fix errors

Author: newpavlov

rand_core/src/block.rs

@@ -20,33 +20,33 @@
 //! reseeding with very low overhead.
 //!
 //! # Example
-//! 
+//!
 //! ```norun
 //! use rand_core::block::{BlockRngCore, BlockRng};
-//! 
+//!
 //! struct MyRngCore;
-//! 
+//!
 //! impl BlockRngCore for MyRngCore {
 //!     type Results = [u32; 16];
-//!     
+//!
 //!     fn generate(&mut self, results: &mut Self::Results) {
 //!         unimplemented!()
 //!     }
 //! }
-//! 
+//!
 //! impl SeedableRng for MyRngCore {
 //!     type Seed = unimplemented!();
 //!     fn from_seed(seed: Self::Seed) -> Self {
 //!         unimplemented!()
 //!     }
 //! }
-//! 
+//!
 //! // optionally, also implement CryptoRng for MyRngCore
-//! 
+//!
 //! // Final RNG.
 //! type MyRng = BlockRng<u32, MyRngCore>;
 //! ```
-//! 
+//!
 //! [`BlockRngCore`]: crate::block::BlockRngCore
 //! [`fill_bytes`]: RngCore::fill_bytes
 
@@ -58,12 +58,12 @@ use impls::{fill_via_u32_chunks, fill_via_u64_chunks};
 /// A trait for RNGs which do not generate random numbers individually, but in
 /// blocks (typically `[u32; N]`). This technique is commonly used by
 /// cryptographic RNGs to improve performance.
-/// 
+///
 /// See the [module][crate::block] documentation for details.
 pub trait BlockRngCore {
     /// Results element type, e.g. `u32`.
     type Item;
-    
+
     /// Results type. This is the 'block' an RNG implementing `BlockRngCore`
     /// generates, which will usually be an array like `[u32; 16]`.
     type Results: AsRef<[Self::Item]> + AsMut<[Self::Item]> + Default;
@@ -141,7 +141,7 @@ impl<R: BlockRngCore> BlockRng<R> {
     }
 
     /// Get the index into the result buffer.
-    /// 
+    ///
     /// If this is equal to or larger than the size of the result buffer then
     /// the buffer is "empty" and `generate()` must be called to produce new
     /// results.

rand_core/src/lib.rs

@@ -8,23 +8,23 @@
 // except according to those terms.
 
 //! Random number generation traits
-//! 
+//!
 //! This crate is mainly of interest to crates publishing implementations of
 //! [`RngCore`]. Other users are encouraged to use the [`rand`] crate instead
 //! which re-exports the main traits and error types.
 //!
 //! [`RngCore`] is the core trait implemented by algorithmic pseudo-random number
 //! generators and external random-number sources.
-//! 
+//!
 //! [`SeedableRng`] is an extension trait for construction from fixed seeds and
 //! other random number generators.
-//! 
+//!
 //! [`Error`] is provided for error-handling. It is safe to use in `no_std`
 //! environments.
-//! 
+//!
 //! The [`impls`] and [`le`] sub-modules include a few small functions to assist
 //! implementation of [`RngCore`].
-//! 
+//!
 //! [`rand`]: https://docs.rs/rand
 
 #![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
@@ -60,34 +60,34 @@ pub mod le;
 
