bump nalgebra to latest version and fix compile

Cargo.toml

@@ -25,16 +25,16 @@ default = []
 minpack-compat = []
 
 [dependencies]
-nalgebra = { version = "0.32.1", default-features = false }
-num-traits = { version = "0.2.14", default-features = false, features = [
+nalgebra = { version = "0.33", default-features = false }
+num-traits = { version = "0.2", default-features = false, features = [
     "libm",
 ] }
 cfg-if = "1.0.0"
 
 [dev-dependencies]
 arrsac = "0.10.0"
 rand = { version = "0.8.4", default-features = false }
-nalgebra = "0.32.1"
+nalgebra = "0.33"
 pcg_rand = "0.13.0"
 sample-consensus = "1.0.2"
 approx = "0.5.1"

src/lm.rs

@@ -257,8 +257,7 @@ impl<F: RealField + Float> LevenbergMarquardt<F> {
         N: Dim,
         M: DimMin<N> + DimMax<N>,
         O: LeastSquaresProblem<F, M, N>,
-        DefaultAllocator:
-            Allocator<F, N> + Reallocator<F, M, N, DimMaximum<M, N>, N> + Allocator<usize, N>,
+        DefaultAllocator: Allocator<N> + Reallocator<F, M, N, DimMaximum<M, N>, N>,
     {
         let (mut lm, mut residuals) = match LM::new(self, target) {
             Err(report) => return report,
@@ -309,7 +308,7 @@ where
     N: Dim,
     M: DimMin<N> + DimMax<N>,
     O: LeastSquaresProblem<F, M, N>,
-    DefaultAllocator: Allocator<F, N> + Allocator<F, DimMaximum<M, N>, N>,
+    DefaultAllocator: Allocator<N> + Allocator<DimMaximum<M, N>, N>,
 {
     config: &'a LevenbergMarquardt<F>,
     /// Current parameters `$\vec{x}$`
@@ -342,7 +341,7 @@ where
     N: Dim,
     M: DimMin<N> + DimMax<N>,
     O: LeastSquaresProblem<F, M, N>,
-    DefaultAllocator: Allocator<F, N> + Allocator<F, DimMaximum<M, N>, N>,
+    DefaultAllocator: Allocator<N> + Allocator<DimMaximum<M, N>, N>,
 {
     #[allow(clippy::type_complexity)]
     fn new(
@@ -455,7 +454,7 @@ where
         lls: &mut LinearLeastSquaresDiagonalProblem<F, M, N>,
     ) -> Result<(), TerminationReason>
     where
-        DefaultAllocator: Allocator<usize, N>,
+        DefaultAllocator: Allocator<N>,
     {
         // Compute norm of scaled gradient and detect degeneracy
         self.gnorm = match lls.max_a_t_b_scaled(self.residuals_norm) {
@@ -510,7 +509,7 @@ where
         param: LMParameter<F, N>,
     ) -> Result<Option<Vector<F, M, O::ResidualStorage>>, TerminationReason>
     where
-        DefaultAllocator: Allocator<usize, N>,
+        DefaultAllocator: Allocator<N>,
     {
         const P1: f64 = 0.1;
         const P0001: f64 = 1.0e-4;

src/lm/test_examples.rs

@@ -512,14 +512,14 @@ impl LeastSquaresProblem<f64, U16, U3> for Meyer {
 #[derive(Clone)]
 struct Watson<P: DimName>
 where
-    DefaultAllocator: Allocator<f64, P>,
+    DefaultAllocator: Allocator<P>,
 {
     params: OVector<f64, P>,
 }
 
 impl<P: DimName> Watson<P>
 where
-    DefaultAllocator: Allocator<f64, P>,
+    DefaultAllocator: Allocator<P>,
 {
     fn new(params: OVector<f64, P>, _n: usize) -> Self {
         Self { params }
@@ -528,7 +528,7 @@ where
 
 impl<P: DimName> LeastSquaresProblem<f64, U31, P> for Watson<P>
 where
-    DefaultAllocator: Allocator<f64, P> + Allocator<f64, U31, P>,
+    DefaultAllocator: Allocator<P> + Allocator<U31, P>,
 {
     type ParameterStorage = Owned<f64, P>;
     type ResidualStorage = Owned<f64, U31>;

src/lm/test_helpers.rs

@@ -15,7 +15,7 @@ pub enum MockCall {
 #[derive(Clone)]
 pub struct MockProblem<N: Dim, M: Dim>
 where
-    DefaultAllocator: Allocator<f64, N> + Allocator<f64, M> + Allocator<f64, M, N>,
+    DefaultAllocator: Allocator<N> + Allocator<M> + Allocator<M, N>,
 {
     call_history: RefCell<Vec<MockCall>>,
     params: Vec<OVector<f64, N>>,
@@ -27,7 +27,7 @@ where
 
 impl<N: Dim, M: Dim> MockProblem<N, M>
 where
-    DefaultAllocator: Allocator<f64, N> + Allocator<f64, M> + Allocator<f64, M, N>,
+    DefaultAllocator: Allocator<N> + Allocator<M> + Allocator<M, N>,
 {
     pub fn new(initial: OVector<f64, N>, residuals: Vec<Option<OVector<f64, M>>>) -> Self {
         Self {
@@ -47,7 +47,7 @@ where
 
