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August 20th 2021, 2:23 am

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vandomej 2021-08-20 02:23:18 -07:00
parent 61786ab303
commit f6de0191cd
6 changed files with 276 additions and 86 deletions
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340
gemla/src/bracket/genetic_node.rs
View file

@ -1,5 +1,5 @@
//! A trait used to interact with the internal state of nodes within the [`Bracket`]
//!
//!
//! [`Bracket`]: crate::bracket::Bracket
use super::genetic_state::GeneticState;
@ -12,21 +12,21 @@ use std::fmt;
/// [`Bracket`]: crate::bracket::Bracket
pub trait GeneticNode {
/// Initializes a new instance of a [`GeneticState`].
///
///
/// # Examples
///
///
/// ```
/// # use gemla::bracket::genetic_node::GeneticNode;
/// #
/// struct Node {
/// pub fit_score: f64,
/// }
///
///
/// impl GeneticNode for Node {
/// fn initialize() -> Result<Box<Self>, String> {
/// Ok(Box::new(Node {fit_score: 0.0}))
/// }
///
///
/// //...
/// #
/// # fn simulate(&mut self, iterations: u64) -> Result<(), String> {
@ -45,7 +45,7 @@ pub trait GeneticNode {
/// # Ok(())
/// # }
/// }
///
///
/// # fn main() -> Result<(), String> {
/// let node = Node::initialize()?;
/// assert_eq!(node.get_fit_score(), 0.0);
@ -66,62 +66,63 @@ pub trait GeneticNode {
/// pub fit_score: f64,
/// //...
/// }
///
///
/// struct Node {
/// pub model: Vec<Model>,
/// pub models: Vec<Model>,
/// //...
/// }
///
/// impl Model {
/// fn fit(&mut self, epochs: u64) -> Result<(), String> {
/// //...
/// # self.fit_score += epochs as f64;
/// # Ok(())
/// # self.fit_score += epochs as f64;
/// # Ok(())
/// }
/// }
///
///
/// impl GeneticNode for Node {
/// # fn initialize() -> Result<Box<Self>, String> {
/// # Ok(Box::new(Node {fit_score: 0.0, model: Model {fit_score: 0.0}}))
/// # Ok(Box::new(Node {models: vec![Model {fit_score: 0.0}]}))
/// # }
/// #
/// //...
///
/// fn simulate(&mut self, iterations: u64) -> Result<(), String> {
/// self.model.fit(iterations)?;
/// self.fit_score = self.model.fit_score;
/// Ok(())
/// }
///
/// fn simulate(&mut self, iterations: u64) -> Result<(), String> {
/// for m in self.models.iter_mut()
/// {
/// m.fit(iterations)?;
/// }
/// Ok(())
/// }
///
/// //...
/// #
/// # fn get_fit_score(&self) -> f64 {
/// # self.fit_score
/// # }
/// #
/// # fn calculate_scores_and_trim(&mut self) -> Result<(), String> {
/// # Ok(())
/// # }
/// #
/// # fn mutate(&mut self) -> Result<(), String> {
/// # Ok(())
/// # }
///
/// # fn get_fit_score(&self) -> f64 {
/// # self.models.iter().max_by(|m1, m2| m1.fit_score.partial_cmp(&m2.fit_score).unwrap()).unwrap().fit_score
/// # }
/// #
/// # fn calculate_scores_and_trim(&mut self) -> Result<(), String> {
/// # Ok(())
/// # }
/// #
/// # fn mutate(&mut self) -> Result<(), String> {
/// # Ok(())
/// # }
/// }
///
///
/// # fn main() -> Result<(), String> {
/// let mut node = Node::initialize()?;
/// (*node).simulate(5)?;
/// # assert_eq!(node.get_fit_score(), 5.0);
/// # Ok(())
/// node.simulate(5)?;
/// assert_eq!(node.get_fit_score(), 5.0);
/// # Ok(())
/// # }
/// ```
/// ```
fn simulate(&mut self, iterations: u64) -> Result<(), String>;
/// Returns a fit score associated with the nodes performance.
/// This will be used by a bracket in order to determine the most successful child.
///
///
/// # Examples
///
/// ```
/// # use gemla::bracket::genetic_node::GeneticNode;
/// #
@ -130,47 +131,242 @@ pub trait GeneticNode {
/// //...
/// }
///
/// impl GeneticNode for Model {
/// # fn initialize() -> Result<Box<Self>, String> {
/// # Ok(Box::new(Model {fit_score: 0.0, model: Model {fit_score: 0.0}}))
/// # }
///
/// struct Node {
/// pub models: Vec<Model>,
/// //...
///
/// # fn simulate(&mut self, iterations: u64) -> Result<(), String> {
/// # self.model.fit(iterations)?;
/// # self.fit_score = self.model.fit_score;
/// # Ok(())
/// # }
/// #
/// #
/// fn get_fit_score(&self) -> f64 {
/// self.fit_score
/// }
///
/// //...
/// #
/// # fn calculate_scores_and_trim(&mut self) -> Result<(), String> {
/// # Ok(())
/// # }
/// #
/// # fn mutate(&mut self) -> Result<(), String> {
/// # Ok(())
/// # }
/// }
///
/// # fn main() -> Result<(), String> {
/// let mut model = Model::initialize()?;
/// assert_eq!(node.get_fit_score(), 0.0);
/// # Ok(())
///
/// # impl Model {
/// # fn fit(&mut self, epochs: u64) -> Result<(), String> {
/// # //...
/// # self.fit_score += epochs as f64;
/// # Ok(())
/// # }
/// # }
/// ```
///
/// impl GeneticNode for Node {
/// # fn initialize() -> Result<Box<Self>, String> {
/// # Ok(Box::new(Node {models: vec![Model {fit_score: 0.0}]}))
/// # }
/// #
/// # //...
/// #
/// # fn simulate(&mut self, iterations: u64) -> Result<(), String> {
/// # for m in self.models.iter_mut()
/// # {
/// # m.fit(iterations)?;
/// # }
/// # Ok(())
/// # }
/// #
/// //...
///
/// fn get_fit_score(&self) -> f64 {
/// self.models.iter().max_by(|m1, m2| m1.fit_score.partial_cmp(&m2.fit_score).unwrap()).unwrap().fit_score
/// }
///
/// //...
/// # fn calculate_scores_and_trim(&mut self) -> Result<(), String> {
/// # Ok(())
/// # }
/// #
/// # fn mutate(&mut self) -> Result<(), String> {
/// # Ok(())
/// # }
/// }
///
/// # fn main() -> Result<(), String> {
/// let mut node = Node::initialize()?;
/// node.simulate(5)?;
/// assert_eq!(node.get_fit_score(), 5.0);
/// # Ok(())
/// # }
/// ```
fn get_fit_score(&self) -> f64;
