def test_gen_quantities_good(self):
stan = os.path.join(datafiles_path, 'bernoulli_ppc.stan')
model = Model(stan_file=stan)
model.compile()
jdata = os.path.join(datafiles_path, 'bernoulli.data.json')
# synthesize stanfit object -
# see test_stanfit.py, method 'test_validate_good_run'
goodfiles_path = os.path.join(datafiles_path, 'runset-good')
output = os.path.join(goodfiles_path, 'bern')
sampler_args = SamplerArgs(
sampling_iters=100, max_treedepth=11, adapt_delta=0.95
)
cmdstan_args = CmdStanArgs(
model_name=model.name,
model_exe=model.exe_file,
chain_ids=[1, 2, 3, 4],
seed=12345,
data=jdata,
output_basename=output,
method_args=sampler_args,
)
sampler_fit = StanFit(args=cmdstan_args, chains=4)
for i in range(4):
sampler_fit._set_retcode(i, 0)
bern_fit = model.run_generated_quantities(
csv_files=sampler_fit.csv_files,
data=jdata)
# check results - ouput files, quantities of interest, draws
self.assertEqual(bern_fit.chains, 4)
for i in range(4):
self.assertEqual(bern_fit._retcodes[i], 0)
csv_file = bern_fit.csv_files[i]
self.assertTrue(os.path.exists(csv_file))
column_names = [
'y_rep.1',
'y_rep.2',
'y_rep.3',
'y_rep.4',
'y_rep.5',
'y_rep.6',
'y_rep.7',
'y_rep.8',
'y_rep.9',
'y_rep.10'
]
self.assertEqual(bern_fit.column_names, tuple(column_names))
self.assertEqual(bern_fit.draws, 100)
def test_validate_good_run(self):
# construct fit using existing sampler output
exe = os.path.join(datafiles_path, 'bernoulli' + EXTENSION)
jdata = os.path.join(datafiles_path, 'bernoulli.data.json')
output = os.path.join(goodfiles_path, 'bern')
sampler_args = SamplerArgs(sampling_iters=100,
max_treedepth=11,
adapt_delta=0.95)
cmdstan_args = CmdStanArgs(
model_name='bernoulli',
model_exe=exe,
chain_ids=[1, 2, 3, 4],
seed=12345,
data=jdata,
output_basename=output,
method_args=sampler_args,
)
fit = StanFit(args=cmdstan_args, chains=4)
retcodes = fit._retcodes
for i in range(len(retcodes)):
fit._set_retcode(i, 0)
self.assertTrue(fit._check_retcodes())
fit._check_console_msgs()
fit._validate_csv_files()
self.assertEqual(4, fit.chains)
self.assertEqual(100, fit.draws)
self.assertEqual(8, len(fit.column_names))
self.assertEqual('lp__', fit.column_names[0])
df = fit.get_drawset()
self.assertEqual(df.shape,
(fit.chains * fit.draws, len(fit.column_names)))
_ = fit.summary()
# TODO - use cmdstan test files instead
expected = '\n'.join([
'Checking sampler transitions treedepth.',
'Treedepth satisfactory for all transitions.',
'\nChecking sampler transitions for divergences.',
'No divergent transitions found.',
'\nChecking E-BFMI - sampler transitions HMC potential energy.',
'E-BFMI satisfactory for all transitions.',
'\nEffective sample size satisfactory.',
])
self.assertIn(expected, fit.diagnose().replace("\r\n", "\n"))
def _do_sample(self, stanfit: StanFit, idx: int) -> None:
"""
Encapsulates call to sampler.
Spawn process, capture console output to file, record returncode.
