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chore: checkpoint before Python removal

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Sienna Meridian Satterwhite
2026-03-26 22:33:59 +00:00
parent 683cec9307
commit e568ddf82a
29972 changed files with 11269302 additions and 2 deletions
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{"files":{".cargo_vcs_info.json":"688f3db7da538688785f6157b3a74bf589a1e7374090f4bdd6f4668d6915d171",".github/workflows/ci.yml":"de14543d024cd7e8e8af3c17d31a1a6d4be8ee887b28ec0dfec6808220de811d","CHANGELOG.md":"cf3d53107bd2a496c38077226782c468f7ad48e6de4fe73fcc8b187566889dae","COPYRIGHT":"7429802d3e67e3308471b91fbea341e484c4e0a23d0fb230a8636c38184cec79","Cargo.toml":"5bd9c11858db53976ad77e8cfec6142ec515d66bbac254d118dbbe97c6778ede","Cargo.toml.orig":"9d4b5e40e37226c096b612e34009a2c626fa84d693ba2bb734bfe8cca380154b","LICENSE-APACHE":"a60eea817514531668d7e00765731449fe14d059d3249e0bc93b36de45f759f2","LICENSE-MIT":"23f18e03dc49df91622fe2a76176497404e46ced8a715d9d2b67a7446571cca3","README.md":"f0a93bc0b7139543f09b54045b4fdc180575d30948ee781beb9771c17b9178ba","rust-toolchain":"19f1c71cabd3cb062544023af771fbb2883524775fdaed6ca5855bae359b7b9c","src/cofactor.rs":"360def02367e55d932493e2b2fbce53e7d817fdaf8acd6a4823d471283f2f825","src/lib.rs":"ef704cbc23b28c24859fd6cfd2050e1298dbb3da79aa38776859231462643d54","src/prime.rs":"886fd7aaa0763912af25bb147264d73caa699cf3c2f9c0794b8230ce4b0675f3","src/tests/mod.rs":"62ce720485ba3eeddcc2a393f845fc2e8c235a28e9b86d31c453d295e7405a95","src/wnaf.rs":"888ad4643521464c1e21efd9e167c08e77e1801c74250c2425eb6e47f7419972"},"package":"f0f9ef7462f7c099f518d754361858f86d8a07af53ba9af0fe635bbccb151a63"}

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{
"git": {
"sha1": "090a7ec2f2fca9b4ddec05e39123e57dc0d73a2f"
}
}

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name: CI checks
on: [push, pull_request]
jobs:
lint:
name: Lint
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: 1.56.0
override: true
# Ensure all code has been formatted with rustfmt
- run: rustup component add rustfmt
- name: Check formatting
uses: actions-rs/cargo@v1
with:
command: fmt
args: -- --check --color always
test:
name: Test on ${{ matrix.os }}
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ubuntu-latest, windows-latest, macOS-latest]
steps:
- uses: actions/checkout@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: 1.56.0
override: true
- name: cargo fetch
uses: actions-rs/cargo@v1
with:
command: fetch
- name: Build tests
uses: actions-rs/cargo@v1
with:
command: build
args: --verbose --release --tests
- name: Run tests
uses: actions-rs/cargo@v1
with:
command: test
args: --verbose --release
- name: Run --all-features tests
uses: actions-rs/cargo@v1
with:
command: test
args: --all-features --verbose --release
no-std:
name: Check no-std compatibility
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: 1.56.0
override: true
- run: rustup target add thumbv6m-none-eabi
- name: cargo fetch
uses: actions-rs/cargo@v1
with:
command: fetch
- name: Build
uses: actions-rs/cargo@v1
with:
command: build
args: --verbose --target thumbv6m-none-eabi --no-default-features
doc-links:
name: Nightly lint
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: nightly
override: true
- name: cargo fetch
uses: actions-rs/cargo@v1
with:
command: fetch
# Ensure intra-documentation links all resolve correctly
# Requires #![deny(intra_doc_link_resolution_failure)] in crate.
- name: Check intra-doc links
uses: actions-rs/cargo@v1
with:
command: doc
args: --document-private-items

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# Changelog
All notable changes to this library will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this library adheres to Rust's notion of
[Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [Unreleased]
## [0.13.0] - 2022-12-06
### Changed
- Bumped `ff` to `0.13`
## [0.12.1] - 2022-10-13
### Added
- `group::{WnafBase, WnafScalar}` structs for caching precomputations of both
bases and scalars, for improved many-base many-scalar multiplication
performance.
- `impl memuse::DynamicUsage for group::{Wnaf WnafBase, WnafScalar}`, behind the
new `wnaf-memuse` feature flag, to enable the heap usage of these types to be
measured at runtime.
### Changed
- Removed temporary allocations from `Wnaf` internals for improved performance.
## [0.12.0] - 2022-05-04
### Changed
- MSRV is now 1.56.0.
- Bumped `ff` to `0.12`
## [0.11.0] - 2021-09-02
### Fixed
- The affine scalar multiplication bounds on the following traits had typos that
prevented multiplying by `&Self::Scalar`, which has now been fixed:
- `group::cofactor::{CofactorCurve::Affine, CofactorCurveAffine}`
- `group::prime::{PrimeCurve::Affine, PrimeCurveAffine}`
### Added
- `Copy + Send + Sync + 'static` bounds on `group::GroupEncoding::Repr`.
### Changed
- Bumped `ff` to 0.11.
## [0.10.0] - 2021-06-01
### Added
- `group::ff`, which re-exports the `ff` crate to make version-matching easier.
### Changed
- MSRV is now 1.51.0.
- Bumped `ff` to 0.10.
### Removed
- `group::cofactor::CofactorGroup::is_torsion_free` provided implementation
(trait implementors must now implement this method themselves). This avoids
a hard dependency on the `ff/bits` feature flag.
## [0.9.0] - 2021-01-06
### Changed
- Bumped dependencies to `ff 0.9`, `rand_core 0.6`, `rand 0.8`.
## [0.8.0] - 2020-09-08
### Added
- `no_std` support.
### Changed
- MSRV is now 1.44.0.
- Bumped `ff` to 0.8.
- `group::{wnaf, Wnaf, WnafGroup}` are now gated behind the (default-enabled)
`alloc` feature flag. The `byteorder` dependency is now optional.
- `group::tests` is now gated behind the `tests` feature flag. The `rand` and
`rand_xorshift` dependencies are now optional.
