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_validate_bad_transcript(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-transcript-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)
with self.assertRaisesRegex(Exception, 'Exception'):
runset.check_console_msgs()