POAP 0.1.2

Python Optimization Asynchronous Plumbing.

POAP provides an event-driven framework for building and combining asynchronous optimization strategies. A typical optimization code written with POAP might look like:

from poap.strategy import FixedSampleStrategy from poap.strategy import CheckWorkStrategy from poap.controller import ThreadController from popa.controller import BasicWorkerThread

# samples = list of sample points …

controller = ThreadController() sampler = FixedSampleStrategy(samples) controller.strategy = CheckWorkerStrategy(controller, sampler)

for i in range(NUM_WORKERS):

t = BasicWorkerThread(controller, objective) controller.add_worker(t) t.setDaemon(True) t.start()

result = controller.run() print ‘Best result: {0} at {1}.format(result.value, result.params)

The basic ingredients are a controller capable of asking workers to run function evaluations and a strategy for choosing where to sample. The strategies send the controller proposed actions, which the controller then accepts or rejects; the controller, in turn, informs the strategies of relevant events through callback functions.

Most users will probably want to provide their own strategies, controllers, or both.