leap_ec.distrib package

Submodules

leap_ec.distrib.asynchronous module

leap_ec.distrib.evaluate module

leap_ec.distrib.individual module

Subclass of core.Individual that adds some state relevant for distrib runs.

Adds:

uuid for each individual
birth ID, a unique birth number; first individual has ID 0, the last N-1.

class leap_ec.distrib.individual.DistributedIndividual(genome, decoder=None, problem=None)

Bases: RobustIndividual

birth_id = count(0): Core individual that has unique UUID and birth ID.

clone()

Create a ‘clone’ of this Individual, copying the genome, but not fitness.

The fitness of the clone is set to None. A new UUID is generated and assigned to sefl.uuid. The parents set is updated to include the UUID of the parent. A shallow copy of the parent is made, too, so that ancillary state is also copied.

A deep copy of the genome will be created, so if your Individual has a custom genome type, it’s important that it implements the __deepcopy__() method.

>>> from leap_ec.binary_rep.problems import MaxOnes
>>> from leap_ec.decoder import IdentityDecoder
>>> import numpy as np
>>> genome = np.array([0, 1, 1, 0])
>>> ind = Individual(genome, IdentityDecoder(), MaxOnes())
>>> ind_copy = ind.clone()
>>> ind_copy.genome == ind.genome
array([ True,  True,  True,  True])
>>> ind_copy.problem == ind.problem
True
>>> ind_copy.decoder == ind.decoder
True

leap_ec.distrib.logger module

leap_ec.distrib.probe module

A collection of probe functions tailored for distrib evaluation

leap_ec.distrib.probe.log_pop(update_interval, stream=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='UTF-8'>, header=True)

Regularly update a CSV formatted stream with snapshots of the given population.

This is useful for asynchronous.steady_state() to regularly probe the regularly updated population.

Parameters

update_interval – how often should we write a row?
stream – open stream to which to write rows
header – True if we want a header for the CSV file

Returns

a function for saving regular population snapshots

leap_ec.distrib.probe.log_worker_location(stream=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='UTF-8'>, header=True)

When debugging dask distribution configurations, this function can be used to track what machine and process was used to evaluate a given individual. Accumulates this information to the given stream as a CSV.

Suitable for being passed as the evaluated_probe argument for leap.distrib.asynchronous.steady_state().