evolvepy package

Subpackages

• evolvepy.callbacks package
  • Submodules
  • evolvepy.callbacks.callback module
    • Callback
      • Callback.__init__()
      • Callback.callbacks
      • Callback.evaluator
      • Callback.generator
      • Callback.on_evaluator_end()
      • Callback.on_generator_end()
      • Callback.on_generator_start()
      • Callback.on_start()
      • Callback.on_stop()
  • evolvepy.callbacks.dynamic_mutation module
    • DynamicMutation
      • DynamicMutation.EXPLORATION
      • DynamicMutation.NORMAL
      • DynamicMutation.REFINEMENT
      • DynamicMutation.__init__()
      • DynamicMutation.on_evaluator_end()
  • evolvepy.callbacks.incremental_evolution module
    • IncrementalEvolution
      • IncrementalEvolution.__init__()
      • IncrementalEvolution.on_generator_start()
  • evolvepy.callbacks.logger module
    • FileStoreLogger
      • FileStoreLogger.__init__()
      • FileStoreLogger.log_name
      • FileStoreLogger.on_start()
      • FileStoreLogger.save_dynamic_log()
      • FileStoreLogger.save_static_log()
    • Logger
      • Logger.__init__()
      • Logger.on_evaluator_end()
      • Logger.on_generator_end()
      • Logger.on_start()
      • Logger.save_dynamic_log()
      • Logger.save_static_log()
    • MemoryStoreLogger
      • MemoryStoreLogger.__init__()
      • MemoryStoreLogger.config_log
      • MemoryStoreLogger.log
      • MemoryStoreLogger.save_dynamic_log()
      • MemoryStoreLogger.save_static_log()
  • Module contents
    • Callback
      • Callback.__init__()
      • Callback.callbacks
      • Callback.evaluator
      • Callback.generator
      • Callback.on_evaluator_end()
      • Callback.on_generator_end()
      • Callback.on_generator_start()
      • Callback.on_start()
      • Callback.on_stop()
    • DynamicMutation
      • DynamicMutation.EXPLORATION
      • DynamicMutation.NORMAL
      • DynamicMutation.REFINEMENT
      • DynamicMutation.__init__()
      • DynamicMutation.on_evaluator_end()
    • FileStoreLogger
      • FileStoreLogger.__init__()
      • FileStoreLogger.log_name
      • FileStoreLogger.on_start()
      • FileStoreLogger.save_dynamic_log()
      • FileStoreLogger.save_static_log()
    • IncrementalEvolution
      • IncrementalEvolution.__init__()
      • IncrementalEvolution.on_generator_start()
    • Logger
      • Logger.__init__()
      • Logger.on_evaluator_end()
      • Logger.on_generator_end()
      • Logger.on_start()
      • Logger.save_dynamic_log()
      • Logger.save_static_log()
    • MemoryStoreLogger
      • MemoryStoreLogger.__init__()
      • MemoryStoreLogger.config_log
      • MemoryStoreLogger.log
      • MemoryStoreLogger.save_dynamic_log()
      • MemoryStoreLogger.save_static_log()
• evolvepy.evaluator package
  • Submodules
  • evolvepy.evaluator.aggregator module
    • FitnessAggregator
      • FitnessAggregator.MAX
      • FitnessAggregator.MEAN
      • FitnessAggregator.MEDIAN
      • FitnessAggregator.MIN
      • FitnessAggregator.MODE_NAMES
      • FitnessAggregator.__init__()
      • FitnessAggregator.call()
      • FitnessAggregator.func
  • evolvepy.evaluator.cache module
    • FitnessCache
      • FitnessCache.__init__()
      • FitnessCache.call()
      • FitnessCache.get_individual_representation()
  • evolvepy.evaluator.evaluator module
    • EvaluationStage
      • EvaluationStage.__init__()
      • EvaluationStage.call()
    • Evaluator
      • Evaluator.__init__()
      • Evaluator.call()
      • Evaluator.scores
  • evolvepy.evaluator.function_evaluator module
    • FunctionEvaluator
      • FunctionEvaluator.JIT
      • FunctionEvaluator.JIT_PARALLEL
      • FunctionEvaluator.NJIT
      • FunctionEvaluator.NJIT_PARALLEL
      • FunctionEvaluator.PYTHON
      • FunctionEvaluator.__init__()
      • FunctionEvaluator.call()
      • FunctionEvaluator.static_call()
  • evolvepy.evaluator.multiple module
    • MultipleEvaluation
      • MultipleEvaluation.__init__()
      • MultipleEvaluation.call()
  • evolvepy.evaluator.process_evaluator module
    • ProcessEvaluator
      • ProcessEvaluator.__init__()
      • ProcessEvaluator.call()
