Reorganized files.

This commit is contained in:
Sébastien Crozet 2013-06-29 00:34:45 +00:00
parent c54eb562ec
commit c58e1ed40d
12 changed files with 984 additions and 1411 deletions

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@ -7,7 +7,7 @@ use traits::inv::Inv;
use traits::division_ring::DivisionRing; use traits::division_ring::DivisionRing;
use traits::transpose::Transpose; use traits::transpose::Transpose;
use traits::rlmul::{RMul, LMul}; use traits::rlmul::{RMul, LMul};
use ndim::dvec::{DVec, zero_vec_with_dim}; use dvec::{DVec, zero_vec_with_dim};
#[deriving(Eq, ToStr, Clone)] #[deriving(Eq, ToStr, Clone)]
pub struct DMat<N> pub struct DMat<N>
@ -133,13 +133,13 @@ LMul<DVec<N>> for DMat<N>
} }
} }
impl<N: Clone + Copy + Eq + DivisionRing> impl<N: Copy + Eq + DivisionRing>
Inv for DMat<N> Inv for DMat<N>
{ {
#[inline] #[inline]
fn inverse(&self) -> DMat<N> fn inverse(&self) -> DMat<N>
{ {
let mut res : DMat<N> = self.clone(); let mut res : DMat<N> = copy *self;
res.invert(); res.invert();

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@ -13,330 +13,7 @@ use traits::transpose::Transpose;
use traits::rlmul::{RMul, LMul}; use traits::rlmul::{RMul, LMul};
use traits::transformation::Transform; use traits::transformation::Transform;
macro_rules! mat_impl( mod mat_impl;
($t: ident, $dim: expr) => (
impl<N> $t<N>
{
#[inline]
pub fn new(mij: [N, ..$dim * $dim]) -> $t<N>
{ $t { mij: mij } }
}
)
)
macro_rules! one_impl(
($t: ident, [ $($value: ident)|+ ] ) => (
impl<N: Copy + One + Zero> One for $t<N>
{
#[inline]
fn one() -> $t<N>
{
let (_0, _1) = (Zero::zero::<N>(), One::one::<N>());
return $t::new( [ $( copy $value, )+ ] )
}
}
)
)
macro_rules! zero_impl(
($t: ident, [ $($value: ident)|+ ] ) => (
impl<N: Copy + Zero> Zero for $t<N>
{
#[inline]
fn zero() -> $t<N>
{
let _0 = Zero::zero();
return $t::new( [ $( copy $value, )+ ] )
}
#[inline]
fn is_zero(&self) -> bool
{ self.mij.iter().all(|e| e.is_zero()) }
}
)
)
macro_rules! dim_impl(
($t: ident, $dim: expr) => (
impl<N> Dim for $t<N>
{
#[inline]
fn dim() -> uint
{ $dim }
}
)
)
macro_rules! mat_indexing_impl(
($t: ident, $dim: expr) => (
impl<N: Copy> $t<N>
{
#[inline]
pub fn offset(&self, i: uint, j: uint) -> uint
{ i * $dim + j }
#[inline]
pub fn set(&mut self, i: uint, j: uint, t: &N)
{
self.mij[self.offset(i, j)] = copy *t
}
#[inline]
pub fn at(&self, i: uint, j: uint) -> N
{
copy self.mij[self.offset(i, j)]
}
}
)
)
macro_rules! mul_impl(
($t: ident, $dim: expr) => (
impl<N: Copy + Ring>
Mul<$t<N>, $t<N>> for $t<N>
{
fn mul(&self, other: &$t<N>) -> $t<N>
{
let mut res: $t<N> = Zero::zero();
for iterate(0u, $dim) |i|
{
for iterate(0u, $dim) |j|
{
let mut acc = Zero::zero::<N>();
for iterate(0u, $dim) |k|
{ acc = acc + self.at(i, k) * other.at(k, j); }
res.set(i, j, &acc);
}
}
res
}
}
)
)
macro_rules! rmul_impl(
($t: ident, $v: ident, $dim: expr) => (
impl<N: Copy + Ring>
RMul<$v<N>> for $t<N>
{
fn rmul(&self, other: &$v<N>) -> $v<N>
{
let mut res : $v<N> = Zero::zero();
for iterate(0u, $dim) |i|
{
for iterate(0u, $dim) |j|
{ res.at[i] = res.at[i] + other.at[j] * self.at(i, j); }
}
res
}
}
)
)
macro_rules! lmul_impl(
($t: ident, $v: ident, $dim: expr) => (
impl<N: Copy + Ring>
LMul<$v<N>> for $t<N>
{
fn lmul(&self, other: &$v<N>) -> $v<N>
{
let mut res : $v<N> = Zero::zero();
for iterate(0u, $dim) |i|
{
for iterate(0u, $dim) |j|
{ res.at[i] = res.at[i] + other.at[j] * self.at(j, i); }
}
res
}
}
)
)
macro_rules! transform_impl(
($t: ident, $v: ident) => (
impl<N: Copy + DivisionRing + Eq>
Transform<$v<N>> for $t<N>
{
#[inline]
fn transform_vec(&self, v: &$v<N>) -> $v<N>
{ self.rmul(v) }
#[inline]
fn inv_transform(&self, v: &$v<N>) -> $v<N>
{ self.inverse().transform_vec(v) }
}
)
)
macro_rules! inv_impl(
($t: ident, $dim: expr) => (
impl<N: Copy + Eq + DivisionRing>
Inv for $t<N>
{
#[inline]
fn inverse(&self) -> $t<N>
{
let mut res : $t<N> = copy *self;
res.invert();
res
}
fn invert(&mut self)
{
let mut res: $t<N> = One::one();
let _0N: N = Zero::zero();
// inversion using Gauss-Jordan elimination
for iterate(0u, $dim) |k|
{
// search a non-zero value on the k-th column
// FIXME: would it be worth it to spend some more time searching for the
// max instead?
let mut n0 = k; // index of a non-zero entry
while (n0 != $dim)
{
if self.at(n0, k) != _0N
{ break; }
n0 = n0 + 1;
}
// swap pivot line
if n0 != k
{
for iterate(0u, $dim) |j|
{
let off_n0_j = self.offset(n0, j);
let off_k_j = self.offset(k, j);
swap(self.mij, off_n0_j, off_k_j);
swap(res.mij, off_n0_j, off_k_j);
}
}
let pivot = self.at(k, k);
for iterate(k, $dim) |j|
{
let selfval = &(self.at(k, j) / pivot);
self.set(k, j, selfval);
}
for iterate(0u, $dim) |j|
{
let resval = &(res.at(k, j) / pivot);
res.set(k, j, resval);
}
for iterate(0u, $dim) |l|
{
if l != k
{
let normalizer = self.at(l, k);
for iterate(k, $dim) |j|
{
let selfval = &(self.at(l, j) - self.at(k, j) * normalizer);
self.set(l, j, selfval);
}
for iterate(0u, $dim) |j|
{
let resval = &(res.at(l, j) - res.at(k, j) * normalizer);
res.set(l, j, resval);
}
}
}
}
*self = res;
}
}
)
)
macro_rules! transpose_impl(
($t: ident, $dim: expr) => (
impl<N: Copy> Transpose for $t<N>
{
#[inline]
fn transposed(&self) -> $t<N>
{
let mut res = copy *self;
res.transpose();
res
}
fn transpose(&mut self)
{
for iterate(1u, $dim) |i|
{
for iterate(0u, $dim - 1) |j|
{
let off_i_j = self.offset(i, j);
let off_j_i = self.offset(j, i);
swap(self.mij, off_i_j, off_j_i);
}
}
}
}
)
)
macro_rules! approx_eq_impl(
($t: ident) => (
impl<N: ApproxEq<N>> ApproxEq<N> for $t<N>
{
#[inline]
fn approx_epsilon() -> N
{ ApproxEq::approx_epsilon::<N, N>() }
#[inline]
fn approx_eq(&self, other: &$t<N>) -> bool
{
let mut zip = self.mij.iter().zip(other.mij.iter());
do zip.all |(a, b)| { a.approx_eq(b) }
