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 swaits
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8cf518200a
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swaits
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41122b7d48
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+44
-1
@@ -7,6 +7,49 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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## [Unreleased]
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## [Unreleased]
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### Added
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- **`heuropt-plot` companion crate (v0.1.0)** at `heuropt-plot/`,
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published independently. Lightweight SVG-only plotter for Pareto
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fronts (`pareto_front_svg`) and convergence traces
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(`convergence_svg`) — hand-rolled SVG output, no `plotters` /
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`tiny-skia` dep so the crate stays a tiny optional addition.
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- `examples/visualize.rs` — runs NSGA-II on Schaffer N.1 with a
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closure observer that records hypervolume per generation, then
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emits `pareto_front.svg` + `convergence.svg` via `heuropt-plot`.
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## [0.7.0] — 2026-05-05
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Theme: async evaluation. heuropt now supports problems where each
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evaluation is a `.await`-able operation — HTTP services, RPC clients,
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spawned subprocesses. This is the differentiating capability vs.
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pymoo / hyperopt / MOEA Framework, none of which ship first-class
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async support.
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No public-API breaks for synchronous users. The new surface is
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gated behind a new `async` feature flag.
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### Added
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- New optional feature `async`, gated on
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[`futures`](https://crates.io/crates/futures).
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- `core::async_problem::AsyncProblem` trait — mirrors `Problem` but
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with `async fn evaluate_async(&self, decision)`. Adapt an
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existing sync `Problem` with a one-line wrapper.
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- Per-algorithm `run_async(&problem, concurrency).await` methods on
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`RandomSearch` and `DifferentialEvolution` — drives evaluations
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through whichever async runtime the caller is using (typically
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tokio). `concurrency` bounds in-flight evaluations.
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- Internal `algorithms::parallel_eval_async::evaluate_batch_async`
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helper — uses `futures::stream::FuturesOrdered` with concurrency-
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bounded chunks, preserves input order so seeded determinism is
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preserved when evaluations are themselves deterministic.
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- `examples/async_eval.rs` — worked example with a simulated 20 ms
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remote service. At concurrency = 1 it's serial; at concurrency = 4
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it's 2× faster; demonstrates DifferentialEvolution under tokio.
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[0.7.0]: https://github.com/swaits/heuropt/releases/tag/v0.7.0
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## [0.6.0] — 2026-05-05
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## [0.6.0] — 2026-05-05
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Theme: production lifecycle. heuropt becomes deployable for long-
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Theme: production lifecycle. heuropt becomes deployable for long-
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@@ -542,5 +585,5 @@ Initial release.
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`RandomSearch`, `Nsga2`, and `DifferentialEvolution`. Seeded runs stay
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`RandomSearch`, `Nsga2`, and `DifferentialEvolution`. Seeded runs stay
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bit-identical to serial mode.
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bit-identical to serial mode.
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[Unreleased]: https://github.com/swaits/heuropt/compare/v0.6.0...HEAD
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[Unreleased]: https://github.com/swaits/heuropt/compare/v0.7.0...HEAD
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[0.1.0]: https://github.com/swaits/heuropt/releases/tag/v0.1.0
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[0.1.0]: https://github.com/swaits/heuropt/releases/tag/v0.1.0
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+12
-1
@@ -1,6 +1,9 @@
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[workspace]
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members = [".", "heuropt-plot"]
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[package]
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[package]
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name = "heuropt"
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name = "heuropt"
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version = "0.6.0"
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version = "0.7.0"
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edition = "2024"
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edition = "2024"
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rust-version = "1.85"
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rust-version = "1.85"
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authors = ["Stephen Waits <steve@waits.net>"]
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authors = ["Stephen Waits <steve@waits.net>"]
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@@ -18,8 +21,10 @@ default = []
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serde = ["dep:serde"]
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serde = ["dep:serde"]
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parallel = ["dep:rayon"]
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parallel = ["dep:rayon"]
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tracing = ["dep:tracing"]
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tracing = ["dep:tracing"]
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async = ["dep:futures"]
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[dependencies]
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[dependencies]
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futures = { version = "0.3", optional = true, default-features = false, features = ["std", "async-await"] }
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rand = "0.9"
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rand = "0.9"
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rand_distr = "0.5"
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rand_distr = "0.5"
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rayon = { version = "1", optional = true }
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rayon = { version = "1", optional = true }
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@@ -28,12 +33,18 @@ tracing = { version = "0.1", optional = true, default-features = false, features
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[dev-dependencies]
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[dev-dependencies]
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gungraun = "0.18"
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gungraun = "0.18"
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heuropt-plot = { path = "heuropt-plot" }
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proptest = "1"
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proptest = "1"
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tokio = { version = "1", features = ["rt-multi-thread", "macros", "time"] }
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[[bench]]
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[[bench]]
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name = "hot_paths"
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name = "hot_paths"
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harness = false
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harness = false
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[[example]]
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name = "async_eval"
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required-features = ["async"]
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# Tighten release codegen for the compare harness and downstream binaries
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# Tighten release codegen for the compare harness and downstream binaries
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# that build heuropt directly (i.e. when this crate is the workspace root).
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# that build heuropt directly (i.e. when this crate is the workspace root).
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# When heuropt is used as a dependency the consumer's profile wins.
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# When heuropt is used as a dependency the consumer's profile wins.
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@@ -0,0 +1,26 @@
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</svg>
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After Width: | Height: | Size: 3.1 KiB |
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||||||
|
<circle cx="414.47" cy="378.59" r="3" fill="#1f77b4" stroke="#0d4a8a" stroke-width="0.5" />
|
||||||
|
<circle cx="616.88" cy="399.02" r="3" fill="#1f77b4" stroke="#0d4a8a" stroke-width="0.5" />
|
||||||
|
<circle cx="419.20" cy="379.46" r="3" fill="#1f77b4" stroke="#0d4a8a" stroke-width="0.5" />
|
||||||
|
</svg>
|
||||||
|
After Width: | Height: | Size: 6.2 KiB |
@@ -0,0 +1,84 @@
|
|||||||
|
//! Async evaluation example: optimize hyperparameters where each
|
||||||
|
//! evaluation is an awaitable (simulated HTTP) call.
|
||||||
|
//!
|
||||||
|
//! Demonstrates:
|
||||||
|
//! - Implementing [`AsyncProblem`].
|
||||||
|
//! - Driving the optimizer through `tokio` with bounded concurrency.
|
||||||
|
//! - Comparing wall-clock time at concurrency = 1 vs 8.
