# will likely look very different (and much more reasonable)
-
-[package]
-name = "rand"
-version = "0.4.6"
-authors = ["The Rust Project Developers"]
-description = "Random number generators and other randomness functionality.\n"
-homepage = "https://github.com/rust-lang-nursery/rand"
-documentation = "https://docs.rs/rand"
-readme = "README.md"
-keywords = ["random", "rng"]
-categories = ["algorithms"]
-license = "MIT/Apache-2.0"
-repository = "https://github.com/rust-lang-nursery/rand"
-
-[features]
-alloc = []
-default = ["std"]
-i128_support = []
-nightly = ["i128_support"]
-std = ["libc"]
-[target."cfg(target_env = \"sgx\")".dependencies.rand_core]
-version = "0.3"
-default-features = false
-
-[target."cfg(target_env = \"sgx\")".dependencies.rdrand]
-version = "0.4.0"
-[target."cfg(target_os = \"fuchsia\")".dependencies.fuchsia-cprng]
-version = "0.1.0"
-[target."cfg(unix)".dependencies.libc]
-version = "0.2"
-optional = true
-[target."cfg(windows)".dependencies.winapi]
-version = "0.3"
-features = ["minwindef", "ntsecapi", "profileapi", "winnt"]
diff --git a/vendor/rand/LICENSE-APACHE b/vendor/rand/LICENSE-APACHE
deleted file mode 100644
index 16fe87b..0000000
--- a/vendor/rand/LICENSE-APACHE
+++ /dev/null
@@ -1,201 +0,0 @@
-                              Apache License
-                        Version 2.0, January 2004
-                     http://www.apache.org/licenses/
-
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-You may obtain a copy of the License at
-
-	http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
diff --git a/vendor/rand/LICENSE-MIT b/vendor/rand/LICENSE-MIT
deleted file mode 100644
index 39d4bdb..0000000
--- a/vendor/rand/LICENSE-MIT
+++ /dev/null
@@ -1,25 +0,0 @@
-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/vendor/rand/README.md b/vendor/rand/README.md
deleted file mode 100644
index f72bd51..0000000
--- a/vendor/rand/README.md
+++ /dev/null
@@ -1,139 +0,0 @@
-rand
-====
-
-A Rust library for random number generators and other randomness functionality.
-
-[![Build Status](https://travis-ci.org/rust-lang-nursery/rand.svg?branch=master)](https://travis-ci.org/rust-lang-nursery/rand)
-[![Build status](https://ci.appveyor.com/api/projects/status/rm5c9o33k3jhchbw?svg=true)](https://ci.appveyor.com/project/alexcrichton/rand)
-
-[Documentation](https://docs.rs/rand)
-
-## Usage
-
-Add this to your `Cargo.toml`:
-
-```toml
-[dependencies]
-rand = "0.4"
-```
-
-and this to your crate root:
-
-```rust
-extern crate rand;
-```
-
-### Versions
-
-Version `0.4`was released in December 2017. It contains almost no breaking
-changes since the `0.3` series, but nevertheless contains some significant
-new code, including a new "external" entropy source (`JitterRng`) and `no_std`
-support.
-
-Version `0.5` is in development and contains significant performance
-improvements for the ISAAC random number generators.
-
-## Examples
-
-There is built-in support for a random number generator (RNG) associated with each thread stored in thread-local storage. This RNG can be accessed via thread_rng, or used implicitly via random. This RNG is normally randomly seeded from an operating-system source of randomness, e.g. /dev/urandom on Unix systems, and will automatically reseed itself from this source after generating 32 KiB of random data.
-
-```rust
-let tuple = rand::random::<(f64, char)>();
-println!("{:?}", tuple)
-```
-
-```rust
-use rand::Rng;
-
-let mut rng = rand::thread_rng();
-if rng.gen() { // random bool
-    println!("i32: {}, u32: {}", rng.gen::<i32>(), rng.gen::<u32>())
-}
-```
-
-It is also possible to use other RNG types, which have a similar interface. The following uses the "ChaCha" algorithm instead of the default.
-
-```rust
-use rand::{Rng, ChaChaRng};
-
-let mut rng = rand::ChaChaRng::new_unseeded();
-println!("i32: {}, u32: {}", rng.gen::<i32>(), rng.gen::<u32>())
-```
-
-## Features
-
-By default, `rand` is built with all stable features available. The following
-optional features are available:
-
--   `i128_support` enables support for generating `u128` and `i128` values
--   `nightly` enables all unstable features (`i128_support`)
--   `std` enabled by default; by setting "default-features = false" `no_std`
-    mode is activated; this removes features depending on `std` functionality:
-    
-        -   `OsRng` is entirely unavailable
-        -   `JitterRng` code is still present, but a nanosecond timer must be
-            provided via `JitterRng::new_with_timer`
-        -   Since no external entropy is available, it is not possible to create
-            generators with fresh seeds (user must provide entropy)
-        -   `thread_rng`, `weak_rng` and `random` are all disabled
-        -   exponential, normal and gamma type distributions are unavailable
-            since `exp` and `log` functions are not provided in `core`
-        -   any code requiring `Vec` or `Box`
--   `alloc` can be used instead of `std` to provide `Vec` and `Box`
-
-## Testing
-
-Unfortunately, `cargo test` does not test everything. The following tests are
-recommended:
-
-```
-# Basic tests for rand and sub-crates
-cargo test --all
-
-# Test no_std support (build only since nearly all tests require std)
-cargo build --all --no-default-features
-
-# Test 128-bit support (requires nightly)
-cargo test --all --features nightly
-
-# Benchmarks (requires nightly)
-cargo bench
-# or just to test the benchmark code:
-cargo test --benches
-```
-
-# `derive(Rand)`
-
-You can derive the `Rand` trait for your custom type via the `#[derive(Rand)]`
-directive. To use this first add this to your Cargo.toml:
-
-```toml
-rand = "0.4"
-rand_derive = "0.3"
-```
-
-Next in your crate:
-
-```rust
-extern crate rand;
-#[macro_use]
-extern crate rand_derive;
-
-#[derive(Rand, Debug)]
-struct MyStruct {
-    a: i32,
-    b: u32,
-}
-
-fn main() {
-    println!("{:?}", rand::random::<MyStruct>());
-}
-```
-
-
-# License
-
-`rand` is primarily distributed under the terms of both the MIT
-license and the Apache License (Version 2.0).
-
-See LICENSE-APACHE, and LICENSE-MIT for details.
diff --git a/vendor/rand/appveyor.yml b/vendor/rand/appveyor.yml
deleted file mode 100644
index 02e217f..0000000
--- a/vendor/rand/appveyor.yml
+++ /dev/null
@@ -1,38 +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 --benches
-  - cargo test
-  - cargo test --features nightly
-  - cargo test --manifest-path rand-derive/Cargo.toml
diff --git a/vendor/rand/benches/bench.rs b/vendor/rand/benches/bench.rs
deleted file mode 100644
index d396f25..0000000
--- a/vendor/rand/benches/bench.rs
+++ /dev/null
@@ -1,34 +0,0 @@
-#![feature(test)]
-
-extern crate test;
-extern crate rand;
-
-const RAND_BENCH_N: u64 = 1000;
-
-mod distributions;
-
-use std::mem::size_of;
-use test::{black_box, Bencher};
-use rand::{StdRng, Rng};
-
-#[bench]
-fn rand_f32(b: &mut Bencher) {
-    let mut rng = StdRng::new().unwrap();
-    b.iter(|| {
-        for _ in 0..RAND_BENCH_N {
-            black_box(rng.next_f32());
-        }
-    });
-    b.bytes = size_of::<f32>() as u64 * RAND_BENCH_N;
-}
-
-#[bench]
-fn rand_f64(b: &mut Bencher) {
-    let mut rng = StdRng::new().unwrap();
-    b.iter(|| {
-        for _ in 0..RAND_BENCH_N {
-            black_box(rng.next_f64());
-        }
-    });
-    b.bytes = size_of::<f64>() as u64 * RAND_BENCH_N;
-}
diff --git a/vendor/rand/benches/distributions/exponential.rs b/vendor/rand/benches/distributions/exponential.rs
deleted file mode 100644
index 152615d..0000000
--- a/vendor/rand/benches/distributions/exponential.rs
+++ /dev/null
@@ -1,18 +0,0 @@
-use std::mem::size_of;
-use test::Bencher;
-use rand;
-use rand::distributions::exponential::Exp;
-use rand::distributions::Sample;
-
-#[bench]
-fn rand_exp(b: &mut Bencher) {
-    let mut rng = rand::weak_rng();
-    let mut exp = Exp::new(2.71828 * 3.14159);
-
-    b.iter(|| {
-        for _ in 0..::RAND_BENCH_N {
-            exp.sample(&mut rng);
-        }
-    });
-    b.bytes = size_of::<f64>() as u64 * ::RAND_BENCH_N;
-}
diff --git a/vendor/rand/benches/distributions/gamma.rs b/vendor/rand/benches/distributions/gamma.rs
deleted file mode 100644
index bf3fd36..0000000
--- a/vendor/rand/benches/distributions/gamma.rs
+++ /dev/null
@@ -1,31 +0,0 @@
-use std::mem::size_of;
-use test::Bencher;
-use rand;
-use rand::distributions::IndependentSample;
-use rand::distributions::gamma::Gamma;
-
-#[bench]
-fn bench_gamma_large_shape(b: &mut Bencher) {
-    let gamma = Gamma::new(10., 1.0);
-    let mut rng = rand::weak_rng();
-
-    b.iter(|| {
-        for _ in 0..::RAND_BENCH_N {
-            gamma.ind_sample(&mut rng);
-        }
-    });
-    b.bytes = size_of::<f64>() as u64 * ::RAND_BENCH_N;
-}
-
-#[bench]
-fn bench_gamma_small_shape(b: &mut Bencher) {
-    let gamma = Gamma::new(0.1, 1.0);
-    let mut rng = rand::weak_rng();
-
-    b.iter(|| {
-        for _ in 0..::RAND_BENCH_N {
-            gamma.ind_sample(&mut rng);
-        }
-    });
-    b.bytes = size_of::<f64>() as u64 * ::RAND_BENCH_N;
-}
diff --git a/vendor/rand/benches/distributions/mod.rs b/vendor/rand/benches/distributions/mod.rs
deleted file mode 100644
index 49f6bd9..0000000
--- a/vendor/rand/benches/distributions/mod.rs
+++ /dev/null
@@ -1,3 +0,0 @@
-mod exponential;
-mod normal;
-mod gamma;
diff --git a/vendor/rand/benches/distributions/normal.rs b/vendor/rand/benches/distributions/normal.rs
deleted file mode 100644
index 1c858b1..0000000
--- a/vendor/rand/benches/distributions/normal.rs
+++ /dev/null
@@ -1,18 +0,0 @@
-use std::mem::size_of;
-use test::Bencher;
-use rand;
-use rand::distributions::Sample;
-use rand::distributions::normal::Normal;
-
-#[bench]
-fn rand_normal(b: &mut Bencher) {
-    let mut rng = rand::weak_rng();
-    let mut normal = Normal::new(-2.71828, 3.14159);
-
-    b.iter(|| {
-        for _ in 0..::RAND_BENCH_N {
-            normal.sample(&mut rng);
-        }
-    });
-    b.bytes = size_of::<f64>() as u64 * ::RAND_BENCH_N;
-}
diff --git a/vendor/rand/benches/generators.rs b/vendor/rand/benches/generators.rs
deleted file mode 100644
index daee7c5..0000000
--- a/vendor/rand/benches/generators.rs
+++ /dev/null
@@ -1,133 +0,0 @@
-#![feature(test)]
-
-extern crate test;
-extern crate rand;
-
-const RAND_BENCH_N: u64 = 1000;
-const BYTES_LEN: usize = 1024;
-
-use std::mem::size_of;
-use test::{black_box, Bencher};
-
-use rand::{Rng, StdRng, OsRng, JitterRng};
-use rand::{XorShiftRng, IsaacRng, Isaac64Rng, ChaChaRng};
-
-macro_rules! gen_bytes {
-    ($fnn:ident, $gen:ident) => {
-        #[bench]
-        fn $fnn(b: &mut Bencher) {
-            let mut rng: $gen = OsRng::new().unwrap().gen();
-            let mut buf = [0u8; BYTES_LEN];
-            b.iter(|| {
-                for _ in 0..RAND_BENCH_N {
-                    rng.fill_bytes(&mut buf);
-                    black_box(buf);
-                }
-            });
-            b.bytes = BYTES_LEN as u64 * RAND_BENCH_N;
-        }
-    }
-}
-
-macro_rules! gen_bytes_new {
-    ($fnn:ident, $gen:ident) => {
-        #[bench]
-        fn $fnn(b: &mut Bencher) {
-            let mut rng = $gen::new().unwrap();
-            let mut buf = [0u8; BYTES_LEN];
-            b.iter(|| {
-                for _ in 0..RAND_BENCH_N {
-                    rng.fill_bytes(&mut buf);
-                    black_box(buf);
-                }
-            });
-            b.bytes = BYTES_LEN as u64 * RAND_BENCH_N;
-        }
-    }
-}
-
-gen_bytes!(gen_bytes_xorshift, XorShiftRng);
-gen_bytes!(gen_bytes_isaac, IsaacRng);
-gen_bytes!(gen_bytes_isaac64, Isaac64Rng);
-gen_bytes!(gen_bytes_chacha, ChaChaRng);
-gen_bytes_new!(gen_bytes_std, StdRng);
-gen_bytes_new!(gen_bytes_os, OsRng);
-
-
-macro_rules! gen_uint {
-    ($fnn:ident, $ty:ty, $gen:ident) => {
-        #[bench]
-        fn $fnn(b: &mut Bencher) {
-            let mut rng: $gen = OsRng::new().unwrap().gen();
-            b.iter(|| {
-                for _ in 0..RAND_BENCH_N {
-                    black_box(rng.gen::<$ty>());
-                }
-            });
-            b.bytes = size_of::<$ty>() as u64 * RAND_BENCH_N;
-        }
-    }
-}
-
-macro_rules! gen_uint_new {
-    ($fnn:ident, $ty:ty, $gen:ident) => {
-        #[bench]
-        fn $fnn(b: &mut Bencher) {
-            let mut rng = $gen::new().unwrap();
-            b.iter(|| {
-                for _ in 0..RAND_BENCH_N {
-                    black_box(rng.gen::<$ty>());
-                }
-            });
-            b.bytes = size_of::<$ty>() as u64 * RAND_BENCH_N;
-        }
-    }
-}
-
-gen_uint!(gen_u32_xorshift, u32, XorShiftRng);
-gen_uint!(gen_u32_isaac, u32, IsaacRng);
-gen_uint!(gen_u32_isaac64, u32, Isaac64Rng);
-gen_uint!(gen_u32_chacha, u32, ChaChaRng);
-gen_uint_new!(gen_u32_std, u32, StdRng);
-gen_uint_new!(gen_u32_os, u32, OsRng);
-
-gen_uint!(gen_u64_xorshift, u64, XorShiftRng);
-gen_uint!(gen_u64_isaac, u64, IsaacRng);
-gen_uint!(gen_u64_isaac64, u64, Isaac64Rng);
-gen_uint!(gen_u64_chacha, u64, ChaChaRng);
-gen_uint_new!(gen_u64_std, u64, StdRng);
-gen_uint_new!(gen_u64_os, u64, OsRng);
-
-#[bench]
-fn gen_u64_jitter(b: &mut Bencher) {
-    let mut rng = JitterRng::new().unwrap();
-    b.iter(|| {
-        black_box(rng.gen::<u64>());
-    });
-    b.bytes = size_of::<u64>() as u64;
-}
-
-macro_rules! init_gen {
-    ($fnn:ident, $gen:ident) => {
-        #[bench]
-        fn $fnn(b: &mut Bencher) {
-            let mut rng: XorShiftRng = OsRng::new().unwrap().gen();
-            b.iter(|| {
-                let r2: $gen = rng.gen();
-                black_box(r2);
-            });
-        }
-    }
-}
-
-init_gen!(init_xorshift, XorShiftRng);
-init_gen!(init_isaac, IsaacRng);
-init_gen!(init_isaac64, Isaac64Rng);
-init_gen!(init_chacha, ChaChaRng);
-
-#[bench]
-fn init_jitter(b: &mut Bencher) {
-    b.iter(|| {
-        black_box(JitterRng::new().unwrap());
-    });
-}
diff --git a/vendor/rand/benches/misc.rs b/vendor/rand/benches/misc.rs
deleted file mode 100644
index 4251761..0000000
--- a/vendor/rand/benches/misc.rs
+++ /dev/null
@@ -1,62 +0,0 @@
-#![feature(test)]
-
-extern crate test;
-extern crate rand;
-
-use test::{black_box, Bencher};
-
-use rand::{Rng, weak_rng};
-use rand::seq::*;
-
-#[bench]
-fn misc_shuffle_100(b: &mut Bencher) {
-    let mut rng = weak_rng();
-    let x : &mut [usize] = &mut [1; 100];
-    b.iter(|| {
-        rng.shuffle(x);
-        black_box(&x);
-    })
-}
-
-#[bench]
-fn misc_sample_iter_10_of_100(b: &mut Bencher) {
-    let mut rng = weak_rng();
-    let x : &[usize] = &[1; 100];
-    b.iter(|| {
-        black_box(sample_iter(&mut rng, x, 10).unwrap_or_else(|e| e));
-    })
-}
-
-#[bench]
-fn misc_sample_slice_10_of_100(b: &mut Bencher) {
-    let mut rng = weak_rng();
-    let x : &[usize] = &[1; 100];
-    b.iter(|| {
-        black_box(sample_slice(&mut rng, x, 10));
-    })
-}
-
-#[bench]
-fn misc_sample_slice_ref_10_of_100(b: &mut Bencher) {
-    let mut rng = weak_rng();
-    let x : &[usize] = &[1; 100];
-    b.iter(|| {
-        black_box(sample_slice_ref(&mut rng, x, 10));
-    })
-}
-
-macro_rules! sample_indices {
-    ($name:ident, $amount:expr, $length:expr) => {
-        #[bench]
-        fn $name(b: &mut Bencher) {
-            let mut rng = weak_rng();
-            b.iter(|| {
-                black_box(sample_indices(&mut rng, $length, $amount));
-            })
-        }
-    }
-}
-
-sample_indices!(misc_sample_indices_10_of_1k, 10, 1000);
-sample_indices!(misc_sample_indices_50_of_1k, 50, 1000);
-sample_indices!(misc_sample_indices_100_of_1k, 100, 1000);
diff --git a/vendor/rand/src/distributions/exponential.rs b/vendor/rand/src/distributions/exponential.rs
deleted file mode 100644
index c3c924c..0000000
--- a/vendor/rand/src/distributions/exponential.rs
+++ /dev/null
@@ -1,124 +0,0 @@
-// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The exponential distribution.
-
-use {Rng, Rand};
-use distributions::{ziggurat, ziggurat_tables, Sample, IndependentSample};
-
-/// A wrapper around an `f64` to generate Exp(1) random numbers.
-///
-/// 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*](http://www.doornik.com/research/ziggurat.pdf). Nuffield
-/// College, Oxford
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::exponential::Exp1;
-///
-/// let Exp1(x) = rand::random();
-/// println!("{}", x);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Exp1(pub f64);
-
-// This could be done via `-rng.gen::<f64>().ln()` but that is slower.
-impl Rand for Exp1 {
-    #[inline]
-    fn rand<R:Rng>(rng: &mut R) -> Exp1 {
-        #[inline]
-        fn pdf(x: f64) -> f64 {
-            (-x).exp()
-        }
-        #[inline]
-        fn zero_case<R:Rng>(rng: &mut R, _u: f64) -> f64 {
-            ziggurat_tables::ZIG_EXP_R - rng.gen::<f64>().ln()
-        }
-
-        Exp1(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`.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::{Exp, IndependentSample};
-///
-/// let exp = Exp::new(2.0);
-/// let v = exp.ind_sample(&mut rand::thread_rng());
-/// println!("{} is from a Exp(2) distribution", v);
-/// ```
-#[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 Sample<f64> for Exp {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) }
-}
-impl IndependentSample<f64> for Exp {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 {
-        let Exp1(n) = rng.gen::<Exp1>();
-        n * self.lambda_inverse
-    }
-}
-
-#[cfg(test)]
-mod test {
-    use distributions::{Sample, IndependentSample};
-    use super::Exp;
-
-    #[test]
-    fn test_exp() {
-        let mut exp = Exp::new(10.0);
-        let mut rng = ::test::rng();
-        for _ in 0..1000 {
-            assert!(exp.sample(&mut rng) >= 0.0);
-            assert!(exp.ind_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/vendor/rand/src/distributions/gamma.rs b/vendor/rand/src/distributions/gamma.rs
deleted file mode 100644
index 2806495..0000000
--- a/vendor/rand/src/distributions/gamma.rs
+++ /dev/null
@@ -1,386 +0,0 @@
-// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-//
-// ignore-lexer-test FIXME #15679
-
-//! The Gamma and derived distributions.
-
-use self::GammaRepr::*;
-use self::ChiSquaredRepr::*;
-
-use {Rng, Open01};
-use super::normal::StandardNormal;
-use super::{IndependentSample, Sample, Exp};
-
-/// The Gamma distribution `Gamma(shape, scale)` distribution.
