GEPA.Result (GEPA v0.3.0)

@type t() :: %GEPA.Result{
  best_candidate: GEPA.Types.candidate() | term() | nil,
  best_idx: non_neg_integer() | nil,
  best_outputs_valset:
    %{required(GEPA.Types.data_id()) => [{GEPA.Types.program_idx(), term()}]}
    | nil,
  candidates: [GEPA.Types.candidate()],
  discovery_eval_counts: [non_neg_integer()],
  i: integer(),
  num_full_ds_evals: non_neg_integer(),
  objective_pareto_front: %{required(String.t()) => float()} | nil,
  parents: [[GEPA.Types.program_idx() | nil]],
  per_objective_best_candidates:
    %{required(String.t()) => MapSet.t(GEPA.Types.program_idx())} | nil,
  per_val_instance_best_candidates: GEPA.Types.pareto_fronts(),
  total_num_evals: non_neg_integer(),
  val_aggregate_scores: [float()],
  val_aggregate_subscores: [%{required(String.t()) => float()}] | nil,
  val_subscores: [GEPA.Types.sparse_scores()]
}

Functions

best_candidate(result)

@spec best_candidate(t()) :: GEPA.Types.candidate()

Get the best candidate program.

best_idx(result)

@spec best_idx(t()) :: non_neg_integer()

Get the index of the best candidate by aggregate score.

best_score(result)

@spec best_score(t()) :: float()

Get the best score achieved.

candidate_tree_dot(result)

@spec candidate_tree_dot(t()) :: String.t()

Generate Graphviz DOT for this result's candidate lineage.

candidate_tree_html(result)

@spec candidate_tree_html(t()) :: String.t()

Generate a self-contained HTML visualization for this result's candidate lineage.

from_dict(data)

@spec from_dict(map()) :: t()

Rebuild a result from to_dict/1 output.

from_state(state)

@spec from_state(GEPA.State.t()) :: t()

Create result from final optimization state.

to_dict(result)

@spec to_dict(t()) :: map()

Convert a result to a plain map suitable for persistence or JSON conversion.