M-Labs/nalgebra
3
0
Fork 1
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge pull request #1104 from dimforge/dev

Browse Source 
Release v0.31.0
This commit is contained in:
Sébastien Crozet 2022-04-30 14:08:22 +02:00 committed by GitHub
commit b7d7b69777
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
64 changed files with 2236 additions and 1041 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
.github/workflows/nalgebra-ci-build.yml vendored
View File

@ -38,8 +38,12 @@ jobs:
run: cargo build --features serde-serialize
- name: Build nalgebra-lapack
run: cd nalgebra-lapack; cargo build;
- name: Build nalgebra-sparse
- name: Build nalgebra-sparse --no-default-features
run: cd nalgebra-sparse; cargo build --no-default-features;
- name: Build nalgebra-sparse (default features)
run: cd nalgebra-sparse; cargo build;
- name: Build nalgebra-sparse --all-features
run: cd nalgebra-sparse; cargo build --all-features;
# Run this on it’s own job because it alone takes a lot of time.
# So it’s best to let it run in parallel to the other jobs.
build-nalgebra-all-features:
@ -57,13 +61,13 @@ jobs:
steps:
- uses: actions/checkout@v2
- name: test
run: cargo test --features arbitrary,rand,serde-serialize,abomonation-serialize,sparse,debug,io,compare,libm,proptest-support,slow-tests;
run: cargo test --features arbitrary,rand,serde-serialize,sparse,debug,io,compare,libm,proptest-support,slow-tests;
test-nalgebra-glm:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: test nalgebra-glm
run: cargo test -p nalgebra-glm --features arbitrary,serde-serialize,abomonation-serialize;
run: cargo test -p nalgebra-glm --features arbitrary,serde-serialize;
test-nalgebra-sparse:
runs-on: ubuntu-latest
steps:
@ -71,10 +75,10 @@ jobs:
- name: test nalgebra-sparse
# Manifest-path is necessary because cargo otherwise won't correctly forward features
# We increase number of proptest cases to hopefully catch more potential bugs
run: PROPTEST_CASES=10000 cargo test --manifest-path=nalgebra-sparse/Cargo.toml --features compare,proptest-support,io
run: PROPTEST_CASES=10000 cargo test --manifest-path=nalgebra-sparse/Cargo.toml --features compare,proptest-support,io,serde-serialize
- name: test nalgebra-sparse (slow tests)
# Unfortunately, the "slow-tests" take so much time that we need to run them with --release
run: PROPTEST_CASES=10000 cargo test --release --manifest-path=nalgebra-sparse/Cargo.toml --features compare,proptest-support,io,slow-tests slow
run: PROPTEST_CASES=10000 cargo test --release --manifest-path=nalgebra-sparse/Cargo.toml --features compare,proptest-support,io,serde-serialize,slow-tests slow
test-nalgebra-macros:
runs-on: ubuntu-latest
steps:
@ -120,6 +124,8 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: Jimver/cuda-toolkit@v0.2.4
with:
cuda: '11.2.2'
- name: Install nightly-2021-12-04
uses: actions-rs/toolchain@v1
with:
@ -128,4 +134,6 @@ jobs:
- uses: actions/checkout@v2
- run: rustup target add nvptx64-nvidia-cuda
- run: cargo build --no-default-features --features cuda
- run: cargo build --no-default-features --features cuda --target=nvptx64-nvidia-cuda
- run: cargo build --no-default-features --features cuda --target=nvptx64-nvidia-cuda
env:
CUDA_ARCH: "350"

30
CHANGELOG.md
View File

@ -4,12 +4,42 @@ documented here.
This project adheres to [Semantic Versioning](https://semver.org/).
## [0.31.0] (30 Apr. 2022)
### Breaking changes
- Switch to `cust` 0.3 (for CUDA support).
- Switch to `rkyv` 0.7
- Remove support for serialization based on `abomonation`.
- Remove support for conversions between `nalgebra` types and `glam` 0.13.
### Modified
- The aliases for `Const` types have been simplified to help `rust-analyzer`.
### Added
- Add `TryFrom` conversion between `UnitVector2/3/4` and `glam`’s `Vec2/3/4`.
- `nalgebra-sparse`: added support for serialization of sparse matrices with `serde`.
- `nalgebra-sparse`: add a CSC matrix constructor from unsorted (but valid) data.
- `nalgebra-lapack`: add generalized eigenvalues/eigenvectors calculation + QZ decomposition.
### Fixed
- Improve stability of SVD.
- Fix slerp for `UnitComplex`.
## [0.30.1] (09 Jan. 2022)
### Added
- Add conversion from/to types of `glam` 0.19 and 0.20.
## [0.30.0] (02 Jan. 2022)
### Breaking changes
- The `Dim` trait is now marked as unsafe.
- The `Matrix::pow` and `Matrix::pow_mut` methods only allow positive integer exponents now. To compute negative
exponents, the user is free to invert the matrix before calling `pow` with the exponent’s absolute value.
- Remove the `Bounded` requirement from `RealField`. Replace it by methods returning `Option<Self>` so that they can
still be implemented by unbounded types (by returning `None`).
- The `ComplexField` trait derives from `FromPrimitive` again. We can actually keep this because all its methods
return `Option<Self>`, meaning that it could be implemented by any type.
### Modified
- Use more concise debug impls for matrices and geometric transformation types.

21
Cargo.toml
View File

@ -1,6 +1,6 @@
[package]
name = "nalgebra"
version = "0.30.0"
version = "0.31.0"
authors = [ "Sébastien Crozet <developer@crozet.re>" ]
description = "General-purpose linear algebra library with transformations and statically-sized or dynamically-sized matrices."
@ -32,17 +32,18 @@ compare = [ "matrixcompare-core" ]
libm = [ "simba/libm" ]
libm-force = [ "simba/libm_force" ]
macros = [ "nalgebra-macros" ]
cuda = [ "cust", "simba/cuda" ]
cuda = [ "cust_core", "simba/cuda" ]
# Conversion
convert-mint = [ "mint" ]
convert-bytemuck = [ "bytemuck" ]
convert-glam013 = [ "glam013" ]
convert-glam014 = [ "glam014" ]
convert-glam015 = [ "glam015" ]
convert-glam016 = [ "glam016" ]
convert-glam017 = [ "glam017" ]
convert-glam018 = [ "glam018" ]
convert-glam019 = [ "glam019" ]
convert-glam020 = [ "glam020" ]
# Serialization
## To use serde in a #[no-std] environment, enable the
@ -51,9 +52,8 @@ convert-glam018 = [ "glam018" ]
## `serde-serialize`.
serde-serialize-no-std = [ "serde", "num-complex/serde" ]
serde-serialize = [ "serde-serialize-no-std", "serde/std" ]
abomonation-serialize = [ "abomonation" ]
rkyv-serialize-no-std = [ "rkyv" ]
rkyv-serialize = [ "rkyv-serialize-no-std", "rkyv/std" ]
rkyv-serialize = [ "rkyv-serialize-no-std", "rkyv/std", "bytecheck" ]
# Randomness
## To use rand in a #[no-std] environment, enable the
@ -79,8 +79,8 @@ alga = { version = "0.9", default-features = false, optional = true }
rand_distr = { version = "0.4", default-features = false, optional = true }
matrixmultiply = { version = "0.3", optional = true }
serde = { version = "1.0", default-features = false, features = [ "derive" ], optional = true }
abomonation = { version = "0.7", optional = true }
rkyv = { version = "~0.6.4", default-features = false, features = ["const_generics"], optional = true }
rkyv = { version = "~0.7.1", optional = true }
bytecheck = { version = "~0.6.1", optional = true }
mint = { version = "0.5", optional = true }
quickcheck = { version = "1", optional = true }
pest = { version = "2", optional = true }
@ -88,15 +88,14 @@ pest_derive = { version = "2", optional = true }
bytemuck = { version = "1.5", optional = true }
matrixcompare-core = { version = "0.1", optional = true }
proptest = { version = "1", optional = true, default-features = false, features = ["std"] }
glam013 = { package = "glam", version = "0.13", optional = true }
glam014 = { package = "glam", version = "0.14", optional = true }
glam015 = { package = "glam", version = "0.15", optional = true }
glam016 = { package = "glam", version = "0.16", optional = true }
glam017 = { package = "glam", version = "0.17", optional = true }
glam018 = { package = "glam", version = "0.18", optional = true }
[target.'cfg(not(target_os = "cuda"))'.dependencies]
cust = { version = "0.2", optional = true }
glam019 = { package = "glam", version = "0.19", optional = true }
glam020 = { package = "glam", version = "0.20", optional = true }
cust_core = { version = "0.1", optional = true }
[dev-dependencies]

5
README.md
View File

@ -42,6 +42,9 @@ And our gold sponsors:
<p>
<a href="https://fragcolor.com">
<img src="https://dimforge.com/img/fragcolor_logo1_color_black.svg" width="151px">
<img src="https://dimforge.com/img/fragcolor_logo2_color_black.svg" width="300px">
</a>
<a href="https://resolutiongames.com/">
<img src="https://dimforge.com/img/logo_resolution_games.png" width="300px" />
</a>
</p>

2
examples/cargo/Cargo.toml
View File

@ -4,7 +4,7 @@ version = "0.0.0"
authors = [ "You" ]
[dependencies]
nalgebra = "0.30.0"
nalgebra = "0.31.0"
[[bin]]
name = "example"

6
nalgebra-glm/Cargo.toml
View File

@ -1,6 +1,6 @@
[package]
name = "nalgebra-glm"
version = "0.16.0"
version = "0.17.0"
authors = ["sebcrozet <developer@crozet.re>"]
description = "A computer-graphics oriented API for nalgebra, inspired by the C++ GLM library."
@ -21,13 +21,11 @@ default = [ "std" ]
std = [ "nalgebra/std", "simba/std" ]
arbitrary = [ "nalgebra/arbitrary" ]
serde-serialize = [ "nalgebra/serde-serialize-no-std" ]
abomonation-serialize = [ "nalgebra/abomonation-serialize" ]
cuda = [ "nalgebra/cuda" ]
# Conversion
convert-mint = [ "nalgebra/mint" ]
convert-bytemuck = [ "nalgebra/bytemuck" ]
convert-glam013 = [ "nalgebra/glam013" ]
convert-glam014 = [ "nalgebra/glam014" ]
convert-glam015 = [ "nalgebra/glam015" ]
convert-glam016 = [ "nalgebra/glam016" ]
@ -38,4 +36,4 @@ convert-glam018 = [ "nalgebra/glam018" ]
num-traits = { version = "0.2", default-features = false }
approx = { version = "0.5", default-features = false }
simba = { version = "0.7", default-features = false }
nalgebra = { path = "..", version = "0.30", default-features = false }
nalgebra = { path = "..", version = "0.31", default-features = false }

6
nalgebra-lapack/Cargo.toml
View File

@ -1,6 +1,6 @@
[package]
name = "nalgebra-lapack"
version = "0.21.0"
version = "0.22.0"
authors = [ "Sébastien Crozet <developer@crozet.re>", "Andrew Straw <strawman@astraw.com>" ]
description = "Matrix decompositions using nalgebra matrices and Lapack bindings."
@ -29,7 +29,7 @@ accelerate = ["lapack-src/accelerate"]
intel-mkl = ["lapack-src/intel-mkl"]
[dependencies]
nalgebra = { version = "0.30", path = ".." }
nalgebra = { version = "0.31", path = ".." }
num-traits = "0.2"
num-complex = { version = "0.4", default-features = false }
simba = "0.7"
@ -39,7 +39,7 @@ lapack-src = { version = "0.8", default-features = false }
# clippy = "*"
[dev-dependencies]
nalgebra = { version = "0.30", features = [ "arbitrary", "rand" ], path = ".." }
nalgebra = { version = "0.31", features = [ "arbitrary", "rand" ], path = ".." }
proptest = { version = "1", default-features = false, features = ["std"] }
quickcheck = "1"
approx = "0.5"

350
nalgebra-lapack/src/generalized_eigenvalues.rs Normal file
View File

@ -0,0 +1,350 @@
#[cfg(feature = "serde-serialize")]
use serde::{Deserialize, Serialize};
use num::Zero;
use num_complex::Complex;
use simba::scalar::RealField;
use crate::ComplexHelper;
use na::allocator::Allocator;
use na::dimension::{Const, Dim};
use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
use lapack;
/// Generalized eigenvalues and generalized eigenvectors (left and right) of a pair of N*N real square matrices.
///
/// Each generalized eigenvalue (lambda) satisfies determinant(A - lambda*B) = 0
///
/// The right eigenvector v(j) corresponding to the eigenvalue lambda(j)
/// of (A,B) satisfies
///
/// A * v(j) = lambda(j) * B * v(j).
///
/// The left eigenvector u(j) corresponding to the eigenvalue lambda(j)
/// of (A,B) satisfies
///
/// u(j)**H * A = lambda(j) * u(j)**H * B .
/// where u(j)**H is the conjugate-transpose of u(j).
#[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
#[cfg_attr(
feature = "serde-serialize",
serde(
bound(serialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
OVector<T, D>: Serialize,
OMatrix<T, D, D>: Serialize")
)
)]
#[cfg_attr(
feature = "serde-serialize",
serde(
bound(deserialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
OVector<T, D>: Deserialize<'de>,
OMatrix<T, D, D>: Deserialize<'de>")
)
)]
#[derive(Clone, Debug)]
pub struct GeneralizedEigen<T: Scalar, D: Dim>
where
DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
{
alphar: OVector<T, D>,
alphai: OVector<T, D>,
beta: OVector<T, D>,
vsl: OMatrix<T, D, D>,
vsr: OMatrix<T, D, D>,
}
impl<T: Scalar + Copy, D: Dim> Copy for GeneralizedEigen<T, D>
where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
OMatrix<T, D, D>: Copy,
OVector<T, D>: Copy,
{
}
impl<T: GeneralizedEigenScalar + RealField + Copy, D: Dim> GeneralizedEigen<T, D>
where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
{
/// Attempts to compute the generalized eigenvalues, and left and right associated eigenvectors
/// via the raw returns from LAPACK's dggev and sggev routines
///
/// Panics if the method did not converge.
pub fn new(a: OMatrix<T, D, D>, b: OMatrix<T, D, D>) -> Self {
Self::try_new(a, b).expect("Calculation of generalized eigenvalues failed.")
}
/// Attempts to compute the generalized eigenvalues (and eigenvectors) via the raw returns from LAPACK's
/// dggev and sggev routines
///
/// Returns `None` if the method did not converge.
pub fn try_new(mut a: OMatrix<T, D, D>, mut b: OMatrix<T, D, D>) -> Option<Self> {
assert!(
a.is_square() && b.is_square(),
"Unable to compute the generalized eigenvalues of non-square matrices."
);
assert!(
a.shape_generic() == b.shape_generic(),
"Unable to compute the generalized eigenvalues of two square matrices of different dimensions."
);
let (nrows, ncols) = a.shape_generic();
let n = nrows.value();
let mut info = 0;
let mut alphar = Matrix::zeros_generic(nrows, Const::<1>);
let mut alphai = Matrix::zeros_generic(nrows, Const::<1>);
let mut beta = Matrix::zeros_generic(nrows, Const::<1>);
let mut vsl = Matrix::zeros_generic(nrows, ncols);
let mut vsr = Matrix::zeros_generic(nrows, ncols);
let lwork = T::xggev_work_size(
b'V',
b'V',
n as i32,
a.as_mut_slice(),
n as i32,
b.as_mut_slice(),
n as i32,
alphar.as_mut_slice(),
alphai.as_mut_slice(),
beta.as_mut_slice(),
vsl.as_mut_slice(),
n as i32,
vsr.as_mut_slice(),
n as i32,
&mut info,
);
lapack_check!(info);
let mut work = vec![T::zero(); lwork as usize];
T::xggev(
b'V',
b'V',
n as i32,
a.as_mut_slice(),
n as i32,
b.as_mut_slice(),
n as i32,
alphar.as_mut_slice(),
alphai.as_mut_slice(),
beta.as_mut_slice(),
vsl.as_mut_slice(),
n as i32,
vsr.as_mut_slice(),
n as i32,
&mut work,
lwork,
&mut info,
);
lapack_check!(info);
Some(GeneralizedEigen {
alphar,
alphai,
beta,
vsl,
vsr,
})
}
/// Calculates the generalized eigenvectors (left and right) associated with the generalized eigenvalues
///
/// Outputs two matrices.
/// The first output matrix contains the left eigenvectors of the generalized eigenvalues
/// as columns.
/// The second matrix contains the right eigenvectors of the generalized eigenvalues
/// as columns.
pub fn eigenvectors(&self) -> (OMatrix<Complex<T>, D, D>, OMatrix<Complex<T>, D, D>)
where
DefaultAllocator:
Allocator<Complex<T>, D, D> + Allocator<Complex<T>, D> + Allocator<(Complex<T>, T), D>,
{
/*
How the eigenvectors are built up:
Since the input entries are all real, the generalized eigenvalues if complex come in pairs
as a consequence of the [complex conjugate root thorem](https://en.wikipedia.org/wiki/Complex_conjugate_root_theorem)
The Lapack routine output reflects this by expecting the user to unpack the real and complex eigenvalues associated
eigenvectors from the real matrix output via the following procedure
(Note: VL stands for the lapack real matrix output containing the left eigenvectors as columns,
VR stands for the lapack real matrix output containing the right eigenvectors as columns)
If the j-th and (j+1)-th eigenvalues form a complex conjugate pair,
then
u(j) = VL(:,j)+i*VL(:,j+1)
u(j+1) = VL(:,j)-i*VL(:,j+1)
and
u(j) = VR(:,j)+i*VR(:,j+1)
v(j+1) = VR(:,j)-i*VR(:,j+1).
*/
let n = self.vsl.shape().0;
let mut l = self.vsl.map(|x| Complex::new(x, T::RealField::zero()));
let mut r = self.vsr.map(|x| Complex::new(x, T::RealField::zero()));
let eigenvalues = self.raw_eigenvalues();
let mut c = 0;
while c < n {
if eigenvalues[c].0.im.abs() != T::RealField::zero() && c + 1 < n {
// taking care of the left eigenvector matrix
l.column_mut(c).zip_apply(&self.vsl.column(c + 1), |r, i| {
*r = Complex::new(r.re.clone(), i.clone());
});
l.column_mut(c + 1).zip_apply(&self.vsl.column(c), |i, r| {
*i = Complex::new(r.clone(), -i.re.clone());
});
// taking care of the right eigenvector matrix
r.column_mut(c).zip_apply(&self.vsr.column(c + 1), |r, i| {
*r = Complex::new(r.re.clone(), i.clone());
});
r.column_mut(c + 1).zip_apply(&self.vsr.column(c), |i, r| {
*i = Complex::new(r.clone(), -i.re.clone());
});
c += 2;
} else {
c += 1;
}
}
(l, r)
}
/// Outputs the unprocessed (almost) version of generalized eigenvalues ((alphar, alphai), beta)
/// straight from LAPACK
#[must_use]
pub fn raw_eigenvalues(&self) -> OVector<(Complex<T>, T), D>
where
DefaultAllocator: Allocator<(Complex<T>, T), D>,
{
let mut out = Matrix::from_element_generic(
self.vsl.shape_generic().0,
Const::<1>,
(Complex::zero(), T::RealField::zero()),
);
for i in 0..out.len() {
out[i] = (Complex::new(self.alphar[i], self.alphai[i]), self.beta[i])
}
out
}
}
/*
*
* Lapack functions dispatch.
*
*/
/// Trait implemented by scalars for which Lapack implements the RealField GeneralizedEigen decomposition.
pub trait GeneralizedEigenScalar: Scalar {
#[allow(missing_docs)]
fn xggev(
jobvsl: u8,
jobvsr: u8,
n: i32,
a: &mut [Self],
lda: i32,
b: &mut [Self],
ldb: i32,
alphar: &mut [Self],
alphai: &mut [Self],
beta: &mut [Self],
vsl: &mut [Self],
ldvsl: i32,
vsr: &mut [Self],
ldvsr: i32,
work: &mut [Self],
lwork: i32,
info: &mut i32,
);
#[allow(missing_docs)]
fn xggev_work_size(
jobvsl: u8,
jobvsr: u8,
n: i32,
a: &mut [Self],
lda: i32,
b: &mut [Self],
ldb: i32,
alphar: &mut [Self],
alphai: &mut [Self],
beta: &mut [Self],
vsl: &mut [Self],
ldvsl: i32,
vsr: &mut [Self],
ldvsr: i32,
info: &mut i32,
) -> i32;
}
macro_rules! generalized_eigen_scalar_impl (
($N: ty, $xggev: path) => (
impl GeneralizedEigenScalar for $N {
#[inline]
fn xggev(jobvsl: u8,
jobvsr: u8,
n: i32,
a: &mut [$N],
lda: i32,
b: &mut [$N],
ldb: i32,
alphar: &mut [$N],
alphai: &mut [$N],
beta : &mut [$N],
vsl: &mut [$N],
ldvsl: i32,
vsr: &mut [$N],
ldvsr: i32,
work: &mut [$N],
lwork: i32,
info: &mut i32) {
unsafe { $xggev(jobvsl, jobvsr, n, a, lda, b, ldb, alphar, alphai, beta, vsl, ldvsl, vsr, ldvsr, work, lwork, info); }
}
#[inline]
fn xggev_work_size(jobvsl: u8,
jobvsr: u8,
n: i32,
a: &mut [$N],
lda: i32,
b: &mut [$N],
ldb: i32,
alphar: &mut [$N],
alphai: &mut [$N],
beta : &mut [$N],
vsl: &mut [$N],
ldvsl: i32,
vsr: &mut [$N],
ldvsr: i32,
info: &mut i32)
-> i32 {
let mut work = [ Zero::zero() ];
let lwork = -1 as i32;
unsafe { $xggev(jobvsl, jobvsr, n, a, lda, b, ldb, alphar, alphai, beta, vsl, ldvsl, vsr, ldvsr, &mut work, lwork, info); }
ComplexHelper::real_part(work[0]) as i32
}
}
)
);
generalized_eigen_scalar_impl!(f32, lapack::sggev);
generalized_eigen_scalar_impl!(f64, lapack::dggev);