}
#[inline]
fn approx_eq_eps(&self, other: &$t<N>, epsilon: &N) -> bool
{
let mut zip = self.mij.iter().zip(other.mij.iter());
do zip.all |(a, b)| { a.approx_eq_eps(b, epsilon) }
}
}
)
)
macro_rules! rand_impl(
($t: ident, $param: ident, [ $($elem: ident)|+ ]) => (
impl<N: Rand> Rand for $t<N>
{
#[inline]
fn rand<R: Rng>($param: &mut R) -> $t<N>
{ $t::new([ $( $elem.gen(), )+ ]) }
}
)
)
#[deriving(ToStr)] #[deriving(ToStr)]
pub struct Mat1<N> pub struct Mat1<N>
@ -508,93 +185,3 @@ rand_impl!(Mat6, rng, [
rng | rng | rng | rng | rng | rng | rng | rng | rng | rng | rng | rng |
rng | rng | rng | rng | rng | rng rng | rng | rng | rng | rng | rng
]) ])
// some specializations:
impl<N: Copy + DivisionRing>
Inv for Mat1<N>
{
#[inline]
fn inverse(&self) -> Mat1<N>
{
let mut res : Mat1<N> = copy *self;
res.invert();
res
}
#[inline]
fn invert(&mut self)
{
assert!(!self.mij[0].is_zero());
self.mij[0] = One::one::<N>() / self.mij[0]
}
}
impl<N: Copy + DivisionRing>
Inv for Mat2<N>
{
#[inline]
fn inverse(&self) -> Mat2<N>
{
let mut res : Mat2<N> = copy *self;
res.invert();
res
}
#[inline]
fn invert(&mut self)
{
let det = self.mij[0 * 2 + 0] * self.mij[1 * 2 + 1] - self.mij[1 * 2 + 0] * self.mij[0 * 2 + 1];
assert!(!det.is_zero());
*self = Mat2::new([self.mij[1 * 2 + 1] / det , -self.mij[0 * 2 + 1] / det,
-self.mij[1 * 2 + 0] / det, self.mij[0 * 2 + 0] / det])
}
}
impl<N: Copy + DivisionRing>
Inv for Mat3<N>
{
#[inline]
fn inverse(&self) -> Mat3<N>
{
let mut res = copy *self;
res.invert();
res
}
#[inline]
fn invert(&mut self)
{
let minor_m12_m23 = self.mij[1 * 3 + 1] * self.mij[2 * 3 + 2] - self.mij[2 * 3 + 1] * self.mij[1 * 3 + 2];
let minor_m11_m23 = self.mij[1 * 3 + 0] * self.mij[2 * 3 + 2] - self.mij[2 * 3 + 0] * self.mij[1 * 3 + 2];
let minor_m11_m22 = self.mij[1 * 3 + 0] * self.mij[2 * 3 + 1] - self.mij[2 * 3 + 0] * self.mij[1 * 3 + 1];
let det = self.mij[0 * 3 + 0] * minor_m12_m23
- self.mij[0 * 3 + 1] * minor_m11_m23
+ self.mij[0 * 3 + 2] * minor_m11_m22;
assert!(!det.is_zero());
*self = Mat3::new( [
(minor_m12_m23 / det),
((self.mij[0 * 3 + 2] * self.mij[2 * 3 + 1] - self.mij[2 * 3 + 2] * self.mij[0 * 3 + 1]) / det),
((self.mij[0 * 3 + 1] * self.mij[1 * 3 + 2] - self.mij[1 * 3 + 1] * self.mij[0 * 3 + 2]) / det),
(-minor_m11_m23 / det),
((self.mij[0 * 3 + 0] * self.mij[2 * 3 + 2] - self.mij[2 * 3 + 0] * self.mij[0 * 3 + 2]) / det),
((self.mij[0 * 3 + 2] * self.mij[1 * 3 + 0] - self.mij[1 * 3 + 2] * self.mij[0 * 3 + 0]) / det),
(minor_m11_m22 / det),
((self.mij[0 * 3 + 1] * self.mij[2 * 3 + 0] - self.mij[2 * 3 + 1] * self.mij[0 * 3 + 0]) / det),
((self.mij[0 * 3 + 0] * self.mij[1 * 3 + 1] - self.mij[1 * 3 + 0] * self.mij[0 * 3 + 1]) / det)
] )
}
}

325
src/mat_impl.rs Normal file
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@ -0,0 +1,325 @@
#[macro_escape];
macro_rules! mat_impl(
($t: ident, $dim: expr) => (
impl<N> $t<N>
{
#[inline]
pub fn new(mij: [N, ..$dim * $dim]) -> $t<N>
{ $t { mij: mij } }
}
)
)
macro_rules! one_impl(
($t: ident, [ $($value: ident)|+ ] ) => (
impl<N: Copy + One + Zero> One for $t<N>
{
#[inline]
fn one() -> $t<N>
{
let (_0, _1) = (Zero::zero::<N>(), One::one::<N>());
return $t::new( [ $( copy $value, )+ ] )
}
}
)
)
macro_rules! zero_impl(
($t: ident, [ $($value: ident)|+ ] ) => (
impl<N: Copy + Zero> Zero for $t<N>
{
#[inline]
fn zero() -> $t<N>
{
let _0 = Zero::zero();
return $t::new( [ $( copy $value, )+ ] )
}
#[inline]
fn is_zero(&self) -> bool
{ self.mij.iter().all(|e| e.is_zero()) }
}
)
)
macro_rules! dim_impl(
($t: ident, $dim: expr) => (
impl<N> Dim for $t<N>
{
#[inline]
fn dim() -> uint
{ $dim }
}
)
)
macro_rules! mat_indexing_impl(
($t: ident, $dim: expr) => (
impl<N: Copy> $t<N>
{
#[inline]
pub fn offset(&self, i: uint, j: uint) -> uint
{ i * $dim + j }
#[inline]
pub fn set(&mut self, i: uint, j: uint, t: &N)
{
self.mij[self.offset(i, j)] = copy *t
}
#[inline]
pub fn at(&self, i: uint, j: uint) -> N
{
copy self.mij[self.offset(i, j)]
}
}
)
)
macro_rules! mul_impl(
($t: ident, $dim: expr) => (
impl<N: Copy + Ring>
Mul<$t<N>, $t<N>> for $t<N>
{
fn mul(&self, other: &$t<N>) -> $t<N>
{
let mut res: $t<N> = Zero::zero();
for iterate(0u, $dim) |i|
{
for iterate(0u, $dim) |j|
{
let mut acc = Zero::zero::<N>();
for iterate(0u, $dim) |k|
{ acc = acc + self.at(i, k) * other.at(k, j); }
res.set(i, j, &acc);
}
}
res
}
}
)
)
macro_rules! rmul_impl(
($t: ident, $v: ident, $dim: expr) => (
impl<N: Copy + Ring>
RMul<$v<N>> for $t<N>
{
fn rmul(&self, other: &$v<N>) -> $v<N>
{
let mut res : $v<N> = Zero::zero();
for iterate(0u, $dim) |i|
{
for iterate(0u, $dim) |j|
{ res.at[i] = res.at[i] + other.at[j] * self.at(i, j); }
}
res
}
}
)
)
macro_rules! lmul_impl(
($t: ident, $v: ident, $dim: expr) => (
impl<N: Copy + Ring>
LMul<$v<N>> for $t<N>
{
fn lmul(&self, other: &$v<N>) -> $v<N>
{
let mut res : $v<N> = Zero::zero();
for iterate(0u, $dim) |i|
{
for iterate(0u, $dim) |j|
{ res.at[i] = res.at[i] + other.at[j] * self.at(j, i); }
}
res
}
}
)
)
macro_rules! transform_impl(
($t: ident, $v: ident) => (
impl<N: Copy + DivisionRing + Eq>
Transform<$v<N>> for $t<N>
{
#[inline]
fn transform_vec(&self, v: &$v<N>) -> $v<N>
{ self.rmul(v) }
#[inline]
fn inv_transform(&self, v: &$v<N>) -> $v<N>
{ self.inverse().transform_vec(v) }
}
)
)
macro_rules! inv_impl(
($t: ident, $dim: expr) => (
impl<N: Copy + Eq + DivisionRing>
Inv for $t<N>
{
#[inline]
fn inverse(&self) -> $t<N>
{
let mut res : $t<N> = copy *self;
res.invert();
res
}
fn invert(&mut self)
{
let mut res: $t<N> = One::one();
let _0N: N = Zero::zero();
// inversion using Gauss-Jordan elimination
for iterate(0u, $dim) |k|
{
// search a non-zero value on the k-th column
// FIXME: would it be worth it to spend some more time searching for the
// max instead?
