create constants for frequently used labels

golem/core/optimisers/genetic/gp_optimizer.py

@@ -1,6 +1,6 @@
 from copy import deepcopy
 from random import choice
-from typing import Sequence, Union, Any
+from typing import Any, Sequence, Union
 
 from golem.core.constants import MAX_GRAPH_GEN_ATTEMPTS
 from golem.core.dag.graph import Graph
@@ -9,15 +9,17 @@
 from golem.core.optimisers.genetic.operators.elitism import Elitism
 from golem.core.optimisers.genetic.operators.inheritance import Inheritance
 from golem.core.optimisers.genetic.operators.mutation import Mutation
-from golem.core.optimisers.genetic.operators.operator import PopulationT, EvaluationOperator
+from golem.core.optimisers.genetic.operators.operator import EvaluationOperator, PopulationT
 from golem.core.optimisers.genetic.operators.regularization import Regularization
 from golem.core.optimisers.genetic.operators.reproduction import ReproductionController
 from golem.core.optimisers.genetic.operators.selection import Selection
 from golem.core.optimisers.genetic.parameters.graph_depth import AdaptiveGraphDepth
 from golem.core.optimisers.genetic.parameters.operators_prob import init_adaptive_operators_prob
-from golem.core.optimisers.genetic.parameters.population_size import init_adaptive_pop_size, PopulationSize
+from golem.core.optimisers.genetic.parameters.population_size import PopulationSize, init_adaptive_pop_size
 from golem.core.optimisers.objective.objective import Objective
 from golem.core.optimisers.opt_history_objects.individual import Individual
+from golem.core.optimisers.opt_history_objects.opt_history import EXTENDED_INITIAL_ASSUMPTIONS_LABEL, \
+    INITIAL_ASSUMPTIONS_LABEL
 from golem.core.optimisers.optimization_parameters import GraphRequirements
 from golem.core.optimisers.optimizer import GraphGenerationParams
 from golem.core.optimisers.populational_optimizer import PopulationalOptimizer
@@ -64,13 +66,13 @@ def __init__(self,
     def _initial_population(self, evaluator: EvaluationOperator):
         """ Initializes the initial population """
         # Adding of initial assumptions to history as zero generation
-        self._update_population(evaluator(self.initial_individuals), 'initial_assumptions')
+        self._update_population(evaluator(self.initial_individuals), INITIAL_ASSUMPTIONS_LABEL)
         pop_size = self.graph_optimizer_params.pop_size
 
         if len(self.initial_individuals) < pop_size:
             self.initial_individuals = self._extend_population(self.initial_individuals, pop_size)
             # Adding of extended population to history
-            self._update_population(evaluator(self.initial_individuals), 'extended_initial_assumptions')
+            self._update_population(evaluator(self.initial_individuals), EXTENDED_INITIAL_ASSUMPTIONS_LABEL)
 
     def _extend_population(self, pop: PopulationT, target_pop_size: int) -> PopulationT:
         verifier = self.graph_generation_params.verifier

golem/core/optimisers/meta/surrogate_optimizer.py

@@ -6,6 +6,7 @@
 from golem.core.optimisers.meta.surrogate_evaluator import SurrogateDispatcher
 from golem.core.optimisers.meta.surrogate_model import RandomValuesSurrogateModel
 from golem.core.optimisers.objective import Objective, ObjectiveFunction
+from golem.core.optimisers.opt_history_objects.opt_history import EVOLUTION_RESULTS_LABEL
 from golem.core.optimisers.optimization_parameters import GraphRequirements
 from golem.core.optimisers.optimizer import GraphGenerationParams
 from golem.core.optimisers.populational_optimizer import EvaluationAttemptsError, _try_unfit_graph
@@ -17,6 +18,7 @@ class SurrogateEachNgenOptimizer(EvoGraphOptimizer):
 
     Additionally, we need to pass surrogate_model object
     """
+
     def __init__(self,
                  objective: Objective,
                  initial_graphs: Sequence[OptGraph],
@@ -54,5 +56,5 @@ def optimise(self, objective: ObjectiveFunction) -> Sequence[OptGraph]:
                     break
                 # Adding of new population to history
                 self._update_population(new_population)
-        self._update_population(self.best_individuals, 'evolution_results')
+        self._update_population(self.best_individuals, EVOLUTION_RESULTS_LABEL)
         return [ind.graph for ind in self.best_individuals]

golem/core/optimisers/opt_history_objects/opt_history.py

@@ -18,6 +18,12 @@
 if TYPE_CHECKING:
     from golem.core.optimisers.opt_history_objects.individual import Individual
 