4
nalgebra-lapack/src/lib.rs
View File

@ -83,9 +83,11 @@ mod lapack_check;
mod cholesky;
mod eigen;
mod generalized_eigenvalues;
mod hessenberg;
mod lu;
mod qr;
mod qz;
mod schur;
mod svd;
mod symmetric_eigen;
@ -94,9 +96,11 @@ use num_complex::Complex;
pub use self::cholesky::{Cholesky, CholeskyScalar};
pub use self::eigen::Eigen;
pub use self::generalized_eigenvalues::GeneralizedEigen;
pub use self::hessenberg::Hessenberg;
pub use self::lu::{LUScalar, LU};
pub use self::qr::QR;
pub use self::qz::QZ;
pub use self::schur::Schur;
pub use self::svd::SVD;
pub use self::symmetric_eigen::SymmetricEigen;

321
nalgebra-lapack/src/qz.rs Normal file
View File

@ -0,0 +1,321 @@
#[cfg(feature = "serde-serialize")]
use serde::{Deserialize, Serialize};
use num::Zero;
use num_complex::Complex;
use simba::scalar::RealField;
use crate::ComplexHelper;
use na::allocator::Allocator;
use na::dimension::{Const, Dim};
use na::{DefaultAllocator, Matrix, OMatrix, OVector, Scalar};
use lapack;
/// QZ decomposition of a pair of N*N square matrices.
///
/// Retrieves the left and right matrices of Schur Vectors (VSL and VSR)
/// the upper-quasitriangular matrix `S` and upper triangular matrix `T` such that the
/// decomposed input matrix `a` equals `VSL * S * VSL.transpose()` and
/// decomposed input matrix `b` equals `VSL * T * VSL.transpose()`.
#[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
#[cfg_attr(
feature = "serde-serialize",
serde(
bound(serialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
OVector<T, D>: Serialize,
OMatrix<T, D, D>: Serialize")
)
)]
#[cfg_attr(
feature = "serde-serialize",
serde(
bound(deserialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
OVector<T, D>: Deserialize<'de>,
OMatrix<T, D, D>: Deserialize<'de>")
)
)]
#[derive(Clone, Debug)]
pub struct QZ<T: Scalar, D: Dim>
where
DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
{
alphar: OVector<T, D>,
alphai: OVector<T, D>,
beta: OVector<T, D>,
vsl: OMatrix<T, D, D>,
s: OMatrix<T, D, D>,
vsr: OMatrix<T, D, D>,
t: OMatrix<T, D, D>,
}
impl<T: Scalar + Copy, D: Dim> Copy for QZ<T, D>
where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
OMatrix<T, D, D>: Copy,
OVector<T, D>: Copy,
{
}
impl<T: QZScalar + RealField, D: Dim> QZ<T, D>
where
DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
{
/// Attempts to compute the QZ decomposition of input real square matrices `a` and `b`.
///
/// i.e retrieves the left and right matrices of Schur Vectors (VSL and VSR)
/// the upper-quasitriangular matrix `S` and upper triangular matrix `T` such that the
/// decomposed matrix `a` equals `VSL * S * VSL.transpose()` and
/// decomposed matrix `b` equals `VSL * T * VSL.transpose()`.
///
/// Panics if the method did not converge.
pub fn new(a: OMatrix<T, D, D>, b: OMatrix<T, D, D>) -> Self {
Self::try_new(a, b).expect("QZ decomposition: convergence failed.")
}
/// Computes the decomposition of input matrices `a` and `b` into a pair of matrices of Schur vectors
/// , a quasi-upper triangular matrix and an upper-triangular matrix .
///
/// Returns `None` if the method did not converge.
pub fn try_new(mut a: OMatrix<T, D, D>, mut b: OMatrix<T, D, D>) -> Option<Self> {
assert!(
a.is_square() && b.is_square(),
"Unable to compute the qz decomposition of non-square matrices."
);
assert!(
a.shape_generic() == b.shape_generic(),
"Unable to compute the qz decomposition of two square matrices of different dimensions."
);
let (nrows, ncols) = a.shape_generic();
let n = nrows.value();
let mut info = 0;
let mut alphar = Matrix::zeros_generic(nrows, Const::<1>);
let mut alphai = Matrix::zeros_generic(nrows, Const::<1>);
let mut beta = Matrix::zeros_generic(nrows, Const::<1>);
let mut vsl = Matrix::zeros_generic(nrows, ncols);
let mut vsr = Matrix::zeros_generic(nrows, ncols);
// Placeholders:
let mut bwork = [0i32];
let mut unused = 0;
let lwork = T::xgges_work_size(
b'V',
b'V',
b'N',
n as i32,
a.as_mut_slice(),
n as i32,
b.as_mut_slice(),
n as i32,
&mut unused,
alphar.as_mut_slice(),
alphai.as_mut_slice(),
beta.as_mut_slice(),
vsl.as_mut_slice(),
n as i32,
vsr.as_mut_slice(),
n as i32,
&mut bwork,
&mut info,
);
lapack_check!(info);
let mut work = vec![T::zero(); lwork as usize];
T::xgges(
b'V',
b'V',
b'N',
n as i32,
a.as_mut_slice(),
n as i32,
b.as_mut_slice(),
n as i32,
&mut unused,
alphar.as_mut_slice(),
alphai.as_mut_slice(),
beta.as_mut_slice(),
vsl.as_mut_slice(),
n as i32,
vsr.as_mut_slice(),
n as i32,
&mut work,
lwork,
&mut bwork,
&mut info,
);
lapack_check!(info);
Some(QZ {
alphar,
alphai,
beta,
vsl,
s: a,
vsr,
t: b,
})
}
/// Retrieves the left and right matrices of Schur Vectors (VSL and VSR)
/// the upper-quasitriangular matrix `S` and upper triangular matrix `T` such that the
/// decomposed input matrix `a` equals `VSL * S * VSL.transpose()` and
/// decomposed input matrix `b` equals `VSL * T * VSL.transpose()`.
pub fn unpack(
self,
) -> (
OMatrix<T, D, D>,
OMatrix<T, D, D>,
OMatrix<T, D, D>,
OMatrix<T, D, D>,
) {
(self.vsl, self.s, self.t, self.vsr)
}
/// outputs the unprocessed (almost) version of generalized eigenvalues ((alphar, alpai), beta)
/// straight from LAPACK
#[must_use]
pub fn raw_eigenvalues(&self) -> OVector<(Complex<T>, T), D>
where
DefaultAllocator: Allocator<(Complex<T>, T), D>,
{
let mut out = Matrix::from_element_generic(
self.vsl.shape_generic().0,
Const::<1>,
(Complex::zero(), T::RealField::zero()),
);
for i in 0..out.len() {
out[i] = (
Complex::new(self.alphar[i].clone(), self.alphai[i].clone()),
self.beta[i].clone(),
)
}
out
}
}
/*
*
* Lapack functions dispatch.
*
*/
/// Trait implemented by scalars for which Lapack implements the RealField QZ decomposition.
pub trait QZScalar: Scalar {
#[allow(missing_docs)]
fn xgges(
jobvsl: u8,
jobvsr: u8,
sort: u8,
// select: ???
n: i32,
a: &mut [Self],
lda: i32,
b: &mut [Self],
ldb: i32,
sdim: &mut i32,
alphar: &mut [Self],
alphai: &mut [Self],
beta: &mut [Self],
vsl: &mut [Self],
ldvsl: i32,
vsr: &mut [Self],
ldvsr: i32,
work: &mut [Self],
lwork: i32,
bwork: &mut [i32],
info: &mut i32,
);
#[allow(missing_docs)]
fn xgges_work_size(
jobvsl: u8,
jobvsr: u8,
sort: u8,
// select: ???
n: i32,
a: &mut [Self],
lda: i32,
b: &mut [Self],
ldb: i32,
sdim: &mut i32,
alphar: &mut [Self],
alphai: &mut [Self],
beta: &mut [Self],
vsl: &mut [Self],
ldvsl: i32,
vsr: &mut [Self],
ldvsr: i32,
bwork: &mut [i32],
info: &mut i32,
) -> i32;
}
macro_rules! qz_scalar_impl (
($N: ty, $xgges: path) => (
impl QZScalar for $N {
#[inline]
fn xgges(jobvsl: u8,
jobvsr: u8,
sort: u8,
// select: ???
n: i32,
a: &mut [$N],
lda: i32,
b: &mut [$N],
ldb: i32,
sdim: &mut i32,
alphar: &mut [$N],
alphai: &mut [$N],
beta : &mut [$N],
vsl: &mut [$N],
ldvsl: i32,
vsr: &mut [$N],
ldvsr: i32,
work: &mut [$N],
lwork: i32,
bwork: &mut [i32],
info: &mut i32) {
unsafe { $xgges(jobvsl, jobvsr, sort, None, n, a, lda, b, ldb, sdim, alphar, alphai, beta, vsl, ldvsl, vsr, ldvsr, work, lwork, bwork, info); }
}
#[inline]
fn xgges_work_size(jobvsl: u8,
jobvsr: u8,
sort: u8,
// select: ???
n: i32,
a: &mut [$N],
lda: i32,
b: &mut [$N],
ldb: i32,
sdim: &mut i32,
alphar: &mut [$N],
alphai: &mut [$N],
beta : &mut [$N],
vsl: &mut [$N],
ldvsl: i32,
vsr: &mut [$N],
ldvsr: i32,
bwork: &mut [i32],
info: &mut i32)
-> i32 {
let mut work = [ Zero::zero() ];
let lwork = -1 as i32;
unsafe { $xgges(jobvsl, jobvsr, sort, None, n, a, lda, b, ldb, sdim, alphar, alphai, beta, vsl, ldvsl, vsr, ldvsr, &mut work, lwork, bwork, info); }
ComplexHelper::real_part(work[0]) as i32
}
}
)
);
qz_scalar_impl!(f32, lapack::sgges);
qz_scalar_impl!(f64, lapack::dgges);

72
nalgebra-lapack/tests/linalg/generalized_eigenvalues.rs Normal file
View File

@ -0,0 +1,72 @@
use na::dimension::Const;
use na::{DMatrix, OMatrix};
use nl::GeneralizedEigen;
use num_complex::Complex;
use simba::scalar::ComplexField;
use crate::proptest::*;
use proptest::{prop_assert, prop_compose, proptest};
prop_compose! {
fn f64_dynamic_dim_squares()
(n in PROPTEST_MATRIX_DIM)
(a in matrix(PROPTEST_F64,n,n), b in matrix(PROPTEST_F64,n,n)) -> (DMatrix<f64>, DMatrix<f64>){
(a,b)
}}
proptest! {
#[test]
fn ge((a,b) in f64_dynamic_dim_squares()){
let a_c = a.clone().map(|x| Complex::new(x, 0.0));
let b_c = b.clone().map(|x| Complex::new(x, 0.0));
let n = a.shape_generic().0;
let ge = GeneralizedEigen::new(a.clone(), b.clone());
let (vsl,vsr) = ge.clone().eigenvectors();
for (i,(alpha,beta)) in ge.raw_eigenvalues().iter().enumerate() {
let l_a = a_c.clone() * Complex::new(*beta, 0.0);
let l_b = b_c.clone() * *alpha;
prop_assert!(
relative_eq!(
((&l_a - &l_b)*vsr.column(i)).map(|x| x.modulus()),
OMatrix::zeros_generic(n, Const::<1>),
epsilon = 1.0e-5));
prop_assert!(
relative_eq!(
(vsl.column(i).adjoint()*(&l_a - &l_b)).map(|x| x.modulus()),
OMatrix::zeros_generic(Const::<1>, n),
epsilon = 1.0e-5))
};
}
#[test]
fn ge_static(a in matrix4(), b in matrix4()) {
let ge = GeneralizedEigen::new(a.clone(), b.clone());
let a_c =a.clone().map(|x| Complex::new(x, 0.0));
let b_c = b.clone().map(|x| Complex::new(x, 0.0));
let (vsl,vsr) = ge.eigenvectors();
let eigenvalues = ge.raw_eigenvalues();
for (i,(alpha,beta)) in eigenvalues.iter().enumerate() {
let l_a = a_c.clone() * Complex::new(*beta, 0.0);
let l_b = b_c.clone() * *alpha;
prop_assert!(
relative_eq!(
((&l_a - &l_b)*vsr.column(i)).map(|x| x.modulus()),
OMatrix::zeros_generic(Const::<4>, Const::<1>),
epsilon = 1.0e-5));
prop_assert!(
relative_eq!((vsl.column(i).adjoint()*(&l_a - &l_b)).map(|x| x.modulus()),
OMatrix::zeros_generic(Const::<1>, Const::<4>),
epsilon = 1.0e-5))
}
}
}

2
nalgebra-lapack/tests/linalg/mod.rs
View File

@ -1,6 +1,8 @@
mod cholesky;
mod generalized_eigenvalues;
mod lu;
mod qr;
mod qz;
mod real_eigensystem;
mod schur;
mod svd;

34
nalgebra-lapack/tests/linalg/qz.rs Normal file
View File

@ -0,0 +1,34 @@
use na::DMatrix;
use nl::QZ;
use crate::proptest::*;
use proptest::{prop_assert, prop_compose, proptest};
prop_compose! {
fn f64_dynamic_dim_squares()
(n in PROPTEST_MATRIX_DIM)
(a in matrix(PROPTEST_F64,n,n), b in matrix(PROPTEST_F64,n,n)) -> (DMatrix<f64>, DMatrix<f64>){
(a,b)
}}
proptest! {
#[test]
fn qz((a,b) in f64_dynamic_dim_squares()) {
let qz = QZ::new(a.clone(), b.clone());
let (vsl,s,t,vsr) = qz.clone().unpack();
prop_assert!(relative_eq!(&vsl * s * vsr.transpose(), a, epsilon = 1.0e-7));
prop_assert!(relative_eq!(vsl * t * vsr.transpose(), b, epsilon = 1.0e-7));
}
#[test]
fn qz_static(a in matrix4(), b in matrix4()) {
let qz = QZ::new(a.clone(), b.clone());
let (vsl,s,t,vsr) = qz.unpack();
prop_assert!(relative_eq!(&vsl * s * vsr.transpose(), a, epsilon = 1.0e-7));
prop_assert!(relative_eq!(vsl * t * vsr.transpose(), b, epsilon = 1.0e-7));
}
}

2
nalgebra-macros/Cargo.toml
View File

@ -21,5 +21,5 @@ quote = "1.0"
proc-macro2 = "1.0"
[dev-dependencies]
nalgebra = { version = "0.30.0", path = ".." }
nalgebra = { version = "0.31.0", path = ".." }
trybuild = "1.0.42"

19
nalgebra-macros/src/lib.rs
View File

@ -111,7 +111,7 @@ impl Parse for Matrix {
/// Construct a fixed-size matrix directly from data.
///
/// **Note: Requires the `macro` feature to be enabled (enabled by default)**.
/// **Note: Requires the `macros` feature to be enabled (enabled by default)**.
///
/// This macro facilitates easy construction of matrices when the entries of the matrix are known
/// (either as constants or expressions). This macro produces an instance of `SMatrix`. This means
@ -125,7 +125,6 @@ impl Parse for Matrix {
/// (`;`) designates that a new row begins.
///
/// # Examples
///
/// ```
/// use nalgebra::matrix;
///
@ -164,12 +163,13 @@ pub fn matrix(stream: TokenStream) -> TokenStream {
/// Construct a dynamic matrix directly from data.
///
/// **Note: Requires the `macro` feature to be enabled (enabled by default)**.
/// **Note: Requires the `macros` feature to be enabled (enabled by default)**.
///
/// The syntax is exactly the same as for [`matrix!`], but instead of producing instances of
/// `SMatrix`, it produces instances of `DMatrix`. At the moment it is not usable
/// in `const fn` contexts.
///
/// # Example
/// ```
/// use nalgebra::dmatrix;
///
@ -233,7 +233,7 @@ impl Parse for Vector {
/// Construct a fixed-size column vector directly from data.
///
/// **Note: Requires the `macro` feature to be enabled (enabled by default)**.
/// **Note: Requires the `macros` feature to be enabled (enabled by default)**.
///
/// Similarly to [`matrix!`], this macro facilitates easy construction of fixed-size vectors.
/// However, whereas the [`matrix!`] macro expects each row to be separated by a semi-colon,
@ -243,8 +243,7 @@ impl Parse for Vector {
/// `vector!` is intended to be the most readable and performant way of constructing small,
/// fixed-size vectors, and it is usable in `const fn` contexts.
///
/// ## Examples
///
/// # Example
/// ```
/// use nalgebra::vector;
///
@ -265,12 +264,13 @@ pub fn vector(stream: TokenStream) -> TokenStream {
/// Construct a dynamic column vector directly from data.
///
/// **Note: Requires the `macro` feature to be enabled (enabled by default)**.
/// **Note: Requires the `macros` feature to be enabled (enabled by default)**.
///
/// The syntax is exactly the same as for [`vector!`], but instead of producing instances of
/// `SVector`, it produces instances of `DVector`. At the moment it is not usable
/// in `const fn` contexts.
///
/// # Example
/// ```
/// use nalgebra::dvector;
///
@ -294,15 +294,14 @@ pub fn dvector(stream: TokenStream) -> TokenStream {
/// Construct a fixed-size point directly from data.
///
/// **Note: Requires the `macro` feature to be enabled (enabled by default)**.
/// **Note: Requires the `macros` feature to be enabled (enabled by default)**.
///
/// Similarly to [`vector!`], this macro facilitates easy construction of points.
///
/// `point!` is intended to be the most readable and performant way of constructing small,
/// points, and it is usable in `const fn` contexts.
///
/// ## Examples
///
/// # Example
/// ```
/// use nalgebra::point;
///

11
nalgebra-sparse/Cargo.toml
View File

@ -1,6 +1,6 @@
[package]
name = "nalgebra-sparse"
version = "0.6.0"
version = "0.7.0"
authors = [ "Andreas Longva", "Sébastien Crozet <developer@crozet.re>" ]
edition = "2018"
description = "Sparse matrix computation based on nalgebra."
@ -15,6 +15,7 @@ license = "Apache-2.0"
[features]
proptest-support = ["proptest", "nalgebra/proptest-support"]
compare = [ "matrixcompare-core" ]
serde-serialize = [ "serde/std" ]
# Enable matrix market I/O
io = [ "pest", "pest_derive" ]
@ -23,18 +24,20 @@ io = [ "pest", "pest_derive" ]
slow-tests = []
[dependencies]
nalgebra = { version="0.30", path = "../" }
nalgebra = { version="0.31", path = "../" }
num-traits = { version = "0.2", default-features = false }
proptest = { version = "1.0", optional = true }
matrixcompare-core = { version = "0.1.0", optional = true }
pest = { version = "2", optional = true }
pest_derive = { version = "2", optional = true }
serde = { version = "1.0", default-features = false, features = [ "derive" ], optional = true }
[dev-dependencies]
itertools = "0.10"
matrixcompare = { version = "0.3.0", features = [ "proptest-support" ] }
nalgebra = { version="0.30", path = "../", features = ["compare"] }
nalgebra = { version="0.31", path = "../", features = ["compare"] }
serde_json = "1.0"
[package.metadata.docs.rs]
# Enable certain features when building docs for docs.rs
features = [ "proptest-support", "compare" ]
features = [ "proptest-support", "compare" ]

20
nalgebra-sparse/src/convert/serial.rs
View File

@ -14,6 +14,7 @@ use crate::coo::CooMatrix;
use crate::cs;
use crate::csc::CscMatrix;
use crate::csr::CsrMatrix;
use crate::utils::{apply_permutation, compute_sort_permutation};
/// Converts a dense matrix to [`CooMatrix`].
pub fn convert_dense_coo<T, R, C, S>(dense: &Matrix<T, R, C, S>) -> CooMatrix<T>
@ -376,29 +377,12 @@ fn sort_lane<T: Clone>(
assert_eq!(values.len(), workspace.len());
let permutation = workspace;
// Set permutation to identity
for (i, p) in permutation.iter_mut().enumerate() {
*p = i;
}
// Compute permutation needed to bring minor indices into sorted order
// Note: Using sort_unstable here avoids internal allocations, which is crucial since
// each lane might have a small number of elements
permutation.sort_unstable_by_key(|idx| minor_idx[*idx]);
compute_sort_permutation(permutation, minor_idx);
apply_permutation(minor_idx_result, minor_idx, permutation);
apply_permutation(values_result, values, permutation);
}
// TODO: Move this into `utils` or something?
fn apply_permutation<T: Clone>(out_slice: &mut [T], in_slice: &[T], permutation: &[usize]) {
assert_eq!(out_slice.len(), in_slice.len());
assert_eq!(out_slice.len(), permutation.len());
for (out_element, old_pos) in out_slice.iter_mut().zip(permutation) {
*out_element = in_slice[*old_pos].clone();
}
}
/// Given *sorted* indices and corresponding scalar values, combines duplicates with the given
/// associative combiner and calls the provided produce methods with combined indices and values.
fn combine_duplicates<T: Clone>(

3
nalgebra-sparse/src/coo.rs
View File

@ -1,5 +1,8 @@
//! An implementation of the COO sparse matrix format.
#[cfg(feature = "serde-serialize")]
mod coo_serde;
use crate::SparseFormatError;
/// A COO representation of a sparse matrix.

