Adding merge function to TestState
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parent
6d29508b83
commit
87ade09e36
3 changed files with 98 additions and 18 deletions
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@ -1,19 +1,20 @@
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use rand::prelude::*;
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use rand::rngs::ThreadRng;
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use gemla::bracket::genetic_node::GeneticNode;
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use gemla::error;
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use rand::prelude::*;
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use rand::rngs::ThreadRng;
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use std::convert::TryInto;
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const POPULATION_SIZE: u64 = 5;
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const POPULATION_REDUCTION_SIZE: u64 = 3;
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struct TestState {
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pub population: Vec<f64>,
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thread_rng: ThreadRng
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thread_rng: ThreadRng,
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}
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impl GeneticNode for TestState {
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fn initialize() -> Result<Box<Self>, error::Error> {
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let mut thread_rng = rand::thread_rng();
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let mut thread_rng = thread_rng();
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let mut population: Vec<f64> = vec![];
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for _ in 0..POPULATION_SIZE {
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@ -22,28 +23,38 @@ impl GeneticNode for TestState {
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Ok(Box::new(TestState {
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population,
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thread_rng
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thread_rng,
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}))
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}
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fn simulate(&mut self, iterations: u64) -> Result<(), error::Error> {
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for _ in 0..iterations {
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self.population = self.population.clone().iter().map(|p| p + self.thread_rng.gen_range(-10.0..10.0)).collect()
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self.population = self
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.population
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.clone()
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.iter()
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.map(|p| p + self.thread_rng.gen_range(-10.0..10.0))
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.collect()
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}
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Ok(())
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}
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fn get_fit_score(&self) -> f64 {
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self.population.clone().into_iter().reduce(f64::max).unwrap()
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self.population
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.clone()
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.into_iter()
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.reduce(f64::max)
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.unwrap()
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}
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fn calculate_scores_and_trim(&mut self) -> Result<(), error::Error> {
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let mut v = self.population.clone();
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v.sort_by(|a, b| a.partial_cmp(b).unwrap());
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v.reverse();
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self.population = v[4..].to_vec();
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self.population = v[0..(POPULATION_REDUCTION_SIZE as usize)].to_vec();
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Ok(())
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}
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@ -56,7 +67,7 @@ impl GeneticNode for TestState {
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let new_individual_index = self.thread_rng.gen_range(0..self.population.len());
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let mut cross_breed_index = self.thread_rng.gen_range(0..self.population.len());
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loop {
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if new_individual_index != cross_breed_index {
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break;
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@ -67,7 +78,7 @@ impl GeneticNode for TestState {
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let mut new_individual = self.population.clone()[new_individual_index];
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let cross_breed = self.population.clone()[cross_breed_index];
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new_individual += cross_breed + self.thread_rng.gen_range(-10.0..10.0);
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self.population.push(new_individual);
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@ -75,4 +86,23 @@ impl GeneticNode for TestState {
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Ok(())
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}
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}
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fn merge(left: &TestState, right: &TestState) -> Result<Box<TestState>, error::Error> {
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let mut v = left.population.clone();
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v.append(&mut right.population.clone());
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v.sort_by(|a, b| a.partial_cmp(b).unwrap());
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v.reverse();
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v = v[..(POPULATION_REDUCTION_SIZE as usize)].to_vec();
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let mut result = TestState {
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population: v,
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thread_rng: thread_rng(),
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};
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result.mutate()?;
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Ok(Box::new(result))
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}
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}
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@ -43,7 +43,7 @@ pub trait GeneticNode {
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/// }
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///
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/// impl GeneticNode for Node {
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/// fn initialize() -> Result<Box<Self>, Error> {
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/// fn initialize() -> Result<Box<Node>, Error> {
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/// Ok(Box::new(Node {fit_score: 0.0}))
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/// }
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///
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@ -64,6 +64,10 @@ pub trait GeneticNode {
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/// # fn mutate(&mut self) -> Result<(), Error> {
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/// # Ok(())
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/// # }
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/// #
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/// # fn merge(left: &Node, right: &Node) -> Result<Box<Node>, Error> {
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/// # Ok(Box::new(Node {fit_score: 0.0}))
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/// # }
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/// }
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///
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/// # fn main() -> Result<(), Error> {
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@ -102,7 +106,7 @@ pub trait GeneticNode {
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/// }
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///
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/// impl GeneticNode for Node {
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/// # fn initialize() -> Result<Box<Self>, Error> {
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/// # fn initialize() -> Result<Box<Node>, Error> {
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/// # Ok(Box::new(Node {models: vec![Model {fit_score: 0.0}]}))
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/// # }
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/// #
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@ -129,6 +133,10 @@ pub trait GeneticNode {
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/// # fn mutate(&mut self) -> Result<(), Error> {
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/// # Ok(())
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/// # }
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/// #
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/// # fn merge(left: &Node, right: &Node) -> Result<Box<Node>, Error> {
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/// # Ok(Box::new(Node {models: vec![Model {fit_score: 0.0}]}))
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/// # }
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/// }
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///
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/// # fn main() -> Result<(), Error> {
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@ -167,7 +175,7 @@ pub trait GeneticNode {
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/// # }
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///
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/// impl GeneticNode for Node {
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/// # fn initialize() -> Result<Box<Self>, Error> {