let mut n0 = k; // index of a non-zero entry
while (n0 != $dim)
{
if self.at(n0, k) != _0N
{ break; }
n0 = n0 + 1;
}
// swap pivot line
if n0 != k
{
for iterate(0u, $dim) |j|
{
let off_n0_j = self.offset(n0, j);
let off_k_j = self.offset(k, j);
swap(self.mij, off_n0_j, off_k_j);
swap(res.mij, off_n0_j, off_k_j);
}
}
let pivot = self.at(k, k);
for iterate(k, $dim) |j|
{
let selfval = &(self.at(k, j) / pivot);
self.set(k, j, selfval);
}
for iterate(0u, $dim) |j|
{
let resval = &(res.at(k, j) / pivot);
res.set(k, j, resval);
}
for iterate(0u, $dim) |l|
{
if l != k
{
let normalizer = self.at(l, k);
for iterate(k, $dim) |j|
{
let selfval = &(self.at(l, j) - self.at(k, j) * normalizer);
self.set(l, j, selfval);
}
for iterate(0u, $dim) |j|
{
let resval = &(res.at(l, j) - res.at(k, j) * normalizer);
res.set(l, j, resval);
}
}
}
}
*self = res;
}
}
)
)
macro_rules! transpose_impl(
($t: ident, $dim: expr) => (
impl<N: Copy> Transpose for $t<N>
{
#[inline]
fn transposed(&self) -> $t<N>
{
let mut res = copy *self;
res.transpose();
res
}
fn transpose(&mut self)
{
for iterate(1u, $dim) |i|
{
for iterate(0u, $dim - 1) |j|
{
let off_i_j = self.offset(i, j);
let off_j_i = self.offset(j, i);
swap(self.mij, off_i_j, off_j_i);
}
}
}
}
)
)
macro_rules! approx_eq_impl(
($t: ident) => (
impl<N: ApproxEq<N>> ApproxEq<N> for $t<N>
{
#[inline]
fn approx_epsilon() -> N
{ ApproxEq::approx_epsilon::<N, N>() }
#[inline]
fn approx_eq(&self, other: &$t<N>) -> bool
{
let mut zip = self.mij.iter().zip(other.mij.iter());
do zip.all |(a, b)| { a.approx_eq(b) }
}
#[inline]
fn approx_eq_eps(&self, other: &$t<N>, epsilon: &N) -> bool
{
let mut zip = self.mij.iter().zip(other.mij.iter());
do zip.all |(a, b)| { a.approx_eq_eps(b, epsilon) }
}
}
)
)
macro_rules! rand_impl(
($t: ident, $param: ident, [ $($elem: ident)|+ ]) => (
impl<N: Rand> Rand for $t<N>
{
#[inline]
fn rand<R: Rng>($param: &mut R) -> $t<N>
{ $t::new([ $( $elem.gen(), )+ ]) }
}
)
)

94
src/mat_spec.rs Normal file
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@ -0,0 +1,94 @@
use std::num::{Zero, One};
use mat::{Mat1, Mat2, Mat3};
use traits::division_ring::DivisionRing;
use traits::inv::Inv;
// some specializations:
impl<N: Copy + DivisionRing>
Inv for Mat1<N>
{
#[inline]
fn inverse(&self) -> Mat1<N>
{
let mut res : Mat1<N> = copy *self;
res.invert();
res
}
#[inline]
fn invert(&mut self)
{
assert!(!self.mij[0].is_zero());
self.mij[0] = One::one::<N>() / self.mij[0]
}
}
impl<N: Copy + DivisionRing>
Inv for Mat2<N>
{
#[inline]
fn inverse(&self) -> Mat2<N>
{
let mut res : Mat2<N> = copy *self;
res.invert();
res
}
#[inline]
fn invert(&mut self)
{
let det = self.mij[0 * 2 + 0] * self.mij[1 * 2 + 1] - self.mij[1 * 2 + 0] * self.mij[0 * 2 + 1];
assert!(!det.is_zero());
*self = Mat2::new([self.mij[1 * 2 + 1] / det , -self.mij[0 * 2 + 1] / det,
-self.mij[1 * 2 + 0] / det, self.mij[0 * 2 + 0] / det])
}
}
impl<N: Copy + DivisionRing>
Inv for Mat3<N>
{
#[inline]
fn inverse(&self) -> Mat3<N>
{
let mut res = copy *self;
res.invert();
res
}
#[inline]
fn invert(&mut self)
{
let minor_m12_m23 = self.mij[1 * 3 + 1] * self.mij[2 * 3 + 2] - self.mij[2 * 3 + 1] * self.mij[1 * 3 + 2];
let minor_m11_m23 = self.mij[1 * 3 + 0] * self.mij[2 * 3 + 2] - self.mij[2 * 3 + 0] * self.mij[1 * 3 + 2];
let minor_m11_m22 = self.mij[1 * 3 + 0] * self.mij[2 * 3 + 1] - self.mij[2 * 3 + 0] * self.mij[1 * 3 + 1];
let det = self.mij[0 * 3 + 0] * minor_m12_m23
- self.mij[0 * 3 + 1] * minor_m11_m23
+ self.mij[0 * 3 + 2] * minor_m11_m22;
assert!(!det.is_zero());
*self = Mat3::new( [
(minor_m12_m23 / det),
((self.mij[0 * 3 + 2] * self.mij[2 * 3 + 1] - self.mij[2 * 3 + 2] * self.mij[0 * 3 + 1]) / det),
((self.mij[0 * 3 + 1] * self.mij[1 * 3 + 2] - self.mij[1 * 3 + 1] * self.mij[0 * 3 + 2]) / det),
(-minor_m11_m23 / det),
((self.mij[0 * 3 + 0] * self.mij[2 * 3 + 2] - self.mij[2 * 3 + 0] * self.mij[0 * 3 + 2]) / det),
((self.mij[0 * 3 + 2] * self.mij[1 * 3 + 0] - self.mij[1 * 3 + 2] * self.mij[0 * 3 + 0]) / det),
(minor_m11_m22 / det),
((self.mij[0 * 3 + 1] * self.mij[2 * 3 + 0] - self.mij[2 * 3 + 1] * self.mij[0 * 3 + 0]) / det),
((self.mij[0 * 3 + 0] * self.mij[1 * 3 + 1] - self.mij[1 * 3 + 0] * self.mij[0 * 3 + 1]) / det)
] )
}
}

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@ -17,15 +17,12 @@ extern mod std;
pub mod vec; pub mod vec;
pub mod mat; pub mod mat;
pub mod dmat;
pub mod dvec;
/// n-dimensional linear algebra (slower). // specialization for some 1d, 2d and 3d operations
pub mod ndim pub mod mat_spec;
{ pub mod vec_spec;
pub mod dmat;
pub mod dvec;
pub mod nvec;
pub mod nmat;
}
/// Wrappers around raw matrices to restrict their behaviour. /// Wrappers around raw matrices to restrict their behaviour.
pub mod adaptors pub mod adaptors

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@ -1,184 +0,0 @@
use std::uint::iterate;
use std::num::{One, Zero};
use std::rand::{Rand, Rng, RngUtil};
use std::cmp::ApproxEq;
use traits::dim::Dim;
use traits::inv::Inv;
use traits::division_ring::DivisionRing;
use traits::transpose::Transpose;
use traits::rlmul::{RMul, LMul};
use ndim::dmat::{DMat, one_mat_with_dim, zero_mat_with_dim, is_zero_mat};
use ndim::nvec::NVec;
// D is a phantom type parameter, used only as a dimensional token.
// Its allows use to encode the vector dimension at the type-level.
// It can be anything implementing the Dim trait. However, to avoid confusion,
// using d0, d1, d2, d3 and d4 tokens are prefered.
