From 671a4647442c043caee52feb98e712a2fd8b6f57 Mon Sep 17 00:00:00 2001 From: morrisnein Date: Fri, 14 Oct 2022 19:01:51 +0300 Subject: [PATCH] rename `uid` -> `uid_of_individual` --- fedot/core/optimisers/gp_comp/evaluation.py | 10 +++++----- .../core/optimisers/opt_history_objects/individual.py | 2 +- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/fedot/core/optimisers/gp_comp/evaluation.py b/fedot/core/optimisers/gp_comp/evaluation.py index c69fd62e8d..ed3fbc3874 100644 --- a/fedot/core/optimisers/gp_comp/evaluation.py +++ b/fedot/core/optimisers/gp_comp/evaluation.py @@ -59,7 +59,7 @@ def apply_evaluation_results(individuals: PopulationT, evaluation_results: EvalResultsList) -> PopulationT: """Applies results of evaluation to the evaluated population. Excludes individuals that weren't evaluated.""" - evaluation_results = {res.uid: res for res in evaluation_results if res} + evaluation_results = {res.uid_of_individual: res for res in evaluation_results if res} individuals_evaluated = [] for ind in individuals: eval_res = evaluation_results.get(ind.uid) @@ -128,7 +128,7 @@ def evaluate_population(self, individuals: PopulationT) -> Optional[PopulationT] successful_evals = self.apply_evaluation_results([single_ind], [evaluation_result]) or None return successful_evals - def evaluate_single(self, graph: OptGraph, uid: str, with_time_limit: bool = True, cache_key: Optional[str] = None, + def evaluate_single(self, graph: OptGraph, uid_of_individual: str, with_time_limit: bool = True, cache_key: Optional[str] = None, logs_initializer: Optional[Tuple[int, pathlib.Path]] = None) -> OptionalEvalResult: if with_time_limit and self.timer.is_time_limit_reached(): @@ -146,7 +146,7 @@ def evaluate_single(self, graph: OptGraph, uid: str, with_time_limit: bool = Tru eval_time_iso = datetime.now().isoformat() eval_res = GraphEvalResult( - uid=uid, fitness=fitness, graph=graph, metadata={ + uid_of_individual=uid_of_individual, fitness=fitness, graph=graph, metadata={ 'computation_time_in_seconds': end_time - start_time, 'evaluation_time_iso': eval_time_iso } @@ -204,7 +204,7 @@ def evaluate_population(self, individuals: PopulationT) -> Optional[PopulationT] evaluated_population = individuals_evaluated + individuals_to_skip or None return evaluated_population - def evaluate_single(self, graph: OptGraph, uid: str, with_time_limit=True) -> OptionalEvalResult: + def evaluate_single(self, graph: OptGraph, uid_of_individual: str, with_time_limit=True) -> OptionalEvalResult: if with_time_limit and self.timer.is_time_limit_reached(): return None @@ -216,7 +216,7 @@ def evaluate_single(self, graph: OptGraph, uid: str, with_time_limit=True) -> Op eval_time_iso = datetime.now().isoformat() eval_res = GraphEvalResult( - uid=uid, fitness=fitness, graph=graph, metadata={ + uid_of_individual=uid_of_individual, fitness=fitness, graph=graph, metadata={ 'computation_time_in_seconds': end_time - start_time, 'evaluation_time_iso': eval_time_iso } diff --git a/fedot/core/optimisers/opt_history_objects/individual.py b/fedot/core/optimisers/opt_history_objects/individual.py index 3096b870ba..d4b509a2dd 100644 --- a/fedot/core/optimisers/opt_history_objects/individual.py +++ b/fedot/core/optimisers/opt_history_objects/individual.py @@ -123,7 +123,7 @@ def __deepcopy__(self, memo): @dataclass class GraphEvalResult: - uid: str + uid_of_individual: str fitness: Fitness graph: OptGraph # For the case if evaluation needs to assign some values to the graph. metadata: Dict[str, Any] = field(default_factory=dict)