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completed rename. merged crates to features

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This commit is contained in:
Jon Janzen
2021-06-13 09:53:38 -06:00
parent 90d3148335
commit 29bccd78fe
20 changed files with 7839 additions and 241 deletions
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features/src/matrix.rs Normal file
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use crate::structs::Tuple;
use std::ops::{Index, IndexMut};
#[derive(Debug)]
pub struct Matrix {
matrix: Vec<Vec<f32>>,
}
impl Matrix {
pub fn default(width: usize, height: usize) -> Self {
Matrix {
matrix: vec![vec![0.0f32; width]; height],
}
}
pub fn from_array<const H: usize, const W: usize>(array: [[f32; W]; H]) -> Matrix {
let mut matrix: Vec<Vec<f32>> = Vec::with_capacity(H);
for r in array.iter() {
let mut row: Vec<f32> = Vec::with_capacity(W);
for v in r.iter() {
row.push(*v);
}
matrix.push(row);
}
Matrix {
matrix,
}
}
pub fn from_vec(matrix: Vec<Vec<f32>>) -> Matrix {
Matrix {
matrix,
}
}
pub fn identity(size: usize) -> Matrix {
let mut m = Self::default(size, size);
for i in 0..m.matrix.len() {
m.matrix[i][i] = 1.0;
}
m
}
pub fn transpose(&mut self) {
for i in 0..self.matrix.len() {
for j in i..self.matrix[0].len() {
let v = self.matrix[i][j];
self.matrix[i][j] = self.matrix[j][i];
self.matrix[j][i] = v;
}
}
}
pub fn determinant(&self) -> f32 {
if self.matrix[0].len() == 2 {
self.matrix[0][0] * self.matrix[1][1] - self.matrix[0][1] * self.matrix[1][0]
} else {
let mut sum = 0.0;
for (col, val) in self.matrix[0].iter().enumerate().take(self.matrix[0].len()) {
sum += val * self.cofactor(0, col);
}
sum
}
}
pub fn minor(&self, row: usize, col: usize) -> f32 {
let m = self.sub_matrix(row, col);
let det = m.determinant();
det
}
pub fn cofactor(&self, row: usize, col: usize) -> f32 {
let minor = self.minor(row, col);
if (row + col) & 0x1 == 0 {
minor
} else {
minor * -1.0
}
}
pub fn sub_matrix(&self, skip_row: usize, skip_col: usize) -> Matrix
{
let mut m = Vec::<Vec<f32>>::with_capacity(self.matrix.len() - 1);
for (i, row) in self.matrix.iter().enumerate().take(self.matrix.len()) {
if i == skip_row { continue; }
let mut r = Vec::<f32>::with_capacity(row.len() - 1);
for (j, col) in row.iter().enumerate().take(row.len()) {
if j == skip_col { continue; }
r.push(*col);
}
m.push(r);
}
Matrix::from_vec(m)
}
pub fn is_invertable(&self) -> bool {
self.determinant() != 0.0
}
pub fn inverse(&self) -> Matrix {
// seems dangerous
if !self.is_invertable() {
panic!("We can't invert {:?}", self.matrix);
}
