Implement `hstack` and `vstack`.
The implementation uses a trait to fold over tuples, summing the
dimensions in one direction and checking for equality in the other, and
then uses `fixed_{rows,columns}_mut` if the dimensions are static, or
`{rows,columns}_mut` if the dimensions are dynamic, together with
`copy_from` to construct the output matrix.
This commit is contained in:
Avi Weinstock
parent
52e6db99c6
commit
317aef574a
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@ -305,3 +305,46 @@ fn dvector_arbitrary_expressions() {
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let a_expected = DVector::from_column_slice(&[1 + 2, 2 * 3, 4 * f(5 + 6), 7 - 8 * 9]);
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assert_eq_and_type!(a, a_expected);
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}
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#[test]
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fn test_stacking() {
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use nalgebra::{hstack, vstack, RowVector3, RowVector4};
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assert_eq_and_type!(
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vstack((&RowVector3::new(1, 2, 3), &RowVector3::new(4, 5, 6))),
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Matrix2x3::new(1, 2, 3, 4, 5, 6)
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);
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assert_eq_and_type!(
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vstack((
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&RowVector3::new(1, 2, 3),
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&RowVector3::new(4, 5, 6),
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&RowVector3::new(7, 8, 9)
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)),
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Matrix3::new(1, 2, 3, 4, 5, 6, 7, 8, 9)
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);
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assert_eq_and_type!(
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hstack((&Vector3::new(1, 2, 3), &Vector3::new(4, 5, 6))),
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Matrix3x2::new(1, 4, 2, 5, 3, 6)
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);
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assert_eq_and_type!(
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hstack((
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&Vector3::new(1, 2, 3),
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&Vector3::new(4, 5, 6),
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&Vector3::new(7, 8, 9)
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)),
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Matrix3::new(1, 4, 7, 2, 5, 8, 3, 6, 9)
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);
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assert_eq_and_type!(
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vstack((
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&hstack((&DMatrix::identity(3, 3), &Vector3::new(2, 2, 2))),
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&RowVector4::new(3, 3, 3, 3)
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)),
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matrix![1, 0, 0, 2; 0, 1, 0, 2; 0, 0, 1, 2; 3, 3, 3, 3]
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);
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assert_eq_and_type!(
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vstack((
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&hstack((&DMatrix::identity(3, 3), &dvector![2, 2, 2],)),
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&dvector![3, 3, 3, 3].transpose(),
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)),
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dmatrix![1, 0, 0, 2; 0, 1, 0, 2; 0, 0, 1, 2; 3, 3, 3, 3]
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);
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}
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@ -8,6 +8,7 @@ pub mod default_allocator;
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pub mod dimension;
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pub mod iter;
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mod ops;
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mod stacking;
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pub mod storage;
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mod alias;
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@ -61,6 +62,7 @@ pub use self::alias_slice::*;
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pub use self::alias_view::*;
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pub use self::array_storage::*;
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pub use self::matrix_view::*;
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pub use self::stacking::{hstack, vstack};
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pub use self::storage::*;
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#[cfg(any(feature = "std", feature = "alloc"))]
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pub use self::vec_storage::*;
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@ -0,0 +1,304 @@
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///! Utilities for stacking matrices horizontally and vertically.
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use crate::{
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base::allocator::Allocator,
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constraint::{DimEq, SameNumberOfColumns, SameNumberOfRows, ShapeConstraint},
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Const, DefaultAllocator, Dim, DimAdd, DimSum, Dyn, Matrix, RawStorage, RawStorageMut, Scalar,
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};
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use num_traits::Zero;
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/// A visitor for each folding over each element of a tuple.
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pub trait Visitor<A> {
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/// The output type of this step.
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type Output;
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/// Visits an element of a tuple.
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fn visit(self, x: A) -> Self::Output;
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}
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/// The driver for visiting each element of a tuple.