 impl<N: Dim, M: Dim> LeastSquaresProblem<f64, M, N> for MockProblem<N, M>
 where
-    DefaultAllocator: Allocator<f64, N> + Allocator<f64, M> + Allocator<f64, M, N>,
+    DefaultAllocator: Allocator<N> + Allocator<M> + Allocator<M, N>,
 {
     type ResidualStorage = Owned<f64, M>;
     type ParameterStorage = Owned<f64, N>;

src/qr.rs

@@ -33,7 +33,7 @@ where
     M: Dim + DimMin<N>,
     N: Dim,
     S: RawStorageMut<F, M, N> + IsContiguous,
-    DefaultAllocator: Allocator<F, N> + Allocator<usize, N>,
+    DefaultAllocator: Allocator<N>,
 {
     /// The column norms of the input matrix `$\mathbf{A}$`
     column_norms: OVector<F, N>,
@@ -54,7 +54,7 @@ where
     M: Dim + DimMin<N> + DimMax<N>,
     N: Dim,
     S: RawStorageMut<F, M, N> + Storage<F, M, N> + IsContiguous,
-    DefaultAllocator: Allocator<F, N> + Allocator<F, DimMaximum<M, N>, N> + Allocator<usize, N>,
+    DefaultAllocator: Allocator<N> + Allocator<DimMaximum<M, N>, N>,
 {
     /// Create a pivoted QR decomposition of a matrix `$\mathbf{A}\in\R^{m\times n}$`.
     pub fn new(mut a: Matrix<F, M, N, S>) -> Self {
@@ -203,7 +203,7 @@ where
     F: nalgebra::RealField + Float + Copy,
     M: Dim + DimMax<N>,
     N: Dim,
-    DefaultAllocator: Allocator<F, N> + Allocator<F, DimMaximum<M, N>, N> + Allocator<usize, N>,
+    DefaultAllocator: Allocator<N> + Allocator<DimMaximum<M, N>, N>,
 {
     /// The first `$n$` entries of `$\mathbf{Q}^\top \vec{b}$`.
     qt_b: OVector<F, N>,
@@ -224,7 +224,7 @@ where
     F: nalgebra::RealField + Copy,
     M: Dim + DimMax<N>,
     N: Dim,
-    DefaultAllocator: Allocator<F, N> + Allocator<F, DimMaximum<M, N>, N> + Allocator<usize, N>,
+    DefaultAllocator: Allocator<N> + Allocator<DimMaximum<M, N>, N>,
 {
     pub permutation: &'a OVector<usize, N>,
     l: &'a OMatrix<F, DimMaximum<M, N>, N>,
@@ -239,7 +239,7 @@ where
     F: nalgebra::RealField + Copy,
     M: Dim + DimMin<N> + DimMax<N>,
     N: Dim,
-    DefaultAllocator: Allocator<F, N> + Allocator<F, DimMaximum<M, N>, N> + Allocator<usize, N>,
+    DefaultAllocator: Allocator<N> + Allocator<DimMaximum<M, N>, N> + Allocator<N>,
 {
     /// Solve the equation `$\mathbf{L}\vec{x} = \mathbf{P}^\top \vec{b}$`.
     pub fn solve(&mut self, mut rhs: OVector<F, N>) -> OVector<F, N> {
@@ -295,7 +295,7 @@ where
     F: nalgebra::RealField + Float + Copy,
     M: Dim + DimMin<N> + DimMax<N>,
     N: Dim,
-    DefaultAllocator: Allocator<F, N> + Allocator<F, DimMaximum<M, N>, N> + Allocator<usize, N>,
+    DefaultAllocator: Allocator<N> + Allocator<DimMaximum<M, N>, N>,
 {
     /// Compute scaled maximum of dot products between `$\vec{b}$` and the columns of `$\mathbf{A}$`.
     ///

src/trust_region.rs

@@ -11,7 +11,7 @@ use num_traits::Float;
 
 pub struct LMParameter<F: RealField, N: Dim>
 where
-    DefaultAllocator: Allocator<F, N>,
+    DefaultAllocator: Allocator<N>,
 {
     pub step: OVector<F, N>,
     pub lambda: F,
@@ -59,7 +59,7 @@ where
     F: RealField + Float,
     N: Dim,
     M: Dim + DimMin<N> + DimMax<N>,
-    DefaultAllocator: Allocator<F, N> + Allocator<F, DimMaximum<M, N>, N> + Allocator<usize, N>,
+    DefaultAllocator: Allocator<N> + Allocator<DimMaximum<M, N>, N>,
 {
     const P1: f64 = 0.1;
     debug_assert!(delta.is_positive());

src/utils.rs

@@ -109,7 +109,7 @@ where
     M: Dim,
     O: LeastSquaresProblem<F, M, N>,
     O::JacobianStorage: Clone,
-    DefaultAllocator: Allocator<F, M, N, Buffer = O::JacobianStorage>,
+    DefaultAllocator: Allocator<M, N, Buffer<F> = O::JacobianStorage>,
 {
     let params = problem.params();
     let n = params.data.shape().0;
@@ -217,9 +217,8 @@ where
     N: Dim,
     M: Dim,
     O: LeastSquaresProblem<Complex<F>, M, N>,
-    DefaultAllocator: Allocator<Complex<F>, N, Buffer = O::ParameterStorage>
-        + Allocator<F, N>
-        + Allocator<F, M, N>,
+    DefaultAllocator:
+        Allocator<N, Buffer<Complex<F>> = O::ParameterStorage> + Allocator<N> + Allocator<M, N>,
 {
     let mut params = problem.params();
     assert!(params.iter().all(|x| x.im.is_zero()), "params must be real");