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, 234 deletions

diff --git a/rand/rand_distr/src/utils.rs b/rand/rand_distr/src/utils.rs
deleted file mode 100644
index 75b3500..0000000
--- a/rand/rand_distr/src/utils.rs
+++ /dev/null
@@ -1,234 +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.
-
-//! Math helper functions
-
-use rand::Rng;
-use crate::ziggurat_tables;
-use rand::distributions::hidden_export::IntoFloat;
-use core::{cmp, ops};
-
-/// Trait for floating-point scalar types
-/// 
-/// This allows many distributions to work with `f32` or `f64` parameters and is
-/// potentially extensible. Note however that the `Exp1` and `StandardNormal`
-/// distributions are implemented exclusively for `f32` and `f64`.
-/// 
-/// The bounds and methods are based purely on internal
-/// requirements, and will change as needed.
-pub trait Float: Copy + Sized + cmp::PartialOrd
-    + ops::Neg<Output = Self>
-    + ops::Add<Output = Self>
-    + ops::Sub<Output = Self>
-    + ops::Mul<Output = Self>
-    + ops::Div<Output = Self>
-    + ops::AddAssign + ops::SubAssign + ops::MulAssign + ops::DivAssign
-{
-    /// The constant π
-    fn pi() -> Self;
-    /// Support approximate representation of a f64 value
-    fn from(x: f64) -> Self;
-    /// Support converting to an unsigned integer.
-    fn to_u64(self) -> Option<u64>;
-    
-    /// Take the absolute value of self
-    fn abs(self) -> Self;
-    /// Take the largest integer less than or equal to self
-    fn floor(self) -> Self;
-    
-    /// Take the exponential of self
-    fn exp(self) -> Self;
-    /// Take the natural logarithm of self
-    fn ln(self) -> Self;
-    /// Take square root of self
-    fn sqrt(self) -> Self;
-    /// Take self to a floating-point power
-    fn powf(self, power: Self) -> Self;
-    
-    /// Take the tangent of self
-    fn tan(self) -> Self;
-    /// Take the logarithm of the gamma function of self
-    fn log_gamma(self) -> Self;
-}
-
-impl Float for f32 {
-    #[inline]
-    fn pi() -> Self { core::f32::consts::PI }
-    #[inline]
-    fn from(x: f64) -> Self { x as f32 }
-    #[inline]
-    fn to_u64(self) -> Option<u64> {
-        if self >= 0. && self <= ::core::u64::MAX as f32 {
-            Some(self as u64)
-        } else {
-            None
-        }
-    }
-    
-    #[inline]
-    fn abs(self) -> Self { self.abs() }
-    #[inline]
-    fn floor(self) -> Self { self.floor() }
-    
-    #[inline]
-    fn exp(self) -> Self { self.exp() }
-    #[inline]
-    fn ln(self) -> Self { self.ln() }
-    #[inline]
-    fn sqrt(self) -> Self { self.sqrt() }
-    #[inline]
-    fn powf(self, power: Self) -> Self { self.powf(power) }
-    
-    #[inline]
-    fn tan(self) -> Self { self.tan() }
-    #[inline]
-    fn log_gamma(self) -> Self {
-        let result = log_gamma(self.into());
-        assert!(result <= ::core::f32::MAX.into());
-        assert!(result >= ::core::f32::MIN.into());
-        result as f32
-    }
-}
-
-impl Float for f64 {
-    #[inline]
-    fn pi() -> Self { core::f64::consts::PI }
-    #[inline]
-    fn from(x: f64) -> Self { x }
-    #[inline]
-    fn to_u64(self) -> Option<u64> {
-        if self >= 0. && self <= ::core::u64::MAX as f64 {
-            Some(self as u64)
-        } else {
-            None
-        }
-    }
-    
-    #[inline]
-    fn abs(self) -> Self { self.abs() }
-    #[inline]
-    fn floor(self) -> Self { self.floor() }
-    
-    #[inline]
-    fn exp(self) -> Self { self.exp() }
-    #[inline]
-    fn ln(self) -> Self { self.ln() }
-    #[inline]
-    fn sqrt(self) -> Self { self.sqrt() }
-    #[inline]
-    fn powf(self, power: Self) -> Self { self.powf(power) }
-    
-    #[inline]
-    fn tan(self) -> Self { self.tan() }
-    #[inline]
-    fn log_gamma(self) -> Self { log_gamma(self) }
-}
-
-/// Calculates ln(gamma(x)) (natural logarithm of the gamma
-/// function) using the Lanczos approximation.
-///
-/// The approximation expresses the gamma function as:
-/// `gamma(z+1) = sqrt(2*pi)*(z+g+0.5)^(z+0.5)*exp(-z-g-0.5)*Ag(z)`
-/// `g` is an arbitrary constant; we use the approximation with `g=5`.
-///
-/// Noting that `gamma(z+1) = z*gamma(z)` and applying `ln` to both sides:
-/// `ln(gamma(z)) = (z+0.5)*ln(z+g+0.5)-(z+g+0.5) + ln(sqrt(2*pi)*Ag(z)/z)`
-///
-/// `Ag(z)` is an infinite series with coefficients that can be calculated
-/// ahead of time - we use just the first 6 terms, which is good enough
-/// for most purposes.
-pub(crate) fn log_gamma(x: f64) -> f64 {
-    // precalculated 6 coefficients for the first 6 terms of the series
-    let coefficients: [f64; 6] = [
-        76.18009172947146,
-        -86.50532032941677,
-        24.01409824083091,
-        -1.231739572450155,
-        0.1208650973866179e-2,
-        -0.5395239384953e-5,
-    ];
-
-    // (x+0.5)*ln(x+g+0.5)-(x+g+0.5)
-    let tmp = x + 5.5;
-    let log = (x + 0.5) * tmp.ln() - tmp;
-
-    // the first few terms of the series for Ag(x)
-    let mut a = 1.000000000190015;
-    let mut denom = x;
-    for &coeff in &coefficients {
-        denom += 1.0;
-        a += coeff / denom;
-    }
-
-    // get everything together
-    // a is Ag(x)
-    // 2.5066... is sqrt(2pi)
-    log + (2.5066282746310005 * a / x).ln()
-}
-
-/// 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.
-#[inline(always)]
-pub(crate) fn ziggurat<R: Rng + ?Sized, 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 {
-    loop {
-        // As an optimisation we re-implement the conversion to a f64.
-        // From the remaining 12 most significant bits we use 8 to construct `i`.
-        // This saves us generating a whole extra random number, while the added
-        // precision of using 64 bits for f64 does not buy us much.
-        let bits = rng.next_u64();
-        let i = bits as usize & 0xff;
-
-        let u = if symmetric {
-            // Convert to a value in the range [2,4) and substract to get [-1,1)
-            // We can't convert to an open range directly, that would require
-            // substracting `3.0 - EPSILON`, which is not representable.
-            // It is possible with an extra step, but an open range does not
-            // seem neccesary for the ziggurat algorithm anyway.
-            (bits >> 12).into_float_with_exponent(1) - 3.0
-        } else {
-            // Convert to a value in the range [1,2) and substract to get (0,1)
-            (bits >> 12).into_float_with_exponent(0)
-            - (1.0 - std::f64::EPSILON / 2.0)
-        };
-        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;
-        }
-    }
-}