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8c6ad490bc
nalgebra/src/geometry/similarity_conversion.rs
Violeta Hernández 281b140365
Fix most clippy warnings
2021-06-18 09:45:37 +02:00

322 lines
11 KiB
Rust
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use num::Zero;
use simba::scalar::{RealField, SubsetOf, SupersetOf};
use simba::simd::{PrimitiveSimdValue, SimdRealField, SimdValue};
use crate::base::allocator::Allocator;
use crate::base::dimension::{DimMin, DimNameAdd, DimNameSum, U1};
use crate::base::{Const, DefaultAllocator, OMatrix, Scalar};
use crate::geometry::{
AbstractRotation, Isometry, Similarity, SuperTCategoryOf, TAffine, Transform, Translation,
};
/*
* This file provides the following conversions:
* =============================================
*
* Similarity -> Similarity
* Similarity -> Transform
* Similarity -> Matrix (homogeneous)
*/
impl<T1, T2, R1, R2, const D: usize> SubsetOf<Similarity<T2, R2, D>> for Similarity<T1, R1, D>
where
T1: RealField + SubsetOf<T2>,
T2: RealField + SupersetOf<T1>,
R1: AbstractRotation<T1, D> + SubsetOf<R2>,
R2: AbstractRotation<T2, D>,
{
#[inline]
fn to_superset(&self) -> Similarity<T2, R2, D> {
Similarity::from_isometry(self.isometry.to_superset(), self.scaling().to_superset())
}
#[inline]
fn is_in_subset(sim: &Similarity<T2, R2, D>) -> bool {
crate::is_convertible::<_, Isometry<T1, R1, D>>(&sim.isometry)
&& crate::is_convertible::<_, T1>(&sim.scaling())
}
#[inline]
fn from_superset_unchecked(sim: &Similarity<T2, R2, D>) -> Self {
Similarity::from_isometry(
sim.isometry.to_subset_unchecked(),
sim.scaling().to_subset_unchecked(),
)
}
}
impl<T1, T2, R, C, const D: usize> SubsetOf<Transform<T2, C, D>> for Similarity<T1, R, D>
where
T1: RealField,
T2: RealField + SupersetOf<T1>,
C: SuperTCategoryOf<TAffine>,
R: AbstractRotation<T1, D>
+ SubsetOf<OMatrix<T1, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>>
+ SubsetOf<OMatrix<T2, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>>,
Const<D>: DimNameAdd<U1> + DimMin<Const<D>, Output = Const<D>>, // needed by .determinant()
DefaultAllocator: Allocator<T1, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>
+ Allocator<T2, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>
+ Allocator<T2, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>,
// + Allocator<(usize, usize), D>
// + Allocator<T1, D>
// + Allocator<T1, D, D>
// + Allocator<T2, D, D>
// + Allocator<T2, D>,
{
#[inline]
fn to_superset(&self) -> Transform<T2, C, D> {
Transform::from_matrix_unchecked(self.to_homogeneous().to_superset())
}
#[inline]
fn is_in_subset(t: &Transform<T2, C, D>) -> bool {
<Self as SubsetOf<_>>::is_in_subset(t.matrix())
}
#[inline]
fn from_superset_unchecked(t: &Transform<T2, C, D>) -> Self {
Self::from_superset_unchecked(t.matrix())
}
}
impl<T1, T2, R, const D: usize>
SubsetOf<OMatrix<T2, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>>
for Similarity<T1, R, D>
where
T1: RealField,
T2: RealField + SupersetOf<T1>,
R: AbstractRotation<T1, D>
+ SubsetOf<OMatrix<T1, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>>
+ SubsetOf<OMatrix<T2, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>>,
Const<D>: DimNameAdd<U1> + DimMin<Const<D>, Output = Const<D>>, // needed by .determinant()
DefaultAllocator: Allocator<T1, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>
+ Allocator<T2, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>
+ Allocator<T2, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>, // + Allocator<(usize, usize), D>
// + Allocator<T1, D>
// + Allocator<T1, D, D>
// + Allocator<T2, D, D>
// + Allocator<T2, D>
{
#[inline]
fn to_superset(&self) -> OMatrix<T2, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>> {
self.to_homogeneous().to_superset()
}
#[inline]
fn is_in_subset(m: &OMatrix<T2, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>) -> bool {
let mut rot = m.fixed_slice::<D, D>(0, 0).clone_owned();
if rot
.fixed_columns_mut::<1>(0)
.try_normalize_mut(T2::zero())
.is_some()
&& rot
.fixed_columns_mut::<1>(1)
.try_normalize_mut(T2::zero())
.is_some()
&& rot
.fixed_columns_mut::<1>(2)
.try_normalize_mut(T2::zero())
.is_some()
{
// TODO: could we avoid explicit the computation of the determinant?