//let mut matrix: Vec<Vec<f32>> = Vec::with_capacity(self.matrix.len());
let mut matrix = Matrix::default(self.matrix.len(), self.matrix[0].len());
let det = self.determinant();
for (row_idx, row) in self.matrix.iter().enumerate().take(self.matrix.len()) {
for (col_idx, _) in row.iter().enumerate().take(row.len()) {
let c = self.cofactor(row_idx, col_idx);
let val = c / det;
matrix[col_idx][row_idx] = val;
}
}
matrix
}
}
impl Index<usize> for Matrix {
type Output = Vec<f32>;
fn index(&self, index: usize) -> &Self::Output {
&self.matrix[index]
}
}
impl IndexMut<usize> for Matrix {
fn index_mut(&mut self, index: usize) -> &mut Self::Output {
&mut self.matrix[index]
}
}
impl PartialEq for Matrix {
fn eq(&self, _rhs: &Self) -> bool {
if self.matrix.len() != _rhs.matrix.len() {
return false;
}
for row_idx in 0..self.matrix.len() {
if self.matrix[row_idx].len() != _rhs.matrix[row_idx].len() {
return false;
}
for col_idx in 0..self.matrix[row_idx].len() {
if !relative_eq!(
self.matrix[row_idx][col_idx],
_rhs.matrix[row_idx][col_idx]) {
return false;
}
}
}
true
}
}
impl Matrix {
fn calc_val_for_mul(&self, row: usize, rhs: &Matrix, col: usize) -> f32 {
let mut sum = 0.0;
for i in 0..self.matrix.len() {
sum += self.matrix[row][i] * rhs.matrix[i][col];
}
sum
}
fn calc_val_for_mul_tuple(&self, row: usize, tuple: &Tuple) -> f32 {
(self.matrix[row][0] * tuple.x()) +
(self.matrix[row][1] * tuple.y()) +
(self.matrix[row][2] * tuple.z()) +
(self.matrix[row][3] * tuple.w())
}
}
impl std::ops::Mul<&Matrix> for &Matrix {
type Output = Matrix;
fn mul(self, _rhs: &Matrix) -> Matrix {
let mut result: Vec<Vec<f32>> = Vec::with_capacity(self.matrix.len());
for row in 0..self.matrix.len() {
let width = self.matrix[row].len();
let mut new_col = Vec::with_capacity(width);
for col in 0..width {
new_col.push( self.calc_val_for_mul(row, &_rhs, col));
}
result.push(new_col);
}
Matrix::from_vec(result)
}
}
impl std::ops::Mul<&Tuple> for &Matrix {
type Output = Tuple;
fn mul(self, _rhs: &Tuple) -> Tuple {
Tuple::new(
self.calc_val_for_mul_tuple(0, &_rhs),
self.calc_val_for_mul_tuple(1, &_rhs),
self.calc_val_for_mul_tuple(2, &_rhs),
self.calc_val_for_mul_tuple(3, &_rhs),
)
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn matrix_4x4() {
let m = [
[1.0, 2.0, 3.0, 4.0],
[5.5, 6.5, 7.5, 8.5],
[9.0, 10.0, 11.0, 12.0],
[13.5, 14.5, 15.5, 16.5],
];
let matrix = Matrix::from_array(m);
assert_eq!(1.0, matrix[0][0]);
assert_eq!(4.0, matrix[0][3]);
assert_eq!(5.5, matrix[1][0]);
assert_eq!(7.5, matrix[1][2]);
assert_eq!(11.0, matrix[2][2]);
assert_eq!(13.5, matrix[3][0]);
assert_eq!(15.5, matrix[3][2]);
}
#[test]
fn matrix_4x4_array() {