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pub trait VisitTuple<F> {
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/// The output type of the fold.
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type Output;
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/// Visits each element of a tuple.
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fn visit(visitor: F, x: Self) -> Self::Output;
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}
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macro_rules! impl_visit_tuple {
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($($is:ident),*) => {
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impl_visit_tuple!(__GENERATE_TAILS, [$($is),*]);
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};
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(__GENERATE_TAILS, [$i:ident]) => {
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impl_visit_tuple!(__GENERATE_CLAUSE, [$i]);
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};
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(__GENERATE_TAILS, [$i:ident, $($is:ident),*]) => {
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impl_visit_tuple!(__GENERATE_CLAUSE, [$i, $($is),*]);
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impl_visit_tuple!(__GENERATE_TAILS, [$($is),*]);
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};
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(__GENERATE_CLAUSE, [$i:ident]) => {
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impl<$i, Func: Visitor<$i>> VisitTuple<Func> for ($i,) {
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type Output = <Func as Visitor<$i>>::Output;
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#[allow(non_snake_case)]
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fn visit(visitor: Func, ($i,): Self) -> Self::Output {
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visitor.visit($i)
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}
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}
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};
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(__GENERATE_CLAUSE, [$i:ident, $($is:ident),*]) => {
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impl<$i, $($is,)* Func: Visitor<$i>> VisitTuple<Func> for ($i, $($is),*)
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where ($($is,)*): VisitTuple<<Func as Visitor<$i>>::Output>
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{
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type Output = <($($is,)*) as VisitTuple<<Func as Visitor<$i>>::Output>>::Output;
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#[allow(non_snake_case)]
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fn visit(visitor: Func, ($i, $($is),*): Self) -> Self::Output {
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VisitTuple::visit(visitor.visit($i), ($($is,)*))
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}
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}
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};
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}
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impl_visit_tuple!(H, G, F, E, D, C, B, A);
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mod vstack_impl {
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use super::*;
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#[derive(Clone, Copy)]
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pub struct VStackShapeInit;
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#[derive(Clone, Copy)]
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pub struct VStackShape<R, C> {
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r: R,
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c: C,
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}
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impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Visitor<&Matrix<T, R, C, S>>
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for VStackShapeInit
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{
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type Output = VStackShape<R, C>;
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fn visit(self, x: &Matrix<T, R, C, S>) -> Self::Output {
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let (r, c) = x.shape_generic();
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VStackShape { r, c }
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}
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}
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impl<T: Scalar, R1: Dim + DimAdd<R2>, C1: Dim, R2: Dim, C2: Dim, S2: RawStorage<T, R2, C2>>
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Visitor<&Matrix<T, R2, C2, S2>> for VStackShape<R1, C1>
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where
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ShapeConstraint: SameNumberOfColumns<C1, C2>,
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{
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type Output =
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VStackShape<DimSum<R1, R2>, <ShapeConstraint as DimEq<C1, C2>>::Representative>;
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fn visit(self, x: &Matrix<T, R2, C2, S2>) -> Self::Output {
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let (r, c) = x.shape_generic();
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VStackShape {
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r: self.r.add(r),
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c: <ShapeConstraint as DimEq<C1, C2>>::Representative::from_usize(c.value()),
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}
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}
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}
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pub struct VStack<T, R, C, S, R2> {
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out: Matrix<T, R, C, S>,
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current_row: R2,
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}
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impl<
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T: Scalar,
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R1: Dim + DimAdd<Const<R2>>,
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C1: Dim,
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S1: RawStorageMut<T, R1, C1>,
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const R2: usize,
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C2: Dim,
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S2: RawStorage<T, Const<R2>, C2>,
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R3: Dim + DimAdd<Const<R2>>,
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> Visitor<&Matrix<T, Const<R2>, C2, S2>> for VStack<T, R1, C1, S1, R3>
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where
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ShapeConstraint: SameNumberOfColumns<C1, C2>,
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{
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type Output = VStack<T, R1, C1, S1, DimSum<R3, Const<R2>>>;