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/// # fn initialize() -> Result<Box<Node>, Error> {
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/// # Ok(Box::new(Node {models: vec![Model {fit_score: 0.0}]}))
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/// # }
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/// #
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@ -195,6 +203,10 @@ pub trait GeneticNode {
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/// # fn mutate(&mut self) -> Result<(), Error> {
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/// # Ok(())
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/// # }
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/// #
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/// # fn merge(left: &Node, right: &Node) -> Result<Box<Node>, Error> {
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/// # Ok(Box::new(Node {models: vec![Model {fit_score: 0.0}]}))
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/// # }
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/// }
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///
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/// # fn main() -> Result<(), Error> {
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@ -233,7 +245,7 @@ pub trait GeneticNode {
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/// # }
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///
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/// impl GeneticNode for Node {
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/// # fn initialize() -> Result<Box<Self>, Error> {
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/// # fn initialize() -> Result<Box<Node>, Error> {
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/// # Ok(Box::new(Node {
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/// # models: vec![
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/// # Model { fit_score: 0.0 },
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@ -276,6 +288,10 @@ pub trait GeneticNode {
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/// # fn mutate(&mut self) -> Result<(), Error> {
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/// # Ok(())
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/// # }
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/// #
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/// # fn merge(left: &Node, right: &Node) -> Result<Box<Node>, Error> {
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/// # Ok(Box::new(Node {models: vec![Model {fit_score: 0.0}], population_size: 1}))
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/// # }
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/// }
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///
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/// # fn main() -> Result<(), Error> {
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@ -328,7 +344,7 @@ pub trait GeneticNode {
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/// }
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///
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/// impl GeneticNode for Node {
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/// # fn initialize() -> Result<Box<Self>, Error> {
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/// # fn initialize() -> Result<Box<Node>, Error> {
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/// # Ok(Box::new(Node {
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/// # models: vec![
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/// # Model { fit_score: 0.0 },
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@ -374,6 +390,10 @@ pub trait GeneticNode {
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/// }
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/// }
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/// }
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/// #
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/// # fn merge(left: &Node, right: &Node) -> Result<Box<Node>, Error> {
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/// # Ok(Box::new(Node {models: vec![Model {fit_score: 0.0}], population_size: 1}))
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/// # }
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/// }
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///
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/// # fn main() -> Result<(), Error> {
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@ -392,6 +412,8 @@ pub trait GeneticNode {
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/// # }
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/// ```
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fn mutate(&mut self) -> Result<(), Error>;
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fn merge(left: &Self, right: &Self) -> Result<Box<Self>, Error>;
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}
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/// Used externally to wrap a node implementing the [`GeneticNode`] trait. Processes state transitions for the given node as
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///
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/// impl GeneticNode for Node {
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/// //...
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/// # fn initialize() -> Result<Box<Self>, Error> {
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/// # fn initialize() -> Result<Box<Node>, Error> {
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/// # Ok(Box::new(Node {fit_score: 0.0}))
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/// # }
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/// #
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/// # fn mutate(&mut self) -> Result<(), Error> {
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/// # Ok(())
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/// # }
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/// #
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/// # fn merge(left: &Node, right: &Node) -> Result<Box<Node>, Error> {
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/// # Ok(Box::new(Node {fit_score: 0.0}))
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/// # }
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/// }
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///
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/// # fn main() -> Result<(), Error> {
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/// # fn initialize() -> Result<Box<Self>, Error> {
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/// # Ok(Box::new(TestState { score: 0.0 }))
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/// # }
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/// #
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/// # fn merge(left: &TestState, right: &TestState) -> Result<Box<Self>, Error> {
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/// # Ok(Box::new(left.clone()))
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/// # }
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/// # }
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/// #
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/// # fn main() {
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/// }
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///
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/// //...
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/// #
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/// # fn merge(left: &TestState, right: &TestState) -> Result<Box<Self>, Error> {
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/// # Ok(Box::new(left.clone()))
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/// # }
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/// }
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///
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/// # fn main() {
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/// # fn initialize() -> Result<Box<Self>, Error> {
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/// # Ok(Box::new(TestState { score: 0.0 }))
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/// # }
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/// #
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/// # fn merge(left: &TestState, right: &TestState) -> Result<Box<Self>, Error> {
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/// # Ok(Box::new(left.clone()))
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/// # }
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/// # }
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/// #
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/// # fn main() {
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/// # fn initialize() -> Result<Box<Self>, Error> {
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/// # Ok(Box::new(TestState { score: 0.0 }))
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/// # }
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/// #
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/// # fn merge(left: &TestState, right: &TestState) -> Result<Box<Self>, Error> {
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/// # Ok(Box::new(left.clone()))
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/// # }
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/// # }
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/// #
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/// # fn main() {
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Ok(())
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}
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fn initialize() -> Result<Box<Self>, Error> {
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fn initialize() -> Result<Box<TestState>, Error> {
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Ok(Box::new(TestState { score: 0.0 }))
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}
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fn merge(left: &TestState, right: &TestState) -> Result<Box<TestState>, Error> {
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Ok(Box::new(if left.get_fit_score() > right.get_fit_score() {
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left.clone()
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} else {
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right.clone()
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}))
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}
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}
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#[test]
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