### Removed
- `fmt::Display` bound from the following traits:
- `group::Group`
- `group::cofactor::CofactorCurveAffine`
- `group::prime::PrimeCurveAffine`

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Copyrights in the "group" library are retained by their contributors. No
copyright assignment is required to contribute to the "group" library.
The "group" library is licensed under either of
* Apache License, Version 2.0, (see ./LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
* MIT license (see ./LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
Unless you explicitly state otherwise, any contribution intentionally
submitted for inclusion in the work by you, as defined in the Apache-2.0
license, shall be dual licensed as above, without any additional terms or
conditions.

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# THIS FILE IS AUTOMATICALLY GENERATED BY CARGO
#
# When uploading crates to the registry Cargo will automatically
# "normalize" Cargo.toml files for maximal compatibility
# with all versions of Cargo and also rewrite `path` dependencies
# to registry (e.g., crates.io) dependencies.
#
# If you are reading this file be aware that the original Cargo.toml
# will likely look very different (and much more reasonable).
# See Cargo.toml.orig for the original contents.
[package]
edition = "2021"
name = "group"
version = "0.13.0"
authors = ["Sean Bowe <ewillbefull@gmail.com>", "Jack Grigg <jack@z.cash>"]
description = "Elliptic curve group traits and utilities"
homepage = "https://github.com/zkcrypto/group"
documentation = "https://docs.rs/group/"
readme = "README.md"
license = "MIT/Apache-2.0"
repository = "https://github.com/zkcrypto/group"
resolver = "2"
[dependencies.ff]
version = "0.13"
default-features = false
[dependencies.memuse]
version = "0.2"
optional = true
[dependencies.rand]
version = "0.8"
optional = true
default-features = false
[dependencies.rand_core]
version = "0.6"
default-features = false
[dependencies.rand_xorshift]
version = "0.3"
optional = true
[dependencies.subtle]
version = "2.2.1"
default-features = false
[features]
alloc = []
default = ["alloc"]
tests = ["alloc", "rand", "rand_xorshift"]
wnaf-memuse = ["alloc", "memuse"]
[badges.maintenance]
status = "actively-developed"

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Apache License
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http://www.apache.org/licenses/
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Permission is hereby granted, free of charge, to any
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# group [![Crates.io](https://img.shields.io/crates/v/group.svg)](https://crates.io/crates/group) #
`group` is a crate for working with groups over elliptic curves.
## License
Licensed under either of
* Apache License, Version 2.0, ([LICENSE-APACHE](LICENSE-APACHE) or
http://www.apache.org/licenses/LICENSE-2.0)
* MIT license ([LICENSE-MIT](LICENSE-MIT) or http://opensource.org/licenses/MIT)
at your option.
### Contribution
Unless you explicitly state otherwise, any contribution intentionally
submitted for inclusion in the work by you, as defined in the Apache-2.0
license, shall be dual licensed as above, without any additional terms or
conditions.

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1.56.0

100
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use core::fmt;
use core::ops::{Mul, Neg};
use ff::PrimeField;
use subtle::{Choice, CtOption};
use crate::{prime::PrimeGroup, Curve, Group, GroupEncoding, GroupOps, GroupOpsOwned};
/// This trait represents an element of a cryptographic group with a large prime-order
/// subgroup and a comparatively-small cofactor.
pub trait CofactorGroup:
Group
+ GroupEncoding
+ GroupOps<<Self as CofactorGroup>::Subgroup>
+ GroupOpsOwned<<Self as CofactorGroup>::Subgroup>
{
/// The large prime-order subgroup in which cryptographic operations are performed.
/// If `Self` implements `PrimeGroup`, then `Self::Subgroup` may be `Self`.
type Subgroup: PrimeGroup<Scalar = Self::Scalar> + Into<Self>;
/// Maps `self` to the prime-order subgroup by multiplying this element by some
/// `k`-multiple of the cofactor.
///
/// The value `k` does not vary between inputs for a given implementation, but may
/// vary between different implementations of `CofactorGroup` because some groups have
/// more efficient methods of clearing the cofactor when `k` is allowed to be
/// different than `1`.
///
/// If `Self` implements [`PrimeGroup`], this returns `self`.
fn clear_cofactor(&self) -> Self::Subgroup;
/// Returns `self` if it is contained in the prime-order subgroup.
///
/// If `Self` implements [`PrimeGroup`], this returns `Some(self)`.
fn into_subgroup(self) -> CtOption<Self::Subgroup>;
/// Determines if this element is of small order.
///
/// Returns:
/// - `true` if `self` is in the torsion subgroup.
/// - `false` if `self` is not in the torsion subgroup.
fn is_small_order(&self) -> Choice {
self.clear_cofactor().is_identity()
}
/// Determines if this element is "torsion free", i.e., is contained in the
/// prime-order subgroup.
///
/// Returns:
/// - `true` if `self` has trivial torsion and is in the prime-order subgroup.
/// - `false` if `self` has non-zero torsion component and is not in the prime-order
/// subgroup.
fn is_torsion_free(&self) -> Choice;
}
/// Efficient representation of an elliptic curve point guaranteed to be
/// in the correct prime order subgroup.
pub trait CofactorCurve:
Curve<AffineRepr = <Self as CofactorCurve>::Affine> + CofactorGroup
{
type Affine: CofactorCurveAffine<Curve = Self, Scalar = Self::Scalar>
+ Mul<Self::Scalar, Output = Self>
+ for<'r> Mul<&'r Self::Scalar, Output = Self>;
}
/// Affine representation of an elliptic curve point guaranteed to be
/// in the correct prime order subgroup.
pub trait CofactorCurveAffine:
GroupEncoding
+ Copy
+ Clone
+ Sized
+ Send
+ Sync
+ fmt::Debug
+ PartialEq
+ Eq
+ 'static
+ Neg<Output = Self>
+ Mul<<Self as CofactorCurveAffine>::Scalar, Output = <Self as CofactorCurveAffine>::Curve>
+ for<'r> Mul<
&'r <Self as CofactorCurveAffine>::Scalar,
Output = <Self as CofactorCurveAffine>::Curve,
>
{
type Scalar: PrimeField;
type Curve: CofactorCurve<Affine = Self, Scalar = Self::Scalar>;
/// Returns the additive identity.
fn identity() -> Self;
/// Returns a fixed generator of unknown exponent.
fn generator() -> Self;
/// Determines if this point represents the point at infinity; the
/// additive identity.
fn is_identity(&self) -> Choice;
/// Converts this element to its curve representation.
fn to_curve(&self) -> Self::Curve;
}

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#![no_std]
// Catch documentation errors caused by code changes.