65
nalgebra-sparse/src/coo/coo_serde.rs Normal file
View File

@ -0,0 +1,65 @@
use crate::coo::CooMatrix;
use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
/// This is an intermediate type for (de)serializing `CooMatrix`.
///
/// Deserialization requires using a `try_from_*` function for validation. We could have used
/// the `remote = "Self"` trick (https://github.com/serde-rs/serde/issues/1220) which allows
/// to directly serialize/deserialize the original fields and combine it with validation.
/// However, this would lead to nested serialization of the `CsMatrix` and `SparsityPattern`
/// types. Instead, we decided that we want a more human-readable serialization format using
/// field names like `row_indices` and `col_indices`. The easiest way to achieve this is to
/// introduce an intermediate type. It also allows the serialization format to stay constant
/// even if the internal layout in `nalgebra` changes.
///
/// We want to avoid unnecessary copies when serializing (i.e. cloning slices into owned
/// storage). Therefore, we use generic arguments to allow using slices during serialization and
/// owned storage (i.e. `Vec`) during deserialization. Without a major update of serde, slices
/// and `Vec`s should always (de)serialize identically.
#[derive(Serialize, Deserialize)]
struct CooMatrixSerializationData<Indices, Values> {
nrows: usize,
ncols: usize,
row_indices: Indices,
col_indices: Indices,
values: Values,
}
impl<T> Serialize for CooMatrix<T>
where
T: Serialize + Clone,
{
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
CooMatrixSerializationData::<&[usize], &[T]> {
nrows: self.nrows(),
ncols: self.ncols(),
row_indices: self.row_indices(),
col_indices: self.col_indices(),
values: self.values(),
}
.serialize(serializer)
}
}
impl<'de, T> Deserialize<'de> for CooMatrix<T>
where
T: Deserialize<'de> + Clone,
{
fn deserialize<D>(deserializer: D) -> Result<CooMatrix<T>, D::Error>
where
D: Deserializer<'de>,
{
let de = CooMatrixSerializationData::<Vec<usize>, Vec<T>>::deserialize(deserializer)?;
CooMatrix::try_from_triplets(
de.nrows,
de.ncols,
de.row_indices,
de.col_indices,
de.values,
)
.map_err(|e| de::Error::custom(e))
}
}

151
nalgebra-sparse/src/cs.rs
View File

@ -6,7 +6,8 @@ use num_traits::One;
use nalgebra::Scalar;
use crate::pattern::SparsityPattern;
use crate::{SparseEntry, SparseEntryMut};
use crate::utils::{apply_permutation, compute_sort_permutation};
use crate::{SparseEntry, SparseEntryMut, SparseFormatError, SparseFormatErrorKind};
/// An abstract compressed matrix.
///
@ -543,3 +544,151 @@ pub fn convert_counts_to_offsets(counts: &mut [usize]) {
offset += count;
}
}
/// Validates cs data, optionally sorts minor indices and values
pub(crate) fn validate_and_optionally_sort_cs_data<T>(
major_dim: usize,
minor_dim: usize,
major_offsets: &[usize],
minor_indices: &mut [usize],
values: Option<&mut [T]>,
sort: bool,
) -> Result<(), SparseFormatError>
where
T: Scalar,
{
let mut values_option = values;
if let Some(values) = values_option.as_mut() {
if minor_indices.len() != values.len() {
return Err(SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::InvalidStructure,
"Number of values and minor indices must be the same.",
));
}
} else if sort {
unreachable!("Internal error: Sorting currently not supported if no values are present.");
}
if major_offsets.len() == 0 {
return Err(SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::InvalidStructure,
"Number of offsets should be greater than 0.",
));
}
if major_offsets.len() != major_dim + 1 {
return Err(SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::InvalidStructure,
"Length of offset array is not equal to (major_dim + 1).",
));
}
// Check that the first and last offsets conform to the specification
{
let first_offset_ok = *major_offsets.first().unwrap() == 0;
let last_offset_ok = *major_offsets.last().unwrap() == minor_indices.len();
if !first_offset_ok || !last_offset_ok {
return Err(SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::InvalidStructure,
"First or last offset is incompatible with format.",
));
}
}
// Set up required buffers up front
let mut minor_idx_buffer: Vec<usize> = Vec::new();
let mut values_buffer: Vec<T> = Vec::new();
let mut minor_index_permutation: Vec<usize> = Vec::new();
// Test that each lane has strictly monotonically increasing minor indices, i.e.
// minor indices within a lane are sorted, unique. Sort minor indices within a lane if needed.
// In addition, each minor index must be in bounds with respect to the minor dimension.
{
for lane_idx in 0..major_dim {
let range_start = major_offsets[lane_idx];
let range_end = major_offsets[lane_idx + 1];
// Test that major offsets are monotonically increasing
if range_start > range_end {
return Err(SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::InvalidStructure,
"Offsets are not monotonically increasing.",
));
}
let minor_idx_in_lane = minor_indices.get(range_start..range_end).ok_or(
SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::IndexOutOfBounds,
"A major offset is out of bounds.",
),
)?;
// We test for in-bounds, uniqueness and monotonicity at the same time
// to ensure that we only visit each minor index once
let mut prev = None;
let mut monotonic = true;
for &minor_idx in minor_idx_in_lane {
if minor_idx >= minor_dim {
return Err(SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::IndexOutOfBounds,
"A minor index is out of bounds.",
));
}
if let Some(prev) = prev {
if prev >= minor_idx {
if !sort {
return Err(SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::InvalidStructure,
"Minor indices are not strictly monotonically increasing in each lane.",
));
}
monotonic = false;
}
}
prev = Some(minor_idx);
}
// sort if indices are not monotonic and sorting is expected
if !monotonic && sort {
let range_size = range_end - range_start;
minor_index_permutation.resize(range_size, 0);
compute_sort_permutation(&mut minor_index_permutation, &minor_idx_in_lane);
minor_idx_buffer.clear();
minor_idx_buffer.extend_from_slice(&minor_idx_in_lane);
apply_permutation(
&mut minor_indices[range_start..range_end],
&minor_idx_buffer,
&minor_index_permutation,
);
// check duplicates
prev = None;
for &minor_idx in &minor_indices[range_start..range_end] {
if let Some(prev) = prev {
if prev == minor_idx {
return Err(SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::DuplicateEntry,
"Input data contains duplicate entries.",
));
}
}
prev = Some(minor_idx);
}
// sort values if they exist
if let Some(values) = values_option.as_mut() {
values_buffer.clear();
values_buffer.extend_from_slice(&values[range_start..range_end]);
apply_permutation(
&mut values[range_start..range_end],
&values_buffer,
&minor_index_permutation,
);
}
}
}
}
Ok(())
}

48
nalgebra-sparse/src/csc.rs
View File

@ -3,6 +3,10 @@
//! This is the module-level documentation. See [`CscMatrix`] for the main documentation of the
//! CSC implementation.
#[cfg(feature = "serde-serialize")]
mod csc_serde;
use crate::cs;
use crate::cs::{CsLane, CsLaneIter, CsLaneIterMut, CsLaneMut, CsMatrix};
use crate::csr::CsrMatrix;
use crate::pattern::{SparsityPattern, SparsityPatternFormatError, SparsityPatternIter};
@ -170,6 +174,50 @@ impl<T> CscMatrix<T> {
Self::try_from_pattern_and_values(pattern, values)
}
/// Try to construct a CSC matrix from raw CSC data with unsorted row indices.
///
/// It is assumed that each column contains unique row indices that are in
/// bounds with respect to the number of rows in the matrix. If this is not the case,
/// an error is returned to indicate the failure.
///
/// An error is returned if the data given does not conform to the CSC storage format
/// with the exception of having unsorted row indices and values.
/// See the documentation for [CscMatrix](struct.CscMatrix.html) for more information.
pub fn try_from_unsorted_csc_data(
num_rows: usize,
num_cols: usize,
col_offsets: Vec<usize>,
mut row_indices: Vec<usize>,
mut values: Vec<T>,
) -> Result<Self, SparseFormatError>
where
T: Scalar,
{
let result = cs::validate_and_optionally_sort_cs_data(
num_cols,
num_rows,
&col_offsets,
&mut row_indices,
Some(&mut values),
true,
);
match result {
Ok(()) => {
let pattern = unsafe {
SparsityPattern::from_offset_and_indices_unchecked(
num_cols,
num_rows,
col_offsets,
row_indices,
)
};
Self::try_from_pattern_and_values(pattern, values)
}
Err(err) => Err(err),
}
}
/// Try to construct a CSC matrix from a sparsity pattern and associated non-zero values.
///
/// Returns an error if the number of values does not match the number of minor indices

65
nalgebra-sparse/src/csc/csc_serde.rs Normal file
View File

@ -0,0 +1,65 @@
use crate::CscMatrix;
use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
/// This is an intermediate type for (de)serializing `CscMatrix`.
///
/// Deserialization requires using a `try_from_*` function for validation. We could have used
/// the `remote = "Self"` trick (https://github.com/serde-rs/serde/issues/1220) which allows
/// to directly serialize/deserialize the original fields and combine it with validation.
/// However, this would lead to nested serialization of the `CsMatrix` and `SparsityPattern`
/// types. Instead, we decided that we want a more human-readable serialization format using
/// field names like `col_offsets` and `row_indices`. The easiest way to achieve this is to
/// introduce an intermediate type. It also allows the serialization format to stay constant
/// even if the internal layout in `nalgebra` changes.
///
/// We want to avoid unnecessary copies when serializing (i.e. cloning slices into owned
/// storage). Therefore, we use generic arguments to allow using slices during serialization and
/// owned storage (i.e. `Vec`) during deserialization. Without a major update of serde, slices
/// and `Vec`s should always (de)serialize identically.
#[derive(Serialize, Deserialize)]
struct CscMatrixSerializationData<Indices, Values> {
nrows: usize,
ncols: usize,
col_offsets: Indices,
row_indices: Indices,
values: Values,
}
impl<T> Serialize for CscMatrix<T>
where
T: Serialize + Clone,
{
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
CscMatrixSerializationData::<&[usize], &[T]> {
nrows: self.nrows(),
ncols: self.ncols(),
col_offsets: self.col_offsets(),
row_indices: self.row_indices(),
values: self.values(),
}
.serialize(serializer)
}
}
impl<'de, T> Deserialize<'de> for CscMatrix<T>
where
T: Deserialize<'de> + Clone,
{
fn deserialize<D>(deserializer: D) -> Result<CscMatrix<T>, D::Error>
where
D: Deserializer<'de>,
{
let de = CscMatrixSerializationData::<Vec<usize>, Vec<T>>::deserialize(deserializer)?;
CscMatrix::try_from_csc_data(
de.nrows,
de.ncols,
de.col_offsets,
de.row_indices,
de.values,
)
.map_err(|e| de::Error::custom(e))
}
}

77
nalgebra-sparse/src/csr.rs
View File

@ -2,6 +2,11 @@
//!
//! This is the module-level documentation. See [`CsrMatrix`] for the main documentation of the
//! CSC implementation.
#[cfg(feature = "serde-serialize")]
mod csr_serde;
use crate::cs;
use crate::cs::{CsLane, CsLaneIter, CsLaneIterMut, CsLaneMut, CsMatrix};
use crate::csc::CscMatrix;
use crate::pattern::{SparsityPattern, SparsityPatternFormatError, SparsityPatternIter};
@ -10,7 +15,6 @@ use crate::{SparseEntry, SparseEntryMut, SparseFormatError, SparseFormatErrorKin
use nalgebra::Scalar;
use num_traits::One;
use std::iter::FromIterator;
use std::slice::{Iter, IterMut};
/// A CSR representation of a sparse matrix.
@ -184,62 +188,35 @@ impl<T> CsrMatrix<T> {
num_rows: usize,
num_cols: usize,
row_offsets: Vec<usize>,
col_indices: Vec<usize>,
values: Vec<T>,
mut col_indices: Vec<usize>,
mut values: Vec<T>,
) -> Result<Self, SparseFormatError>
where
T: Scalar,
{
use SparsityPatternFormatError::*;
let count = col_indices.len();
let mut p: Vec<usize> = (0..count).collect();
if col_indices.len() != values.len() {
return Err(SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::InvalidStructure,
"Number of values and column indices must be the same",
));
}
if row_offsets.len() == 0 {
return Err(SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::InvalidStructure,
"Number of offsets should be greater than 0",
));
}
for (index, &offset) in row_offsets[0..row_offsets.len() - 1].iter().enumerate() {
let next_offset = row_offsets[index + 1];
if next_offset > count {
return Err(SparseFormatError::from_kind_and_msg(
SparseFormatErrorKind::InvalidStructure,
"No row offset should be greater than the number of column indices",
));
}
if offset > next_offset {
return Err(NonmonotonicOffsets).map_err(pattern_format_error_to_csr_error);
}
p[offset..next_offset].sort_by(|a, b| {
let x = &col_indices[*a];
let y = &col_indices[*b];
x.partial_cmp(y).unwrap()
});
}
// permute indices
let sorted_col_indices: Vec<usize> =
Vec::from_iter((p.iter().map(|i| &col_indices[*i])).cloned());
// permute values
let sorted_values: Vec<T> = Vec::from_iter((p.iter().map(|i| &values[*i])).cloned());
return Self::try_from_csr_data(
let result = cs::validate_and_optionally_sort_cs_data(
num_rows,
num_cols,
row_offsets,
sorted_col_indices,
sorted_values,
&row_offsets,
&mut col_indices,
Some(&mut values),
true,
);
match result {
Ok(()) => {
let pattern = unsafe {
SparsityPattern::from_offset_and_indices_unchecked(
num_rows,
num_cols,
row_offsets,
col_indices,
)
};
Self::try_from_pattern_and_values(pattern, values)
}
Err(err) => Err(err),
}
}
/// Try to construct a CSR matrix from a sparsity pattern and associated non-zero values.

65
nalgebra-sparse/src/csr/csr_serde.rs Normal file
View File

@ -0,0 +1,65 @@
use crate::CsrMatrix;
use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
/// This is an intermediate type for (de)serializing `CsrMatrix`.
///
/// Deserialization requires using a `try_from_*` function for validation. We could have used
/// the `remote = "Self"` trick (https://github.com/serde-rs/serde/issues/1220) which allows
/// to directly serialize/deserialize the original fields and combine it with validation.
/// However, this would lead to nested serialization of the `CsMatrix` and `SparsityPattern`
/// types. Instead, we decided that we want a more human-readable serialization format using
/// field names like `row_offsets` and `cal_indices`. The easiest way to achieve this is to
/// introduce an intermediate type. It also allows the serialization format to stay constant
/// even if the internal layout in `nalgebra` changes.
///
/// We want to avoid unnecessary copies when serializing (i.e. cloning slices into owned
/// storage). Therefore, we use generic arguments to allow using slices during serialization and
/// owned storage (i.e. `Vec`) during deserialization. Without a major update of serde, slices
/// and `Vec`s should always (de)serialize identically.
#[derive(Serialize, Deserialize)]
struct CsrMatrixSerializationData<Indices, Values> {
nrows: usize,
ncols: usize,
row_offsets: Indices,
col_indices: Indices,
values: Values,
}
impl<T> Serialize for CsrMatrix<T>
where
T: Serialize + Clone,
{
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
CsrMatrixSerializationData::<&[usize], &[T]> {
nrows: self.nrows(),
ncols: self.ncols(),
row_offsets: self.row_offsets(),
col_indices: self.col_indices(),
values: self.values(),
}
.serialize(serializer)
}
}
impl<'de, T> Deserialize<'de> for CsrMatrix<T>
where
T: Deserialize<'de> + Clone,
{
fn deserialize<D>(deserializer: D) -> Result<CsrMatrix<T>, D::Error>
where
D: Deserializer<'de>,
{
let de = CsrMatrixSerializationData::<Vec<usize>, Vec<T>>::deserialize(deserializer)?;
CsrMatrix::try_from_csr_data(
de.nrows,
de.ncols,
de.row_offsets,
de.col_indices,
de.values,
)
.map_err(|e| de::Error::custom(e))
}
}

1
nalgebra-sparse/src/lib.rs
View File

@ -160,6 +160,7 @@ pub mod ops;
pub mod pattern;
pub(crate) mod cs;
pub(crate) mod utils;
#[cfg(feature = "proptest-support")]
pub mod proptest;

33
nalgebra-sparse/src/pattern.rs
View File

@ -1,4 +1,8 @@
//! Sparsity patterns for CSR and CSC matrices.
#[cfg(feature = "serde-serialize")]
mod pattern_serde;
use crate::cs::transpose_cs;
use crate::SparseFormatError;
use std::error::Error;
@ -184,6 +188,35 @@ impl SparsityPattern {
})
}
/// Try to construct a sparsity pattern from the given dimensions, major offsets
/// and minor indices.
///
/// # Panics
///
/// Panics if the number of major offsets is not exactly one greater than the major dimension
/// or if major offsets do not start with 0 and end with the number of minor indices.
pub unsafe fn from_offset_and_indices_unchecked(
major_dim: usize,
minor_dim: usize,
major_offsets: Vec<usize>,
minor_indices: Vec<usize>,
) -> Self {
assert_eq!(major_offsets.len(), major_dim + 1);
// Check that the first and last offsets conform to the specification
{
let first_offset_ok = *major_offsets.first().unwrap() == 0;
let last_offset_ok = *major_offsets.last().unwrap() == minor_indices.len();
assert!(first_offset_ok && last_offset_ok);
}
Self {
major_offsets,
minor_indices,
minor_dim,
}
}
/// An iterator over the explicitly stored "non-zero" entries (i, j).
///
/// The iteration happens in a lane-major fashion, meaning that the lane index i