#[deriving(Eq, ToStr)]
pub struct NMat<D, N>
{ mij: DMat<N> }
impl<D: Dim, N: Copy> NMat<D, N>
{
#[inline]
fn offset(i: uint, j: uint) -> uint
{ i * Dim::dim::<D>() + j }
#[inline]
fn set(&mut self, i: uint, j: uint, t: &N)
{ self.mij.set(i, j, t) }
}
impl<D: Dim, N> Dim for NMat<D, N>
{
#[inline]
fn dim() -> uint
{ Dim::dim::<D>() }
}
impl<D: Dim, N: Copy> Index<(uint, uint), N> for NMat<D, N>
{
#[inline]
fn index(&self, &idx: &(uint, uint)) -> N
{ self.mij[idx] }
}
impl<D: Dim, N: Copy + One + Zero> One for NMat<D, N>
{
#[inline]
fn one() -> NMat<D, N>
{ NMat { mij: one_mat_with_dim(Dim::dim::<D>()) } }
}
impl<D: Dim, N: Copy + Zero> Zero for NMat<D, N>
{
#[inline]
fn zero() -> NMat<D, N>
{ NMat { mij: zero_mat_with_dim(Dim::dim::<D>()) } }
#[inline]
fn is_zero(&self) -> bool
{ is_zero_mat(&self.mij) }
}
impl<D: Dim, N: Copy + Mul<N, N> + Add<N, N> + Zero>
Mul<NMat<D, N>, NMat<D, N>> for NMat<D, N>
{
fn mul(&self, other: &NMat<D, N>) -> NMat<D, N>
{
let dim = Dim::dim::<D>();
let mut res = Zero::zero::<NMat<D, N>>();
for iterate(0u, dim) |i|
{
for iterate(0u, dim) |j|
{
let mut acc: N = Zero::zero();
for iterate(0u, dim) |k|
{ acc = acc + self[(i, k)] * other[(k, j)]; }
res.set(i, j, &acc);
}
}
res
}
}
impl<D: Dim, N: Copy + Add<N, N> + Mul<N, N> + Zero>
RMul<NVec<D, N>> for NMat<D, N>
{
fn rmul(&self, other: &NVec<D, N>) -> NVec<D, N>
{
let dim = Dim::dim::<D>();
let mut res : NVec<D, N> = Zero::zero();
for iterate(0u, dim) |i|
{
for iterate(0u, dim) |j|
{ res.at.at[i] = res.at.at[i] + other.at.at[j] * self[(i, j)]; }
}
res
}
}
impl<D: Dim, N: Copy + Add<N, N> + Mul<N, N> + Zero>
LMul<NVec<D, N>> for NMat<D, N>
{
fn lmul(&self, other: &NVec<D, N>) -> NVec<D, N>
{
let dim = Dim::dim::<D>();
let mut res : NVec<D, N> = Zero::zero();
for iterate(0u, dim) |i|
{
for iterate(0u, dim) |j|
{ res.at.at[i] = res.at.at[i] + other.at.at[j] * self[(j, i)]; }
}
res
}
}
impl<D: Dim, N: Clone + Copy + Eq + DivisionRing>
Inv for NMat<D, N>
{
#[inline]
fn inverse(&self) -> NMat<D, N>
{ NMat { mij: self.mij.inverse() } }
#[inline]
fn invert(&mut self)
{ self.mij.invert() }
}
impl<D: Dim, N:Copy> Transpose for NMat<D, N>
{
#[inline]
fn transposed(&self) -> NMat<D, N>
{
let mut res = copy *self;
res.transpose();
res
}
#[inline]
fn transpose(&mut self)
{ self.mij.transpose() }
}
impl<D, N: ApproxEq<N>> ApproxEq<N> for NMat<D, N>
{
#[inline]
fn approx_epsilon() -> N
{ ApproxEq::approx_epsilon::<N, N>() }
#[inline]
fn approx_eq(&self, other: &NMat<D, N>) -> bool
{ self.mij.approx_eq(&other.mij) }
#[inline]
fn approx_eq_eps(&self, other: &NMat<D, N>, epsilon: &N) -> bool
{ self.mij.approx_eq_eps(&other.mij, epsilon) }
}
impl<D: Dim, N: Rand + Zero + Copy> Rand for NMat<D, N>
{
fn rand<R: Rng>(rng: &mut R) -> NMat<D, N>
{
let dim = Dim::dim::<D>();
let mut res : NMat<D, N> = Zero::zero();
for iterate(0u, dim) |i|
{
for iterate(0u, dim) |j|
{ res.set(i, j, &rng.gen()); }
}
res
}
}

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@ -1,276 +0,0 @@
use std::uint::iterate;
use std::num::{Zero, Algebraic, Bounded};
use std::rand::{Rand, Rng, RngUtil};
use std::vec::{VecIterator, VecMutIterator};
use std::cmp::ApproxEq;
use std::iterator::{IteratorUtil, FromIterator};
use ndim::dvec::{DVec, zero_vec_with_dim, is_zero_vec};
use traits::iterable::{Iterable, IterableMut};
use traits::basis::Basis;
use traits::ring::Ring;
use traits::division_ring::DivisionRing;
use traits::dim::Dim;
use traits::dot::Dot;
use traits::sub_dot::SubDot;
use traits::norm::Norm;
use traits::translation::{Translation, Translatable};
use traits::scalar_op::{ScalarMul, ScalarDiv, ScalarAdd, ScalarSub};
// D is a phantom parameter, used only as a dimensional token.
// Its allows use to encode the vector dimension at the type-level.
// It can be anything implementing the Dim trait. However, to avoid confusion,
// using d0, d1, d2, d3, ..., d7 (or your own dn) are prefered.
#[deriving(Eq, Ord, ToStr)]
pub struct NVec<D, N>
{ at: DVec<N> }
impl<D: Dim, N> Dim for NVec<D, N>
{
#[inline]
fn dim() -> uint
{ Dim::dim::<D>() }
}
impl<D, N: Clone> Clone for NVec<D, N>
{
#[inline]
fn clone(&self) -> NVec<D, N>
{ NVec{ at: self.at.clone() } }
}
impl<D, N> Iterable<N> for NVec<D, N>
{
fn iter<'l>(&'l self) -> VecIterator<'l, N>
{ self.at.iter() }
}
impl<D, N> IterableMut<N> for NVec<D, N>
{
fn mut_iter<'l>(&'l mut self) -> VecMutIterator<'l, N>
{ self.at.mut_iter() }
}
impl<D: Dim, N: Zero + Copy, Iter: Iterator<N>> FromIterator<N, Iter> for NVec<D, N>
{
fn from_iterator(param: &mut Iter) -> NVec<D, N>
{
let mut res: NVec<D, N> = Zero::zero();
let mut i = 0;
for param.advance |e|
{
res.at.at[i] = e;
i = i + 1;
}
res
}
}
impl<D, N: Copy + Add<N,N>> Add<NVec<D, N>, NVec<D, N>> for NVec<D, N>
{
#[inline]
fn add(&self, other: &NVec<D, N>) -> NVec<D, N>
{ NVec { at: self.at + other.at } }
}
impl<D, N: Copy + Sub<N,N>> Sub<NVec<D, N>, NVec<D, N>> for NVec<D, N>
{
#[inline]
fn sub(&self, other: &NVec<D, N>) -> NVec<D, N>
{ NVec { at: self.at - other.at } }
}
impl<D, N: Neg<N>> Neg<NVec<D, N>> for NVec<D, N>
{
#[inline]
fn neg(&self) -> NVec<D, N>
{ NVec { at: -self.at } }
}
impl<D: Dim, N: Ring>
Dot<N> for NVec<D, N>
{
#[inline]
fn dot(&self, other: &NVec<D, N>) -> N
{ self.at.dot(&other.at) }
}
impl<D: Dim, N: Ring> SubDot<N> for NVec<D, N>
{
#[inline]
fn sub_dot(&self, a: &NVec<D, N>, b: &NVec<D, N>) -> N
{ self.at.sub_dot(&a.at, &b.at) }
}
impl<D: Dim, N: Mul<N, N>>
ScalarMul<N> for NVec<D, N>
{
#[inline]
fn scalar_mul(&self, s: &N) -> NVec<D, N>
{ NVec { at: self.at.scalar_mul(s) } }
#[inline]
fn scalar_mul_inplace(&mut self, s: &N)
{ self.at.scalar_mul_inplace(s) }
}
impl<D: Dim, N: Div<N, N>>
ScalarDiv<N> for NVec<D, N>
{
#[inline]
fn scalar_div(&self, s: &N) -> NVec<D, N>
{ NVec { at: self.at.scalar_div(s) } }
#[inline]
fn scalar_div_inplace(&mut self, s: &N)
{ self.at.scalar_div_inplace(s) }
}
impl<D: Dim, N: Add<N, N>>
ScalarAdd<N> for NVec<D, N>
{
#[inline]
fn scalar_add(&self, s: &N) -> NVec<D, N>
{ NVec { at: self.at.scalar_add(s) } }
#[inline]
fn scalar_add_inplace(&mut self, s: &N)
{ self.at.scalar_add_inplace(s) }
}
impl<D: Dim, N: Sub<N, N>>
ScalarSub<N> for NVec<D, N>
{
#[inline]
fn scalar_sub(&self, s: &N) -> NVec<D, N>
{ NVec { at: self.at.scalar_sub(s) } }
#[inline]
fn scalar_sub_inplace(&mut self, s: &N)
{ self.at.scalar_sub_inplace(s) }
}
impl<D: Dim, N: Clone + Copy + Add<N, N> + Neg<N>> Translation<NVec<D, N>> for NVec<D, N>
