Wraps any inner Pruner and requires it to recommend pruning for N
consecutive steps before actually pruning. Useful for noisy
intermediate values where a single bad step shouldn't trigger pruning.
Prunes trials whose intermediate values are worse than the median
of completed trials at the same step. Supports configurable warmup
steps and minimum trial count before pruning activates.
- Add `Pruned` variant to `TrialState`
- Add `Error::TrialPruned` variant and standalone `TrialPruned` struct
with `From<TrialPruned> for Error` for ergonomic `?` usage
- Add `state` field to `CompletedTrial` (defaults to `Complete`)
- Add `Study::prune_trial()` and `Study::n_pruned_trials()`
- `optimize()` and `optimize_with_callback()` detect `TrialPruned`
errors via Any downcasting and record pruned trials instead of
failing them
- `best_trial()` / `best_value()` now filter to only `Complete` trials
- Re-export `TrialPruned` from crate root and prelude
- Add report(step, value) and should_prune() methods to Trial
- Store intermediate_values in Trial, copied to CompletedTrial on completion
- Pass pruner through trial factory so trials can consult it
- Rebuild trial factory when pruner is changed via set_pruner()
Introduce the pruning extension point for the trial pruning system.
The Pruner trait allows deciding whether to stop a trial early based
on intermediate values. NopPruner (never prunes) is the default.
- Add `.name()` builder method on all 5 parameter types for custom labels
- Add `CompletedTrial::get(¶m)` for typed parameter access
- Add `Display` impl on `ParamValue`
- Add prelude module at `optimizer::prelude::*`
- Shadow `_with_sampler` methods on `Study<f64>` so `optimize()` auto-uses
the configured sampler; deprecate `_with_sampler` variants
- Use runtime `Any` downcasting with `trial_factory` to avoid E0592
- Update all examples and tests to use the new API
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The old example used the removed string-based trial.suggest_float()
API. Updated to use FloatParam::new() with param.suggest(trial).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Manuel Raimann