Completely remove the scalar type from the allocator trait

dimforge · May 20, 2024 · 91bd7a5 · 91bd7a5
1 parent 5a6eaf1
commit 91bd7a5
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diff --git a/examples/dimensional_genericity.rs b/examples/dimensional_genericity.rs
@@ -12,7 +12,7 @@ fn reflect_wrt_hyperplane_with_dimensional_genericity<T: RealField, D: Dim>(
 where
     T: RealField,
     D: Dim,
-    DefaultAllocator: Allocator<T, D>,
+    DefaultAllocator: Allocator<D>,
 {
     let n = plane_normal.as_ref(); // Get the underlying V.
     vector - n * (n.dot(vector) * na::convert(2.0))

diff --git a/nalgebra-lapack/Cargo.toml b/nalgebra-lapack/Cargo.toml
@@ -1,47 +1,47 @@
 [package]
-name    = "nalgebra-lapack"
+name = "nalgebra-lapack"
 version = "0.24.0"
-authors = [ "Sébastien Crozet <developer@crozet.re>", "Andrew Straw <strawman@astraw.com>" ]
+authors = ["Sébastien Crozet <developer@crozet.re>", "Andrew Straw <strawman@astraw.com>"]
 
-description   = "Matrix decompositions using nalgebra matrices and Lapack bindings."
+description = "Matrix decompositions using nalgebra matrices and Lapack bindings."
 documentation = "https://www.nalgebra.org/docs"
 homepage = "https://nalgebra.org"
 repository = "https://github.com/dimforge/nalgebra"
 readme = "../README.md"
-categories = [ "science", "mathematics" ]
-keywords = [ "linear", "algebra", "matrix", "vector", "lapack" ]
+categories = ["science", "mathematics"]
+keywords = ["linear", "algebra", "matrix", "vector", "lapack"]
 license = "MIT"
 edition = "2018"
 
 [badges]
 maintenance = { status = "actively-developed" }
 
 [features]
-serde-serialize  = [ "serde", "nalgebra/serde-serialize" ]
-proptest-support = [ "nalgebra/proptest-support" ]
-arbitrary        = [ "nalgebra/arbitrary" ]
+serde-serialize = ["serde", "nalgebra/serde-serialize"]
+proptest-support = ["nalgebra/proptest-support"]
+arbitrary = ["nalgebra/arbitrary"]
 
 # For BLAS/LAPACK
-default    = ["netlib"]
-openblas   = ["lapack-src/openblas"]
-netlib     = ["lapack-src/netlib"]
+default = ["openblas"]
+openblas = ["lapack-src/openblas"]
+netlib = ["lapack-src/netlib"]
 accelerate = ["lapack-src/accelerate"]
-intel-mkl  = ["lapack-src/intel-mkl"]
+intel-mkl = ["lapack-src/intel-mkl"]
 
 [dependencies]
-nalgebra      = { version = "0.32", path = ".." }
-num-traits    = "0.2"
-num-complex   = { version = "0.4", default-features = false }
-simba         = "0.8"
-serde         = { version = "1.0", features = [ "derive" ], optional = true }
-lapack        = { version = "0.19", default-features = false }
-lapack-src    = { version = "0.8", default-features = false }
+nalgebra = { version = "0.32", path = ".." }
+num-traits = "0.2"
+num-complex = { version = "0.4", default-features = false }
+simba = "0.8"
+serde = { version = "1.0", features = ["derive"], optional = true }
+lapack = { version = "0.19", default-features = false }
+lapack-src = { version = "0.8", default-features = false }
 # clippy = "*"
 