56
nalgebra-sparse/src/pattern/pattern_serde.rs Normal file
View File

@ -0,0 +1,56 @@
use crate::pattern::SparsityPattern;
use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
/// This is an intermediate type for (de)serializing `SparsityPattern`.
///
/// Deserialization requires using a `try_from_*` function for validation. We could have used
/// the `remote = "Self"` trick (https://github.com/serde-rs/serde/issues/1220) which allows
/// to directly serialize/deserialize the original fields and combine it with validation.
/// However, this would lead to nested serialization of the `CsMatrix` and `SparsityPattern`
/// types. Instead, we decided that we want a more human-readable serialization format using
/// field names like `major_offsets` and `minor_indices`. The easiest way to achieve this is to
/// introduce an intermediate type. It also allows the serialization format to stay constant
/// even when the internal layout in `nalgebra` changes.
///
/// We want to avoid unnecessary copies when serializing (i.e. cloning slices into owned
/// storage). Therefore, we use generic arguments to allow using slices during serialization and
/// owned storage (i.e. `Vec`) during deserialization. Without a major update of serde, slices
/// and `Vec`s should always (de)serialize identically.
#[derive(Serialize, Deserialize)]
struct SparsityPatternSerializationData<Indices> {
major_dim: usize,
minor_dim: usize,
major_offsets: Indices,
minor_indices: Indices,
}
impl Serialize for SparsityPattern {
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
SparsityPatternSerializationData::<&[usize]> {
major_dim: self.major_dim(),
minor_dim: self.minor_dim(),
major_offsets: self.major_offsets(),
minor_indices: self.minor_indices(),
}
.serialize(serializer)
}
}
impl<'de> Deserialize<'de> for SparsityPattern {
fn deserialize<D>(deserializer: D) -> Result<SparsityPattern, D::Error>
where
D: Deserializer<'de>,
{
let de = SparsityPatternSerializationData::<Vec<usize>>::deserialize(deserializer)?;
SparsityPattern::try_from_offsets_and_indices(
de.major_dim,
de.minor_dim,
de.major_offsets,
de.minor_indices,
)
.map_err(|e| de::Error::custom(e))
}
}

26
nalgebra-sparse/src/utils.rs Normal file
View File

@ -0,0 +1,26 @@
//! Helper functions for sparse matrix computations
/// permutes entries of in_slice according to permutation slice and puts them to out_slice
#[inline]
pub fn apply_permutation<T: Clone>(out_slice: &mut [T], in_slice: &[T], permutation: &[usize]) {
assert_eq!(out_slice.len(), in_slice.len());
assert_eq!(out_slice.len(), permutation.len());
for (out_element, old_pos) in out_slice.iter_mut().zip(permutation) {
*out_element = in_slice[*old_pos].clone();
}
}
/// computes permutation by using provided indices as keys
#[inline]
pub fn compute_sort_permutation(permutation: &mut [usize], indices: &[usize]) {
assert_eq!(permutation.len(), indices.len());
// Set permutation to identity
for (i, p) in permutation.iter_mut().enumerate() {
*p = i;
}
// Compute permutation needed to bring minor indices into sorted order
// Note: Using sort_unstable here avoids internal allocations, which is crucial since
// each lane might have a small number of elements
permutation.sort_unstable_by_key(|idx| indices[*idx]);
}

206
nalgebra-sparse/tests/serde.rs Normal file
View File

@ -0,0 +1,206 @@
#![cfg(feature = "serde-serialize")]
//! Serialization tests
#[cfg(any(not(feature = "proptest-support"), not(feature = "compare")))]
compile_error!("Tests must be run with features `proptest-support` and `compare`");
#[macro_use]
pub mod common;
use nalgebra_sparse::coo::CooMatrix;
use nalgebra_sparse::csc::CscMatrix;
use nalgebra_sparse::csr::CsrMatrix;
use nalgebra_sparse::pattern::SparsityPattern;
use proptest::prelude::*;
use serde::{Deserialize, Serialize};
use crate::common::{csc_strategy, csr_strategy};
fn json_roundtrip<T: Serialize + for<'a> Deserialize<'a>>(csr: &T) -> T {
let serialized = serde_json::to_string(csr).unwrap();
let deserialized: T = serde_json::from_str(&serialized).unwrap();
deserialized
}
#[test]
fn pattern_roundtrip() {
{
// A pattern with zero explicitly stored entries
let pattern =
SparsityPattern::try_from_offsets_and_indices(3, 2, vec![0, 0, 0, 0], Vec::new())
.unwrap();
assert_eq!(json_roundtrip(&pattern), pattern);
}
{
// Arbitrary pattern
let offsets = vec![0, 2, 2, 5];
let indices = vec![0, 5, 1, 2, 3];
let pattern =
SparsityPattern::try_from_offsets_and_indices(3, 6, offsets.clone(), indices.clone())
.unwrap();
assert_eq!(json_roundtrip(&pattern), pattern);
}
}
#[test]
#[rustfmt::skip]
fn pattern_deserialize_invalid() {
assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0,2,2,5],"minor_indices":[0,5,1,2,3]}"#).is_ok());
assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":0,"minor_dim":0,"major_offsets":[],"minor_indices":[]}"#).is_err());
assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 3, 5],"minor_indices":[0, 1, 2, 3, 5]}"#).is_err());
assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[1, 2, 2, 5],"minor_indices":[0, 5, 1, 2, 3]}"#).is_err());
assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 2, 2, 4],"minor_indices":[0, 5, 1, 2, 3]}"#).is_err());
assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 2, 2],"minor_indices":[0, 5, 1, 2, 3]}"#).is_err());
assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 3, 2, 5],"minor_indices":[0, 1, 2, 3, 4]}"#).is_err());
assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 2, 2, 5],"minor_indices":[0, 2, 3, 1, 4]}"#).is_err());
assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 2, 2, 5],"minor_indices":[0, 6, 1, 2, 3]}"#).is_err());
assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 2, 2, 5],"minor_indices":[0, 5, 2, 2, 3]}"#).is_err());
}
#[test]
fn coo_roundtrip() {
{
// A COO matrix without entries
let matrix =
CooMatrix::<i32>::try_from_triplets(3, 2, Vec::new(), Vec::new(), Vec::new()).unwrap();
assert_eq!(json_roundtrip(&matrix), matrix);
}
{
// Arbitrary COO matrix, no duplicates
let i = vec![0, 1, 0, 0, 2];
let j = vec![0, 2, 1, 3, 3];
let v = vec![2, 3, 7, 3, 1];
let matrix =
CooMatrix::<i32>::try_from_triplets(3, 5, i.clone(), j.clone(), v.clone()).unwrap();
assert_eq!(json_roundtrip(&matrix), matrix);
}
}
#[test]
fn coo_deserialize_invalid() {
// Valid matrix: {"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,1]}
assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,1]}"#).is_ok());
assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":0,"ncols":0,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,4]}"#).is_err());
assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":-3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,4]}"#).is_err());
assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3]}"#).is_err());
assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,4,5]}"#).is_err());
assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,8,3],"values":[2,3,7,3,4]}"#).is_err());
assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0],"col_indices":[0,2,1,8,3],"values":[2,3,7,3,4]}"#).is_err());
assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,10,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,4]}"#).is_err());
assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,30,3],"values":[2,3,7,3,4]}"#).is_err());
}
#[test]
fn coo_deserialize_duplicates() {
assert_eq!(
serde_json::from_str::<CooMatrix<i32>>(
r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2,0,1],"col_indices":[0,2,1,3,3,0,2],"values":[2,3,7,3,1,5,6]}"#
).unwrap(),
CooMatrix::<i32>::try_from_triplets(
3,
5,
vec![0, 1, 0, 0, 2, 0, 1],
vec![0, 2, 1, 3, 3, 0, 2],
vec![2, 3, 7, 3, 1, 5, 6]
)
.unwrap()
);
}
#[test]
fn csc_roundtrip() {
{
// A CSC matrix with zero explicitly stored entries
let offsets = vec![0, 0, 0, 0];
let indices = vec![];
let values = Vec::<i32>::new();
let matrix = CscMatrix::try_from_csc_data(2, 3, offsets, indices, values).unwrap();
assert_eq!(json_roundtrip(&matrix), matrix);
}
{
// An arbitrary CSC matrix
let offsets = vec![0, 2, 2, 5];
let indices = vec![0, 5, 1, 2, 3];
let values = vec![0, 1, 2, 3, 4];
let matrix =
CscMatrix::try_from_csc_data(6, 3, offsets.clone(), indices.clone(), values.clone())
.unwrap();
assert_eq!(json_roundtrip(&matrix), matrix);
}
}
#[test]
fn csc_deserialize_invalid() {
// Valid matrix: {"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}
assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_ok());
assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":0,"ncols":0,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":-6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3]}"#).is_err());
assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4,5]}"#).is_err());
assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,8,3],"values":[0,1,2,3,4]}"#).is_err());
assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3,1,1],"values":[0,1,2,3,4]}"#).is_err());
// The following actually panics ('range end index 10 out of range for slice of length 5', nalgebra-sparse\src\pattern.rs:156:38)
//assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,10,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
}
#[test]
fn csr_roundtrip() {
{
// A CSR matrix with zero explicitly stored entries
let offsets = vec![0, 0, 0, 0];
let indices = vec![];
let values = Vec::<i32>::new();
let matrix = CsrMatrix::try_from_csr_data(3, 2, offsets, indices, values).unwrap();
assert_eq!(json_roundtrip(&matrix), matrix);
}
{
// An arbitrary CSR matrix
let offsets = vec![0, 2, 2, 5];
let indices = vec![0, 5, 1, 2, 3];
let values = vec![0, 1, 2, 3, 4];
let matrix =
CsrMatrix::try_from_csr_data(3, 6, offsets.clone(), indices.clone(), values.clone())
.unwrap();
assert_eq!(json_roundtrip(&matrix), matrix);
}
}
#[test]
fn csr_deserialize_invalid() {
// Valid matrix: {"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}
assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_ok());
assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":0,"ncols":0,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":-3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3]}"#).is_err());
assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4,5]}"#).is_err());
assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,8,3],"values":[0,1,2,3,4]}"#).is_err());
assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3,1,1],"values":[0,1,2,3,4]}"#).is_err());
// The following actually panics ('range end index 10 out of range for slice of length 5', nalgebra-sparse\src\pattern.rs:156:38)
//assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,10,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
}
proptest! {
#[test]
fn csc_roundtrip_proptest(csc in csc_strategy()) {
prop_assert_eq!(json_roundtrip(&csc), csc);
}
#[test]
fn csr_roundtrip_proptest(csr in csr_strategy()) {
prop_assert_eq!(json_roundtrip(&csr), csr);
}
}

164
nalgebra-sparse/tests/unit_tests/csc.rs
View File

@ -5,6 +5,8 @@ use nalgebra_sparse::{SparseEntry, SparseEntryMut, SparseFormatErrorKind};
use proptest::prelude::*;
use proptest::sample::subsequence;
use super::test_data_examples::{InvalidCsDataExamples, ValidCsDataExamples};
use crate::assert_panics;
use crate::common::csc_strategy;
@ -171,11 +173,26 @@ fn csc_matrix_valid_data() {
}
}
#[test]
fn csc_matrix_valid_data_unsorted_column_indices() {
let valid_data: ValidCsDataExamples = ValidCsDataExamples::new();
let (offsets, indices, values) = valid_data.valid_unsorted_cs_data;
let csc = CscMatrix::try_from_unsorted_csc_data(5, 4, offsets, indices, values).unwrap();
let (offsets2, indices2, values2) = valid_data.valid_cs_data;
let expected_csc = CscMatrix::try_from_csc_data(5, 4, offsets2, indices2, values2).unwrap();
assert_eq!(csc, expected_csc);
}
#[test]
fn csc_matrix_try_from_invalid_csc_data() {
let invalid_data: InvalidCsDataExamples = InvalidCsDataExamples::new();
{
// Empty offset array (invalid length)
let matrix = CscMatrix::try_from_csc_data(0, 0, Vec::new(), Vec::new(), Vec::<u32>::new());
let (offsets, indices, values) = invalid_data.empty_offset_array;
let matrix = CscMatrix::try_from_csc_data(0, 0, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::InvalidStructure
@ -184,10 +201,8 @@ fn csc_matrix_try_from_invalid_csc_data() {
{
// Offset array invalid length for arbitrary data
let offsets = vec![0, 3, 5];
let indices = vec![0, 1, 2, 3, 5];
let values = vec![0, 1, 2, 3, 4];
let (offsets, indices, values) =
invalid_data.offset_array_invalid_length_for_arbitrary_data;
let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
@ -197,9 +212,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
{
// Invalid first entry in offsets array
let offsets = vec![1, 2, 2, 5];
let indices = vec![0, 5, 1, 2, 3];
let values = vec![0, 1, 2, 3, 4];
let (offsets, indices, values) = invalid_data.invalid_first_entry_in_offsets_array;
let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
@ -209,9 +222,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
{
// Invalid last entry in offsets array
let offsets = vec![0, 2, 2, 4];
let indices = vec![0, 5, 1, 2, 3];
let values = vec![0, 1, 2, 3, 4];
let (offsets, indices, values) = invalid_data.invalid_last_entry_in_offsets_array;
let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
@ -221,9 +232,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
{
// Invalid length of offsets array
let offsets = vec![0, 2, 2];
let indices = vec![0, 5, 1, 2, 3];
let values = vec![0, 1, 2, 3, 4];
let (offsets, indices, values) = invalid_data.invalid_length_of_offsets_array;
let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
@ -233,9 +242,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
{
// Nonmonotonic offsets
let offsets = vec![0, 3, 2, 5];
let indices = vec![0, 1, 2, 3, 4];
let values = vec![0, 1, 2, 3, 4];
let (offsets, indices, values) = invalid_data.nonmonotonic_offsets;
let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
@ -257,9 +264,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
{
// Minor index out of bounds
let offsets = vec![0, 2, 2, 5];
let indices = vec![0, 6, 1, 2, 3];
let values = vec![0, 1, 2, 3, 4];
let (offsets, indices, values) = invalid_data.minor_index_out_of_bounds;
let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
@ -269,9 +274,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
{
// Duplicate entry
let offsets = vec![0, 2, 2, 5];
let indices = vec![0, 5, 2, 2, 3];
let values = vec![0, 1, 2, 3, 4];
let (offsets, indices, values) = invalid_data.duplicate_entry;
let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
@ -280,6 +283,121 @@ fn csc_matrix_try_from_invalid_csc_data() {
}
}
#[test]
fn csc_matrix_try_from_unsorted_invalid_csc_data() {
let invalid_data: InvalidCsDataExamples = InvalidCsDataExamples::new();
{
// Empty offset array (invalid length)
let (offsets, indices, values) = invalid_data.empty_offset_array;
let matrix = CscMatrix::try_from_unsorted_csc_data(0, 0, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::InvalidStructure
);
}
{
// Offset array invalid length for arbitrary data
let (offsets, indices, values) =
invalid_data.offset_array_invalid_length_for_arbitrary_data;
let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::InvalidStructure
);
}
{
// Invalid first entry in offsets array
let (offsets, indices, values) = invalid_data.invalid_first_entry_in_offsets_array;
let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::InvalidStructure
);
}
{
// Invalid last entry in offsets array
let (offsets, indices, values) = invalid_data.invalid_last_entry_in_offsets_array;
let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::InvalidStructure
);
}
{
// Invalid length of offsets array
let (offsets, indices, values) = invalid_data.invalid_length_of_offsets_array;
let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::InvalidStructure
);
}
{
// Nonmonotonic offsets
let (offsets, indices, values) = invalid_data.nonmonotonic_offsets;
let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::InvalidStructure
);
}
{
// Major offset out of bounds
let (offsets, indices, values) = invalid_data.major_offset_out_of_bounds;
let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::IndexOutOfBounds
);
}
{
// Minor index out of bounds
let (offsets, indices, values) = invalid_data.minor_index_out_of_bounds;
let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::IndexOutOfBounds
);
}
{
// Duplicate entry
let (offsets, indices, values) = invalid_data.duplicate_entry;
let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::DuplicateEntry
);
}
{
// Duplicate entry in unsorted lane
let (offsets, indices, values) = invalid_data.duplicate_entry_unsorted;
let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::DuplicateEntry
);
}
{
// Wrong values length
let (offsets, indices, values) = invalid_data.wrong_values_length;
let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::InvalidStructure
);
}
}
#[test]
fn csc_disassemble_avoids_clone_when_owned() {
// Test that disassemble avoids cloning the sparsity pattern when it holds the sole reference

58
nalgebra-sparse/tests/unit_tests/csr.rs
View File

@ -5,7 +5,7 @@ use nalgebra_sparse::{SparseEntry, SparseEntryMut, SparseFormatErrorKind};
use proptest::prelude::*;
use proptest::sample::subsequence;
use super::test_data_examples::InvalidCsrDataExamples;
use super::test_data_examples::{InvalidCsDataExamples, ValidCsDataExamples};
use crate::assert_panics;
use crate::common::csr_strategy;
@ -175,30 +175,20 @@ fn csr_matrix_valid_data() {
#[test]
fn csr_matrix_valid_data_unsorted_column_indices() {
let csr = CsrMatrix::try_from_unsorted_csr_data(
4,
5,
vec![0, 3, 5, 8, 11],
vec![4, 1, 3, 3, 1, 2, 3, 0, 3, 4, 1],
vec![5, 1, 4, 7, 4, 2, 3, 1, 8, 9, 6],
)
.unwrap();
let valid_data: ValidCsDataExamples = ValidCsDataExamples::new();
let expected_csr = CsrMatrix::try_from_csr_data(
4,
5,
vec![0, 3, 5, 8, 11],
vec![1, 3, 4, 1, 3, 0, 2, 3, 1, 3, 4],
vec![1, 4, 5, 4, 7, 1, 2, 3, 6, 8, 9],
)
.unwrap();
let (offsets, indices, values) = valid_data.valid_unsorted_cs_data;
let csr = CsrMatrix::try_from_unsorted_csr_data(4, 5, offsets, indices, values).unwrap();
let (offsets2, indices2, values2) = valid_data.valid_cs_data;
let expected_csr = CsrMatrix::try_from_csr_data(4, 5, offsets2, indices2, values2).unwrap();
assert_eq!(csr, expected_csr);
}
#[test]
fn csr_matrix_try_from_invalid_csr_data() {
let invalid_data: InvalidCsrDataExamples = InvalidCsrDataExamples::new();
let invalid_data: InvalidCsDataExamples = InvalidCsDataExamples::new();
{
// Empty offset array (invalid length)
let (offsets, indices, values) = invalid_data.empty_offset_array;
@ -293,7 +283,7 @@ fn csr_matrix_try_from_invalid_csr_data() {
#[test]
fn csr_matrix_try_from_unsorted_invalid_csr_data() {
let invalid_data: InvalidCsrDataExamples = InvalidCsrDataExamples::new();
let invalid_data: InvalidCsDataExamples = InvalidCsDataExamples::new();
{
// Empty offset array (invalid length)
let (offsets, indices, values) = invalid_data.empty_offset_array;
@ -355,6 +345,16 @@ fn csr_matrix_try_from_unsorted_invalid_csr_data() {
);
}
{
// Major offset out of bounds
let (offsets, indices, values) = invalid_data.major_offset_out_of_bounds;
let matrix = CsrMatrix::try_from_unsorted_csr_data(3, 6, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::IndexOutOfBounds
);
}
{
// Minor index out of bounds
let (offsets, indices, values) = invalid_data.minor_index_out_of_bounds;
@ -374,6 +374,26 @@ fn csr_matrix_try_from_unsorted_invalid_csr_data() {
&SparseFormatErrorKind::DuplicateEntry
);
}
{
// Duplicate entry in unsorted lane
let (offsets, indices, values) = invalid_data.duplicate_entry_unsorted;
let matrix = CsrMatrix::try_from_unsorted_csr_data(3, 6, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::DuplicateEntry
);
}
{
// Wrong values length
let (offsets, indices, values) = invalid_data.wrong_values_length;
let matrix = CsrMatrix::try_from_unsorted_csr_data(6, 3, offsets, indices, values);
assert_eq!(
matrix.unwrap_err().kind(),
&SparseFormatErrorKind::InvalidStructure
);
}
}
#[test]

