Spiril

Spiril is an implementation of a genetic algorithm for obtaining optimum variables (genetics) for a task through mutation and natural selection.

The API allows you to specify an initial group of units, which will act as the original parents of all subsequent units. Unit types implement a fitness function and a breed function for introducing new genetic combinations and mutations into subsequent generations.

Fitnesses can be calculated across a population using parallel threads.

Sudoku example

externcrate spiril;externcrate rand;use spiril::unit::Unit;use spiril::population::Population;use rand::{StdRng,SeedableRng,Rng};structSudokuUnit{sudoku:Vec<usize>,// 9x9 gridanswer:Vec<usize>,// 9x9 grid}implUnitforSudokuUnit{fnfitness(&self) -> f64{letmut score = 1.0_f64;for i in0..9{letmut seen_row:[usize;9] = [0,0,0,0,0,0,0,0,0];letmut seen_col:[usize;9] = [0,0,0,0,0,0,0,0,0];letmut seen_sqr:[usize;9] = [0,0,0,0,0,0,0,0,0];for j in0..9{
seen_row[self.answer[i *9 + j] - 1] += 1;
seen_col[self.answer[i + 9* j] - 1] += 1;let sqr_index = ((i % 3)*3) + (((i / 3) % 3)*27) + (9*(j / 3)) + j % 3;
seen_sqr[self.answer[sqr_index] - 1] += 1;}
seen_row
.iter().chain(seen_col.iter()).chain(seen_sqr.iter()).map(|x| if*x == 0{// score -= (1.0 / 729.0);
score *= 0.9;}).last();}
score
}fnbreed_with(&self,other:&SudokuUnit) -> SudokuUnit{// Even rows taken from self, odd rows taken from other.// Mutations applied at random.letmut new_unit:SudokuUnit = SudokuUnit{sudoku:self.sudoku.clone(),answer:self.answer.clone(),};(0_usize..81_usize).filter(|x| self.sudoku[*x] == 0).map(|x| {if rand::thread_rng().gen_range(0,1) == 1{
new_unit.answer[x] = other.answer[x];}
new_unit.answer[x]}).last();loop{let i = rand::thread_rng().gen_range(0,81);ifself.sudoku[i] == 0{
new_unit.answer[i] = rand::thread_rng().gen_range(1,10);break;}}
new_unit
}}fnmain(){let test_doku:Vec<usize> = vec![7,2,6,0,9,3,8,1,5,3,0,5,7,2,8,9,0,6,4,8,0,6,0,1,2,3,7,8,5,2,1,4,0,6,9,3,0,7,3,9,8,5,1,2,4,9,4,1,0,6,2,0,5,8,1,9,0,8,3,0,5,7,2,5,6,7,2,1,4,3,8,0,2,0,8,5,0,9,4,6,1,];let seed:&[_] = &[0];letmut init_rng:StdRng = SeedableRng::from_seed(seed);let units:Vec<SudokuUnit> = (0..1000).map(|_| {SudokuUnit{sudoku: test_doku.clone(),answer: test_doku
.clone().iter().map(|x| if*x == 0{
init_rng.gen_range(1,10)}else{*x
}).collect(),}}).collect();assert_eq!(Population::new(units).set_size(1000).set_breed_factor(0.3).set_survival_factor(0.5).epochs_parallel(5000,4)// 4 CPU cores.finish().first().unwrap().fitness(),1.0);}