nalgebra/src/linalg/inverse.rs
2017-08-15 19:07:18 +02:00

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use alga::general::Real;
use core::{DefaultAllocator, SquareMatrix, MatrixN};
use core::dimension::Dim;
use core::storage::{Storage, StorageMut};
use core::allocator::Allocator;
use linalg::lu;
impl<N: Real, D: Dim, S: Storage<N, D, D>> SquareMatrix<N, D, S> {
/// Attempts to invert this matrix.
#[inline]
pub fn try_inverse(self) -> Option<MatrixN<N, D>>
where DefaultAllocator: Allocator<N, D, D> {
let mut me = self.into_owned();
if me.try_inverse_mut() {
Some(me)
}
else {
None
}
}
}
impl<N: Real, D: Dim, S: StorageMut<N, D, D>> SquareMatrix<N, D, S> {
/// Attempts to invert this matrix in-place. Returns `false` and leaves `self` untouched if
/// inversion fails.
#[inline]
pub fn try_inverse_mut(&mut self) -> bool
where DefaultAllocator: Allocator<N, D, D> {
assert!(self.is_square(), "Unable to invert a non-square matrix.");
let dim = self.shape().0;
unsafe {
match dim {
0 => true,
1 => {
let determinant = self.get_unchecked(0, 0).clone();
if determinant == N::zero() {
false
}
else {
*self.get_unchecked_mut(0, 0) = N::one() / determinant;
true
}
},
2 => {
let m11 = *self.get_unchecked(0, 0); let m12 = *self.get_unchecked(0, 1);
let m21 = *self.get_unchecked(1, 0); let m22 = *self.get_unchecked(1, 1);
let determinant = m11 * m22 - m21 * m12;
if determinant == N::zero() {
false
}
else {
*self.get_unchecked_mut(0, 0) = m22 / determinant;
*self.get_unchecked_mut(0, 1) = -m12 / determinant;
*self.get_unchecked_mut(1, 0) = -m21 / determinant;
*self.get_unchecked_mut(1, 1) = m11 / determinant;
true
}
},
3 => {
let m11 = *self.get_unchecked(0, 0);
let m12 = *self.get_unchecked(0, 1);
let m13 = *self.get_unchecked(0, 2);
let m21 = *self.get_unchecked(1, 0);
let m22 = *self.get_unchecked(1, 1);
let m23 = *self.get_unchecked(1, 2);
let m31 = *self.get_unchecked(2, 0);
let m32 = *self.get_unchecked(2, 1);
let m33 = *self.get_unchecked(2, 2);
let minor_m12_m23 = m22 * m33 - m32 * m23;
let minor_m11_m23 = m21 * m33 - m31 * m23;
let minor_m11_m22 = m21 * m32 - m31 * m22;
let determinant = m11 * minor_m12_m23 -
m12 * minor_m11_m23 +
m13 * minor_m11_m22;
if determinant == N::zero() {
false
}
else {
*self.get_unchecked_mut(0, 0) = minor_m12_m23 / determinant;
*self.get_unchecked_mut(0, 1) = (m13 * m32 - m33 * m12) / determinant;
*self.get_unchecked_mut(0, 2) = (m12 * m23 - m22 * m13) / determinant;
*self.get_unchecked_mut(1, 0) = -minor_m11_m23 / determinant;
*self.get_unchecked_mut(1, 1) = (m11 * m33 - m31 * m13) / determinant;
*self.get_unchecked_mut(1, 2) = (m13 * m21 - m23 * m11) / determinant;
*self.get_unchecked_mut(2, 0) = minor_m11_m22 / determinant;
*self.get_unchecked_mut(2, 1) = (m12 * m31 - m32 * m11) / determinant;
*self.get_unchecked_mut(2, 2) = (m11 * m22 - m21 * m12) / determinant;
true
}
},
4=> {
let oself = self.clone_owned();
do_inverse4(&oself, self)
}
_ => {
let oself = self.clone_owned();
lu::try_invert_to(oself, self)
}
}
}
}
}
// NOTE: this is an extremely efficient, loop-unrolled matrix inverse from MESA (MIT licenced).