let m = [
[1.0, 2.0, 3.0, 4.0],
[5.5, 6.5, 7.5, 8.5],
[9.0, 10.0, 11.0, 12.0],
[13.5, 14.5, 15.5, 16.5],
];
let matrix = Matrix::from_array(m);
assert_eq!(1.0, matrix[0][0]);
assert_eq!(4.0, matrix[0][3]);
assert_eq!(5.5, matrix[1][0]);
assert_eq!(7.5, matrix[1][2]);
assert_eq!(11.0, matrix[2][2]);
assert_eq!(13.5, matrix[3][0]);
assert_eq!(15.5, matrix[3][2]);
}
#[test]
fn matrix_2x2() {
let m = [
[-3.0, 5.0,],
[1.0, 2.0,],
];
let matrix = Matrix::from_array(m);
assert_eq!(-3.0, matrix[0][0]);
assert_eq!(5.0, matrix[0][1]);
assert_eq!(1.0, matrix[1][0]);
assert_eq!(2.0, matrix[1][1]);
}
#[test]
fn matrix_3x3() {
let m = [
[-3.0, 5.0, 0.0],
[1.0, -2.0, -7.0],
[0.0, 1.0, 1.0],
];
let matrix = Matrix::from_array(m);
assert_eq!(-3.0, matrix[0][0]);
assert_eq!(-2.0, matrix[1][1]);
assert_eq!(1.0, matrix[2][2]);
}
#[test]
fn matrix_equality_a() {
let a = [
[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0],
[9.0, 8.0, 7.0, 6.0],
[5.0, 4.0, 3.0, 2.0],
];
let m_a = Matrix::from_array(a);
let b = [
[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0],
[9.0, 8.0, 7.0, 6.0],
[5.0, 4.0, 3.0, 2.0],
];
let m_b = Matrix::from_array(b);
assert_eq!(m_a, m_b);
}
#[test]
fn matrix_equality_b() {
let a = [
[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0],
[9.0, 8.0, 7.0, 6.0],
[5.0, 4.0, 3.0, 2.0],
];
let m_a = Matrix::from_array(a);
let b = [
[2.0, 3.0, 4.0, 5.0],
[6.0, 7.0, 8.0, 9.0],
[8.0, 7.0, 6.0, 5.0],
[4.0, 3.0, 2.0, 1.0],
];
let m_b = Matrix::from_array(b);
assert_ne!(m_a, m_b);
}
#[test]
fn multiply() {
let matrix_a = Matrix::from_array([
[1.0, 2.0, 3.0, 4.0,],
[5.0, 6.0, 7.0, 8.0,],
[9.0, 8.0, 7.0, 6.0,],
[5.0, 4.0, 3.0, 2.0,],
]);
let matrix_b = Matrix::from_array([
[-2.0, 1.0, 2.0, 3.0,],
[3.0, 2.0, 1.0, -1.0,],
[4.0, 3.0, 6.0, 5.0,],
[1.0, 2.0, 7.0, 8.0,],
]);
let expected = Matrix::from_array([
[20.0, 22.0, 50.0, 48.0],
[44.0, 54.0, 114.0, 108.0],
[40.0, 58.0, 110.0, 102.0,],
[16.0, 26.0, 46.0, 42.0],
]);
assert_eq!(&matrix_a * &matrix_b, expected);
}
#[test]
fn multiply_by_tuple() {
let matrix = Matrix::from_array([
[1.0, 2.0, 3.0, 4.0],
[2.0, 4.0, 4.0, 2.0],
[8.0, 6.0, 4.0, 1.0],
[0.0, 0.0, 0.0, 1.0],
]);
let tuple = Tuple::new(1.0, 2.0, 3.0, 1.0);
let expected = Tuple::new(18.0, 24.0, 33.0, 1.0);
assert_eq!(&matrix * &tuple, expected);
}
#[test]
fn matrix_by_identity() {
let matrix = Matrix::from_array([
[0.0, 1.0, 2.0, 4.0,],
[1.0, 2.0, 4.0, 8.0,],
[2.0, 4.0, 8.0, 16.0],
[4.0, 8.0, 16.0, 32.0,]
]);
let expected = Matrix::from_array([
[0.0, 1.0, 2.0, 4.0,],
[1.0, 2.0, 4.0, 8.0,],
[2.0, 4.0, 8.0, 16.0],
[4.0, 8.0, 16.0, 32.0,]
]);