    • ProcessFitnessFunction
      • ProcessFitnessFunction.__init__()
      • ProcessFitnessFunction.evaluate()
      • ProcessFitnessFunction.setup()
    • evaluate_forever()
  • Module contents
• evolvepy.generator package
  • Subpackages
    • evolvepy.generator.crossover package
      • Submodules
      • evolvepy.generator.crossover.crossover module
      • Module contents
    • evolvepy.generator.mutation package
      • Submodules
      • evolvepy.generator.mutation.binary_mutation module
      • evolvepy.generator.mutation.mutation module
      • evolvepy.generator.mutation.numeric_mutation module
      • Module contents
    • evolvepy.generator.selection package
      • Submodules
      • evolvepy.generator.selection.selection module
      • Module contents
  • Submodules
  • evolvepy.generator.basic_layers module
    • Block
      • Block.__init__()
      • Block.call()
    • ElitismLayer
      • ElitismLayer.__init__()
      • ElitismLayer.call()
    • FilterFirsts
      • FilterFirsts.__init__()
      • FilterFirsts.call()
    • RandomPredation
      • RandomPredation.__init__()
      • RandomPredation.call()
    • Sort
      • Sort.__init__()
      • Sort.call()
  • evolvepy.generator.combine module
    • CombineLayer
      • CombineLayer.__init__()
      • CombineLayer.call_chromosomes()
      • CombineLayer.combine()
  • evolvepy.generator.context module
    • Context
      • Context.__init__()
      • Context.block_all
      • Context.chromosome_names
      • Context.copy()
      • Context.default_values
      • Context.have_value()
      • Context.population_size
      • Context.sorted
  • evolvepy.generator.descriptor module
    • Descriptor
      • Descriptor.__init__()
      • Descriptor.chromosome_names
      • Descriptor.chromosome_ranges
      • Descriptor.dtype
  • evolvepy.generator.firstgen module
    • FirstGenLayer
      • FirstGenLayer.__init__()
      • FirstGenLayer.call()
      • FirstGenLayer.call_chromosomes()
  • evolvepy.generator.generator module
    • Generator
      • Generator.__init__()
      • Generator.add()
      • Generator.fitness
      • Generator.generate()
      • Generator.get_all_dynamic_parameters()
      • Generator.get_all_static_parameters()
      • Generator.get_parameter()
      • Generator.get_parameters()
      • Generator.set_parameter()
      • Generator.set_parameters()
  • evolvepy.generator.layer module
    • ChromosomeOperator
      • ChromosomeOperator.__init__()
      • ChromosomeOperator.call()
      • ChromosomeOperator.call_chromosomes()
    • Concatenate
      • Concatenate.__init__()
    • Layer
      • Layer.__init__()
      • Layer.call()
      • Layer.context
      • Layer.fitness
      • Layer.next
      • Layer.population
      • Layer.send_next()
  • evolvepy.generator.thread_pool module
    • ThreadPool
      • ThreadPool.add_job()
      • ThreadPool.end_queue
      • ThreadPool.initialized
      • ThreadPool.job_queue
      • ThreadPool.n_thread
      • ThreadPool.serial
      • ThreadPool.thread_pool
      • ThreadPool.wait_for_end()
      • ThreadPool.waiting
    • thread_function()
  • Module contents
• evolvepy.integrations package
  • Subpackages
    • evolvepy.integrations.gym package
      • Submodules
      • evolvepy.integrations.gym.gym module
      • Module contents
    • evolvepy.integrations.nvtx package
      • Submodules
      • evolvepy.integrations.nvtx.annotate_se module
      • evolvepy.integrations.nvtx.colors module
      • evolvepy.integrations.nvtx.mock module
      • Module contents
    • evolvepy.integrations.ray package
      • Submodules
      • evolvepy.integrations.ray.distributed_evaluator module
      • Module contents
    • evolvepy.integrations.tf_keras package
      • Submodules
      • evolvepy.integrations.tf_keras.tf_keras module
      • Module contents
    • evolvepy.integrations.unity_gym package
      • Submodules
      • evolvepy.integrations.unity_gym.unity module
      • Module contents
    • evolvepy.integrations.wandb package
      • Submodules
      • evolvepy.integrations.wandb.wandb module
      • Module contents
  • Module contents