-///
-/// The density function of this distribution is
-///
-/// ```text
-/// f(x) =  x^(k - 1) * exp(-x / θ) / (Γ(k) * θ^k)
-/// ```
-///
-/// where `Γ` is the Gamma function, `k` is the shape and `θ` is the
-/// scale and both `k` and `θ` 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 [1] for
-/// `shape < 1`.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::{IndependentSample, Gamma};
-///
-/// let gamma = Gamma::new(2.0, 5.0);
-/// let v = gamma.ind_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](http://doi.acm.org/10.1145/358407.358414)
-#[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: 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: scale,
-            c: 1. / (9. * d).sqrt(),
-            d: d
-        }
-    }
-}
-
-impl Sample<f64> for Gamma {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) }
-}
-impl Sample<f64> for GammaSmallShape {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) }
-}
-impl Sample<f64> for GammaLargeShape {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) }
-}
-
-impl IndependentSample<f64> for Gamma {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 {
-        match self.repr {
-            Small(ref g) => g.ind_sample(rng),
-            One(ref g) => g.ind_sample(rng),
-            Large(ref g) => g.ind_sample(rng),
-        }
-    }
-}
-impl IndependentSample<f64> for GammaSmallShape {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 {
-        let Open01(u) = rng.gen::<Open01<f64>>();
-
-        self.large_shape.ind_sample(rng) * u.powf(self.inv_shape)
-    }
-}
-impl IndependentSample<f64> for GammaLargeShape {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 {
-        loop {
-            let StandardNormal(x) = rng.gen::<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 Open01(u) = rng.gen::<Open01<f64>>();
-
-            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 `χ²(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
-/// `χ²(k) = Gamma(k/2, 2)`.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::{ChiSquared, IndependentSample};
-///
-/// let chi = ChiSquared::new(11.0);
-/// let v = chi.ind_sample(&mut rand::thread_rng());
-/// println!("{} is from a χ²(11) distribution", v)
-/// ```
-#[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: repr }
-    }
-}
-impl Sample<f64> for ChiSquared {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) }
-}
-impl IndependentSample<f64> for ChiSquared {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 {
-        match self.repr {
-            DoFExactlyOne => {
-                // k == 1 => N(0,1)^2
-                let StandardNormal(norm) = rng.gen::<StandardNormal>();
-                norm * norm
-            }
-            DoFAnythingElse(ref g) => g.ind_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) = (χ²(m)/m) /
-/// (χ²(n)/n)`.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::{FisherF, IndependentSample};
-///
-/// let f = FisherF::new(2.0, 32.0);
-/// let v = f.ind_sample(&mut rand::thread_rng());
-/// println!("{} is from an F(2, 32) distribution", v)
-/// ```
-#[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 Sample<f64> for FisherF {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) }
-}
-impl IndependentSample<f64> for FisherF {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 {
-        self.numer.ind_sample(rng) / self.denom.ind_sample(rng) * self.dof_ratio
-    }
-}
-
-/// The Student t distribution, `t(nu)`, where `nu` is the degrees of
-/// freedom.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::{StudentT, IndependentSample};
-///
-/// let t = StudentT::new(11.0);
-/// let v = t.ind_sample(&mut rand::thread_rng());
-/// println!("{} is from a t(11) distribution", v)
-/// ```
-#[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 Sample<f64> for StudentT {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) }
-}
-impl IndependentSample<f64> for StudentT {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 {
-        let StandardNormal(norm) = rng.gen::<StandardNormal>();
-        norm * (self.dof / self.chi.ind_sample(rng)).sqrt()
-    }
-}
-
-#[cfg(test)]
-mod test {
-    use distributions::{Sample, IndependentSample};
-    use super::{ChiSquared, StudentT, FisherF};
-
-    #[test]
-    fn test_chi_squared_one() {
-        let mut chi = ChiSquared::new(1.0);
-        let mut rng = ::test::rng();
-        for _ in 0..1000 {
-            chi.sample(&mut rng);
-            chi.ind_sample(&mut rng);
-        }
-    }
-    #[test]
-    fn test_chi_squared_small() {
-        let mut chi = ChiSquared::new(0.5);
-        let mut rng = ::test::rng();
-        for _ in 0..1000 {
-            chi.sample(&mut rng);
-            chi.ind_sample(&mut rng);
-        }
-    }
-    #[test]
-    fn test_chi_squared_large() {
-        let mut chi = ChiSquared::new(30.0);
-        let mut rng = ::test::rng();
-        for _ in 0..1000 {
-            chi.sample(&mut rng);
-            chi.ind_sample(&mut rng);
-        }
-    }
-    #[test]
-    #[should_panic]
-    fn test_chi_squared_invalid_dof() {
-        ChiSquared::new(-1.0);
-    }
-
-    #[test]
-    fn test_f() {
-        let mut f = FisherF::new(2.0, 32.0);
-        let mut rng = ::test::rng();
-        for _ in 0..1000 {
-            f.sample(&mut rng);
-            f.ind_sample(&mut rng);
-        }
-    }
-
-    #[test]
-    fn test_t() {
-        let mut t = StudentT::new(11.0);
-        let mut rng = ::test::rng();
-        for _ in 0..1000 {
-            t.sample(&mut rng);
-            t.ind_sample(&mut rng);
-        }
-    }
-}
diff --git a/vendor/rand/src/distributions/mod.rs b/vendor/rand/src/distributions/mod.rs
deleted file mode 100644
index 5de8efb..0000000
--- a/vendor/rand/src/distributions/mod.rs
+++ /dev/null
@@ -1,409 +0,0 @@
-// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Sampling from random distributions.
-//!
-//! This is a generalization of `Rand` to allow parameters to control the
-//! exact properties of the generated values, e.g. the mean and standard
-//! deviation of a normal distribution. The `Sample` trait is the most
-//! general, and allows for generating values that change some state
-//! internally. The `IndependentSample` trait is for generating values
-//! that do not need to record state.
-
-use core::marker;
-
-use {Rng, Rand};
-
-pub use self::range::Range;
-#[cfg(feature="std")]
-pub use self::gamma::{Gamma, ChiSquared, FisherF, StudentT};
-#[cfg(feature="std")]
-pub use self::normal::{Normal, LogNormal};
-#[cfg(feature="std")]
-pub use self::exponential::Exp;
-
-pub mod range;
-#[cfg(feature="std")]
-pub mod gamma;
-#[cfg(feature="std")]
-pub mod normal;
-#[cfg(feature="std")]
-pub mod exponential;
-
-#[cfg(feature="std")]
-mod ziggurat_tables;
-
-/// Types that can be used to create a random instance of `Support`.
-pub trait Sample<Support> {
-    /// Generate a random value of `Support`, using `rng` as the
-    /// source of randomness.
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> Support;
-}
-
-/// `Sample`s that do not require keeping track of state.
-///
-/// Since no state is recorded, each sample is (statistically)
-/// independent of all others, assuming the `Rng` used has this
-/// property.
-// FIXME maybe having this separate is overkill (the only reason is to
-// take &self rather than &mut self)? or maybe this should be the
-// trait called `Sample` and the other should be `DependentSample`.
-pub trait IndependentSample<Support>: Sample<Support> {
-    /// Generate a random value.
-    fn ind_sample<R: Rng>(&self, &mut R) -> Support;
-}
-
-/// A wrapper for generating types that implement `Rand` via the
-/// `Sample` & `IndependentSample` traits.
-#[derive(Debug)]
-pub struct RandSample<Sup> {
-    _marker: marker::PhantomData<fn() -> Sup>,
-}
-
-impl<Sup> Copy for RandSample<Sup> {}
-impl<Sup> Clone for RandSample<Sup> {
-    fn clone(&self) -> Self { *self }
-}
-
-impl<Sup: Rand> Sample<Sup> for RandSample<Sup> {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> Sup { self.ind_sample(rng) }
-}
-
-impl<Sup: Rand> IndependentSample<Sup> for RandSample<Sup> {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> Sup {
-        rng.gen()
-    }
-}
-
-impl<Sup> RandSample<Sup> {
-    pub fn new() -> RandSample<Sup> {
-        RandSample { _marker: marker::PhantomData }
-    }
-}
-
-/// A value with a particular weight for use with `WeightedChoice`.
-#[derive(Copy, Clone, Debug)]
-pub struct Weighted<T> {
-    /// The numerical weight of this item
-    pub weight: u32,
-    /// The actual item which is being weighted
-    pub item: T,
-}
-
-/// A distribution that selects from a finite collection of weighted items.
-///
-/// Each item has an associated weight that influences how likely it
-/// is to be chosen: higher weight is more likely.
-///
-/// The `Clone` restriction is a limitation of the `Sample` and
-/// `IndependentSample` traits. Note that `&T` is (cheaply) `Clone` for
-/// all `T`, as is `u32`, so one can store references or indices into
-/// another vector.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::{Weighted, WeightedChoice, IndependentSample};
-///
-/// let mut items = vec!(Weighted { weight: 2, item: 'a' },
-///                      Weighted { weight: 4, item: 'b' },
-///                      Weighted { weight: 1, item: 'c' });
-/// let wc = WeightedChoice::new(&mut items);
-/// let mut rng = rand::thread_rng();
-/// for _ in 0..16 {
-///      // on average prints 'a' 4 times, 'b' 8 and 'c' twice.
-///      println!("{}", wc.ind_sample(&mut rng));
-/// }
-/// ```
-#[derive(Debug)]
-pub struct WeightedChoice<'a, T:'a> {
-    items: &'a mut [Weighted<T>],
-    weight_range: Range<u32>
-}
-
-impl<'a, T: Clone> WeightedChoice<'a, T> {
-    /// Create a new `WeightedChoice`.
-    ///
-    /// Panics if:
-    ///
-    /// - `items` is empty
-    /// - the total weight is 0
-    /// - the total weight is larger than a `u32` can contain.
-    pub fn new(items: &'a mut [Weighted<T>]) -> WeightedChoice<'a, T> {
-        // strictly speaking, this is subsumed by the total weight == 0 case
-        assert!(!items.is_empty(), "WeightedChoice::new called with no items");
-
-        let mut running_total: u32 = 0;
-
-        // we convert the list from individual weights to cumulative
-        // weights so we can binary search. This *could* drop elements
-        // with weight == 0 as an optimisation.
-        for item in items.iter_mut() {
-            running_total = match running_total.checked_add(item.weight) {
-                Some(n) => n,
-                None => panic!("WeightedChoice::new called with a total weight \
-                               larger than a u32 can contain")
-            };
-
-            item.weight = running_total;
-        }
-        assert!(running_total != 0, "WeightedChoice::new called with a total weight of 0");
-
-        WeightedChoice {
-            items: items,
-            // we're likely to be generating numbers in this range
-            // relatively often, so might as well cache it
-            weight_range: Range::new(0, running_total)
-        }
-    }
-}
-
-impl<'a, T: Clone> Sample<T> for WeightedChoice<'a, T> {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> T { self.ind_sample(rng) }
-}
-
-impl<'a, T: Clone> IndependentSample<T> for WeightedChoice<'a, T> {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> T {
-        // we want to find the first element that has cumulative
-        // weight > sample_weight, which we do by binary since the
-        // cumulative weights of self.items are sorted.
-
-        // choose a weight in [0, total_weight)
-        let sample_weight = self.weight_range.ind_sample(rng);
-
-        // short circuit when it's the first item
-        if sample_weight < self.items[0].weight {
-            return self.items[0].item.clone();
-        }
-
-        let mut idx = 0;
-        let mut modifier = self.items.len();
-
-        // now we know that every possibility has an element to the
-        // left, so we can just search for the last element that has
-        // cumulative weight <= sample_weight, then the next one will
-        // be "it". (Note that this greatest element will never be the
-        // last element of the vector, since sample_weight is chosen
-        // in [0, total_weight) and the cumulative weight of the last
-        // one is exactly the total weight.)
-        while modifier > 1 {
-            let i = idx + modifier / 2;
-            if self.items[i].weight <= sample_weight {
-                // we're small, so look to the right, but allow this
-                // exact element still.
-                idx = i;
-                // we need the `/ 2` to round up otherwise we'll drop
-                // the trailing elements when `modifier` is odd.
-                modifier += 1;
-            } else {
-                // otherwise we're too big, so go left. (i.e. do
-                // nothing)
-            }
-            modifier /= 2;
-        }
-        return self.items[idx + 1].item.clone();
-    }
-}
-
-/// 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)]
-fn ziggurat<R: Rng, 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 {
-    const SCALE: f64 = (1u64 << 53) as f64;
-    loop {
-        // reimplement the f64 generation as an optimisation suggested
-        // by the Doornik paper: we have a lot of precision-space
-        // (i.e. there are 11 bits of the 64 of a u64 to use after
-        // creating a f64), so we might as well reuse some to save
-        // generating a whole extra random number. (Seems to be 15%
-        // faster.)
-        //
-        // This unfortunately misses out on the benefits of direct
-        // floating point generation if an RNG like dSMFT is
-        // used. (That is, such RNGs create floats directly, highly
-        // efficiently and overload next_f32/f64, so by not calling it
-        // this may be slower than it would be otherwise.)
-        // FIXME: investigate/optimise for the above.
-        let bits: u64 = rng.gen();
-        let i = (bits & 0xff) as usize;
-        let f = (bits >> 11) as f64 / SCALE;
-
-        // u is either U(-1, 1) or U(0, 1) depending on if this is a
-        // symmetric distribution or not.
-        let u = if symmetric {2.0 * f - 1.0} else {f};
-        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;
-        }
-    }
-}
-
-#[cfg(test)]
-mod tests {
-
-    use {Rng, Rand};
-    use super::{RandSample, WeightedChoice, Weighted, Sample, IndependentSample};
-
-    #[derive(PartialEq, Debug)]
-    struct ConstRand(usize);
-    impl Rand for ConstRand {
-        fn rand<R: Rng>(_: &mut R) -> ConstRand {
-            ConstRand(0)
-        }
-    }
-
-    // 0, 1, 2, 3, ...
-    struct CountingRng { i: u32 }
-    impl Rng for CountingRng {
-        fn next_u32(&mut self) -> u32 {
-            self.i += 1;
-            self.i - 1
-        }
-        fn next_u64(&mut self) -> u64 {
-            self.next_u32() as u64
-        }
-    }
-
-    #[test]
-    fn test_rand_sample() {
-        let mut rand_sample = RandSample::<ConstRand>::new();
-
-        assert_eq!(rand_sample.sample(&mut ::test::rng()), ConstRand(0));
-        assert_eq!(rand_sample.ind_sample(&mut ::test::rng()), ConstRand(0));
-    }
-    #[test]
-    fn test_weighted_choice() {
-        // this makes assumptions about the internal implementation of
-        // WeightedChoice, specifically: it doesn't reorder the items,
-        // it doesn't do weird things to the RNG (so 0 maps to 0, 1 to
-        // 1, internally; modulo a modulo operation).
-
-        macro_rules! t {
-            ($items:expr, $expected:expr) => {{
-                let mut items = $items;
-                let wc = WeightedChoice::new(&mut items);
-                let expected = $expected;
-
-                let mut rng = CountingRng { i: 0 };
-
-                for &val in expected.iter() {
-                    assert_eq!(wc.ind_sample(&mut rng), val)
-                }
-            }}
-        }
-
-        t!(vec!(Weighted { weight: 1, item: 10}), [10]);
-
-        // skip some
-        t!(vec!(Weighted { weight: 0, item: 20},
-                Weighted { weight: 2, item: 21},
-                Weighted { weight: 0, item: 22},
-                Weighted { weight: 1, item: 23}),
-           [21,21, 23]);
-
-        // different weights
-        t!(vec!(Weighted { weight: 4, item: 30},
-                Weighted { weight: 3, item: 31}),
-           [30,30,30,30, 31,31,31]);
-
-        // check that we're binary searching
-        // correctly with some vectors of odd
-        // length.
-        t!(vec!(Weighted { weight: 1, item: 40},
-                Weighted { weight: 1, item: 41},
-                Weighted { weight: 1, item: 42},
-                Weighted { weight: 1, item: 43},
-                Weighted { weight: 1, item: 44}),
-           [40, 41, 42, 43, 44]);
-        t!(vec!(Weighted { weight: 1, item: 50},
-                Weighted { weight: 1, item: 51},
-                Weighted { weight: 1, item: 52},
-                Weighted { weight: 1, item: 53},
-                Weighted { weight: 1, item: 54},
-                Weighted { weight: 1, item: 55},
-                Weighted { weight: 1, item: 56}),
-           [50, 51, 52, 53, 54, 55, 56]);
-    }
-
-    #[test]
-    fn test_weighted_clone_initialization() {
-        let initial : Weighted<u32> = Weighted {weight: 1, item: 1};
-        let clone = initial.clone();
-        assert_eq!(initial.weight, clone.weight);
-        assert_eq!(initial.item, clone.item);
-    }
-
-    #[test] #[should_panic]
-    fn test_weighted_clone_change_weight() {
-        let initial : Weighted<u32> = Weighted {weight: 1, item: 1};
-        let mut clone = initial.clone();
-        clone.weight = 5;
-        assert_eq!(initial.weight, clone.weight);
-    }
-
-    #[test] #[should_panic]
-    fn test_weighted_clone_change_item() {
-        let initial : Weighted<u32> = Weighted {weight: 1, item: 1};
-        let mut clone = initial.clone();
-        clone.item = 5;
-        assert_eq!(initial.item, clone.item);
-
-    }
-
-    #[test] #[should_panic]
-    fn test_weighted_choice_no_items() {
-        WeightedChoice::<isize>::new(&mut []);
-    }
-    #[test] #[should_panic]
-    fn test_weighted_choice_zero_weight() {
-        WeightedChoice::new(&mut [Weighted { weight: 0, item: 0},
-                                  Weighted { weight: 0, item: 1}]);
-    }
-    #[test] #[should_panic]
-    fn test_weighted_choice_weight_overflows() {
-        let x = ::std::u32::MAX / 2; // x + x + 2 is the overflow
-        WeightedChoice::new(&mut [Weighted { weight: x, item: 0 },
-                                  Weighted { weight: 1, item: 1 },
-                                  Weighted { weight: x, item: 2 },
-                                  Weighted { weight: 1, item: 3 }]);
-    }
-}
diff --git a/vendor/rand/src/distributions/normal.rs b/vendor/rand/src/distributions/normal.rs
deleted file mode 100644
index 280613d..0000000
--- a/vendor/rand/src/distributions/normal.rs
+++ /dev/null
@@ -1,201 +0,0 @@
-// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The normal and derived distributions.
-
-use {Rng, Rand, Open01};
-use distributions::{ziggurat, ziggurat_tables, Sample, IndependentSample};
-
-/// A wrapper around an `f64` to generate N(0, 1) random numbers
-/// (a.k.a.  a standard normal, or Gaussian).
-///
-/// 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*](http://www.doornik.com/research/ziggurat.pdf). Nuffield
-/// College, Oxford
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::normal::StandardNormal;
-///
-/// let StandardNormal(x) = rand::random();
-/// println!("{}", x);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct StandardNormal(pub f64);
-
-impl Rand for StandardNormal {
-    fn rand<R:Rng>(rng: &mut R) -> StandardNormal {
-        #[inline]
-        fn pdf(x: f64) -> f64 {
-            (-x*x/2.0).exp()
-        }
-        #[inline]
-        fn zero_case<R:Rng>(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 Open01(x_) = rng.gen::<Open01<f64>>();
-                let Open01(y_) = rng.gen::<Open01<f64>>();
-
-                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 }
-        }
-
-        StandardNormal(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.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::{Normal, IndependentSample};
-///
-/// // mean 2, standard deviation 3
-/// let normal = Normal::new(2.0, 3.0);
-/// let v = normal.ind_sample(&mut rand::thread_rng());
-/// println!("{} is from a N(2, 9) distribution", v)
-/// ```
-#[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: mean,
-            std_dev: std_dev
-        }
-    }
-}
-impl Sample<f64> for Normal {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) }
-}
-impl IndependentSample<f64> for Normal {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 {
-        let StandardNormal(n) = rng.gen::<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
-///
-/// ```rust
-/// use rand::distributions::{LogNormal, IndependentSample};
-///
-/// // mean 2, standard deviation 3
-/// let log_normal = LogNormal::new(2.0, 3.0);
-/// let v = log_normal.ind_sample(&mut rand::thread_rng());
-/// println!("{} is from an ln N(2, 9) distribution", v)
-/// ```
-#[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 Sample<f64> for LogNormal {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) }
-}
-impl IndependentSample<f64> for LogNormal {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 {
-        self.norm.ind_sample(rng).exp()
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use distributions::{Sample, IndependentSample};
-    use super::{Normal, LogNormal};
-
-    #[test]
-    fn test_normal() {
-        let mut norm = Normal::new(10.0, 10.0);
-        let mut rng = ::test::rng();
-        for _ in 0..1000 {
-            norm.sample(&mut rng);
-            norm.ind_sample(&mut rng);
-        }
-    }
-    #[test]
-    #[should_panic]
-    fn test_normal_invalid_sd() {
-        Normal::new(10.0, -1.0);
-    }
-
-
-    #[test]
-    fn test_log_normal() {
-        let mut lnorm = LogNormal::new(10.0, 10.0);
-        let mut rng = ::test::rng();
-        for _ in 0..1000 {
-            lnorm.sample(&mut rng);
-            lnorm.ind_sample(&mut rng);
-        }
-    }
-    #[test]
-    #[should_panic]
-    fn test_log_normal_invalid_sd() {
-        LogNormal::new(10.0, -1.0);
-    }
-}
diff --git a/vendor/rand/src/distributions/range.rs b/vendor/rand/src/distributions/range.rs
deleted file mode 100644
index 935a00a..0000000
--- a/vendor/rand/src/distributions/range.rs
+++ /dev/null
@@ -1,241 +0,0 @@
-// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Generating numbers between two others.
-
-// this is surprisingly complicated to be both generic & correct
-
-use core::num::Wrapping as w;
-
-use Rng;
-use distributions::{Sample, IndependentSample};
-
-/// Sample values uniformly between two bounds.
-///
-/// This gives a uniform distribution (assuming the RNG used to sample
-/// it is itself uniform & the `SampleRange` implementation for the
-/// given type is correct), even for edge cases like `low = 0u8`,
-/// `high = 170u8`, for which a naive modulo operation would return
-/// numbers less than 85 with double the probability to those greater
-/// than 85.
-///
-/// Types should attempt to sample in `[low, high)`, i.e., not
-/// including `high`, but this may be very difficult. All the
-/// primitive integer types satisfy this property, and the float types
-/// normally satisfy it, but rounding may mean `high` can occur.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::{IndependentSample, Range};
-///
-/// fn main() {
-///     let between = Range::new(10, 10000);
-///     let mut rng = rand::thread_rng();
-///     let mut sum = 0;
-///     for _ in 0..1000 {
-///         sum += between.ind_sample(&mut rng);
-///     }
-///     println!("{}", sum);
-/// }
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Range<X> {
-    low: X,
-    range: X,
-    accept_zone: X
-}
-
-impl<X: SampleRange + PartialOrd> Range<X> {
-    /// Create a new `Range` instance that samples uniformly from
-    /// `[low, high)`. Panics if `low >= high`.
-    pub fn new(low: X, high: X) -> Range<X> {
-        assert!(low < high, "Range::new called with `low >= high`");
-        SampleRange::construct_range(low, high)
-    }
-}
-
-impl<Sup: SampleRange> Sample<Sup> for Range<Sup> {
-    #[inline]
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> Sup { self.ind_sample(rng) }
-}
-impl<Sup: SampleRange> IndependentSample<Sup> for Range<Sup> {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> Sup {
-        SampleRange::sample_range(self, rng)
-    }
-}
-
-/// The helper trait for types that have a sensible way to sample
-/// uniformly between two values. This should not be used directly,
-/// and is only to facilitate `Range`.
-pub trait SampleRange : Sized {
-    /// Construct the `Range` object that `sample_range`
-    /// requires. This should not ever be called directly, only via
-    /// `Range::new`, which will check that `low < high`, so this
-    /// function doesn't have to repeat the check.
-    fn construct_range(low: Self, high: Self) -> Range<Self>;
-
-    /// Sample a value from the given `Range` with the given `Rng` as
-    /// a source of randomness.
-    fn sample_range<R: Rng>(r: &Range<Self>, rng: &mut R) -> Self;
-}
-
-macro_rules! integer_impl {
-    ($ty:ty, $unsigned:ident) => {
-        impl SampleRange for $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 & a
-            // bijection.