|
||||||
|
//!
|
||||||
|
//! Run with: `cargo run --release --features async --example async_eval`
|
||||||
|
|
||||||
|
use std::time::Instant;
|
||||||
|
|
||||||
|
use heuropt::core::async_problem::AsyncProblem;
|
||||||
|
use heuropt::prelude::*;
|
||||||
|
|
||||||
|
struct RemoteService;
|
||||||
|
|
||||||
|
impl AsyncProblem for RemoteService {
|
||||||
|
type Decision = Vec<f64>;
|
||||||
|
|
||||||
|
fn objectives(&self) -> ObjectiveSpace {
|
||||||
|
ObjectiveSpace::new(vec![Objective::minimize("loss")])
|
||||||
|
}
|
||||||
|
|
||||||
|
async fn evaluate_async(&self, x: &Vec<f64>) -> Evaluation {
|
||||||
|
// Simulate a 20 ms remote-service round-trip per evaluation.
|
||||||
|
// The compute itself is ~free; the latency is the bottleneck.
|
||||||
|
tokio::time::sleep(std::time::Duration::from_millis(20)).await;
|
||||||
|
let loss: f64 = x.iter().map(|v| v * v).sum();
|
||||||
|
Evaluation::new(vec![loss])
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
#[tokio::main]
|
||||||
|
async fn main() {
|
||||||
|
let bounds = vec![(-1.0_f64, 1.0_f64); 4];
|
||||||
|
let problem = RemoteService;
|
||||||
|
|
||||||
|
println!("RandomSearch with 200 evaluations (20 ms each)");
|
||||||
|
println!();
|
||||||
|
|
||||||
|
for &concurrency in &[1_usize, 4, 16] {
|
||||||
|
let mut opt = RandomSearch::new(
|
||||||
|
RandomSearchConfig {
|
||||||
|
iterations: 100,
|
||||||
|
batch_size: 2,
|
||||||
|
seed: 42,
|
||||||
|
},
|
||||||
|
RealBounds::new(bounds.clone()),
|
||||||
|
);
|
||||||
|
let started = Instant::now();
|
||||||
|
let result = opt.run_async(&problem, concurrency).await;
|
||||||
|
let elapsed = started.elapsed();
|
||||||
|
println!(
|
||||||
|
"concurrency = {:>2} elapsed = {:>5} ms best loss = {:>8.5} evaluations = {}",
|
||||||
|
concurrency,
|
||||||
|
elapsed.as_millis(),
|
||||||
|
result.best.unwrap().evaluation.objectives[0],
|
||||||
|
result.evaluations,
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
println!();
|
||||||
|
println!("DifferentialEvolution at concurrency=8");
|
||||||
|
let started = Instant::now();
|
||||||
|
let mut de = DifferentialEvolution::new(
|
||||||
|
DifferentialEvolutionConfig {
|
||||||
|
population_size: 8,
|
||||||
|
generations: 10,
|
||||||
|
differential_weight: 0.5,
|
||||||
|
crossover_probability: 0.9,
|
||||||
|
seed: 42,
|
||||||
|
},
|
||||||
|
RealBounds::new(bounds.clone()),
|
||||||
|
);
|
||||||
|
let result = de.run_async(&problem, 8).await;
|
||||||
|
let elapsed = started.elapsed();
|
||||||
|
println!(
|
||||||
|
"elapsed = {:>5} ms best loss = {:>8.5} evaluations = {}",
|
||||||
|
elapsed.as_millis(),
|
||||||
|
result.best.unwrap().evaluation.objectives[0],
|
||||||
|
result.evaluations,
|
||||||
|
);
|
||||||
|
}
|
||||||
@@ -0,0 +1,89 @@
|
|||||||
|
//! Visualize an NSGA-II run on Schaffer N.1 — produces two SVGs:
|
||||||
|
//! `pareto_front.svg` (scatter plot of the final front) and
|
||||||
|
//! `convergence.svg` (best-so-far hypervolume per generation).
|
||||||
|
//!
|
||||||
|
//! Uses the `heuropt-plot` companion crate plus the v0.6 observer
|
||||||
|
//! API (`Periodic`) to record per-generation hypervolume into a Vec
|
||||||
|
//! during the run.
|
||||||
|
//!
|
||||||
|
//! Run with: `cargo run --release --example visualize`
|
||||||
|
|
||||||
|
use std::cell::RefCell;
|
||||||
|
use std::ops::ControlFlow;
|
||||||
|
|
||||||
|
use heuropt::metrics::hypervolume_2d;
|
||||||
|
use heuropt::prelude::*;
|
||||||
|
use heuropt_plot::{convergence_svg, pareto_front_svg};
|
||||||
|
|
||||||
|
struct Schaffer;
|
||||||
|
|
||||||
|
impl Problem for Schaffer {
|
||||||
|
type Decision = Vec<f64>;
|
||||||
|
fn objectives(&self) -> ObjectiveSpace {
|
||||||
|
ObjectiveSpace::new(vec![Objective::minimize("f1"), Objective::minimize("f2")])
|
||||||
|
}
|
||||||
|
fn evaluate(&self, x: &Vec<f64>) -> Evaluation {
|
||||||
|
Evaluation::new(vec![x[0] * x[0], (x[0] - 2.0).powi(2)])
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
fn main() {
|
||||||
|
let problem = Schaffer;
|
||||||
|
let bounds = vec![(-5.0_f64, 5.0_f64)];
|
||||||
|
let space = problem.objectives();
|
||||||
|
let ref_point = [10.0, 10.0];
|
||||||
|
|
||||||
|
// Per-generation hypervolume trace, recorded by the observer.