+INITIAL_ASSUMPTIONS_LABEL = 'initial_assumptions'
+EXTENDED_INITIAL_ASSUMPTIONS_LABEL = 'extended_initial_assumptions'
+EVOLUTION_RESULTS_LABEL = 'evolution_results'
+TUNING_START_LABEL = 'tuning_start'
+TUNING_RESULT_LABEL = 'tuning_result'
+
 
 class OptHistory:
     """
@@ -212,7 +218,7 @@ def initial_assumptions(self) -> Optional[Generation]:
         if not self.generations:
             return None
         for gen in self.generations:
-            if gen.label == 'initial_assumptions':
+            if gen.label == INITIAL_ASSUMPTIONS_LABEL:
                 return gen
 
     @property
@@ -224,23 +230,23 @@ def evolution_results(self) -> Optional[Generation]:
         if not self.generations:
             return None
         for gen in reversed(self.generations):
-            if gen.label == 'evolution_results':
+            if gen.label == EVOLUTION_RESULTS_LABEL:
                 return gen
 
     @property
     def tuning_start(self) -> Optional[Generation]:
         if not self.generations:
             return None
         for gen in reversed(self.generations):
-            if gen.label == 'tuning_start':
+            if gen.label == TUNING_START_LABEL:
                 return gen
 
     @property
     def tuning_result(self) -> Optional[Generation]:
         if not self.generations:
             return None
         for gen in reversed(self.generations):
-            if gen.label == 'tuning_result':
+            if gen.label == TUNING_RESULT_LABEL:
                 return gen
 
     @property

golem/core/optimisers/populational_optimizer.py

@@ -1,17 +1,18 @@
 from abc import abstractmethod
 from random import choice
-from typing import Any, Optional, Sequence, Dict
+from typing import Any, Dict, Optional, Sequence
 
 from golem.core.constants import MIN_POP_SIZE
 from golem.core.dag.graph import Graph
 from golem.core.optimisers.archive import GenerationKeeper
 from golem.core.optimisers.genetic.evaluation import MultiprocessingDispatcher, SequentialDispatcher
-from golem.core.optimisers.genetic.operators.operator import PopulationT, EvaluationOperator
+from golem.core.optimisers.genetic.operators.operator import EvaluationOperator, PopulationT
 from golem.core.optimisers.objective import GraphFunction, ObjectiveFunction
 from golem.core.optimisers.objective.objective import Objective
 from golem.core.optimisers.opt_history_objects.individual import Individual
+from golem.core.optimisers.opt_history_objects.opt_history import EVOLUTION_RESULTS_LABEL
 from golem.core.optimisers.optimization_parameters import GraphRequirements
-from golem.core.optimisers.optimizer import GraphGenerationParams, GraphOptimizer, AlgorithmParameters
+from golem.core.optimisers.optimizer import AlgorithmParameters, GraphGenerationParams, GraphOptimizer
 from golem.core.optimisers.timer import OptimisationTimer
 from golem.core.utilities.grouped_condition import GroupedCondition
 
@@ -105,7 +106,7 @@ def optimise(self, objective: ObjectiveFunction) -> Sequence[Graph]:
                 # Adding of new population to history
                 self._update_population(new_population)
         pbar.close()
-        self._update_population(self.best_individuals, 'evolution_results')
+        self._update_population(self.best_individuals, EVOLUTION_RESULTS_LABEL)
         return [ind.graph for ind in self.best_individuals]
 
     @property

golem/core/optimisers/random/random_mutation_optimizer.py

@@ -1,11 +1,13 @@
-from typing import Union, Optional, Sequence
+from typing import Optional, Sequence, Union
 
 from golem.core.dag.graph import Graph
 from golem.core.optimisers.genetic.gp_params import GPAlgorithmParameters
 from golem.core.optimisers.genetic.operators.mutation import Mutation
 from golem.core.optimisers.genetic.operators.operator import EvaluationOperator, PopulationT
 from golem.core.optimisers.objective import Objective
 from golem.core.optimisers.opt_history_objects.individual import Individual
+from golem.core.optimisers.opt_history_objects.opt_history import EXTENDED_INITIAL_ASSUMPTIONS_LABEL, \
+    INITIAL_ASSUMPTIONS_LABEL
 from golem.core.optimisers.optimization_parameters import GraphRequirements
 from golem.core.optimisers.optimizer import GraphGenerationParams
 from golem.core.optimisers.populational_optimizer import PopulationalOptimizer
@@ -38,13 +40,13 @@ def _evolve_population(self, evaluator: EvaluationOperator) -> PopulationT:
         return new_population
 
     def _initial_population(self, evaluator: EvaluationOperator):
-        self._update_population(evaluator(self.initial_individuals), 'initial_assumptions')
+        self._update_population(evaluator(self.initial_individuals), INITIAL_ASSUMPTIONS_LABEL)
         pop_size = self.graph_optimizer_params.pop_size
 
         if len(self.initial_individuals) < pop_size:
             self.initial_individuals = self._extend_population(self.initial_individuals, pop_size)
             # Adding of extended population to history
-            self._update_population(evaluator(self.initial_individuals), 'extended_initial_assumptions')
+            self._update_population(evaluator(self.initial_individuals), EXTENDED_INITIAL_ASSUMPTIONS_LABEL)
 