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fn visit(self, x: &Matrix<T, Const<R2>, C2, S2>) -> Self::Output {
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let (r2, _) = x.shape_generic();
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let VStack {
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mut out,
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current_row,
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} = self;
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out.fixed_rows_mut::<{ R2 }>(current_row.value())
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.copy_from::<Const<R2>, C2, S2>(x);
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let current_row = current_row.add(r2);
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VStack { out, current_row }
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}
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}
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impl<
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T: Scalar,
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R1: Dim + DimAdd<Dyn>,
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C1: Dim,
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S1: RawStorageMut<T, R1, C1>,
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C2: Dim,
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S2: RawStorage<T, Dyn, C2>,
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R3: Dim + DimAdd<Dyn>,
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> Visitor<&Matrix<T, Dyn, C2, S2>> for VStack<T, R1, C1, S1, R3>
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where
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ShapeConstraint: SameNumberOfColumns<C1, C2>,
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{
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type Output = VStack<T, R1, C1, S1, DimSum<R3, Dyn>>;
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fn visit(self, x: &Matrix<T, Dyn, C2, S2>) -> Self::Output {
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let (r2, _) = x.shape_generic();
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let VStack {
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mut out,
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current_row,
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} = self;
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out.rows_mut(current_row.value(), r2.value())
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.copy_from::<Dyn, C2, S2>(x);
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let current_row = current_row.add(r2);
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VStack { out, current_row }
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}
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}
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/// Stack a tuple of references to matrices with equal column counts vertically, yielding a
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/// matrix with every row of the input matrices.
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pub fn vstack<
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T: Scalar + Zero,
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R: Dim,
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C: Dim,
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X: Copy
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+ VisitTuple<VStackShapeInit, Output = VStackShape<R, C>>
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+ VisitTuple<
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VStack<T, R, C, <DefaultAllocator as Allocator<T, R, C>>::Buffer, Const<0>>,
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Output = VStack<T, R, C, <DefaultAllocator as Allocator<T, R, C>>::Buffer, R>,
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>,
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>(
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x: X,
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) -> Matrix<T, R, C, <DefaultAllocator as Allocator<T, R, C>>::Buffer>
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where
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DefaultAllocator: Allocator<T, R, C>,
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{
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let vstack_shape = VStackShapeInit;
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let vstack_shape = <X as VisitTuple<_>>::visit(vstack_shape, x);
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let vstack_visitor = VStack {
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out: Matrix::zeros_generic(vstack_shape.r, vstack_shape.c),
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current_row: Const,
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};
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let vstack_visitor = <X as VisitTuple<_>>::visit(vstack_visitor, x);
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vstack_visitor.out
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}
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}
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pub use vstack_impl::vstack;
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mod hstack_impl {
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use super::*;
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#[derive(Clone, Copy)]
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pub struct HStackShapeInit;
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#[derive(Clone, Copy)]
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pub struct HStackShape<R, C> {
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r: R,
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c: C,
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}
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impl<T: Scalar, R: Dim, C: Dim, S: RawStorage<T, R, C>> Visitor<&Matrix<T, R, C, S>>
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for HStackShapeInit
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{
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type Output = HStackShape<R, C>;
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fn visit(self, x: &Matrix<T, R, C, S>) -> Self::Output {
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let (r, c) = x.shape_generic();
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HStackShape { r, c }
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}
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}
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impl<T: Scalar, R1: Dim, C1: Dim + DimAdd<C2>, R2: Dim, C2: Dim, S2: RawStorage<T, R2, C2>>
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Visitor<&Matrix<T, R2, C2, S2>> for HStackShape<R1, C1>
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where
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ShapeConstraint: SameNumberOfRows<R1, R2>,
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{
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type Output =
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HStackShape<<ShapeConstraint as DimEq<R1, R2>>::Representative, DimSum<C1, C2>>;
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fn visit(self, x: &Matrix<T, R2, C2, S2>) -> Self::Output {
