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    // 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_) }
        }
    }

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