assert_eq!(&matrix * &Matrix::identity(4), expected);
}
#[test]
fn tuple_by_identity() {
let t = Tuple::new(1.0, 2.0, 3.0, 4.0);
let expected = Tuple::new(1.0, 2.0, 3.0, 4.0);
assert_eq!(&Matrix::identity(4) * &t, expected);
}
#[test]
fn transposition() {
let mut m = Matrix::from_array([
[0.0, 9.0, 3.0, 0.0],
[9.0, 8.0, 0.0, 8.0],
[1.0, 8.0, 5.0, 3.0],
[0.0, 0.0, 5.0, 8.0],
]);
let expected = Matrix::from_array([
[0.0, 9.0, 1.0, 0.0],
[9.0, 8.0, 8.0, 0.0],
[3.0, 0.0, 5.0, 5.0],
[0.0, 8.0, 3.0, 8.0],
]);
m.transpose();
assert_eq!(m, expected);
}
#[test]
fn transpose_identity() {
let mut m = Matrix::identity(4);
m.transpose();
assert_eq!(m, Matrix::identity(4));
}
#[test]
fn determinant_2x2() {
let m = Matrix::from_array([
[1.0, 5.0],
[-3.0, 2.0],
]);
assert_eq!(17.0, m.determinant());
}
#[test]
fn submatrix_3x3() {
let start = Matrix::from_array([
[1.0, 5.0, 0.0],
[-3.0, 2.0, 7.0],
[0.0, 6.0, -3.0],
]);
let expected = Matrix::from_array([
[-3.0, 2.0],
[0.0, 6.0],
]);
assert_eq!(expected, start.sub_matrix(0, 2));
}
#[test]
fn submatrix_4x4() {
let start = Matrix::from_array([
[-6.0, 1.0, 1.0, 6.0],
[-8.0, 5.0, 8.0, 6.0],
[-1.0, 0.0, 8.0, 2.0],
[-7.0, 1.0, -1.0, 1.0],
]);
let expected = Matrix::from_array([
[-6.0, 1.0, 6.0],
[-8.0, 8.0, 6.0],
[-7.0, -1.0, 1.0],
]);
assert_eq!(expected, start.sub_matrix(2, 1));
}
#[test]
fn minor_3x3() {
let m = Matrix::from_array([
[3.0, 5.0, 0.0],
[2.0, -1.0, -7.0],
[6.0, -1.0, 5.0],
]);
let s = m.sub_matrix(1, 0);
assert_eq!(25.0, s.determinant());
assert_eq!(25.0, m.minor(1, 0));
}
#[test]
fn cofactor_3x3() {
let m = Matrix::from_array([
[3.0, 5.0, 0.0],
[2.0, -1.0, -7.0],
[6.0, -1.0, 5.0],
]);
assert_eq!(-12.0, m.minor(0, 0));
assert_eq!(-12.0, m.cofactor(0, 0));
assert_eq!(25.0, m.minor(1, 0));
assert_eq!(-25.0, m.cofactor(1, 0));
}
#[test]
fn determinant_3x3() {
let m = Matrix::from_array([
[1.0, 2.0, 6.0],
[-5.0, 8.0, -4.0],
[2.0, 6.0, 4.0],
]);
assert_eq!(56.0, m.cofactor(0, 0));
assert_eq!(12.0, m.cofactor(0, 1));
assert_eq!(-46.0, m.cofactor(0, 2));
assert_eq!(-196.0, m.determinant());
}
#[test]
fn determinant_4x4() {
let m = Matrix::from_array([
[-2.0, -8.0, 3.0, 5.0],
[-3.0, 1.0, 7.0, 3.0],
[1.0, 2.0, -9.0, 6.0],
[-6.0, 7.0, 7.0, -9.0],
]);
assert_eq!(690.0, m.cofactor(0, 0));
assert_eq!(447.0, m.cofactor(0, 1));
assert_eq!(210.0, m.cofactor(0, 2));
assert_eq!(51.0, m.cofactor(0, 3));
assert_eq!(-4071.0, m.determinant());
}
#[test]
fn can_invert_invertable() {
let m = Matrix::from_array([
[6.0, 4.0, 4.0, 4.0],
[5.0, 5.0, 7.0, 6.0],
[4.0, -9.0, 3.0, -7.0],
[9.0, 1.0, 7.0, -6.0],
]);
assert_eq!(-2120.0, m.determinant());