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let (r, c) = x.shape_generic();
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HStackShape {
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r: <ShapeConstraint as DimEq<R1, R2>>::Representative::from_usize(r.value()),
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c: self.c.add(c),
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}
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}
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}
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pub struct HStack<T, R, C, S, C2> {
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out: Matrix<T, R, C, S>,
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current_col: C2,
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}
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impl<
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T: Scalar,
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R1: Dim,
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C1: Dim + DimAdd<Const<C2>>,
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S1: RawStorageMut<T, R1, C1>,
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R2: Dim,
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const C2: usize,
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S2: RawStorage<T, R2, Const<C2>>,
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C3: Dim + DimAdd<Const<C2>>,
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> Visitor<&Matrix<T, R2, Const<C2>, S2>> for HStack<T, R1, C1, S1, C3>
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where
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ShapeConstraint: SameNumberOfRows<R1, R2>,
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{
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type Output = HStack<T, R1, C1, S1, DimSum<C3, Const<C2>>>;
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fn visit(self, x: &Matrix<T, R2, Const<C2>, S2>) -> Self::Output {
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let (_, c2) = x.shape_generic();
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let HStack {
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mut out,
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current_col,
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} = self;
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out.fixed_columns_mut::<{ C2 }>(current_col.value())
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.copy_from::<R2, Const<C2>, S2>(x);
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let current_col = current_col.add(c2);
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HStack { out, current_col }
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}
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}
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impl<
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T: Scalar,
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R1: Dim,
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C1: Dim + DimAdd<Dyn>,
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S1: RawStorageMut<T, R1, C1>,
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R2: Dim,
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S2: RawStorage<T, R2, Dyn>,
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C3: Dim + DimAdd<Dyn>,
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> Visitor<&Matrix<T, R2, Dyn, S2>> for HStack<T, R1, C1, S1, C3>
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where
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ShapeConstraint: SameNumberOfRows<R1, R2>,
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{
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type Output = HStack<T, R1, C1, S1, DimSum<C3, Dyn>>;
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fn visit(self, x: &Matrix<T, R2, Dyn, S2>) -> Self::Output {
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let (_, c2) = x.shape_generic();
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let HStack {
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mut out,
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current_col,
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} = self;
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out.columns_mut(current_col.value(), c2.value())
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.copy_from::<R2, Dyn, S2>(x);
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let current_col = current_col.add(c2);
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HStack { out, current_col }
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}
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}
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/// Stack a tuple of references to matrices with equal row counts horizontally, yielding a
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/// matrix with every column of the input matrices.
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pub fn hstack<
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T: Scalar + Zero,
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R: Dim,
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C: Dim,
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X: Copy
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+ VisitTuple<HStackShapeInit, Output = HStackShape<R, C>>
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+ VisitTuple<
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HStack<T, R, C, <DefaultAllocator as Allocator<T, R, C>>::Buffer, Const<0>>,
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Output = HStack<T, R, C, <DefaultAllocator as Allocator<T, R, C>>::Buffer, C>,
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>,
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>(
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x: X,
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) -> Matrix<T, R, C, <DefaultAllocator as Allocator<T, R, C>>::Buffer>
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where
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DefaultAllocator: Allocator<T, R, C>,
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{
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let hstack_shape = HStackShapeInit;
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let hstack_shape = <X as VisitTuple<_>>::visit(hstack_shape, x);
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let hstack_visitor = HStack {
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out: Matrix::zeros_generic(hstack_shape.r, hstack_shape.c),
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current_col: Const,
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};
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let hstack_visitor = <X as VisitTuple<_>>::visit(hstack_visitor, x);
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hstack_visitor.out
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}
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}
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pub use hstack_impl::hstack;
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Loading…
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