|
||||||
|
let history: RefCell<Vec<f64>> = RefCell::new(Vec::new());
|
||||||
|
|
||||||
|
let mut recorder = |snap: &Snapshot<'_, Vec<f64>>| -> ControlFlow<()> {
|
||||||
|
let hv = match snap.pareto_front {
|
||||||
|
Some(front) => hypervolume_2d(front, snap.objectives, ref_point),
|
||||||
|
None => 0.0,
|
||||||
|
};
|
||||||
|
history.borrow_mut().push(hv);
|
||||||
|
ControlFlow::Continue(())
|
||||||
|
};
|
||||||
|
|
||||||
|
let mut opt = Nsga2::new(
|
||||||
|
Nsga2Config {
|
||||||
|
population_size: 50,
|
||||||
|
generations: 100,
|
||||||
|
seed: 42,
|
||||||
|
},
|
||||||
|
RealBounds::new(bounds.clone()),
|
||||||
|
CompositeVariation {
|
||||||
|
crossover: SimulatedBinaryCrossover::new(bounds.clone(), 15.0, 0.5),
|
||||||
|
mutation: PolynomialMutation::new(bounds, 20.0, 1.0),
|
||||||
|
},
|
||||||
|
);
|
||||||
|
|
||||||
|
let result = opt.run_with(&problem, &mut recorder);
|
||||||
|
|
||||||
|
let front_svg = pareto_front_svg(
|
||||||
|
&result.pareto_front,
|
||||||
|
&space,
|
||||||
|
700,
|
||||||
|
450,
|
||||||
|
"NSGA-II on Schaffer N.1 — final Pareto front",
|
||||||
|
);
|
||||||
|
std::fs::write("pareto_front.svg", front_svg).expect("write pareto_front.svg");
|
||||||
|
|
||||||
|
let trace = history.borrow();
|
||||||
|
let conv_svg = convergence_svg(
|
||||||
|
&trace,
|
||||||
|
700,
|
||||||
|
450,
|
||||||
|
"NSGA-II on Schaffer N.1 — hypervolume per generation",
|
||||||
|
"hypervolume",
|
||||||
|
false, // higher is better
|
||||||
|
);
|
||||||
|
std::fs::write("convergence.svg", conv_svg).expect("write convergence.svg");
|
||||||
|
|
||||||
|
println!("Final front size: {}", result.pareto_front.len());
|
||||||
|
println!(
|
||||||
|
"Final hypervolume: {:.4}",
|
||||||
|
trace.last().copied().unwrap_or(0.0)
|
||||||
|
);
|
||||||
|
println!("Wrote pareto_front.svg and convergence.svg");
|
||||||
|
}
|
||||||
@@ -0,0 +1,17 @@
|
|||||||
|
[package]
|
||||||
|
name = "heuropt-plot"
|
||||||
|
version = "0.1.0"
|
||||||
|
edition = "2024"
|
||||||
|
rust-version = "1.85"
|
||||||
|
authors = ["Stephen Waits <steve@waits.net>"]
|
||||||
|
description = "Lightweight SVG visualization for heuropt Pareto fronts and convergence traces."
|
||||||
|
license = "MIT"
|
||||||
|
readme = "README.md"
|
||||||
|
repository = "https://github.com/swaits/heuropt"
|
||||||
|
homepage = "https://github.com/swaits/heuropt"
|
||||||
|
documentation = "https://docs.rs/heuropt-plot"
|
||||||
|
keywords = ["optimization", "pareto", "svg", "plotting", "heuropt"]
|
||||||
|
categories = ["algorithms", "visualization"]
|
||||||
|
|
||||||
|
[dependencies]
|
||||||
|
heuropt = { version = "0.7", path = ".." }
|
||||||
@@ -0,0 +1,46 @@
|
|||||||
|
# heuropt-plot
|
||||||
|
|
||||||
|
[](https://crates.io/crates/heuropt-plot)
|
||||||
|
[](https://docs.rs/heuropt-plot)
|
||||||
|
[](../LICENSE)
|
||||||
|
|
||||||
|
Lightweight SVG plotting helpers for [`heuropt`](https://crates.io/crates/heuropt)
|
||||||
|
results.
|
||||||
|
|
||||||
|
Hand-rolled SVG output (no `plotters`, no `tiny-skia`, no
|
||||||
|
heavyweight dependency) so adding `heuropt-plot` to your project
|
||||||
|
costs ~20 KB of compiled code.
|
||||||
|
|
||||||
|
## What's in the box
|
||||||
|
|
||||||
|
- `pareto_front_svg` — render a 2-objective Pareto front as an SVG
|
||||||
|
scatter plot with axes and labels.
|
||||||
|
- `convergence_svg` — render a "best fitness so far" trace as an
|
||||||
|
SVG line plot.
|
||||||
|
|
||||||
|
Output is a `String` of valid SVG. Write it to a file, embed it in
|
||||||
|
HTML, or pipe it to a browser.
|
||||||
|
|
||||||
|
## Example
|
||||||
|
|
||||||
|
```rust
|
||||||
|
use heuropt::prelude::*;
|
||||||
|
use heuropt_plot::pareto_front_svg;
|
||||||
|
|
||||||
|
let space = ObjectiveSpace::new(vec![
|
||||||
|
Objective::minimize("f1"),
|
||||||
|
Objective::minimize("f2"),
|
||||||
|
]);
|
||||||
|
let front = vec![
|
||||||
|
Candidate::new((), Evaluation::new(vec![0.0, 1.0])),
|
||||||
|
Candidate::new((), Evaluation::new(vec![0.5, 0.5])),
|
||||||
|
Candidate::new((), Evaluation::new(vec![1.0, 0.0])),
|
||||||
|
];
|
||||||
|
|
||||||
|
let svg = pareto_front_svg(&front, &space, 600, 400, "Sample front");
|
||||||
|
std::fs::write("front.svg", svg).unwrap();
|
||||||
|
```
|
||||||
|
|
||||||
|
## License
|
||||||
|
|
||||||
|
MIT — see [LICENSE](../LICENSE) at the repo root.
|
||||||
@@ -0,0 +1,368 @@
|
|||||||
|
//! Lightweight SVG plotting helpers for `heuropt` results.
|
||||||
|
//!
|
||||||
|
//! Two core primitives:
|
||||||
|
//!
|
||||||
|
//! - [`pareto_front_svg`] — render a 2-objective Pareto front as an
|
||||||
|
//! SVG scatter plot with axes and labels.
|
||||||
|
//! - [`convergence_svg`] — render a per-generation "best-fitness so
|
||||||
|
//! far" trace as an SVG line plot.
|
||||||
|
//!
|
||||||
|
//! Hand-rolled SVG output (no `plotters` / `tiny-skia` dep) so the
|
||||||
|
//! crate stays a tiny optional dependency. Output is a `String` of
|
||||||
|
//! valid SVG — write it to a file, embed it in HTML, or pipe it to a
|
||||||
|
//! browser.
|
||||||
|
//!
|
||||||
|
//! # Example
|
||||||
|
//!
|
||||||
|
//! ```
|
||||||
|
//! use heuropt::prelude::*;
|
||||||
|
//! use heuropt_plot::pareto_front_svg;
|
||||||
|
//!