#![deny(rustdoc::broken_intra_doc_links)]
#[cfg(feature = "alloc")]
#[macro_use]
extern crate alloc;
// Re-export ff to make version-matching easier.
pub use ff;
use core::fmt;
use core::iter::Sum;
use core::ops::{Add, AddAssign, Mul, MulAssign, Neg, Sub, SubAssign};
use ff::PrimeField;
use rand_core::RngCore;
use subtle::{Choice, CtOption};
pub mod cofactor;
pub mod prime;
#[cfg(feature = "tests")]
pub mod tests;
#[cfg(feature = "alloc")]
mod wnaf;
#[cfg(feature = "alloc")]
pub use self::wnaf::{Wnaf, WnafBase, WnafGroup, WnafScalar};
/// A helper trait for types with a group operation.
pub trait GroupOps<Rhs = Self, Output = Self>:
Add<Rhs, Output = Output> + Sub<Rhs, Output = Output> + AddAssign<Rhs> + SubAssign<Rhs>
{
}
impl<T, Rhs, Output> GroupOps<Rhs, Output> for T where
T: Add<Rhs, Output = Output> + Sub<Rhs, Output = Output> + AddAssign<Rhs> + SubAssign<Rhs>
{
}
/// A helper trait for references with a group operation.
pub trait GroupOpsOwned<Rhs = Self, Output = Self>: for<'r> GroupOps<&'r Rhs, Output> {}
impl<T, Rhs, Output> GroupOpsOwned<Rhs, Output> for T where T: for<'r> GroupOps<&'r Rhs, Output> {}
/// A helper trait for types implementing group scalar multiplication.
pub trait ScalarMul<Rhs, Output = Self>: Mul<Rhs, Output = Output> + MulAssign<Rhs> {}
impl<T, Rhs, Output> ScalarMul<Rhs, Output> for T where T: Mul<Rhs, Output = Output> + MulAssign<Rhs>
{}
/// A helper trait for references implementing group scalar multiplication.
pub trait ScalarMulOwned<Rhs, Output = Self>: for<'r> ScalarMul<&'r Rhs, Output> {}
impl<T, Rhs, Output> ScalarMulOwned<Rhs, Output> for T where T: for<'r> ScalarMul<&'r Rhs, Output> {}
/// This trait represents an element of a cryptographic group.
pub trait Group:
Clone
+ Copy
+ fmt::Debug
+ Eq
+ Sized
+ Send
+ Sync
+ 'static
+ Sum
+ for<'a> Sum<&'a Self>
+ Neg<Output = Self>
+ GroupOps
+ GroupOpsOwned
+ ScalarMul<<Self as Group>::Scalar>
+ ScalarMulOwned<<Self as Group>::Scalar>
{
/// Scalars modulo the order of this group's scalar field.
type Scalar: PrimeField;
/// Returns an element chosen uniformly at random from the non-identity elements of
/// this group.
///
/// This function is non-deterministic, and samples from the user-provided RNG.
fn random(rng: impl RngCore) -> Self;
/// Returns the additive identity, also known as the "neutral element".
fn identity() -> Self;
/// Returns a fixed generator of the prime-order subgroup.
fn generator() -> Self;
/// Determines if this point is the identity.
fn is_identity(&self) -> Choice;
/// Doubles this element.
#[must_use]
fn double(&self) -> Self;
}
/// Efficient representation of an elliptic curve point guaranteed.
pub trait Curve:
Group + GroupOps<<Self as Curve>::AffineRepr> + GroupOpsOwned<<Self as Curve>::AffineRepr>
{
/// The affine representation for this elliptic curve.
type AffineRepr;
/// Converts a batch of projective elements into affine elements. This function will
/// panic if `p.len() != q.len()`.
fn batch_normalize(p: &[Self], q: &mut [Self::AffineRepr]) {
assert_eq!(p.len(), q.len());
for (p, q) in p.iter().zip(q.iter_mut()) {
*q = p.to_affine();
}
}
/// Converts this element into its affine representation.
fn to_affine(&self) -> Self::AffineRepr;
}
pub trait GroupEncoding: Sized {
/// The encoding of group elements.
///
/// The `Default` implementation is not required to return a valid point encoding. The
/// bound is present to enable encodings to be constructed generically:
/// ```
/// # use group::GroupEncoding;
/// # use subtle::CtOption;
/// # struct G;
/// # impl GroupEncoding for G {
/// # type Repr = [u8; 0];
/// # fn from_bytes(bytes: &Self::Repr) -> CtOption<Self> { unimplemented!() }
/// # fn from_bytes_unchecked(bytes: &Self::Repr) -> CtOption<Self> { unimplemented!() }
/// # fn to_bytes(&self) -> Self::Repr { unimplemented!() }
/// # }
/// # let buf = &[0u8; 0][..];
/// let mut encoding = <G as GroupEncoding>::Repr::default();
/// encoding.as_mut().copy_from_slice(buf);
/// ```
///
/// It is recommended that the default should be the all-zeroes encoding.
type Repr: Copy + Default + Send + Sync + 'static + AsRef<[u8]> + AsMut<[u8]>;
/// Attempts to deserialize a group element from its encoding.
fn from_bytes(bytes: &Self::Repr) -> CtOption<Self>;
/// Attempts to deserialize a group element, not checking if the element is valid.
///
/// **This is dangerous to call unless you trust the bytes you are reading; otherwise,
/// API invariants may be broken.** Please consider using
/// [`GroupEncoding::from_bytes`] instead.
fn from_bytes_unchecked(bytes: &Self::Repr) -> CtOption<Self>;
/// Converts this element into its byte encoding. This may or may not support
/// encoding the identity.
// TODO: Figure out how to handle identity encoding generically.
fn to_bytes(&self) -> Self::Repr;
}
/// Affine representation of a point on an elliptic curve that has a defined uncompressed
/// encoding.
pub trait UncompressedEncoding: Sized {
type Uncompressed: Default + AsRef<[u8]> + AsMut<[u8]>;
/// Attempts to deserialize an element from its uncompressed encoding.
fn from_uncompressed(bytes: &Self::Uncompressed) -> CtOption<Self>;
/// Attempts to deserialize an uncompressed element, not checking if the element is in
/// the correct subgroup.
