def test_iter_yield_times(self):
"""Sampler.__iter__ yields for each interval"""
process = Process([stocal.Event([], ['a'], 3., 3.)])
target = [30., 60., 90.]
sampler = self.Sampler(process.sample({}))
for a,b in zip((result[0] for result in sampler), target):
self.assertEqual(a, b)
def test_iter_skipping_behavior(self):
"""Sampler.__iter__ skips empty iterations if initialized with skip=True"""
process = Process([stocal.Event([], ['a'], 0.5, 2.4)])
target = [1., 3., 6., 8., 11.]
sampler = self.Sampler(process.sample({}), skip=True)
for a,b in zip((result[0] for result in sampler), target):
self.assertEqual(a, b)
def test_iter_works_when_chained(self):
"""test that every and until can be chained"""
process = Process([stocal.MassAction(['a'], [], .1)])
sampler = self.Sampler(process.sample({'a': 20}))
sampler = sampler.until(time=5)
time, trans, state = next(iter(sampler))
self.assertEqual(time, 1.)
def test_iter_empty_filter_list(self):
"""Sampler.__iter__ advances to simulation end when transitions are empty"""
process = Process([stocal.MassAction(['a'], [''], 1.)])
sampler = self.Sampler(process.sample({'a':10}), [])
with self.assertRaises(StopIteration):
next(iter(sampler))
self.assertEqual(sampler.state['a'], 0)
def test_iter_correct_averages(self):
"""Sampler.__iter__ calculates correct averages"""
process = Process([stocal.Event([], ['a'], 0., 3.)])
target = [5.5, 15.5, 25.5]
sampler = self.Sampler(process.sample({}))
for a,b in zip((result[1]['a'] for result in sampler), target):
self.assertAlmostEqual(a, b)
def test_iter_empty_does_not_proceed(self, steps=10):
"""Sampler.__iter__ does not increase steps for empty process"""
process = Process([])
traj = process.sample({})
sampler = self.Sampler(traj, steps)
for _ in sampler:
pass
self.assertEqual(sampler.step, 0)
def test_iter_number_of_steps(self, steps=10):
"""Sampler.__iter__ yields exact number of steps"""
process = Process([stocal.MassAction([], ['a'], 1.)])
traj = process.sample({})
sampler = self.Sampler(traj, steps)
for _ in sampler:
pass
self.assertEqual(sampler.step, steps)
def test_iter_performs_all_transitions(self, target=100):
"""Sampler.__iter__ performs all transitions"""
process = Process([stocal.MassAction(['a'], [], 1.)])
sampler = self.Sampler(process.sample({'a': target}))
total = 0
for time, state, trans in sampler:
total += sum(trans.values())
self.assertEqual(total, target)
def test_iter_advances_empty(self, tmax=10.):
"""Sampler.__iter__ advances to end time for empty processes"""
process = Process()
traj = process.sample({})
sampler = self.Sampler(traj, tmax)
for _ in sampler:
pass
self.assertEqual(sampler.time, tmax)
def test_iter_correct_transitions(self):
"""Sampler.__iter__ only yields after declared transitions"""
r1 = stocal.MassAction(['a'], ['b'], 1.)
r2 = stocal.MassAction(['b'], ['c'], 1.)
process = Process([r1, r2])
sampler = self.Sampler(process.sample({'a':50, 'b':50}), [r1])
for result in sampler:
self.assertIn(r1, result[2])
def test_iter_advances_short(self, tmax=10.):
"""Sampler.__iter__ advances to end time for short lasting processes"""
process = Process([stocal.Event(['a'], [], 1., 1.)])
traj = process.sample({'a': 3})
sampler = self.Sampler(traj, tmax)
for _ in sampler:
pass
self.assertEqual(sampler.time, tmax)
def test_iter_returns_triple(self):
"""Sampler.__iter__ returns time, state, dict triple"""
process = Process([stocal.Event([], ['a'], 1.)])
sampler = process.sample({})
result = next(iter(sampler))
self.assertEqual(len(result), 3)
self.assertIsInstance(result[0], float)
self.assertIsInstance(result[1], stocal.multiset)
self.assertIsInstance(result[2], dict)
def test_iter_correct_skipped_averages(self):
"""Sampler.__iter__ calculates correct averages"""
process = Process([
stocal.Event([], ['a'], 0., 3.),
stocal.Event([], ['a'], 1., 2.)])
target = [1., 2., 4., 5. ,6., 7., 9., 10., 11.]
sampler = self.Sampler(process.sample({}), skip=True)
for a,b in zip((result[1]['a'] for result in sampler), target):
self.assertAlmostEqual(a, b)
def test_iter_includes_all_transitions_at_tmax(self, tmax=1.):
"""Sampler.__iter__ includes all events that happen at tmax"""
process = Process([
stocal.Event([], ['a'], tmax),
stocal.Event([], ['b'], 0., tmax),
stocal.Event([], ['c'], tmax/2, tmax/2)])
traj = process.sample({})
sampler = self.Sampler(traj, tmax)
for _ in sampler:
pass
self.assertEqual(sampler.step, 5)
def test_time_returns_trajectory_time(self):
"""Sampler.time returns trajectory time"""
process = Process([stocal.Event([], ['a'], 1., 10.)])
sampler = process.sample({})
self.assertIsInstance(sampler.time, float)
def test_state_returns_trajectory_state(self):
"""Sampler.state returns trajectory state"""
process = Process([stocal.Event([], ['a'], 1., 10.)])
state = {}
sampler = process.sample(state)
self.assertEqual(sampler.state, state)
def test_filter_returns_correct_sampler(self):
"""Sampler.filter() returns FilteredSampler"""
process = Process([stocal.Event([], ['a'], 1., 10.)])
sampler = process.sample({}).filter([stocal.MassAction])
self.assertIsInstance(sampler, stocal.experimental.samplers.FilteredSampler)
def test_average_steps_returns_correct_sampler(self):
"""Sampler.average(steps) returns AverageStepSampler"""
process = Process([stocal.Event([], ['a'], 1., 10.)])
sampler = process.sample({}).average(steps=10)
self.assertIsInstance(sampler, stocal.experimental.samplers.AverageStepSampler)
def test_every_time_returns_correct_sampler(self):
"""Sampler.every(time) returns EveryTimeSampler"""
process = Process([stocal.Event([], ['a'], 1., 10.)])
sampler = process.sample({}).every(time=1.)
self.assertIsInstance(sampler, stocal.experimental.samplers.EveryTimeSampler)
def test_iter_yields_stop_when_empty(self):
"""Sampler.__iter__ raises StopIteration for empty process"""
process = Process([])
with self.assertRaises(StopIteration):
next(iter(process.sample({})))