// (its sign is needed to see if the scaling factor is negative).
if rot.determinant() < T2::zero() {
rot.fixed_columns_mut::<1>(0).neg_mut();
rot.fixed_columns_mut::<1>(1).neg_mut();
rot.fixed_columns_mut::<1>(2).neg_mut();
}
let bottom = m.fixed_slice::<1, D>(D, 0);
// Scalar types agree.
m.iter().all(|e| SupersetOf::<T1>::is_in_subset(e)) &&
// The normalized block part is a rotation.
// rot.is_special_orthogonal(T2::default_epsilon().sqrt()) &&
// The bottom row is (0, 0, ..., 1)
bottom.iter().all(|e| e.is_zero()) && m[(D, D)] == T2::one()
} else {
false
}
}
#[inline]
fn from_superset_unchecked(
m: &OMatrix<T2, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>,
) -> Self {
let mut mm = m.clone_owned();
let na = mm.fixed_slice_mut::<D, 1>(0, 0).normalize_mut();
let nb = mm.fixed_slice_mut::<D, 1>(0, 1).normalize_mut();
let nc = mm.fixed_slice_mut::<D, 1>(0, 2).normalize_mut();
let mut scale = (na + nb + nc) / crate::convert(3.0); // We take the mean, for robustness.
// TODO: could we avoid the explicit computation of the determinant?
// (its sign is needed to see if the scaling factor is negative).
if mm.fixed_slice::<D, D>(0, 0).determinant() < T2::zero() {
mm.fixed_slice_mut::<D, 1>(0, 0).neg_mut();
mm.fixed_slice_mut::<D, 1>(0, 1).neg_mut();
mm.fixed_slice_mut::<D, 1>(0, 2).neg_mut();
scale = -scale;
}
let t = m.fixed_slice::<D, 1>(0, D).into_owned();
let t = Translation {
vector: crate::convert_unchecked(t),
};
Self::from_parts(
t,
crate::convert_unchecked(mm),
crate::convert_unchecked(scale),
)
}
}
impl<T: SimdRealField, R, const D: usize> From<Similarity<T, R, D>>
for OMatrix<T, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>
where
Const<D>: DimNameAdd<U1>,
R: SubsetOf<OMatrix<T, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>>,
DefaultAllocator: Allocator<T, DimNameSum<Const<D>, U1>, DimNameSum<Const<D>, U1>>, // + Allocator<T, D>
{
#[inline]
fn from(sim: Similarity<T, R, D>) -> Self {
sim.to_homogeneous()
}
}
impl<T: Scalar + Zero + PrimitiveSimdValue, R, const D: usize>
From<[Similarity<T::Element, R::Element, D>; 2]> for Similarity<T, R, D>
where
T: From<[<T as SimdValue>::Element; 2]>,
R: SimdValue + AbstractRotation<T, D> + From<[<R as SimdValue>::Element; 2]>,
R::Element: AbstractRotation<T::Element, D>,
T::Element: Scalar + Zero + Copy,
R::Element: Scalar + Zero + Copy,
{
#[inline]
fn from(arr: [Similarity<T::Element, R::Element, D>; 2]) -> Self {
let iso = Isometry::from([arr[0].isometry, arr[1].isometry]);
let scale = T::from([arr[0].scaling(), arr[1].scaling()]);
Self::from_isometry(iso, scale)
}
}
impl<T: Scalar + Zero + PrimitiveSimdValue, R, const D: usize>