///
/// **This is dangerous to call unless you trust the bytes you are reading; otherwise,
/// API invariants may be broken.** Please consider using
/// [`UncompressedEncoding::from_uncompressed`] instead.
fn from_uncompressed_unchecked(bytes: &Self::Uncompressed) -> CtOption<Self>;
/// Converts this element into its uncompressed encoding, so long as it's not
/// the point at infinity.
fn to_uncompressed(&self) -> Self::Uncompressed;
}

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vendor/group/src/prime.rs vendored Normal file
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use core::fmt;
use core::ops::{Mul, Neg};
use ff::PrimeField;
use subtle::Choice;
use crate::{Curve, Group, GroupEncoding};
/// This trait represents an element of a prime-order cryptographic group.
pub trait PrimeGroup: Group + GroupEncoding {}
/// Efficient representation of an elliptic curve point guaranteed to be
/// in the correct prime order subgroup.
pub trait PrimeCurve: Curve<AffineRepr = <Self as PrimeCurve>::Affine> + PrimeGroup {
type Affine: PrimeCurveAffine<Curve = Self, Scalar = Self::Scalar>
+ Mul<Self::Scalar, Output = Self>
+ for<'r> Mul<&'r Self::Scalar, Output = Self>;
}
/// Affine representation of an elliptic curve point guaranteed to be
/// in the correct prime order subgroup.
pub trait PrimeCurveAffine: GroupEncoding
+ Copy
+ Clone
+ Sized
+ Send
+ Sync
+ fmt::Debug
+ PartialEq
+ Eq
+ 'static
+ Neg<Output = Self>
+ Mul<<Self as PrimeCurveAffine>::Scalar, Output = <Self as PrimeCurveAffine>::Curve>
+ for<'r> Mul<&'r <Self as PrimeCurveAffine>::Scalar, Output = <Self as PrimeCurveAffine>::Curve>
{
type Scalar: PrimeField;
type Curve: PrimeCurve<Affine = Self, Scalar = Self::Scalar>;
/// Returns the additive identity.
fn identity() -> Self;
/// Returns a fixed generator of unknown exponent.
fn generator() -> Self;
/// Determines if this point represents the point at infinity; the
/// additive identity.
fn is_identity(&self) -> Choice;
/// Converts this element to its curve representation.
fn to_curve(&self) -> Self::Curve;
}

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use alloc::vec::Vec;
use core::ops::{Mul, Neg};
use ff::{Field, PrimeField};
use rand::SeedableRng;
use rand_xorshift::XorShiftRng;
use crate::{
prime::{PrimeCurve, PrimeCurveAffine},
wnaf::WnafGroup,
GroupEncoding, UncompressedEncoding,
};
pub fn curve_tests<G: PrimeCurve>() {
let mut rng = XorShiftRng::from_seed([
0x59, 0x62, 0xbe, 0x5d, 0x76, 0x3d, 0x31, 0x8d, 0x17, 0xdb, 0x37, 0x32, 0x54, 0x06, 0xbc,
0xe5,
]);
// Negation edge case with identity.
{
let z = G::identity().neg();
assert!(bool::from(z.is_identity()));
}
// Doubling edge case with identity.
{
let z = G::identity().double();
assert!(bool::from(z.is_identity()));
}
// Addition edge cases with identity
{
let mut r = G::random(&mut rng);
let rcopy = r;
r.add_assign(&G::identity());
assert_eq!(r, rcopy);
r.add_assign(&G::Affine::identity());
assert_eq!(r, rcopy);
let mut z = G::identity();
z.add_assign(&G::identity());
assert!(bool::from(z.is_identity()));
z.add_assign(&G::Affine::identity());
assert!(bool::from(z.is_identity()));
let mut z2 = z;
z2.add_assign(&r);
z.add_assign(&r.to_affine());
assert_eq!(z, z2);
assert_eq!(z, r);
}
// Transformations
{
let a = G::random(&mut rng);
let b = a.to_affine().to_curve();
let c = a.to_affine().to_curve().to_affine().to_curve();
assert_eq!(a, b);
assert_eq!(b, c);
}
random_addition_tests::<G>();
random_multiplication_tests::<G>();
random_doubling_tests::<G>();
random_negation_tests::<G>();
random_transformation_tests::<G>();
random_compressed_encoding_tests::<G>();
}
pub fn random_wnaf_tests<G: WnafGroup>() {
use crate::wnaf::*;
let mut rng = XorShiftRng::from_seed([
0x59, 0x62, 0xbe, 0x5d, 0x76, 0x3d, 0x31, 0x8d, 0x17, 0xdb, 0x37, 0x32, 0x54, 0x06, 0xbc,
0xe5,
]);
{
let mut table = vec![];
let mut wnaf = vec![];
for w in 2..14 {
for _ in 0..100 {
let g = G::random(&mut rng);
let s = G::Scalar::random(&mut rng);
let mut g1 = g;
g1.mul_assign(s);
wnaf_table(&mut table, g, w);
wnaf_form(&mut wnaf, s.to_repr(), w);
let g2 = wnaf_exp(&table, &wnaf);
assert_eq!(g1, g2);
}
}
}
{
fn only_compiles_if_send<S: Send>(_: &S) {}
for _ in 0..100 {
let g = G::random(&mut rng);
let s = G::Scalar::random(&mut rng);
let mut g1 = g;
g1.mul_assign(s);
let g2 = {
let mut wnaf = Wnaf::new();
wnaf.base(g, 1).scalar(&s)
};
let g3 = {
let mut wnaf = Wnaf::new();
wnaf.scalar(&s).base(g)
};
let g4 = {
let mut wnaf = Wnaf::new();
let mut shared = wnaf.base(g, 1).shared();
only_compiles_if_send(&shared);
shared.scalar(&s)
};
let g5 = {
let mut wnaf = Wnaf::new();
let mut shared = wnaf.scalar(&s).shared();
only_compiles_if_send(&shared);
shared.base(g)
};
let g6 = {
let mut wnaf = Wnaf::new();
{
// Populate the vectors.
wnaf.base(G::random(&mut rng), 1)
.scalar(&G::Scalar::random(&mut rng));
}
wnaf.base(g, 1).scalar(&s)
};
let g7 = {
let mut wnaf = Wnaf::new();
{
// Populate the vectors.
wnaf.base(G::random(&mut rng), 1)
.scalar(&G::Scalar::random(&mut rng));
}
wnaf.scalar(&s).base(g)
};
let g8 = {
let mut wnaf = Wnaf::new();
{
// Populate the vectors.