-
-            #[inline]
-            fn construct_range(low: $ty, high: $ty) -> Range<$ty> {
-                let range = (w(high as $unsigned) - w(low as $unsigned)).0;
-                let unsigned_max: $unsigned = ::core::$unsigned::MAX;
-
-                // this is the largest number that fits into $unsigned
-                // that `range` divides evenly, so, if we've sampled
-                // `n` uniformly from this region, then `n % range` is
-                // uniform in [0, range)
-                let zone = unsigned_max - unsigned_max % range;
-
-                Range {
-                    low: low,
-                    range: range as $ty,
-                    accept_zone: zone as $ty
-                }
-            }
-
-            #[inline]
-            fn sample_range<R: Rng>(r: &Range<$ty>, rng: &mut R) -> $ty {
-                loop {
-                    // rejection sample
-                    let v = rng.gen::<$unsigned>();
-                    // until we find something that fits into the
-                    // region which r.range evenly divides (this will
-                    // be uniformly distributed)
-                    if v < r.accept_zone as $unsigned {
-                        // and return it, with some adjustments
-                        return (w(r.low) + w((v % r.range as $unsigned) as $ty)).0;
-                    }
-                }
-            }
-        }
-    }
-}
-
-integer_impl! { i8, u8 }
-integer_impl! { i16, u16 }
-integer_impl! { i32, u32 }
-integer_impl! { i64, u64 }
-#[cfg(feature = "i128_support")]
-integer_impl! { i128, u128 }
-integer_impl! { isize, usize }
-integer_impl! { u8, u8 }
-integer_impl! { u16, u16 }
-integer_impl! { u32, u32 }
-integer_impl! { u64, u64 }
-#[cfg(feature = "i128_support")]
-integer_impl! { u128, u128 }
-integer_impl! { usize, usize }
-
-macro_rules! float_impl {
-    ($ty:ty) => {
-        impl SampleRange for $ty {
-            fn construct_range(low: $ty, high: $ty) -> Range<$ty> {
-                Range {
-                    low: low,
-                    range: high - low,
-                    accept_zone: 0.0 // unused
-                }
-            }
-            fn sample_range<R: Rng>(r: &Range<$ty>, rng: &mut R) -> $ty {
-                r.low + r.range * rng.gen::<$ty>()
-            }
-        }
-    }
-}
-
-float_impl! { f32 }
-float_impl! { f64 }
-
-#[cfg(test)]
-mod tests {
-    use distributions::{Sample, IndependentSample};
-    use super::Range as Range;
-
-    #[should_panic]
-    #[test]
-    fn test_range_bad_limits_equal() {
-        Range::new(10, 10);
-    }
-    #[should_panic]
-    #[test]
-    fn test_range_bad_limits_flipped() {
-        Range::new(10, 5);
-    }
-
-    #[test]
-    fn test_integers() {
-        let mut rng = ::test::rng();
-        macro_rules! t {
-            ($($ty:ident),*) => {{
-                $(
-                   let v: &[($ty, $ty)] = &[(0, 10),
-                                            (10, 127),
-                                            (::core::$ty::MIN, ::core::$ty::MAX)];
-                   for &(low, high) in v.iter() {
-                        let mut sampler: Range<$ty> = Range::new(low, high);
-                        for _ in 0..1000 {
-                            let v = sampler.sample(&mut rng);
-                            assert!(low <= v && v < high);
-                            let v = sampler.ind_sample(&mut rng);
-                            assert!(low <= v && v < high);
-                        }
-                    }
-                 )*
-            }}
-        }
-        #[cfg(not(feature = "i128_support"))]
-        t!(i8, i16, i32, i64, isize,
-           u8, u16, u32, u64, usize);
-        #[cfg(feature = "i128_support")]
-        t!(i8, i16, i32, i64, i128, isize,
-           u8, u16, u32, u64, u128, usize);
-    }
-
-    #[test]
-    fn test_floats() {
-        let mut rng = ::test::rng();
-        macro_rules! t {
-            ($($ty:ty),*) => {{
-                $(
-                   let v: &[($ty, $ty)] = &[(0.0, 100.0),
-                                            (-1e35, -1e25),
-                                            (1e-35, 1e-25),
-                                            (-1e35, 1e35)];
-                   for &(low, high) in v.iter() {
-                        let mut sampler: Range<$ty> = Range::new(low, high);
-                        for _ in 0..1000 {
-                            let v = sampler.sample(&mut rng);
-                            assert!(low <= v && v < high);
-                            let v = sampler.ind_sample(&mut rng);
-                            assert!(low <= v && v < high);
-                        }
-                    }
-                 )*
-            }}
-        }
-
-        t!(f32, f64)
-    }
-
-}
diff --git a/vendor/rand/src/distributions/ziggurat_tables.rs b/vendor/rand/src/distributions/ziggurat_tables.rs
deleted file mode 100644
index b6de4bf..0000000
--- a/vendor/rand/src/distributions/ziggurat_tables.rs
+++ /dev/null
@@ -1,280 +0,0 @@
-// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. 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/vendor/rand/src/jitter.rs b/vendor/rand/src/jitter.rs
deleted file mode 100644
index 3693481..0000000
--- a/vendor/rand/src/jitter.rs
+++ /dev/null
@@ -1,754 +0,0 @@
-// Copyright 2017 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. 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.
-
-use Rng;
-
-use core::{fmt, mem, ptr};
-#[cfg(feature="std")]
-use std::sync::atomic::{AtomicUsize, ATOMIC_USIZE_INIT, 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.
-///
-/// 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 is orders of magnitude slower than `OsRng`
-/// and PRNGs (about 10^3 .. 10^6 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.
-///
-/// Use of `JitterRng` is recommended for initializing cryptographic PRNGs when
-/// `OsRng` is not available.
-///
-/// This implementation is based on
-/// [Jitterentropy](http://www.chronox.de/jent.html) version 2.1.0.
-//
-// Note: the C implementation relies on being compiled without optimizations.
-// This implementation goes through lengths to make the compiler not optimise
-// out what is technically dead code, but that does influence timing jitter.
-pub struct JitterRng {
-    data: u64, // Actual random number
-    // Number of rounds to run the entropy collector per 64 bits
-    rounds: u32,
-    // Timer and previous time stamp, used by `measure_jitter`
-    timer: fn() -> u64,
-    prev_time: u64,
-    // Deltas used for the stuck test
-    last_delta: i64,
-    last_delta2: i64,
-    // Memory for the Memory Access noise source
-    mem_prev_index: usize,
-    mem: [u8; MEMORY_SIZE],
-    // Make `next_u32` not waste 32 bits
-    data_remaining: Option<u32>,
-}
-
-// 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 {{}}")
-    }
-}
-
-/// An error that can occur when `test_timer` fails.
-#[derive(Debug, Clone, PartialEq, Eq)]
-pub enum TimerError {
-    /// No timer available.
-    NoTimer,
-    /// Timer too coarse to use as an entropy source.
-    CoarseTimer,
-    /// Timer is not monotonically increasing.
-    NotMonotonic,
-    /// Variations of deltas of time too small.
-    TinyVariantions,
-    /// Too many stuck results (indicating no added entropy).
-    TooManyStuck,
-    #[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()
-    }
-}
-
-// Initialise to zero; must be positive
-#[cfg(feature="std")]
-static JITTER_ROUNDS: AtomicUsize = ATOMIC_USIZE_INIT;
-
-impl JitterRng {
-    /// Create a new `JitterRng`.
-    /// Makes use of `std::time` for a timer.
-    ///
-    /// 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(feature="std")]
-    pub fn new() -> Result<JitterRng, TimerError> {
-        let mut ec = JitterRng::new_with_timer(platform::get_nstime);
-        let mut rounds = JITTER_ROUNDS.load(Ordering::Relaxed) as u32;
-        if rounds == 0 {
-            // No result yet: run test.
-            // This allows the timer test to run multiple times; we don't care.
-            rounds = ec.test_timer()?;
-            JITTER_ROUNDS.store(rounds as usize, Ordering::Relaxed);
-        }
-        ec.set_rounds(rounds);
-        Ok(ec)
-    }
-
-    /// 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()`.
-    pub fn new_with_timer(timer: fn() -> u64) -> JitterRng {
-        let mut ec = JitterRng {
-            data: 0,
-            rounds: 64,
-            timer: timer,
-            prev_time: 0,
-            last_delta: 0,
-            last_delta2: 0,
-            mem_prev_index: 0,
-            mem: [0; MEMORY_SIZE],
-            data_remaining: None,
-        };
-
-        // Fill `data`, `prev_time`, `last_delta` and `last_delta2` with
-        // non-zero values.
-        ec.prev_time = timer();
-        ec.gen_entropy();
-
-        // Do a single read from `self.mem` to make sure the Memory Access noise
-        // source is not optimised out.
-        // Note: this read is important, it effects optimisations for the entire
-        // module!
-        black_box(ec.mem[0]);
-
-        ec
-    }
-
-    /// 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.
-    pub fn set_rounds(&mut self, rounds: u32) {
-        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 = 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 = 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, 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;
-        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
-            let tmp = self.mem[index];
-            self.mem[index] = tmp.wrapping_add(1);
-        }
-        self.mem_prev_index = index;
-    }
-
-
-    // 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: i64) -> 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
-    }
-
-    // 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 `self.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) -> Option<()> {
-        // Invoke one noise source before time measurement to add variations
-        self.memaccess(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(self.prev_time) as i64;
-        self.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 self.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 {
-        // Prime `self.prev_time`, and run the noice sources to make sure the
-        // first loop round collects the expected entropy.
-        let _ = self.measure_jitter();
-
-        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().is_none() {}
-        }
-
-        self.stir_pool();
-        self.data
-    }
-
-    /// Basic quality tests on the timer, by measuring CPU timing jitter a few
-    /// hundred times.
-    ///
-    /// If succesful, 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<u32, TimerError> {
-        // 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.
-
-        #[cfg(all(target_arch = "wasm32", not(target_os = "emscripten")))]
-        return Err(TimerError::NoTimer);
-
-        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;
-
-        // 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(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;
-
-            // 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 self.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;
-        }
-
-        // 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`.
-        //
-        // To have smaller rounding errors, intermediate values are multiplied
-        // by `FACTOR`. To compensate for `log2` and division rounding down,
-        // add 1.
-        let delta_average = delta_sum / TESTLOOPCOUNT;
-        // println!("delta_average: {}", delta_average);
-
-        const FACTOR: u32  = 3;
-        fn log2(x: u64) -> u32 { 64 - x.leading_zeros() }
-
-        // pow(δ, FACTOR) must be representable; if you have overflow reduce FACTOR
-        Ok(64 * 2 * FACTOR / (log2(delta_average.pow(FACTOR)) + 1))
-    }
-
-    /// Statistical test: return the timer delta of one normal run of the
-    /// `JitterEntropy` 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
-    /// `JitterEntropy` 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 entropy collector can collect in the worst case.
-    ///
-    /// # Example
-    ///
-    /// Use `timer_stats` to run the [NIST SP 800-90B Entropy Estimation Suite]
-    /// (https://github.com/usnistgov/SP800-90B_EntropyAssessment).
-    ///
-    /// This is the recommended way to test the quality of `JitterRng`. It
-    /// should be run before using the RNG on untested hardware, after changes
-    /// that could effect how the code is optimised, and after major compiler
-    /// compiler changes, like a new LLVM version.
-    ///
-    /// First generate two files `jitter_rng_var.bin` and `jitter_rng_var.min`.
-    ///
-    /// Execute `python noniid_main.py -v jitter_rng_var.bin 8`, and validate it
-    /// with `restart.py -v jitter_rng_var.bin 8 <min-entropy>`.
-    /// This number is the expected amount of entropy that is at least available
-    /// for each round of the entropy collector. This number should be greater
-    /// than the amount estimated with `64 / test_timer()`.
-    ///
-    /// Execute `python noniid_main.py -v -u 4 jitter_rng_var.bin 4`, and
-    /// validate it with `restart.py -v -u 4 jitter_rng_var.bin 4 <min-entropy>`.
-    /// This number is 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.
-    ///
-    /// Execute `python noniid_main.py -v -u 4 jitter_rng_var.bin 4`, and
-    /// validate it with `restart.py -v -u 4 jitter_rng_var.bin 4 <min-entropy>`.
-    /// This number is the expected amount of entropy that is available to the
-    /// entropy collecter if both noice sources only run their minimal number of
-    /// times. This measures the absolute worst-case, and gives a lower bound
-    /// for the available entropy.
-    ///
-    /// ```rust,no_run
-    /// use rand::JitterRng;
-    ///
-    /// # use std::error::Error;
-    /// # use std::fs::File;
-    /// # use std::io::Write;
-    /// #
-    /// # fn try_main() -> Result<(), Box<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
-    /// }
-    ///
-    /// // Do not initialize with `JitterRng::new`, but with `new_with_timer`.
-    /// // 'new' always runst `test_timer`, and can therefore fail to
-    /// // initialize. We want to be able to get the statistics even when the
-    /// // timer test fails.
-    /// let mut rng = JitterRng::new_with_timer(get_nstime);
-    ///
-    /// // 1_000_000 results are required for the NIST SP 800-90B Entropy
-    /// // Estimation Suite
-    /// // FIXME: this number is smaller here, otherwise the Doc-test is too slow
-    /// const ROUNDS: usize = 10_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(())
-    /// # }
-    /// #
-    /// # fn main() {
-    /// #     try_main().unwrap();
-    /// # }
-    /// ```
-    #[cfg(feature="std")]
-    pub fn timer_stats(&mut self, var_rounds: bool) -> i64 {
-        let time = platform::get_nstime();
-        self.memaccess(var_rounds);
-        self.lfsr_time(time, var_rounds);
-        let time2 = platform::get_nstime();
-        time2.wrapping_sub(time) as i64
-    }
-}
-
-#[cfg(feature="std")]
-mod platform {
-    #[cfg(not(any(target_os = "macos", target_os = "ios", target_os = "windows", all(target_arch = "wasm32", not(target_os = "emscripten")))))]
-    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 {
-        extern crate 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 {
-        extern crate winapi;
-        unsafe {
-            let mut t = super::mem::zeroed();
-            winapi::um::profileapi::QueryPerformanceCounter(&mut t);
-            *t.QuadPart() as u64
-        }
-    }
-
-    #[cfg(all(target_arch = "wasm32", not(target_os = "emscripten")))]
-    pub fn get_nstime() -> u64 {
-        unreachable!()
-    }
-}
-
-// 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 Rng for JitterRng {
-    fn next_u32(&mut self) -> u32 {
-        // We want to use both parts of the generated entropy
-        if let Some(high) = self.data_remaining.take() {
-            high
-        } else {
-            let data = self.next_u64();
-            self.data_remaining = Some((data >> 32) as u32);
-            data as u32
-        }
-    }
-
-    fn next_u64(&mut self) -> u64 {
-       self.gen_entropy()
-    }
-
-    fn fill_bytes(&mut self, 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] = unsafe {
-                mem::transmute(self.next_u64().to_le())
-            };
-            l.copy_from_slice(&chunk);
-        }
-        let n = left.len();
-        if n > 0 {
-            let chunk: [u8; 8] = unsafe {
-                mem::transmute(self.next_u64().to_le())
-            };
-            left.copy_from_slice(&chunk[..n]);
-        }
-    }
-}
-
-// There are no tests included because (1) this is an "external" RNG, so output
-// is not reproducible and (2) `test_timer` *will* fail on some platforms.
diff --git a/vendor/rand/src/lib.rs b/vendor/rand/src/lib.rs
deleted file mode 100644
index 696ff6f..0000000
--- a/vendor/rand/src/lib.rs
+++ /dev/null
@@ -1,1220 +0,0 @@
-// Copyright 2013-2017 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Utilities for random number generation
-//!
-//! The key functions are `random()` and `Rng::gen()`. These are polymorphic and
-//! so can be used to generate any type that implements `Rand`. Type inference
-//! means that often a simple call to `rand::random()` or `rng.gen()` will
-//! suffice, but sometimes an annotation is required, e.g.
-//! `rand::random::<f64>()`.
-//!
-//! See the `distributions` submodule for sampling random numbers from
-//! distributions like normal and exponential.
-//!
-//! # Usage
-//!
-//! This crate is [on crates.io](https://crates.io/crates/rand) and can be
-//! used by adding `rand` to the dependencies in your project's `Cargo.toml`.
-//!
-//! ```toml
-//! [dependencies]
-//! rand = "0.4"
-//! ```
-//!
-//! and this to your crate root:
-//!
-//! ```rust
-//! extern crate rand;
-//! ```
-//!
-//! # Thread-local RNG
-//!
-//! There is built-in support for a RNG associated with each thread stored
-//! in thread-local storage. This RNG can be accessed via `thread_rng`, or
-//! used implicitly via `random`. This RNG is normally randomly seeded
-//! from an operating-system source of randomness, e.g. `/dev/urandom` on
-//! Unix systems, and will automatically reseed itself from this source
-//! after generating 32 KiB of random data.
-//!
-//! # Cryptographic security
-//!
-//! An application that requires an entropy source for cryptographic purposes
-//! must use `OsRng`, which reads randomness from the source that the operating
-//! system provides (e.g. `/dev/urandom` on Unixes or `CryptGenRandom()` on
-//! Windows).
-//! The other random number generators provided by this module are not suitable
-//! for such purposes.
-//!
-//! *Note*: many Unix systems provide `/dev/random` as well as `/dev/urandom`.
-//! This module uses `/dev/urandom` for the following reasons:
-//!
-//! -   On Linux, `/dev/random` may block if entropy pool is empty;
-//!     `/dev/urandom` will not block.  This does not mean that `/dev/random`
-//!     provides better output than `/dev/urandom`; the kernel internally runs a
-//!     cryptographically secure pseudorandom number generator (CSPRNG) based on
-//!     entropy pool for random number generation, so the "quality" of
-//!     `/dev/random` is not better than `/dev/urandom` in most cases.  However,
-//!     this means that `/dev/urandom` can yield somewhat predictable randomness
-//!     if the entropy pool is very small, such as immediately after first
-//!     booting.  Linux 3.17 added the `getrandom(2)` system call which solves
-//!     the issue: it blocks if entropy pool is not initialized yet, but it does
-//!     not block once initialized.  `OsRng` tries to use `getrandom(2)` if
-//!     available, and use `/dev/urandom` fallback if not.  If an application
-//!     does not have `getrandom` and likely to be run soon after first booting,
-//!     or on a system with very few entropy sources, one should consider using
-//!     `/dev/random` via `ReadRng`.
-//! -   On some systems (e.g. FreeBSD, OpenBSD and Mac OS X) there is no
-//!     difference between the two sources. (Also note that, on some systems
-//!     e.g.  FreeBSD, both `/dev/random` and `/dev/urandom` may block once if
-//!     the CSPRNG has not seeded yet.)
-//!
-//! # Examples
-//!
-//! ```rust
-//! use rand::Rng;
-//!
-//! let mut rng = rand::thread_rng();
-//! if rng.gen() { // random bool
-//!     println!("i32: {}, u32: {}", rng.gen::<i32>(), rng.gen::<u32>())
-//! }
-//! ```
-//!
-//! ```rust
-//! let tuple = rand::random::<(f64, char)>();
-//! println!("{:?}", tuple)
-//! ```
-//!
-//! ## Monte Carlo estimation of π
-//!
-//! For this example, imagine we have a square with sides of length 2 and a unit
-//! circle, both centered at the origin. Since the area of a unit circle is π,
-//! we have:
-//!
-//! ```text
-//!     (area of unit circle) / (area of square) = π / 4
-//! ```
-//!
-//! So if we sample many points randomly from the square, roughly π / 4 of them
-//! should be inside the circle.
-//!
-//! We can use the above fact to estimate the value of π: pick many points in
-//! the square at random, calculate the fraction that fall within the circle,
-//! and multiply this fraction by 4.
-//!
-//! ```
-//! use rand::distributions::{IndependentSample, Range};
-//!
-//! fn main() {
-//!    let between = Range::new(-1f64, 1.);
-//!    let mut rng = rand::thread_rng();
-//!
-//!    let total = 1_000_000;
-//!    let mut in_circle = 0;
-//!
-//!    for _ in 0..total {
-//!        let a = between.ind_sample(&mut rng);
-//!        let b = between.ind_sample(&mut rng);
-//!        if a*a + b*b <= 1. {
-//!            in_circle += 1;
-//!        }
-//!    }
-//!
-//!    // prints something close to 3.14159...
-//!    println!("{}", 4. * (in_circle as f64) / (total as f64));
-//! }
-//! ```
-//!
-//! ## 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]: http://en.wikipedia.org/wiki/Monty_Hall_problem
-//!
-//! ```
-//! use rand::Rng;
-//! use rand::distributions::{IndependentSample, Range};
-//!
-//! struct SimulationResult {
-//!     win: bool,
-//!     switch: bool,
-//! }
-//!
-//! // Run a single simulation of the Monty Hall problem.
-//! fn simulate<R: Rng>(random_door: &Range<u32>, rng: &mut R)
-//!                     -> SimulationResult {
-//!     let car = random_door.ind_sample(rng);
-//!
-//!     // This is our initial choice
-//!     let mut choice = random_door.ind_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: 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 {
-//!     let choices = free_doors(&[car, choice]);
-//!     rand::seq::sample_slice(rng, &choices, 1)[0]
-//! }
-//!
-//! // 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 = Range::new(0, 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);
-//! }
-//! ```
-
-#![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/0.4")]
-
-#![deny(missing_debug_implementations)]
-
-#![cfg_attr(not(feature="std"), no_std)]
-#![cfg_attr(all(feature="alloc", not(feature="std")), feature(alloc))]
-#![cfg_attr(feature = "i128_support", feature(i128_type, i128))]
-
-#[cfg(feature="std")] extern crate std as core;
-#[cfg(all(feature = "alloc", not(feature="std")))] extern crate alloc;
-
-#[cfg(target_env = "sgx")]
-extern crate rdrand;
-
-#[cfg(target_env = "sgx")]
-extern crate rand_core;
-
-use core::marker;
-use core::mem;
-#[cfg(feature="std")] use std::cell::RefCell;
-#[cfg(feature="std")] use std::io;
-#[cfg(feature="std")] use std::rc::Rc;
-
-// external rngs
-pub use jitter::JitterRng;
-#[cfg(feature="std")] pub use os::OsRng;
-
-// pseudo rngs
-pub use isaac::{IsaacRng, Isaac64Rng};
-pub use chacha::ChaChaRng;
-pub use prng::XorShiftRng;
-
-// local use declarations
-#[cfg(target_pointer_width = "32")]
-use prng::IsaacRng as IsaacWordRng;
-#[cfg(target_pointer_width = "64")]
-use prng::Isaac64Rng as IsaacWordRng;
-
-use distributions::{Range, IndependentSample};
-use distributions::range::SampleRange;
-
-// public modules
-pub mod distributions;
-pub mod jitter;
-#[cfg(feature="std")] pub mod os;
-#[cfg(feature="std")] pub mod read;
-pub mod reseeding;
-#[cfg(any(feature="std", feature = "alloc"))] pub mod seq;
-
-// These tiny modules are here to avoid API breakage, probably only temporarily
-pub mod chacha {
-    //! The ChaCha random number generator.
-    pub use prng::ChaChaRng;
-}
-pub mod isaac {
-    //! The ISAAC random number generator.
-    pub use prng::{IsaacRng, Isaac64Rng};
-}
-
-// private modules
-mod rand_impls;
-mod prng;
-
-
-/// A type that can be randomly generated using an `Rng`.
-///
-/// ## Built-in Implementations
-///
-/// This crate implements `Rand` for various primitive types.  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)`.  (The [`Open01`], [`Closed01`], [`Exp1`], and
-///   [`StandardNormal`] wrapper types produce floating point numbers with
-///   alternative ranges or distributions.)
-///
-/// [`Open01`]: struct.Open01.html
-/// [`Closed01`]: struct.Closed01.html
-/// [`Exp1`]: distributions/exponential/struct.Exp1.html
-/// [`StandardNormal`]: distributions/normal/struct.StandardNormal.html
-///
-/// The following aggregate types also implement `Rand` as long as their
-/// component types implement it:
-///
-/// * Tuples and arrays: Each element of the tuple or array is generated
-///   independently, using its own `Rand` implementation.
-/// * `Option<T>`: Returns `None` with probability 0.5; otherwise generates a
-///   random `T` and returns `Some(T)`.
-pub trait Rand : Sized {
-    /// Generates a random instance of this type using the specified source of
-    /// randomness.
-    fn rand<R: Rng>(rng: &mut R) -> Self;
-}
-
-/// A random number generator.
-pub trait Rng {
-    /// Return the next random u32.
-    ///
-    /// This rarely needs to be called directly, prefer `r.gen()` to
-    /// `r.next_u32()`.
-    // FIXME #rust-lang/rfcs#628: Should be implemented in terms of next_u64
-    fn next_u32(&mut self) -> u32;
-
-    /// Return the next random u64.
-    ///
-    /// By default this is implemented in terms of `next_u32`. An
-    /// implementation of this trait must provide at least one of
-    /// these two methods. Similarly to `next_u32`, this rarely needs
-    /// to be called directly, prefer `r.gen()` to `r.next_u64()`.
-    fn next_u64(&mut self) -> u64 {
-        ((self.next_u32() as u64) << 32) | (self.next_u32() as u64)
-    }
-
-    /// Return the next random f32 selected from the half-open
-    /// interval `[0, 1)`.
