def test_validate_outputs(self):
# construct runset using existing sampler output
stan = os.path.join(datafiles_path, 'bernoulli.stan')
exe = os.path.join(datafiles_path, 'bernoulli')
model = Model(exe_file=exe, stan_file=stan)
jdata = os.path.join(datafiles_path, 'bernoulli.data.json')
output = os.path.join(goodfiles_path, 'bern')
args = SamplerArgs(
model,
chain_ids=[1, 2, 3, 4],
seed=12345,
data=jdata,
output_file=output,
sampling_iters=100,
max_treedepth=11,
adapt_delta=0.95,
)
runset = RunSet(chains=4, args=args)
retcodes = runset.retcodes
for i in range(len(retcodes)):
runset.set_retcode(i, 0)
self.assertTrue(runset.check_retcodes())
runset.check_console_msgs()
runset.validate_csv_files()
self.assertEqual(4, runset.chains)
self.assertEqual(100, runset.draws)
self.assertEqual(8, len(runset.column_names))
self.assertEqual('lp__', runset.column_names[0])
def test_check_retcodes(self):
stan = os.path.join(datafiles_path, 'bernoulli.stan')
exe = os.path.join(datafiles_path, 'bernoulli')
model = Model(exe_file=exe, stan_file=stan)
jdata = os.path.join(datafiles_path, 'bernoulli.data.json')
output = os.path.join(goodfiles_path, 'bern')
args = SamplerArgs(
model,
chain_ids=[1, 2, 3, 4],
seed=12345,
data=jdata,
output_file=output,
sampling_iters=100,
max_treedepth=11,
adapt_delta=0.95,
)
runset = RunSet(chains=4, args=args)
retcodes = runset.retcodes
self.assertEqual(4, len(retcodes))
for i in range(len(retcodes)):
self.assertEqual(-1, runset.retcode(i))
runset.set_retcode(0, 0)
self.assertEqual(0, runset.retcode(0))
for i in range(1, len(retcodes)):
self.assertEqual(-1, runset.retcode(i))
self.assertFalse(runset.check_retcodes())
for i in range(1, len(retcodes)):
runset.set_retcode(i, 0)
self.assertTrue(runset.check_retcodes())
def test_validate_bad_hdr(self):
stan = os.path.join(datafiles_path, 'bernoulli.stan')
exe = os.path.join(datafiles_path, 'bernoulli')
model = Model(exe_file=exe, stan_file=stan)
jdata = os.path.join(datafiles_path, 'bernoulli.data.json')
output = os.path.join(badfiles_path, 'bad-hdr-bern')
args = SamplerArgs(model, chain_ids=[1,2,3,4],
seed=12345,
data=jdata,
output_file=output,
sampling_iters=100,
max_treedepth=11,
adapt_delta=0.95)
runset = RunSet(chains=4, args=args)
retcodes = runset.retcodes
for i in range(len(retcodes)):
runset.set_retcode(i, 0)
self.assertTrue(runset.check_retcodes())
with self.assertRaisesRegex(ValueError, 'header mismatch'):
runset.validate_csv_files()
def do_sample(runset: RunSet, idx: int) -> None:
"""
Encapsulates call to sampler.
Spawn process, capture console output to file, record returncode.
"""
cmd = runset.cmds[idx]
print('start chain {}. '.format(idx + 1))
proc = subprocess.Popen(cmd.split(),
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
proc.wait()
stdout, stderr = proc.communicate()
transcript_file = runset.console_files[idx]
print('finish chain {}. '.format(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'))
runset.set_retcode(idx, proc.returncode)