44
nalgebra-sparse/tests/unit_tests/test_data_examples.rs
View File

@ -1,5 +1,31 @@
/// Examples of *invalid* raw CSR data `(offsets, indices, values)`.
pub struct InvalidCsrDataExamples {
/// Examples of *valid* raw CS data `(offsets, indices, values)`.
pub struct ValidCsDataExamples {
pub valid_cs_data: (Vec<usize>, Vec<usize>, Vec<i32>),
pub valid_unsorted_cs_data: (Vec<usize>, Vec<usize>, Vec<i32>),
}
impl ValidCsDataExamples {
pub fn new() -> Self {
let valid_cs_data = (
vec![0, 3, 5, 8, 11],
vec![1, 3, 4, 1, 3, 0, 2, 3, 1, 3, 4],
vec![1, 4, 5, 4, 7, 1, 2, 3, 6, 8, 9],
);
let valid_unsorted_cs_data = (
vec![0, 3, 5, 8, 11],
vec![4, 1, 3, 3, 1, 2, 3, 0, 3, 4, 1],
vec![5, 1, 4, 7, 4, 2, 3, 1, 8, 9, 6],
);
return Self {
valid_cs_data,
valid_unsorted_cs_data,
};
}
}
/// Examples of *invalid* raw CS data `(offsets, indices, values)`.
pub struct InvalidCsDataExamples {
pub empty_offset_array: (Vec<usize>, Vec<usize>, Vec<i32>),
pub offset_array_invalid_length_for_arbitrary_data: (Vec<usize>, Vec<usize>, Vec<i32>),
pub invalid_first_entry_in_offsets_array: (Vec<usize>, Vec<usize>, Vec<i32>),
@ -7,11 +33,14 @@ pub struct InvalidCsrDataExamples {
pub invalid_length_of_offsets_array: (Vec<usize>, Vec<usize>, Vec<i32>),
pub nonmonotonic_offsets: (Vec<usize>, Vec<usize>, Vec<i32>),
pub nonmonotonic_minor_indices: (Vec<usize>, Vec<usize>, Vec<i32>),
pub major_offset_out_of_bounds: (Vec<usize>, Vec<usize>, Vec<i32>),
pub minor_index_out_of_bounds: (Vec<usize>, Vec<usize>, Vec<i32>),
pub duplicate_entry: (Vec<usize>, Vec<usize>, Vec<i32>),
pub duplicate_entry_unsorted: (Vec<usize>, Vec<usize>, Vec<i32>),
pub wrong_values_length: (Vec<usize>, Vec<usize>, Vec<i32>),
}
impl InvalidCsrDataExamples {
impl InvalidCsDataExamples {
pub fn new() -> Self {
let empty_offset_array = (Vec::<usize>::new(), Vec::<usize>::new(), Vec::<i32>::new());
let offset_array_invalid_length_for_arbitrary_data =
@ -25,9 +54,13 @@ impl InvalidCsrDataExamples {
let nonmonotonic_offsets = (vec![0, 3, 2, 5], vec![0, 1, 2, 3, 4], vec![0, 1, 2, 3, 4]);
let nonmonotonic_minor_indices =
(vec![0, 2, 2, 5], vec![0, 2, 3, 1, 4], vec![0, 1, 2, 3, 4]);
let major_offset_out_of_bounds =
(vec![0, 7, 2, 5], vec![0, 2, 3, 1, 4], vec![0, 1, 2, 3, 4]);
let minor_index_out_of_bounds =
(vec![0, 2, 2, 5], vec![0, 6, 1, 2, 3], vec![0, 1, 2, 3, 4]);
let duplicate_entry = (vec![0, 2, 2, 5], vec![0, 5, 2, 2, 3], vec![0, 1, 2, 3, 4]);
let duplicate_entry = (vec![0, 1, 2, 5], vec![1, 3, 2, 3, 3], vec![0, 1, 2, 3, 4]);
let duplicate_entry_unsorted = (vec![0, 1, 4, 5], vec![1, 3, 2, 3, 3], vec![0, 1, 2, 3, 4]);
let wrong_values_length = (vec![0, 1, 2, 5], vec![1, 3, 2, 3, 0], vec![5, 4]);
return Self {
empty_offset_array,
@ -37,8 +70,11 @@ impl InvalidCsrDataExamples {
invalid_length_of_offsets_array,
nonmonotonic_minor_indices,
nonmonotonic_offsets,
major_offset_out_of_bounds,
minor_index_out_of_bounds,
duplicate_entry,
duplicate_entry_unsorted,
wrong_values_length,
};
}
}

79
src/base/array_storage.rs
View File

@ -1,7 +1,5 @@
use std::fmt::{self, Debug, Formatter};
// use std::hash::{Hash, Hasher};
#[cfg(feature = "abomonation-serialize")]
use std::io::{Result as IOResult, Write};
use std::ops::Mul;
#[cfg(feature = "serde-serialize-no-std")]
@ -13,9 +11,6 @@ use serde::{Deserialize, Deserializer, Serialize, Serializer};
#[cfg(feature = "serde-serialize-no-std")]
use std::marker::PhantomData;
#[cfg(feature = "abomonation-serialize")]
use abomonation::Abomonation;
use crate::base::allocator::Allocator;
use crate::base::default_allocator::DefaultAllocator;
use crate::base::dimension::{Const, ToTypenum};
@ -32,10 +27,12 @@ use std::mem;
/// A array-based statically sized matrix data storage.
#[repr(transparent)]
#[derive(Copy, Clone, PartialEq, Eq, Hash)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
pub struct ArrayStorage<T, const R: usize, const C: usize>(pub [[T; R]; C]);
impl<T, const R: usize, const C: usize> ArrayStorage<T, R, C> {
@ -281,71 +278,3 @@ unsafe impl<T: Scalar + Copy + bytemuck::Pod, const R: usize, const C: usize> by
for ArrayStorage<T, R, C>
{
}
#[cfg(feature = "abomonation-serialize")]
impl<T, const R: usize, const C: usize> Abomonation for ArrayStorage<T, R, C>
where
T: Scalar + Abomonation,
{
unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
for element in self.as_slice() {
element.entomb(writer)?;
}
Ok(())
}
unsafe fn exhume<'a, 'b>(&'a mut self, mut bytes: &'b mut [u8]) -> Option<&'b mut [u8]> {
for element in self.as_mut_slice() {
let temp = bytes;
bytes = element.exhume(temp)?
}
Some(bytes)
}
fn extent(&self) -> usize {
self.as_slice().iter().fold(0, |acc, e| acc + e.extent())
}
}
#[cfg(feature = "rkyv-serialize-no-std")]
mod rkyv_impl {
use super::ArrayStorage;
use rkyv::{offset_of, project_struct, Archive, Deserialize, Fallible, Serialize};
impl<T: Archive, const R: usize, const C: usize> Archive for ArrayStorage<T, R, C> {
type Archived = ArrayStorage<T::Archived, R, C>;
type Resolver = <[[T; R]; C] as Archive>::Resolver;
fn resolve(
&self,
pos: usize,
resolver: Self::Resolver,
out: &mut core::mem::MaybeUninit<Self::Archived>,
) {
self.0.resolve(
pos + offset_of!(Self::Archived, 0),
resolver,
project_struct!(out: Self::Archived => 0),
);
}
}
impl<T: Serialize<S>, S: Fallible + ?Sized, const R: usize, const C: usize> Serialize<S>
for ArrayStorage<T, R, C>
{
fn serialize(&self, serializer: &mut S) -> Result<Self::Resolver, S::Error> {
self.0.serialize(serializer)
}
}
impl<T: Archive, D: Fallible + ?Sized, const R: usize, const C: usize>
Deserialize<ArrayStorage<T, R, C>, D> for ArrayStorage<T::Archived, R, C>
where
T::Archived: Deserialize<T, D>,
{
fn deserialize(&self, deserializer: &mut D) -> Result<ArrayStorage<T, R, C>, D::Error> {
Ok(ArrayStorage(self.0.deserialize(deserializer)?))
}
}
}

69
src/base/blas.rs
View File

@ -175,8 +175,7 @@ where
/// Note that this is **not** the matrix multiplication as in, e.g., numpy. For matrix
/// multiplication, use one of: `.gemm`, `.mul_to`, `.mul`, the `*` operator.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::{Vector3, Matrix2x3};
/// let vec1 = Vector3::new(1.0, 2.0, 3.0);
@ -207,8 +206,7 @@ where
/// Note that this is **not** the matrix multiplication as in, e.g., numpy. For matrix
/// multiplication, use one of: `.gemm`, `.mul_to`, `.mul`, the `*` operator.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::{Vector2, Complex};
/// let vec1 = Vector2::new(Complex::new(1.0, 2.0), Complex::new(3.0, 4.0));
@ -232,8 +230,7 @@ where
/// The dot product between the transpose of `self` and `rhs`.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::{Vector3, RowVector3, Matrix2x3, Matrix3x2};
/// let vec1 = Vector3::new(1.0, 2.0, 3.0);
@ -285,8 +282,7 @@ where
///
/// If `b` is zero, `self` is never read from.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::Vector3;
/// let mut vec1 = Vector3::new(1.0, 2.0, 3.0);
@ -308,8 +304,7 @@ where
///
/// If `b` is zero, `self` is never read from.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::Vector3;
/// let mut vec1 = Vector3::new(1.0, 2.0, 3.0);
@ -333,8 +328,7 @@ where
///
/// If `beta` is zero, `self` is never read.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::{Matrix2, Vector2};
/// let mut vec1 = Vector2::new(1.0, 2.0);
@ -425,8 +419,7 @@ where
/// If `beta` is zero, `self` is never read. If `self` is read, only its lower-triangular part
/// (including the diagonal) is actually read.
///
/// # Examples:
///
/// # Examples
/// ```
/// # use nalgebra::{Matrix2, Vector2};
/// let mat = Matrix2::new(1.0, 2.0,
@ -468,8 +461,7 @@ where
/// If `beta` is zero, `self` is never read. If `self` is read, only its lower-triangular part
/// (including the diagonal) is actually read.
///
/// # Examples:
///
/// # Examples
/// ```
/// # use nalgebra::{Matrix2, Vector2, Complex};
/// let mat = Matrix2::new(Complex::new(1.0, 0.0), Complex::new(2.0, -0.1),
@ -552,8 +544,7 @@ where
///
/// If `beta` is zero, `self` is never read.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::{Matrix2, Vector2};
/// let mat = Matrix2::new(1.0, 3.0,
@ -587,8 +578,7 @@ where
/// For real matrices, this is the same as `.gemv_tr`.
/// If `beta` is zero, `self` is never read.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::{Matrix2, Vector2, Complex};
/// let mat = Matrix2::new(Complex::new(1.0, 2.0), Complex::new(3.0, 4.0),
@ -656,8 +646,7 @@ where
///
/// If `beta` is zero, `self` is never read.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::{Matrix2x3, Vector2, Vector3};
/// let mut mat = Matrix2x3::repeat(4.0);
@ -688,8 +677,7 @@ where
///
/// If `beta` is zero, `self` is never read.
///
/// # Examples:
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{Matrix2x3, Vector2, Vector3, Complex};
@ -722,8 +710,7 @@ where
///
/// If `beta` is zero, `self` is never read.
///
/// # Examples:
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{Matrix2x3, Matrix3x4, Matrix2x4};
@ -763,8 +750,7 @@ where
///
/// If `beta` is zero, `self` is never read.
///
/// # Examples:
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{Matrix3x2, Matrix3x4, Matrix2x4};
@ -821,8 +807,7 @@ where
///
/// If `beta` is zero, `self` is never read.
///
/// # Examples:
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{Matrix3x2, Matrix3x4, Matrix2x4, Complex};
@ -921,8 +906,7 @@ where
/// If `beta` is zero, `self` is never read. The result is symmetric. Only the lower-triangular
/// (including the diagonal) part of `self` is read/written.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::{Matrix2, Vector2};
/// let mut mat = Matrix2::identity();
@ -934,6 +918,7 @@ where
/// mat.ger_symm(10.0, &vec1, &vec2, 5.0);
/// assert_eq!(mat.lower_triangle(), expected.lower_triangle());
/// assert_eq!(mat.m12, 99999.99999); // This was untouched.
/// ```
#[inline]
#[deprecated(note = "This is renamed `syger` to match the original BLAS terminology.")]
pub fn ger_symm<D2: Dim, D3: Dim, SB, SC>(
@ -958,8 +943,7 @@ where
/// If `beta` is zero, `self` is never read. The result is symmetric. Only the lower-triangular
/// (including the diagonal) part of `self` is read/written.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::{Matrix2, Vector2};
/// let mut mat = Matrix2::identity();
@ -971,6 +955,7 @@ where
/// mat.syger(10.0, &vec1, &vec2, 5.0);
/// assert_eq!(mat.lower_triangle(), expected.lower_triangle());
/// assert_eq!(mat.m12, 99999.99999); // This was untouched.
/// ```
#[inline]
pub fn syger<D2: Dim, D3: Dim, SB, SC>(
&mut self,
@ -993,8 +978,7 @@ where
/// If `beta` is zero, `self` is never read. The result is symmetric. Only the lower-triangular
/// (including the diagonal) part of `self` is read/written.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::{Matrix2, Vector2, Complex};
/// let mut mat = Matrix2::identity();
@ -1006,6 +990,7 @@ where
/// mat.hegerc(Complex::new(10.0, 20.0), &vec1, &vec2, Complex::new(5.0, 15.0));
/// assert_eq!(mat.lower_triangle(), expected.lower_triangle());
/// assert_eq!(mat.m12, Complex::new(99999.99999, 88888.88888)); // This was untouched.
/// ```
#[inline]
pub fn hegerc<D2: Dim, D3: Dim, SB, SC>(
&mut self,
@ -1031,8 +1016,7 @@ where
///
/// This uses the provided workspace `work` to avoid allocations for intermediate results.
///
/// # Examples:
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{DMatrix, DVector};
@ -1053,6 +1037,7 @@ where
///
/// mat.quadform_tr_with_workspace(&mut workspace, 10.0, &lhs, &mid, 5.0);
/// assert_relative_eq!(mat, expected);
/// ```
pub fn quadform_tr_with_workspace<D2, S2, R3, C3, S3, D4, S4>(
&mut self,
work: &mut Vector<T, D2, S2>,
@ -1085,8 +1070,7 @@ where
/// If `D1` is a type-level integer, then the allocation is performed on the stack.
/// Use `.quadform_tr_with_workspace(...)` instead to avoid allocations.
///
/// # Examples:
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{Matrix2, Matrix3, Matrix2x3, Vector2};
@ -1100,6 +1084,7 @@ where
///
/// mat.quadform_tr(10.0, &lhs, &mid, 5.0);
/// assert_relative_eq!(mat, expected);
/// ```
pub fn quadform_tr<R3, C3, S3, D4, S4>(
&mut self,
alpha: T,
@ -1124,6 +1109,7 @@ where
///
/// This uses the provided workspace `work` to avoid allocations for intermediate results.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{DMatrix, DVector};
@ -1145,6 +1131,7 @@ where
///
/// mat.quadform_with_workspace(&mut workspace, 10.0, &mid, &rhs, 5.0);
/// assert_relative_eq!(mat, expected);
/// ```
pub fn quadform_with_workspace<D2, S2, D3, S3, R4, C4, S4>(
&mut self,
work: &mut Vector<T, D2, S2>,
@ -1180,6 +1167,7 @@ where
/// If `D2` is a type-level integer, then the allocation is performed on the stack.
/// Use `.quadform_with_workspace(...)` instead to avoid allocations.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{Matrix2, Matrix3x2, Matrix3};
@ -1194,6 +1182,7 @@ where
///
/// mat.quadform(10.0, &mid, &rhs, 5.0);
/// assert_relative_eq!(mat, expected);
/// ```
pub fn quadform<D2, S2, R3, C3, S3>(
&mut self,
alpha: T,

71
src/base/dimension.rs
View File

@ -13,10 +13,12 @@ use serde::{Deserialize, Deserializer, Serialize, Serializer};
/// Dim of dynamically-sized algebraic entities.
#[derive(Clone, Copy, Eq, PartialEq, Debug)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
pub struct Dynamic {
value: usize,
}
@ -202,9 +204,11 @@ dim_ops!(
#[derive(Debug, Copy, Clone, PartialEq, Eq, Hash)]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
pub struct Const<const R: usize>;
/// Trait implemented exclusively by type-level integers.
@ -239,37 +243,6 @@ impl<'de, const D: usize> Deserialize<'de> for Const<D> {
}
}
#[cfg(feature = "rkyv-serialize-no-std")]
mod rkyv_impl {
use super::Const;
use rkyv::{Archive, Deserialize, Fallible, Serialize};
impl<const R: usize> Archive for Const<R> {
type Archived = Self;
type Resolver = ();
fn resolve(
&self,
_: usize,
_: Self::Resolver,
_: &mut core::mem::MaybeUninit<Self::Archived>,
) {
}
}
impl<S: Fallible + ?Sized, const R: usize> Serialize<S> for Const<R> {
fn serialize(&self, _: &mut S) -> Result<Self::Resolver, S::Error> {
Ok(())
}
}
impl<D: Fallible + ?Sized, const R: usize> Deserialize<Self, D> for Const<R> {
fn deserialize(&self, _: &mut D) -> Result<Self, D::Error> {
Ok(Const)
}
}
}
pub trait ToConst {
type Const: DimName;
}
@ -309,24 +282,24 @@ impl<const T: usize> DimName for Const<T> {
pub type U1 = Const<1>;
impl ToTypenum for Const<{ typenum::U1::USIZE }> {
impl ToTypenum for Const<1> {
type Typenum = typenum::U1;
}
impl ToConst for typenum::U1 {
type Const = Const<{ typenum::U1::USIZE }>;
type Const = Const<1>;
}
macro_rules! from_to_typenum (
($($D: ident),* $(,)*) => {$(
pub type $D = Const<{ typenum::$D::USIZE }>;
($($D: ident, $VAL: expr);* $(;)*) => {$(
pub type $D = Const<$VAL>;
impl ToTypenum for Const<{ typenum::$D::USIZE }> {
impl ToTypenum for Const<$VAL> {
type Typenum = typenum::$D;
}
impl ToConst for typenum::$D {
type Const = Const<{ typenum::$D::USIZE }>;
type Const = Const<$VAL>;
}
impl IsNotStaticOne for $D { }
@ -334,12 +307,12 @@ macro_rules! from_to_typenum (
);
from_to_typenum!(
U0, /*U1,*/ U2, U3, U4, U5, U6, U7, U8, U9, U10, U11, U12, U13, U14, U15, U16, U17, U18,
U19, U20, U21, U22, U23, U24, U25, U26, U27, U28, U29, U30, U31, U32, U33, U34, U35, U36, U37,
U38, U39, U40, U41, U42, U43, U44, U45, U46, U47, U48, U49, U50, U51, U52, U53, U54, U55, U56,
U57, U58, U59, U60, U61, U62, U63, U64, U65, U66, U67, U68, U69, U70, U71, U72, U73, U74, U75,
U76, U77, U78, U79, U80, U81, U82, U83, U84, U85, U86, U87, U88, U89, U90, U91, U92, U93, U94,
U95, U96, U97, U98, U99, U100, U101, U102, U103, U104, U105, U106, U107, U108, U109, U110,
U111, U112, U113, U114, U115, U116, U117, U118, U119, U120, U121, U122, U123, U124, U125, U126,
U127
U0, 0; /*U1,1;*/ U2, 2; U3, 3; U4, 4; U5, 5; U6, 6; U7, 7; U8, 8; U9, 9; U10, 10; U11, 11; U12, 12; U13, 13; U14, 14; U15, 15; U16, 16; U17, 17; U18, 18;
U19, 19; U20, 20; U21, 21; U22, 22; U23, 23; U24, 24; U25, 25; U26, 26; U27, 27; U28, 28; U29, 29; U30, 30; U31, 31; U32, 32; U33, 33; U34, 34; U35, 35; U36, 36; U37, 37;
U38, 38; U39, 39; U40, 40; U41, 41; U42, 42; U43, 43; U44, 44; U45, 45; U46, 46; U47, 47; U48, 48; U49, 49; U50, 50; U51, 51; U52, 52; U53, 53; U54, 54; U55, 55; U56, 56;
U57, 57; U58, 58; U59, 59; U60, 60; U61, 61; U62, 62; U63, 63; U64, 64; U65, 65; U66, 66; U67, 67; U68, 68; U69, 69; U70, 70; U71, 71; U72, 72; U73, 73; U74, 74; U75, 75;
U76, 76; U77, 77; U78, 78; U79, 79; U80, 80; U81, 81; U82, 82; U83, 83; U84, 84; U85, 85; U86, 86; U87, 87; U88, 88; U89, 89; U90, 90; U91, 91; U92, 92; U93, 93; U94, 94;
U95, 95; U96, 96; U97, 97; U98, 98; U99, 99; U100, 100; U101, 101; U102, 102; U103, 103; U104, 104; U105, 105; U106, 106; U107, 107; U108, 108; U109, 109; U110, 110;
U111, 111; U112, 112; U113, 113; U114, 114; U115, 115; U116, 116; U117, 117; U118, 118; U119, 119; U120, 120; U121, 121; U122, 122; U123, 123; U124, 124; U125, 125; U126, 126;
U127, 127
);