-    ///
-    /// This uses a technique described by Saito and Matsumoto at
-    /// MCQMC'08. Given that the IEEE floating point numbers are
-    /// uniformly distributed over [1,2), we generate a number in
-    /// this range and then offset it onto the range [0,1). Our
-    /// choice of bits (masking v. shifting) is arbitrary and
-    /// should be immaterial for high quality generators. For low
-    /// quality generators (ex. LCG), prefer bitshifting due to
-    /// correlation between sequential low order bits.
-    ///
-    /// See:
-    /// A PRNG specialized in double precision floating point numbers using
-    /// an affine transition
-    ///
-    /// * <http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/ARTICLES/dSFMT.pdf>
-    /// * <http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/dSFMT-slide-e.pdf>
-    ///
-    /// By default this is implemented in terms of `next_u32`, but a
-    /// random number generator which can generate numbers satisfying
-    /// the requirements directly can overload this for performance.
-    /// It is required that the return value lies in `[0, 1)`.
-    ///
-    /// See `Closed01` for the closed interval `[0,1]`, and
-    /// `Open01` for the open interval `(0,1)`.
-    fn next_f32(&mut self) -> f32 {
-        const UPPER_MASK: u32 = 0x3F800000;
-        const LOWER_MASK: u32 = 0x7FFFFF;
-        let tmp = UPPER_MASK | (self.next_u32() & LOWER_MASK);
-        let result: f32 = unsafe { mem::transmute(tmp) };
-        result - 1.0
-    }
-
-    /// Return the next random f64 selected from the half-open
-    /// interval `[0, 1)`.
-    ///
-    /// By default this is implemented in terms of `next_u64`, but a
-    /// random number generator which can generate numbers satisfying
-    /// the requirements directly can overload this for performance.
-    /// It is required that the return value lies in `[0, 1)`.
-    ///
-    /// See `Closed01` for the closed interval `[0,1]`, and
-    /// `Open01` for the open interval `(0,1)`.
-    fn next_f64(&mut self) -> f64 {
-        const UPPER_MASK: u64 = 0x3FF0000000000000;
-        const LOWER_MASK: u64 = 0xFFFFFFFFFFFFF;
-        let tmp = UPPER_MASK | (self.next_u64() & LOWER_MASK);
-        let result: f64 = unsafe { mem::transmute(tmp) };
-        result - 1.0
-    }
-
-    /// Fill `dest` with random data.
-    ///
-    /// This has a default implementation in terms of `next_u64` and
-    /// `next_u32`, but should be overridden by implementations that
-    /// offer a more efficient solution than just calling those
-    /// methods repeatedly.
-    ///
-    /// This method does *not* have a requirement to bear any fixed
-    /// relationship to the other methods, for example, it does *not*
-    /// have to result in the same output as progressively filling
-    /// `dest` with `self.gen::<u8>()`, and any such behaviour should
-    /// not be relied upon.
-    ///
-    /// 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).
-    ///
-    /// # Example
-    ///
-    /// ```rust
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let mut v = [0u8; 13579];
-    /// thread_rng().fill_bytes(&mut v);
-    /// println!("{:?}", &v[..]);
-    /// ```
-    fn fill_bytes(&mut self, dest: &mut [u8]) {
-        // this could, in theory, be done by transmuting dest to a
-        // [u64], but this is (1) likely to be undefined behaviour for
-        // LLVM, (2) has to be very careful about alignment concerns,
-        // (3) adds more `unsafe` that needs to be checked, (4)
-        // probably doesn't give much performance gain if
-        // optimisations are on.
-        let mut count = 0;
-        let mut num = 0;
-        for byte in dest.iter_mut() {
-            if count == 0 {
-                // we could micro-optimise here by generating a u32 if
-                // we only need a few more bytes to fill the vector
-                // (i.e. at most 4).
-                num = self.next_u64();
-                count = 8;
-            }
-
-            *byte = (num & 0xff) as u8;
-            num >>= 8;
-            count -= 1;
-        }
-    }
-
-    /// Return a random value of a `Rand` type.
-    ///
-    /// # Example
-    ///
-    /// ```rust
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let mut rng = thread_rng();
-    /// let x: u32 = rng.gen();
-    /// println!("{}", x);
-    /// println!("{:?}", rng.gen::<(f64, bool)>());
-    /// ```
-    #[inline(always)]
-    fn gen<T: Rand>(&mut self) -> T where Self: Sized {
-        Rand::rand(self)
-    }
-
-    /// Return an iterator that will yield an infinite number of randomly
-    /// generated items.
-    ///
-    /// # Example
-    ///
-    /// ```
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let mut rng = thread_rng();
-    /// let x = rng.gen_iter::<u32>().take(10).collect::<Vec<u32>>();
-    /// println!("{:?}", x);
-    /// println!("{:?}", rng.gen_iter::<(f64, bool)>().take(5)
-    ///                     .collect::<Vec<(f64, bool)>>());
-    /// ```
-    fn gen_iter<'a, T: Rand>(&'a mut self) -> Generator<'a, T, Self> where Self: Sized {
-        Generator { rng: self, _marker: marker::PhantomData }
-    }
-
-    /// Generate a random value in the range [`low`, `high`).
-    ///
-    /// This is a convenience wrapper around
-    /// `distributions::Range`. If this function will be called
-    /// repeatedly with the same arguments, one should use `Range`, as
-    /// that will amortize the computations that allow for perfect
-    /// uniformity, as they only happen on initialization.
-    ///
-    /// # Panics
-    ///
-    /// Panics if `low >= high`.
-    ///
-    /// # Example
-    ///
-    /// ```rust
-    /// 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);
-    /// ```
-    fn gen_range<T: PartialOrd + SampleRange>(&mut self, low: T, high: T) -> T where Self: Sized {
-        assert!(low < high, "Rng.gen_range called with low >= high");
-        Range::new(low, high).ind_sample(self)
-    }
-
-    /// Return a bool with a 1 in n chance of true
-    ///
-    /// # Example
-    ///
-    /// ```rust
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let mut rng = thread_rng();
-    /// println!("{}", rng.gen_weighted_bool(3));
-    /// ```
-    fn gen_weighted_bool(&mut self, n: u32) -> bool where Self: Sized {
-        n <= 1 || self.gen_range(0, n) == 0
-    }
-
-    /// Return an iterator of random characters from the set A-Z,a-z,0-9.
-    ///
-    /// # Example
-    ///
-    /// ```rust
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let s: String = thread_rng().gen_ascii_chars().take(10).collect();
-    /// println!("{}", s);
-    /// ```
-    fn gen_ascii_chars<'a>(&'a mut self) -> AsciiGenerator<'a, Self> where Self: Sized {
-        AsciiGenerator { rng: self }
-    }
-
-    /// Return a random element from `values`.
-    ///
-    /// Return `None` if `values` is empty.
-    ///
-    /// # Example
-    ///
-    /// ```
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let choices = [1, 2, 4, 8, 16, 32];
-    /// let mut rng = thread_rng();
-    /// println!("{:?}", rng.choose(&choices));
-    /// assert_eq!(rng.choose(&choices[..0]), None);
-    /// ```
-    fn choose<'a, T>(&mut self, values: &'a [T]) -> Option<&'a T> where Self: Sized {
-        if values.is_empty() {
-            None
-        } else {
-            Some(&values[self.gen_range(0, values.len())])
-        }
-    }
-
-    /// Return a mutable pointer to a random element from `values`.
-    ///
-    /// Return `None` if `values` is empty.
-    fn choose_mut<'a, T>(&mut self, values: &'a mut [T]) -> Option<&'a mut T> where Self: Sized {
-        if values.is_empty() {
-            None
-        } else {
-            let len = values.len();
-            Some(&mut values[self.gen_range(0, len)])
-        }
-    }
-
-    /// Shuffle a mutable slice in place.
-    ///
-    /// This applies Durstenfeld's algorithm for the [Fisher–Yates shuffle](https://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle#The_modern_algorithm)
-    /// which produces an unbiased permutation.
-    ///
-    /// # Example
-    ///
-    /// ```rust
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let mut rng = thread_rng();
-    /// let mut y = [1, 2, 3];
-    /// rng.shuffle(&mut y);
-    /// println!("{:?}", y);
-    /// rng.shuffle(&mut y);
-    /// println!("{:?}", y);
-    /// ```
-    fn shuffle<T>(&mut self, values: &mut [T]) where Self: Sized {
-        let mut i = values.len();
-        while i >= 2 {
-            // invariant: elements with index >= i have been locked in place.
-            i -= 1;
-            // lock element i in place.
-            values.swap(i, self.gen_range(0, i + 1));
-        }
-    }
-}
-
-impl<'a, R: ?Sized> Rng for &'a mut R where R: Rng {
-    fn next_u32(&mut self) -> u32 {
-        (**self).next_u32()
-    }
-
-    fn next_u64(&mut self) -> u64 {
-        (**self).next_u64()
-    }
-
-    fn next_f32(&mut self) -> f32 {
-        (**self).next_f32()
-    }
-
-    fn next_f64(&mut self) -> f64 {
-        (**self).next_f64()
-    }
-
-    fn fill_bytes(&mut self, dest: &mut [u8]) {
-        (**self).fill_bytes(dest)
-    }
-}
-
-#[cfg(feature="std")]
-impl<R: ?Sized> Rng for Box<R> where R: Rng {
-    fn next_u32(&mut self) -> u32 {
-        (**self).next_u32()
-    }
-
-    fn next_u64(&mut self) -> u64 {
-        (**self).next_u64()
-    }
-
-    fn next_f32(&mut self) -> f32 {
-        (**self).next_f32()
-    }
-
-    fn next_f64(&mut self) -> f64 {
-        (**self).next_f64()
-    }
-
-    fn fill_bytes(&mut self, dest: &mut [u8]) {
-        (**self).fill_bytes(dest)
-    }
-}
-
-/// Iterator which will generate a stream of random items.
-///
-/// This iterator is created via the [`gen_iter`] method on [`Rng`].
-///
-/// [`gen_iter`]: trait.Rng.html#method.gen_iter
-/// [`Rng`]: trait.Rng.html
-#[derive(Debug)]
-pub struct Generator<'a, T, R:'a> {
-    rng: &'a mut R,
-    _marker: marker::PhantomData<fn() -> T>,
-}
-
-impl<'a, T: Rand, R: Rng> Iterator for Generator<'a, T, R> {
-    type Item = T;
-
-    fn next(&mut self) -> Option<T> {
-        Some(self.rng.gen())
-    }
-}
-
-/// Iterator which will continuously generate random ascii characters.
-///
-/// This iterator is created via the [`gen_ascii_chars`] method on [`Rng`].
-///
-/// [`gen_ascii_chars`]: trait.Rng.html#method.gen_ascii_chars
-/// [`Rng`]: trait.Rng.html
-#[derive(Debug)]
-pub struct AsciiGenerator<'a, R:'a> {
-    rng: &'a mut R,
-}
-
-impl<'a, R: Rng> Iterator for AsciiGenerator<'a, R> {
-    type Item = char;
-
-    fn next(&mut self) -> Option<char> {
-        const GEN_ASCII_STR_CHARSET: &'static [u8] =
-            b"ABCDEFGHIJKLMNOPQRSTUVWXYZ\
-              abcdefghijklmnopqrstuvwxyz\
-              0123456789";
-        Some(*self.rng.choose(GEN_ASCII_STR_CHARSET).unwrap() as char)
-    }
-}
-
-/// A random number generator that can be explicitly seeded to produce
-/// the same stream of randomness multiple times.
-pub trait SeedableRng<Seed>: Rng {
-    /// Reseed an RNG with the given seed.
-    ///
-    /// # Example
-    ///
-    /// ```rust
-    /// use rand::{Rng, SeedableRng, StdRng};
-    ///
-    /// let seed: &[_] = &[1, 2, 3, 4];
-    /// let mut rng: StdRng = SeedableRng::from_seed(seed);
-    /// println!("{}", rng.gen::<f64>());
-    /// rng.reseed(&[5, 6, 7, 8]);
-    /// println!("{}", rng.gen::<f64>());
-    /// ```
-    fn reseed(&mut self, Seed);
-
-    /// Create a new RNG with the given seed.
-    ///
-    /// # Example
-    ///
-    /// ```rust
-    /// use rand::{Rng, SeedableRng, StdRng};
-    ///
-    /// let seed: &[_] = &[1, 2, 3, 4];
-    /// let mut rng: StdRng = SeedableRng::from_seed(seed);
-    /// println!("{}", rng.gen::<f64>());
-    /// ```
-    fn from_seed(seed: Seed) -> Self;
-}
-
-/// A wrapper for generating floating point numbers uniformly in the
-/// open interval `(0,1)` (not including either endpoint).
-///
-/// Use `Closed01` for the closed interval `[0,1]`, and the default
-/// `Rand` implementation for `f32` and `f64` for the half-open
-/// `[0,1)`.
-///
-/// # Example
-/// ```rust
-/// use rand::{random, Open01};
-///
-/// let Open01(val) = random::<Open01<f32>>();
-/// println!("f32 from (0,1): {}", val);
-/// ```
-#[derive(Debug)]
-pub struct Open01<F>(pub F);
-
-/// A wrapper for generating floating point numbers uniformly in the
-/// closed interval `[0,1]` (including both endpoints).
-///
-/// Use `Open01` for the closed interval `(0,1)`, and the default
-/// `Rand` implementation of `f32` and `f64` for the half-open
-/// `[0,1)`.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::{random, Closed01};
-///
-/// let Closed01(val) = random::<Closed01<f32>>();
-/// println!("f32 from [0,1]: {}", val);
-/// ```
-#[derive(Debug)]
-pub struct Closed01<F>(pub F);
-
-/// The standard RNG. This is designed to be efficient on the current
-/// platform.
-#[derive(Copy, Clone, Debug)]
-pub struct StdRng {
-    rng: IsaacWordRng,
-}
-
-impl StdRng {
-    /// Create a randomly seeded instance of `StdRng`.
-    ///
-    /// This is a very expensive operation as it has to read
-    /// randomness from the operating system and use this in an
-    /// expensive seeding operation. If one is only generating a small
-    /// number of random numbers, or doesn't need the utmost speed for
-    /// generating each number, `thread_rng` and/or `random` may be more
-    /// appropriate.
-    ///
-    /// Reading the randomness from the OS may fail, and any error is
-    /// propagated via the `io::Result` return value.
-    #[cfg(feature="std")]
-    pub fn new() -> io::Result<StdRng> {
-        match OsRng::new() {
-            Ok(mut r) => Ok(StdRng { rng: r.gen() }),
-            Err(e1) => {
-                match JitterRng::new() {
-                    Ok(mut r) => Ok(StdRng { rng: r.gen() }),
-                    Err(_) => {
-                        Err(e1)
-                    }
-                }
-            }
-        }
-    }
-}
-
-impl Rng for StdRng {
-    #[inline]
-    fn next_u32(&mut self) -> u32 {
-        self.rng.next_u32()
-    }
-
-    #[inline]
-    fn next_u64(&mut self) -> u64 {
-        self.rng.next_u64()
-    }
-}
-
-impl<'a> SeedableRng<&'a [usize]> for StdRng {
-    fn reseed(&mut self, seed: &'a [usize]) {
-        // the internal RNG can just be seeded from the above
-        // randomness.
-        self.rng.reseed(unsafe {mem::transmute(seed)})
-    }
-
-    fn from_seed(seed: &'a [usize]) -> StdRng {
-        StdRng { rng: SeedableRng::from_seed(unsafe {mem::transmute(seed)}) }
-    }
-}
-
-/// Create a weak random number generator with a default algorithm and seed.
-///
-/// It returns the fastest `Rng` algorithm currently available in Rust without
-/// consideration for cryptography or security. If you require a specifically
-/// seeded `Rng` for consistency over time you should pick one algorithm and
-/// create the `Rng` yourself.
-///
-/// This will seed the generator with randomness from thread_rng.
-#[cfg(feature="std")]
-pub fn weak_rng() -> XorShiftRng {
-    thread_rng().gen()
-}
-
-/// Controls how the thread-local RNG is reseeded.
-#[cfg(feature="std")]
-#[derive(Debug)]
-struct ThreadRngReseeder;
-
-#[cfg(feature="std")]
-impl reseeding::Reseeder<StdRng> for ThreadRngReseeder {
-    fn reseed(&mut self, rng: &mut StdRng) {
-        match StdRng::new() {
-            Ok(r) => *rng = r,
-            Err(e) => panic!("No entropy available: {}", e),
-        }
-    }
-}
-#[cfg(feature="std")]
-const THREAD_RNG_RESEED_THRESHOLD: u64 = 32_768;
-#[cfg(feature="std")]
-type ThreadRngInner = reseeding::ReseedingRng<StdRng, ThreadRngReseeder>;
-
-/// The thread-local RNG.
-#[cfg(feature="std")]
-#[derive(Clone, Debug)]
-pub struct ThreadRng {
-    rng: Rc<RefCell<ThreadRngInner>>,
-}
-
-/// 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>()`.
-///
-/// After generating a certain amount of randomness, the RNG will reseed itself
-/// from the operating system or, if the operating system RNG returns an error,
-/// a seed based on the current system time.
-///
-/// The internal RNG used is platform and architecture dependent, even
-/// if the operating system random number generator is rigged to give
-/// the same sequence always. If absolute consistency is required,
-/// explicitly select an RNG, e.g. `IsaacRng` or `Isaac64Rng`.
-#[cfg(feature="std")]
-pub fn thread_rng() -> ThreadRng {
-    // used to make space in TLS for a random number generator
-    thread_local!(static THREAD_RNG_KEY: Rc<RefCell<ThreadRngInner>> = {
-        let r = match StdRng::new() {
-            Ok(r) => r,
-            Err(e) => panic!("No entropy available: {}", e),
-        };
-        let rng = reseeding::ReseedingRng::new(r,
-                                               THREAD_RNG_RESEED_THRESHOLD,
-                                               ThreadRngReseeder);
-        Rc::new(RefCell::new(rng))
-    });
-
-    ThreadRng { rng: THREAD_RNG_KEY.with(|t| t.clone()) }
-}
-
-#[cfg(feature="std")]
-impl Rng for ThreadRng {
-    fn next_u32(&mut self) -> u32 {
-        self.rng.borrow_mut().next_u32()
-    }
-
-    fn next_u64(&mut self) -> u64 {
-        self.rng.borrow_mut().next_u64()
-    }
-
-    #[inline]
-    fn fill_bytes(&mut self, bytes: &mut [u8]) {
-        self.rng.borrow_mut().fill_bytes(bytes)
-    }
-}
-
-/// Generates a random value using the thread-local random number generator.
-///
-/// `random()` can generate various types of random things, and so may require
-/// type hinting to generate the specific type you want.
-///
-/// This function uses the thread local random number generator. This means
-/// that if you're calling `random()` in a loop, caching the generator can
-/// increase performance. An example is shown below.
-///
-/// # 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!");
-/// }
-/// ```
-///
-/// Caching the thread local random number generator:
-///
-/// ```
-/// 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();
-/// }
-/// ```
-#[cfg(feature="std")]
-#[inline]
-pub fn random<T: Rand>() -> T {
-    thread_rng().gen()
-}
-
-/// DEPRECATED: use `seq::sample_iter` instead.
-///
-/// Randomly sample up to `amount` elements from a finite iterator.
-/// The order of elements in the sample is not random.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::{thread_rng, sample};
-///
-/// let mut rng = thread_rng();
-/// let sample = sample(&mut rng, 1..100, 5);
-/// println!("{:?}", sample);
-/// ```
-#[cfg(feature="std")]
-#[inline(always)]
-#[deprecated(since="0.4.0", note="renamed to seq::sample_iter")]
-pub fn sample<T, I, R>(rng: &mut R, iterable: I, amount: usize) -> Vec<T>
-    where I: IntoIterator<Item=T>,
-          R: Rng,
-{
-    // the legacy sample didn't care whether amount was met
-    seq::sample_iter(rng, iterable, amount)
-        .unwrap_or_else(|e| e)
-}
-
-#[cfg(test)]
-mod test {
-    use super::{Rng, thread_rng, random, SeedableRng, StdRng, weak_rng};
-    use std::iter::repeat;
-
-    pub struct MyRng<R> { inner: R }
-
-    impl<R: Rng> Rng for MyRng<R> {
-        fn next_u32(&mut self) -> u32 {
-            fn next<T: Rng>(t: &mut T) -> u32 {
-                t.next_u32()
-            }
-            next(&mut self.inner)
-        }
-    }
-
-    pub fn rng() -> MyRng<::ThreadRng> {
-        MyRng { inner: ::thread_rng() }
-    }
-
-    struct ConstRng { i: u64 }
-    impl Rng for ConstRng {
-        fn next_u32(&mut self) -> u32 { self.i as u32 }
-        fn next_u64(&mut self) -> u64 { self.i }
-
-        // no fill_bytes on purpose
-    }
-
-    pub fn iter_eq<I, J>(i: I, j: J) -> bool
-        where I: IntoIterator,
-              J: IntoIterator<Item=I::Item>,
-              I::Item: Eq
-    {
-        // make sure the iterators have equal length
-        let mut i = i.into_iter();
-        let mut j = j.into_iter();
-        loop {
-            match (i.next(), j.next()) {
-                (Some(ref ei), Some(ref ej)) if ei == ej => { }
-                (None, None) => return true,
-                _ => return false,
-            }
-        }
-    }
-
-    #[test]
-    fn test_fill_bytes_default() {
-        let mut r = ConstRng { i: 0x11_22_33_44_55_66_77_88 };
-
-        // 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 v = repeat(0u8).take(n).collect::<Vec<_>>();
-            r.fill_bytes(&mut 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_gen_range() {
-        let mut r = thread_rng();
-        for _ in 0..1000 {
-            let a = r.gen_range(-3, 42);
-            assert!(a >= -3 && a < 42);
-            assert_eq!(r.gen_range(0, 1), 0);
-            assert_eq!(r.gen_range(-12, -11), -12);
-        }
-
-        for _ in 0..1000 {
-            let a = r.gen_range(10, 42);
-            assert!(a >= 10 && a < 42);
-            assert_eq!(r.gen_range(0, 1), 0);
-            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 = thread_rng();
-        r.gen_range(5, -2);
-    }
-
-    #[test]
-    #[should_panic]
-    fn test_gen_range_panic_usize() {
-        let mut r = thread_rng();
-        r.gen_range(5, 2);
-    }
-
-    #[test]
-    fn test_gen_weighted_bool() {
-        let mut r = thread_rng();
-        assert_eq!(r.gen_weighted_bool(0), true);
-        assert_eq!(r.gen_weighted_bool(1), true);
-    }
-
-    #[test]
-    fn test_gen_ascii_str() {
-        let mut r = thread_rng();
-        assert_eq!(r.gen_ascii_chars().take(0).count(), 0);
-        assert_eq!(r.gen_ascii_chars().take(10).count(), 10);
-        assert_eq!(r.gen_ascii_chars().take(16).count(), 16);
-    }
-
-    #[test]
-    fn test_gen_vec() {
-        let mut r = thread_rng();
-        assert_eq!(r.gen_iter::<u8>().take(0).count(), 0);
-        assert_eq!(r.gen_iter::<u8>().take(10).count(), 10);
-        assert_eq!(r.gen_iter::<f64>().take(16).count(), 16);
-    }
-
-    #[test]
-    fn test_choose() {
-        let mut r = thread_rng();
-        assert_eq!(r.choose(&[1, 1, 1]).map(|&x|x), Some(1));
-
-        let v: &[isize] = &[];
-        assert_eq!(r.choose(v), None);
-    }
-
-    #[test]
-    fn test_shuffle() {
-        let mut r = thread_rng();
-        let empty: &mut [isize] = &mut [];
-        r.shuffle(empty);
-        let mut one = [1];
-        r.shuffle(&mut one);
-        let b: &[_] = &[1];
-        assert_eq!(one, b);
-
-        let mut two = [1, 2];
-        r.shuffle(&mut two);
-        assert!(two == [1, 2] || two == [2, 1]);
-
-        let mut x = [1, 1, 1];
-        r.shuffle(&mut x);
-        let b: &[_] = &[1, 1, 1];
-        assert_eq!(x, b);
-    }
-
-    #[test]
-    fn test_thread_rng() {
-        let mut r = thread_rng();
-        r.gen::<i32>();
-        let mut v = [1, 1, 1];
-        r.shuffle(&mut v);
-        let b: &[_] = &[1, 1, 1];
-        assert_eq!(v, b);
-        assert_eq!(r.gen_range(0, 1), 0);
-    }
-
-    #[test]
-    fn test_rng_trait_object() {
-        let mut rng = thread_rng();
-        {
-            let mut r = &mut rng as &mut Rng;
-            r.next_u32();
-            (&mut r).gen::<i32>();
-            let mut v = [1, 1, 1];
-            (&mut r).shuffle(&mut v);
-            let b: &[_] = &[1, 1, 1];
-            assert_eq!(v, b);
-            assert_eq!((&mut r).gen_range(0, 1), 0);
-        }
-        {
-            let mut r = Box::new(rng) as Box<Rng>;
-            r.next_u32();
-            r.gen::<i32>();
-            let mut v = [1, 1, 1];
-            r.shuffle(&mut v);
-            let b: &[_] = &[1, 1, 1];
-            assert_eq!(v, b);
-            assert_eq!(r.gen_range(0, 1), 0);
-        }
-    }
-
-    #[test]
-    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]
-    fn test_std_rng_seeded() {
-        let s = thread_rng().gen_iter::<usize>().take(256).collect::<Vec<usize>>();
-        let mut ra: StdRng = SeedableRng::from_seed(&s[..]);
-        let mut rb: StdRng = SeedableRng::from_seed(&s[..]);
-        assert!(iter_eq(ra.gen_ascii_chars().take(100),
-                        rb.gen_ascii_chars().take(100)));
-    }
-
-    #[test]
-    fn test_std_rng_reseed() {
-        let s = thread_rng().gen_iter::<usize>().take(256).collect::<Vec<usize>>();
-        let mut r: StdRng = SeedableRng::from_seed(&s[..]);
-        let string1 = r.gen_ascii_chars().take(100).collect::<String>();
-
-        r.reseed(&s);
-
-        let string2 = r.gen_ascii_chars().take(100).collect::<String>();
-        assert_eq!(string1, string2);
-    }
-
-    #[test]
-    fn test_weak_rng() {
-        let s = weak_rng().gen_iter::<usize>().take(256).collect::<Vec<usize>>();
-        let mut ra: StdRng = SeedableRng::from_seed(&s[..]);
-        let mut rb: StdRng = SeedableRng::from_seed(&s[..]);
-        assert!(iter_eq(ra.gen_ascii_chars().take(100),
-                        rb.gen_ascii_chars().take(100)));
-    }
-}
diff --git a/vendor/rand/src/os.rs b/vendor/rand/src/os.rs
deleted file mode 100644
index c33a8cb..0000000
--- a/vendor/rand/src/os.rs
+++ /dev/null
@@ -1,656 +0,0 @@
-// Copyright 2013-2015 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Interfaces to the operating system provided random number
-//! generators.