 
 class RandomMutationOptimizer(RandomSearchOptimizer):

golem/core/optimisers/random/random_search.py

@@ -9,8 +9,9 @@
 from golem.core.optimisers.graph import OptGraph
 from golem.core.optimisers.objective import Objective, ObjectiveFunction
 from golem.core.optimisers.opt_history_objects.individual import Individual
+from golem.core.optimisers.opt_history_objects.opt_history import EVOLUTION_RESULTS_LABEL, INITIAL_ASSUMPTIONS_LABEL
 from golem.core.optimisers.optimization_parameters import GraphRequirements
-from golem.core.optimisers.optimizer import GraphOptimizer, GraphGenerationParams
+from golem.core.optimisers.optimizer import GraphGenerationParams, GraphOptimizer
 from golem.core.optimisers.timer import OptimisationTimer
 from golem.core.utilities.grouped_condition import GroupedCondition
 
@@ -34,7 +35,7 @@ def __init__(self,
                 'Optimisation stopped: Time limit is reached'
             ).add_condition(
                 lambda: requirements.num_of_generations is not None and
-                self.current_iteration_num >= requirements.num_of_generations,
+                        self.current_iteration_num >= requirements.num_of_generations,
                 'Optimisation stopped: Max number of iterations reached')
 
     def optimise(self, objective: ObjectiveFunction) -> Sequence[OptGraph]:
@@ -46,14 +47,14 @@ def optimise(self, objective: ObjectiveFunction) -> Sequence[OptGraph]:
 
         with self.timer, self._progressbar as pbar:
             self.best_individual = self._eval_initial_individual(evaluator)
-            self._update_best_individual(self.best_individual, 'initial_assumptions')
+            self._update_best_individual(self.best_individual, INITIAL_ASSUMPTIONS_LABEL)
             while not self.stop_optimization():
                 new_individual = self._generate_new_individual()
                 evaluator([new_individual])
                 self.current_iteration_num += 1
                 self._update_best_individual(new_individual)
                 pbar.update()
-        self._update_best_individual(self.best_individual, 'evolution_results')
+        self._update_best_individual(self.best_individual, EVOLUTION_RESULTS_LABEL)
         pbar.close()
         return [self.best_individual.graph]
 

golem/core/tuning/tuner_interface.py

@@ -14,7 +14,7 @@
 from golem.core.optimisers.graph import OptGraph
 from golem.core.optimisers.objective import ObjectiveEvaluate, ObjectiveFunction
 from golem.core.optimisers.opt_history_objects.individual import Individual
-from golem.core.optimisers.opt_history_objects.opt_history import OptHistory
+from golem.core.optimisers.opt_history_objects.opt_history import OptHistory, TUNING_RESULT_LABEL, TUNING_START_LABEL
 from golem.core.optimisers.opt_history_objects.parent_operator import ParentOperator
 from golem.core.tuning.search_space import SearchSpace, convert_parameters
 from golem.core.utilities.data_structures import ensure_wrapped_in_sequence
@@ -96,7 +96,7 @@ def init_check(self, graph: OptGraph) -> None:
         graph = deepcopy(graph)
         fitness = self.objective_evaluate(graph)
         self.init_individual = self._create_individual(graph, fitness)
-        self._add_to_history([self.init_individual], label='tuning_start')
+        self._add_to_history([self.init_individual], label=TUNING_START_LABEL)
 
         init_metric = self._fitness_to_metric_value(fitness)
         self.log.message(f'Initial graph: {graph_structure(graph)} \n'
@@ -154,7 +154,7 @@ def _single_obj_final_check(self, tuned_graph: OptGraph):
             self.log.message('Final metric is None')
 
         self.obtained_individual = final_individual
-        self._add_to_history([self.obtained_individual], label='tuning_result')
+        self._add_to_history([self.obtained_individual], label=TUNING_RESULT_LABEL)
 
         return self.obtained_individual.graph
 
@@ -179,7 +179,7 @@ def _multi_obj_final_check(self, tuned_graphs: Sequence[OptGraph]) -> Sequence[O
             self.obtained_individual = [self.init_individual]
             final_graphs = [self.init_individual.graph]
 
-        self._add_to_history(self.obtained_individual, label='tuning_result')
+        self._add_to_history(self.obtained_individual, label=TUNING_RESULT_LABEL)
 
         return final_graphs
 
@@ -284,7 +284,7 @@ def _add_to_history(self, individuals: Sequence[Individual], label: Optional[str
 
         if label is None:
             label = f'tuning_iteration_{self.evaluations_count}'
-        if label not in ('tuning_start', 'tuning_result'):
+        if label not in (TUNING_START_LABEL, TUNING_RESULT_LABEL):
             individuals = list(individuals)
             individuals.append(self.init_individual)  # add initial individual to maintain consistency of inheritance
         history.add_to_history(individuals=individuals,