96
src/base/matrix.rs
View File

@ -1,6 +1,4 @@
use num::{One, Zero};
#[cfg(feature = "abomonation-serialize")]
use std::io::{Result as IOResult, Write};
use approx::{AbsDiffEq, RelativeEq, UlpsEq};
use std::any::TypeId;
@ -13,9 +11,6 @@ use std::mem;
#[cfg(feature = "serde-serialize-no-std")]
use serde::{Deserialize, Deserializer, Serialize, Serializer};
#[cfg(feature = "abomonation-serialize")]
use abomonation::Abomonation;
use simba::scalar::{ClosedAdd, ClosedMul, ClosedSub, Field, SupersetOf};
use simba::simd::SimdPartialOrd;
@ -155,10 +150,12 @@ pub type MatrixCross<T, R1, C1, R2, C2> =
/// some concrete types for `T` and a compatible data storage type `S`).
#[repr(C)]
#[derive(Clone, Copy)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
pub struct Matrix<T, R, C, S> {
/// The data storage that contains all the matrix components. Disappointed?
///
@ -254,21 +251,6 @@ where
}
}
#[cfg(feature = "abomonation-serialize")]
impl<T: Scalar, R: Dim, C: Dim, S: Abomonation> Abomonation for Matrix<T, R, C, S> {
unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
self.data.entomb(writer)
}
unsafe fn exhume<'a, 'b>(&'a mut self, bytes: &'b mut [u8]) -> Option<&'b mut [u8]> {
self.data.exhume(bytes)
}
fn extent(&self) -> usize {
self.data.extent()
}
}
#[cfg(feature = "compare")]
impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> matrixcompare_core::Matrix<T>
for Matrix<T, R, C, S>
@ -311,53 +293,6 @@ where
{
}
#[cfg(feature = "rkyv-serialize-no-std")]
mod rkyv_impl {
use super::Matrix;
use core::marker::PhantomData;
use rkyv::{offset_of, project_struct, Archive, Deserialize, Fallible, Serialize};
impl<T: Archive, R: Archive, C: Archive, S: Archive> Archive for Matrix<T, R, C, S> {
type Archived = Matrix<T::Archived, R::Archived, C::Archived, S::Archived>;
type Resolver = S::Resolver;
fn resolve(
&self,
pos: usize,
resolver: Self::Resolver,
out: &mut core::mem::MaybeUninit<Self::Archived>,
) {
self.data.resolve(
pos + offset_of!(Self::Archived, data),
resolver,
project_struct!(out: Self::Archived => data),
);
}
}
impl<T: Archive, R: Archive, C: Archive, S: Serialize<_S>, _S: Fallible + ?Sized> Serialize<_S>
for Matrix<T, R, C, S>
{
fn serialize(&self, serializer: &mut _S) -> Result<Self::Resolver, _S::Error> {
self.data.serialize(serializer)
}
}
impl<T: Archive, R: Archive, C: Archive, S: Archive, D: Fallible + ?Sized>
Deserialize<Matrix<T, R, C, S>, D>
for Matrix<T::Archived, R::Archived, C::Archived, S::Archived>
where
S::Archived: Deserialize<S, D>,
{
fn deserialize(&self, deserializer: &mut D) -> Result<Matrix<T, R, C, S>, D::Error> {
Ok(Matrix {
data: self.data.deserialize(deserializer)?,
_phantoms: PhantomData,
})
}
}
}
impl<T, R, C, S> Matrix<T, R, C, S> {
/// Creates a new matrix with the given data without statically checking that the matrix
/// dimension matches the storage dimension.
@ -434,8 +369,6 @@ where
{
/// Assumes a matrix's entries to be initialized. This operation should be near zero-cost.
///
/// For the similar method that operates on matrix slices, see [`slice_assume_init`].
///
/// # Safety
/// The user must make sure that every single entry of the buffer has been initialized,
/// or Undefined Behavior will immediately occur.
@ -456,12 +389,12 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
/// The shape of this matrix returned as the tuple (number of rows, number of columns).
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::Matrix3x4;
/// let mat = Matrix3x4::<f32>::zeros();
/// assert_eq!(mat.shape(), (3, 4));
/// ```
#[inline]
#[must_use]
pub fn shape(&self) -> (usize, usize) {
@ -478,12 +411,12 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
/// The number of rows of this matrix.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::Matrix3x4;
/// let mat = Matrix3x4::<f32>::zeros();
/// assert_eq!(mat.nrows(), 3);
/// ```
#[inline]
#[must_use]
pub fn nrows(&self) -> usize {
@ -492,12 +425,12 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
/// The number of columns of this matrix.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::Matrix3x4;
/// let mat = Matrix3x4::<f32>::zeros();
/// assert_eq!(mat.ncols(), 4);
/// ```
#[inline]
#[must_use]
pub fn ncols(&self) -> usize {
@ -506,14 +439,14 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
/// The strides (row stride, column stride) of this matrix.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::DMatrix;
/// let mat = DMatrix::<f32>::zeros(10, 10);
/// let slice = mat.slice_with_steps((0, 0), (5, 3), (1, 2));
/// // The column strides is the number of steps (here 2) multiplied by the corresponding dimension.
/// assert_eq!(mat.strides(), (1, 10));
/// ```
#[inline]
#[must_use]
pub fn strides(&self) -> (usize, usize) {
@ -1108,8 +1041,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
/// Iterates through this matrix coordinates in column-major order.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::Matrix2x3;
/// let mat = Matrix2x3::new(11, 12, 13,
@ -1122,6 +1054,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
/// assert_eq!(*it.next().unwrap(), 13);
/// assert_eq!(*it.next().unwrap(), 23);
/// assert!(it.next().is_none());
/// ```
#[inline]
pub fn iter(&self) -> MatrixIter<'_, T, R, C, S> {
MatrixIter::new(&self.data)
@ -1144,6 +1077,7 @@ impl<T, R: Dim, C: Dim, S: RawStorage<T, R, C>> Matrix<T, R, C, S> {
}
/// Iterate through the columns of this matrix.
///
/// # Example
/// ```
/// # use nalgebra::Matrix2x3;

76
src/base/unit.rs
View File

@ -1,14 +1,9 @@
use std::fmt;
#[cfg(feature = "abomonation-serialize")]
use std::io::{Result as IOResult, Write};
use std::ops::Deref;
#[cfg(feature = "serde-serialize-no-std")]
use serde::{Deserialize, Deserializer, Serialize, Serializer};
#[cfg(feature = "abomonation-serialize")]
use abomonation::Abomonation;
use crate::allocator::Allocator;
use crate::base::DefaultAllocator;
use crate::storage::RawStorage;
@ -26,10 +21,12 @@ use crate::{Dim, Matrix, OMatrix, RealField, Scalar, SimdComplexField, SimdRealF
/// in their documentation, read their dedicated pages directly.
#[repr(transparent)]
#[derive(Clone, Hash, Copy)]
// #[cfg_attr(
// all(not(target_os = "cuda"), feature = "cuda"),
// derive(cust::DeviceCopy)
// )]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
// #[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
pub struct Unit<T> {
pub(crate) value: T,
}
@ -66,65 +63,8 @@ impl<'de, T: Deserialize<'de>> Deserialize<'de> for Unit<T> {
}
}
#[cfg(feature = "abomonation-serialize")]
impl<T: Abomonation> Abomonation for Unit<T> {
unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
self.value.entomb(writer)
}
fn extent(&self) -> usize {
self.value.extent()
}
unsafe fn exhume<'a, 'b>(&'a mut self, bytes: &'b mut [u8]) -> Option<&'b mut [u8]> {
self.value.exhume(bytes)
}
}
#[cfg(feature = "rkyv-serialize-no-std")]
mod rkyv_impl {
use super::Unit;
use rkyv::{offset_of, project_struct, Archive, Deserialize, Fallible, Serialize};
impl<T: Archive> Archive for Unit<T> {
type Archived = Unit<T::Archived>;
type Resolver = T::Resolver;
fn resolve(
&self,
pos: usize,
resolver: Self::Resolver,
out: &mut ::core::mem::MaybeUninit<Self::Archived>,
) {
self.value.resolve(
pos + offset_of!(Self::Archived, value),
resolver,
project_struct!(out: Self::Archived => value),
);
}
}
impl<T: Serialize<S>, S: Fallible + ?Sized> Serialize<S> for Unit<T> {
fn serialize(&self, serializer: &mut S) -> Result<Self::Resolver, S::Error> {
self.value.serialize(serializer)
}
}
impl<T: Archive, D: Fallible + ?Sized> Deserialize<Unit<T>, D> for Unit<T::Archived>
where
T::Archived: Deserialize<T, D>,
{
fn deserialize(&self, deserializer: &mut D) -> Result<Unit<T>, D::Error> {
Ok(Unit {
value: self.value.deserialize(deserializer)?,
})
}
}
}
#[cfg(all(not(target_os = "cuda"), feature = "cuda"))]
unsafe impl<T: cust::memory::DeviceCopy, R, C, S> cust::memory::DeviceCopy
for Unit<Matrix<T, R, C, S>>
#[cfg(feature = "cuda")]
unsafe impl<T: cust_core::DeviceCopy, R, C, S> cust_core::DeviceCopy for Unit<Matrix<T, R, C, S>>
where
T: Scalar,
R: Dim,

20
src/base/vec_storage.rs
View File

@ -1,6 +1,3 @@
#[cfg(feature = "abomonation-serialize")]
use std::io::{Result as IOResult, Write};
#[cfg(all(feature = "alloc", not(feature = "std")))]
use alloc::vec::Vec;
@ -18,8 +15,6 @@ use serde::{
};
use crate::Storage;
#[cfg(feature = "abomonation-serialize")]
use abomonation::Abomonation;
use std::mem::MaybeUninit;
/*
@ -402,21 +397,6 @@ where
}
}
#[cfg(feature = "abomonation-serialize")]
impl<T: Abomonation, R: Dim, C: Dim> Abomonation for VecStorage<T, R, C> {
unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
self.data.entomb(writer)
}
unsafe fn exhume<'a, 'b>(&'a mut self, bytes: &'b mut [u8]) -> Option<&'b mut [u8]> {
self.data.exhume(bytes)
}
fn extent(&self) -> usize {
self.data.extent()
}
}
impl<T, R: Dim> Extend<T> for VecStorage<T, R, Dynamic> {
/// Extends the number of columns of the `VecStorage` with elements
/// from the given iterator.

17
src/geometry/dual_quaternion.rs
View File

@ -19,6 +19,7 @@ use simba::scalar::{ClosedNeg, RealField};
/// `DualQuaternions` are stored as \[..real, ..dual\].
/// Both of the quaternion components are laid out in `i, j, k, w` order.
///
/// # Example
/// ```
/// # use nalgebra::{DualQuaternion, Quaternion};
///
@ -39,10 +40,12 @@ use simba::scalar::{ClosedNeg, RealField};
/// See <https://github.com/dimforge/nalgebra/issues/487>
#[repr(C)]
#[derive(Debug, Copy, Clone)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
pub struct DualQuaternion<T> {
/// The real component of the quaternion
pub real: Quaternion<T>,
@ -623,6 +626,7 @@ where
/// dq.rotation().euler_angles().0, std::f32::consts::FRAC_PI_2, epsilon = 1.0e-6
/// );
/// assert_relative_eq!(dq.translation().vector.y, 3.0, epsilon = 1.0e-6);
/// ```
#[inline]
#[must_use]
pub fn sclerp(&self, other: &Self, t: T) -> Self
@ -713,6 +717,7 @@ where
/// Return the rotation part of this unit dual quaternion.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{UnitDualQuaternion, UnitQuaternion, Vector3};
@ -733,6 +738,7 @@ where
/// Return the translation part of this unit dual quaternion.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{UnitDualQuaternion, UnitQuaternion, Vector3};
@ -758,6 +764,7 @@ where
/// Builds an isometry from this unit dual quaternion.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{UnitDualQuaternion, UnitQuaternion, Vector3};
@ -783,6 +790,7 @@ where
///
/// This is the same as the multiplication `self * pt`.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{UnitDualQuaternion, UnitQuaternion, Vector3, Point3};
@ -807,6 +815,7 @@ where
///
/// This is the same as the multiplication `self * v`.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{UnitDualQuaternion, UnitQuaternion, Vector3};
@ -831,6 +840,7 @@ where
/// This may be cheaper than inverting the unit dual quaternion and
/// transforming the point.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{UnitDualQuaternion, UnitQuaternion, Vector3, Point3};
@ -856,6 +866,7 @@ where
/// This may be cheaper than inverting the unit dual quaternion and
/// transforming the vector.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{UnitDualQuaternion, UnitQuaternion, Vector3};
@ -880,6 +891,7 @@ where
/// cheaper than inverting the unit dual quaternion and transforming the
/// vector.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{UnitDualQuaternion, UnitQuaternion, Unit, Vector3};
@ -909,6 +921,7 @@ where
/// Converts this unit dual quaternion interpreted as an isometry
/// into its equivalent homogeneous transformation matrix.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{Matrix4, UnitDualQuaternion, UnitQuaternion, Vector3};

4
src/geometry/dual_quaternion_construction.rs
View File

@ -27,7 +27,6 @@ impl<T: Scalar> DualQuaternion<T> {
/// The dual quaternion multiplicative identity.
///
/// # Example
///
/// ```
/// # use nalgebra::{DualQuaternion, Quaternion};
///
@ -134,6 +133,7 @@ impl<T: SimdRealField> UnitDualQuaternion<T> {
/// The unit dual quaternion multiplicative identity, which also represents
/// the identity transformation as an isometry.
///
/// # Example
/// ```
/// # use nalgebra::{UnitDualQuaternion, UnitQuaternion, Vector3, Point3};
/// let ident = UnitDualQuaternion::identity();
@ -171,6 +171,7 @@ where
/// Return a dual quaternion representing the translation and orientation
/// given by the provided rotation quaternion and translation vector.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{UnitDualQuaternion, UnitQuaternion, Vector3, Point3};
@ -196,6 +197,7 @@ where
/// Return a unit dual quaternion representing the translation and orientation
/// given by the provided isometry.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::{Isometry3, UnitDualQuaternion, UnitQuaternion, Vector3, Point3};

98
src/geometry/isometry.rs
View File

@ -1,15 +1,10 @@
use approx::{AbsDiffEq, RelativeEq, UlpsEq};
use std::fmt;
use std::hash;
#[cfg(feature = "abomonation-serialize")]
use std::io::{Result as IOResult, Write};
#[cfg(feature = "serde-serialize-no-std")]
use serde::{Deserialize, Serialize};
#[cfg(feature = "abomonation-serialize")]
use abomonation::Abomonation;
use simba::scalar::{RealField, SubsetOf};
use simba::simd::SimdRealField;
@ -55,10 +50,7 @@ use crate::geometry::{AbstractRotation, Point, Translation};
///
#[repr(C)]
#[derive(Debug, Copy, Clone)]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
#[cfg_attr(feature = "serde-serialize-no-std", derive(Serialize, Deserialize))]
#[cfg_attr(
feature = "serde-serialize-no-std",
@ -74,6 +66,11 @@ use crate::geometry::{AbstractRotation, Point, Translation};
Owned<T, Const<D>>: Deserialize<'de>,
T: Scalar"))
)]
#[cfg_attr(
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
pub struct Isometry<T, R, const D: usize> {
/// The pure rotational part of this isometry.
pub rotation: R,
@ -81,89 +78,6 @@ pub struct Isometry<T, R, const D: usize> {
pub translation: Translation<T, D>,
}
#[cfg(feature = "abomonation-serialize")]
impl<T, R, const D: usize> Abomonation for Isometry<T, R, D>
where
T: SimdRealField,
R: Abomonation,
Translation<T, D>: Abomonation,
{
unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
self.rotation.entomb(writer)?;
self.translation.entomb(writer)
}
fn extent(&self) -> usize {
self.rotation.extent() + self.translation.extent()
}
unsafe fn exhume<'a, 'b>(&'a mut self, bytes: &'b mut [u8]) -> Option<&'b mut [u8]> {
self.rotation
.exhume(bytes)
.and_then(|bytes| self.translation.exhume(bytes))
}
}
#[cfg(feature = "rkyv-serialize-no-std")]
mod rkyv_impl {
use super::Isometry;
use crate::{base::Scalar, geometry::Translation};
use rkyv::{offset_of, project_struct, Archive, Deserialize, Fallible, Serialize};
impl<T: Scalar + Archive, R: Archive, const D: usize> Archive for Isometry<T, R, D>
where
T::Archived: Scalar,
{
type Archived = Isometry<T::Archived, R::Archived, D>;
type Resolver = (R::Resolver, <Translation<T, D> as Archive>::Resolver);
fn resolve(
&self,
pos: usize,
resolver: Self::Resolver,
out: &mut core::mem::MaybeUninit<Self::Archived>,
) {
self.rotation.resolve(
pos + offset_of!(Self::Archived, rotation),
resolver.0,
project_struct!(out: Self::Archived => rotation),
);
self.translation.resolve(
pos + offset_of!(Self::Archived, translation),
resolver.1,
project_struct!(out: Self::Archived => translation),
);
}
}
impl<T: Scalar + Serialize<S>, R: Serialize<S>, S: Fallible + ?Sized, const D: usize>
Serialize<S> for Isometry<T, R, D>
where
T::Archived: Scalar,
{
fn serialize(&self, serializer: &mut S) -> Result<Self::Resolver, S::Error> {
Ok((
self.rotation.serialize(serializer)?,
self.translation.serialize(serializer)?,
))
}
}
impl<T: Scalar + Archive, R: Archive, _D: Fallible + ?Sized, const D: usize>
Deserialize<Isometry<T, R, D>, _D> for Isometry<T::Archived, R::Archived, D>
where
T::Archived: Scalar + Deserialize<T, _D>,
R::Archived: Scalar + Deserialize<R, _D>,
{
fn deserialize(&self, deserializer: &mut _D) -> Result<Isometry<T, R, D>, _D::Error> {
Ok(Isometry {
rotation: self.rotation.deserialize(deserializer)?,
translation: self.translation.deserialize(deserializer)?,
})
}
}
}
impl<T: Scalar + hash::Hash, R: hash::Hash, const D: usize> hash::Hash for Isometry<T, R, D>
where
Owned<T, Const<D>>: hash::Hash,

21
src/geometry/orthographic.rs
View File

@ -19,10 +19,12 @@ use crate::geometry::{Point3, Projective3};
/// A 3D orthographic projection stored as a homogeneous 4x4 matrix.
#[repr(C)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
#[derive(Copy, Clone)]
pub struct Orthographic3<T> {
matrix: Matrix4<T>,
@ -319,6 +321,7 @@ impl<T: RealField> Orthographic3<T> {
/// The left offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -336,6 +339,7 @@ impl<T: RealField> Orthographic3<T> {
/// The right offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -353,6 +357,7 @@ impl<T: RealField> Orthographic3<T> {
/// The bottom offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -370,6 +375,7 @@ impl<T: RealField> Orthographic3<T> {
/// The top offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -387,6 +393,7 @@ impl<T: RealField> Orthographic3<T> {
/// The near plane offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -404,6 +411,7 @@ impl<T: RealField> Orthographic3<T> {
/// The far plane offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -526,6 +534,7 @@ impl<T: RealField> Orthographic3<T> {
/// Sets the left offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -545,6 +554,7 @@ impl<T: RealField> Orthographic3<T> {
/// Sets the right offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -564,6 +574,7 @@ impl<T: RealField> Orthographic3<T> {
/// Sets the bottom offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -583,6 +594,7 @@ impl<T: RealField> Orthographic3<T> {
/// Sets the top offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -602,6 +614,7 @@ impl<T: RealField> Orthographic3<T> {
/// Sets the near plane offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -621,6 +634,7 @@ impl<T: RealField> Orthographic3<T> {
/// Sets the far plane offset of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -640,6 +654,7 @@ impl<T: RealField> Orthographic3<T> {
/// Sets the view cuboid offsets along the `x` axis.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -665,6 +680,7 @@ impl<T: RealField> Orthographic3<T> {
/// Sets the view cuboid offsets along the `y` axis.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;
@ -690,6 +706,7 @@ impl<T: RealField> Orthographic3<T> {
/// Sets the near and far plane offsets of the view cuboid.
///
/// # Example
/// ```
/// # #[macro_use] extern crate approx;
/// # use nalgebra::Orthographic3;

6
src/geometry/perspective.rs
View File

@ -20,10 +20,12 @@ use crate::geometry::{Point3, Projective3};
/// A 3D perspective projection stored as a homogeneous 4x4 matrix.
#[repr(C)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
#[derive(Copy, Clone)]
pub struct Perspective3<T> {
matrix: Matrix4<T>,