|
||||||
|
//! let space = ObjectiveSpace::new(vec![
|
||||||
|
//! Objective::minimize("f1"),
|
||||||
|
//! Objective::minimize("f2"),
|
||||||
|
//! ]);
|
||||||
|
//! let front = vec![
|
||||||
|
//! Candidate::new((), Evaluation::new(vec![0.0, 1.0])),
|
||||||
|
//! Candidate::new((), Evaluation::new(vec![0.5, 0.5])),
|
||||||
|
//! Candidate::new((), Evaluation::new(vec![1.0, 0.0])),
|
||||||
|
//! ];
|
||||||
|
//! let svg = pareto_front_svg(&front, &space, 600, 400, "Sample front");
|
||||||
|
//! assert!(svg.starts_with("<svg"));
|
||||||
|
//! assert!(svg.contains("</svg>"));
|
||||||
|
//! ```
|
||||||
|
|
||||||
|
use std::fmt::Write as _;
|
||||||
|
|
||||||
|
use heuropt::core::candidate::Candidate;
|
||||||
|
use heuropt::core::objective::ObjectiveSpace;
|
||||||
|
|
||||||
|
/// Render a 2-objective Pareto front as an SVG scatter plot.
|
||||||
|
///
|
||||||
|
/// `width` and `height` are the SVG viewport dimensions in pixels.
|
||||||
|
/// `title` is rendered at the top.
|
||||||
|
///
|
||||||
|
/// Points are plotted in minimization-oriented coordinates.
|
||||||
|
///
|
||||||
|
/// # Panics
|
||||||
|
///
|
||||||
|
/// If `objectives.len() != 2`.
|
||||||
|
pub fn pareto_front_svg<D>(
|
||||||
|
front: &[Candidate<D>],
|
||||||
|
objectives: &ObjectiveSpace,
|
||||||
|
width: u32,
|
||||||
|
height: u32,
|
||||||
|
title: &str,
|
||||||
|
) -> String {
|
||||||
|
assert_eq!(
|
||||||
|
objectives.len(),
|
||||||
|
2,
|
||||||
|
"pareto_front_svg requires exactly 2 objectives",
|
||||||
|
);
|
||||||
|
let oriented: Vec<[f64; 2]> = front
|
||||||
|
.iter()
|
||||||
|
.map(|c| {
|
||||||
|
let m = objectives.as_minimization(&c.evaluation.objectives);
|
||||||
|
[m[0], m[1]]
|
||||||
|
})
|
||||||
|
.collect();
|
||||||
|
let (xs_label, ys_label) = (
|
||||||
|
objectives.objectives[0].name.as_str(),
|
||||||
|
objectives.objectives[1].name.as_str(),
|
||||||
|
);
|
||||||
|
|
||||||
|
let (xmin, xmax) = bounds(oriented.iter().map(|p| p[0]));
|
||||||
|
let (ymin, ymax) = bounds(oriented.iter().map(|p| p[1]));
|
||||||
|
let xspan = (xmax - xmin).max(1e-12);
|
||||||
|
let yspan = (ymax - ymin).max(1e-12);
|
||||||
|
|
||||||
|
// Margins so axes/labels have room.
|
||||||
|
let m_left = 60.0_f64;
|
||||||
|
let m_right = 20.0_f64;
|
||||||
|
let m_top = 40.0_f64;
|
||||||
|
let m_bot = 50.0_f64;
|
||||||
|
let plot_w = width as f64 - m_left - m_right;
|
||||||
|
let plot_h = height as f64 - m_top - m_bot;
|
||||||
|
|
||||||
|
let to_x = |v: f64| m_left + (v - xmin) / xspan * plot_w;
|
||||||
|
// Y is inverted: lower minimization value → higher pixel.
|
||||||
|
let to_y = |v: f64| m_top + plot_h - (v - ymin) / yspan * plot_h;
|
||||||
|
|
||||||
|
let mut out = String::new();
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
"<svg xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 {width} {height}\" \
|
||||||
|
font-family=\"system-ui, sans-serif\" font-size=\"12\">",
|
||||||
|
);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <rect x=\"0\" y=\"0\" width=\"{width}\" height=\"{height}\" fill=\"white\"/>",
|
||||||
|
);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <text x=\"{x}\" y=\"22\" font-size=\"16\" font-weight=\"bold\">{title}</text>",
|
||||||
|
x = m_left,
|
||||||
|
title = escape_xml(title),
|
||||||
|
);
|
||||||
|
|
||||||
|
// Axes box.
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <rect x=\"{}\" y=\"{}\" width=\"{}\" height=\"{}\" fill=\"none\" stroke=\"#888\" />",
|
||||||
|
m_left, m_top, plot_w, plot_h,
|
||||||
|
);
|
||||||
|
|
||||||
|
// X-axis ticks (3 ticks).
|
||||||
|
for i in 0..=3 {
|
||||||
|
let t = i as f64 / 3.0;
|
||||||
|
let v = xmin + t * xspan;
|
||||||
|
let x = to_x(v);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <line x1=\"{x}\" y1=\"{y0}\" x2=\"{x}\" y2=\"{y1}\" stroke=\"#888\" />",
|
||||||
|
y0 = m_top + plot_h,
|
||||||
|
y1 = m_top + plot_h + 5.0,
|
||||||
|
);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <text x=\"{x}\" y=\"{y}\" text-anchor=\"middle\">{v:.3}</text>",
|
||||||
|
y = m_top + plot_h + 18.0,
|
||||||
|
);
|
||||||
|
}
|
||||||
|
// Y-axis ticks.
|
||||||
|
for i in 0..=3 {
|
||||||
|
let t = i as f64 / 3.0;
|
||||||
|
let v = ymin + t * yspan;
|
||||||
|
let y = to_y(v);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <line x1=\"{x0}\" y1=\"{y}\" x2=\"{x1}\" y2=\"{y}\" stroke=\"#888\" />",
|
||||||
|
x0 = m_left - 5.0,
|
||||||
|
x1 = m_left,
|
||||||
|
);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <text x=\"{x}\" y=\"{y}\" text-anchor=\"end\" dominant-baseline=\"middle\">{v:.3}</text>",
|
||||||
|
x = m_left - 8.0,
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
// Axis labels.
