def __init__(self, path, treatments, name=None, seed=1, analysis_path=None, full=True):
logtools.set_logging()
if name is None:
name = _make_name_from_program()
self.path = _construct_path(path, name)
if analysis_path:
self.analysis_path = _construct_path(analysis_path, name)
else:
self.analysis_path = self.path
self.next_treatment_seq = 0
if full:
self.lineage_class = FullLineage
else:
self.lineage_class = SnapshotLineage
self.seed = seed
self.rng = random.Random(seed)
self.user_interrupt = False
self.treatments = []
for t in treatments:
assert isinstance(t, Treatment)
self.treatments.append(t)
t._bind(self)
self._construct()
def calc_gens(verbose, treatment, replicate):
set_logging(verbose)
try:
the_t, the_rep = NS.experiment.find_matching(treatment, replicate)
except ExperimentError as e:
raise click.BadParameter(e.message)
# First, let's find the best fitness
NS.experiment.visit_lineages(StatsGenerations(NS.experiment),
only_treatment=the_t,
only_replicate=the_rep)
def run(overwrite, verbose, treatment, replicate):
"""Run the simulation.
This will create a new simulation or complete an existing one (if
unfinished).
"""
set_logging(verbose)
try:
the_t, the_rep = NS.experiment.find_matching(treatment, replicate)
except ExperimentError as e:
raise click.BadParameter(e.message)
NS.experiment.run(overwrite=overwrite,
only_treatment=the_t,
only_replicate=the_rep)
def stats(every, treatment, replicate, verbose):
"""Gather statistics about the simulation"""
set_logging(verbose)
try:
the_t, the_rep = NS.experiment.find_matching(treatment, replicate)
except ExperimentError as e:
raise click.BadParameter(e.message)
visitor = StatsVisitor(NS.experiment,
[StatsRelevantControl, StatsFitness,
StatsMutualInformation, StatsBindings])
NS.experiment.visit_generations(visitor,
only_treatment=the_t,
only_replicate=the_rep,
every=every)
def env_robustness(verbose, treatment, replicate, every, only):
set_logging(verbose)
try:
the_t, the_rep = NS.experiment.find_matching(treatment, replicate)
except ExperimentError as e:
raise click.BadParameter(e.message)
# First, let's find the best fitness
visitor = StatsVisitor(NS.experiment,
[StatsEnvironmental])
NS.experiment.visit_generations(visitor,
only_treatment=the_t,
only_replicate=the_rep,
every=every,
only=only)