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use ::*;
use ea::*;
use math::*;
#[derive(Clone, Debug, Deserialize, Serialize)]
pub struct EAResult<T: Individual> {
pub min_fitness: Vec<f32>,
pub max_fitness: Vec<f32>,
pub avg_fitness: Vec<f32>,
pub best: T,
pub best_fe_count: u32,
pub first_hit_fe_count: u32,
pub fe_count: u32,
}
impl<T: Individual> EAResult<T> {
pub fn new() -> EAResult<T> {
EAResult{avg_fitness: Vec::new(),
min_fitness: Vec::new(),
max_fitness: Vec::new(),
best: T::new(),
best_fe_count: 0,
first_hit_fe_count: 0,
fe_count: 0,
}
}
}
impl<T: Individual+Clone+DeserializeOwned+Serialize> Jsonable for EAResult<T> {
type T = Self;
}
#[derive(Clone, Debug, Deserialize, Serialize)]
pub struct EAResultMultiple<T: Individual> {
pub min_fitness: Vec<f32>,
pub max_fitness: Vec<f32>,
pub avg_fitness_mean: Vec<f32>,
pub avg_fitness_sd: Vec<f32>,
pub best: T,
pub best_fe_count_mean: f32,
pub best_fe_count_sd: f32,
pub first_hit_fe_count_mean: f32,
pub first_hit_fe_count_sd: f32,
pub success_count: u32,
pub run_count: u32,
}
impl<T: Individual+Clone> EAResultMultiple<T> {
pub fn new(rs: &[EAResult<T>]) -> EAResultMultiple<T> {
let mut avg_fitness_mean: Vec<f32> = Vec::new();
let mut avg_fitness_sd: Vec<f32> = Vec::new();
let mut min_fitness: Vec<f32> = Vec::new();
let mut max_fitness: Vec<f32> = Vec::new();
let mut best_fe_count_mean = 0f32;
let mut best_fe_count_sd = 0f32;
let mut first_hit_fe_count_mean = 0f32;
let mut first_hit_fe_count_sd = 0f32;
let mut success_count = 0;
let mut best_fitness = std::f32::MAX;
let mut best_run_idx = std::usize::MAX;
let run_count = rs.len();
for k in 0..run_count {
let cur_res = &rs[k];
if k != 0 {
acc(&mut avg_fitness_mean, &cur_res.avg_fitness);
acc(&mut avg_fitness_sd, &sqr(&cur_res.avg_fitness));
min_inplace_vv(&mut min_fitness, &cur_res.min_fitness);
max_inplace_vv(&mut max_fitness, &cur_res.max_fitness);
} else {
avg_fitness_mean = cur_res.avg_fitness.clone();
avg_fitness_sd = sqr(&cur_res.avg_fitness);
min_fitness = cur_res.min_fitness.clone();
max_fitness = cur_res.max_fitness.clone();
}
best_fe_count_mean += cur_res.best_fe_count as f32;
best_fe_count_sd += ((cur_res.best_fe_count) * (cur_res.best_fe_count)) as f32;
if cur_res.first_hit_fe_count > 0 {
first_hit_fe_count_mean += cur_res.first_hit_fe_count as f32;
first_hit_fe_count_sd += ((cur_res.first_hit_fe_count) * (cur_res.first_hit_fe_count)) as f32;
success_count += 1;
}
if rs[k].best.get_fitness() < best_fitness {
best_fitness = cur_res.best.get_fitness();
best_run_idx = k;
}
}
mul_inplace(&mut avg_fitness_mean, 1f32/run_count as f32);
mul_inplace(&mut avg_fitness_sd, 1f32/run_count as f32);
sub_inplace(&mut avg_fitness_sd, &sqr(&avg_fitness_mean));
max_inplace_vv(&mut avg_fitness_sd, &vec![0f32; avg_fitness_mean.len()]);
best_fe_count_mean /= run_count as f32;
best_fe_count_sd = best_fe_count_sd / run_count as f32 - best_fe_count_mean*best_fe_count_mean;
if success_count > 0 {
first_hit_fe_count_mean /= success_count as f32;
first_hit_fe_count_sd = first_hit_fe_count_sd / success_count as f32 - first_hit_fe_count_mean * first_hit_fe_count_mean;
}
EAResultMultiple::<T>{
avg_fitness_mean: avg_fitness_mean,
avg_fitness_sd: avg_fitness_sd,
min_fitness: min_fitness,
max_fitness: max_fitness,
best: rs[best_run_idx].best.clone(),