 
 /// The core of a random number generator.
-/// 
+///
 /// This trait encapsulates the low-level functionality common to all
 /// generators, and is the "back end", to be implemented by generators.
-/// End users should normally use `Rng` trait from the [`rand`] crate,
+/// End users should normally use the `Rng` trait from the [`rand`] crate,
 /// which is automatically implemented for every type implementing `RngCore`.
-/// 
+///
 /// Three different methods for generating random data are provided since the
 /// optimal implementation of each is dependent on the type of generator. There
 /// is no required relationship between the output of each; e.g. many
 /// implementations of [`fill_bytes`] consume a whole number of `u32` or `u64`
 /// values and drop any remaining unused bytes.
-/// 
+///
 /// The [`try_fill_bytes`] method is a variant of [`fill_bytes`] allowing error
 /// handling; it is not deemed sufficiently useful to add equivalents for
 /// [`next_u32`] or [`next_u64`] since the latter methods are almost always used
 /// with algorithmic generators (PRNGs), which are normally infallible.
-/// 
+///
 /// Algorithmic generators implementing [`SeedableRng`] should normally have
 /// *portable, reproducible* output, i.e. fix Endianness when converting values
 /// to avoid platform differences, and avoid making any changes which affect
 /// output (except by communicating that the release has breaking changes).
-/// 
+///
 /// Typically implementators will implement only one of the methods available
 /// in this trait directly, then use the helper functions from the
 /// [`impls`] module to implement the other methods.
-/// 
+///
 /// It is recommended that implementations also implement:
-/// 
+///
 /// - `Debug` with a custom implementation which *does not* print any internal
 ///   state (at least, [`CryptoRng`]s should not risk leaking state through
 ///   `Debug`).
@@ -99,37 +99,37 @@ pub mod le;
 ///   implement [`SeedableRng`], to guide users towards proper seeding.
 ///   External / hardware RNGs can choose to implement `Default`.
 /// - `Eq` and `PartialEq` could be implemented, but are probably not useful.
-/// 
+///
 /// # Example
-/// 
+///
 /// A simple example, obviously not generating very *random* output:
-/// 
+///
 /// ```
 /// #![allow(dead_code)]
 /// use rand_core::{RngCore, Error, impls};
-/// 
+///
 /// struct CountingRng(u64);
-/// 
+///
 /// impl RngCore for CountingRng {
 ///     fn next_u32(&mut self) -> u32 {
 ///         self.next_u64() as u32
 ///     }
-///     
+///
 ///     fn next_u64(&mut self) -> u64 {
 ///         self.0 += 1;
 ///         self.0
 ///     }
-///     
+///
 ///     fn fill_bytes(&mut self, dest: &mut [u8]) {
 ///         impls::fill_bytes_via_next(self, dest)
 ///     }
-///     
+///
 ///     fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
 ///         Ok(self.fill_bytes(dest))
 ///     }
 /// }
 /// ```
-/// 
+///
 /// [`rand`]: https://docs.rs/rand
 /// [`try_fill_bytes`]: RngCore::try_fill_bytes
 /// [`fill_bytes`]: RngCore::fill_bytes
@@ -148,7 +148,7 @@ pub trait RngCore {
     ///
     /// RNGs must implement at least one method from this trait directly. In
     /// the case this method is not implemented directly, it can be implemented
-    /// via [`next_u32`][impls::next_u64_via_u32] or via 
+    /// via [`next_u32`][impls::next_u64_via_u32] or via
     /// [`fill_bytes`][impls::next_u64_via_fill].
     fn next_u64(&mut self) -> u64;
 
@@ -161,7 +161,7 @@ pub trait RngCore {
     /// fail the implementation must choose how best to handle errors here
     /// (e.g. panic with a descriptive message or log a warning and retry a few
     /// times).
-    /// 
+    ///
     /// This method should guarantee that `dest` is entirely filled
     /// with new data, and may panic if this is impossible
     /// (e.g. reading past the end of a file that is being used as the
@@ -174,49 +174,49 @@ pub trait RngCore {
     /// generating random data thus making this the primary method implemented
     /// by external (true) RNGs (e.g. `OsRng`) which can fail. It may be used
     /// directly to generate keys and to seed (infallible) PRNGs.
-    /// 
+    ///
     /// Other than error handling, this method is identical to [`fill_bytes`];
     /// thus this may be implemented using `Ok(self.fill_bytes(dest))` or
     /// `fill_bytes` may be implemented with
     /// `self.try_fill_bytes(dest).unwrap()` or more specific error handling.
-    /// 
+    ///
     /// [`fill_bytes`]: RngCore::fill_bytes
     fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error>;
 }
 
 /// A marker trait used to indicate that an [`RngCore`] or [`BlockRngCore`]
 /// implementation is supposed to be cryptographically secure.
-/// 
+///
 /// *Cryptographically secure generators*, also known as *CSPRNGs*, should
 /// satisfy an additional properties over other generators: given the first
 /// *k* bits of an algorithm's output
 /// sequence, it should not be possible using polynomial-time algorithms to
 /// predict the next bit with probability significantly greater than 50%.
-/// 
+///
 /// Some generators may satisfy an additional property, however this is not
 /// required by this trait: if the CSPRNG's state is revealed, it should not be
 /// computationally-feasible to reconstruct output prior to this. Some other
 /// generators allow backwards-computation and are consided *reversible*.
-/// 
+///
 /// Note that this trait is provided for guidance only and cannot guarantee
 /// suitability for cryptographic applications. In general it should only be
 /// implemented for well-reviewed code implementing well-regarded algorithms.
-/// 
+///
 /// Note also that use of a `CryptoRng` does not protect against other
 /// weaknesses such as seeding from a weak entropy source or leaking state.
-/// 
+///
 /// [`BlockRngCore`]: block::BlockRngCore
 pub trait CryptoRng {}
 