/// Used when scoring the nodes after simulating and should remove underperforming children.
///
/// # Examples
/// ```
/// # use gemla::bracket::genetic_node::GeneticNode;
/// #
/// struct Model {
/// pub fit_score: f64,
/// //...
/// }
///
/// struct Node {
/// pub models: Vec<Model>,
/// population_size: i64,
/// //...
/// }
///
/// # impl Model {
/// # fn fit(&mut self, epochs: u64) -> Result<(), String> {
/// # //...
/// # self.fit_score += epochs as f64;
/// # Ok(())
/// # }
/// # }
///
/// impl GeneticNode for Node {
/// # fn initialize() -> Result<Box<Self>, String> {
/// # Ok(Box::new(Node {
/// # models: vec![
/// # Model { fit_score: 0.0 },
/// # Model { fit_score: 1.0 },
/// # Model { fit_score: 2.0 },
/// # Model { fit_score: 3.0 },
/// # Model { fit_score: 4.0 },
/// # ],
/// # population_size: 5,
/// # }))
/// # }
/// #
/// # //...
/// #
/// # fn simulate(&mut self, iterations: u64) -> Result<(), String> {
/// # for m in self.models.iter_mut() {
/// # m.fit(iterations)?;
/// # }
/// # Ok(())
/// # }
/// #
/// //...
///
/// # fn get_fit_score(&self) -> f64 {
/// # self.models
/// # .iter()
/// # .max_by(|m1, m2| m1.fit_score.partial_cmp(&m2.fit_score).unwrap())
/// # .unwrap()
/// # .fit_score
/// # }
/// #
/// fn calculate_scores_and_trim(&mut self) -> Result<(), String> {
/// self.models.sort_by(|a, b| a.fit_score.partial_cmp(&b.fit_score).unwrap().reverse());
/// self.models.truncate(3);
/// Ok(())
/// }
///
/// //...
/// #
/// # fn mutate(&mut self) -> Result<(), String> {
/// # Ok(())
/// # }
/// }
///
/// # fn main() -> Result<(), String> {
/// let mut node = Node::initialize()?;
/// assert_eq!(node.models.len(), 5);
///
/// node.simulate(5)?;
/// node.calculate_scores_and_trim()?;
/// assert_eq!(node.models.len(), 3);
///
/// # assert_eq!(node.get_fit_score(), 9.0);
/// # Ok(())
/// # }
/// ```
fn calculate_scores_and_trim(&mut self) -> Result<(), String>;
/// Mutates members in a population and/or crossbreeds them to produce new offspring.
///
/// # Examples
/// ```
/// # use gemla::bracket::genetic_node::GeneticNode;
/// # use std::convert::TryInto;
/// #
/// struct Model {
/// pub fit_score: f64,
/// //...
/// }
///
/// struct Node {
/// pub models: Vec<Model>,
/// population_size: i64,
/// //...
/// }
///
/// # impl Model {
/// # fn fit(&mut self, epochs: u64) -> Result<(), String> {
/// # //...
/// # self.fit_score += epochs as f64;
/// # Ok(())
/// # }
/// # }
///
/// fn mutate_random_individuals(_models: &Vec<Model>) -> Model
/// {
/// //...
/// # Model {
/// # fit_score: 0.0
/// # }
/// }
///
/// impl GeneticNode for Node {
/// # fn initialize() -> Result<Box<Self>, String> {
/// # Ok(Box::new(Node {
/// # models: vec![
/// # Model { fit_score: 0.0 },
/// # Model { fit_score: 1.0 },
/// # Model { fit_score: 2.0 },
/// # Model { fit_score: 3.0 },
/// # Model { fit_score: 4.0 },
/// # ],
/// # population_size: 5,
/// # }))
/// # }
/// #
/// # fn simulate(&mut self, iterations: u64) -> Result<(), String> {
/// # for m in self.models.iter_mut() {
/// # m.fit(iterations)?;
/// # }
/// # Ok(())
/// # }
/// #
/// # fn get_fit_score(&self) -> f64 {
/// # self.models
/// # .iter()
/// # .max_by(|m1, m2| m1.fit_score.partial_cmp(&m2.fit_score).unwrap())
/// # .unwrap()
/// # .fit_score
/// # }
/// #
/// # fn calculate_scores_and_trim(&mut self) -> Result<(), String> {
/// # self.models.sort_by(|a, b| a.fit_score.partial_cmp(&b.fit_score).unwrap().reverse());
/// # self.models.truncate(3);
/// # Ok(())
/// # }
/// //...
///
/// fn mutate(&mut self) -> Result<(), String> {
/// loop {
/// if self.models.len() < self.population_size.try_into().unwrap()
/// {
/// self.models.push(mutate_random_individuals(&self.models))
/// }
/// else{
/// return Ok(());
/// }
/// }
/// }
/// }
///
/// # fn main() -> Result<(), String> {
/// let mut node = Node::initialize()?;
/// assert_eq!(node.models.len(), 5);
///
/// node.simulate(5)?;
/// node.calculate_scores_and_trim()?;
/// assert_eq!(node.models.len(), 3);
///
/// node.mutate()?;
/// assert_eq!(node.models.len(), 5);
///
/// # assert_eq!(node.get_fit_score(), 9.0);
/// # Ok(())
/// # }
/// ```
fn mutate(&mut self) -> Result<(), String>;
}
@ -191,8 +387,8 @@ where
T: GeneticNode + fmt::Debug,
{
/// Initializes a wrapper around a GeneticNode. If the initialization is successful the internal state will be changed to
/// `GeneticState::Simulate` otherwise it will remain as `GeneticState::Initialize` and will attempt to be created in
/// [`process_node`](#method.process_node).
/// `GeneticState::Simulate` otherwise it will remain as `GeneticState::Initialize` and will attempt to be created in
/// [`process_node`](#method.process_node).
///
/// # Examples
/// ```
@ -252,7 +448,7 @@ where
/// Will loop through the node training and scoring process for the given number of `iterations`.
///
/// ## Transitions
/// - `GeneticState::Initialize`: will attempt to call [`initialize`] on the node. When done successfully will change
/// - `GeneticState::Initialize`: will attempt to call [`initialize`] on the node. When done successfully will change
/// the state to `GeneticState::Simulate`
/// - `GeneticState::Simulate`: Will call [`simulate`] with a number of iterations (not for `iterations`). Will change the state to `GeneticState::Score`
/// - `GeneticState::Score`: Will call [`calculate_scores_and_trim`] and when the number of `iterations` have been reached will change

