def test_basics():
exp = ap.Experiment(MyModel, [{'steps': 1}] * 3)
results = exp.run()
assert 'variables' not in results
assert exp.name == 'MyModel'
exp = ap.Experiment(MyModel, [{'steps': 1}] * 3, record=True)
results = exp.run()
assert 'variables' in results
def test_parallel_processing():
exp = ap.Experiment(MyModel, [{'steps': 1}] * 3)
pool = mp.Pool(mp.cpu_count())
results = exp.run(pool)
exp2 = ap.Experiment(MyModel, [{'steps': 1}] * 3)
results2 = exp2.run()
del results.info
del results2.info
assert results == results2
def test_sobol():
param_ranges = {'x': (0., 1.)}
sample = ap.sample_saltelli(param_ranges, n=10)
results = ap.Experiment(MyModel, sample).run()
ap.sensitivity_sobol(results, param_ranges, measures='x')
assert results.sensitivity['S1'][0] == 0.6607875959282447
# Test if a non-varied parameter causes errors
param_ranges = {'x': (0., 1.), 'y': 1}
sample = ap.sample_saltelli(param_ranges, n=10)
results = ap.Experiment(MyModel, sample).run()
ap.sensitivity_sobol(results, param_ranges)
assert results.sensitivity['S1'][0] == 0.6607875959282447
def test_calc_sobol():
si = 1.2380952380952384
parameters = {'x': ap.Range(0., 1.)}
sample = ap.Sample(parameters,
n=8,
method='saltelli',
calc_second_order=False)
results = ap.Experiment(SobolModel, sample).run(display=False)
results.calc_sobol(reporters='x')
assert results.sensitivity.sobol['S1'][0] == si
# Test if a non-varied parameter causes errors
parameters = {'x': ap.Range(0., 1.), 'y': 1}
sample = ap.Sample(parameters,
n=8,
method='saltelli',
calc_second_order=False)
results = ap.Experiment(SobolModel, sample).run(display=False)
results.calc_sobol()
assert results.sensitivity.sobol['S1'][0] == si
# Test wrong sample type raises error
parameters = {'x': ap.Range(0., 1.), 'y': 1}
sample = ap.Sample(parameters, n=8)
results = ap.Experiment(SobolModel, sample).run(display=False)
with pytest.raises(AgentpyError):
results.calc_sobol()
# Test merging iterations
# TODO Improve
parameters = {'x': ap.Range(0., 1.)}
sample = ap.Sample(parameters,
n=8,
method='saltelli',
calc_second_order=False)
results = ap.Experiment(SobolModel, sample,
iterations=10).run(display=False)
results.calc_sobol(reporters='x')
assert results.sensitivity.sobol['S1'][0] == si
# Test calc_second_order
parameters = {'x': ap.Range(0., 1.), 'y': 1}
sample = ap.Sample(parameters,
n=8,
method='saltelli',
calc_second_order=True)
results = ap.Experiment(SobolModel, sample).run(display=False)
results.calc_sobol()
assert results.sensitivity.sobol[('S2', 'x')][0].__repr__() == 'nan'
def test_interactive():
"""Test only for errors."""
def interactive_plot(m):
print("x =", m.p.x)
param_ranges = {'x': (0., 1.)}
sample = ap.sample(param_ranges, n=10)
exp = ap.Experiment(ap.Model, sample)
exp.interactive(interactive_plot)
assert True
def test_random():
parameters = {'steps': 0, 'seed': ap.Values(1, 1, 2)}
class Model(ap.Model):
def setup(self):
self.report('x', self.model.random.random())
sample = ap.Sample(parameters)
exp = ap.Experiment(Model, sample, iterations=2, randomize=True)
results = exp.run()
l = list(results.reporters['x'])
assert l[0] != l[1]
assert l[0:2] == l[2:4]
assert l[0:2] != l[4:6]
sample = ap.Sample(parameters)
exp = ap.Experiment(Model, sample, iterations=2, randomize=False)
results = exp.run()
l = list(results.reporters['x'])
assert l[0] == l[1]
assert l[0:2] == l[2:4]
assert l[0:2] != l[4:6]
exp = ap.Experiment(Model, parameters, iterations=2)
results = exp.run()
l1 = list(results.reporters['x'])
assert l1 == [0.03542265363082542, 0.08363464439430013]
parameters['seed'] = 1
exp = ap.Experiment(Model, parameters, iterations=2)
results = exp.run()
l2 = list(results.reporters['x'])
assert l1 == l2
def test_arrange_scenarios():
class MyModel(ap.Model):
def step(self):
self.record('test', 1)
self.measure('test', 1)
self.stop()
exp = ap.Experiment(MyModel, scenarios=['sc1', 'sc2'], record=True)
results = exp.run()
assert results.arrange() is None
assert results.arrange(variables='all', scenarios='sc1').shape == (1, 4)
assert results.arrange(measures='all', scenarios='sc1').shape == (1, 3)
def test_testing_model():
parameters = {'steps': 2, 'px': ap.Values(1, 2)}
sample = ap.Sample(parameters)
settings = {'iterations': 2, 'record': True}
pytest.model_instance = model = ModelType0(list(sample)[0])
pytest.model_results = model_results = model.run(display=False)
exp = ap.Experiment(ModelType0, sample, **settings)
pytest.exp_results = exp_results = exp.run(display=False)
type_list = ['AgentType1', 'AgentType2', 'EnvType3', 'EnvType4']
assert list(model_results.variables.keys()) == type_list
assert list(exp_results.variables.keys()) == type_list
def test_repr():
param_ranges = {'x': ap.Range(0., 1.), 'y': 1}
sample = ap.Sample(param_ranges, n=10)
results = ap.Experiment(MyModel, sample, record=True).run()
assert results.__repr__() == repr
def step(self):
self.agents.record('wealth')
self.agents.wealth_transfer()
# Perform single run
parameters = {'n': 10, 'steps': 10}
model = MoneyModel(parameters)
results = model.run()
# Perform multiple runs
variable_params = {
'n': ap.IntRange(10, 500),
'steps': 10
}
sample = ap.Sample(variable_params, n=49)
exp = ap.Experiment(
MoneyModel,
sample,
iterations=5,
record=True
)
results = exp.run()