From<[Similarity<T::Element, R::Element, D>; 4]> for Similarity<T, R, D>
where
T: From<[<T as SimdValue>::Element; 4]>,
R: SimdValue + AbstractRotation<T, D> + From<[<R as SimdValue>::Element; 4]>,
R::Element: AbstractRotation<T::Element, D>,
T::Element: Scalar + Zero + Copy,
R::Element: Scalar + Zero + Copy,
{
#[inline]
fn from(arr: [Similarity<T::Element, R::Element, D>; 4]) -> Self {
let iso = Isometry::from([
arr[0].isometry,
arr[1].isometry,
arr[2].isometry,
arr[3].isometry,
]);
let scale = T::from([
arr[0].scaling(),
arr[1].scaling(),
arr[2].scaling(),
arr[3].scaling(),
]);
Self::from_isometry(iso, scale)
}
}
impl<T: Scalar + Zero + PrimitiveSimdValue, R, const D: usize>
From<[Similarity<T::Element, R::Element, D>; 8]> for Similarity<T, R, D>
where
T: From<[<T as SimdValue>::Element; 8]>,
R: SimdValue + AbstractRotation<T, D> + From<[<R as SimdValue>::Element; 8]>,
R::Element: AbstractRotation<T::Element, D>,
T::Element: Scalar + Zero + Copy,
R::Element: Scalar + Zero + Copy,
{
#[inline]
fn from(arr: [Similarity<T::Element, R::Element, D>; 8]) -> Self {
let iso = Isometry::from([
arr[0].isometry,
arr[1].isometry,
arr[2].isometry,
arr[3].isometry,
arr[4].isometry,
arr[5].isometry,
arr[6].isometry,
arr[7].isometry,
]);
let scale = T::from([
arr[0].scaling(),
arr[1].scaling(),
arr[2].scaling(),
arr[3].scaling(),
arr[4].scaling(),
arr[5].scaling(),
arr[6].scaling(),
arr[7].scaling(),
]);
Self::from_isometry(iso, scale)
}
}
impl<T: Scalar + Zero + PrimitiveSimdValue, R, const D: usize>
From<[Similarity<T::Element, R::Element, D>; 16]> for Similarity<T, R, D>
where
T: From<[<T as SimdValue>::Element; 16]>,
R: SimdValue + AbstractRotation<T, D> + From<[<R as SimdValue>::Element; 16]>,
R::Element: AbstractRotation<T::Element, D>,
T::Element: Scalar + Zero + Copy,
R::Element: Scalar + Zero + Copy,
{
#[inline]
fn from(arr: [Similarity<T::Element, R::Element, D>; 16]) -> Self {
let iso = Isometry::from([
arr[0].isometry,
arr[1].isometry,
arr[2].isometry,
arr[3].isometry,
arr[4].isometry,
arr[5].isometry,
arr[6].isometry,
arr[7].isometry,
arr[8].isometry,
arr[9].isometry,
arr[10].isometry,
arr[11].isometry,
arr[12].isometry,
arr[13].isometry,
arr[14].isometry,
arr[15].isometry,
]);
let scale = T::from([
arr[0].scaling(),
arr[1].scaling(),
arr[2].scaling(),
arr[3].scaling(),
arr[4].scaling(),
arr[5].scaling(),
arr[6].scaling(),
arr[7].scaling(),
arr[8].scaling(),
arr[9].scaling(),
arr[10].scaling(),
arr[11].scaling(),
arr[12].scaling(),
arr[13].scaling(),
arr[14].scaling(),
arr[15].scaling(),
]);
Self::from_isometry(iso, scale)
}
}
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