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <text x=\"{x}\" y=\"{y}\" text-anchor=\"middle\">{xs_label}</text>",
|
||||||
|
x = m_left + plot_w / 2.0,
|
||||||
|
y = height as f64 - 12.0,
|
||||||
|
xs_label = escape_xml(xs_label),
|
||||||
|
);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <text x=\"15\" y=\"{y}\" text-anchor=\"middle\" \
|
||||||
|
transform=\"rotate(-90 15 {y})\">{ys_label}</text>",
|
||||||
|
y = m_top + plot_h / 2.0,
|
||||||
|
ys_label = escape_xml(ys_label),
|
||||||
|
);
|
||||||
|
|
||||||
|
// Points.
|
||||||
|
for p in &oriented {
|
||||||
|
let cx = to_x(p[0]);
|
||||||
|
let cy = to_y(p[1]);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <circle cx=\"{cx:.2}\" cy=\"{cy:.2}\" r=\"3\" fill=\"#1f77b4\" \
|
||||||
|
stroke=\"#0d4a8a\" stroke-width=\"0.5\" />",
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
out.push_str("</svg>");
|
||||||
|
out
|
||||||
|
}
|
||||||
|
|
||||||
|
/// Render a per-generation "best fitness so far" trace as an SVG line
|
||||||
|
/// plot. `bests[i]` is the best fitness *after* generation `i`.
|
||||||
|
///
|
||||||
|
/// `direction_minimize` controls which way is "improvement": `true`
|
||||||
|
/// for minimize problems, `false` for maximize.
|
||||||
|
pub fn convergence_svg(
|
||||||
|
bests: &[f64],
|
||||||
|
width: u32,
|
||||||
|
height: u32,
|
||||||
|
title: &str,
|
||||||
|
y_axis_label: &str,
|
||||||
|
_direction_minimize: bool,
|
||||||
|
) -> String {
|
||||||
|
let n = bests.len();
|
||||||
|
if n == 0 {
|
||||||
|
return format!(
|
||||||
|
"<svg xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 {width} {height}\">\
|
||||||
|
<text x=\"10\" y=\"20\">{}</text></svg>",
|
||||||
|
escape_xml(title)
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
let (ymin, ymax) = bounds(bests.iter().copied());
|
||||||
|
let yspan = (ymax - ymin).max(1e-12);
|
||||||
|
let xspan = (n - 1).max(1) as f64;
|
||||||
|
|
||||||
|
let m_left = 70.0_f64;
|
||||||
|
let m_right = 20.0_f64;
|
||||||
|
let m_top = 40.0_f64;
|
||||||
|
let m_bot = 50.0_f64;
|
||||||
|
let plot_w = width as f64 - m_left - m_right;
|
||||||
|
let plot_h = height as f64 - m_top - m_bot;
|
||||||
|
|
||||||
|
let to_x = |i: usize| m_left + (i as f64) / xspan * plot_w;
|
||||||
|
let to_y = |v: f64| m_top + plot_h - (v - ymin) / yspan * plot_h;
|
||||||
|
|
||||||
|
let mut out = String::new();
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
"<svg xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 {width} {height}\" \
|
||||||
|
font-family=\"system-ui, sans-serif\" font-size=\"12\">",
|
||||||
|
);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <rect x=\"0\" y=\"0\" width=\"{width}\" height=\"{height}\" fill=\"white\"/>",
|
||||||
|
);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <text x=\"{x}\" y=\"22\" font-size=\"16\" font-weight=\"bold\">{title}</text>",
|
||||||
|
x = m_left,
|
||||||
|
title = escape_xml(title),
|
||||||
|
);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <rect x=\"{}\" y=\"{}\" width=\"{}\" height=\"{}\" fill=\"none\" stroke=\"#888\" />",
|
||||||
|
m_left, m_top, plot_w, plot_h,
|
||||||
|
);
|
||||||
|
|
||||||
|
// X axis: generation index.
|
||||||
|
for i in 0..=4 {
|
||||||
|
let t = i as f64 / 4.0;
|
||||||
|
let g = (t * (n - 1) as f64).round() as usize;
|
||||||
|
let x = to_x(g);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <line x1=\"{x}\" y1=\"{y0}\" x2=\"{x}\" y2=\"{y1}\" stroke=\"#888\" />",
|
||||||
|
y0 = m_top + plot_h,
|
||||||
|
y1 = m_top + plot_h + 5.0,
|
||||||
|
);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <text x=\"{x}\" y=\"{y}\" text-anchor=\"middle\">{g}</text>",
|
||||||
|
y = m_top + plot_h + 18.0,
|
||||||
|
);
|
||||||
|
}
|
||||||
|
// Y ticks.
|
||||||
|
for i in 0..=3 {
|
||||||
|
let t = i as f64 / 3.0;
|
||||||
|
let v = ymin + t * yspan;
|
||||||
|
let y = to_y(v);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <line x1=\"{x0}\" y1=\"{y}\" x2=\"{x1}\" y2=\"{y}\" stroke=\"#888\" />",
|
||||||
|
x0 = m_left - 5.0,
|
||||||
|
x1 = m_left,
|
||||||
|
);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <text x=\"{x}\" y=\"{y}\" text-anchor=\"end\" dominant-baseline=\"middle\">{v:.3e}</text>",
|
||||||
|
x = m_left - 8.0,
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
// Axis labels.
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <text x=\"{x}\" y=\"{y}\" text-anchor=\"middle\">generation</text>",
|
||||||
|
x = m_left + plot_w / 2.0,
|
||||||
|
y = height as f64 - 12.0,
|
||||||
|
);
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <text x=\"15\" y=\"{y}\" text-anchor=\"middle\" \
|
||||||
|
transform=\"rotate(-90 15 {y})\">{label}</text>",
|
||||||
|
y = m_top + plot_h / 2.0,
|
||||||
|
label = escape_xml(y_axis_label),
|
||||||
|
);
|
||||||
|
|
||||||
|
// Polyline.
|
||||||
|
let mut points = String::new();
|
||||||
|
for (i, &v) in bests.iter().enumerate() {
|
||||||
|
if i > 0 {
|
||||||
|
points.push(' ');
|
||||||
|
}
|
||||||
|
let _ = write!(points, "{:.2},{:.2}", to_x(i), to_y(v));
|
||||||
|
}
|
||||||
|
let _ = writeln!(
|
||||||
|
out,
|
||||||
|
" <polyline points=\"{points}\" fill=\"none\" stroke=\"#1f77b4\" stroke-width=\"1.5\" />",
|
||||||
|
);
|
||||||
|
|
||||||
|
out.push_str("</svg>");
|
||||||
|
out
|
||||||
|
}
|
||||||
|
|
||||||
|
fn bounds<I: IntoIterator<Item = f64>>(it: I) -> (f64, f64) {
|
||||||
|
let mut lo = f64::INFINITY;
|
||||||
|
let mut hi = f64::NEG_INFINITY;
|
||||||
|
for v in it {
|
||||||
|
if v.is_finite() {
|
||||||
|
if v < lo {
|
||||||
|
lo = v;
|
||||||
|
}
|
||||||
|
if v > hi {
|
||||||
|
hi = v;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
if lo.is_infinite() {
|
||||||
|
(0.0, 1.0)
|
||||||
|
} else if (hi - lo).abs() < f64::EPSILON {
|
||||||
|
// All points equal — give a small artificial span.
