Update 1.0.0

.github/workflows/ci-cd.yml

@@ -2,7 +2,7 @@ name: CI-CD
 
 on:
     push:
-        branches: [main]
+        branches: [main, dev]
     pull_request: 
 
 jobs:

.gitignore

@@ -1,2 +1,4 @@
 /target/
-/.vscode/
+/.vscode/
+best-agent.json
+fitness-plot.svg

CONTRIBUTING.md

@@ -0,0 +1,7 @@
+Thanks for contributing to this project.
+
+To get started, check out the [issues page](https://github.com/hypercodec/neat). You can either find a feature/fix from there or start a new issue, then begin implementing it in your own fork of this repo.
+
+Once you are done making the changes you'd like the make, start a pull request to the [dev](https://github.com/hypercodec/neat/tree/dev) branch. State your changes and request a review. After all branch rules have been satisfied and the pull request has a valid reason, someone with management permissions on this repository will merge it.
+
+You could also make a draft PR while implementing your features if you want feedback or discussion before finalizing your changes.

Cargo.toml

@@ -3,9 +3,9 @@ name = "neat"
 description = "Crate for working with NEAT in rust"
 version = "0.5.1"
 edition = "2021"
-authors = ["Inflectrix"]
-repository = "https://github.com/inflectrix/neat"
-homepage = "https://github.com/inflectrix/neat"
+authors = ["HyperCodec"]
+repository = "https://github.com/HyperCodec/neat"
+homepage = "https://github.com/HyperCodec/neat"
 readme = "README.md"
 keywords = ["genetic", "machine-learning", "ai", "algorithm", "evolution"]
 categories = ["algorithms", "science", "simulation"]
@@ -18,22 +18,19 @@ rustdoc-args = ["--cfg", "docsrs"]
 # See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
 
 [features]
-default = ["max-index"]
-crossover = ["genetic-rs/crossover"]
-rayon = ["genetic-rs/rayon", "dep:rayon"]
-max-index = []
+default = []
 serde = ["dep:serde", "dep:serde-big-array"]
 
 
 [dependencies]
-bitflags = "2.5.0"
-genetic-rs = { version = "0.5.1", features = ["derive"] }
-lazy_static = "1.4.0"
-rand = "0.8.5"
-rayon = { version = "1.8.1", optional = true }
-serde = { version = "1.0.197", features = ["derive"], optional = true }
+atomic_float = "1.1.0"
+bitflags = "2.8.0"
+genetic-rs = { version = "0.5.4", features = ["rayon", "derive"] }
+lazy_static = "1.5.0"
+rayon = "1.10.0"
+replace_with = "0.1.7"
+serde = { version = "1.0.217", features = ["derive"], optional = true }
 serde-big-array = { version = "0.5.1", optional = true }
 
 [dev-dependencies]
-bincode = "1.3.3"
-serde_json = "1.0.114"
+serde_json = "1.0.138"

README.md

@@ -1,102 +1,17 @@
 # neat
-[<img alt="github" src="https://img.shields.io/github/last-commit/inflectrix/neat" height="20">](https://github.com/inflectrix/neat)
+[<img alt="github" src="https://img.shields.io/github/last-commit/hypercodec/neat" height="20">](https://github.com/hypercodec/neat)
 [<img alt="crates.io" src="https://img.shields.io/crates/d/neat" height="20">](https://crates.io/crates/neat)
 [<img alt="docs.rs" src="https://img.shields.io/docsrs/neat" height="20">](https://docs.rs/neat)
 
 Implementation of the NEAT algorithm using `genetic-rs`.
 
 ### Features
-- rayon - Uses parallelization on the `NeuralNetwork` struct and adds the `rayon` feature to the `genetic-rs` re-export.
-- serde - Adds the NNTSerde struct and allows for serialization of `NeuralNetworkTopology`
-- crossover - Implements the `CrossoverReproduction` trait on `NeuralNetworkTopology` and adds the `crossover` feature to the `genetic-rs` re-export.
+- serde - Implements `Serialize` and `Deserialize` on most of the types in this crate.
 
-*Do you like this repo and want to support it? If so, leave a ⭐*
+*Do you like this crate and want to support it? If so, leave a ⭐*
 
-### How To Use
-When working with this crate, you'll want to use the `NeuralNetworkTopology` struct in your agent's DNA and
-the use `NeuralNetwork::from` when you finally want to test its performance. The `genetic-rs` crate is also re-exported with the rest of this crate.
-
-Here's an example of how one might use this crate:
-```rust
-use neat::*;
-
-#[derive(Clone, RandomlyMutable, DivisionReproduction)]
-struct MyAgentDNA {
-    network: NeuralNetworkTopology<1, 2>,
-}
-
-impl GenerateRandom for MyAgentDNA {
-    fn gen_random(rng: &mut impl rand::Rng) -> Self {
-        Self {
-            network: NeuralNetworkTopology::new(0.01, 3, rng),
-        }
-    }
-}
-
-struct MyAgent {
-    network: NeuralNetwork<1, 2>,
-    // ... other state
-}
-
-impl From<&MyAgentDNA> for MyAgent {
-    fn from(value: &MyAgentDNA) -> Self {
-        Self {
-            network: NeuralNetwork::from(&value.network),
-        }
-    }
-}
-
-fn fitness(dna: &MyAgentDNA) -> f32 {
-    // agent will simply try to predict whether a number is greater than 0.5
-    let mut agent = MyAgent::from(dna);
-    let mut rng = rand::thread_rng();
-    let mut fitness = 0;
-
-    // use repeated tests to avoid situational bias and some local maximums, overall providing more accurate score
-    for _ in 0..10 {
-        let n = rng.gen::<f32>();
-        let above = n > 0.5;
-
-        let res = agent.network.predict([n]);
-        let resi = res.iter().max_index();
-
-        if resi == 0 ^ above {
-            // agent did not guess correctly, punish slightly (too much will hinder exploration)
-            fitness -= 0.5;
-
-            continue;
-        }
-
-        // agent guessed correctly, they become more fit.
-        fitness += 3.;
-    }
-
-    fitness
-}
-
-fn main() {
-    let mut rng = rand::thread_rng();
-
-    let mut sim = GeneticSim::new(
-        Vec::gen_random(&mut rng, 100),
-        fitness,
-        division_pruning_nextgen,
-    );
-
-    // simulate 100 generations
-    for _ in 0..100 {
-        sim.next_generation();
-    }
-
-    // display fitness results
-    let fits: Vec<_> = sim.entities
-        .iter()
-        .map(fitness)
-        .collect();
-
-    dbg!(&fits, fits.iter().max());
-}
-```
+# How To Use
+TODO
 
 ### License
 This crate falls under the `MIT` license