best_fe_count_mean: best_fe_count_mean,
best_fe_count_sd: best_fe_count_sd,
first_hit_fe_count_mean: first_hit_fe_count_mean,
first_hit_fe_count_sd: first_hit_fe_count_sd,
success_count: success_count,
run_count: run_count as u32,
}
}
}
impl<T: Individual+Clone+DeserializeOwned+Serialize> Jsonable for EAResultMultiple<T> {
type T = Self;
}
#[cfg(test)]
mod test {
#[allow(unused_imports)]
use ea::*;
use ga::*;
use problem::*;
use result::*;
use settings::*;
#[test]
fn test_json_earesult() {
let pop_size = 10u32;
let problem_dim = 5u32;
let problem = SphereProblem{};
let gen_count = 10u32;
let settings = EASettings::new(pop_size, gen_count, problem_dim);
let mut ga: GA<SphereProblem> = GA::new(&problem);
let res = ga.run(settings).expect("Error during GA run");
let filename = "test_json_earesult.json";
res.to_json(&filename);
let res2: EAResult<RealCodedIndividual> = EAResult::from_json(&filename);
assert!(res.best_fe_count == res2.best_fe_count);
assert!(res.fe_count == res2.fe_count);
assert!(res.first_hit_fe_count == res2.first_hit_fe_count);
assert!(res.best.fitness == res2.best.fitness);
}
#[test]
fn test_json_earesult_mult() {
let pop_size = 10u32;
let problem_dim = 5u32;
let problem = SphereProblem{};
let gen_count = 10u32;
let ress = (0..3).into_iter()
.map(|_ | {
let settings = EASettings::new(pop_size, gen_count, problem_dim);
let mut ga: GA<SphereProblem> = GA::new(&problem);
ga.run(settings).expect("Error during GA run").clone()
})
.collect::<Vec<EAResult<RealCodedIndividual>>>();
let filename = "test_json_earesult_mult.json";
let res = EAResultMultiple::new(&ress);
res.to_json(&filename);
let res2: EAResultMultiple<RealCodedIndividual> = EAResultMultiple::from_json(&filename);
assert!(res.run_count == res2.run_count);
assert!(res.success_count == res2.success_count);
assert!(res.first_hit_fe_count_mean == res2.first_hit_fe_count_mean);
assert!(res.first_hit_fe_count_sd == res2.first_hit_fe_count_sd);
assert!(res.best_fe_count_mean == res2.best_fe_count_mean);
assert!(res.best_fe_count_sd == res2.best_fe_count_sd);
assert!(res.best.fitness == res2.best.fitness);
assert!(res.best.genes == res2.best.genes);
assert!(res.min_fitness == res2.min_fitness);
assert!(res.max_fitness == res2.max_fitness);
assert!(res.avg_fitness_mean == res2.avg_fitness_mean);
assert!(res.avg_fitness_sd == res2.avg_fitness_sd);
}
#[test]
fn test_earesult_mult() {
let pop_size = 10u32;
let problem_dim = 5u32;
let problem = SphereProblem{};
let gen_count = 10u32;
let ress = (0..3).into_iter()
.map(|_ | {
let settings = EASettings::new(pop_size, gen_count, problem_dim);
let mut ga: GA<SphereProblem> = GA::new(&problem);
ga.run(settings).expect("Error during GA run").clone()
})
.collect::<Vec<EAResult<RealCodedIndividual>>>();
let filename = "test_json_earesult_mult.json";
let res = EAResultMultiple::new(&ress);
res.to_json(&filename);
assert!(res.run_count == 3);
assert!(res.min_fitness.len() == gen_count as usize);
assert!(res.min_fitness.iter().zip(res.max_fitness.iter()).all(|(&min_f, &max_f)| min_f <= max_f));
assert!(res.min_fitness.iter().zip(res.avg_fitness_mean.iter()).all(|(&min_f, &avg_f)| min_f <= avg_f));
assert!(res.avg_fitness_sd.iter().all(|&f| f >= 0f32));
assert!(res.min_fitness[(gen_count-1) as usize] == res.best.fitness);
}
}