39
src/geometry/point.rs
View File

@ -3,15 +3,10 @@ use num::One;
use std::cmp::Ordering;
use std::fmt;
use std::hash;
#[cfg(feature = "abomonation-serialize")]
use std::io::{Result as IOResult, Write};
#[cfg(feature = "serde-serialize-no-std")]
use serde::{Deserialize, Deserializer, Serialize, Serializer};
#[cfg(feature = "abomonation-serialize")]
use abomonation::Abomonation;
use simba::simd::SimdPartialOrd;
use crate::base::allocator::Allocator;
@ -41,6 +36,11 @@ use std::mem::MaybeUninit;
/// of said transformations for details.
#[repr(C)]
#[derive(Clone)]
#[cfg_attr(
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
pub struct OPoint<T: Scalar, D: DimName>
where
DefaultAllocator: Allocator<T, D>,
@ -74,12 +74,11 @@ where
{
}
#[cfg(all(not(target_os = "cuda"), feature = "cuda"))]
unsafe impl<T: Scalar + cust::memory::DeviceCopy, D: DimName> cust::memory::DeviceCopy
for OPoint<T, D>
#[cfg(feature = "cuda")]
unsafe impl<T: Scalar + cust_core::DeviceCopy, D: DimName> cust_core::DeviceCopy for OPoint<T, D>
where
DefaultAllocator: Allocator<T, D>,
OVector<T, D>: cust::memory::DeviceCopy,
OVector<T, D>: cust_core::DeviceCopy,
{
}
@ -130,26 +129,6 @@ where
}
}
#[cfg(feature = "abomonation-serialize")]
impl<T, D: DimName> Abomonation for OPoint<T, D>
where
T: Scalar,
OVector<T, D>: Abomonation,
DefaultAllocator: Allocator<T, D>,
{
unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
self.coords.entomb(writer)
}
fn extent(&self) -> usize {
self.coords.extent()
}
unsafe fn exhume<'a, 'b>(&'a mut self, bytes: &'b mut [u8]) -> Option<&'b mut [u8]> {
self.coords.exhume(bytes)
}
}
impl<T: Scalar, D: DimName> OPoint<T, D>
where
DefaultAllocator: Allocator<T, D>,
@ -292,6 +271,7 @@ where
/// assert_eq!(it.next(), Some(2.0));
/// assert_eq!(it.next(), Some(3.0));
/// assert_eq!(it.next(), None);
/// ```
#[inline]
pub fn iter(
&self,
@ -318,6 +298,7 @@ where
/// }
///
/// assert_eq!(p, Point3::new(10.0, 20.0, 30.0));
/// ```
#[inline]
pub fn iter_mut(
&mut self,

86
src/geometry/quaternion.rs
View File

@ -2,17 +2,12 @@ use approx::{AbsDiffEq, RelativeEq, UlpsEq};
use num::Zero;
use std::fmt;
use std::hash::{Hash, Hasher};
#[cfg(feature = "abomonation-serialize")]
use std::io::{Result as IOResult, Write};
#[cfg(feature = "serde-serialize-no-std")]
use crate::base::storage::Owned;
#[cfg(feature = "serde-serialize-no-std")]
use serde::{Deserialize, Deserializer, Serialize, Serializer};
#[cfg(feature = "abomonation-serialize")]
use abomonation::Abomonation;
use simba::scalar::{ClosedNeg, RealField};
use simba::simd::{SimdBool, SimdOption, SimdRealField};
@ -28,10 +23,12 @@ use crate::geometry::{Point3, Rotation};
/// that may be used as a rotation.
#[repr(C)]
#[derive(Copy, Clone)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
pub struct Quaternion<T> {
/// This quaternion as a 4D vector of coordinates in the `[ x, y, z, w ]` storage order.
pub coords: Vector4<T>,
@ -77,24 +74,6 @@ where
{
}
#[cfg(feature = "abomonation-serialize")]
impl<T: Scalar> Abomonation for Quaternion<T>
where
Vector4<T>: Abomonation,
{
unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
self.coords.entomb(writer)
}
fn extent(&self) -> usize {
self.coords.extent()
}
unsafe fn exhume<'a, 'b>(&'a mut self, bytes: &'b mut [u8]) -> Option<&'b mut [u8]> {
self.coords.exhume(bytes)
}
}
#[cfg(feature = "serde-serialize-no-std")]
impl<T: Scalar> Serialize for Quaternion<T>
where
@ -123,48 +102,6 @@ where
}
}
#[cfg(feature = "rkyv-serialize-no-std")]
mod rkyv_impl {
use super::Quaternion;
use crate::base::Vector4;
use rkyv::{offset_of, project_struct, Archive, Deserialize, Fallible, Serialize};
impl<T: Archive> Archive for Quaternion<T> {
type Archived = Quaternion<T::Archived>;
type Resolver = <Vector4<T> as Archive>::Resolver;
fn resolve(
&self,
pos: usize,
resolver: Self::Resolver,
out: &mut core::mem::MaybeUninit<Self::Archived>,
) {
self.coords.resolve(
pos + offset_of!(Self::Archived, coords),
resolver,
project_struct!(out: Self::Archived => coords),
);
}
}
impl<T: Serialize<S>, S: Fallible + ?Sized> Serialize<S> for Quaternion<T> {
fn serialize(&self, serializer: &mut S) -> Result<Self::Resolver, S::Error> {
self.coords.serialize(serializer)
}
}
impl<T: Archive, D: Fallible + ?Sized> Deserialize<Quaternion<T>, D> for Quaternion<T::Archived>
where
T::Archived: Deserialize<T, D>,
{
fn deserialize(&self, deserializer: &mut D) -> Result<Quaternion<T>, D::Error> {
Ok(Quaternion {
coords: self.coords.deserialize(deserializer)?,
})
}
}
}
impl<T: SimdRealField> Quaternion<T>
where
T::Element: SimdRealField,
@ -428,6 +365,7 @@ where
/// let expected = Quaternion::new(-20.0, 0.0, 0.0, 0.0);
/// let result = a.inner(&b);
/// assert_relative_eq!(expected, result, epsilon = 1.0e-5);
/// ```
#[inline]
#[must_use]
pub fn inner(&self, other: &Self) -> Self {
@ -1068,8 +1006,8 @@ impl<T: RealField + fmt::Display> fmt::Display for Quaternion<T> {
/// A unit quaternions. May be used to represent a rotation.
pub type UnitQuaternion<T> = Unit<Quaternion<T>>;
#[cfg(all(not(target_os = "cuda"), feature = "cuda"))]
unsafe impl<T: cust::memory::DeviceCopy> cust::memory::DeviceCopy for UnitQuaternion<T> {}
#[cfg(feature = "cuda")]
unsafe impl<T: cust_core::DeviceCopy> cust_core::DeviceCopy for UnitQuaternion<T> {}
impl<T: Scalar + ClosedNeg + PartialEq> PartialEq for UnitQuaternion<T> {
#[inline]
@ -1253,8 +1191,7 @@ where
/// Panics if the angle between both quaternion is 180 degrees (in which case the interpolation
/// is not well-defined). Use `.try_slerp` instead to avoid the panic.
///
/// # Examples:
///
/// # Example
/// ```
/// # use nalgebra::geometry::UnitQuaternion;
///
@ -1476,7 +1413,6 @@ where
/// Builds a rotation matrix from this unit quaternion.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -1559,7 +1495,6 @@ where
/// Converts this unit quaternion into its equivalent homogeneous transformation matrix.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -1583,7 +1518,6 @@ where
/// This is the same as the multiplication `self * pt`.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -1604,7 +1538,6 @@ where
/// This is the same as the multiplication `self * v`.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -1625,7 +1558,6 @@ where
/// point.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -1648,7 +1580,6 @@ where
/// vector.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -1669,7 +1600,6 @@ where
/// vector.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;

30
src/geometry/rotation.rs
View File

@ -2,8 +2,6 @@ use approx::{AbsDiffEq, RelativeEq, UlpsEq};
use num::{One, Zero};
use std::fmt;
use std::hash;
#[cfg(feature = "abomonation-serialize")]
use std::io::{Result as IOResult, Write};
#[cfg(feature = "serde-serialize-no-std")]
use serde::{Deserialize, Deserializer, Serialize, Serializer};
@ -11,9 +9,6 @@ use serde::{Deserialize, Deserializer, Serialize, Serializer};
#[cfg(feature = "serde-serialize-no-std")]
use crate::base::storage::Owned;
#[cfg(feature = "abomonation-serialize")]
use abomonation::Abomonation;
use simba::scalar::RealField;
use simba::simd::SimdRealField;
@ -54,10 +49,12 @@ use crate::geometry::Point;
/// * [Conversion to a matrix <span style="float:right;">`matrix`, `to_homogeneous`…</span>](#conversion-to-a-matrix)
///
#[repr(C)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
#[derive(Copy, Clone)]
pub struct Rotation<T, const D: usize> {
matrix: SMatrix<T, D, D>,
@ -94,25 +91,6 @@ where
{
}
#[cfg(feature = "abomonation-serialize")]
impl<T, const D: usize> Abomonation for Rotation<T, D>
where
T: Scalar,
SMatrix<T, D, D>: Abomonation,
{
unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
self.matrix.entomb(writer)
}
fn extent(&self) -> usize {
self.matrix.extent()
}
unsafe fn exhume<'a, 'b>(&'a mut self, bytes: &'b mut [u8]) -> Option<&'b mut [u8]> {
self.matrix.exhume(bytes)
}
}
#[cfg(feature = "serde-serialize-no-std")]
impl<T: Scalar, const D: usize> Serialize for Rotation<T, D>
where

73
src/geometry/scale.rs
View File

@ -2,15 +2,10 @@ use approx::{AbsDiffEq, RelativeEq, UlpsEq};
use num::{One, Zero};
use std::fmt;
use std::hash;
#[cfg(feature = "abomonation-serialize")]
use std::io::{Result as IOResult, Write};
#[cfg(feature = "serde-serialize-no-std")]
use serde::{Deserialize, Deserializer, Serialize, Serializer};
#[cfg(feature = "abomonation-serialize")]
use abomonation::Abomonation;
use crate::base::allocator::Allocator;
use crate::base::dimension::{DimNameAdd, DimNameSum, U1};
use crate::base::storage::Owned;
@ -22,10 +17,12 @@ use crate::geometry::Point;
/// A scale which supports non-uniform scaling.
#[repr(C)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
#[derive(Copy, Clone)]
pub struct Scale<T, const D: usize> {
/// The scale coordinates, i.e., how much is multiplied to a point's coordinates when it is
@ -64,25 +61,6 @@ where
{
}
#[cfg(feature = "abomonation-serialize")]
impl<T, const D: usize> Abomonation for Scale<T, D>
where
T: Scalar,
SVector<T, D>: Abomonation,
{
unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
self.vector.entomb(writer)
}
fn extent(&self) -> usize {
self.vector.extent()
}
unsafe fn exhume<'a, 'b>(&'a mut self, bytes: &'b mut [u8]) -> Option<&'b mut [u8]> {
self.vector.exhume(bytes)
}
}
#[cfg(feature = "serde-serialize-no-std")]
impl<T: Scalar, const D: usize> Serialize for Scale<T, D>
where
@ -111,49 +89,6 @@ where
}
}
#[cfg(feature = "rkyv-serialize-no-std")]
mod rkyv_impl {
use super::Scale;
use crate::base::SVector;
use rkyv::{offset_of, project_struct, Archive, Deserialize, Fallible, Serialize};
impl<T: Archive, const D: usize> Archive for Scale<T, D> {
type Archived = Scale<T::Archived, D>;
type Resolver = <SVector<T, D> as Archive>::Resolver;
fn resolve(
&self,
pos: usize,
resolver: Self::Resolver,
out: &mut core::mem::MaybeUninit<Self::Archived>,
) {
self.vector.resolve(
pos + offset_of!(Self::Archived, vector),
resolver,
project_struct!(out: Self::Archived => vector),
);
}
}
impl<T: Serialize<S>, S: Fallible + ?Sized, const D: usize> Serialize<S> for Scale<T, D> {
fn serialize(&self, serializer: &mut S) -> Result<Self::Resolver, S::Error> {
self.vector.serialize(serializer)
}
}
impl<T: Archive, _D: Fallible + ?Sized, const D: usize> Deserialize<Scale<T, D>, _D>
for Scale<T::Archived, D>
where
T::Archived: Deserialize<T, _D>,
{
fn deserialize(&self, deserializer: &mut _D) -> Result<Scale<T, D>, _D::Error> {
Ok(Scale {
vector: self.vector.deserialize(deserializer)?,
})
}
}
}
impl<T: Scalar, const D: usize> Scale<T, D> {
/// Inverts `self`.
///

34
src/geometry/similarity.rs
View File

@ -3,15 +3,9 @@ use num::Zero;
use std::fmt;
use std::hash;
#[cfg(feature = "abomonation-serialize")]
use std::io::{Result as IOResult, Write};
#[cfg(feature = "serde-serialize-no-std")]
use serde::{Deserialize, Serialize};
#[cfg(feature = "abomonation-serialize")]
use abomonation::Abomonation;
use simba::scalar::{RealField, SubsetOf};
use simba::simd::SimdRealField;
@ -24,10 +18,7 @@ use crate::geometry::{AbstractRotation, Isometry, Point, Translation};
/// A similarity, i.e., an uniform scaling, followed by a rotation, followed by a translation.
#[repr(C)]
#[derive(Debug, Copy, Clone)]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
#[cfg_attr(feature = "serde-serialize-no-std", derive(Serialize, Deserialize))]
#[cfg_attr(
feature = "serde-serialize-no-std",
@ -43,30 +34,17 @@ use crate::geometry::{AbstractRotation, Isometry, Point, Translation};
DefaultAllocator: Allocator<T, Const<D>>,
Owned<T, Const<D>>: Deserialize<'de>"))
)]
#[cfg_attr(
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
pub struct Similarity<T, R, const D: usize> {
/// The part of this similarity that does not include the scaling factor.
pub isometry: Isometry<T, R, D>,
scaling: T,
}
#[cfg(feature = "abomonation-serialize")]
impl<T: Scalar, R, const D: usize> Abomonation for Similarity<T, R, D>
where
Isometry<T, R, D>: Abomonation,
{
unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
self.isometry.entomb(writer)
}
fn extent(&self) -> usize {
self.isometry.extent()
}
unsafe fn exhume<'a, 'b>(&'a mut self, bytes: &'b mut [u8]) -> Option<&'b mut [u8]> {
self.isometry.exhume(bytes)
}
}
impl<T: Scalar + hash::Hash, R: hash::Hash, const D: usize> hash::Hash for Similarity<T, R, D>
where
Owned<T, Const<D>>: hash::Hash,

10
src/geometry/similarity_construction.rs
View File

@ -38,7 +38,6 @@ where
/// Creates a new identity similarity.
///
/// # Example
///
/// ```
/// # use nalgebra::{Similarity2, Point2, Similarity3, Point3};
///
@ -95,7 +94,6 @@ where
/// its axis passing through the point `p`.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -146,7 +144,6 @@ where
/// Creates a new similarity from a translation, a rotation, and an uniform scaling factor.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -188,7 +185,6 @@ where
/// Creates a new similarity from a translation and a rotation angle.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -232,7 +228,6 @@ macro_rules! similarity_construction_impl(
/// factor.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -288,7 +283,6 @@ macro_rules! similarity_construction_impl(
/// to `eye - at`. Non-collinearity is not checked.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -316,7 +310,7 @@ macro_rules! similarity_construction_impl(
Self::from_isometry(Isometry::<_, $Rot<T>, 3>::face_towards(eye, target, up), scaling)
}
/// Deprecated: Use [`SimilarityMatrix3::face_towards`] instead.
/// Deprecated: Use [`SimilarityMatrix3::face_towards`](Self::face_towards) instead.
#[deprecated(note="renamed to `face_towards`")]
pub fn new_observer_frames(eye: &Point3<T>,
target: &Point3<T>,
@ -338,7 +332,6 @@ macro_rules! similarity_construction_impl(
/// requirement of this parameter is to not be collinear to `target - eye`.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;
@ -376,7 +369,6 @@ macro_rules! similarity_construction_impl(
/// requirement of this parameter is to not be collinear to `target - eye`.
///
/// # Example
///
/// ```
/// # #[macro_use] extern crate approx;
/// # use std::f32;

23
src/geometry/transform.rs
View File

@ -60,26 +60,17 @@ where
/// Tag representing the most general (not necessarily inversible) `Transform` type.
#[derive(Debug, Copy, Clone, Hash, PartialEq, Eq)]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
pub enum TGeneral {}
/// Tag representing the most general inversible `Transform` type.
#[derive(Debug, Copy, Clone, Hash, PartialEq, Eq)]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
pub enum TProjective {}
/// Tag representing an affine `Transform`. Its bottom-row is equal to `(0, 0 ... 0, 1)`.
#[derive(Debug, Copy, Clone, Hash, PartialEq, Eq)]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
pub enum TAffine {}
impl TCategory for TGeneral {
@ -207,13 +198,13 @@ where
{
}
#[cfg(all(not(target_os = "cuda"), feature = "cuda"))]
unsafe impl<T: RealField + cust::memory::DeviceCopy, C: TCategory, const D: usize>
cust::memory::DeviceCopy for Transform<T, C, D>
#[cfg(feature = "cuda")]
unsafe impl<T: RealField + cust_core::DeviceCopy, C: TCategory, const D: usize>
cust_core::DeviceCopy for Transform<T, C, D>
where
Const<D>: DimNameAdd<U1>,
DefaultAllocator: Allocator<T, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>,
Owned<T, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>: cust::memory::DeviceCopy,
Owned<T, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>: cust_core::DeviceCopy,
{
}

75
src/geometry/translation.rs
View File

@ -2,15 +2,10 @@ use approx::{AbsDiffEq, RelativeEq, UlpsEq};
use num::{One, Zero};
use std::fmt;
use std::hash;
#[cfg(feature = "abomonation-serialize")]
use std::io::{Result as IOResult, Write};
#[cfg(feature = "serde-serialize-no-std")]
use serde::{Deserialize, Deserializer, Serialize, Serializer};
#[cfg(feature = "abomonation-serialize")]
use abomonation::Abomonation;
use simba::scalar::{ClosedAdd, ClosedNeg, ClosedSub};
use crate::base::allocator::Allocator;
@ -22,10 +17,12 @@ use crate::geometry::Point;
/// A translation.
#[repr(C)]
#[cfg_attr(feature = "rkyv-serialize", derive(bytecheck::CheckBytes))]
#[cfg_attr(
all(not(target_os = "cuda"), feature = "cuda"),
derive(cust::DeviceCopy)
feature = "rkyv-serialize-no-std",
derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize)
)]
#[cfg_attr(feature = "cuda", derive(cust_core::DeviceCopy))]
#[derive(Copy, Clone)]
pub struct Translation<T, const D: usize> {
/// The translation coordinates, i.e., how much is added to a point's coordinates when it is
@ -64,25 +61,6 @@ where
{
}
#[cfg(feature = "abomonation-serialize")]
impl<T, const D: usize> Abomonation for Translation<T, D>
where
T: Scalar,
SVector<T, D>: Abomonation,
{
unsafe fn entomb<W: Write>(&self, writer: &mut W) -> IOResult<()> {
self.vector.entomb(writer)
}
fn extent(&self) -> usize {
self.vector.extent()
}
unsafe fn exhume<'a, 'b>(&'a mut self, bytes: &'b mut [u8]) -> Option<&'b mut [u8]> {
self.vector.exhume(bytes)
}
}
#[cfg(feature = "serde-serialize-no-std")]
impl<T: Scalar, const D: usize> Serialize for Translation<T, D>
where
@ -111,49 +89,6 @@ where
}
}
#[cfg(feature = "rkyv-serialize-no-std")]
mod rkyv_impl {
use super::Translation;
use crate::base::SVector;
use rkyv::{offset_of, project_struct, Archive, Deserialize, Fallible, Serialize};
impl<T: Archive, const D: usize> Archive for Translation<T, D> {
type Archived = Translation<T::Archived, D>;
type Resolver = <SVector<T, D> as Archive>::Resolver;
fn resolve(
&self,
pos: usize,
resolver: Self::Resolver,
out: &mut core::mem::MaybeUninit<Self::Archived>,
) {
self.vector.resolve(
pos + offset_of!(Self::Archived, vector),
resolver,
project_struct!(out: Self::Archived => vector),
);
}
}
impl<T: Serialize<S>, S: Fallible + ?Sized, const D: usize> Serialize<S> for Translation<T, D> {
fn serialize(&self, serializer: &mut S) -> Result<Self::Resolver, S::Error> {
self.vector.serialize(serializer)
}
}
impl<T: Archive, _D: Fallible + ?Sized, const D: usize> Deserialize<Translation<T, D>, _D>
for Translation<T::Archived, D>
where
T::Archived: Deserialize<T, _D>,
{
fn deserialize(&self, deserializer: &mut _D) -> Result<Translation<T, D>, _D::Error> {
Ok(Translation {
vector: self.vector.deserialize(deserializer)?,
})
}
}
}
impl<T: Scalar, const D: usize> Translation<T, D> {
/// Creates a new translation from the given vector.
#[inline]
@ -255,6 +190,7 @@ impl<T: Scalar + ClosedAdd, const D: usize> Translation<T, D> {
/// let t = Translation3::new(1.0, 2.0, 3.0);
/// let transformed_point = t.transform_point(&Point3::new(4.0, 5.0, 6.0));
/// assert_eq!(transformed_point, Point3::new(5.0, 7.0, 9.0));
/// ```
#[inline]
#[must_use]
pub fn transform_point(&self, pt: &Point<T, D>) -> Point<T, D> {
@ -271,6 +207,7 @@ impl<T: Scalar + ClosedSub, const D: usize> Translation<T, D> {
/// let t = Translation3::new(1.0, 2.0, 3.0);
/// let transformed_point = t.inverse_transform_point(&Point3::new(4.0, 5.0, 6.0));
/// assert_eq!(transformed_point, Point3::new(3.0, 3.0, 3.0));
/// ```
#[inline]
#[must_use]
pub fn inverse_transform_point(&self, pt: &Point<T, D>) -> Point<T, D> {