wnaf.base(G::random(&mut rng), 1)
.scalar(&G::Scalar::random(&mut rng));
}
let mut shared = wnaf.base(g, 1).shared();
only_compiles_if_send(&shared);
shared.scalar(&s)
};
let g9 = {
let mut wnaf = Wnaf::new();
{
// Populate the vectors.
wnaf.base(G::random(&mut rng), 1)
.scalar(&G::Scalar::random(&mut rng));
}
let mut shared = wnaf.scalar(&s).shared();
only_compiles_if_send(&shared);
shared.base(g)
};
assert_eq!(g1, g2);
assert_eq!(g1, g3);
assert_eq!(g1, g4);
assert_eq!(g1, g5);
assert_eq!(g1, g6);
assert_eq!(g1, g7);
assert_eq!(g1, g8);
assert_eq!(g1, g9);
}
}
}
fn random_negation_tests<G: PrimeCurve>() {
let mut rng = XorShiftRng::from_seed([
0x59, 0x62, 0xbe, 0x5d, 0x76, 0x3d, 0x31, 0x8d, 0x17, 0xdb, 0x37, 0x32, 0x54, 0x06, 0xbc,
0xe5,
]);
for _ in 0..1000 {
let r = G::random(&mut rng);
let s = G::Scalar::random(&mut rng);
let sneg = s.neg();
let mut t1 = r;
t1.mul_assign(s);
let mut t2 = r;
t2.mul_assign(sneg);
let mut t3 = t1;
t3.add_assign(&t2);
assert!(bool::from(t3.is_identity()));
let mut t4 = t1;
t4.add_assign(&t2.to_affine());
assert!(bool::from(t4.is_identity()));
assert_eq!(t1.neg(), t2);
}
}
fn random_doubling_tests<G: PrimeCurve>() {
let mut rng = XorShiftRng::from_seed([
0x59, 0x62, 0xbe, 0x5d, 0x76, 0x3d, 0x31, 0x8d, 0x17, 0xdb, 0x37, 0x32, 0x54, 0x06, 0xbc,
0xe5,
]);
for _ in 0..1000 {
let mut a = G::random(&mut rng);
let mut b = G::random(&mut rng);
// 2(a + b)
let tmp1 = (a + b).double();
// 2a + 2b
a = a.double();
b = b.double();
let mut tmp2 = a;
tmp2.add_assign(&b);
let mut tmp3 = a;
tmp3.add_assign(&b.to_affine());
assert_eq!(tmp1, tmp2);
assert_eq!(tmp1, tmp3);
}
}
fn random_multiplication_tests<G: PrimeCurve>() {
let mut rng = XorShiftRng::from_seed([
0x59, 0x62, 0xbe, 0x5d, 0x76, 0x3d, 0x31, 0x8d, 0x17, 0xdb, 0x37, 0x32, 0x54, 0x06, 0xbc,
0xe5,
]);
for _ in 0..1000 {
let mut a = G::random(&mut rng);
let mut b = G::random(&mut rng);
let a_affine = a.to_affine();
let b_affine = b.to_affine();
let s = G::Scalar::random(&mut rng);
// s ( a + b )
let mut tmp1 = a;
tmp1.add_assign(&b);
tmp1.mul_assign(s);
// sa + sb
a.mul_assign(s);
b.mul_assign(s);
let mut tmp2 = a;
tmp2.add_assign(&b);
// Affine multiplication
let mut tmp3 = Mul::<G::Scalar>::mul(a_affine, s);
tmp3.add_assign(Mul::<G::Scalar>::mul(b_affine, s));
assert_eq!(tmp1, tmp2);
assert_eq!(tmp1, tmp3);
}
}
fn random_addition_tests<G: PrimeCurve>() {
let mut rng = XorShiftRng::from_seed([
0x59, 0x62, 0xbe, 0x5d, 0x76, 0x3d, 0x31, 0x8d, 0x17, 0xdb, 0x37, 0x32, 0x54, 0x06, 0xbc,
0xe5,
]);
for _ in 0..1000 {
let a = G::random(&mut rng);
let b = G::random(&mut rng);
let c = G::random(&mut rng);
let a_affine = a.to_affine();
let b_affine = b.to_affine();
let c_affine = c.to_affine();
// a + a should equal the doubling
{
let mut aplusa = a;
aplusa.add_assign(&a);
let mut aplusamixed = a;
aplusamixed.add_assign(&a.to_affine());
let adouble = a.double();
assert_eq!(aplusa, adouble);
assert_eq!(aplusa, aplusamixed);
}
let mut tmp = vec![G::identity(); 6];
// (a + b) + c
tmp[0] = a;
tmp[0].add_assign(&b);
tmp[0].add_assign(&c);
// a + (b + c)
tmp[1] = b;
tmp[1].add_assign(&c);
tmp[1].add_assign(&a);
// (a + c) + b
tmp[2] = a;
tmp[2].add_assign(&c);
tmp[2].add_assign(&b);
// Mixed addition
// (a + b) + c
tmp[3] = a_affine.to_curve();
tmp[3].add_assign(&b_affine);
tmp[3].add_assign(&c_affine);
// a + (b + c)
tmp[4] = b_affine.to_curve();
tmp[4].add_assign(&c_affine);
tmp[4].add_assign(&a_affine);
// (a + c) + b
tmp[5] = a_affine.to_curve();
tmp[5].add_assign(&c_affine);
tmp[5].add_assign(&b_affine);
// Comparisons
for i in 0..6 {
for j in 0..6 {
assert_eq!(tmp[i], tmp[j]);
assert_eq!(tmp[i].to_affine(), tmp[j].to_affine());
}
assert!(tmp[i] != a);
assert!(tmp[i] != b);
assert!(tmp[i] != c);
assert!(a != tmp[i]);
assert!(b != tmp[i]);
assert!(c != tmp[i]);
}
}
}
fn random_transformation_tests<G: PrimeCurve>() {
let mut rng = XorShiftRng::from_seed([
0x59, 0x62, 0xbe, 0x5d, 0x76, 0x3d, 0x31, 0x8d, 0x17, 0xdb, 0x37, 0x32, 0x54, 0x06, 0xbc,
0xe5,
]);
for _ in 0..1000 {
let g = G::random(&mut rng);
let g_affine = g.to_affine();
let g_projective = g_affine.to_curve();
assert_eq!(g, g_projective);
}
// Batch normalization
for _ in 0..10 {
let mut v = (0..1000).map(|_| G::random(&mut rng)).collect::<Vec<_>>();
use rand::distributions::{Distribution, Uniform};
let between = Uniform::new(0, 1000);
// Sprinkle in some normalized points
for _ in 0..5 {
v[between.sample(&mut rng)] = G::identity();
}
for _ in 0..5 {
let s = between.sample(&mut rng);
v[s] = v[s].to_affine().to_curve();
}
let expected_v = v.iter().map(|v| v.to_affine()).collect::<Vec<_>>();
let mut normalized = vec![G::Affine::identity(); v.len()];
G::batch_normalize(&v, &mut normalized);