|
||||||
|
(lo - 0.5, hi + 0.5)
|
||||||
|
} else {
|
||||||
|
(lo, hi)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
fn escape_xml(s: &str) -> String {
|
||||||
|
s.replace('&', "&")
|
||||||
|
.replace('<', "<")
|
||||||
|
.replace('>', ">")
|
||||||
|
}
|
||||||
|
|
||||||
|
#[cfg(test)]
|
||||||
|
mod tests {
|
||||||
|
use super::*;
|
||||||
|
use heuropt::core::evaluation::Evaluation;
|
||||||
|
use heuropt::core::objective::Objective;
|
||||||
|
|
||||||
|
#[test]
|
||||||
|
fn pareto_svg_well_formed() {
|
||||||
|
let space = ObjectiveSpace::new(vec![Objective::minimize("f1"), Objective::minimize("f2")]);
|
||||||
|
let front = vec![
|
||||||
|
Candidate::new((), Evaluation::new(vec![0.0, 1.0])),
|
||||||
|
Candidate::new((), Evaluation::new(vec![1.0, 0.0])),
|
||||||
|
];
|
||||||
|
let svg = pareto_front_svg(&front, &space, 400, 300, "test");
|
||||||
|
assert!(svg.starts_with("<svg"));
|
||||||
|
assert!(svg.contains("</svg>"));
|
||||||
|
assert!(svg.contains("<circle"));
|
||||||
|
}
|
||||||
|
|
||||||
|
#[test]
|
||||||
|
fn convergence_svg_well_formed() {
|
||||||
|
let bests = vec![10.0, 5.0, 2.0, 1.0, 0.5];
|
||||||
|
let svg = convergence_svg(&bests, 400, 300, "convergence", "best", true);
|
||||||
|
assert!(svg.starts_with("<svg"));
|
||||||
|
assert!(svg.contains("polyline"));
|
||||||
|
}
|
||||||
|
|
||||||
|
#[test]
|
||||||
|
fn convergence_empty_returns_valid_svg() {
|
||||||
|
let svg = convergence_svg(&[], 200, 100, "empty", "y", true);
|
||||||
|
assert!(svg.contains("<svg"));
|
||||||
|
assert!(svg.contains("</svg>"));
|
||||||
|
}
|
||||||
|
}
|
||||||
@@ -237,6 +237,107 @@ where
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
#[cfg(feature = "async")]
|
||||||
|
impl DifferentialEvolution {
|
||||||
|
/// Async version of [`Optimizer::run`] — drives evaluations through
|
||||||
|
/// the user-chosen async runtime. Available only with the `async`
|
||||||
|
/// feature.
|
||||||
|
///
|
||||||
|
/// `concurrency` bounds in-flight evaluations per batch (initial
|
||||||
|
/// population and per-generation trials).
|
||||||
|
pub async fn run_async<P>(
|
||||||
|
&mut self,
|
||||||
|
problem: &P,
|
||||||
|
concurrency: usize,
|
||||||
|
) -> OptimizationResult<Vec<f64>>
|
||||||
|
where
|
||||||
|
P: crate::core::async_problem::AsyncProblem<Decision = Vec<f64>>,
|
||||||
|
{
|
||||||
|
use rand::Rng as _;
|
||||||
|
|
||||||
|
use crate::algorithms::parallel_eval_async::evaluate_batch_async;
|
||||||
|
use crate::core::candidate::Candidate;
|
||||||
|
use crate::traits::Initializer as _;
|
||||||
|
|
||||||
|
assert!(
|
||||||
|
self.config.population_size >= 4,
|
||||||
|
"DifferentialEvolution requires population_size >= 4",
|
||||||
|
);
|
||||||
|
assert!(
|
||||||
|
(0.0..=1.0).contains(&self.config.crossover_probability),
|
||||||
|
"DifferentialEvolution crossover_probability must be in [0.0, 1.0]",
|
||||||
|
);
|
||||||
|
|
||||||
|
let objectives = problem.objectives();
|
||||||
|
assert!(
|
||||||
|
objectives.is_single_objective(),
|
||||||
|
"DifferentialEvolution only supports single-objective problems",
|
||||||
|
);
|
||||||
|
let direction = objectives.objectives[0].direction;
|
||||||
|
|
||||||
|
let dim = self.bounds.bounds.len();
|
||||||
|
let n = self.config.population_size;
|
||||||
|
let mut rng = rng_from_seed(self.config.seed);
|
||||||
|
|
||||||
|
let mut decisions: Vec<Vec<f64>> = self.bounds.initialize(n, &mut rng);
|
||||||
|
let initial_pop = evaluate_batch_async(problem, decisions.clone(), concurrency).await;
|
||||||
|
let mut evaluations = initial_pop.len();
|
||||||
|
let mut current_pop = initial_pop;
|
||||||
|
let mut evals: Vec<f64> = current_pop
|
||||||
|
.iter()
|
||||||
|
.map(|c| c.evaluation.objectives[0])
|
||||||
|
.collect();
|
||||||
|
|
||||||
|
for _generation in 0..self.config.generations {
|
||||||
|
let trials: Vec<Vec<f64>> = (0..n)
|
||||||
|
.map(|i| {
|
||||||
|
let (r1, r2, r3) = pick_three_distinct(n, i, &mut rng);
|
||||||
|
let j_rand = rng.random_range(0..dim);
|
||||||
|
let mut trial = decisions[i].clone();
|
||||||
|
for j in 0..dim {
|
||||||
|
let take_donor =
|
||||||
|
rng.random_bool(self.config.crossover_probability) || j == j_rand;
|
||||||
|
if take_donor {
|
||||||
|
let mutant = decisions[r1][j]
|
||||||
|
+ self.config.differential_weight
|
||||||
|
* (decisions[r2][j] - decisions[r3][j]);
|
||||||
|
let (lo, hi) = self.bounds.bounds[j];
|
||||||
|
trial[j] = mutant.clamp(lo, hi);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
trial
|
||||||
|
})
|
||||||
|
.collect();
|
||||||
|