assert_eq!(true, m.is_invertable());
}
#[test]
fn can_invert_not_invertable() {
let m = Matrix::from_array([
[-4.0, 2.0, -2.0, -3.0],
[9.0, 6.0, 2.0, 6.0],
[0.0, -5.0, 1.0, -5.0],
[0.0, 0.0, 0.0, 0.0],
]);
assert_eq!(0.0, m.determinant());
assert_eq!(false, m.is_invertable());
}
fn assert_matrix_eq(_lhs: &Matrix, _rhs: &Matrix, max_relative: f32) -> bool {
if _lhs.matrix.len() != _rhs.matrix.len() {
return false;
}
for row_idx in 0.._lhs.matrix.len() {
if _lhs.matrix[row_idx].len() != _rhs.matrix[row_idx].len() {
return false;
}
for col_idx in 0.._lhs.matrix[row_idx].len() {
assert_relative_eq!( _lhs.matrix[row_idx][col_idx],
_rhs.matrix[row_idx][col_idx],
max_relative = max_relative);
}
}
true
}
#[test]
fn inverse() {
let m = Matrix::from_array([
[-5.0, 2.0, 6.0, -8.0],
[1.0, -5.0, 1.0, 8.0],
[7.0, 7.0, -6.0, -7.0],
[1.0, -3.0, 7.0, 4.0],
]);
let b = m.inverse();
assert_eq!(532.0, m.determinant());
assert_eq!(-160.0, m.cofactor(2, 3));
assert_eq!(-160.0/532.0, b[3][2]);
assert_eq!(105.0, m.cofactor(3, 2));
assert_eq!(105.0/532.0, b[2][3]);
let expected = Matrix::from_array([
[0.21805, 0.45113, 0.24060, -0.04511],
[-0.80827, -1.45677, -0.44361, 0.52068],
[-0.07895, -0.22368, -0.05263, 0.19737],
[-0.52256, -0.81392, -0.30075, 0.30639],
]);
assert_matrix_eq(&expected, &b, 0.0001);
}
#[test]
fn inverse_2() {
let m = Matrix::from_array([
[8.0, -5.0, 9.0, 2.0],
[7.0, 5.0, 6.0, 1.0],
[-6.0, 0.0, 9.0, 6.0],
[-3.0, 0.0, -9.0, -4.0],
]).inverse();
let expected = Matrix::from_array([
[-0.15385, -0.15385, -0.28205, -0.53846],
[-0.07692, 0.12308, 0.02564, 0.03077],
[0.35897, 0.35897, 0.43590, 0.92308],
[-0.69321, -0.69321, -0.76923, -1.92308],
]);
assert_matrix_eq(&expected, &m, 0.01);
}
#[test]
fn inverse_3() {
let m = Matrix::from_array([
[9.0, 3.0, 0.0, 9.0],
[-5.0, -2.0, -6.0, -3.0],
[-4.0, 9.0, 6.0, 4.0],
[-7.0, 6.0, 6.0, 2.0],
]).inverse();
let expected = Matrix::from_array([
[-0.04074, -0.07778, 0.14444, -0.22222],
[-0.07778, 0.03333, 0.36667, -0.33333],
[-0.02901, -0.14630, -0.10926, 0.12963],
[0.17778, 0.06667, -0.26667, 0.33333],
]);
assert_matrix_eq(&expected, &m, 0.01);
}
#[test]
fn multiply_by_inverse() {
let a = Matrix::from_array([
[3.0, -9.0, 7.0, 3.0],
[3.0, -8.0, 2.0, -9.0],
[-4.0, 4.0, 4.0, 1.0],
[-6.0, 5.0, -1.0, 1.0],
]);
let b = Matrix::from_array([
[8.0, 2.0, 2.0, 2.0],
[3.0, -1.0, 7.0, 0.0],
[7.0, 0.0, 5.0, 4.0],
[6.0, -2.0, 0.0, 5.0],
]);
let c = &a * &b;
let r = &c * &b.inverse();
let expected = Matrix::from_array([
[3.0, -9.0, 7.0, 3.0],
[3.0, -8.0, 2.0, -9.0],
[-4.0, 4.0, 4.0, 1.0],
[-6.0, 5.0, -1.0, 1.0],
]);
assert_matrix_eq(&r, &expected, 0.00001);
}
}