def test_chains_per_parameter_read_correctly():
"""The chains per parameter option should take effect when passed."""
d = {k: v for k,v in MCMC_RUN_DICT.items()}
d['mcmc']['chains_per_parameter'] = 6
parsed_settings = get_run_settings(d)
assert parsed_settings['mcmc']['chains_per_parameter'] == 6
d['mcmc']['chains_per_parameter'] = 5
with pytest.raises(ValueError):
get_run_settings(d)
def test_correct_defaults_are_applied_from_minimal_specification():
"""A minimal run should generate several default settings for i/o and optional settings."""
# parameters are popped off in order to assert that no additional parameters
# are added and none are not tested.
d = get_run_settings(FULL_RUN_DICT)
assert d.get('output') is not None
assert d['output'].pop('verbosity') == 0
assert d['output'].pop('output_db') == 'out.tdb'
assert d['output'].pop('logfile') == None
assert d['output'].pop('tracefile') == 'trace.npy'
assert d['output'].pop('probfile') == 'lnprob.npy'
assert len(d['output']) == 0
assert d['generate_parameters'].pop('ridge_alpha') == None
assert d['generate_parameters'].pop('aicc_penalty_factor') == None
assert len(d['generate_parameters']) == 2
assert d['mcmc'].pop('save_interval') == 1
assert d['mcmc'].pop('scheduler') == 'dask'
assert d['mcmc'].pop('chains_per_parameter') == 2
assert d['mcmc'].pop('chain_std_deviation') == 0.1
assert d['mcmc'].pop('deterministic') == True
assert d['mcmc'].pop('data_weights') == {
'ACR': 1.0,
'CPM': 1.0,
'HM': 1.0,
'SM': 1.0,
'ZPF': 1.0
}
assert d['mcmc'].pop('prior') == {'name': 'zero'}
assert len(d['mcmc']) == 1
def test_nullable_arguments_are_all_nullable():
nullable_dict = yaml.safe_load(NULL_OUTPUTS_YAML)
null_settings = get_run_settings(nullable_dict)
assert null_settings['output']['tracefile'] is None
assert null_settings['output']['logfile'] is None
assert null_settings['output']['probfile'] is None
assert null_settings['mcmc']['scheduler'] is None
def test_correct_defaults_are_applied_from_minimal_specification():
"""A minimal run should generate several default settings for i/o and optional settings."""
d = get_run_settings(FULL_RUN_DICT)
assert d.get('output') is not None
assert d['output']['verbosity'] == 0
assert d['output']['output_db'] == 'out.tdb'
assert d['output']['tracefile'] == 'trace.npy'
assert d['output']['probfile'] == 'lnprob.npy'
assert d['mcmc']['save_interval'] == 1
assert d['mcmc']['scheduler'] == 'dask'
assert d['mcmc']['chains_per_parameter'] == 2
assert d['mcmc']['chain_std_deviation'] == 0.1
assert d['mcmc']['deterministic'] == True
def test_input_yaml_valid_for_generate_parameters_only():
"""A minimal generate parameters only input file should validate"""
d = get_run_settings(GEN_PARAMS_DICT)
assert d.get('mcmc') is None
def test_input_yaml_valid_for_full_run():
"""A minimal full run input file should validate"""
d = get_run_settings(FULL_RUN_DICT)
def test_SR2016_refdata():
d = {k: v for k,v in GEN_PARAMS_DICT.items()}
d['generate_parameters']['ref_state'] = 'SR2016'
parsed_settings = get_run_settings(d)
assert parsed_settings['generate_parameters']['ref_state'] == 'SR2016'
def test_input_yaml_invalid_for_mcmc_when_input_is_overspecified():
"""An MCMC run must get input from only generate_parameters or an input tdb (w/ or w/o a restart)."""
with pytest.raises(ValueError):
get_run_settings(MCMC_OVERSPECIFIED_INPUT_DICT)
def test_input_yaml_invalid_for_mcmc_when_input_not_defined():
"""An MCMC run must get input from generate_parameters, an input tdb, or a restart and input tdb."""
with pytest.raises(ValueError):
get_run_settings(MCMC_NO_INPUT_DICT)
def test_input_yaml_valid_for_mcmc_from_restart():
"""A minimal mcmc run from a restart should validate"""
d = get_run_settings(MCMC_RESTART_DICT)
assert d.get('generate_parameters') is None
def test_input_yaml_valid_for_mcmc_from_tdb():
"""A minimal mcmc run from tdb input file should validate"""
d = get_run_settings(MCMC_RUN_DICT)
assert d.get('generate_parameters') is None