let trial_cands: Vec<Candidate<Vec<f64>>> =
|
||||||
|
evaluate_batch_async(problem, trials, concurrency).await;
|
||||||
|
evaluations += trial_cands.len();
|
||||||
|
for (i, trial_cand) in trial_cands.into_iter().enumerate() {
|
||||||
|
let trial_obj = trial_cand.evaluation.objectives[0];
|
||||||
|
let target_obj = evals[i];
|
||||||
|
let trial_better = match direction {
|
||||||
|
crate::core::objective::Direction::Minimize => trial_obj <= target_obj,
|
||||||
|
crate::core::objective::Direction::Maximize => trial_obj >= target_obj,
|
||||||
|
};
|
||||||
|
if trial_better {
|
||||||
|
decisions[i] = trial_cand.decision.clone();
|
||||||
|
evals[i] = trial_obj;
|
||||||
|
current_pop[i] = trial_cand;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
let front = pareto_front(¤t_pop, &objectives);
|
||||||
|
let best = best_candidate(¤t_pop, &objectives);
|
||||||
|
OptimizationResult::new(
|
||||||
|
Population::new(current_pop),
|
||||||
|
front,
|
||||||
|
best,
|
||||||
|
evaluations,
|
||||||
|
self.config.generations,
|
||||||
|
)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
fn pick_three_distinct(
|
fn pick_three_distinct(
|
||||||
n: usize,
|
n: usize,
|
||||||
exclude: usize,
|
exclude: usize,
|
||||||
|
|||||||
@@ -22,6 +22,8 @@ pub mod nsga3;
|
|||||||
pub mod one_plus_one_es;
|
pub mod one_plus_one_es;
|
||||||
pub mod paes;
|
pub mod paes;
|
||||||
pub(crate) mod parallel_eval;
|
pub(crate) mod parallel_eval;
|
||||||
|
#[cfg(feature = "async")]
|
||||||
|
pub(crate) mod parallel_eval_async;
|
||||||
pub mod particle_swarm;
|
pub mod particle_swarm;
|
||||||
pub mod pesa2;
|
pub mod pesa2;
|
||||||
pub mod random_search;
|
pub mod random_search;
|
||||||
|
|||||||
@@ -0,0 +1,58 @@
|
|||||||
|
//! Async population evaluator.
|
||||||
|
//!
|
||||||
|
//! Available only with the `async` feature. Used by the `run_async`
|
||||||
|
//! method on algorithms that support async problems.
|
||||||
|
|
||||||
|
use futures::stream::{FuturesOrdered, StreamExt};
|
||||||
|
|
||||||
|
use crate::core::async_problem::AsyncProblem;
|
||||||
|
use crate::core::candidate::Candidate;
|
||||||
|
|
||||||
|
/// Evaluate every decision concurrently against `problem`, preserving
|
||||||
|
/// input order in the returned vector. Concurrency is bounded by
|
||||||
|
/// `concurrency` (≥ 1) — too high a value wastes memory and may
|
||||||
|
/// overload downstream services; too low forfeits parallelism.
|
||||||
|
///
|
||||||
|
/// Returns a future that the caller drives via their preferred
|
||||||
|
/// runtime (typically tokio).
|
||||||
|
pub async fn evaluate_batch_async<P>(
|
||||||
|
problem: &P,
|
||||||
|
decisions: Vec<P::Decision>,
|
||||||
|
concurrency: usize,
|
||||||
|
) -> Vec<Candidate<P::Decision>>
|
||||||
|
where
|
||||||
|
P: AsyncProblem,
|
||||||
|
{
|
||||||
|
assert!(
|
||||||
|
concurrency >= 1,
|
||||||
|
"evaluate_batch_async concurrency must be >= 1"
|
||||||
|
);
|
||||||
|
let mut out: Vec<Candidate<P::Decision>> = Vec::with_capacity(decisions.len());
|
||||||
|
|
||||||
|
// Process in concurrency-bounded chunks to keep peak memory low
|
||||||
|
// and avoid blasting downstream services. Each chunk uses
|
||||||
|
// FuturesOrdered to preserve per-chunk order, and chunks are
|
||||||
|
// emitted in their natural order.
|
||||||
|
let mut iter = decisions.into_iter();
|
||||||
|
loop {
|
||||||
|
let mut futs = FuturesOrdered::new();
|
||||||
|
for _ in 0..concurrency {
|
||||||
|
match iter.next() {
|
||||||
|
Some(d) => {
|
||||||
|
futs.push_back(async move {
|
||||||
|
let e = problem.evaluate_async(&d).await;
|
||||||
|
Candidate::new(d, e)
|
||||||
|
});
|
||||||
|
}
|
||||||
|
None => break,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
if futs.is_empty() {
|
||||||
|
break;
|
||||||
|
}
|
||||||
|
while let Some(c) = futs.next().await {
|
||||||
|
out.push(c);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
out
|
||||||
|
}
|
||||||
@@ -134,6 +134,51 @@ where
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
#[cfg(feature = "async")]
|
||||||
|
impl<I> RandomSearch<I> {
|
||||||
|
/// Async version of [`Optimizer::run`] — drives evaluations through
|
||||||
|
/// the user-chosen async runtime (typically tokio). Useful when
|
||||||
|
/// `evaluate` is IO-bound (HTTP, RPC, subprocess).
|
||||||
|
///
|
||||||
|
/// `concurrency` bounds how many evaluations are in-flight at once;
|
||||||
|
/// `1` is sequential, larger values push more load to the
|
||||||
|
/// downstream service.
|
||||||
|
///
|
||||||
|
/// Available only with the `async` feature.