 /// A random number generator that can be explicitly seeded.
 ///
 /// This trait encapsulates the low-level functionality common to all
 /// pseudo-random number generators (PRNGs, or algorithmic generators).
-/// 
-/// The `FromEntropy` trait from [`rand`] crate is automatically
+///
+/// The `FromEntropy` trait from the [`rand`] crate is automatically
 /// implemented for every type implementing `SeedableRng`, providing
 /// a convenient `from_entropy()` constructor.
-/// 
+///
 /// [`rand`]: https://docs.rs/rand
 pub trait SeedableRng: Sized {
     /// Seed type, which is restricted to types mutably-dereferencable as `u8`
@@ -288,17 +288,17 @@ pub trait SeedableRng: Sized {
     /// for example `0xBAD5EEDu32` or `0x0DDB1A5E5BAD5EEDu64` ("odd biases? bad
     /// seed"). This is assuming only a small number of values must be rejected.
     fn from_seed(seed: Self::Seed) -> Self;
-    
+
     /// Create a new PRNG using a `u64` seed.
-    /// 
+    ///
     /// This is a convenience-wrapper around `from_seed` to allow construction
     /// of any `SeedableRng` from a simple `u64` value. It is designed such that
     /// low Hamming Weight numbers like 0 and 1 can be used and should still
     /// result in good, independent seeds to the PRNG which is returned.
-    /// 
+    ///
     /// This **is not suitable for cryptography**, as should be clear given that
     /// the input size is only 64 bits.
-    /// 
+    ///
     /// Implementations for PRNGs *may* provide their own implementations of
     /// this function, but the default implementation should be good enough for
     /// all purposes. *Changing* the implementation of this function should be
@@ -307,33 +307,33 @@ pub trait SeedableRng: Sized {
         // We use PCG32 to generate a u32 sequence, and copy to the seed
         const MUL: u64 = 6364136223846793005;
         const INC: u64 = 11634580027462260723;
-        
+
         let mut seed = Self::Seed::default();
         for chunk in seed.as_mut().chunks_mut(4) {
             // We advance the state first (to get away from the input value,
             // in case it has low Hamming Weight).
             state = state.wrapping_mul(MUL).wrapping_add(INC);
-            
+
             // Use PCG output function with to_le to generate x:
             let xorshifted = (((state >> 18) ^ state) >> 27) as u32;
             let rot = (state >> 59) as u32;
             let x = xorshifted.rotate_right(rot).to_le();
-            
+
             unsafe {
                 let p = &x as *const u32 as *const u8;
                 copy_nonoverlapping(p, chunk.as_mut_ptr(), chunk.len());
             }
         }
-        
+
         Self::from_seed(seed)
     }
-    
+
     /// Create a new PRNG seeded from another `Rng`.
     ///
     /// This is the recommended way to initialize PRNGs with fresh entropy. The
-    /// `FromEntropy` trait from [`rand`] crate provides a convenient
+    /// `FromEntropy` trait from the [`rand`] crate provides a convenient
     /// `from_entropy` method based on `from_rng`.
-    /// 
+    ///
     /// Usage of this method is not recommended when reproducibility is required
     /// since implementing PRNGs are not required to fix Endianness and are
     /// allowed to modify implementations in new releases.
@@ -346,7 +346,7 @@ pub trait SeedableRng: Sized {
     /// between them.
     ///
     /// Prefer to seed from a strong external entropy source like `OsRng` from
-    /// [`rand_os`] crate or from a cryptographic PRNG; if creating a new
+    /// the [`rand_os`] crate or from a cryptographic PRNG; if creating a new
     /// generator for cryptographic uses you *must* seed from a strong source.
     ///
     /// Seeding a small PRNG from another small PRNG is possible, but
@@ -357,7 +357,7 @@ pub trait SeedableRng: Sized {
     ///
     /// PRNG implementations are allowed to assume that a good RNG is provided
     /// for seeding, and that it is cryptographically secure when appropriate.
-    /// 
+    ///
     /// [`rand`]: https://docs.rs/rand
     /// [`rand_os`]: https://docs.rs/rand_os
     fn from_rng<R: RngCore>(mut rng: R) -> Result<Self, Error> {
@@ -436,7 +436,7 @@ impl<R: CryptoRng + ?Sized> CryptoRng for Box<R> {}
 #[cfg(test)]
 mod test {
     use super::*;
-    
+
     #[test]
     fn test_seed_from_u64() {
         struct SeedableNum(u64);
@@ -448,29 +448,29 @@ mod test {
                 SeedableNum(x[0])
             }
         }
-        
+
         const N: usize = 8;
         const SEEDS: [u64; N] = [0u64, 1, 2, 3, 4, 8, 16, -1i64 as u64];
         let mut results = [0u64; N];
         for (i, seed) in SEEDS.iter().enumerate() {
             let SeedableNum(x) = SeedableNum::seed_from_u64(*seed);
             results[i] = x;
         }
-        
+
         for (i1, r1) in results.iter().enumerate() {
             let weight = r1.count_ones();
             // This is the binomial distribution B(64, 0.5), so chance of
             // weight < 20 is binocdf(19, 64, 0.5) = 7.8e-4, and same for
             // weight > 44.
             assert!(weight >= 20 && weight <= 44);
-            
+
             for (i2, r2) in results.iter().enumerate() {
                 if i1 == i2 { continue; }
                 let diff_weight = (r1 ^ r2).count_ones();
                 assert!(diff_weight >= 20);
             }
         }
-        
+
         // value-breakage test:
         assert_eq!(results[0], 5029875928683246316);
     }