{
#[inline]
fn translation(&self) -> NVec<D, N>
{ self.clone() }
#[inline]
fn inv_translation(&self) -> NVec<D, N>
{ -self.clone() }
#[inline]
fn translate_by(&mut self, t: &NVec<D, N>)
{ *self = *self + *t; }
}
impl<D: Dim, N: Add<N, N> + Copy> Translatable<NVec<D, N>, NVec<D, N>> for NVec<D, N>
{
#[inline]
fn translated(&self, t: &NVec<D, N>) -> NVec<D, N>
{ self + *t }
}
impl<D: Dim, N: Copy + DivisionRing + Algebraic + Clone>
Norm<N> for NVec<D, N>
{
#[inline]
fn sqnorm(&self) -> N
{ self.at.sqnorm() }
#[inline]
fn norm(&self) -> N
{ self.at.norm() }
#[inline]
fn normalized(&self) -> NVec<D, N>
{
let mut res : NVec<D, N> = self.clone();
res.normalize();
res
}
#[inline]
fn normalize(&mut self) -> N
{ self.at.normalize() }
}
impl<D: Dim,
N: Copy + DivisionRing + Algebraic + Clone + ApproxEq<N>>
Basis for NVec<D, N>
{
#[inline]
fn canonical_basis() -> ~[NVec<D, N>]
{ DVec::canonical_basis_with_dim(Dim::dim::<D>()).map(|&e| NVec { at: e }) }
#[inline]
fn orthogonal_subspace_basis(&self) -> ~[NVec<D, N>]
{ self.at.orthogonal_subspace_basis().map(|&e| NVec { at: e }) }
}
// FIXME: I dont really know how te generalize the cross product int
// n-dimensions…
// impl<N: Copy + Mul<N, N> + Sub<N, N>> Cross<N> for NVec<D, N>
// {
// fn cross(&self, other: &NVec<D, N>) -> N
// { self.x * other.y - self.y * other.x }
// }
impl<D: Dim, N: Copy + Zero> Zero for NVec<D, N>
{
#[inline]
fn zero() -> NVec<D, N>
{ NVec { at: zero_vec_with_dim(Dim::dim::<D>()) } }
#[inline]
fn is_zero(&self) -> bool
{ is_zero_vec(&self.at) }
}
impl<D, N: ApproxEq<N>> ApproxEq<N> for NVec<D, N>
{
#[inline]
fn approx_epsilon() -> N
{ ApproxEq::approx_epsilon::<N, N>() }
#[inline]
fn approx_eq(&self, other: &NVec<D, N>) -> bool
{ self.at.approx_eq(&other.at) }
#[inline]
fn approx_eq_eps(&self, other: &NVec<D, N>, epsilon: &N) -> bool
{ self.at.approx_eq_eps(&other.at, epsilon) }
}
impl<D: Dim, N: Rand + Zero + Copy> Rand for NVec<D, N>
{
#[inline]
fn rand<R: Rng>(rng: &mut R) -> NVec<D, N>
{
let dim = Dim::dim::<D>();
let mut res : NVec<D, N> = Zero::zero();
for iterate(0u, dim) |i|
{ res.at.at[i] = rng.gen() }
res
}
}
impl<D: Dim, N: Bounded + Zero + Add<N, N> + Copy> Bounded for NVec<D, N>
{
#[inline]
fn max_value() -> NVec<D, N>
{ Zero::zero::<NVec<D, N>>().scalar_add(&Bounded::max_value()) }
#[inline]
fn min_value() -> NVec<D, N>
{ Zero::zero::<NVec<D, N>>().scalar_add(&Bounded::min_value()) }
}

View File

@ -7,11 +7,7 @@ use std::rand::{random};
#[test] #[test]
use std::cmp::ApproxEq; use std::cmp::ApproxEq;
#[test] #[test]
use vec::{Vec1, Vec2, Vec3}; use vec::{Vec1, Vec2, Vec3, Vec4, Vec5, Vec6};
#[test]
use ndim::nvec::NVec;
#[test]
use traits::dim::d7;
#[test] #[test]
use traits::basis::Basis; use traits::basis::Basis;
#[test] #[test]
@ -133,7 +129,7 @@ fn test_cross_vec3()
#[test] #[test]
fn test_commut_dot_nvec() fn test_commut_dot_nvec()
{ test_commut_dot_impl!(NVec<d7, f64>); } { test_commut_dot_impl!(Vec6<f64>); }
#[test] #[test]
fn test_commut_dot_vec3() fn test_commut_dot_vec3()
@ -160,8 +156,16 @@ fn test_basis_vec3()
{ test_basis_impl!(Vec3<f64>); } { test_basis_impl!(Vec3<f64>); }
#[test] #[test]
fn test_basis_nvec() fn test_basis_vec4()
{ test_basis_impl!(NVec<d7, f64>); } { test_basis_impl!(Vec4<f64>); }
#[test]
fn test_basis_vec5()
{ test_basis_impl!(Vec5<f64>); }
#[test]
fn test_basis_vec6()
{ test_basis_impl!(Vec6<f64>); }
#[test] #[test]
fn test_subspace_basis_vec1() fn test_subspace_basis_vec1()
@ -176,8 +180,16 @@ fn test_subspace_basis_vec3()
{ test_subspace_basis_impl!(Vec3<f64>); } { test_subspace_basis_impl!(Vec3<f64>); }
#[test] #[test]
fn test_subspace_basis_nvec() fn test_subspace_basis_vec4()
{ test_subspace_basis_impl!(NVec<d7, f64>); } { test_subspace_basis_impl!(Vec4<f64>); }
#[test]
fn test_subspace_basis_vec5()
{ test_subspace_basis_impl!(Vec5<f64>); }
#[test]
fn test_subspace_basis_vec6()
{ test_subspace_basis_impl!(Vec6<f64>); }
#[test] #[test]
fn test_scalar_op_vec1() fn test_scalar_op_vec1()
@ -192,8 +204,16 @@ fn test_scalar_op_vec3()
{ test_scalar_op_impl!(Vec3<f64>, f64); } { test_scalar_op_impl!(Vec3<f64>, f64); }
#[test] #[test]
fn test_scalar_op_nvec() fn test_scalar_op_vec4()
{ test_scalar_op_impl!(NVec<d7, f64>, f64); } { test_scalar_op_impl!(Vec4<f64>, f64); }
#[test]
fn test_scalar_op_vec5()
{ test_scalar_op_impl!(Vec5<f64>, f64); }
#[test]
fn test_scalar_op_vec6()
{ test_scalar_op_impl!(Vec6<f64>, f64); }
#[test] #[test]
fn test_iterator_vec1() fn test_iterator_vec1()
@ -208,5 +228,13 @@ fn test_iterator_vec3()
{ test_iterator_impl!(Vec3<f64>, f64); } { test_iterator_impl!(Vec3<f64>, f64); }
#[test] #[test]
fn test_iterator_nvec() fn test_iterator_vec4()
{ test_iterator_impl!(NVec<d7, f64>, f64); } { test_iterator_impl!(Vec4<f64>, f64); }
#[test]
fn test_iterator_vec5()
{ test_iterator_impl!(Vec5<f64>, f64); }
#[test]
fn test_iterator_vec6()
{ test_iterator_impl!(Vec6<f64>, f64); }

View File

@ -1,457 +1,22 @@
use std::num::{abs, Zero, One, Algebraic, Bounded}; use std::num::{Zero, One, Algebraic, Bounded};
use std::rand::{Rand, Rng, RngUtil}; use std::rand::{Rand, Rng, RngUtil};
use std::vec::{VecIterator, VecMutIterator}; use std::vec::{VecIterator, VecMutIterator};
use std::iterator::{Iterator, FromIterator}; use std::iterator::{Iterator, IteratorUtil, FromIterator};
use std::cmp::ApproxEq; use std::cmp::ApproxEq;
use std::uint::iterate;
use traits::iterable::{Iterable, IterableMut, FromAnyIterator}; use traits::iterable::{Iterable, IterableMut, FromAnyIterator};
use traits::basis::Basis; use traits::basis::Basis;
use traits::cross::Cross;
use traits::dim::Dim; use traits::dim::Dim;
use traits::dot::Dot; use traits::dot::Dot;
use traits::sub_dot::SubDot; use traits::sub_dot::SubDot;
use traits::norm::Norm; use traits::norm::Norm;
use traits::translation::{Translation, Translatable}; use traits::translation::{Translation, Translatable};
use traits::scalar_op::{ScalarMul, ScalarDiv, ScalarAdd, ScalarSub}; use traits::scalar_op::{ScalarMul, ScalarDiv, ScalarAdd, ScalarSub};
use std::uint::iterate;
use std::iterator::IteratorUtil;
use traits::ring::Ring; use traits::ring::Ring;
use traits::division_ring::DivisionRing; use traits::division_ring::DivisionRing;
// FIXME: is there a way to split this file: mod vec_impl;
// one file for macros
// another file for macro calls and specializations
// ?