fn do_inverse4<N: Real, D: Dim, S: StorageMut<N, D, D>>(m: &MatrixN<N, D>, out: &mut SquareMatrix<N, D, S>) -> bool
where DefaultAllocator: Allocator<N, D, D> {
let m = m.data.as_slice();
out[(0, 0)] = m[5] * m[10] * m[15] -
m[5] * m[11] * m[14] -
m[9] * m[6] * m[15] +
m[9] * m[7] * m[14] +
m[13] * m[6] * m[11] -
m[13] * m[7] * m[10];
out[(1, 0)] = -m[1] * m[10] * m[15] +
m[1] * m[11] * m[14] +
m[9] * m[2] * m[15] -
m[9] * m[3] * m[14] -
m[13] * m[2] * m[11] +
m[13] * m[3] * m[10];
out[(2, 0)] = m[1] * m[6] * m[15] -
m[1] * m[7] * m[14] -
m[5] * m[2] * m[15] +
m[5] * m[3] * m[14] +
m[13] * m[2] * m[7] -
m[13] * m[3] * m[6];
out[(3, 0)] = -m[1] * m[6] * m[11] +
m[1] * m[7] * m[10] +
m[5] * m[2] * m[11] -
m[5] * m[3] * m[10] -
m[9] * m[2] * m[7] +
m[9] * m[3] * m[6];
out[(0, 1)] = -m[4] * m[10] * m[15] +
m[4] * m[11] * m[14] +
m[8] * m[6] * m[15] -
m[8] * m[7] * m[14] -
m[12] * m[6] * m[11] +
m[12] * m[7] * m[10];
out[(1, 1)] = m[0] * m[10] * m[15] -
m[0] * m[11] * m[14] -
m[8] * m[2] * m[15] +
m[8] * m[3] * m[14] +
m[12] * m[2] * m[11] -
m[12] * m[3] * m[10];
out[(2, 1)] = -m[0] * m[6] * m[15] +
m[0] * m[7] * m[14] +
m[4] * m[2] * m[15] -
m[4] * m[3] * m[14] -
m[12] * m[2] * m[7] +
m[12] * m[3] * m[6];
out[(3, 1)] = m[0] * m[6] * m[11] -
m[0] * m[7] * m[10] -
m[4] * m[2] * m[11] +
m[4] * m[3] * m[10] +
m[8] * m[2] * m[7] -
m[8] * m[3] * m[6];
out[(0, 2)] = m[4] * m[9] * m[15] -
m[4] * m[11] * m[13] -
m[8] * m[5] * m[15] +
m[8] * m[7] * m[13] +
m[12] * m[5] * m[11] -
m[12] * m[7] * m[9];
out[(1, 2)] = -m[0] * m[9] * m[15] +
m[0] * m[11] * m[13] +
m[8] * m[1] * m[15] -
m[8] * m[3] * m[13] -
m[12] * m[1] * m[11] +
m[12] * m[3] * m[9];
out[(2, 2)] = m[0] * m[5] * m[15] -
m[0] * m[7] * m[13] -
m[4] * m[1] * m[15] +
m[4] * m[3] * m[13] +
m[12] * m[1] * m[7] -
m[12] * m[3] * m[5];
out[(0, 3)] = -m[4] * m[9] * m[14] +
m[4] * m[10] * m[13] +
m[8] * m[5] * m[14] -
m[8] * m[6] * m[13] -
m[12] * m[5] * m[10] +
m[12] * m[6] * m[9];
out[(3, 2)] = -m[0] * m[5] * m[11] +
m[0] * m[7] * m[9] +
m[4] * m[1] * m[11] -
m[4] * m[3] * m[9] -
m[8] * m[1] * m[7] +
m[8] * m[3] * m[5];
out[(1, 3)] = m[0] * m[9] * m[14] -
m[0] * m[10] * m[13] -
m[8] * m[1] * m[14] +
m[8] * m[2] * m[13] +
m[12] * m[1] * m[10] -
m[12] * m[2] * m[9];
out[(2, 3)] = -m[0] * m[5] * m[14] +
m[0] * m[6] * m[13] +
m[4] * m[1] * m[14] -
m[4] * m[2] * m[13] -
m[12] * m[1] * m[6] +
m[12] * m[2] * m[5];
out[(3, 3)] = m[0] * m[5] * m[10] -
m[0] * m[6] * m[9] -
m[4] * m[1] * m[10] +
m[4] * m[2] * m[9] +
m[8] * m[1] * m[6] -
m[8] * m[2] * m[5];
let det = m[0] * out[(0, 0)] + m[1] * out[(0, 1)] + m[2] * out[(0, 2)] + m[3] * out[(0, 3)];
if !det.is_zero() {
let inv_det = N::one() / det;
for j in 0 .. 4 {
for i in 0 .. 4 {
out[(i, j)] *= inv_det;
}
}
true
}
else {
false
}
}