def value(self) -> 'simulation.GenMenus':
assert self.alt_count is not None
generator: simulation.MenuGenerator
defaults: bool
if self.rbExhaustive.isChecked():
generator = simulation.Exhaustive()
elif self.rbSampleWithReplacement.isChecked():
generator = simulation.SampleWithReplacement(
menu_count=self.sbSampleWithReplacementCount.value(), )
elif self.rbBinary.isChecked():
generator = simulation.Binary()
else:
raise gui.ValidationError('please select a choice distribution')
if self.cbDefault.currentIndex() == 0:
defaults = False
elif self.cbDefault.currentIndex() == 1:
defaults = True
else:
raise gui.ValidationError('unrecognised choice of defaults')
return simulation.GenMenus(
generator=generator,
defaults=defaults,
)
def _simulation_gen():
f_in = io.BytesIO()
f_out = io.BytesIO()
with Core(f_tee=(f_in, f_out)) as core:
response = simulation.run(
core,
simulation.Request(
name='random',
alternatives=['A', 'B', 'C', 'D', 'E'],
gen_menus=simulation.GenMenus(
generator=simulation.Exhaustive(),
defaults=False,
),
gen_choices=simulation.Uniform(
forced_choice=True,
multiple_choice=False,
),
preserve_deferrals=False,
))
with open('in.bin', 'wb') as f:
f.write(f_in.getbuffer())
with open('out.bin', 'wb') as f:
f.write(f_out.getbuffer())
def test_simulation(nsubjects=256, f_mock=None):
with Core(f_mock=f_mock) as core:
response = simulation.run(
core,
simulation.Request(
name='random',
alternatives=('A', 'B', 'C', 'D', 'E'),
gen_menus=simulation.GenMenus(
generator=simulation.Exhaustive(),
defaults=False,
),
gen_choices=simulation.Uniform(
forced_choice=True,
multiple_choice=False,
),
))
assert len(response.subject_packed) == 223
def analysis_simulation(
self, worker: Worker,
options: 'gui.copycat_simulation.Options') -> 'ExperimentalData':
subjects: List[PackedSubject] = []
with Core() as core:
worker.interrupt = lambda: core.shutdown(
) # register interrupt hook
worker.set_work_size(len(self.subjects) * options.multiplicity)
position = 0
for subject_packed in self.subjects:
for j in range(options.multiplicity):
response = simulation.run(
core,
simulation.Request(
name='random%d' % (j + 1),
alternatives=self.
alternatives, # we don't use subject.alternatives here
gen_menus=simulation.GenMenus(
generator=simulation.Copycat(subject_packed),
defaults=False, # this will be ignored, anyway
),
gen_choices=options.gen_choices,
preserve_deferrals=options.preserve_deferrals,
))
subjects.append(response.subject_packed)
position += 1
if position % 1024 == 0:
worker.set_progress(position)
ds = ExperimentalData(name=options.name,
alternatives=self.alternatives)
ds.subjects = subjects
ds.observ_count = options.multiplicity * self.observ_count
return ds