macro_rules! new_impl(
($t: ident, $dim: expr) => (
impl<N> $t<N>
{
#[inline]
pub fn new(at: [N, ..$dim]) -> $t<N>
{ $t { at: at } }
}
)
)
macro_rules! new_repeat_impl(
($t: ident, $param: ident, [ $($elem: ident)|+ ]) => (
impl<N: Copy> $t<N>
{
#[inline]
pub fn new_repeat($param: N) -> $t<N>
{ $t{ at: [ $( copy $elem, )+ ] } }
}
)
)
macro_rules! iterable_impl(
($t: ident) => (
impl<N> Iterable<N> for $t<N>
{
fn iter<'l>(&'l self) -> VecIterator<'l, N>
{ self.at.iter() }
}
)
)
macro_rules! iterable_mut_impl(
($t: ident) => (
impl<N> IterableMut<N> for $t<N>
{
fn mut_iter<'l>(&'l mut self) -> VecMutIterator<'l, N>
{ self.at.mut_iter() }
}
)
)
macro_rules! eq_impl(
($t: ident) => (
impl<N: Eq> Eq for $t<N>
{
#[inline]
fn eq(&self, other: &$t<N>) -> bool
{ self.at.iter().zip(other.at.iter()).all(|(a, b)| a == b) }
#[inline]
fn ne(&self, other: &$t<N>) -> bool
{ self.at.iter().zip(other.at.iter()).all(|(a, b)| a != b) }
}
)
)
macro_rules! dim_impl(
($t: ident, $dim: expr) => (
impl<N> Dim for $t<N>
{
#[inline]
fn dim() -> uint
{ $dim }
}
)
)
// FIXME: add the possibility to specialize that
macro_rules! basis_impl(
($t: ident, $dim: expr) => (
impl<N: Copy + DivisionRing + Algebraic + ApproxEq<N>> Basis for $t<N>
{
pub fn canonical_basis() -> ~[$t<N>]
{
let mut res : ~[$t<N>] = ~[];
for iterate(0u, $dim) |i|
{
let mut basis_element : $t<N> = Zero::zero();
basis_element.at[i] = One::one();
res.push(basis_element);
}
res
}
pub fn orthogonal_subspace_basis(&self) -> ~[$t<N>]
{
// compute the basis of the orthogonal subspace using Gram-Schmidt
// orthogonalization algorithm
let mut res : ~[$t<N>] = ~[];
for iterate(0u, $dim) |i|
{
let mut basis_element : $t<N> = Zero::zero();
basis_element.at[i] = One::one();
if res.len() == $dim - 1
{ break; }
let mut elt = copy basis_element;
elt = elt - self.scalar_mul(&basis_element.dot(self));
for res.iter().advance |v|
{ elt = elt - v.scalar_mul(&elt.dot(v)) };
if !elt.sqnorm().approx_eq(&Zero::zero())
{ res.push(elt.normalized()); }
}
res
}
}
)
)
macro_rules! add_impl(
($t: ident) => (
impl<N: Copy + Add<N,N>> Add<$t<N>, $t<N>> for $t<N>
{
#[inline]
fn add(&self, other: &$t<N>) -> $t<N>
{
self.at.iter()
.zip(other.at.iter())
.transform(|(a, b)| { *a + *b })
.collect()
}
}
)
)
macro_rules! sub_impl(
($t: ident) => (
impl<N: Copy + Sub<N,N>> Sub<$t<N>, $t<N>> for $t<N>
{
#[inline]
fn sub(&self, other: &$t<N>) -> $t<N>
{
self.at.iter()
.zip(other.at.iter())
.transform(| (a, b) | { *a - *b })
.collect()
}
}
)
)
macro_rules! neg_impl(
($t: ident) => (
impl<N: Neg<N>> Neg<$t<N>> for $t<N>
{
#[inline]
fn neg(&self) -> $t<N>
{ self.at.iter().transform(|a| -a).collect() }
}
)
)
macro_rules! dot_impl(
($t: ident, $dim: expr) => (
impl<N: Ring> Dot<N> for $t<N>
{
#[inline]
fn dot(&self, other: &$t<N>) -> N
{
let mut res = Zero::zero::<N>();
for iterate(0u, $dim) |i|
{ res = res + self.at[i] * other.at[i]; }
res
}
}
)
)
macro_rules! sub_dot_impl(
($t: ident, $dim: expr) => (
impl<N: Ring> SubDot<N> for $t<N>
{
#[inline]
fn sub_dot(&self, a: &$t<N>, b: &$t<N>) -> N
{
let mut res = Zero::zero::<N>();
for iterate(0u, $dim) |i|
{ res = res + (self.at[i] - a.at[i]) * b.at[i]; }
res
}
}
)
)
macro_rules! scalar_mul_impl(
($t: ident, $dim: expr) => (
impl<N: Mul<N, N>> ScalarMul<N> for $t<N>
{
#[inline]
fn scalar_mul(&self, s: &N) -> $t<N>
{ self.at.iter().transform(|a| a * *s).collect() }
#[inline]
fn scalar_mul_inplace(&mut self, s: &N)
{
for iterate(0u, $dim) |i|
{ self.at[i] = self.at[i] * *s; }
}
}
)
)
macro_rules! scalar_div_impl(
($t: ident, $dim: expr) => (
impl<N: Div<N, N>> ScalarDiv<N> for $t<N>
{
#[inline]
fn scalar_div(&self, s: &N) -> $t<N>
{ self.at.iter().transform(|a| a / *s).collect() }
#[inline]
fn scalar_div_inplace(&mut self, s: &N)
{
for iterate(0u, $dim) |i|
{ self.at[i] = self.at[i] / *s; }
}
}
)
)
macro_rules! scalar_add_impl(
($t: ident, $dim: expr) => (
impl<N: Add<N, N>> ScalarAdd<N> for $t<N>
{
#[inline]
fn scalar_add(&self, s: &N) -> $t<N>
{ self.at.iter().transform(|a| a + *s).collect() }
#[inline]
fn scalar_add_inplace(&mut self, s: &N)
{
for iterate(0u, $dim) |i|
{ self.at[i] = self.at[i] + *s; }
}
}
)
)
macro_rules! scalar_sub_impl(
($t: ident, $dim: expr) => (
impl<N: Sub<N, N>> ScalarSub<N> for $t<N>
{
#[inline]
fn scalar_sub(&self, s: &N) -> $t<N>
{ self.at.iter().transform(|a| a - *s).collect() }
#[inline]
fn scalar_sub_inplace(&mut self, s: &N)
{
for iterate(0u, $dim) |i|
{ self.at[i] = self.at[i] - *s; }
}
}
)
)
macro_rules! translation_impl(
($t: ident) => (
impl<N: Copy + Add<N, N> + Neg<N>> Translation<$t<N>> for $t<N>
{
#[inline]
fn translation(&self) -> $t<N>
{ copy *self }
#[inline]
fn inv_translation(&self) -> $t<N>
{ -self }
#[inline]
fn translate_by(&mut self, t: &$t<N>)
{ *self = *self + *t; }
}
)
)
macro_rules! translatable_impl(
($t: ident) => (
impl<N: Add<N, N> + Copy> Translatable<$t<N>, $t<N>> for $t<N>
{
#[inline]
fn translated(&self, t: &$t<N>) -> $t<N>
{ self + *t }
}
)
)
macro_rules! norm_impl(
($t: ident, $dim: expr) => (
impl<N: Copy + DivisionRing + Algebraic> Norm<N> for $t<N>
{
#[inline]
fn sqnorm(&self) -> N
{ self.dot(self) }
#[inline]
fn norm(&self) -> N
{ self.sqnorm().sqrt() }
#[inline]
fn normalized(&self) -> $t<N>
{
let mut res : $t<N> = copy *self;
res.normalize();
res
}
#[inline]
fn normalize(&mut self) -> N
{
let l = self.norm();
for iterate(0u, $dim) |i|
{ self.at[i] = self.at[i] / l; }
l
}
}
)
)
macro_rules! approx_eq_impl(
($t: ident) => (
impl<N: ApproxEq<N>> ApproxEq<N> for $t<N>
{
#[inline]
fn approx_epsilon() -> N
{ ApproxEq::approx_epsilon::<N, N>() }
#[inline]
fn approx_eq(&self, other: &$t<N>) -> bool
{
let mut zip = self.at.iter().zip(other.at.iter());
do zip.all |(a, b)| { a.approx_eq(b) }
}
#[inline]
fn approx_eq_eps(&self, other: &$t<N>, epsilon: &N) -> bool
{
let mut zip = self.at.iter().zip(other.at.iter());
do zip.all |(a, b)| { a.approx_eq_eps(b, epsilon) }
}
}
)
)
macro_rules! zero_impl(
($t: ident) => (
impl<N: Copy + Zero> Zero for $t<N>
{
#[inline]
fn zero() -> $t<N>
{ $t::new_repeat(Zero::zero()) }
#[inline]
fn is_zero(&self) -> bool
{ self.at.iter().all(|e| e.is_zero()) }
}
)
)
macro_rules! rand_impl(
