164 lines
7.1 KiB
Rust
164 lines
7.1 KiB
Rust
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use alga::general::{Real, SubsetOf, SupersetOf};
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use alga::linear::Rotation;
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use core::{SquareMatrix, OwnedSquareMatrix};
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use core::dimension::{DimName, DimNameAdd, DimNameSum, U1};
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use core::storage::OwnedStorage;
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use core::allocator::{Allocator, OwnedAllocator};
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use geometry::{PointBase, TranslationBase, IsometryBase, SimilarityBase, TransformBase, SuperTCategoryOf, TAffine};
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/*
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* This file provides the following conversions:
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* =============================================
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*
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* SimilarityBase -> SimilarityBase
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* SimilarityBase -> TransformBase
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* SimilarityBase -> Matrix (homogeneous)
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*/
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impl<N1, N2, D: DimName, SA, SB, R1, R2> SubsetOf<SimilarityBase<N2, D, SB, R2>> for SimilarityBase<N1, D, SA, R1>
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where N1: Real + SubsetOf<N2>,
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N2: Real + SupersetOf<N1>,
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R1: Rotation<PointBase<N1, D, SA>> + SubsetOf<R2>,
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R2: Rotation<PointBase<N2, D, SB>>,
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SA: OwnedStorage<N1, D, U1>,
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SB: OwnedStorage<N2, D, U1>,
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SA::Alloc: OwnedAllocator<N1, D, U1, SA>,
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SB::Alloc: OwnedAllocator<N2, D, U1, SB> {
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#[inline]
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fn to_superset(&self) -> SimilarityBase<N2, D, SB, R2> {
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SimilarityBase::from_isometry(
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self.isometry.to_superset(),
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self.scaling().to_superset()
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)
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}
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#[inline]
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fn is_in_subset(sim: &SimilarityBase<N2, D, SB, R2>) -> bool {
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::is_convertible::<_, IsometryBase<N1, D, SA, R1>>(&sim.isometry) &&
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::is_convertible::<_, N1>(&sim.scaling())
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}
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#[inline]
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unsafe fn from_superset_unchecked(sim: &SimilarityBase<N2, D, SB, R2>) -> Self {
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SimilarityBase::from_isometry(
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sim.isometry.to_subset_unchecked(),
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sim.scaling().to_subset_unchecked()
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)
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}
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}
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impl<N1, N2, D, SA, SB, R, C> SubsetOf<TransformBase<N2, D, SB, C>> for SimilarityBase<N1, D, SA, R>
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where N1: Real,
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N2: Real + SupersetOf<N1>,
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SA: OwnedStorage<N1, D, U1>,
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SB: OwnedStorage<N2, DimNameSum<D, U1>, DimNameSum<D, U1>>,
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C: SuperTCategoryOf<TAffine>,
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R: Rotation<PointBase<N1, D, SA>> +
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SubsetOf<OwnedSquareMatrix<N1, DimNameSum<D, U1>, SA::Alloc>> + // needed by: .to_homogeneous()
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SubsetOf<SquareMatrix<N2, DimNameSum<D, U1>, SB>>, // needed by: ::convert_unchecked(mm)
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D: DimNameAdd<U1>,
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SA::Alloc: OwnedAllocator<N1, D, U1, SA> +
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Allocator<N1, D, D> + // needed by R
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Allocator<N1, DimNameSum<D, U1>, DimNameSum<D, U1>> + // needed by: .to_homogeneous()
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Allocator<N2, DimNameSum<D, U1>, DimNameSum<D, U1>>, // needed by R
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SB::Alloc: OwnedAllocator<N2, DimNameSum<D, U1>, DimNameSum<D, U1>, SB> +
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Allocator<N2, D, D> + // needed by: mm.fixed_slice_mut
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Allocator<N2, D, U1> + // needed by: m.fixed_slice
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Allocator<N2, U1, D> { // needed by: m.fixed_slice
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#[inline]
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fn to_superset(&self) -> TransformBase<N2, D, SB, C> {
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TransformBase::from_matrix_unchecked(self.to_homogeneous().to_superset())
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}
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#[inline]
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fn is_in_subset(t: &TransformBase<N2, D, SB, C>) -> bool {
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<Self as SubsetOf<_>>::is_in_subset(t.matrix())
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}
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#[inline]
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unsafe fn from_superset_unchecked(t: &TransformBase<N2, D, SB, C>) -> Self {
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Self::from_superset_unchecked(t.matrix())