assert_eq!(normalized, expected_v);
}
}
fn random_compressed_encoding_tests<G: PrimeCurve>() {
let mut rng = XorShiftRng::from_seed([
0x59, 0x62, 0xbe, 0x5d, 0x76, 0x3d, 0x31, 0x8d, 0x17, 0xdb, 0x37, 0x32, 0x54, 0x06, 0xbc,
0xe5,
]);
assert_eq!(
G::Affine::from_bytes(&G::Affine::identity().to_bytes()).unwrap(),
G::Affine::identity()
);
for _ in 0..1000 {
let mut r = G::random(&mut rng).to_affine();
let compressed = r.to_bytes();
let de_compressed = G::Affine::from_bytes(&compressed).unwrap();
assert_eq!(de_compressed, r);
r = r.neg();
let compressed = r.to_bytes();
let de_compressed = G::Affine::from_bytes(&compressed).unwrap();
assert_eq!(de_compressed, r);
}
}
pub fn random_uncompressed_encoding_tests<G: PrimeCurve>()
where
<G as PrimeCurve>::Affine: UncompressedEncoding,
{
let mut rng = XorShiftRng::from_seed([
0x59, 0x62, 0xbe, 0x5d, 0x76, 0x3d, 0x31, 0x8d, 0x17, 0xdb, 0x37, 0x32, 0x54, 0x06, 0xbc,
0xe5,
]);
assert_eq!(
G::Affine::from_uncompressed(&G::Affine::identity().to_uncompressed()).unwrap(),
G::Affine::identity()
);
for _ in 0..1000 {
let r = G::random(&mut rng).to_affine();
let uncompressed = r.to_uncompressed();
let de_uncompressed = G::Affine::from_uncompressed(&uncompressed).unwrap();
assert_eq!(de_uncompressed, r);
}
}

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use alloc::vec::Vec;
use core::iter;
use core::marker::PhantomData;
use core::ops::Mul;
use ff::PrimeField;
use super::Group;
/// Extension trait on a [`Group`] that provides helpers used by [`Wnaf`].
pub trait WnafGroup: Group {
/// Recommends a wNAF window size given the number of scalars you intend to multiply
/// a base by. Always returns a number between 2 and 22, inclusive.
fn recommended_wnaf_for_num_scalars(num_scalars: usize) -> usize;
}
/// Replaces the contents of `table` with a w-NAF window table for the given window size.
pub(crate) fn wnaf_table<G: Group>(table: &mut Vec<G>, mut base: G, window: usize) {
table.truncate(0);
table.reserve(1 << (window - 1));
let dbl = base.double();
for _ in 0..(1 << (window - 1)) {
table.push(base);
base.add_assign(&dbl);
}
}
/// This struct represents a view of a sequence of bytes as a sequence of
/// `u64` limbs in little-endian byte order. It maintains a current index, and
/// allows access to the limb at that index and the one following it. Bytes
/// beyond the end of the original buffer are treated as zero.
struct LimbBuffer<'a> {
buf: &'a [u8],
cur_idx: usize,
cur_limb: u64,
next_limb: u64,
}
impl<'a> LimbBuffer<'a> {
fn new(buf: &'a [u8]) -> Self {
let mut ret = Self {
buf,
cur_idx: 0,
cur_limb: 0,
next_limb: 0,
};
// Initialise the limb buffers.
ret.increment_limb();
ret.increment_limb();
ret.cur_idx = 0usize;
ret
}
fn increment_limb(&mut self) {
self.cur_idx += 1;
self.cur_limb = self.next_limb;
match self.buf.len() {
// There are no more bytes in the buffer; zero-extend.
0 => self.next_limb = 0,
// There are fewer bytes in the buffer than a u64 limb; zero-extend.
x @ 1..=7 => {
let mut next_limb = [0; 8];
next_limb[..x].copy_from_slice(self.buf);
self.next_limb = u64::from_le_bytes(next_limb);
self.buf = &[];
}
// There are at least eight bytes in the buffer; read the next u64 limb.
_ => {
let (next_limb, rest) = self.buf.split_at(8);
self.next_limb = u64::from_le_bytes(next_limb.try_into().unwrap());
self.buf = rest;
}
}
}
fn get(&mut self, idx: usize) -> (u64, u64) {
assert!([self.cur_idx, self.cur_idx + 1].contains(&idx));
if idx > self.cur_idx {
self.increment_limb();
}
(self.cur_limb, self.next_limb)
}
}
/// Replaces the contents of `wnaf` with the w-NAF representation of a little-endian
/// scalar.
pub(crate) fn wnaf_form<S: AsRef<[u8]>>(wnaf: &mut Vec<i64>, c: S, window: usize) {
// Required by the NAF definition
debug_assert!(window >= 2);
// Required so that the NAF digits fit in i64
debug_assert!(window <= 64);
let bit_len = c.as_ref().len() * 8;
wnaf.truncate(0);
wnaf.reserve(bit_len);
// Initialise the current and next limb buffers.
let mut limbs = LimbBuffer::new(c.as_ref());
let width = 1u64 << window;
let window_mask = width - 1;
let mut pos = 0;
let mut carry = 0;
while pos < bit_len {
// Construct a buffer of bits of the scalar, starting at bit `pos`
let u64_idx = pos / 64;
let bit_idx = pos % 64;
let (cur_u64, next_u64) = limbs.get(u64_idx);
let bit_buf = if bit_idx + window < 64 {
// This window's bits are contained in a single u64
cur_u64 >> bit_idx
} else {
// Combine the current u64's bits with the bits from the next u64
(cur_u64 >> bit_idx) | (next_u64 << (64 - bit_idx))
};
// Add the carry into the current window
let window_val = carry + (bit_buf & window_mask);
if window_val & 1 == 0 {
// If the window value is even, preserve the carry and emit 0.
// Why is the carry preserved?