($t: ident, $param: ident, [ $($elem: ident)|+ ]) => (
impl<N: Rand> Rand for $t<N>
{
#[inline]
fn rand<R: Rng>($param: &mut R) -> $t<N>
{ $t::new([ $( $elem.gen(), )+ ]) }
}
)
)
macro_rules! from_any_iterator_impl(
($t: ident, $param: ident, [ $($elem: ident)|+ ]) => (
impl<N: Copy> FromAnyIterator<N> for $t<N>
{
fn from_iterator<'l>($param: &mut VecIterator<'l, N>) -> $t<N>
{ $t { at: [ $( copy *$elem.next().unwrap(), )+ ] } }
fn from_mut_iterator<'l>($param: &mut VecMutIterator<'l, N>) -> $t<N>
{ $t { at: [ $( copy *$elem.next().unwrap(), )+ ] } }
}
)
)
macro_rules! from_iterator_impl(
($t: ident, $param: ident, [ $($elem: ident)|+ ]) => (
impl<N, Iter: Iterator<N>> FromIterator<N, Iter> for $t<N>
{
fn from_iterator($param: &mut Iter) -> $t<N>
{ $t { at: [ $( $elem.next().unwrap(), )+ ] } }
}
)
)
macro_rules! bounded_impl(
($t: ident) => (
impl<N: Bounded + Copy> Bounded for $t<N>
{
#[inline]
fn max_value() -> $t<N>
{ $t::new_repeat(Bounded::max_value()) }
#[inline]
fn min_value() -> $t<N>
{ $t::new_repeat(Bounded::min_value()) }
}
)
)
#[deriving(Ord, ToStr)] #[deriving(Ord, ToStr)]
pub struct Vec1<N> pub struct Vec1<N>
@ -632,74 +197,3 @@ from_any_iterator_impl!(Vec6, iterator, [iterator | iterator | iterator | iterat
bounded_impl!(Vec6) bounded_impl!(Vec6)
iterable_impl!(Vec6) iterable_impl!(Vec6)
iterable_mut_impl!(Vec6) iterable_mut_impl!(Vec6)
impl<N: Mul<N, N> + Sub<N, N>> Cross<Vec1<N>> for Vec2<N>
{
#[inline]
fn cross(&self, other : &Vec2<N>) -> Vec1<N>
{ Vec1::new([self.at[0] * other.at[1] - self.at[1] * other.at[0]]) }
}
impl<N: Mul<N, N> + Sub<N, N>> Cross<Vec3<N>> for Vec3<N>
{
#[inline]
fn cross(&self, other : &Vec3<N>) -> Vec3<N>
{
Vec3::new(
[self.at[1] * other.at[2] - self.at[2] * other.at[1],
self.at[2] * other.at[0] - self.at[0] * other.at[2],
self.at[0] * other.at[1] - self.at[1] * other.at[0]]
)
}
}
impl<N: One> Basis for Vec1<N>
{
#[inline]
fn canonical_basis() -> ~[Vec1<N>]
{ ~[ Vec1::new([One::one()]) ] } // FIXME: this should be static
#[inline]
fn orthogonal_subspace_basis(&self) -> ~[Vec1<N>]
{ ~[] }
}
impl<N: Copy + One + Zero + Neg<N>> Basis for Vec2<N>
{
#[inline]
fn canonical_basis() -> ~[Vec2<N>]
{
// FIXME: this should be static
~[ Vec2::new([One::one(), Zero::zero()]),
Vec2::new([Zero::zero(), One::one()]) ]
}
#[inline]
fn orthogonal_subspace_basis(&self) -> ~[Vec2<N>]
{ ~[ Vec2::new([-self.at[1], copy self.at[0]]) ] }
}
impl<N: Copy + DivisionRing + Ord + Algebraic>
Basis for Vec3<N>
{
#[inline]
fn canonical_basis() -> ~[Vec3<N>]
{
// FIXME: this should be static
~[ Vec3::new([One::one(), Zero::zero(), Zero::zero()]),
Vec3::new([Zero::zero(), One::one(), Zero::zero()]),
Vec3::new([Zero::zero(), Zero::zero(), One::one()]) ]
}
#[inline]
fn orthogonal_subspace_basis(&self) -> ~[Vec3<N>]
{
let a =
if abs(copy self.at[0]) > abs(copy self.at[1])
{ Vec3::new([copy self.at[2], Zero::zero(), -copy self.at[0]]).normalized() }
else
{ Vec3::new([Zero::zero(), -self.at[2], copy self.at[1]]).normalized() };
~[ a.cross(self), a ]
}
}

431
src/vec_impl.rs Normal file
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@ -0,0 +1,431 @@
#[macro_escape];
macro_rules! new_impl(
($t: ident, $dim: expr) => (
impl<N> $t<N>
{
#[inline]
pub fn new(at: [N, ..$dim]) -> $t<N>
{ $t { at: at } }
}
)
)
macro_rules! new_repeat_impl(
($t: ident, $param: ident, [ $($elem: ident)|+ ]) => (
impl<N: Copy> $t<N>
{
#[inline]
pub fn new_repeat($param: N) -> $t<N>
{ $t{ at: [ $( copy $elem, )+ ] } }
}
)
)
macro_rules! iterable_impl(
($t: ident) => (
impl<N> Iterable<N> for $t<N>
{
fn iter<'l>(&'l self) -> VecIterator<'l, N>
{ self.at.iter() }
}
)
)
macro_rules! iterable_mut_impl(
($t: ident) => (
impl<N> IterableMut<N> for $t<N>
{
fn mut_iter<'l>(&'l mut self) -> VecMutIterator<'l, N>
{ self.at.mut_iter() }
}
)
)
macro_rules! eq_impl(
($t: ident) => (
impl<N: Eq> Eq for $t<N>
{
#[inline]
fn eq(&self, other: &$t<N>) -> bool
{ self.at.iter().zip(other.at.iter()).all(|(a, b)| a == b) }
#[inline]
fn ne(&self, other: &$t<N>) -> bool
{ self.at.iter().zip(other.at.iter()).all(|(a, b)| a != b) }
}
)
)
macro_rules! dim_impl(
($t: ident, $dim: expr) => (
impl<N> Dim for $t<N>
{
#[inline]
fn dim() -> uint
{ $dim }
}
)
)
// FIXME: add the possibility to specialize that
macro_rules! basis_impl(
($t: ident, $dim: expr) => (
impl<N: Copy + DivisionRing + Algebraic + ApproxEq<N>> Basis for $t<N>
{
pub fn canonical_basis() -> ~[$t<N>]
{
let mut res : ~[$t<N>] = ~[];
for iterate(0u, $dim) |i|
{
let mut basis_element : $t<N> = Zero::zero();
basis_element.at[i] = One::one();
res.push(basis_element);
}
res
}
pub fn orthogonal_subspace_basis(&self) -> ~[$t<N>]
{
// compute the basis of the orthogonal subspace using Gram-Schmidt
// orthogonalization algorithm
let mut res : ~[$t<N>] = ~[];
for iterate(0u, $dim) |i|
{
let mut basis_element : $t<N> = Zero::zero();
basis_element.at[i] = One::one();
if res.len() == $dim - 1
{ break; }
let mut elt = copy basis_element;
elt = elt - self.scalar_mul(&basis_element.dot(self));
for res.iter().advance |v|
{ elt = elt - v.scalar_mul(&elt.dot(v)) };
if !elt.sqnorm().approx_eq(&Zero::zero())
{ res.push(elt.normalized()); }
}
res
}
}
)
)
macro_rules! add_impl(
($t: ident) => (
impl<N: Copy + Add<N,N>> Add<$t<N>, $t<N>> for $t<N>
{
#[inline]
fn add(&self, other: &$t<N>) -> $t<N>
{
self.at.iter()
.zip(other.at.iter())
.transform(|(a, b)| { *a + *b })
.collect()
}
}
)
)
macro_rules! sub_impl(
($t: ident) => (
impl<N: Copy + Sub<N,N>> Sub<$t<N>, $t<N>> for $t<N>
{
#[inline]
fn sub(&self, other: &$t<N>) -> $t<N>
{
self.at.iter()
.zip(other.at.iter())
.transform(| (a, b) | { *a - *b })
.collect()
}
}
)
)
macro_rules! neg_impl(
($t: ident) => (
impl<N: Neg<N>> Neg<$t<N>> for $t<N>
{
#[inline]
fn neg(&self) -> $t<N>
{ self.at.iter().transform(|a| -a).collect() }
}
)
)
macro_rules! dot_impl(
($t: ident, $dim: expr) => (
impl<N: Ring> Dot<N> for $t<N>
{
#[inline]
fn dot(&self, other: &$t<N>) -> N
{
let mut res = Zero::zero::<N>();
for iterate(0u, $dim) |i|
{ res = res + self.at[i] * other.at[i]; }
res
}
}
)
)
macro_rules! sub_dot_impl(
($t: ident, $dim: expr) => (
impl<N: Ring> SubDot<N> for $t<N>