-
-use std::{io, fmt};
-
-#[cfg(not(target_env = "sgx"))]
-use std::mem;
-
-use Rng;
-
-/// A random number generator that retrieves randomness straight from
-/// the operating system. Platform sources:
-///
-/// - Unix-like systems (Linux, Android, Mac OSX): read directly from
-///   `/dev/urandom`, or from `getrandom(2)` system call if available.
-/// - OpenBSD: calls `getentropy(2)`
-/// - FreeBSD: uses the `kern.arandom` `sysctl(2)` mib
-/// - Windows: calls `RtlGenRandom`, exported from `advapi32.dll` as
-///   `SystemFunction036`.
-/// - iOS: calls SecRandomCopyBytes as /dev/(u)random is sandboxed.
-/// - PNaCl: calls into the `nacl-irt-random-0.1` IRT interface.
-///
-/// This usually does not block. On some systems (e.g. FreeBSD, OpenBSD,
-/// Max OS X, and modern Linux) this may block very early in the init
-/// process, if the CSPRNG has not been seeded yet.[1]
-///
-/// [1] See <https://www.python.org/dev/peps/pep-0524/> for a more
-///     in-depth discussion.
-pub struct OsRng(imp::OsRng);
-
-impl OsRng {
-    /// Create a new `OsRng`.
-    pub fn new() -> io::Result<OsRng> {
-        imp::OsRng::new().map(OsRng)
-    }
-}
-
-impl Rng for OsRng {
-    fn next_u32(&mut self) -> u32 { self.0.next_u32() }
-    fn next_u64(&mut self) -> u64 { self.0.next_u64() }
-    fn fill_bytes(&mut self, v: &mut [u8]) { self.0.fill_bytes(v) }
-}
-
-impl fmt::Debug for OsRng {
-    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
-        write!(f, "OsRng {{}}")
-    }
-}
-
-#[cfg(not(target_env = "sgx"))]
-fn next_u32(fill_buf: &mut FnMut(&mut [u8])) -> u32 {
-    let mut buf: [u8; 4] = [0; 4];
-    fill_buf(&mut buf);
-    unsafe { mem::transmute::<[u8; 4], u32>(buf) }
-}
-
-#[cfg(not(target_env = "sgx"))]
-fn next_u64(fill_buf: &mut FnMut(&mut [u8])) -> u64 {
-    let mut buf: [u8; 8] = [0; 8];
-    fill_buf(&mut buf);
-    unsafe { mem::transmute::<[u8; 8], u64>(buf) }
-}
-
-#[cfg(all(unix, not(target_os = "ios"),
-          not(target_os = "nacl"),
-          not(target_os = "freebsd"),
-          not(target_os = "fuchsia"),
-          not(target_os = "openbsd"),
-          not(target_os = "redox")))]
-mod imp {
-    extern crate libc;
-
-    use super::{next_u32, next_u64};
-    use self::OsRngInner::*;
-
-    use std::io;
-    use std::fs::File;
-    use Rng;
-    use read::ReadRng;
-
-    #[cfg(all(target_os = "linux",
-              any(target_arch = "x86_64",
-                  target_arch = "x86",
-                  target_arch = "arm",
-                  target_arch = "aarch64",
-                  target_arch = "powerpc")))]
-    fn getrandom(buf: &mut [u8]) -> libc::c_long {
-        extern "C" {
-            fn syscall(number: libc::c_long, ...) -> libc::c_long;
-        }
-
-        #[cfg(target_arch = "x86_64")]
-        const NR_GETRANDOM: libc::c_long = 318;
-        #[cfg(target_arch = "x86")]
-        const NR_GETRANDOM: libc::c_long = 355;
-        #[cfg(target_arch = "arm")]
-        const NR_GETRANDOM: libc::c_long = 384;
-        #[cfg(target_arch = "aarch64")]
-        const NR_GETRANDOM: libc::c_long = 278;
-        #[cfg(target_arch = "powerpc")]
-        const NR_GETRANDOM: libc::c_long = 359;
-
-        unsafe {
-            syscall(NR_GETRANDOM, buf.as_mut_ptr(), buf.len(), 0)
-        }
-    }
-
-    #[cfg(not(all(target_os = "linux",
-                  any(target_arch = "x86_64",
-                      target_arch = "x86",
-                      target_arch = "arm",
-                      target_arch = "aarch64",
-                      target_arch = "powerpc"))))]
-    fn getrandom(_buf: &mut [u8]) -> libc::c_long { -1 }
-
-    fn getrandom_fill_bytes(v: &mut [u8]) {
-        let mut read = 0;
-        let len = v.len();
-        while read < len {
-            let result = getrandom(&mut v[read..]);
-            if result == -1 {
-                let err = io::Error::last_os_error();
-                if err.kind() == io::ErrorKind::Interrupted {
-                    continue
-                } else {
-                    panic!("unexpected getrandom error: {}", err);
-                }
-            } else {
-                read += result as usize;
-            }
-        }
-    }
-
-    #[cfg(all(target_os = "linux",
-              any(target_arch = "x86_64",
-                  target_arch = "x86",
-                  target_arch = "arm",
-                  target_arch = "aarch64",
-                  target_arch = "powerpc")))]
-    fn is_getrandom_available() -> bool {
-        use std::sync::atomic::{AtomicBool, ATOMIC_BOOL_INIT, Ordering};
-        use std::sync::{Once, ONCE_INIT};
-
-        static CHECKER: Once = ONCE_INIT;
-        static AVAILABLE: AtomicBool = ATOMIC_BOOL_INIT;
-
-        CHECKER.call_once(|| {
-            let mut buf: [u8; 0] = [];
-            let result = getrandom(&mut buf);
-            let available = if result == -1 {
-                let err = io::Error::last_os_error().raw_os_error();
-                err != Some(libc::ENOSYS)
-            } else {
-                true
-            };
-            AVAILABLE.store(available, Ordering::Relaxed);
-        });
-
-        AVAILABLE.load(Ordering::Relaxed)
-    }
-
-    #[cfg(not(all(target_os = "linux",
-                  any(target_arch = "x86_64",
-                      target_arch = "x86",
-                      target_arch = "arm",
-                      target_arch = "aarch64",
-                      target_arch = "powerpc"))))]
-    fn is_getrandom_available() -> bool { false }
-
-    pub struct OsRng {
-        inner: OsRngInner,
-    }
-
-    enum OsRngInner {
-        OsGetrandomRng,
-        OsReadRng(ReadRng<File>),
-    }
-
-    impl OsRng {
-        pub fn new() -> io::Result<OsRng> {
-            if is_getrandom_available() {
-                return Ok(OsRng { inner: OsGetrandomRng });
-            }
-
-            let reader = try!(File::open("/dev/urandom"));
-            let reader_rng = ReadRng::new(reader);
-
-            Ok(OsRng { inner: OsReadRng(reader_rng) })
-        }
-    }
-
-    impl Rng for OsRng {
-        fn next_u32(&mut self) -> u32 {
-            match self.inner {
-                OsGetrandomRng => next_u32(&mut getrandom_fill_bytes),
-                OsReadRng(ref mut rng) => rng.next_u32(),
-            }
-        }
-        fn next_u64(&mut self) -> u64 {
-            match self.inner {
-                OsGetrandomRng => next_u64(&mut getrandom_fill_bytes),
-                OsReadRng(ref mut rng) => rng.next_u64(),
-            }
-        }
-        fn fill_bytes(&mut self, v: &mut [u8]) {
-            match self.inner {
-                OsGetrandomRng => getrandom_fill_bytes(v),
-                OsReadRng(ref mut rng) => rng.fill_bytes(v)
-            }
-        }
-    }
-}
-
-#[cfg(target_os = "ios")]
-mod imp {
-    extern crate libc;
-
-    use super::{next_u32, next_u64};
-
-    use std::io;
-    use Rng;
-    use self::libc::{c_int, size_t};
-
-    #[derive(Debug)]
-    pub struct OsRng;
-
-    enum SecRandom {}
-
-    #[allow(non_upper_case_globals)]
-    const kSecRandomDefault: *const SecRandom = 0 as *const SecRandom;
-
-    #[link(name = "Security", kind = "framework")]
-    extern {
-        fn SecRandomCopyBytes(rnd: *const SecRandom,
-                              count: size_t, bytes: *mut u8) -> c_int;
-    }
-
-    impl OsRng {
-        pub fn new() -> io::Result<OsRng> {
-            Ok(OsRng)
-        }
-    }
-
-    impl Rng for OsRng {
-        fn next_u32(&mut self) -> u32 {
-            next_u32(&mut |v| self.fill_bytes(v))
-        }
-        fn next_u64(&mut self) -> u64 {
-            next_u64(&mut |v| self.fill_bytes(v))
-        }
-        fn fill_bytes(&mut self, v: &mut [u8]) {
-            let ret = unsafe {
-                SecRandomCopyBytes(kSecRandomDefault, v.len() as size_t, v.as_mut_ptr())
-            };
-            if ret == -1 {
-                panic!("couldn't generate random bytes: {}", io::Error::last_os_error());
-            }
-        }
-    }
-}
-
-#[cfg(target_os = "freebsd")]
-mod imp {
-    extern crate libc;
-
-    use std::{io, ptr};
-    use Rng;
-
-    use super::{next_u32, next_u64};
-
-    #[derive(Debug)]
-    pub struct OsRng;
-
-    impl OsRng {
-        pub fn new() -> io::Result<OsRng> {
-            Ok(OsRng)
-        }
-    }
-
-    impl Rng for OsRng {
-        fn next_u32(&mut self) -> u32 {
-            next_u32(&mut |v| self.fill_bytes(v))
-        }
-        fn next_u64(&mut self) -> u64 {
-            next_u64(&mut |v| self.fill_bytes(v))
-        }
-        fn fill_bytes(&mut self, v: &mut [u8]) {
-            let mib = [libc::CTL_KERN, libc::KERN_ARND];
-            // kern.arandom permits a maximum buffer size of 256 bytes
-            for s in v.chunks_mut(256) {
-                let mut s_len = s.len();
-                let ret = unsafe {
-                    libc::sysctl(mib.as_ptr(), mib.len() as libc::c_uint,
-                                 s.as_mut_ptr() as *mut _, &mut s_len,
-                                 ptr::null(), 0)
-                };
-                if ret == -1 || s_len != s.len() {
-                    panic!("kern.arandom sysctl failed! (returned {}, s.len() {}, oldlenp {})",
-                           ret, s.len(), s_len);
-                }
-            }
-        }
-    }
-}
-
-#[cfg(target_os = "openbsd")]
-mod imp {
-    extern crate libc;
-
-    use std::io;
-    use Rng;
-
-    use super::{next_u32, next_u64};
-
-    #[derive(Debug)]
-    pub struct OsRng;
-
-    impl OsRng {
-        pub fn new() -> io::Result<OsRng> {
-            Ok(OsRng)
-        }
-    }
-
-    impl Rng for OsRng {
-        fn next_u32(&mut self) -> u32 {
-            next_u32(&mut |v| self.fill_bytes(v))
-        }
-        fn next_u64(&mut self) -> u64 {
-            next_u64(&mut |v| self.fill_bytes(v))
-        }
-        fn fill_bytes(&mut self, v: &mut [u8]) {
-            // getentropy(2) permits a maximum buffer size of 256 bytes
-            for s in v.chunks_mut(256) {
-                let ret = unsafe {
-                    libc::getentropy(s.as_mut_ptr() as *mut libc::c_void, s.len())
-                };
-                if ret == -1 {
-                    let err = io::Error::last_os_error();
-                    panic!("getentropy failed: {}", err);
-                }
-            }
-        }
-    }
-}
-
-#[cfg(target_os = "redox")]
-mod imp {
-    use std::io;
-    use std::fs::File;
-    use Rng;
-    use read::ReadRng;
-
-    #[derive(Debug)]
-    pub struct OsRng {
-        inner: ReadRng<File>,
-    }
-
-    impl OsRng {
-        pub fn new() -> io::Result<OsRng> {
-            let reader = try!(File::open("rand:"));
-            let reader_rng = ReadRng::new(reader);
-
-            Ok(OsRng { inner: reader_rng })
-        }
-    }
-
-    impl Rng for OsRng {
-        fn next_u32(&mut self) -> u32 {
-            self.inner.next_u32()
-        }
-        fn next_u64(&mut self) -> u64 {
-            self.inner.next_u64()
-        }
-        fn fill_bytes(&mut self, v: &mut [u8]) {
-            self.inner.fill_bytes(v)
-        }
-    }
-}
-
-#[cfg(target_os = "fuchsia")]
-mod imp {
-    extern crate fuchsia_cprng;
-
-    use std::io;
-    use Rng;
-
-    use super::{next_u32, next_u64};
-
-    #[derive(Debug)]
-    pub struct OsRng;
-
-    impl OsRng {
-        pub fn new() -> io::Result<OsRng> {
-            Ok(OsRng)
-        }
-    }
-
-    impl Rng for OsRng {
-        fn next_u32(&mut self) -> u32 {
-            next_u32(&mut |v| self.fill_bytes(v))
-        }
-        fn next_u64(&mut self) -> u64 {
-            next_u64(&mut |v| self.fill_bytes(v))
-        }
-        fn fill_bytes(&mut self, v: &mut [u8]) {
-            fuchsia_cprng::cprng_draw(v);
-        }
-    }
-}
-
-#[cfg(windows)]
-mod imp {
-    extern crate winapi;
-
-    use std::io;
-    use Rng;
-
-    use super::{next_u32, next_u64};
-
-    use self::winapi::shared::minwindef::ULONG;
-    use self::winapi::um::ntsecapi::RtlGenRandom;
-    use self::winapi::um::winnt::PVOID;
-
-    #[derive(Debug)]
-    pub struct OsRng;
-
-    impl OsRng {
-        pub fn new() -> io::Result<OsRng> {
-            Ok(OsRng)
-        }
-    }
-
-    impl Rng for OsRng {
-        fn next_u32(&mut self) -> u32 {
-            next_u32(&mut |v| self.fill_bytes(v))
-        }
-        fn next_u64(&mut self) -> u64 {
-            next_u64(&mut |v| self.fill_bytes(v))
-        }
-        fn fill_bytes(&mut self, v: &mut [u8]) {
-            // RtlGenRandom takes an ULONG (u32) for the length so we need to
-            // split up the buffer.
-            for slice in v.chunks_mut(<ULONG>::max_value() as usize) {
-                let ret = unsafe {
-                    RtlGenRandom(slice.as_mut_ptr() as PVOID, slice.len() as ULONG)
-                };
-                if ret == 0 {
-                    panic!("couldn't generate random bytes: {}",
-                           io::Error::last_os_error());
-                }
-            }
-        }
-    }
-}
-
-#[cfg(target_os = "nacl")]
-mod imp {
-    extern crate libc;
-
-    use std::io;
-    use std::mem;
-    use Rng;
-
-    use super::{next_u32, next_u64};
-
-    #[derive(Debug)]
-    pub struct OsRng(extern fn(dest: *mut libc::c_void,
-                               bytes: libc::size_t,
-                               read: *mut libc::size_t) -> libc::c_int);
-
-    extern {
-        fn nacl_interface_query(name: *const libc::c_char,
-                                table: *mut libc::c_void,
-                                table_size: libc::size_t) -> libc::size_t;
-    }
-
-    const INTERFACE: &'static [u8] = b"nacl-irt-random-0.1\0";
-
-    #[repr(C)]
-    struct NaClIRTRandom {
-        get_random_bytes: Option<extern fn(dest: *mut libc::c_void,
-                                           bytes: libc::size_t,
-                                           read: *mut libc::size_t) -> libc::c_int>,
-    }
-
-    impl OsRng {
-        pub fn new() -> io::Result<OsRng> {
-            let mut iface = NaClIRTRandom {
-                get_random_bytes: None,
-            };
-            let result = unsafe {
-                nacl_interface_query(INTERFACE.as_ptr() as *const _,
-                                     mem::transmute(&mut iface),
-                                     mem::size_of::<NaClIRTRandom>() as libc::size_t)
-            };
-            if result != 0 {
-                assert!(iface.get_random_bytes.is_some());
-                let result = OsRng(iface.get_random_bytes.take().unwrap());
-                Ok(result)
-            } else {
-                let error = io::ErrorKind::NotFound;
-                let error = io::Error::new(error, "IRT random interface missing");
-                Err(error)
-            }
-        }
-    }
-
-    impl Rng for OsRng {
-        fn next_u32(&mut self) -> u32 {
-            next_u32(&mut |v| self.fill_bytes(v))
-        }
-        fn next_u64(&mut self) -> u64 {
-            next_u64(&mut |v| self.fill_bytes(v))
-        }
-        fn fill_bytes(&mut self, v: &mut [u8]) {
-            let mut read = 0;
-            loop {
-                let mut r: libc::size_t = 0;
-                let len = v.len();
-                let error = (self.0)(v[read..].as_mut_ptr() as *mut _,
-                                     (len - read) as libc::size_t,
-                                     &mut r as *mut _);
-                assert!(error == 0, "`get_random_bytes` failed!");
-                read += r as usize;
-
-                if read >= v.len() { break; }
-            }
-        }
-    }
-}
-
-#[cfg(all(target_arch = "wasm32", not(target_os = "emscripten")))]
-mod imp {
-    use std::io;
-    use Rng;
-
-    #[derive(Debug)]
-    pub struct OsRng;
-
-    impl OsRng {
-        pub fn new() -> io::Result<OsRng> {
-            Err(io::Error::new(io::ErrorKind::Other, "Not supported"))
-        }
-    }
-
-    impl Rng for OsRng {
-        fn next_u32(&mut self) -> u32 {
-            panic!("Not supported")
-        }
-    }
-}
-
-#[cfg(target_env = "sgx")]
-mod imp {
-    use rdrand::RdRand;
-    use std::io;
-    use rand_core::RngCore;
-
-    pub struct OsRng{
-        gen: RdRand
-    }
-
-    impl OsRng {
-        pub fn new() -> io::Result<OsRng> {
-            match RdRand::new() {
-                Ok(rng) => Ok(OsRng { gen: rng }),
-                Err(_) => Err(io::Error::new(io::ErrorKind::Other, "Not supported"))
-            }
-        }
-
-        pub(crate) fn next_u32(&mut self) -> u32 {
-            match self.gen.try_next_u32() {
-                Some(n) => n,
-                None => panic!("Non-recoverable hardware failure has occured")
-            }
-        }
-
-        pub(crate) fn next_u64(&mut self) -> u64 {
-            match self.gen.try_next_u64() {
-                Some(n) => n,
-                None => panic!("Non-recoverable hardware failure has occured")
-            }
-        }
-
-        pub(crate) fn fill_bytes(&mut self, v: &mut [u8]) {
-            match self.gen.try_fill_bytes(v) {
-                Ok(_) => {},
-                Err(_) => panic!("Non-recoverable hardware failure has occured")
-            }
-        }
-    }
-}
-
-#[cfg(test)]
-mod test {
-    use std::sync::mpsc::channel;
-    use Rng;
-    use OsRng;
-    use std::thread;
-
-    #[test]
-    fn test_os_rng() {
-        let mut r = OsRng::new().unwrap();
-
-        r.next_u32();
-        r.next_u64();
-
-        let mut v = [0u8; 1000];
-        r.fill_bytes(&mut v);
-    }
-
-    #[test]
-    fn test_os_rng_tasks() {
-
-        let mut txs = vec!();
-        for _ in 0..20 {
-            let (tx, rx) = channel();
-            txs.push(tx);
-
-            thread::spawn(move|| {
-                // wait until all the tasks are ready to go.
-                rx.recv().unwrap();
-
-                // deschedule to attempt to interleave things as much
-                // as possible (XXX: is this a good test?)
-                let mut r = OsRng::new().unwrap();
-                thread::yield_now();
-                let mut v = [0u8; 1000];
-
-                for _ in 0..100 {
-                    r.next_u32();
-                    thread::yield_now();
-                    r.next_u64();
-                    thread::yield_now();
-                    r.fill_bytes(&mut v);
-                    thread::yield_now();
-                }
-            });
-        }
-
-        // start all the tasks
-        for tx in txs.iter() {
-            tx.send(()).unwrap();
-        }
-    }
-}
diff --git a/vendor/rand/src/prng/chacha.rs b/vendor/rand/src/prng/chacha.rs
deleted file mode 100644
index a73e8e7..0000000
--- a/vendor/rand/src/prng/chacha.rs
+++ /dev/null
@@ -1,321 +0,0 @@
-// Copyright 2014 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The ChaCha random number generator.
