Remove vendored dependencies

While it appears that by now we actually can get successful builds
without Cargo insisting on Internet access by virtue of using the
--frozen flag, maintaining vendored dependencies is somewhat of a pain
point. This state will also get worse with upcoming changes that replace
argparse in favor of structopt and pull in a slew of new dependencies by
doing so. Then there is also the repository structure aspect, which is
non-standard due to the way we vendor dependencies and a potential
source of confusion.
In order to fix these problems, this change removes all the vendored
dependencies we have.

Delete subrepo argparse/:argparse
Delete subrepo base32/:base32
Delete subrepo cc/:cc
Delete subrepo cfg-if/:cfg-if
Delete subrepo getrandom/:getrandom
Delete subrepo lazy-static/:lazy-static
Delete subrepo libc/:libc
Delete subrepo nitrokey-sys/:nitrokey-sys
Delete subrepo nitrokey/:nitrokey
Delete subrepo rand/:rand

1 files changed, 0 insertions, 363 deletions

diff --git a/rand/src/distributions/weighted/mod.rs b/rand/src/distributions/weighted/mod.rs
deleted file mode 100644
index 2711637..0000000
--- a/rand/src/distributions/weighted/mod.rs
+++ /dev/null
@@ -1,363 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! Weighted index sampling
-//! 
-//! This module provides two implementations for sampling indices:
-//! 
-//! *   [`WeightedIndex`] allows `O(log N)` sampling
-//! *   [`alias_method::WeightedIndex`] allows `O(1)` sampling, but with
-//!      much greater set-up cost
-//!      
-//! [`alias_method::WeightedIndex`]: alias_method/struct.WeightedIndex.html
-
-pub mod alias_method;
-
-use crate::Rng;
-use crate::distributions::Distribution;
-use crate::distributions::uniform::{UniformSampler, SampleUniform, SampleBorrow};
-use core::cmp::PartialOrd;
-use core::fmt;
-
-// Note that this whole module is only imported if feature="alloc" is enabled.
-#[cfg(not(feature="std"))] use crate::alloc::vec::Vec;
-
-/// A distribution using weighted sampling to pick a discretely selected
-/// item.
-///
-/// Sampling a `WeightedIndex` distribution returns the index of a randomly
-/// selected element from the iterator used when the `WeightedIndex` was
-/// created. The chance of a given element being picked is proportional to the
-/// value of the element. The weights can use any type `X` for which an
-/// implementation of [`Uniform<X>`] exists.
-///
-/// # Performance
-///
-/// A `WeightedIndex<X>` contains a `Vec<X>` and a [`Uniform<X>`] and so its
-/// size is the sum of the size of those objects, possibly plus some alignment.
-///
-/// Creating a `WeightedIndex<X>` will allocate enough space to hold `N - 1`
-/// weights of type `X`, where `N` is the number of weights. However, since
-/// `Vec` doesn't guarantee a particular growth strategy, additional memory
-/// might be allocated but not used. Since the `WeightedIndex` object also
-/// contains, this might cause additional allocations, though for primitive
-/// types, ['Uniform<X>`] doesn't allocate any memory.
-///
-/// Time complexity of sampling from `WeightedIndex` is `O(log N)` where
-/// `N` is the number of weights.
-///
-/// Sampling from `WeightedIndex` will result in a single call to
-/// `Uniform<X>::sample` (method of the [`Distribution`] trait), which typically
-/// will request a single value from the underlying [`RngCore`], though the
-/// exact number depends on the implementaiton of `Uniform<X>::sample`.
-///
-/// # Example
-///
-/// ```
-/// use rand::prelude::*;
-/// use rand::distributions::WeightedIndex;
-///
-/// let choices = ['a', 'b', 'c'];
-/// let weights = [2,   1,   1];
-/// let dist = WeightedIndex::new(&weights).unwrap();
-/// let mut rng = thread_rng();
-/// for _ in 0..100 {
-///     // 50% chance to print 'a', 25% chance to print 'b', 25% chance to print 'c'
-///     println!("{}", choices[dist.sample(&mut rng)]);
-/// }
-///
-/// let items = [('a', 0), ('b', 3), ('c', 7)];
-/// let dist2 = WeightedIndex::new(items.iter().map(|item| item.1)).unwrap();
-/// for _ in 0..100 {
-///     // 0% chance to print 'a', 30% chance to print 'b', 70% chance to print 'c'
-///     println!("{}", items[dist2.sample(&mut rng)].0);
-/// }
-/// ```
-///
-/// [`Uniform<X>`]: crate::distributions::uniform::Uniform
-/// [`RngCore`]: crate::RngCore
-#[derive(Debug, Clone)]
-pub struct WeightedIndex<X: SampleUniform + PartialOrd> {
-    cumulative_weights: Vec<X>,
-    total_weight: X,
-    weight_distribution: X::Sampler,
-}
-
-impl<X: SampleUniform + PartialOrd> WeightedIndex<X> {
-    /// Creates a new a `WeightedIndex` [`Distribution`] using the values
-    /// in `weights`. The weights can use any type `X` for which an
-    /// implementation of [`Uniform<X>`] exists.