{
#[inline]
fn sub_dot(&self, a: &$t<N>, b: &$t<N>) -> N
{
let mut res = Zero::zero::<N>();
for iterate(0u, $dim) |i|
{ res = res + (self.at[i] - a.at[i]) * b.at[i]; }
res
}
}
)
)
macro_rules! scalar_mul_impl(
($t: ident, $dim: expr) => (
impl<N: Mul<N, N>> ScalarMul<N> for $t<N>
{
#[inline]
fn scalar_mul(&self, s: &N) -> $t<N>
{ self.at.iter().transform(|a| a * *s).collect() }
#[inline]
fn scalar_mul_inplace(&mut self, s: &N)
{
for iterate(0u, $dim) |i|
{ self.at[i] = self.at[i] * *s; }
}
}
)
)
macro_rules! scalar_div_impl(
($t: ident, $dim: expr) => (
impl<N: Div<N, N>> ScalarDiv<N> for $t<N>
{
#[inline]
fn scalar_div(&self, s: &N) -> $t<N>
{ self.at.iter().transform(|a| a / *s).collect() }
#[inline]
fn scalar_div_inplace(&mut self, s: &N)
{
for iterate(0u, $dim) |i|
{ self.at[i] = self.at[i] / *s; }
}
}
)
)
macro_rules! scalar_add_impl(
($t: ident, $dim: expr) => (
impl<N: Add<N, N>> ScalarAdd<N> for $t<N>
{
#[inline]
fn scalar_add(&self, s: &N) -> $t<N>
{ self.at.iter().transform(|a| a + *s).collect() }
#[inline]
fn scalar_add_inplace(&mut self, s: &N)
{
for iterate(0u, $dim) |i|
{ self.at[i] = self.at[i] + *s; }
}
}
)
)
macro_rules! scalar_sub_impl(
($t: ident, $dim: expr) => (
impl<N: Sub<N, N>> ScalarSub<N> for $t<N>
{
#[inline]
fn scalar_sub(&self, s: &N) -> $t<N>
{ self.at.iter().transform(|a| a - *s).collect() }
#[inline]
fn scalar_sub_inplace(&mut self, s: &N)
{
for iterate(0u, $dim) |i|
{ self.at[i] = self.at[i] - *s; }
}
}
)
)
macro_rules! translation_impl(
($t: ident) => (
impl<N: Copy + Add<N, N> + Neg<N>> Translation<$t<N>> for $t<N>
{
#[inline]
fn translation(&self) -> $t<N>
{ copy *self }
#[inline]
fn inv_translation(&self) -> $t<N>
{ -self }
#[inline]
fn translate_by(&mut self, t: &$t<N>)
{ *self = *self + *t; }
}
)
)
macro_rules! translatable_impl(
($t: ident) => (
impl<N: Add<N, N> + Copy> Translatable<$t<N>, $t<N>> for $t<N>
{
#[inline]
fn translated(&self, t: &$t<N>) -> $t<N>
{ self + *t }
}
)
)
macro_rules! norm_impl(
($t: ident, $dim: expr) => (
impl<N: Copy + DivisionRing + Algebraic> Norm<N> for $t<N>
{
#[inline]
fn sqnorm(&self) -> N
{ self.dot(self) }
#[inline]
fn norm(&self) -> N
{ self.sqnorm().sqrt() }
#[inline]
fn normalized(&self) -> $t<N>
{
let mut res : $t<N> = copy *self;
res.normalize();
res
}
#[inline]
fn normalize(&mut self) -> N
{
let l = self.norm();
for iterate(0u, $dim) |i|
{ self.at[i] = self.at[i] / l; }
l
}
}
)
)
macro_rules! approx_eq_impl(
($t: ident) => (
impl<N: ApproxEq<N>> ApproxEq<N> for $t<N>
{
#[inline]
fn approx_epsilon() -> N
{ ApproxEq::approx_epsilon::<N, N>() }
#[inline]
fn approx_eq(&self, other: &$t<N>) -> bool
{
let mut zip = self.at.iter().zip(other.at.iter());
do zip.all |(a, b)| { a.approx_eq(b) }
}
#[inline]
fn approx_eq_eps(&self, other: &$t<N>, epsilon: &N) -> bool
{
let mut zip = self.at.iter().zip(other.at.iter());
do zip.all |(a, b)| { a.approx_eq_eps(b, epsilon) }
}
}
)
)
macro_rules! zero_impl(
($t: ident) => (
impl<N: Copy + Zero> Zero for $t<N>
{
#[inline]
fn zero() -> $t<N>
{ $t::new_repeat(Zero::zero()) }
#[inline]
fn is_zero(&self) -> bool
{ self.at.iter().all(|e| e.is_zero()) }
}
)
)
macro_rules! rand_impl(
($t: ident, $param: ident, [ $($elem: ident)|+ ]) => (
impl<N: Rand> Rand for $t<N>
{
#[inline]
fn rand<R: Rng>($param: &mut R) -> $t<N>
{ $t::new([ $( $elem.gen(), )+ ]) }
}
)
)
macro_rules! from_any_iterator_impl(
($t: ident, $param: ident, [ $($elem: ident)|+ ]) => (
impl<N: Copy> FromAnyIterator<N> for $t<N>
{
fn from_iterator<'l>($param: &mut VecIterator<'l, N>) -> $t<N>
{ $t { at: [ $( copy *$elem.next().unwrap(), )+ ] } }
fn from_mut_iterator<'l>($param: &mut VecMutIterator<'l, N>) -> $t<N>
{ $t { at: [ $( copy *$elem.next().unwrap(), )+ ] } }
}
)
)
macro_rules! from_iterator_impl(
($t: ident, $param: ident, [ $($elem: ident)|+ ]) => (
impl<N, Iter: Iterator<N>> FromIterator<N, Iter> for $t<N>
{
fn from_iterator($param: &mut Iter) -> $t<N>
{ $t { at: [ $( $elem.next().unwrap(), )+ ] } }
}
)
)
macro_rules! bounded_impl(
($t: ident) => (
impl<N: Bounded + Copy> Bounded for $t<N>
{
#[inline]
fn max_value() -> $t<N>
{ $t::new_repeat(Bounded::max_value()) }
#[inline]
fn min_value() -> $t<N>
{ $t::new_repeat(Bounded::min_value()) }
}
)
)

77
src/vec_spec.rs Normal file
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@ -0,0 +1,77 @@
use std::num::{Zero, One, abs};
use traits::basis::Basis;
use traits::cross::Cross;
use traits::division_ring::DivisionRing;
use traits::norm::Norm;
use vec::{Vec1, Vec2, Vec3};
impl<N: Mul<N, N> + Sub<N, N>> Cross<Vec1<N>> for Vec2<N>
{
#[inline]
fn cross(&self, other : &Vec2<N>) -> Vec1<N>
{ Vec1::new([self.at[0] * other.at[1] - self.at[1] * other.at[0]]) }
}
impl<N: Mul<N, N> + Sub<N, N>> Cross<Vec3<N>> for Vec3<N>
{
#[inline]
fn cross(&self, other : &Vec3<N>) -> Vec3<N>
{
Vec3::new(
[self.at[1] * other.at[2] - self.at[2] * other.at[1],
self.at[2] * other.at[0] - self.at[0] * other.at[2],
self.at[0] * other.at[1] - self.at[1] * other.at[0]]
)
}
}
impl<N: One> Basis for Vec1<N>
{
#[inline]
fn canonical_basis() -> ~[Vec1<N>]
{ ~[ Vec1::new([One::one()]) ] } // FIXME: this should be static
#[inline]
fn orthogonal_subspace_basis(&self) -> ~[Vec1<N>]
{ ~[] }
}
impl<N: Copy + One + Zero + Neg<N>> Basis for Vec2<N>
{
#[inline]
fn canonical_basis() -> ~[Vec2<N>]
{
// FIXME: this should be static
~[ Vec2::new([One::one(), Zero::zero()]),
Vec2::new([Zero::zero(), One::one()]) ]
}
#[inline]
fn orthogonal_subspace_basis(&self) -> ~[Vec2<N>]
{ ~[ Vec2::new([-self.at[1], copy self.at[0]]) ] }
}
impl<N: Copy + DivisionRing + Ord + Algebraic>
Basis for Vec3<N>
{
#[inline]
fn canonical_basis() -> ~[Vec3<N>]
{
// FIXME: this should be static
~[ Vec3::new([One::one(), Zero::zero(), Zero::zero()]),
Vec3::new([Zero::zero(), One::one(), Zero::zero()]),
Vec3::new([Zero::zero(), Zero::zero(), One::one()]) ]
}
#[inline]
fn orthogonal_subspace_basis(&self) -> ~[Vec3<N>]
{
let a =
if abs(copy self.at[0]) > abs(copy self.at[1])
{ Vec3::new([copy self.at[2], Zero::zero(), -copy self.at[0]]).normalized() }
else
{ Vec3::new([Zero::zero(), -self.at[2], copy self.at[1]]).normalized() };
~[ a.cross(self), a ]
}
}