4
gemla/src/bracket/genetic_state.rs
View file

@ -1,11 +1,11 @@
//! An enum used to control the state of a [`GeneticNode`]
//!
//!
//! [`GeneticNode`]: crate::bracket::genetic_node
use serde::{Deserialize, Serialize};
/// An enum used to control the state of a [`GeneticNode`]
///
///
/// [`GeneticNode`]: crate::bracket::genetic_node
#[derive(Clone, Debug, Serialize, Deserialize, Copy)]
#[serde(tag = "enumType", content = "enumContent")]

8
gemla/src/bracket/mod.rs
View file

@ -124,10 +124,9 @@ where
}
#[cfg(test)]
mod tests
{
mod tests {
use super::*;
use serde::{Deserialize, Serialize};
use std::fmt;
use std::str::FromStr;
@ -237,5 +236,4 @@ mod tests
std::fs::remove_file("./temp2").expect("Unable to remove file");
}
}
}

1
gemla/src/file_linked/mod.rs
View file

@ -141,5 +141,4 @@ mod tests {
Ok(())
}
}

2
gemla/src/lib.rs
View file

@ -4,4 +4,4 @@ extern crate regex;
pub mod tree;
pub mod bracket;
pub mod constants;
pub mod file_linked;
pub mod file_linked;

7
gemla/src/tree/mod.rs
View file

@ -23,7 +23,6 @@
//! //# }
//! ```
use serde::de::DeserializeOwned;
use serde::{Deserialize, Serialize};
use std::fmt;
@ -136,10 +135,8 @@ where
}
}
#[cfg(test)]
mod tests
{
mod tests {
use super::*;
#[test]
@ -176,4 +173,4 @@ mod tests
);
assert_eq!(Tree::<i32>::fmt_node(&None), "_");
}
}
}