 [dev-dependencies]
-nalgebra   = { version = "0.32", features = [ "arbitrary", "rand" ], path = ".." }
-proptest   = { version = "1", default-features = false, features = ["std"] }
+nalgebra = { version = "0.32", features = ["arbitrary", "rand"], path = ".." }
+proptest = { version = "1", default-features = false, features = ["std"] }
 quickcheck = "1"
-approx     = "0.5"
-rand       = "0.8"
+approx = "0.5"
+rand = "0.8"
 
diff --git a/nalgebra-lapack/src/cholesky.rs b/nalgebra-lapack/src/cholesky.rs
@@ -15,32 +15,32 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<T, D>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<D>,
          OMatrix<T, D, D>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<T, D>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<D>,
          OMatrix<T, D, D>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct Cholesky<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D, D>,
 {
     l: OMatrix<T, D, D>,
 }
 
 impl<T: Scalar + Copy, D: Dim> Copy for Cholesky<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D, D>,
     OMatrix<T, D, D>: Copy,
 {
 }
 
 impl<T: CholeskyScalar + Zero, D: Dim> Cholesky<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D, D>,
 {
     /// Computes the cholesky decomposition of the given symmetric-definite-positive square
     /// matrix.
@@ -105,7 +105,7 @@ where
     ) -> Option<OMatrix<T, R2, C2>>
     where
         S2: Storage<T, R2, C2>,
-        DefaultAllocator: Allocator<T, R2, C2>,
+        DefaultAllocator: Allocator<R2, C2>,
     {
         let mut res = b.clone_owned();
         if self.solve_mut(&mut res) {
@@ -119,7 +119,7 @@ where
     /// the unknown to be determined.
     pub fn solve_mut<R2: Dim, C2: Dim>(&self, b: &mut OMatrix<T, R2, C2>) -> bool
     where
-        DefaultAllocator: Allocator<T, R2, C2>,
+        DefaultAllocator: Allocator<R2, C2>,
     {
         let dim = self.l.nrows();
 

diff --git a/nalgebra-lapack/src/eigen.rs b/nalgebra-lapack/src/eigen.rs
@@ -16,24 +16,20 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(serialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Serialize,
-         OMatrix<T, D, D>: Serialize")
-    )
+         OMatrix<T, D, D>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(deserialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Serialize,
-         OMatrix<T, D, D>: Deserialize<'de>")
-    )
+         OMatrix<T, D, D>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct Eigen<T: Scalar, D: Dim>
 where
-    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D> + Allocator<D, D>,
 {
     /// The real parts of eigenvalues of the decomposed matrix.
     pub eigenvalues_re: OVector<T, D>,
@@ -47,15 +43,15 @@ where
 
 impl<T: Scalar + Copy, D: Dim> Copy for Eigen<T, D>
 where
-    DefaultAllocator: Allocator<T, D> + Allocator<T, D, D>,
+    DefaultAllocator: Allocator<D> + Allocator<D, D>,
     OVector<T, D>: Copy,
     OMatrix<T, D, D>: Copy,
 {
 }
 
 impl<T: EigenScalar + RealField, D: Dim> Eigen<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
 {
     /// Computes the eigenvalues and eigenvectors of the square matrix `m`.
     ///
@@ -177,7 +173,7 @@ where
         Option<Vec<OVector<T, D>>>,
     )
     where
-        DefaultAllocator: Allocator<T, D>,
+        DefaultAllocator: Allocator<D>,
     {
         let (number_of_elements, _) = self.eigenvalues_re.shape_generic();
         let number_of_elements_value = number_of_elements.value();
@@ -234,7 +230,7 @@ where
         Option<Vec<OVector<Complex<T>, D>>>,
     )
     where
-        DefaultAllocator: Allocator<Complex<T>, D>,
+        DefaultAllocator: Allocator<D>,
     {
         match self.eigenvalues_are_real() {
             true => (None, None, None),

diff --git a/nalgebra-lapack/src/generalized_eigenvalues.rs b/nalgebra-lapack/src/generalized_eigenvalues.rs
@@ -30,24 +30,20 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(serialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Serialize,
-         OMatrix<T, D, D>: Serialize")
-    )
+         OMatrix<T, D, D>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(
-        bound(deserialize = "DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<D, D> + Allocator<D>,
          OVector<T, D>: Deserialize<'de>,
-         OMatrix<T, D, 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>,
+    DefaultAllocator: Allocator<D> + Allocator<D, D>,
 {
     alphar: OVector<T, D>,
     alphai: OVector<T, D>,
@@ -58,15 +54,15 @@ where
 