-
-use core::num::Wrapping as w;
-use {Rng, SeedableRng, Rand};
-
-#[allow(bad_style)]
-type w32 = w<u32>;
-
-const KEY_WORDS    : usize =  8; // 8 words for the 256-bit key
-const STATE_WORDS  : usize = 16;
-const CHACHA_ROUNDS: u32 = 20; // Cryptographically secure from 8 upwards as of this writing
-
-/// A random number generator that uses the ChaCha20 algorithm [1].
-///
-/// The ChaCha algorithm is widely accepted as suitable for
-/// cryptographic purposes, but this implementation has not been
-/// verified as such. Prefer a generator like `OsRng` that defers to
-/// the operating system for cases that need high security.
-///
-/// [1]: D. J. Bernstein, [*ChaCha, a variant of
-/// Salsa20*](http://cr.yp.to/chacha.html)
-#[derive(Copy, Clone, Debug)]
-pub struct ChaChaRng {
-    buffer:  [w32; STATE_WORDS], // Internal buffer of output
-    state:   [w32; STATE_WORDS], // Initial state
-    index:   usize,                 // Index into state
-}
-
-static EMPTY: ChaChaRng = ChaChaRng {
-    buffer:  [w(0); STATE_WORDS],
-    state:   [w(0); STATE_WORDS],
-    index:   STATE_WORDS
-};
-
-
-macro_rules! quarter_round{
-    ($a: expr, $b: expr, $c: expr, $d: expr) => {{
-        $a = $a + $b; $d = $d ^ $a; $d = w($d.0.rotate_left(16));
-        $c = $c + $d; $b = $b ^ $c; $b = w($b.0.rotate_left(12));
-        $a = $a + $b; $d = $d ^ $a; $d = w($d.0.rotate_left( 8));
-        $c = $c + $d; $b = $b ^ $c; $b = w($b.0.rotate_left( 7));
-    }}
-}
-
-macro_rules! double_round{
-    ($x: expr) => {{
-        // Column round
-        quarter_round!($x[ 0], $x[ 4], $x[ 8], $x[12]);
-        quarter_round!($x[ 1], $x[ 5], $x[ 9], $x[13]);
-        quarter_round!($x[ 2], $x[ 6], $x[10], $x[14]);
-        quarter_round!($x[ 3], $x[ 7], $x[11], $x[15]);
-        // Diagonal round
-        quarter_round!($x[ 0], $x[ 5], $x[10], $x[15]);
-        quarter_round!($x[ 1], $x[ 6], $x[11], $x[12]);
-        quarter_round!($x[ 2], $x[ 7], $x[ 8], $x[13]);
-        quarter_round!($x[ 3], $x[ 4], $x[ 9], $x[14]);
-    }}
-}
-
-#[inline]
-fn core(output: &mut [w32; STATE_WORDS], input: &[w32; STATE_WORDS]) {
-    *output = *input;
-
-    for _ in 0..CHACHA_ROUNDS / 2 {
-        double_round!(output);
-    }
-
-    for i in 0..STATE_WORDS {
-        output[i] = output[i] + input[i];
-    }
-}
-
-impl ChaChaRng {
-
-    /// Create an ChaCha random number generator using the default
-    /// fixed key of 8 zero words.
-    ///
-    /// # Examples
-    ///
-    /// ```rust
-    /// use rand::{Rng, ChaChaRng};
-    ///
-    /// let mut ra = ChaChaRng::new_unseeded();
-    /// println!("{:?}", ra.next_u32());
-    /// println!("{:?}", ra.next_u32());
-    /// ```
-    ///
-    /// Since this equivalent to a RNG with a fixed seed, repeated executions
-    /// of an unseeded RNG will produce the same result. This code sample will
-    /// consistently produce:
-    ///
-    /// - 2917185654
-    /// - 2419978656
-    pub fn new_unseeded() -> ChaChaRng {
-        let mut rng = EMPTY;
-        rng.init(&[0; KEY_WORDS]);
-        rng
-    }
-
-    /// Sets the internal 128-bit ChaCha counter to
-    /// a user-provided value. This permits jumping
-    /// arbitrarily ahead (or backwards) in the pseudorandom stream.
-    ///
-    /// Since the nonce words are used to extend the counter to 128 bits,
-    /// users wishing to obtain the conventional ChaCha pseudorandom stream
-    /// associated with a particular nonce can call this function with
-    /// arguments `0, desired_nonce`.
-    ///
-    /// # Examples
-    ///
-    /// ```rust
-    /// use rand::{Rng, ChaChaRng};
-    ///
-    /// let mut ra = ChaChaRng::new_unseeded();
-    /// ra.set_counter(0u64, 1234567890u64);
-    /// println!("{:?}", ra.next_u32());
-    /// println!("{:?}", ra.next_u32());
-    /// ```
-    pub fn set_counter(&mut self, counter_low: u64, counter_high: u64) {
-        self.state[12] = w((counter_low >>  0) as u32);
-        self.state[13] = w((counter_low >> 32) as u32);
-        self.state[14] = w((counter_high >>  0) as u32);
-        self.state[15] = w((counter_high >> 32) as u32);
-        self.index = STATE_WORDS; // force recomputation
-    }
-
-    /// Initializes `self.state` with the appropriate key and constants
-    ///
-    /// We deviate slightly from the ChaCha specification regarding
-    /// the nonce, which is used to extend the counter to 128 bits.
-    /// This is provably as strong as the original cipher, though,
-    /// since any distinguishing attack on our variant also works
-    /// against ChaCha with a chosen-nonce. See the XSalsa20 [1]
-    /// security proof for a more involved example of this.
-    ///
-    /// The modified word layout is:
-    /// ```text
-    /// constant constant constant constant
-    /// key      key      key      key
-    /// key      key      key      key
-    /// counter  counter  counter  counter
-    /// ```
-    /// [1]: Daniel J. Bernstein. [*Extending the Salsa20
-    /// nonce.*](http://cr.yp.to/papers.html#xsalsa)
-    fn init(&mut self, key: &[u32; KEY_WORDS]) {
-        self.state[0] = w(0x61707865);
-        self.state[1] = w(0x3320646E);
-        self.state[2] = w(0x79622D32);
-        self.state[3] = w(0x6B206574);
-
-        for i in 0..KEY_WORDS {
-            self.state[4+i] = w(key[i]);
-        }
-
-        self.state[12] = w(0);
-        self.state[13] = w(0);
-        self.state[14] = w(0);
-        self.state[15] = w(0);
-
-        self.index = STATE_WORDS;
-    }
-
-    /// Refill the internal output buffer (`self.buffer`)
-    fn update(&mut self) {
-        core(&mut self.buffer, &self.state);
-        self.index = 0;
-        // update 128-bit counter
-        self.state[12] = self.state[12] + w(1);
-        if self.state[12] != w(0) { return };
-        self.state[13] = self.state[13] + w(1);
-        if self.state[13] != w(0) { return };
-        self.state[14] = self.state[14] + w(1);
-        if self.state[14] != w(0) { return };
-        self.state[15] = self.state[15] + w(1);
-    }
-}
-
-impl Rng for ChaChaRng {
-    #[inline]
-    fn next_u32(&mut self) -> u32 {
-        if self.index == STATE_WORDS {
-            self.update();
-        }
-
-        let value = self.buffer[self.index % STATE_WORDS];
-        self.index += 1;
-        value.0
-    }
-}
-
-impl<'a> SeedableRng<&'a [u32]> for ChaChaRng {
-
-    fn reseed(&mut self, seed: &'a [u32]) {
-        // reset state
-        self.init(&[0u32; KEY_WORDS]);
-        // set key in place
-        let key = &mut self.state[4 .. 4+KEY_WORDS];
-        for (k, s) in key.iter_mut().zip(seed.iter()) {
-            *k = w(*s);
-        }
-    }
-
-    /// Create a ChaCha generator from a seed,
-    /// obtained from a variable-length u32 array.
-    /// Only up to 8 words are used; if less than 8
-    /// words are used, the remaining are set to zero.
-    fn from_seed(seed: &'a [u32]) -> ChaChaRng {
-        let mut rng = EMPTY;
-        rng.reseed(seed);
-        rng
-    }
-}
-
-impl Rand for ChaChaRng {
-    fn rand<R: Rng>(other: &mut R) -> ChaChaRng {
-        let mut key : [u32; KEY_WORDS] = [0; KEY_WORDS];
-        for word in key.iter_mut() {
-            *word = other.gen();
-        }
-        SeedableRng::from_seed(&key[..])
-    }
-}
-
-
-#[cfg(test)]
-mod test {
-    use {Rng, SeedableRng};
-    use super::ChaChaRng;
-
-    #[test]
-    fn test_rng_rand_seeded() {
-        let s = ::test::rng().gen_iter::<u32>().take(8).collect::<Vec<u32>>();
-        let mut ra: ChaChaRng = SeedableRng::from_seed(&s[..]);
-        let mut rb: ChaChaRng = SeedableRng::from_seed(&s[..]);
-        assert!(::test::iter_eq(ra.gen_ascii_chars().take(100),
-                                rb.gen_ascii_chars().take(100)));
-    }
-
-    #[test]
-    fn test_rng_seeded() {
-        let seed : &[_] = &[0,1,2,3,4,5,6,7];
-        let mut ra: ChaChaRng = SeedableRng::from_seed(seed);
-        let mut rb: ChaChaRng = SeedableRng::from_seed(seed);
-        assert!(::test::iter_eq(ra.gen_ascii_chars().take(100),
-                                rb.gen_ascii_chars().take(100)));
-    }
-
-    #[test]
-    fn test_rng_reseed() {
-        let s = ::test::rng().gen_iter::<u32>().take(8).collect::<Vec<u32>>();
-        let mut r: ChaChaRng = SeedableRng::from_seed(&s[..]);
-        let string1: String = r.gen_ascii_chars().take(100).collect();
-
-        r.reseed(&s);
-
-        let string2: String = r.gen_ascii_chars().take(100).collect();
-        assert_eq!(string1, string2);
-    }
-
-    #[test]
-    fn test_rng_true_values() {
-        // Test vectors 1 and 2 from
-        // http://tools.ietf.org/html/draft-nir-cfrg-chacha20-poly1305-04
-        let seed : &[_] = &[0u32; 8];
-        let mut ra: ChaChaRng = SeedableRng::from_seed(seed);
-
-        let v = (0..16).map(|_| ra.next_u32()).collect::<Vec<_>>();
-        assert_eq!(v,
-                   vec!(0xade0b876, 0x903df1a0, 0xe56a5d40, 0x28bd8653,
-                        0xb819d2bd, 0x1aed8da0, 0xccef36a8, 0xc70d778b,
-                        0x7c5941da, 0x8d485751, 0x3fe02477, 0x374ad8b8,
-                        0xf4b8436a, 0x1ca11815, 0x69b687c3, 0x8665eeb2));
-
-        let v = (0..16).map(|_| ra.next_u32()).collect::<Vec<_>>();
-        assert_eq!(v,
-                   vec!(0xbee7079f, 0x7a385155, 0x7c97ba98, 0x0d082d73,
-                        0xa0290fcb, 0x6965e348, 0x3e53c612, 0xed7aee32,
-                        0x7621b729, 0x434ee69c, 0xb03371d5, 0xd539d874,
-                        0x281fed31, 0x45fb0a51, 0x1f0ae1ac, 0x6f4d794b));
-
-
-        let seed : &[_] = &[0,1,2,3,4,5,6,7];
-        let mut ra: ChaChaRng = SeedableRng::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 v : Vec<u32> = Vec::new();
-        for _ in 0..16 {
-            v.push(ra.next_u32());
-            for _ in 0..16 {
-                ra.next_u32();
-            }
-        }
-
-        assert_eq!(v,
-                   vec!(0xf225c81a, 0x6ab1be57, 0x04d42951, 0x70858036,
-                        0x49884684, 0x64efec72, 0x4be2d186, 0x3615b384,
-                        0x11cfa18e, 0xd3c50049, 0x75c775f6, 0x434c6530,
-                        0x2c5bad8f, 0x898881dc, 0x5f1c86d9, 0xc1f8e7f4));
-    }
-
-    #[test]
-    fn test_rng_clone() {
-        let seed : &[_] = &[0u32; 8];
-        let mut rng: ChaChaRng = SeedableRng::from_seed(seed);
-        let mut clone = rng.clone();
-        for _ in 0..16 {
-            assert_eq!(rng.next_u64(), clone.next_u64());
-        }
-    }
-}
diff --git a/vendor/rand/src/prng/isaac.rs b/vendor/rand/src/prng/isaac.rs
deleted file mode 100644
index cf5eb67..0000000
--- a/vendor/rand/src/prng/isaac.rs
+++ /dev/null
@@ -1,328 +0,0 @@
-// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The ISAAC random number generator.
-
-#![allow(non_camel_case_types)]
-
-use core::slice;
-use core::iter::repeat;
-use core::num::Wrapping as w;
-use core::fmt;
-
-use {Rng, SeedableRng, Rand};
-
-#[allow(bad_style)]
-type w32 = w<u32>;
-
-const RAND_SIZE_LEN: usize = 8;
-const RAND_SIZE: u32 = 1 << RAND_SIZE_LEN;
-const RAND_SIZE_USIZE: usize = 1 << RAND_SIZE_LEN;
-
-/// A random number generator that uses the ISAAC algorithm[1].
-///
-/// The ISAAC algorithm is generally accepted as suitable for
-/// cryptographic purposes, but this implementation has not be
-/// verified as such. Prefer a generator like `OsRng` that defers to
-/// the operating system for cases that need high security.
-///
-/// [1]: Bob Jenkins, [*ISAAC: A fast cryptographic random number
-/// generator*](http://www.burtleburtle.net/bob/rand/isaacafa.html)
-#[derive(Copy)]
-pub struct IsaacRng {
-    cnt: u32,
-    rsl: [w32; RAND_SIZE_USIZE],
-    mem: [w32; RAND_SIZE_USIZE],
-    a: w32,
-    b: w32,
-    c: w32,
-}
-
-static EMPTY: IsaacRng = IsaacRng {
-    cnt: 0,
-    rsl: [w(0); RAND_SIZE_USIZE],
-    mem: [w(0); RAND_SIZE_USIZE],
-    a: w(0), b: w(0), c: w(0),
-};
-
-impl IsaacRng {
-
-    /// Create an ISAAC random number generator using the default
-    /// fixed seed.
-    pub fn new_unseeded() -> IsaacRng {
-        let mut rng = EMPTY;
-        rng.init(false);
-        rng
-    }
-
-    /// Initialises `self`. If `use_rsl` is true, then use the current value
-    /// of `rsl` as a seed, otherwise construct one algorithmically (not
-    /// randomly).
-    fn init(&mut self, use_rsl: bool) {
-        let mut a = w(0x9e3779b9);
-        let mut b = a;
-        let mut c = a;
-        let mut d = a;
-        let mut e = a;
-        let mut f = a;
-        let mut g = a;
-        let mut h = a;
-
-        macro_rules! mix {
-            () => {{
-                a=a^(b<<11); d=d+a; b=b+c;
-                b=b^(c>>2);  e=e+b; c=c+d;
-                c=c^(d<<8);  f=f+c; d=d+e;
-                d=d^(e>>16); g=g+d; e=e+f;
-                e=e^(f<<10); h=h+e; f=f+g;
-                f=f^(g>>4);  a=a+f; g=g+h;
-                g=g^(h<<8);  b=b+g; h=h+a;
-                h=h^(a>>9);  c=c+h; a=a+b;
-            }}
-        }
-
-        for _ in 0..4 {
-            mix!();
-        }
-
-        if use_rsl {
-            macro_rules! memloop {
-                ($arr:expr) => {{
-                    for i in (0..RAND_SIZE_USIZE/8).map(|i| i * 8) {
-                        a=a+$arr[i  ]; b=b+$arr[i+1];
-                        c=c+$arr[i+2]; d=d+$arr[i+3];
-                        e=e+$arr[i+4]; f=f+$arr[i+5];
-                        g=g+$arr[i+6]; h=h+$arr[i+7];
-                        mix!();
-                        self.mem[i  ]=a; self.mem[i+1]=b;
-                        self.mem[i+2]=c; self.mem[i+3]=d;
-                        self.mem[i+4]=e; self.mem[i+5]=f;
-                        self.mem[i+6]=g; self.mem[i+7]=h;
-                    }
-                }}
-            }
-
-            memloop!(self.rsl);
-            memloop!(self.mem);
-        } else {
-            for i in (0..RAND_SIZE_USIZE/8).map(|i| i * 8) {
-                mix!();
-                self.mem[i  ]=a; self.mem[i+1]=b;
-                self.mem[i+2]=c; self.mem[i+3]=d;
-                self.mem[i+4]=e; self.mem[i+5]=f;
-                self.mem[i+6]=g; self.mem[i+7]=h;
-            }
-        }
-
-        self.isaac();
-    }
-
-    /// Refills the output buffer (`self.rsl`)
-    #[inline]
-    fn isaac(&mut self) {
-        self.c = self.c + w(1);
-        // abbreviations
-        let mut a = self.a;
-        let mut b = self.b + self.c;
-
-        const MIDPOINT: usize = RAND_SIZE_USIZE / 2;
-
-        macro_rules! ind {
-            ($x:expr) => ( self.mem[($x >> 2usize).0 as usize & (RAND_SIZE_USIZE - 1)] )
-        }
-
-        let r = [(0, MIDPOINT), (MIDPOINT, 0)];
-        for &(mr_offset, m2_offset) in r.iter() {
-
-            macro_rules! rngstepp {
-                ($j:expr, $shift:expr) => {{
-                    let base = $j;
-                    let mix = a << $shift;
-
-                    let x = self.mem[base  + mr_offset];
-                    a = (a ^ mix) + self.mem[base + m2_offset];
-                    let y = ind!(x) + a + b;
-                    self.mem[base + mr_offset] = y;
-
-                    b = ind!(y >> RAND_SIZE_LEN) + x;
-                    self.rsl[base + mr_offset] = b;
-                }}
-            }
-
-            macro_rules! rngstepn {
-                ($j:expr, $shift:expr) => {{
-                    let base = $j;
-                    let mix = a >> $shift;
-
-                    let x = self.mem[base  + mr_offset];
-                    a = (a ^ mix) + self.mem[base + m2_offset];
-                    let y = ind!(x) + a + b;
-                    self.mem[base + mr_offset] = y;
-
-                    b = ind!(y >> RAND_SIZE_LEN) + x;
-                    self.rsl[base + mr_offset] = b;
-                }}
-            }
-
-            for i in (0..MIDPOINT/4).map(|i| i * 4) {
-                rngstepp!(i + 0, 13);
-                rngstepn!(i + 1, 6);
-                rngstepp!(i + 2, 2);
-                rngstepn!(i + 3, 16);
-            }
-        }
-
-        self.a = a;
-        self.b = b;
-        self.cnt = RAND_SIZE;
-    }
-}
-
-// Cannot be derived because [u32; 256] does not implement Clone
-impl Clone for IsaacRng {
-    fn clone(&self) -> IsaacRng {
-        *self
-    }
-}
-
-impl Rng for IsaacRng {
-    #[inline]
-    fn next_u32(&mut self) -> u32 {
-        if self.cnt == 0 {
-            // make some more numbers
-            self.isaac();
-        }
-        self.cnt -= 1;
-
-        // self.cnt is at most RAND_SIZE, but that is before the
-        // subtraction above. We want to index without bounds
-        // checking, but this could lead to incorrect code if someone
-        // misrefactors, so we check, sometimes.
-        //
-        // (Changes here should be reflected in Isaac64Rng.next_u64.)
-        debug_assert!(self.cnt < RAND_SIZE);
-
-        // (the % is cheaply telling the optimiser that we're always
-        // in bounds, without unsafe. NB. this is a power of two, so
-        // it optimises to a bitwise mask).
-        self.rsl[(self.cnt % RAND_SIZE) as usize].0
-    }
-}
-
-impl<'a> SeedableRng<&'a [u32]> for IsaacRng {
-    fn reseed(&mut self, seed: &'a [u32]) {
-        // make the seed into [seed[0], seed[1], ..., seed[seed.len()
-        // - 1], 0, 0, ...], to fill rng.rsl.
-        let seed_iter = seed.iter().map(|&x| x).chain(repeat(0u32));
-
-        for (rsl_elem, seed_elem) in self.rsl.iter_mut().zip(seed_iter) {
-            *rsl_elem = w(seed_elem);
-        }
-        self.cnt = 0;
-        self.a = w(0);
-        self.b = w(0);
-        self.c = w(0);
-
-        self.init(true);
-    }
-
-    /// Create an ISAAC random number generator with a seed. This can
-    /// be any length, although the maximum number of elements used is
-    /// 256 and any more will be silently ignored. A generator
-    /// constructed with a given seed will generate the same sequence
-    /// of values as all other generators constructed with that seed.
-    fn from_seed(seed: &'a [u32]) -> IsaacRng {
-        let mut rng = EMPTY;
-        rng.reseed(seed);
-        rng
-    }
-}
-
-impl Rand for IsaacRng {
-    fn rand<R: Rng>(other: &mut R) -> IsaacRng {
-        let mut ret = EMPTY;
-        unsafe {
-            let ptr = ret.rsl.as_mut_ptr() as *mut u8;
-
-            let slice = slice::from_raw_parts_mut(ptr, RAND_SIZE_USIZE * 4);
-            other.fill_bytes(slice);
-        }
-        ret.cnt = 0;
-        ret.a = w(0);
-        ret.b = w(0);
-        ret.c = w(0);
-
-        ret.init(true);
-        return ret;
-    }
-}
-
-impl fmt::Debug for IsaacRng {
-    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
-        write!(f, "IsaacRng {{}}")
-    }
-}
-
-#[cfg(test)]
-mod test {
-    use {Rng, SeedableRng};
-    use super::IsaacRng;
-
-    #[test]
-    fn test_rng_32_rand_seeded() {
-        let s = ::test::rng().gen_iter::<u32>().take(256).collect::<Vec<u32>>();
-        let mut ra: IsaacRng = SeedableRng::from_seed(&s[..]);
-        let mut rb: IsaacRng = SeedableRng::from_seed(&s[..]);
-        assert!(::test::iter_eq(ra.gen_ascii_chars().take(100),
-                                rb.gen_ascii_chars().take(100)));
-    }
-
-    #[test]
-    fn test_rng_32_seeded() {
-        let seed: &[_] = &[1, 23, 456, 7890, 12345];
-        let mut ra: IsaacRng = SeedableRng::from_seed(seed);
-        let mut rb: IsaacRng = SeedableRng::from_seed(seed);
-        assert!(::test::iter_eq(ra.gen_ascii_chars().take(100),
-                                rb.gen_ascii_chars().take(100)));
-    }
-
-    #[test]
-    fn test_rng_32_reseed() {
-        let s = ::test::rng().gen_iter::<u32>().take(256).collect::<Vec<u32>>();
-        let mut r: IsaacRng = SeedableRng::from_seed(&s[..]);
-        let string1: String = r.gen_ascii_chars().take(100).collect();
-
-        r.reseed(&s[..]);
-
-        let string2: String = r.gen_ascii_chars().take(100).collect();
-        assert_eq!(string1, string2);
-    }
-
-    #[test]
-    fn test_rng_32_true_values() {
-        let seed: &[_] = &[1, 23, 456, 7890, 12345];
-        let mut ra: IsaacRng = SeedableRng::from_seed(seed);
-        // Regression test that isaac is actually using the above vector
-        let v = (0..10).map(|_| ra.next_u32()).collect::<Vec<_>>();
-        assert_eq!(v,
-                   vec!(2558573138, 873787463, 263499565, 2103644246, 3595684709,
-                        4203127393, 264982119, 2765226902, 2737944514, 3900253796));
-
-        let seed: &[_] = &[12345, 67890, 54321, 9876];
-        let mut rb: IsaacRng = SeedableRng::from_seed(seed);
-        // skip forward to the 10000th number
-        for _ in 0..10000 { rb.next_u32(); }
-
-        let v = (0..10).map(|_| rb.next_u32()).collect::<Vec<_>>();
-        assert_eq!(v,
-                   vec!(3676831399, 3183332890, 2834741178, 3854698763, 2717568474,
-                        1576568959, 3507990155, 179069555, 141456972, 2478885421));
-    }
-}
diff --git a/vendor/rand/src/prng/isaac64.rs b/vendor/rand/src/prng/isaac64.rs
deleted file mode 100644
index b98e3fe..0000000
--- a/vendor/rand/src/prng/isaac64.rs
+++ /dev/null
@@ -1,340 +0,0 @@
-// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The ISAAC-64 random number generator.
