def test_util_random_seed(self):
samples = 10
stochastic_samples = []
for i in range(samples):
pyprob.seed(None)
dist = pyprob.distributions.Normal(0, 1)
sample = dist.sample()
stochastic_samples.append(float(sample))
deterministic_samples = []
for i in range(samples):
pyprob.seed(123)
dist = pyprob.distributions.Normal(0, 1)
sample = dist.sample()
deterministic_samples.append(float(sample))
util.eval_print('samples', 'stochastic_samples',
'deterministic_samples')
self.assertTrue(not all(sample == stochastic_samples[0]
for sample in stochastic_samples))
self.assertTrue(
all(sample == deterministic_samples[0]
for sample in deterministic_samples))
'graph/posterior_rmh_graph')
pyprob.diagnostics.graph(posterior_rmh,
file_name=posterior_rmh_graph_file_name)
posterior_rmh_graph_aggregated_file_name = os.path.join(
results_dir, 'graph_aggregated/posterior_rmh_graph_aggregated')
pyprob.diagnostics.graph(
posterior_rmh,
use_address_base=True,
file_name=posterior_rmh_graph_aggregated_file_name)
posterior_is.close()
posterior_ic.close()
posterior_rmh.close()
posterior_rmh_gt.close()
if __name__ == '__main__':
pyprob.seed(1)
current_dir = os.path.dirname(os.path.abspath(__file__))
print('Current dir: {}'.format(current_dir))
results_dir = os.path.join(current_dir, 'gum_marsaglia/replace_true')
produce_results(replace=True, results_dir=results_dir)
results_dir = os.path.join(current_dir, 'gum_marsaglia/replace_false')
produce_results(replace=False, results_dir=results_dir)
print('Done')
#
# posterior = self._model.posterior(1, inference_engine=InferenceEngine.LIGHTWEIGHT_METROPOLIS_HASTINGS, observe={'obs0': 8, 'obs1': 9})
# trace = posterior[0]
# trace_addresses_controlled = [v.address for v in trace.variables_controlled]
# trace_addresses = [v.address for v in trace.variables]
#
# util.eval_print('trace', 'trace_addresses_controlled', 'trace_addresses_controlled_correct', 'trace_addresses', 'trace_addresses_correct')
#
# self.assertEqual(trace_addresses_controlled_correct, trace_addresses_controlled)
# self.assertEqual(trace_addresses_correct, trace_addresses)
#
# def test_trace_posterior_random_walk_metropolis_hastings(self):
# trace_addresses_controlled_correct = ['30__forward__x__Uniform__1', '40__forward__y__Uniform__1', '30__forward__x__Uniform__2', '40__forward__y__Uniform__2']
# trace_addresses_correct = ['30__forward__x__Uniform__1', '40__forward__y__Uniform__1', '30__forward__x__Uniform__2', '40__forward__y__Uniform__2', '84__forward__?__Normal__1', '98__forward__?__Normal__1']
#
# posterior = self._model.posterior(1, inference_engine=InferenceEngine.RANDOM_WALK_METROPOLIS_HASTINGS, observe={'obs0': 8, 'obs1': 9})
# trace = posterior[0]
# trace_addresses_controlled = [v.address for v in trace.variables_controlled]
# trace_addresses = [v.address for v in trace.variables]
#
# util.eval_print('trace', 'trace_addresses_controlled', 'trace_addresses_controlled_correct', 'trace_addresses', 'trace_addresses_correct')
#
# self.assertEqual(trace_addresses_controlled_correct, trace_addresses_controlled)
# self.assertEqual(trace_addresses_correct, trace_addresses)
if __name__ == '__main__':
pyprob.seed(123)
pyprob.set_verbosity(1)
unittest.main(verbosity=2)
def random():
pyprob.seed(123)