 impl<T: Scalar + Copy, D: Dim> Copy for GeneralizedEigen<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, D>,
+    DefaultAllocator: Allocator<D, D> + Allocator<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>,
+    DefaultAllocator: Allocator<D, D> + Allocator<D>,
 {
     /// Attempts to compute the generalized eigenvalues, and left and right associated eigenvectors
     /// via the raw returns from LAPACK's dggev and sggev routines
@@ -162,8 +158,7 @@ where
     /// 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>,
+        DefaultAllocator: Allocator<D, D> + Allocator<D>,
     {
         /*
          How the eigenvectors are built up:
@@ -230,7 +225,7 @@ where
     #[must_use]
     pub fn raw_eigenvalues(&self) -> OVector<(Complex<T>, T), D>
     where
-        DefaultAllocator: Allocator<(Complex<T>, T), D>,
+        DefaultAllocator: Allocator<D>,
     {
         let mut out = Matrix::from_element_generic(
             self.vsl.shape_generic().0,

diff --git a/nalgebra-lapack/src/hessenberg.rs b/nalgebra-lapack/src/hessenberg.rs
@@ -12,38 +12,38 @@ use lapack;
 #[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(serialize = "DefaultAllocator: Allocator<T, D, D> +
-                           Allocator<T, DimDiff<D, U1>>,
+    serde(bound(serialize = "DefaultAllocator: Allocator<D, D> +
+                           Allocator<DimDiff<D, U1>>,
          OMatrix<T, D, D>: Serialize,
          OVector<T, DimDiff<D, U1>>: Serialize"))
 )]
 #[cfg_attr(
     feature = "serde-serialize",
-    serde(bound(deserialize = "DefaultAllocator: Allocator<T, D, D> +
-                           Allocator<T, DimDiff<D, U1>>,
+    serde(bound(deserialize = "DefaultAllocator: Allocator<D, D> +
+                           Allocator<DimDiff<D, U1>>,
          OMatrix<T, D, D>: Deserialize<'de>,
          OVector<T, DimDiff<D, U1>>: Deserialize<'de>"))
 )]
 #[derive(Clone, Debug)]
 pub struct Hessenberg<T: Scalar, D: DimSub<U1>>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
+    DefaultAllocator: Allocator<D, D> + Allocator<DimDiff<D, U1>>,
 {
     h: OMatrix<T, D, D>,
     tau: OVector<T, DimDiff<D, U1>>,
 }
 
 impl<T: Scalar + Copy, D: DimSub<U1>> Copy for Hessenberg<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
+    DefaultAllocator: Allocator<D, D> + Allocator<DimDiff<D, U1>>,
     OMatrix<T, D, D>: Copy,
     OVector<T, DimDiff<D, U1>>: Copy,
 {
 }
 
 impl<T: HessenbergScalar + Zero, D: DimSub<U1>> Hessenberg<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
+    DefaultAllocator: Allocator<D, D> + Allocator<DimDiff<D, U1>>,
 {
     /// Computes the hessenberg decomposition of the matrix `m`.
     pub fn new(mut m: OMatrix<T, D, D>) -> Self {
@@ -97,7 +97,7 @@ where
 
 impl<T: HessenbergReal + Zero, D: DimSub<U1>> Hessenberg<T, D>
 where
-    DefaultAllocator: Allocator<T, D, D> + Allocator<T, DimDiff<D, U1>>,
+    DefaultAllocator: Allocator<D, D> + Allocator<DimDiff<D, U1>>,
 {
     /// Computes the matrices `(Q, H)` of this decomposition.
     #[inline]