Submodules

evolvepy.configurable module

class evolvepy.configurable.Configurable(parameters: Dict[str, object] | None = None, dynamic_parameters: Dict[str, bool] | None = None, name: str | None = None)

Bases: ABC

Base class for Configurable classes.

Configurable elements classes have parameters that can be logged using EvolvePy’s loggers.

__element_count

The number of created class instances. Is a class attribute.

Type:

int

__init__(parameters: Dict[str, object] | None = None, dynamic_parameters: Dict[str, bool] | None = None, name: str | None = None) → None

Configurable constructor.

Parameters:

• parameters (Dict[str, object]) – Object logable parameters.

• dynamic_parameters (Dict[str, bool]) – Parameters that may change mid-run. The existence of a key indicates that it can change, its value indicates whether the change is locked (False) or not (True).

property dynamic_parameters: Dict[str, object]

All dynamic parameters.

lock_parameter(name: str) → None

Lock some parameter, avoiding its change.

Parameters:

name (str) – The parameter name.

property name: str

Object name for logs.

property parameters: Dict[str, object]

Object parameters.

Setter:

Parameters:

value (Union[Dict[str, object], Tuple[str, object]]) – If Dict[str, object], changes the value of all valid keys, if Tuple[str, object], changes the single key value, if valid.

classmethod reset_count()

Reset the class instances count.

property static_parameters: Dict[str, object]

All static parameters.

unlock_parameter(name: str) → None

Unlock some parameter, allowing its change.

Parameters:

name (str) – The parameter name.

evolvepy.evolver module

class evolvepy.evolver.Evolver(generator: Generator, evaluator: Evaluator, population_size: int, callbacks: Callback | List[Callback] | None = None)

Bases: object

Basic class for evolving generations.

It combines the generator, evaluator and callbacks and runs the evolutionary process.

__init__(generator: Generator, evaluator: Evaluator, population_size: int, callbacks: Callback | List[Callback] | None = None)

Evolver constructor.

Parameters:

• generator (Generator) – Generator for generating populations.

• evaluator (Evaluator) – Evaluator for evaluating individuals.

• population_size (int) – Size of population.

• callbacks (Union[Callback, List[Callback]], optional) – Callabacks that will be called during evolution. Defaults to None.

evolve(generations: int, verbose: bool = False) → Tuple[ndarray, ndarray]

Evolves the population for a few generations

Parameters:

• generations (int) – Number of generations to evolve

• verbose (bool) – If should print the generation number, maximum fitness and time. Defaults to False.

Returns:

The first element is the fitness history of all generations, in order.

The second is the last population evaluated.

Return type:

Tuple[np.ndarray, np.ndarray]

Module contents