"""
cmd = stanfit.cmds[idx]
self._logger.info('start chain %u', idx + 1)
self._logger.debug('sampling: %s', cmd)
proc = subprocess.Popen(cmd.split(),
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
proc.wait()
stdout, stderr = proc.communicate()
transcript_file = stanfit.console_files[idx]
self._logger.info('finish chain %u', idx + 1)
with open(transcript_file, 'w+') as transcript:
if stdout:
transcript.write(stdout.decode('utf-8'))
if stderr:
transcript.write('ERROR')
transcript.write(stderr.decode('utf-8'))
stanfit._set_retcode(idx, proc.returncode)
def test_check_retcodes(self):
exe = os.path.join(datafiles_path, 'bernoulli' + EXTENSION)
jdata = os.path.join(datafiles_path, 'bernoulli.data.json')
sampler_args = SamplerArgs()
cmdstan_args = CmdStanArgs(
model_name='bernoulli',
model_exe=exe,
chain_ids=[1, 2, 3, 4],
data=jdata,
method_args=sampler_args,
)
fit = StanFit(args=cmdstan_args, chains=4)
retcodes = fit._retcodes
self.assertEqual(4, len(retcodes))
for i in range(len(retcodes)):
self.assertEqual(-1, fit._retcode(i))
fit._set_retcode(0, 0)
self.assertEqual(0, fit._retcode(0))
for i in range(1, len(retcodes)):
self.assertEqual(-1, fit._retcode(i))
self.assertFalse(fit._check_retcodes())
for i in range(1, len(retcodes)):
fit._set_retcode(i, 0)
self.assertTrue(fit._check_retcodes())
def test_validate_bad_run(self):
exe = os.path.join(datafiles_path, 'bernoulli' + EXTENSION)
jdata = os.path.join(datafiles_path, 'bernoulli.data.json')
sampler_args = SamplerArgs(sampling_iters=100,
max_treedepth=11,
adapt_delta=0.95)
# some chains had errors
output = os.path.join(badfiles_path, 'bad-transcript-bern')
cmdstan_args = CmdStanArgs(
model_name='bernoulli',
model_exe=exe,
chain_ids=[1, 2, 3, 4],
seed=12345,
data=jdata,
output_basename=output,
method_args=sampler_args,
)
fit = StanFit(args=cmdstan_args, chains=4)
with self.assertRaisesRegex(Exception, 'Exception'):
fit._check_console_msgs()
# csv file headers inconsistent
output = os.path.join(badfiles_path, 'bad-hdr-bern')
cmdstan_args = CmdStanArgs(
model_name='bernoulli',
model_exe=exe,
chain_ids=[1, 2, 3, 4],
seed=12345,
data=jdata,
output_basename=output,
method_args=sampler_args,
)
fit = StanFit(args=cmdstan_args, chains=4)
retcodes = fit._retcodes
for i in range(len(retcodes)):
fit._set_retcode(i, 0)
self.assertTrue(fit._check_retcodes())
with self.assertRaisesRegex(ValueError, 'header mismatch'):
fit._validate_csv_files()
# bad draws
output = os.path.join(badfiles_path, 'bad-draws-bern')
cmdstan_args = CmdStanArgs(
model_name='bernoulli',
model_exe=exe,
chain_ids=[1, 2, 3, 4],
seed=12345,
data=jdata,
output_basename=output,
method_args=sampler_args,
)
fit = StanFit(args=cmdstan_args, chains=4)
retcodes = fit._retcodes
for i in range(len(retcodes)):
fit._set_retcode(i, 0)
self.assertTrue(fit._check_retcodes())
with self.assertRaisesRegex(ValueError, 'draws'):
fit._validate_csv_files()
# mismatch - column headers, draws
output = os.path.join(badfiles_path, 'bad-cols-bern')
cmdstan_args = CmdStanArgs(
model_name='bernoulli',
model_exe=exe,
chain_ids=[1, 2, 3, 4],
seed=12345,
data=jdata,
output_basename=output,
method_args=sampler_args,
)
fit = StanFit(args=cmdstan_args, chains=4)
retcodes = fit._retcodes
for i in range(len(retcodes)):
fit._set_retcode(i, 0)
self.assertTrue(fit._check_retcodes())
with self.assertRaisesRegex(ValueError, 'bad draw'):
fit._validate_csv_files()