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diff --git a/vendor/rand/src/jitter.rs b/vendor/rand/src/jitter.rs
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--- a/vendor/rand/src/jitter.rs
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@@ -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.