-
-use core::slice;
-use core::iter::repeat;
-use core::num::Wrapping as w;
-use core::fmt;
-
-use {Rng, SeedableRng, Rand};
-
-#[allow(bad_style)]
-type w64 = w<u64>;
-
-const RAND_SIZE_64_LEN: usize = 8;
-const RAND_SIZE_64: usize = 1 << RAND_SIZE_64_LEN;
-
-/// A random number generator that uses ISAAC-64[1], the 64-bit
-/// variant of the ISAAC algorithm.
-///
-/// The ISAAC algorithm is generally accepted as suitable for
-/// cryptographic purposes, but this implementation has not be
-/// verified as such. Prefer a generator like `OsRng` that defers to
-/// the operating system for cases that need high security.
-///
-/// [1]: Bob Jenkins, [*ISAAC: A fast cryptographic random number
-/// generator*](http://www.burtleburtle.net/bob/rand/isaacafa.html)
-#[derive(Copy)]
-pub struct Isaac64Rng {
-    cnt: usize,
-    rsl: [w64; RAND_SIZE_64],
-    mem: [w64; RAND_SIZE_64],
-    a: w64,
-    b: w64,
-    c: w64,
-}
-
-static EMPTY_64: Isaac64Rng = Isaac64Rng {
-    cnt: 0,
-    rsl: [w(0); RAND_SIZE_64],
-    mem: [w(0); RAND_SIZE_64],
-    a: w(0), b: w(0), c: w(0),
-};
-
-impl Isaac64Rng {
-    /// Create a 64-bit ISAAC random number generator using the
-    /// default fixed seed.
-    pub fn new_unseeded() -> Isaac64Rng {
-        let mut rng = EMPTY_64;
-        rng.init(false);
-        rng
-    }
-
-    /// Initialises `self`. If `use_rsl` is true, then use the current value
-    /// of `rsl` as a seed, otherwise construct one algorithmically (not
-    /// randomly).
-    fn init(&mut self, use_rsl: bool) {
-        macro_rules! init {
-            ($var:ident) => (
-                let mut $var = w(0x9e3779b97f4a7c13);
-            )
-        }
-        init!(a); init!(b); init!(c); init!(d);
-        init!(e); init!(f); init!(g); init!(h);
-
-        macro_rules! mix {
-            () => {{
-                a=a-e; f=f^(h>>9);  h=h+a;
-                b=b-f; g=g^(a<<9);  a=a+b;
-                c=c-g; h=h^(b>>23); b=b+c;
-                d=d-h; a=a^(c<<15); c=c+d;
-                e=e-a; b=b^(d>>14); d=d+e;
-                f=f-b; c=c^(e<<20); e=e+f;
-                g=g-c; d=d^(f>>17); f=f+g;
-                h=h-d; e=e^(g<<14); g=g+h;
-            }}
-        }
-
-        for _ in 0..4 {
-            mix!();
-        }
-
-        if use_rsl {
-            macro_rules! memloop {
-                ($arr:expr) => {{
-                    for i in (0..RAND_SIZE_64 / 8).map(|i| i * 8) {
-                        a=a+$arr[i  ]; b=b+$arr[i+1];
-                        c=c+$arr[i+2]; d=d+$arr[i+3];
-                        e=e+$arr[i+4]; f=f+$arr[i+5];
-                        g=g+$arr[i+6]; h=h+$arr[i+7];
-                        mix!();
-                        self.mem[i  ]=a; self.mem[i+1]=b;
-                        self.mem[i+2]=c; self.mem[i+3]=d;
-                        self.mem[i+4]=e; self.mem[i+5]=f;
-                        self.mem[i+6]=g; self.mem[i+7]=h;
-                    }
-                }}
-            }
-
-            memloop!(self.rsl);
-            memloop!(self.mem);
-        } else {
-            for i in (0..RAND_SIZE_64 / 8).map(|i| i * 8) {
-                mix!();
-                self.mem[i  ]=a; self.mem[i+1]=b;
-                self.mem[i+2]=c; self.mem[i+3]=d;
-                self.mem[i+4]=e; self.mem[i+5]=f;
-                self.mem[i+6]=g; self.mem[i+7]=h;
-            }
-        }
-
-        self.isaac64();
-    }
-
-    /// Refills the output buffer (`self.rsl`)
-    fn isaac64(&mut self) {
-        self.c = self.c + w(1);
-        // abbreviations
-        let mut a = self.a;
-        let mut b = self.b + self.c;
-        const MIDPOINT: usize =  RAND_SIZE_64 / 2;
-        const MP_VEC: [(usize, usize); 2] = [(0,MIDPOINT), (MIDPOINT, 0)];
-        macro_rules! ind {
-            ($x:expr) => {
-                *self.mem.get_unchecked((($x >> 3usize).0 as usize) & (RAND_SIZE_64 - 1))
-            }
-        }
-
-        for &(mr_offset, m2_offset) in MP_VEC.iter() {
-            for base in (0..MIDPOINT / 4).map(|i| i * 4) {
-
-                macro_rules! rngstepp {
-                    ($j:expr, $shift:expr) => {{
-                        let base = base + $j;
-                        let mix = a ^ (a << $shift);
-                        let mix = if $j == 0 {!mix} else {mix};
-
-                        unsafe {
-                            let x = *self.mem.get_unchecked(base + mr_offset);
-                            a = mix + *self.mem.get_unchecked(base + m2_offset);
-                            let y = ind!(x) + a + b;
-                            *self.mem.get_unchecked_mut(base + mr_offset) = y;
-
-                            b = ind!(y >> RAND_SIZE_64_LEN) + x;
-                            *self.rsl.get_unchecked_mut(base + mr_offset) = b;
-                        }
-                    }}
-                }
-
-                macro_rules! rngstepn {
-                    ($j:expr, $shift:expr) => {{
-                        let base = base + $j;
-                        let mix = a ^ (a >> $shift);
-                        let mix = if $j == 0 {!mix} else {mix};
-
-                        unsafe {
-                            let x = *self.mem.get_unchecked(base + mr_offset);
-                            a = mix + *self.mem.get_unchecked(base + m2_offset);
-                            let y = ind!(x) + a + b;
-                            *self.mem.get_unchecked_mut(base + mr_offset) = y;
-
-                            b = ind!(y >> RAND_SIZE_64_LEN) + x;
-                            *self.rsl.get_unchecked_mut(base + mr_offset) = b;
-                        }
-                    }}
-                }
-
-                rngstepp!(0, 21);
-                rngstepn!(1, 5);
-                rngstepp!(2, 12);
-                rngstepn!(3, 33);
-            }
-        }
-
-        self.a = a;
-        self.b = b;
-        self.cnt = RAND_SIZE_64;
-    }
-}
-
-// Cannot be derived because [u32; 256] does not implement Clone
-impl Clone for Isaac64Rng {
-    fn clone(&self) -> Isaac64Rng {
-        *self
-    }
-}
-
-impl Rng for Isaac64Rng {
-    #[inline]
-    fn next_u32(&mut self) -> u32 {
-        self.next_u64() as u32
-    }
-
-    #[inline]
-    fn next_u64(&mut self) -> u64 {
-        if self.cnt == 0 {
-            // make some more numbers
-            self.isaac64();
-        }
-        self.cnt -= 1;
-
-        // See corresponding location in IsaacRng.next_u32 for
-        // explanation.
-        debug_assert!(self.cnt < RAND_SIZE_64);
-        self.rsl[(self.cnt % RAND_SIZE_64) as usize].0
-    }
-}
-
-impl<'a> SeedableRng<&'a [u64]> for Isaac64Rng {
-    fn reseed(&mut self, seed: &'a [u64]) {
-        // make the seed into [seed[0], seed[1], ..., seed[seed.len()
-        // - 1], 0, 0, ...], to fill rng.rsl.
-        let seed_iter = seed.iter().map(|&x| x).chain(repeat(0u64));
-
-        for (rsl_elem, seed_elem) in self.rsl.iter_mut().zip(seed_iter) {
-            *rsl_elem = w(seed_elem);
-        }
-        self.cnt = 0;
-        self.a = w(0);
-        self.b = w(0);
-        self.c = w(0);
-
-        self.init(true);
-    }
-
-    /// Create an ISAAC random number generator with a seed. This can
-    /// be any length, although the maximum number of elements used is
-    /// 256 and any more will be silently ignored. A generator
-    /// constructed with a given seed will generate the same sequence
-    /// of values as all other generators constructed with that seed.
-    fn from_seed(seed: &'a [u64]) -> Isaac64Rng {
-        let mut rng = EMPTY_64;
-        rng.reseed(seed);
-        rng
-    }
-}
-
-impl Rand for Isaac64Rng {
-    fn rand<R: Rng>(other: &mut R) -> Isaac64Rng {
-        let mut ret = EMPTY_64;
-        unsafe {
-            let ptr = ret.rsl.as_mut_ptr() as *mut u8;
-
-            let slice = slice::from_raw_parts_mut(ptr, RAND_SIZE_64 * 8);
-            other.fill_bytes(slice);
-        }
-        ret.cnt = 0;
-        ret.a = w(0);
-        ret.b = w(0);
-        ret.c = w(0);
-
-        ret.init(true);
-        return ret;
-    }
-}
-
-impl fmt::Debug for Isaac64Rng {
-    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
-        write!(f, "Isaac64Rng {{}}")
-    }
-}
-
-#[cfg(test)]
-mod test {
-    use {Rng, SeedableRng};
-    use super::Isaac64Rng;
-
-    #[test]
-    fn test_rng_64_rand_seeded() {
-        let s = ::test::rng().gen_iter::<u64>().take(256).collect::<Vec<u64>>();
-        let mut ra: Isaac64Rng = SeedableRng::from_seed(&s[..]);
-        let mut rb: Isaac64Rng = SeedableRng::from_seed(&s[..]);
-        assert!(::test::iter_eq(ra.gen_ascii_chars().take(100),
-                                rb.gen_ascii_chars().take(100)));
-    }
-
-    #[test]
-    fn test_rng_64_seeded() {
-        let seed: &[_] = &[1, 23, 456, 7890, 12345];
-        let mut ra: Isaac64Rng = SeedableRng::from_seed(seed);
-        let mut rb: Isaac64Rng = SeedableRng::from_seed(seed);
-        assert!(::test::iter_eq(ra.gen_ascii_chars().take(100),
-                                rb.gen_ascii_chars().take(100)));
-    }
-
-    #[test]
-    fn test_rng_64_reseed() {
-        let s = ::test::rng().gen_iter::<u64>().take(256).collect::<Vec<u64>>();
-        let mut r: Isaac64Rng = SeedableRng::from_seed(&s[..]);
-        let string1: String = r.gen_ascii_chars().take(100).collect();
-
-        r.reseed(&s[..]);
-
-        let string2: String = r.gen_ascii_chars().take(100).collect();
-        assert_eq!(string1, string2);
-    }
-
-    #[test]
-    fn test_rng_64_true_values() {
-        let seed: &[_] = &[1, 23, 456, 7890, 12345];
-        let mut ra: Isaac64Rng = SeedableRng::from_seed(seed);
-        // Regression test that isaac is actually using the above vector
-        let v = (0..10).map(|_| ra.next_u64()).collect::<Vec<_>>();
-        assert_eq!(v,
-                   vec!(547121783600835980, 14377643087320773276, 17351601304698403469,
-                        1238879483818134882, 11952566807690396487, 13970131091560099343,
-                        4469761996653280935, 15552757044682284409, 6860251611068737823,
-                        13722198873481261842));
-
-        let seed: &[_] = &[12345, 67890, 54321, 9876];
-        let mut rb: Isaac64Rng = SeedableRng::from_seed(seed);
-        // skip forward to the 10000th number
-        for _ in 0..10000 { rb.next_u64(); }
-
-        let v = (0..10).map(|_| rb.next_u64()).collect::<Vec<_>>();
-        assert_eq!(v,
-                   vec!(18143823860592706164, 8491801882678285927, 2699425367717515619,
-                        17196852593171130876, 2606123525235546165, 15790932315217671084,
-                        596345674630742204, 9947027391921273664, 11788097613744130851,
-                        10391409374914919106));
-    }
-
-    #[test]
-    fn test_rng_clone() {
-        let seed: &[_] = &[1, 23, 456, 7890, 12345];
-        let mut rng: Isaac64Rng = SeedableRng::from_seed(seed);
-        let mut clone = rng.clone();
-        for _ in 0..16 {
-            assert_eq!(rng.next_u64(), clone.next_u64());
-        }
-    }
-}
diff --git a/vendor/rand/src/prng/mod.rs b/vendor/rand/src/prng/mod.rs
deleted file mode 100644
index ed3e018..0000000
--- a/vendor/rand/src/prng/mod.rs
+++ /dev/null
@@ -1,51 +0,0 @@
-// Copyright 2017 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Pseudo random number generators are algorithms to produce *apparently
-//! random* numbers deterministically, and usually fairly quickly.
-//! 
-//! So long as the algorithm is computationally secure, is initialised with
-//! sufficient entropy (i.e. unknown by an attacker), and its internal state is
-//! also protected (unknown to an attacker), the output will also be
-//! *computationally secure*. Computationally Secure Pseudo Random Number
-//! Generators (CSPRNGs) are thus suitable sources of random numbers for
-//! cryptography. There are a couple of gotchas here, however. First, the seed
-//! used for initialisation must be unknown. Usually this should be provided by
-//! the operating system and should usually be secure, however this may not
-//! always be the case (especially soon after startup). Second, user-space
-//! memory may be vulnerable, for example when written to swap space, and after
-//! forking a child process should reinitialise any user-space PRNGs. For this
-//! reason it may be preferable to source random numbers directly from the OS
-//! for cryptographic applications.
-//! 
-//! PRNGs are also widely used for non-cryptographic uses: randomised
-//! algorithms, simulations, games. In these applications it is usually not
-//! important for numbers to be cryptographically *unguessable*, but even
-//! distribution and independence from other samples (from the point of view
-//! of someone unaware of the algorithm used, at least) may still be important.
-//! Good PRNGs should satisfy these properties, but do not take them for
-//! granted; Wikipedia's article on 
-//! [Pseudorandom number generators](https://en.wikipedia.org/wiki/Pseudorandom_number_generator)
-//! provides some background on this topic.
-//! 
-//! Care should be taken when seeding (initialising) PRNGs. Some PRNGs have
-//! short periods for some seeds. If one PRNG is seeded from another using the
-//! same algorithm, it is possible that both will yield the same sequence of
-//! values (with some lag).
-
-mod chacha;
-mod isaac;
-mod isaac64;
-mod xorshift;
-
-pub use self::chacha::ChaChaRng;
-pub use self::isaac::IsaacRng;
-pub use self::isaac64::Isaac64Rng;
-pub use self::xorshift::XorShiftRng;
diff --git a/vendor/rand/src/prng/xorshift.rs b/vendor/rand/src/prng/xorshift.rs
deleted file mode 100644
index dd367e9..0000000
--- a/vendor/rand/src/prng/xorshift.rs
+++ /dev/null
@@ -1,101 +0,0 @@
-// Copyright 2017 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Xorshift generators
-
-use core::num::Wrapping as w;
-use {Rng, SeedableRng, Rand};
-
-/// An Xorshift[1] random number
-/// generator.
-///
-/// The Xorshift 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 `IsaacRng` or `OsRng`.
-///
-/// [1]: Marsaglia, George (July 2003). ["Xorshift
-/// RNGs"](http://www.jstatsoft.org/v08/i14/paper). *Journal of
-/// Statistical Software*. Vol. 8 (Issue 14).
-#[allow(missing_copy_implementations)]
-#[derive(Clone, Debug)]
-pub struct XorShiftRng {
-    x: w<u32>,
-    y: w<u32>,
-    z: w<u32>,
-    w: w<u32>,
-}
-
-impl XorShiftRng {
-    /// Creates a new XorShiftRng instance which is not seeded.
-    ///
-    /// The initial values of this RNG are constants, so all generators created
-    /// by this function will yield the same stream of random numbers. It is
-    /// highly recommended that this is created through `SeedableRng` instead of
-    /// this function
-    pub fn new_unseeded() -> XorShiftRng {
-        XorShiftRng {
-            x: w(0x193a6754),
-            y: w(0xa8a7d469),
-            z: w(0x97830e05),
-            w: w(0x113ba7bb),
-        }
-    }
-}
-
-impl Rng 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
-    }
-}
-
-impl SeedableRng<[u32; 4]> for XorShiftRng {
-    /// Reseed an XorShiftRng. This will panic if `seed` is entirely 0.
-    fn reseed(&mut self, seed: [u32; 4]) {
-        assert!(!seed.iter().all(|&x| x == 0),
-                "XorShiftRng.reseed called with an all zero seed.");
-
-        self.x = w(seed[0]);
-        self.y = w(seed[1]);
-        self.z = w(seed[2]);
-        self.w = w(seed[3]);
-    }
-
-    /// Create a new XorShiftRng. This will panic if `seed` is entirely 0.
-    fn from_seed(seed: [u32; 4]) -> XorShiftRng {
-        assert!(!seed.iter().all(|&x| x == 0),
-                "XorShiftRng::from_seed called with an all zero seed.");
-
-        XorShiftRng {
-            x: w(seed[0]),
-            y: w(seed[1]),
-            z: w(seed[2]),
-            w: w(seed[3]),
-        }
-    }
-}
-
-impl Rand for XorShiftRng {
-    fn rand<R: Rng>(rng: &mut R) -> XorShiftRng {
-        let mut tuple: (u32, u32, u32, u32) = rng.gen();
-        while tuple == (0, 0, 0, 0) {
-            tuple = rng.gen();
-        }
-        let (x, y, z, w_) = tuple;
-        XorShiftRng { x: w(x), y: w(y), z: w(z), w: w(w_) }
-    }
-}
diff --git a/vendor/rand/src/rand_impls.rs b/vendor/rand/src/rand_impls.rs
deleted file mode 100644
index a865bb6..0000000
--- a/vendor/rand/src/rand_impls.rs
+++ /dev/null
@@ -1,299 +0,0 @@
-// Copyright 2013-2014 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The implementations of `Rand` for the built-in types.
-
-use core::{char, mem};
-
-use {Rand,Rng};
-
-impl Rand for isize {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> isize {
-        if mem::size_of::<isize>() == 4 {
-            rng.gen::<i32>() as isize
-        } else {
-            rng.gen::<i64>() as isize
-        }
-    }
-}
-
-impl Rand for i8 {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> i8 {
-        rng.next_u32() as i8
-    }
-}
-
-impl Rand for i16 {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> i16 {
-        rng.next_u32() as i16
-    }
-}
-
-impl Rand for i32 {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> i32 {
-        rng.next_u32() as i32
-    }
-}
-
-impl Rand for i64 {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> i64 {
-        rng.next_u64() as i64
-    }
-}
-
-#[cfg(feature = "i128_support")]
-impl Rand for i128 {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> i128 {
-        rng.gen::<u128>() as i128
-    }
-}
-
-impl Rand for usize {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> usize {
-        if mem::size_of::<usize>() == 4 {
-            rng.gen::<u32>() as usize
-        } else {
-            rng.gen::<u64>() as usize
-        }
-    }
-}
-
-impl Rand for u8 {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> u8 {
-        rng.next_u32() as u8
-    }
-}
-
-impl Rand for u16 {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> u16 {
-        rng.next_u32() as u16
-    }
-}
-
-impl Rand for u32 {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> u32 {
-        rng.next_u32()
-    }
-}
-
-impl Rand for u64 {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> u64 {
-        rng.next_u64()
-    }
-}
-
-#[cfg(feature = "i128_support")]
-impl Rand for u128 {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> u128 {
-        ((rng.next_u64() as u128) << 64) | (rng.next_u64() as u128)
-    }
-}
-
-
-macro_rules! float_impls {
-    ($mod_name:ident, $ty:ty, $mantissa_bits:expr, $method_name:ident) => {
-        mod $mod_name {
-            use {Rand, Rng, Open01, Closed01};
-
-            const SCALE: $ty = (1u64 << $mantissa_bits) as $ty;
-
-            impl Rand for $ty {
-                /// Generate a floating point number in the half-open
-                /// interval `[0,1)`.
-                ///
-                /// See `Closed01` for the closed interval `[0,1]`,
-                /// and `Open01` for the open interval `(0,1)`.
-                #[inline]
-                fn rand<R: Rng>(rng: &mut R) -> $ty {
-                    rng.$method_name()
-                }
-            }
-            impl Rand for Open01<$ty> {
-                #[inline]
-                fn rand<R: Rng>(rng: &mut R) -> Open01<$ty> {
-                    // add a small amount (specifically 2 bits below
-                    // the precision of f64/f32 at 1.0), so that small
-                    // numbers are larger than 0, but large numbers
-                    // aren't pushed to/above 1.
-                    Open01(rng.$method_name() + 0.25 / SCALE)
-                }
-            }
-            impl Rand for Closed01<$ty> {
-                #[inline]
-                fn rand<R: Rng>(rng: &mut R) -> Closed01<$ty> {
-                    // rescale so that 1.0 - epsilon becomes 1.0
-                    // precisely.
-                    Closed01(rng.$method_name() * SCALE / (SCALE - 1.0))
-                }
-            }
-        }
-    }
-}
-float_impls! { f64_rand_impls, f64, 53, next_f64 }
-float_impls! { f32_rand_impls, f32, 24, next_f32 }
-
-impl Rand for char {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> char {
-        // a char is 21 bits
-        const CHAR_MASK: u32 = 0x001f_ffff;
-        loop {
-            // Rejection sampling. About 0.2% of numbers with at most
-            // 21-bits are invalid codepoints (surrogates), so this
-            // will succeed first go almost every time.
-            match char::from_u32(rng.next_u32() & CHAR_MASK) {
-                Some(c) => return c,
-                None => {}
-            }
-        }
-    }
-}
-
-impl Rand for bool {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> bool {
-        rng.gen::<u8>() & 1 == 1
-    }
-}
-
-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 : Rand ),*
-            > Rand for ( $( $tyvar ),* , ) {
-
-            #[inline]
-            fn rand<R: Rng>(_rng: &mut R) -> ( $( $tyvar ),* , ) {
-                (
-                    // use the $tyvar's to get the appropriate number of
-                    // repeats (they're not actually needed)
-                    $(
-                        _rng.gen::<$tyvar>()
-                    ),*
-                    ,
-                )
-            }
-        }
-    }
-}
-
-impl Rand for () {
-    #[inline]
-    fn rand<R: Rng>(_: &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 {
-    {$n:expr, $t:ident, $($ts:ident,)*} => {
-        array_impl!{($n - 1), $($ts,)*}
-
-        impl<T> Rand for [T; $n] where T: Rand {
-            #[inline]
-            fn rand<R: Rng>(_rng: &mut R) -> [T; $n] {
-                [_rng.gen::<$t>(), $(_rng.gen::<$ts>()),*]
-            }
-        }
-    };
-    {$n:expr,} => {
-        impl<T> Rand for [T; $n] {
-            fn rand<R: Rng>(_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:Rand> Rand for Option<T> {
-    #[inline]
-    fn rand<R: Rng>(rng: &mut R) -> Option<T> {
-        if rng.gen() {
-            Some(rng.gen())
-        } else {
-            None
-        }
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use {Rng, thread_rng, Open01, Closed01};
-
-    struct ConstantRng(u64);
-    impl Rng for ConstantRng {
-        fn next_u32(&mut self) -> u32 {
-            let ConstantRng(v) = *self;
-            v as u32
-        }
-        fn next_u64(&mut self) -> u64 {
-            let ConstantRng(v) = *self;
-            v
-        }
-    }
-
-    #[test]
-    fn floating_point_edge_cases() {
-        // the test for exact equality is correct here.