-    ///
-    /// Returns an error if the iterator is empty, if any weight is `< 0`, or
-    /// if its total value is 0.
-    ///
-    /// [`Uniform<X>`]: crate::distributions::uniform::Uniform
-    pub fn new<I>(weights: I) -> Result<WeightedIndex<X>, WeightedError>
-        where I: IntoIterator,
-              I::Item: SampleBorrow<X>,
-              X: for<'a> ::core::ops::AddAssign<&'a X> +
-                 Clone +
-                 Default {
-        let mut iter = weights.into_iter();
-        let mut total_weight: X = iter.next()
-                                      .ok_or(WeightedError::NoItem)?
-                                      .borrow()
-                                      .clone();
-
-        let zero = <X as Default>::default();
-        if total_weight < zero {
-            return Err(WeightedError::InvalidWeight);
-        }
-
-        let mut weights = Vec::<X>::with_capacity(iter.size_hint().0);
-        for w in iter {
-            if *w.borrow() < zero {
-                return Err(WeightedError::InvalidWeight);
-            }
-            weights.push(total_weight.clone());
-            total_weight += w.borrow();
-        }
-
-        if total_weight == zero {
-            return Err(WeightedError::AllWeightsZero);
-        }
-        let distr = X::Sampler::new(zero, total_weight.clone());
-
-        Ok(WeightedIndex { cumulative_weights: weights, total_weight, weight_distribution: distr })
-    }
-
-    /// Update a subset of weights, without changing the number of weights.
-    ///
-    /// `new_weights` must be sorted by the index.
-    ///
-    /// Using this method instead of `new` might be more efficient if only a small number of
-    /// weights is modified. No allocations are performed, unless the weight type `X` uses
-    /// allocation internally.
-    ///
-    /// In case of error, `self` is not modified.
-    pub fn update_weights(&mut self, new_weights: &[(usize, &X)]) -> Result<(), WeightedError>
-        where X: for<'a> ::core::ops::AddAssign<&'a X> +
-                 for<'a> ::core::ops::SubAssign<&'a X> +
-                 Clone +
-                 Default {
-        if new_weights.is_empty() {
-            return Ok(());
-        }
-
-        let zero = <X as Default>::default();
-
-        let mut total_weight = self.total_weight.clone();
-
-        // Check for errors first, so we don't modify `self` in case something
-        // goes wrong.
-        let mut prev_i = None;
-        for &(i, w) in new_weights {
-            if let Some(old_i) = prev_i {
-                if old_i >= i {
-                    return Err(WeightedError::InvalidWeight);
-                }
-            }
-            if *w < zero {
-                return Err(WeightedError::InvalidWeight);
-            }
-            if i >= self.cumulative_weights.len() + 1 {
-                return Err(WeightedError::TooMany);
-            }
-
-            let mut old_w = if i < self.cumulative_weights.len() {
-                self.cumulative_weights[i].clone()
-            } else {
-                self.total_weight.clone()
-            };
-            if i > 0 {
-                old_w -= &self.cumulative_weights[i - 1];
-            }
-
-            total_weight -= &old_w;
-            total_weight += w;
-            prev_i = Some(i);
-        }
-        if total_weight == zero {
-            return Err(WeightedError::AllWeightsZero);
-        }
-
-        // Update the weights. Because we checked all the preconditions in the
-        // previous loop, this should never panic.
-        let mut iter = new_weights.iter();
-
-        let mut prev_weight = zero.clone();
-        let mut next_new_weight = iter.next();
-        let &(first_new_index, _) = next_new_weight.unwrap();
-        let mut cumulative_weight = if first_new_index > 0 {
-            self.cumulative_weights[first_new_index - 1].clone()
-        } else {
-            zero.clone() 
-        };
-        for i in first_new_index..self.cumulative_weights.len() {
-            match next_new_weight {
-                Some(&(j, w)) if i == j => {
-                    cumulative_weight += w;
-                    next_new_weight = iter.next();
-                },
-                _ => {
-                    let mut tmp = self.cumulative_weights[i].clone();
-                    tmp -= &prev_weight;  // We know this is positive.
-                    cumulative_weight += &tmp;
-                }
-            }
-            prev_weight = cumulative_weight.clone();
-            core::mem::swap(&mut prev_weight, &mut self.cumulative_weights[i]);
-        }
-
-        self.total_weight = total_weight;
-        self.weight_distribution = X::Sampler::new(zero, self.total_weight.clone());
-
-        Ok(())
-    }
-}
-
-impl<X> Distribution<usize> for WeightedIndex<X> where
-    X: SampleUniform + PartialOrd {
-    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> usize {
-        use ::core::cmp::Ordering;
-        let chosen_weight = self.weight_distribution.sample(rng);
-        // Find the first item which has a weight *higher* than the chosen weight.