// If carry == 0 and window_val & 1 == 0, then the next carry should be 0
// If carry == 1 and window_val & 1 == 0, then bit_buf & 1 == 1 so the next carry should be 1
wnaf.push(0);
pos += 1;
} else {
wnaf.push(if window_val < width / 2 {
carry = 0;
window_val as i64
} else {
carry = 1;
(window_val as i64).wrapping_sub(width as i64)
});
wnaf.extend(iter::repeat(0).take(window - 1));
pos += window;
}
}
}
/// Performs w-NAF exponentiation with the provided window table and w-NAF form scalar.
///
/// This function must be provided a `table` and `wnaf` that were constructed with
/// the same window size; otherwise, it may panic or produce invalid results.
pub(crate) fn wnaf_exp<G: Group>(table: &[G], wnaf: &[i64]) -> G {
let mut result = G::identity();
let mut found_one = false;
for n in wnaf.iter().rev() {
if found_one {
result = result.double();
}
if *n != 0 {
found_one = true;
if *n > 0 {
result += &table[(n / 2) as usize];
} else {
result -= &table[((-n) / 2) as usize];
}
}
}
result
}
/// A "w-ary non-adjacent form" scalar multiplication (also known as exponentiation)
/// context.
///
/// # Examples
///
/// This struct can be used to implement several patterns:
///
/// ## One base, one scalar
///
/// For this pattern, you can use a transient `Wnaf` context:
///
/// ```ignore
/// use group::Wnaf;
///
/// let result = Wnaf::new().scalar(&scalar).base(base);
/// ```
///
/// ## Many bases, one scalar
///
/// For this pattern, you create a `Wnaf` context, load the scalar into it, and then
/// process each base in turn:
///
/// ```ignore
/// use group::Wnaf;
///
/// let mut wnaf = Wnaf::new();
/// let mut wnaf_scalar = wnaf.scalar(&scalar);
/// let results: Vec<_> = bases
/// .into_iter()
/// .map(|base| wnaf_scalar.base(base))
/// .collect();
/// ```
///
/// ## One base, many scalars
///
/// For this pattern, you create a `Wnaf` context, load the base into it, and then process
/// each scalar in turn:
///
/// ```ignore
/// use group::Wnaf;
///
/// let mut wnaf = Wnaf::new();
/// let mut wnaf_base = wnaf.base(base, scalars.len());
/// let results: Vec<_> = scalars
/// .iter()
/// .map(|scalar| wnaf_base.scalar(scalar))
/// .collect();
/// ```
///
/// ## Many bases, many scalars
///
/// Say you have `n` bases and `m` scalars, and want to produce `n * m` results. For this
/// pattern, you need to cache the w-NAF tables for the bases and then compute the w-NAF
/// form of the scalars on the fly for every base, or vice versa:
///
/// ```ignore
/// use group::Wnaf;
///
/// let mut wnaf_contexts: Vec<_> = (0..bases.len()).map(|_| Wnaf::new()).collect();
/// let mut wnaf_bases: Vec<_> = wnaf_contexts
/// .iter_mut()
/// .zip(bases)
/// .map(|(wnaf, base)| wnaf.base(base, scalars.len()))
/// .collect();
/// let results: Vec<_> = wnaf_bases
/// .iter()
/// .flat_map(|wnaf_base| scalars.iter().map(|scalar| wnaf_base.scalar(scalar)))
/// .collect();
/// ```
///
/// Alternatively, use the [`WnafBase`] and [`WnafScalar`] types, which enable the various
/// tables and w-NAF forms to be cached individually per base and scalar. These types can
/// then be directly multiplied without any additional runtime work, at the cost of fixing
/// a specific window size (rather than choosing the window size dynamically).
#[derive(Debug)]
pub struct Wnaf<W, B, S> {
base: B,
scalar: S,
window_size: W,
}
impl<G: Group> Wnaf<(), Vec<G>, Vec<i64>> {
/// Construct a new wNAF context without allocating.
pub fn new() -> Self {
Wnaf {
base: vec![],
scalar: vec![],
window_size: (),
}
}
}
#[cfg(feature = "wnaf-memuse")]
impl<G: Group + memuse::DynamicUsage> memuse::DynamicUsage for Wnaf<(), Vec<G>, Vec<i64>> {
fn dynamic_usage(&self) -> usize {
self.base.dynamic_usage() + self.scalar.dynamic_usage()
}
fn dynamic_usage_bounds(&self) -> (usize, Option<usize>) {
let (base_lower, base_upper) = self.base.dynamic_usage_bounds();
let (scalar_lower, scalar_upper) = self.scalar.dynamic_usage_bounds();
(
base_lower + scalar_lower,
base_upper.zip(scalar_upper).map(|(a, b)| a + b),
)
}
}
impl<G: WnafGroup> Wnaf<(), Vec<G>, Vec<i64>> {
/// Given a base and a number of scalars, compute a window table and return a `Wnaf` object that
/// can perform exponentiations with `.scalar(..)`.
pub fn base(&mut self, base: G, num_scalars: usize) -> Wnaf<usize, &[G], &mut Vec<i64>> {
// Compute the appropriate window size based on the number of scalars.
let window_size = G::recommended_wnaf_for_num_scalars(num_scalars);
// Compute a wNAF table for the provided base and window size.
wnaf_table(&mut self.base, base, window_size);
// Return a Wnaf object that immutably borrows the computed base storage location,
// but mutably borrows the scalar storage location.
Wnaf {
base: &self.base[..],
scalar: &mut self.scalar,
window_size,
}
}
/// Given a scalar, compute its wNAF representation and return a `Wnaf` object that can perform
/// exponentiations with `.base(..)`.
pub fn scalar(&mut self, scalar: &<G as Group>::Scalar) -> Wnaf<usize, &mut Vec<G>, &[i64]> {
// We hard-code a window size of 4.
let window_size = 4;
// Compute the wNAF form of the scalar.
wnaf_form(&mut self.scalar, scalar.to_repr(), window_size);
// Return a Wnaf object that mutably borrows the base storage location, but
// immutably borrows the computed wNAF form scalar location.