7
src/geometry/unit_complex.rs
View File

@ -31,8 +31,8 @@ use std::cmp::{Eq, PartialEq};
/// * [Conversion to a matrix <span style="float:right;">`to_rotation_matrix`, `to_homogeneous`…</span>](#conversion-to-a-matrix)
pub type UnitComplex<T> = Unit<Complex<T>>;
#[cfg(all(not(target_os = "cuda"), feature = "cuda"))]
unsafe impl<T: cust::memory::DeviceCopy> cust::memory::DeviceCopy for UnitComplex<T> {}
#[cfg(feature = "cuda")]
unsafe impl<T: cust_core::DeviceCopy> cust_core::DeviceCopy for UnitComplex<T> {}
impl<T: Scalar + PartialEq> PartialEq for UnitComplex<T> {
#[inline]
@ -410,7 +410,8 @@ where
#[inline]
#[must_use]
pub fn slerp(&self, other: &Self, t: T) -> Self {
Self::new(self.angle() * (T::one() - t.clone()) + other.angle() * t)
let delta = other / self;
self * Self::new(delta.angle() * t)
}
}

7
src/lib.rs
View File

@ -78,12 +78,13 @@ an optimized set of tools for computer graphics and physics. Those features incl
unused_mut,
unused_parens,
unused_qualifications,
unused_results,
rust_2018_idioms,
rust_2018_compatibility,
future_incompatible,
missing_copy_implementations
)]
#![cfg_attr(feature = "rkyv-serialize-no-std", warn(unused_results))] // TODO: deny this once bytecheck stops generating warnings.
#![cfg_attr(not(feature = "rkyv-serialize-no-std"), deny(unused_results))]
#![doc(
html_favicon_url = "https://nalgebra.org/img/favicon.ico",
html_root_url = "https://docs.rs/nalgebra/0.25.0"
@ -246,8 +247,8 @@ pub fn min<T: Ord>(a: T, b: T) -> T {
/// The absolute value of `a`.
///
/// Deprecated: Use [`Matrix::abs`] or [`RealField::abs`] instead.
#[deprecated(note = "use the inherent method `Matrix::abs` or `RealField::abs` instead")]
/// Deprecated: Use [`Matrix::abs`] or [`ComplexField::abs`] instead.
#[deprecated(note = "use the inherent method `Matrix::abs` or `ComplexField::abs` instead")]
#[inline]
pub fn abs<T: Signed>(a: &T) -> T {
a.abs()

14
src/linalg/svd.rs
View File

@ -98,7 +98,7 @@ where
matrix,
compute_u,
compute_v,
T::RealField::default_epsilon(),
T::RealField::default_epsilon() * crate::convert(5.0),
0,
)
.unwrap()
@ -888,13 +888,13 @@ fn compute_2x2_uptrig_svd<T: RealField>(
v_t = Some(csv.clone());
}
if compute_u {
let cu = (m11.scale(csv.c()) + m12 * csv.s()) / v1.clone();
let su = (m22 * csv.s()) / v1.clone();
let (csu, sgn_u) = GivensRotation::new(cu, su);
let cu = (m11.scale(csv.c()) + m12 * csv.s()) / v1.clone();
let su = (m22 * csv.s()) / v1.clone();
let (csu, sgn_u) = GivensRotation::new(cu, su);
v1 *= sgn_u.clone();
v2 *= sgn_u;
v1 *= sgn_u.clone();
v2 *= sgn_u;
if compute_u {
u = Some(csu);
}
}

66
src/third_party/glam/common/glam_isometry.rs vendored
View File

@ -1,5 +1,5 @@
use super::glam::{DMat3, DMat4, DQuat, DVec2, DVec3, Mat3, Mat4, Quat, Vec2, Vec3};
use crate::{Isometry2, Isometry3, Matrix3, Matrix4, Translation3, UnitQuaternion, Vector2};
use crate::{Isometry2, Isometry3, Matrix3, Matrix4, Translation3, UnitQuaternion};
use std::convert::TryFrom;
impl From<Isometry2<f32>> for Mat3 {
@ -36,18 +36,18 @@ impl From<Isometry3<f64>> for (DVec3, DQuat) {
}
}
impl From<Isometry2<f32>> for (Vec3, Quat) {
fn from(iso: Isometry2<f32>) -> (Vec3, Quat) {
let tra = Vec3::new(iso.translation.x, iso.translation.y, 0.0);
let rot = Quat::from_axis_angle(Vec3::Z, iso.rotation.angle());
impl From<Isometry2<f32>> for (Vec2, f32) {
fn from(iso: Isometry2<f32>) -> (Vec2, f32) {
let tra = Vec2::new(iso.translation.x, iso.translation.y);
let rot = iso.rotation.angle();
(tra, rot)
}
}
impl From<Isometry2<f64>> for (DVec3, DQuat) {
fn from(iso: Isometry2<f64>) -> (DVec3, DQuat) {
let tra = DVec3::new(iso.translation.x, iso.translation.y, 0.0);
let rot = DQuat::from_axis_angle(DVec3::Z, iso.rotation.angle());
impl From<Isometry2<f64>> for (DVec2, f64) {
fn from(iso: Isometry2<f64>) -> (DVec2, f64) {
let tra = DVec2::new(iso.translation.x, iso.translation.y);
let rot = iso.rotation.angle();
(tra, rot)
}
}
@ -64,30 +64,6 @@ impl From<(DVec3, DQuat)> for Isometry3<f64> {
}
}
impl From<(Vec3, Quat)> for Isometry2<f32> {
fn from((tra, rot): (Vec3, Quat)) -> Self {
Isometry2::new([tra.x, tra.y].into(), rot.to_axis_angle().1)
}
}
impl From<(DVec3, DQuat)> for Isometry2<f64> {
fn from((tra, rot): (DVec3, DQuat)) -> Self {
Isometry2::new([tra.x, tra.y].into(), rot.to_axis_angle().1)
}
}
impl From<(Vec2, Quat)> for Isometry2<f32> {
fn from((tra, rot): (Vec2, Quat)) -> Self {
Isometry2::new(tra.into(), rot.to_axis_angle().1)
}
}
impl From<(DVec2, DQuat)> for Isometry2<f64> {
fn from((tra, rot): (DVec2, DQuat)) -> Self {
Isometry2::new(tra.into(), rot.to_axis_angle().1)
}
}
impl From<(Vec2, f32)> for Isometry2<f32> {
fn from((tra, rot): (Vec2, f32)) -> Self {
Isometry2::new(tra.into(), rot)
@ -112,18 +88,6 @@ impl From<DQuat> for Isometry3<f64> {
}
}
impl From<Quat> for Isometry2<f32> {
fn from(rot: Quat) -> Self {
Isometry2::new(Vector2::zeros(), rot.to_axis_angle().1)
}
}
impl From<DQuat> for Isometry2<f64> {
fn from(rot: DQuat) -> Self {
Isometry2::new(Vector2::zeros(), rot.to_axis_angle().1)
}
}
impl From<Vec3> for Isometry3<f32> {
fn from(tra: Vec3) -> Self {
Isometry3::from_parts(tra.into(), UnitQuaternion::identity())
@ -148,18 +112,6 @@ impl From<DVec2> for Isometry2<f64> {
}
}
impl From<Vec3> for Isometry2<f32> {
fn from(tra: Vec3) -> Self {
Isometry2::new([tra.x, tra.y].into(), 0.0)
}
}
impl From<DVec3> for Isometry2<f64> {
fn from(tra: DVec3) -> Self {
Isometry2::new([tra.x, tra.y].into(), 0.0)
}
}
impl TryFrom<Mat3> for Isometry2<f32> {
type Error = ();

78
src/third_party/glam/common/glam_matrix.rs vendored
View File

@ -3,7 +3,11 @@ use super::glam::{
Mat4, UVec2, UVec3, UVec4, Vec2, Vec3, Vec3A, Vec4,
};
use crate::storage::RawStorage;
use crate::{Matrix, Matrix2, Matrix3, Matrix4, Vector, Vector2, Vector3, Vector4, U2, U3, U4};
use crate::{
Matrix, Matrix2, Matrix3, Matrix4, Unit, UnitVector2, UnitVector3, UnitVector4, Vector,
Vector2, Vector3, Vector4, U2, U3, U4,
};
use std::convert::TryFrom;
macro_rules! impl_vec_conversion(
($N: ty, $Vec2: ty, $Vec3: ty, $Vec4: ty) => {
@ -66,6 +70,63 @@ impl_vec_conversion!(i32, IVec2, IVec3, IVec4);
impl_vec_conversion!(u32, UVec2, UVec3, UVec4);
impl_vec_conversion!(bool, BVec2, BVec3, BVec4);
const ERR: &'static str = "Normalization failed.";
macro_rules! impl_unit_vec_conversion(
($N: ty, $Vec2: ty, $Vec3: ty, $Vec4: ty) => {
impl TryFrom<$Vec2> for UnitVector2<$N> {
type Error = &'static str;
#[inline]
fn try_from(e: $Vec2) -> Result<Self, Self::Error> {
Unit::try_new(e.into(), 0.0).ok_or(ERR)
}
}
impl From<UnitVector2<$N>> for $Vec2
{
#[inline]
fn from(e: UnitVector2<$N>) -> $Vec2 {
e.into_inner().into()
}
}
impl TryFrom<$Vec3> for UnitVector3<$N> {
type Error = &'static str;
#[inline]
fn try_from(e: $Vec3) -> Result<Self, Self::Error> {
Unit::try_new(e.into(), 0.0).ok_or(ERR)
}
}
impl From<UnitVector3<$N>> for $Vec3
{
#[inline]
fn from(e: UnitVector3<$N>) -> $Vec3 {
e.into_inner().into()
}
}
impl TryFrom<$Vec4> for UnitVector4<$N> {
type Error = &'static str;
#[inline]
fn try_from(e: $Vec4) -> Result<Self, Self::Error> {
Unit::try_new(e.into(), 0.0).ok_or(ERR)
}
}
impl From<UnitVector4<$N>> for $Vec4
{
#[inline]
fn from(e: UnitVector4<$N>) -> $Vec4 {
e.into_inner().into()
}
}
}
);
impl_unit_vec_conversion!(f32, Vec2, Vec3, Vec4);
impl_unit_vec_conversion!(f64, DVec2, DVec3, DVec4);
impl From<Vec3A> for Vector3<f32> {
#[inline]
fn from(e: Vec3A) -> Vector3<f32> {
@ -83,6 +144,21 @@ where
}
}
impl TryFrom<Vec3A> for UnitVector3<f32> {
type Error = &'static str;
#[inline]
fn try_from(e: Vec3A) -> Result<Self, Self::Error> {
Unit::try_new(e.into(), 0.0).ok_or(ERR)
}
}
impl From<UnitVector3<f32>> for Vec3A {
#[inline]
fn from(e: UnitVector3<f32>) -> Vec3A {
e.into_inner().into()
}
}
impl From<Mat2> for Matrix2<f32> {
#[inline]
fn from(e: Mat2) -> Matrix2<f32> {

6
src/third_party/glam/mod.rs vendored
View File

@ -1,5 +1,3 @@
#[cfg(feature = "glam013")]
mod v013;
#[cfg(feature = "glam014")]
mod v014;
#[cfg(feature = "glam015")]
@ -10,3 +8,7 @@ mod v016;
mod v017;
#[cfg(feature = "glam018")]
mod v018;
#[cfg(feature = "glam019")]
mod v019;
#[cfg(feature = "glam020")]
mod v020;

2
src/third_party/glam/v013/mod.rs → src/third_party/glam/v019/mod.rs vendored
View File

@ -15,4 +15,4 @@ mod glam_translation;
#[path = "../common/glam_unit_complex.rs"]
mod glam_unit_complex;
pub(self) use glam013 as glam;
pub(self) use glam019 as glam;

18
src/third_party/glam/v020/mod.rs vendored Normal file
View File

@ -0,0 +1,18 @@
#[path = "../common/glam_isometry.rs"]
mod glam_isometry;
#[path = "../common/glam_matrix.rs"]
mod glam_matrix;
#[path = "../common/glam_point.rs"]
mod glam_point;
#[path = "../common/glam_quaternion.rs"]
mod glam_quaternion;
#[path = "../common/glam_rotation.rs"]
mod glam_rotation;
#[path = "../common/glam_similarity.rs"]
mod glam_similarity;
#[path = "../common/glam_translation.rs"]
mod glam_translation;
#[path = "../common/glam_unit_complex.rs"]
mod glam_unit_complex;
pub(self) use glam020 as glam;

51
tests/core/abomonation.rs
View File

@ -1,51 +0,0 @@
use abomonation::{decode, encode, Abomonation};
use na::{
DMatrix, Isometry3, IsometryMatrix3, Matrix3x4, Point3, Quaternion, Rotation3, Similarity3,
SimilarityMatrix3, Translation3,
};
use rand::random;
#[test]
fn abomonate_dmatrix() {
assert_encode_and_decode(DMatrix::<f32>::new_random(3, 5));
}
macro_rules! test_abomonation(
($($test: ident, $ty: ty);* $(;)*) => {$(
#[test]
fn $test() {
assert_encode_and_decode(random::<$ty>());
}
)*}
);
test_abomonation! {
abomonate_matrix3x4, Matrix3x4<f32>;
abomonate_point3, Point3<f32>;
abomonate_translation3, Translation3<f64>;
abomonate_rotation3, Rotation3<f64>;
abomonate_isometry3, Isometry3<f32>;
abomonate_isometry_matrix3, IsometryMatrix3<f64>;
abomonate_similarity3, Similarity3<f32>;
abomonate_similarity_matrix3, SimilarityMatrix3<f32>;
abomonate_quaternion, Quaternion<f32>;
}
fn assert_encode_and_decode<T: Abomonation + PartialEq + Clone>(original_data: T) {
// Hold on to a clone for later comparison
let data = original_data.clone();
// Encode
let mut bytes = Vec::new();
unsafe {
let _ = encode(&original_data, &mut bytes);
}
// Drop the original, so that dangling pointers are revealed by the test
drop(original_data);
if let Some((result, rest)) = unsafe { decode::<T>(&mut bytes) } {
assert!(result == &data);
assert!(rest.len() == 0, "binary data was not decoded completely");
}
}

2
tests/core/mod.rs
View File

@ -1,5 +1,3 @@
#[cfg(feature = "abomonation-serialize")]
mod abomonation;
mod blas;
mod cg;
mod conversion;

71
tests/geometry/rotation.rs
View File

@ -32,7 +32,9 @@ fn quaternion_euler_angles_issue_494() {
#[cfg(feature = "proptest-support")]
mod proptest_tests {
use approx::AbsDiffEq;
use na::{self, Rotation2, Rotation3, Unit};
use na::{UnitComplex, UnitQuaternion};
use simba::scalar::RealField;
use std::f64;
@ -229,5 +231,74 @@ mod proptest_tests {
prop_assert_eq!(r, Rotation3::identity())
}
}
//
//In general, `slerp(a,b,t)` should equal `(b/a)^t * a` even though in practice,
//we may not use that formula directly for complex numbers or quaternions
//
#[test]
fn slerp_powf_agree_2(a in unit_complex(), b in unit_complex(), t in PROPTEST_F64) {
let z1 = a.slerp(&b, t);
let z2 = (b/a).powf(t) * a;
prop_assert!(relative_eq!(z1,z2,epsilon=1e-10));
}
#[test]
fn slerp_powf_agree_3(a in unit_quaternion(), b in unit_quaternion(), t in PROPTEST_F64) {
if let Some(z1) = a.try_slerp(&b, t, f64::default_epsilon()) {
let z2 = (b/a).powf(t) * a;
prop_assert!(relative_eq!(z1,z2,epsilon=1e-10));
}
}
//
//when not antipodal, slerp should always take the shortest path between two orientations
//
#[test]
fn slerp_takes_shortest_path_2(
z in unit_complex(), dtheta in -f64::pi()..f64::pi(), t in 0.0..1.0f64
) {
//ambiguous when at ends of angle range, so we don't really care here
if dtheta.abs() != f64::pi() {
//make two complex numbers separated by an angle between -pi and pi
let (z1, z2) = (z, z * UnitComplex::new(dtheta));
let z3 = z1.slerp(&z2, t);
//since the angle is no larger than a half-turn, and t is between 0 and 1,
//the shortest path just corresponds to adding the scaled angle
let a1 = z3.angle();
let a2 = na::wrap(z1.angle() + dtheta*t, -f64::pi(), f64::pi());
prop_assert!(relative_eq!(a1, a2, epsilon=1e-10));
}
}
#[test]
fn slerp_takes_shortest_path_3(
q in unit_quaternion(), dtheta in -f64::pi()..f64::pi(), t in 0.0..1.0f64
) {
//ambiguous when at ends of angle range, so we don't really care here
if let Some(axis) = q.axis() {
//make two quaternions separated by an angle between -pi and pi
let (q1, q2) = (q, q * UnitQuaternion::from_axis_angle(&axis, dtheta));
let q3 = q1.slerp(&q2, t);
//since the angle is no larger than a half-turn, and t is between 0 and 1,
//the shortest path just corresponds to adding the scaled angle
let q4 = q1 * UnitQuaternion::from_axis_angle(&axis, dtheta*t);
prop_assert!(relative_eq!(q3, q4, epsilon=1e-10));
}
}
}
}

2
tests/lib.rs
View File

@ -9,8 +9,6 @@ compile_error!(
Example: `cargo test --features debug,compare,rand,macros`"
);
#[cfg(feature = "abomonation-serialize")]
extern crate abomonation;
#[cfg(all(feature = "debug", feature = "compare", feature = "rand"))]
#[macro_use]
extern crate approx;

39
tests/linalg/svd.rs
View File

@ -460,3 +460,42 @@ fn svd_sorted() {
epsilon = 1.0e-5
);
}
#[test]
// Exercises bug reported in issue #983 of nalgebra (https://github.com/dimforge/nalgebra/issues/983)
fn svd_regression_issue_983() {
let m = nalgebra::dmatrix![
10.74785316637712f64, -5.994983325167452, -6.064492921857296;
-4.149751381521569, 20.654504205822462, -4.470436210703133;
-22.772715014220207, -1.4554372570788008, 18.108113992170573
]
.transpose();
let svd1 = m.clone().svd(true, true);
let svd2 = m.clone().svd(false, true);
let svd3 = m.clone().svd(true, false);
let svd4 = m.svd(false, false);
assert_relative_eq!(svd1.singular_values, svd2.singular_values, epsilon = 1e-9);
assert_relative_eq!(svd1.singular_values, svd3.singular_values, epsilon = 1e-9);
assert_relative_eq!(svd1.singular_values, svd4.singular_values, epsilon = 1e-9);
assert_relative_eq!(
svd1.singular_values,
nalgebra::dvector![3.16188022e+01, 2.23811978e+01, 0.],
epsilon = 1e-6
);
}
#[test]
// Exercises bug reported in issue #1072 of nalgebra (https://github.com/dimforge/nalgebra/issues/1072)
fn svd_regression_issue_1072() {
let x = nalgebra::dmatrix![-6.206610118536945f64, -3.67612186839874; -1.2755730783423473, 6.047238193479124];
let mut x_svd = x.svd(true, true);
x_svd.singular_values = nalgebra::dvector![1.0, 0.0];
let y = x_svd.recompose().unwrap();
let y_svd = y.svd(true, true);
assert_relative_eq!(
y_svd.singular_values,
nalgebra::dvector![1.0, 0.0],
epsilon = 1e-9
);
}