-        self.cumulative_weights.binary_search_by(
-            |w| if *w <= chosen_weight { Ordering::Less } else { Ordering::Greater }).unwrap_err()
-    }
-}
-
-#[cfg(test)]
-mod test {
-    use super::*;
-
-    #[test]
-    #[cfg(not(miri))] // Miri is too slow
-    fn test_weightedindex() {
-        let mut r = crate::test::rng(700);
-        const N_REPS: u32 = 5000;
-        let weights = [1u32, 2, 3, 0, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7];
-        let total_weight = weights.iter().sum::<u32>() as f32;
-
-        let verify = |result: [i32; 14]| {
-            for (i, count) in result.iter().enumerate() {
-                let exp = (weights[i] * N_REPS) as f32 / total_weight;
-                let mut err = (*count as f32 - exp).abs();
-                if err != 0.0 {
-                    err /= exp;
-                }
-                assert!(err <= 0.25);
-            }
-        };
-
-        // WeightedIndex from vec
-        let mut chosen = [0i32; 14];
-        let distr = WeightedIndex::new(weights.to_vec()).unwrap();
-        for _ in 0..N_REPS {
-            chosen[distr.sample(&mut r)] += 1;
-        }
-        verify(chosen);
-
-        // WeightedIndex from slice
-        chosen = [0i32; 14];
-        let distr = WeightedIndex::new(&weights[..]).unwrap();
-        for _ in 0..N_REPS {
-            chosen[distr.sample(&mut r)] += 1;
-        }
-        verify(chosen);
-
-        // WeightedIndex from iterator
-        chosen = [0i32; 14];
-        let distr = WeightedIndex::new(weights.iter()).unwrap();
-        for _ in 0..N_REPS {
-            chosen[distr.sample(&mut r)] += 1;
-        }
-        verify(chosen);
-
-        for _ in 0..5 {
-            assert_eq!(WeightedIndex::new(&[0, 1]).unwrap().sample(&mut r), 1);
-            assert_eq!(WeightedIndex::new(&[1, 0]).unwrap().sample(&mut r), 0);
-            assert_eq!(WeightedIndex::new(&[0, 0, 0, 0, 10, 0]).unwrap().sample(&mut r), 4);
-        }
-
-        assert_eq!(WeightedIndex::new(&[10][0..0]).unwrap_err(), WeightedError::NoItem);
-        assert_eq!(WeightedIndex::new(&[0]).unwrap_err(), WeightedError::AllWeightsZero);
-        assert_eq!(WeightedIndex::new(&[10, 20, -1, 30]).unwrap_err(), WeightedError::InvalidWeight);
-        assert_eq!(WeightedIndex::new(&[-10, 20, 1, 30]).unwrap_err(), WeightedError::InvalidWeight);
-        assert_eq!(WeightedIndex::new(&[-10]).unwrap_err(), WeightedError::InvalidWeight);
-    }
-
-    #[test]
-    fn test_update_weights() {
-        let data = [
-            (&[10u32, 2, 3, 4][..],
-             &[(1, &100), (2, &4)][..],  // positive change
-             &[10, 100, 4, 4][..]),
-            (&[1u32, 2, 3, 0, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7][..],
-             &[(2, &1), (5, &1), (13, &100)][..],  // negative change and last element
-             &[1u32, 2, 1, 0, 5, 1, 7, 1, 2, 3, 4, 5, 6, 100][..]),
-        ];
-
-        for (weights, update, expected_weights) in data.into_iter() {
-            let total_weight = weights.iter().sum::<u32>();
-            let mut distr = WeightedIndex::new(weights.to_vec()).unwrap();
-            assert_eq!(distr.total_weight, total_weight);
-
-            distr.update_weights(update).unwrap();
-            let expected_total_weight = expected_weights.iter().sum::<u32>();
-            let expected_distr = WeightedIndex::new(expected_weights.to_vec()).unwrap();
-            assert_eq!(distr.total_weight, expected_total_weight);
-            assert_eq!(distr.total_weight, expected_distr.total_weight);
-            assert_eq!(distr.cumulative_weights, expected_distr.cumulative_weights);
-        }
-    }
-}
-
-/// Error type returned from `WeightedIndex::new`.
-#[derive(Debug, Clone, Copy, PartialEq, Eq)]
-pub enum WeightedError {
-    /// The provided weight collection contains no items.
-    NoItem,
-
-    /// A weight is either less than zero, greater than the supported maximum or
-    /// otherwise invalid.
-    InvalidWeight,
-
-    /// All items in the provided weight collection are zero.
-    AllWeightsZero,
-    
-    /// Too many weights are provided (length greater than `u32::MAX`)
-    TooMany,
-}
-
-impl WeightedError {
-    fn msg(&self) -> &str {
-        match *self {
-            WeightedError::NoItem => "No weights provided.",
-            WeightedError::InvalidWeight => "A weight is invalid.",
-            WeightedError::AllWeightsZero => "All weights are zero.",
-            WeightedError::TooMany => "Too many weights (hit u32::MAX)",
-        }
-    }
-}
-
-#[cfg(feature="std")]
-impl ::std::error::Error for WeightedError {
-    fn description(&self) -> &str {
-        self.msg()
-    }
-    fn cause(&self) -> Option<&dyn (::std::error::Error)> {
-        None
-    }
-}
-
-impl fmt::Display for WeightedError {
-    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
-        write!(f, "{}", self.msg())
-    }
-}