|
||||||
|
pub async fn run_async<P>(
|
||||||
|
&mut self,
|
||||||
|
problem: &P,
|
||||||
|
concurrency: usize,
|
||||||
|
) -> OptimizationResult<P::Decision>
|
||||||
|
where
|
||||||
|
P: crate::core::async_problem::AsyncProblem,
|
||||||
|
I: Initializer<P::Decision>,
|
||||||
|
{
|
||||||
|
use crate::algorithms::parallel_eval_async::evaluate_batch_async;
|
||||||
|
let objectives = problem.objectives();
|
||||||
|
let mut rng = rng_from_seed(self.config.seed);
|
||||||
|
let mut all: Vec<Candidate<P::Decision>> = Vec::new();
|
||||||
|
let mut evaluations = 0usize;
|
||||||
|
for _ in 0..self.config.iterations {
|
||||||
|
let decisions = self
|
||||||
|
.initializer
|
||||||
|
.initialize(self.config.batch_size, &mut rng);
|
||||||
|
evaluations += decisions.len();
|
||||||
|
let cands = evaluate_batch_async(problem, decisions, concurrency).await;
|
||||||
|
all.extend(cands);
|
||||||
|
}
|
||||||
|
let front = pareto_front(&all, &objectives);
|
||||||
|
let best = best_candidate(&all, &objectives);
|
||||||
|
OptimizationResult::new(
|
||||||
|
Population::new(all),
|
||||||
|
front,
|
||||||
|
best,
|
||||||
|
evaluations,
|
||||||
|
self.config.iterations,
|
||||||
|
)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
#[cfg(test)]
|
#[cfg(test)]
|
||||||
mod tests {
|
mod tests {
|
||||||
use super::*;
|
use super::*;
|
||||||
|
|||||||
@@ -0,0 +1,54 @@
|
|||||||
|
//! Async-evaluable problems for IO-bound workloads.
|
||||||
|
//!
|
||||||
|
//! Most heuropt algorithms operate synchronously: their `Problem::evaluate`
|
||||||
|
//! returns immediately. For workloads where evaluation is *IO-bound* — calling
|
||||||
|
//! an HTTP service, querying a remote model, spawning a subprocess —
|
||||||
|
//! awaiting an async fn is much more efficient than blocking a worker
|
||||||
|
//! thread.
|
||||||
|
//!
|
||||||
|
//! [`AsyncProblem`] mirrors [`Problem`](crate::core::Problem) but its
|
||||||
|
//! `evaluate_async` returns a future. Algorithms that support async
|
||||||
|
//! evaluation (NSGA-II, DE, RandomSearch as of v0.7.0; others land
|
||||||
|
//! incrementally) expose a `run_async` method that drives evaluations
|
||||||
|
//! through a user-chosen async runtime (typically tokio).
|
||||||
|
//!
|
||||||
|
//! Available only with the `async` feature.
|
||||||
|
|
||||||
|
use std::future::Future;
|
||||||
|
|
||||||
|
use crate::core::evaluation::Evaluation;
|
||||||
|
use crate::core::objective::ObjectiveSpace;
|
||||||
|
|
||||||
|
/// A problem whose evaluation is async — useful when `evaluate` does
|
||||||
|
/// IO (HTTP, RPC, subprocess) rather than pure CPU work.
|
||||||
|
///
|
||||||
|
/// Mirrors [`Problem`](crate::core::Problem) one-for-one except that
|
||||||
|
/// `evaluate_async` returns a future. The returned future must be
|
||||||
|
/// `Send` so the algorithm can run many evaluations concurrently
|
||||||
|
/// across a runtime's worker pool.
|
||||||
|
///
|
||||||
|
/// Implementors who already have a synchronous `Problem` can adapt
|
||||||
|
/// to `AsyncProblem` with a one-line wrapper:
|
||||||
|
///
|
||||||
|
/// ```ignore
|
||||||
|
/// impl AsyncProblem for MyProblem {
|
||||||
|
/// type Decision = <Self as Problem>::Decision;
|
||||||
|
/// fn objectives(&self) -> ObjectiveSpace { Problem::objectives(self) }
|
||||||
|
/// async fn evaluate_async(&self, x: &Self::Decision) -> Evaluation {
|
||||||
|
/// Problem::evaluate(self, x)
|
||||||
|
/// }
|
||||||
|
/// }
|
||||||
|
/// ```
|
||||||
|
pub trait AsyncProblem: Sync {
|
||||||
|
/// The thing the optimizer changes. Same constraints as
|
||||||
|
/// [`Problem::Decision`](crate::core::Problem::Decision).
|
||||||
|
type Decision: Clone + Send + Sync;
|
||||||
|
|
||||||
|
/// Return the objectives for this problem.
|
||||||
|
fn objectives(&self) -> ObjectiveSpace;
|
||||||
|
|
||||||
|
/// Evaluate `decision` asynchronously. The returned future is
|
||||||
|
/// driven by whichever runtime the algorithm's `run_async` is
|
||||||
|
/// invoked from.
|
||||||
|
fn evaluate_async(&self, decision: &Self::Decision) -> impl Future<Output = Evaluation> + Send;
|
||||||
|
}
|
||||||
@@ -1,5 +1,7 @@
|
|||||||
//! Concrete data types and the `Problem` trait that the rest of the crate is built on.
|
//! Concrete data types and the `Problem` trait that the rest of the crate is built on.
|
||||||
|
|
||||||
|
#[cfg(feature = "async")]
|
||||||
|
pub mod async_problem;
|
||||||
pub mod candidate;
|
pub mod candidate;
|
||||||
pub mod evaluation;
|
pub mod evaluation;
|
||||||
pub mod objective;
|
pub mod objective;
|
||||||
@@ -9,6 +11,8 @@ pub mod problem;
|
|||||||
pub mod result;
|
pub mod result;
|
||||||
pub mod rng;
|
pub mod rng;
|
||||||
|
|
||||||
|
#[cfg(feature = "async")]
|
||||||
|
pub use async_problem::AsyncProblem;
|
||||||
pub use candidate::*;
|
pub use candidate::*;
|
||||||
pub use evaluation::*;
|
pub use evaluation::*;
|
||||||
pub use objective::*;
|
pub use objective::*;
|
||||||
|
|||||||
@@ -4,6 +4,8 @@
|
|||||||
//! use heuropt::prelude::*;
|
//! use heuropt::prelude::*;
|
||||||
//! ```
|
//! ```
|
||||||
|
|
||||||
|
#[cfg(feature = "async")]
|
||||||
|
pub use crate::core::async_problem::AsyncProblem;
|
||||||
pub use crate::core::{
|
pub use crate::core::{
|
||||||
Candidate, Direction, Evaluation, Objective, ObjectiveSpace, OptimizationResult,
|
Candidate, Direction, Evaluation, Objective, ObjectiveSpace, OptimizationResult,
|
||||||
PartialProblem, Population, Problem, Rng, rng_from_seed,
|
PartialProblem, Population, Problem, Rng, rng_from_seed,
|
||||||
|
|||||||
Reference in New Issue
Block a user