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}
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}
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impl<N1, N2, D, SA, SB, R> SubsetOf<SquareMatrix<N2, DimNameSum<D, U1>, SB>> for SimilarityBase<N1, D, SA, R>
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where N1: Real,
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N2: Real + SupersetOf<N1>,
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SA: OwnedStorage<N1, D, U1>,
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SB: OwnedStorage<N2, DimNameSum<D, U1>, DimNameSum<D, U1>>,
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R: Rotation<PointBase<N1, D, SA>> +
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SubsetOf<OwnedSquareMatrix<N1, DimNameSum<D, U1>, SA::Alloc>> + // needed by: .to_homogeneous()
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SubsetOf<SquareMatrix<N2, DimNameSum<D, U1>, SB>>, // needed by: ::convert_unchecked(mm)
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D: DimNameAdd<U1>,
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SA::Alloc: OwnedAllocator<N1, D, U1, SA> +
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Allocator<N1, D, D> + // needed by R
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Allocator<N1, DimNameSum<D, U1>, DimNameSum<D, U1>> + // needed by: .to_homogeneous()
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Allocator<N2, DimNameSum<D, U1>, DimNameSum<D, U1>>, // needed by R
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SB::Alloc: OwnedAllocator<N2, DimNameSum<D, U1>, DimNameSum<D, U1>, SB> +
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Allocator<N2, D, D> + // needed by: mm.fixed_slice_mut
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Allocator<N2, D, U1> + // needed by: m.fixed_slice
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Allocator<N2, U1, D> { // needed by: m.fixed_slice
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#[inline]
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fn to_superset(&self) -> SquareMatrix<N2, DimNameSum<D, U1>, SB> {
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self.to_homogeneous().to_superset()
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}
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#[inline]
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fn is_in_subset(m: &SquareMatrix<N2, DimNameSum<D, U1>, SB>) -> bool {
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let mut rot = m.fixed_slice::<D, D>(0, 0).clone_owned();
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if rot.fixed_columns_mut::<U1>(0).try_normalize_mut(N2::zero()).is_some() &&
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rot.fixed_columns_mut::<U1>(1).try_normalize_mut(N2::zero()).is_some() &&
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rot.fixed_columns_mut::<U1>(2).try_normalize_mut(N2::zero()).is_some() {
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// FIXME: could we avoid explicit the computation of the determinant?
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// (its sign is needed to see if the scaling factor is negative).
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if rot.determinant() < N2::zero() {
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rot.fixed_columns_mut::<U1>(0).neg_mut();
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rot.fixed_columns_mut::<U1>(1).neg_mut();
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rot.fixed_columns_mut::<U1>(2).neg_mut();
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}
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let bottom = m.fixed_slice::<U1, D>(D::dim(), 0);
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// Scalar types agree.
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m.iter().all(|e| SupersetOf::<N1>::is_in_subset(e)) &&
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// The normalized block part is a rotation.
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// rot.is_special_orthogonal(N2::default_epsilon().sqrt()) &&
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// The bottom row is (0, 0, ..., 1)
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bottom.iter().all(|e| e.is_zero()) &&
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m[(D::dim(), D::dim())] == N2::one()
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}
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else {
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false
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}
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}
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#[inline]
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unsafe fn from_superset_unchecked(m: &SquareMatrix<N2, DimNameSum<D, U1>, SB>) -> Self {
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let mut mm = m.clone_owned();
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let na = mm.fixed_slice_mut::<D, U1>(0, 0).normalize_mut();
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let nb = mm.fixed_slice_mut::<D, U1>(0, 1).normalize_mut();
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let nc = mm.fixed_slice_mut::<D, U1>(0, 2).normalize_mut();
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let mut scale = (na + nb + nc) / ::convert(3.0); // We take the mean, for robustness.
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// FIXME: could we avoid the explicit computation of the determinant?
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// (its sign is needed to see if the scaling factor is negative).
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if mm.fixed_slice::<D, D>(0, 0).determinant() < N2::zero() {
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mm.fixed_slice_mut::<D, U1>(0, 0).neg_mut();
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mm.fixed_slice_mut::<D, U1>(0, 1).neg_mut();
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mm.fixed_slice_mut::<D, U1>(0, 2).neg_mut();
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scale = -scale;
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}
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let t = m.fixed_slice::<D, U1>(0, D::dim()).into_owned();
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let t = TranslationBase::from_vector(::convert_unchecked(t));
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Self::from_parts(t, ::convert_unchecked(mm), ::convert_unchecked(scale))
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}
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}
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