Wnaf {
base: &mut self.base,
scalar: &self.scalar[..],
window_size,
}
}
}
impl<'a, G: Group> Wnaf<usize, &'a [G], &'a mut Vec<i64>> {
/// Constructs new space for the scalar representation while borrowing
/// the computed window table, for sending the window table across threads.
pub fn shared(&self) -> Wnaf<usize, &'a [G], Vec<i64>> {
Wnaf {
base: self.base,
scalar: vec![],
window_size: self.window_size,
}
}
}
#[cfg(feature = "wnaf-memuse")]
impl<'a, G: Group> memuse::DynamicUsage for Wnaf<usize, &'a [G], Vec<i64>> {
fn dynamic_usage(&self) -> usize {
// The heap memory for the window table is counted in the parent `Wnaf`.
self.scalar.dynamic_usage()
}
fn dynamic_usage_bounds(&self) -> (usize, Option<usize>) {
self.scalar.dynamic_usage_bounds()
}
}
impl<'a, G: Group> Wnaf<usize, &'a mut Vec<G>, &'a [i64]> {
/// Constructs new space for the window table while borrowing
/// the computed scalar representation, for sending the scalar representation
/// across threads.
pub fn shared(&self) -> Wnaf<usize, Vec<G>, &'a [i64]> {
Wnaf {
base: vec![],
scalar: self.scalar,
window_size: self.window_size,
}
}
}
#[cfg(feature = "wnaf-memuse")]
impl<'a, G: Group + memuse::DynamicUsage> memuse::DynamicUsage for Wnaf<usize, Vec<G>, &'a [i64]> {
fn dynamic_usage(&self) -> usize {
// The heap memory for the scalar representation is counted in the parent `Wnaf`.
self.base.dynamic_usage()
}
fn dynamic_usage_bounds(&self) -> (usize, Option<usize>) {
self.base.dynamic_usage_bounds()
}
}
impl<B, S: AsRef<[i64]>> Wnaf<usize, B, S> {
/// Performs exponentiation given a base.
pub fn base<G: Group>(&mut self, base: G) -> G
where
B: AsMut<Vec<G>>,
{
wnaf_table(self.base.as_mut(), base, self.window_size);
wnaf_exp(self.base.as_mut(), self.scalar.as_ref())
}
}
impl<B, S: AsMut<Vec<i64>>> Wnaf<usize, B, S> {
/// Performs exponentiation given a scalar.
pub fn scalar<G: Group>(&mut self, scalar: &<G as Group>::Scalar) -> G
where
B: AsRef<[G]>,
{
wnaf_form(self.scalar.as_mut(), scalar.to_repr(), self.window_size);
wnaf_exp(self.base.as_ref(), self.scalar.as_mut())
}
}
/// A "w-ary non-adjacent form" scalar, that uses precomputation to improve the speed of
/// scalar multiplication.
///
/// # Examples
///
/// See [`WnafBase`] for usage examples.
#[derive(Clone, Debug)]
pub struct WnafScalar<F: PrimeField, const WINDOW_SIZE: usize> {
wnaf: Vec<i64>,
field: PhantomData<F>,
}
#[cfg(feature = "wnaf-memuse")]
impl<F: PrimeField, const WINDOW_SIZE: usize> memuse::DynamicUsage for WnafScalar<F, WINDOW_SIZE> {
fn dynamic_usage(&self) -> usize {
self.wnaf.dynamic_usage()
}
fn dynamic_usage_bounds(&self) -> (usize, Option<usize>) {
self.wnaf.dynamic_usage_bounds()
}
}
impl<F: PrimeField, const WINDOW_SIZE: usize> WnafScalar<F, WINDOW_SIZE> {
/// Computes the w-NAF representation of the given scalar with the specified
/// `WINDOW_SIZE`.
pub fn new(scalar: &F) -> Self {
let mut wnaf = vec![];
// Compute the w-NAF form of the scalar.
wnaf_form(&mut wnaf, scalar.to_repr(), WINDOW_SIZE);
WnafScalar {
wnaf,
field: PhantomData::default(),
}
}
}
/// A fixed window table for a group element, precomputed to improve the speed of scalar
/// multiplication.
///
/// This struct is designed for usage patterns that have long-term cached bases and/or
/// scalars, or [Cartesian products] of bases and scalars. The [`Wnaf`] API enables one or
/// the other to be cached, but requires either the base window tables or the scalar w-NAF
/// forms to be computed repeatedly on the fly, which can become a significant performance
/// issue for some use cases.
///
/// `WnafBase` and [`WnafScalar`] enable an alternative trade-off: by fixing the window
/// size at compile time, the precomputations are guaranteed to only occur once per base
/// and once per scalar. Users should select their window size based on how long the bases
/// are expected to live; a larger window size will consume more memory and take longer to
/// precompute, but result in faster scalar multiplications.
///
/// [Cartesian products]: https://en.wikipedia.org/wiki/Cartesian_product
///
/// # Examples
///
/// ```ignore
/// use group::{WnafBase, WnafScalar};
///
/// let wnaf_bases: Vec<_> = bases.into_iter().map(WnafBase::<_, 4>::new).collect();
/// let wnaf_scalars: Vec<_> = scalars.iter().map(WnafScalar::new).collect();
/// let results: Vec<_> = wnaf_bases
/// .iter()
/// .flat_map(|base| wnaf_scalars.iter().map(|scalar| base * scalar))
/// .collect();
/// ```
///
/// Note that this pattern requires specifying a fixed window size (unlike previous
/// patterns that picked a suitable window size internally). This is necessary to ensure
/// in the type system that the base and scalar `Wnaf`s were computed with the same window
/// size, allowing the result to be computed infallibly.
#[derive(Clone, Debug)]
pub struct WnafBase<G: Group, const WINDOW_SIZE: usize> {
table: Vec<G>,
}
#[cfg(feature = "wnaf-memuse")]
impl<G: Group + memuse::DynamicUsage, const WINDOW_SIZE: usize> memuse::DynamicUsage
for WnafBase<G, WINDOW_SIZE>
{
fn dynamic_usage(&self) -> usize {
self.table.dynamic_usage()
}
fn dynamic_usage_bounds(&self) -> (usize, Option<usize>) {
self.table.dynamic_usage_bounds()
}
}
impl<G: Group, const WINDOW_SIZE: usize> WnafBase<G, WINDOW_SIZE> {
/// Computes a window table for the given base with the specified `WINDOW_SIZE`.
pub fn new(base: G) -> Self {
let mut table = vec![];
// Compute a window table for the provided base and window size.
wnaf_table(&mut table, base, WINDOW_SIZE);
WnafBase { table }
}
}
impl<G: Group, const WINDOW_SIZE: usize> Mul<&WnafScalar<G::Scalar, WINDOW_SIZE>>
for &WnafBase<G, WINDOW_SIZE>
{
type Output = G;
fn mul(self, rhs: &WnafScalar<G::Scalar, WINDOW_SIZE>) -> Self::Output {
wnaf_exp(&self.table, &rhs.wnaf)
}
}

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