Implement grid search

README.md

@@ -1,6 +1,6 @@
 # optimizer
 
-A Rust library for black-box optimization using Tree-Parzen Estimator (TPE).
+A Rust library for black-box optimization with multiple sampling strategies.
 
 [![Docs](https://docs.rs/optimizer/badge.svg)](https://docs.rs/optimizer)
 [![Crates.io](https://img.shields.io/crates/v/optimizer.svg)](https://crates.io/crates/optimizer)
@@ -9,6 +9,10 @@ A Rust library for black-box optimization using Tree-Parzen Estimator (TPE).
 ## Features
 
 - Optuna-like API for hyperparameter optimization
+- Multiple sampling strategies:
+  - **Random Search** - Simple random sampling for baseline comparisons
+  - **TPE (Tree-Parzen Estimator)** - Bayesian optimization for efficient search
+  - **Grid Search** - Exhaustive search over a specified parameter grid
 - Float, integer, and categorical parameter types
 - Log-scale and stepped parameter sampling
 - Sync and async optimization with parallel trial evaluation
@@ -16,9 +20,10 @@ A Rust library for black-box optimization using Tree-Parzen Estimator (TPE).
 ## Quick Start
 
 ```rust
-use optimizer::{Direction, Study, TpeSampler};
+use optimizer::{Direction, Study};
+use optimizer::sampler::tpe::TpeSampler;
 
-let sampler = TpeSampler::builder().seed(42).build();
+let sampler = TpeSampler::builder().seed(42).build().unwrap();
 let study: Study<f64> = Study::with_sampler(Direction::Minimize, sampler);
 
 study
@@ -32,6 +37,50 @@ let best = study.best_trial().unwrap();
 println!("Best value: {} at x={:?}", best.value, best.params);
 ```
 
+## Samplers
+
+### Random Search
+
+```rust
+use optimizer::{Direction, Study};
+use optimizer::sampler::random::RandomSampler;
+
+let study: Study<f64> = Study::with_sampler(
+    Direction::Minimize,
+    RandomSampler::with_seed(42),
+);
+```
+
+### TPE (Tree-Parzen Estimator)
+
+```rust
+use optimizer::{Direction, Study};
+use optimizer::sampler::tpe::TpeSampler;
+
+let sampler = TpeSampler::builder()
+    .gamma(0.15)           // Quantile for good/bad split
+    .n_startup_trials(20)  // Random trials before TPE kicks in
+    .n_ei_candidates(32)   // Candidates to evaluate
+    .seed(42)
+    .build()
+    .unwrap();
+
+let study: Study<f64> = Study::with_sampler(Direction::Minimize, sampler);
+```
+
+### Grid Search
+
+```rust
+use optimizer::{Direction, Study};
+use optimizer::sampler::grid::GridSearchSampler;
+
+let sampler = GridSearchSampler::builder()
+    .n_points_per_param(10)  // Number of points per parameter dimension
+    .build();
+
+let study: Study<f64> = Study::with_sampler(Direction::Minimize, sampler);
+```
+
 ## Feature Flags
 
 - `async` - Enable async optimization methods (requires tokio)