-        assert!(ConstantRng(0xffff_ffff).gen::<f32>() != 1.0);
-        assert!(ConstantRng(0xffff_ffff_ffff_ffff).gen::<f64>() != 1.0);
-    }
-
-    #[test]
-    fn rand_open() {
-        // this is unlikely to catch an incorrect implementation that
-        // generates exactly 0 or 1, but it keeps it sane.
-        let mut rng = thread_rng();
-        for _ in 0..1_000 {
-            // strict inequalities
-            let Open01(f) = rng.gen::<Open01<f64>>();
-            assert!(0.0 < f && f < 1.0);
-
-            let Open01(f) = rng.gen::<Open01<f32>>();
-            assert!(0.0 < f && f < 1.0);
-        }
-    }
-
-    #[test]
-    fn rand_closed() {
-        let mut rng = thread_rng();
-        for _ in 0..1_000 {
-            // strict inequalities
-            let Closed01(f) = rng.gen::<Closed01<f64>>();
-            assert!(0.0 <= f && f <= 1.0);
-
-            let Closed01(f) = rng.gen::<Closed01<f32>>();
-            assert!(0.0 <= f && f <= 1.0);
-        }
-    }
-}
diff --git a/vendor/rand/src/read.rs b/vendor/rand/src/read.rs
deleted file mode 100644
index c7351b7..0000000
--- a/vendor/rand/src/read.rs
+++ /dev/null
@@ -1,123 +0,0 @@
-// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. 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::{self, Read};
-use std::mem;
-use Rng;
-
-/// An RNG that reads random bytes straight from a `Read`. This will
-/// work best with an infinite reader, but this is not required.
-///
-/// # Panics
-///
-/// It will panic if it there is insufficient data to fulfill a request.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::{read, Rng};
-///
-/// let data = vec![1, 2, 3, 4, 5, 6, 7, 8];
-/// let mut rng = read::ReadRng::new(&data[..]);
-/// println!("{:x}", rng.gen::<u32>());
-/// ```
-#[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> Rng for ReadRng<R> {
-    fn next_u32(&mut self) -> u32 {
-        // This is designed for speed: reading a LE integer on a LE
-        // platform just involves blitting the bytes into the memory
-        // of the u32, similarly for BE on BE; avoiding byteswapping.
-        let mut buf = [0; 4];
-        fill(&mut self.reader, &mut buf).unwrap();
-        unsafe { *(buf.as_ptr() as *const u32) }
-    }
-    fn next_u64(&mut self) -> u64 {
-        // see above for explanation.
-        let mut buf = [0; 8];
-        fill(&mut self.reader, &mut buf).unwrap();
-        unsafe { *(buf.as_ptr() as *const u64) }
-    }
-    fn fill_bytes(&mut self, v: &mut [u8]) {
-        if v.len() == 0 { return }
-        fill(&mut self.reader, v).unwrap();
-    }
-}
-
-fn fill(r: &mut Read, mut buf: &mut [u8]) -> io::Result<()> {
-    while buf.len() > 0 {
-        match try!(r.read(buf)) {
-            0 => return Err(io::Error::new(io::ErrorKind::Other,
-                                           "end of file reached")),
-            n => buf = &mut mem::replace(&mut buf, &mut [])[n..],
-        }
-    }
-    Ok(())
-}
-
-#[cfg(test)]
-mod test {
-    use super::ReadRng;
-    use Rng;
-
-    #[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]
-    #[should_panic]
-    fn test_reader_rng_insufficient_bytes() {
-        let mut rng = ReadRng::new(&[][..]);
-        let mut v = [0u8; 3];
-        rng.fill_bytes(&mut v);
-    }
-}
diff --git a/vendor/rand/src/reseeding.rs b/vendor/rand/src/reseeding.rs
deleted file mode 100644
index 1f24e20..0000000
--- a/vendor/rand/src/reseeding.rs
+++ /dev/null
@@ -1,229 +0,0 @@
-// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! A wrapper around another RNG that reseeds it after it
-//! generates a certain number of random bytes.
-
-use core::default::Default;
-
-use {Rng, SeedableRng};
-
-/// How many bytes of entropy the underling RNG is allowed to generate
-/// before it is reseeded
-const DEFAULT_GENERATION_THRESHOLD: u64 = 32 * 1024;
-
-/// A wrapper around any RNG which reseeds the underlying RNG after it
-/// has generated a certain number of random bytes.
-#[derive(Debug)]
-pub struct ReseedingRng<R, Rsdr> {
-    rng: R,
-    generation_threshold: u64,
-    bytes_generated: u64,
-    /// Controls the behaviour when reseeding the RNG.
-    pub reseeder: Rsdr,
-}
-
-impl<R: Rng, Rsdr: Reseeder<R>> ReseedingRng<R, Rsdr> {
-    /// Create a new `ReseedingRng` with the given parameters.
-    ///
-    /// # Arguments
-    ///
-    /// * `rng`: the random number generator to use.
-    /// * `generation_threshold`: the number of bytes of entropy at which to reseed the RNG.
-    /// * `reseeder`: the reseeding object to use.
-    pub fn new(rng: R, generation_threshold: u64, reseeder: Rsdr) -> ReseedingRng<R,Rsdr> {
-        ReseedingRng {
-            rng: rng,
-            generation_threshold: generation_threshold,
-            bytes_generated: 0,
-            reseeder: reseeder
-        }
-    }
-
-    /// Reseed the internal RNG if the number of bytes that have been
-    /// generated exceed the threshold.
-    pub fn reseed_if_necessary(&mut self) {
-        if self.bytes_generated >= self.generation_threshold {
-            self.reseeder.reseed(&mut self.rng);
-            self.bytes_generated = 0;
-        }
-    }
-}
-
-
-impl<R: Rng, Rsdr: Reseeder<R>> Rng for ReseedingRng<R, Rsdr> {
-    fn next_u32(&mut self) -> u32 {
-        self.reseed_if_necessary();
-        self.bytes_generated += 4;
-        self.rng.next_u32()
-    }
-
-    fn next_u64(&mut self) -> u64 {
-        self.reseed_if_necessary();
-        self.bytes_generated += 8;
-        self.rng.next_u64()
-    }
-
-    fn fill_bytes(&mut self, dest: &mut [u8]) {
-        self.reseed_if_necessary();
-        self.bytes_generated += dest.len() as u64;
-        self.rng.fill_bytes(dest)
-    }
-}
-
-impl<S, R: SeedableRng<S>, Rsdr: Reseeder<R> + Default>
-     SeedableRng<(Rsdr, S)> for ReseedingRng<R, Rsdr> {
-    fn reseed(&mut self, (rsdr, seed): (Rsdr, S)) {
-        self.rng.reseed(seed);
-        self.reseeder = rsdr;
-        self.bytes_generated = 0;
-    }
-
-    /// Create a new `ReseedingRng` from the given reseeder and
-    /// seed. This uses a default value for `generation_threshold`.
-    fn from_seed((rsdr, seed): (Rsdr, S)) -> ReseedingRng<R, Rsdr> {
-        ReseedingRng {
-            rng: SeedableRng::from_seed(seed),
-            generation_threshold: DEFAULT_GENERATION_THRESHOLD,
-            bytes_generated: 0,
-            reseeder: rsdr
-        }
-    }
-}
-
-/// Something that can be used to reseed an RNG via `ReseedingRng`.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::{Rng, SeedableRng, StdRng};
-/// use rand::reseeding::{Reseeder, ReseedingRng};
-///
-/// struct TickTockReseeder { tick: bool }
-/// impl Reseeder<StdRng> for TickTockReseeder {
-///     fn reseed(&mut self, rng: &mut StdRng) {
-///         let val = if self.tick {0} else {1};
-///         rng.reseed(&[val]);
-///         self.tick = !self.tick;
-///     }
-/// }
-/// fn main() {
-///     let rsdr = TickTockReseeder { tick: true };
-///
-///     let inner = StdRng::new().unwrap();
-///     let mut rng = ReseedingRng::new(inner, 10, rsdr);
-///
-///     // this will repeat, because it gets reseeded very regularly.
-///     let s: String = rng.gen_ascii_chars().take(100).collect();
-///     println!("{}", s);
-/// }
-///
-/// ```
-pub trait Reseeder<R> {
-    /// Reseed the given RNG.
-    fn reseed(&mut self, rng: &mut R);
-}
-
-/// Reseed an RNG using a `Default` instance. This reseeds by
-/// replacing the RNG with the result of a `Default::default` call.
-#[derive(Clone, Copy, Debug)]
-pub struct ReseedWithDefault;
-
-impl<R: Rng + Default> Reseeder<R> for ReseedWithDefault {
-    fn reseed(&mut self, rng: &mut R) {
-        *rng = Default::default();
-    }
-}
-impl Default for ReseedWithDefault {
-    fn default() -> ReseedWithDefault { ReseedWithDefault }
-}
-
-#[cfg(test)]
-mod test {
-    use std::default::Default;
-    use std::iter::repeat;
-    use super::{ReseedingRng, ReseedWithDefault};
-    use {SeedableRng, Rng};
-
-    struct Counter {
-        i: u32
-    }
-
-    impl Rng for Counter {
-        fn next_u32(&mut self) -> u32 {
-            self.i += 1;
-            // very random
-            self.i - 1
-        }
-    }
-    impl Default for Counter {
-        fn default() -> Counter {
-            Counter { i: 0 }
-        }
-    }
-    impl SeedableRng<u32> for Counter {
-        fn reseed(&mut self, seed: u32) {
-            self.i = seed;
-        }
-        fn from_seed(seed: u32) -> Counter {
-            Counter { i: seed }
-        }
-    }
-    type MyRng = ReseedingRng<Counter, ReseedWithDefault>;
-
-    #[test]
-    fn test_reseeding() {
-        let mut rs = ReseedingRng::new(Counter {i:0}, 400, ReseedWithDefault);
-
-        let mut i = 0;
-        for _ in 0..1000 {
-            assert_eq!(rs.next_u32(), i % 100);
-            i += 1;
-        }
-    }
-
-    #[test]
-    fn test_rng_seeded() {
-        let mut ra: MyRng = SeedableRng::from_seed((ReseedWithDefault, 2));
-        let mut rb: MyRng = SeedableRng::from_seed((ReseedWithDefault, 2));
-        assert!(::test::iter_eq(ra.gen_ascii_chars().take(100),
-                                rb.gen_ascii_chars().take(100)));
-    }
-
-    #[test]
-    fn test_rng_reseed() {
-        let mut r: MyRng = SeedableRng::from_seed((ReseedWithDefault, 3));
-        let string1: String = r.gen_ascii_chars().take(100).collect();
-
-        r.reseed((ReseedWithDefault, 3));
-
-        let string2: String = r.gen_ascii_chars().take(100).collect();
-        assert_eq!(string1, string2);
-    }
-
-    const FILL_BYTES_V_LEN: usize = 13579;
-    #[test]
-    fn test_rng_fill_bytes() {
-        let mut v = repeat(0u8).take(FILL_BYTES_V_LEN).collect::<Vec<_>>();
-        ::test::rng().fill_bytes(&mut v);
-
-        // Sanity test: if we've gotten here, `fill_bytes` has not infinitely
-        // recursed.
-        assert_eq!(v.len(), FILL_BYTES_V_LEN);
-
-        // To test that `fill_bytes` actually did something, check that the
-        // average of `v` is not 0.
-        let mut sum = 0.0;
-        for &x in v.iter() {
-            sum += x as f64;
-        }
-        assert!(sum / v.len() as f64 != 0.0);
-    }
-}
diff --git a/vendor/rand/src/seq.rs b/vendor/rand/src/seq.rs
deleted file mode 100644
index a7889fe..0000000
--- a/vendor/rand/src/seq.rs
+++ /dev/null
@@ -1,337 +0,0 @@
-// Copyright 2017 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Functions for randomly accessing and sampling sequences.
-
-use super::Rng;
-
-// This crate is only enabled when either std or alloc is available.
-// BTreeMap is not as fast in tests, but better than nothing.
-#[cfg(feature="std")] use std::collections::HashMap;
-#[cfg(not(feature="std"))] use alloc::btree_map::BTreeMap;
-
-#[cfg(not(feature="std"))] use alloc::Vec;
-
-/// Randomly sample `amount` elements from a finite iterator.
-///
-/// The following can be returned:
-/// - `Ok`: `Vec` of `amount` non-repeating randomly sampled elements. The order is not random.
-/// - `Err`: `Vec` of all the elements from `iterable` in sequential order. This happens when the
-///   length of `iterable` was less than `amount`. This is considered an error since exactly
-///   `amount` elements is typically expected.
-///
-/// This implementation uses `O(len(iterable))` time and `O(amount)` memory.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::{thread_rng, seq};
-///
-/// let mut rng = thread_rng();
-/// let sample = seq::sample_iter(&mut rng, 1..100, 5).unwrap();
-/// println!("{:?}", sample);
-/// ```
-pub fn sample_iter<T, I, R>(rng: &mut R, iterable: I, amount: usize) -> Result<Vec<T>, Vec<T>>
-    where I: IntoIterator<Item=T>,
-          R: Rng,
-{
-    let mut iter = iterable.into_iter();
-    let mut reservoir = Vec::with_capacity(amount);
-    reservoir.extend(iter.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 iter.enumerate() {
-            let k = rng.gen_range(0, i + 1 + amount);
-            if let Some(spot) = reservoir.get_mut(k) {
-                *spot = elem;
-            }
-        }
-        Ok(reservoir)
-    } else {
-        // Don't hang onto extra memory. There is a corner case where
-        // `amount` was much less than `len(iterable)`.
-        reservoir.shrink_to_fit();
-        Err(reservoir)
-    }
-}
-
-/// Randomly sample exactly `amount` values from `slice`.
-///
-/// The values are non-repeating and in random order.
-///
-/// This implementation uses `O(amount)` time and memory.
-///
-/// Panics if `amount > slice.len()`
-///
-/// # Example
-///
-/// ```rust
-/// use rand::{thread_rng, seq};
-///
-/// let mut rng = thread_rng();
-/// let values = vec![5, 6, 1, 3, 4, 6, 7];
-/// println!("{:?}", seq::sample_slice(&mut rng, &values, 3));
-/// ```
-pub fn sample_slice<R, T>(rng: &mut R, slice: &[T], amount: usize) -> Vec<T>
-    where R: Rng,
-          T: Clone
-{
-    let indices = sample_indices(rng, slice.len(), amount);
-
-    let mut out = Vec::with_capacity(amount);
-    out.extend(indices.iter().map(|i| slice[*i].clone()));
-    out
-}
-
-/// Randomly sample exactly `amount` references from `slice`.
-///
-/// The references are non-repeating and in random order.
-///
-/// This implementation uses `O(amount)` time and memory.
-///
-/// Panics if `amount > slice.len()`
-///
-/// # Example
-///
-/// ```rust
-/// use rand::{thread_rng, seq};
-///
-/// let mut rng = thread_rng();
-/// let values = vec![5, 6, 1, 3, 4, 6, 7];
-/// println!("{:?}", seq::sample_slice_ref(&mut rng, &values, 3));
-/// ```
-pub fn sample_slice_ref<'a, R, T>(rng: &mut R, slice: &'a [T], amount: usize) -> Vec<&'a T>
-    where R: Rng
-{
-    let indices = sample_indices(rng, slice.len(), amount);
-
-    let mut out = Vec::with_capacity(amount);
-    out.extend(indices.iter().map(|i| &slice[*i]));
-    out
-}
-
-/// Randomly sample exactly `amount` indices from `0..length`.
-///
-/// The values are non-repeating and in random order.
-///
-/// This implementation uses `O(amount)` time and memory.
-///
-/// 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.
-///
-/// Panics if `amount > length`
-pub fn sample_indices<R>(rng: &mut R, length: usize, amount: usize) -> Vec<usize>
-    where R: Rng,
-{
-    if amount > length {
-        panic!("`amount` must be less than or equal to `slice.len()`");
-    }
-
-    // We are going to have to allocate at least `amount` for the output no matter what. However,
-    // if we use the `cached` version we will have to allocate `amount` as a HashMap as well since
-    // it inserts an element for every loop.
-    //
-    // Therefore, if `amount >= length / 2` then inplace will be both faster and use less memory.
-    // In fact, benchmarks show the inplace version is faster for length up to about 20 times
-    // faster than amount.
-    //
-    // TODO: there is probably even more fine-tuning that can be done here since
-    // `HashMap::with_capacity(amount)` probably allocates more than `amount` in practice,
-    // and a trade off could probably be made between memory/cpu, since hashmap operations
-    // are slower than array index swapping.
-    if amount >= length / 20 {
-        sample_indices_inplace(rng, length, amount)
-    } else {
-        sample_indices_cache(rng, length, amount)
-    }
-}
-
-/// 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 is better than using a HashMap "cache" when `amount >= length / 2` since it does not
-/// require allocating an extra cache and is much faster.
-fn sample_indices_inplace<R>(rng: &mut R, length: usize, amount: usize) -> Vec<usize>
-    where R: Rng,
-{
-    debug_assert!(amount <= length);
-    let mut indices: Vec<usize> = Vec::with_capacity(length);
-    indices.extend(0..length);
-    for i in 0..amount {
-        let j: usize = rng.gen_range(i, length);
-        let tmp = indices[i];
-        indices[i] = indices[j];
-        indices[j] = tmp;
-    }
-    indices.truncate(amount);
-    debug_assert_eq!(indices.len(), amount);
-    indices
-}
-
-
-/// This method performs a partial fisher-yates on a range of indices using a HashMap
-/// as a cache to record potential collisions.
-///
-/// The cache avoids allocating the entire `length` of values. This is especially useful when
-/// `amount <<< length`, i.e. select 3 non-repeating from 1_000_000
-fn sample_indices_cache<R>(
-    rng: &mut R,
-    length: usize,
-    amount: usize,
-) -> Vec<usize>
-    where R: Rng,
-{
-    debug_assert!(amount <= length);
-    #[cfg(feature="std")] let mut cache = HashMap::with_capacity(amount);
-    #[cfg(not(feature="std"))] let mut cache = BTreeMap::new();
-    let mut out = Vec::with_capacity(amount);
-    for i in 0..amount {
-        let j: usize = rng.gen_range(i, length);
-
-        // equiv: let tmp = slice[i];
-        let tmp = match cache.get(&i) {
-            Some(e) => *e,
-            None => i,
-        };
-
-        // equiv: slice[i] = slice[j];
-        let x = match cache.get(&j) {
-            Some(x) => *x,
-            None => j,
-        };
-
-        // equiv: slice[j] = tmp;
-        cache.insert(j, tmp);
-
-        // note that in the inplace version, slice[i] is automatically "returned" value
-        out.push(x);
-    }
-    debug_assert_eq!(out.len(), amount);
-    out
-}
-
-#[cfg(test)]
-mod test {
-    use super::*;
-    use {thread_rng, XorShiftRng, SeedableRng};
-
-    #[test]
-    fn test_sample_iter() {
-        let min_val = 1;
-        let max_val = 100;
-
-        let mut r = thread_rng();
-        let vals = (min_val..max_val).collect::<Vec<i32>>();
-        let small_sample = sample_iter(&mut r, vals.iter(), 5).unwrap();
-        let large_sample = sample_iter(&mut r, vals.iter(), vals.len() + 5).unwrap_err();
-
-        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]
-    fn test_sample_slice_boundaries() {
-        let empty: &[u8] = &[];
-
-        let mut r = thread_rng();
-
-        // sample 0 items
-        assert_eq!(sample_slice(&mut r, empty, 0), vec![]);
-        assert_eq!(sample_slice(&mut r, &[42, 2, 42], 0), vec![]);
-
-        // sample 1 item
-        assert_eq!(sample_slice(&mut r, &[42], 1), vec![42]);
-        let v = sample_slice(&mut r, &[1, 42], 1)[0];
-        assert!(v == 1 || v == 42);
-
-        // sample "all" the items
-        let v = sample_slice(&mut r, &[42, 133], 2);
-        assert!(v == vec![42, 133] || v == vec![133, 42]);
-
-        assert_eq!(sample_indices_inplace(&mut r, 0, 0), vec![]);
-        assert_eq!(sample_indices_inplace(&mut r, 1, 0), vec![]);
-        assert_eq!(sample_indices_inplace(&mut r, 1, 1), vec![0]);
-
-        assert_eq!(sample_indices_cache(&mut r, 0, 0), vec![]);
-        assert_eq!(sample_indices_cache(&mut r, 1, 0), vec![]);
-        assert_eq!(sample_indices_cache(&mut r, 1, 1), vec![0]);
-
-        // Make sure lucky 777's aren't lucky
-        let slice = &[42, 777];
-        let mut num_42 = 0;
-        let total = 1000;
-        for _ in 0..total {
-            let v = sample_slice(&mut r, slice, 1);
-            assert_eq!(v.len(), 1);
-            let v = v[0];
-            assert!(v == 42 || v == 777);
-            if v == 42 {
-                num_42 += 1;
-            }
-        }
-        let ratio_42 = num_42 as f64 / 1000 as f64;
-        assert!(0.4 <= ratio_42 || ratio_42 <= 0.6, "{}", ratio_42);
-    }
-
-    #[test]
-    fn test_sample_slice() {
-        let xor_rng = XorShiftRng::from_seed;
-
-        let max_range = 100;
-        let mut r = thread_rng();
-
-        for length in 1usize..max_range {
-            let amount = r.gen_range(0, length);
-            let seed: [u32; 4] = [
-                r.next_u32(), r.next_u32(), r.next_u32(), r.next_u32()
-            ];
-
-            println!("Selecting indices: len={}, amount={}, seed={:?}", length, amount, seed);
-
-            // assert that the two index methods give exactly the same result
-            let inplace = sample_indices_inplace(
-                &mut xor_rng(seed), length, amount);
-            let cache = sample_indices_cache(
-                &mut xor_rng(seed), length, amount);
-            assert_eq!(inplace, cache);
-
-            // assert the basics work
-            let regular = sample_indices(
-                &mut xor_rng(seed), length, amount);
-            assert_eq!(regular.len(), amount);
-            assert!(regular.iter().all(|e| *e < length));
-            assert_eq!(regular, inplace);
-
-            // also test that sampling the slice works
-            let vec: Vec<usize> = (0..length).collect();
-            {
-                let result = sample_slice(&mut xor_rng(seed), &vec, amount);
-                assert_eq!(result, regular);
-            }
-
-            {
-                let result = sample_slice_ref(&mut xor_rng(seed), &vec, amount);
-                let expected = regular.iter().map(|v| v).collect::<Vec<_>>();
-                assert_eq!(result, expected);
-            }
-        }
-    }
-}
diff --git a/vendor/rand/utils/ziggurat_tables.py b/vendor/rand/utils/ziggurat_tables.py
deleted file mode 100755
index 762f956..0000000
--- a/vendor/rand/utils/ziggurat_tables.py
+++ /dev/null
@@ -1,127 +0,0 @@
-#!/usr/bin/env python
-#
-# Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-# file at the top-level directory of this distribution and at
-# http://rust-lang.org/COPYRIGHT.
-#
-# 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. 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 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// 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. 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))