def _load_tests_from_cache(test_corpus):
tests, file_key = tests_cache.get(test_corpus, (None, None))
latest_on_s3 = find_latest_s3_file(EMMAA_BUCKET_NAME,
f'tests/{test_corpus}', '.pkl')
if file_key != latest_on_s3:
tests, file_key = load_tests_from_s3(test_corpus, EMMAA_BUCKET_NAME)
if isinstance(tests, dict):
tests = tests['tests']
tests_cache[test_corpus] = (tests, file_key)
else:
logger.info(f'Loaded {test_corpus} from cache.')
return tests
def test_load_tests_from_s3():
# Local imports are recommended when using moto
from emmaa.model_tests import load_tests_from_s3, StatementCheckingTest
client = setup_bucket(add_tests=True)
test_dict, _ = load_tests_from_s3('simple_tests', bucket=TEST_BUCKET_NAME)
assert isinstance(test_dict, dict)
tests = test_dict['tests']
assert isinstance(tests, list)
assert len(tests) == 1
test = tests[0]
assert isinstance(test, StatementCheckingTest)
assert isinstance(test_dict['test_data'], dict)
assert isinstance(test_dict['test_data']['description'], str)
def test_model_to_tests():
# Local imports are recommended when using moto
from emmaa.model_tests import model_to_tests, load_tests_from_s3, \
StatementCheckingTest
client = setup_bucket(add_model=True)
test_dict = model_to_tests('test', bucket=TEST_BUCKET_NAME)
assert isinstance(test_dict, dict)
assert 'test_data' in test_dict
assert 'tests' in test_dict
tests = test_dict['tests']
assert len(tests) == 2
assert isinstance(tests[0], StatementCheckingTest)
loaded_tests, _ = load_tests_from_s3('test_tests', bucket=TEST_BUCKET_NAME)
assert loaded_tests
assert isinstance(loaded_tests, dict)
assert 'test_data' in loaded_tests
assert 'tests' in loaded_tests
def test_model_to_tests():
# Local imports are recommended when using moto
from emmaa.model_tests import model_to_tests, load_tests_from_s3, \
StatementCheckingTest
from emmaa.model import save_config_to_s3, load_config_from_s3
client = setup_bucket(add_model=True, add_mm=True)
test_dict = model_to_tests('test', bucket=TEST_BUCKET_NAME)
assert isinstance(test_dict, dict)
assert 'test_data' in test_dict
assert 'tests' in test_dict
tests = test_dict['tests']
# With default config get tests for each statement
assert len(tests) == 2
# Modify config to filter
config = load_config_from_s3('test', bucket=TEST_BUCKET_NAME)
config['make_tests'] = {
'filter': {
'conditions': {
'curated': False
},
'evid_policy': 'any'
}
}
save_config_to_s3('test', config, bucket=TEST_BUCKET_NAME)
test_dict = model_to_tests('test', bucket=TEST_BUCKET_NAME)
assert isinstance(test_dict, dict)
assert 'test_data' in test_dict
assert 'tests' in test_dict
tests = test_dict['tests']
# With modified config statements are filtered
assert len(tests) == 1
assert isinstance(tests[0], StatementCheckingTest)
loaded_tests, _ = load_tests_from_s3('test_tests', bucket=TEST_BUCKET_NAME)
assert loaded_tests
assert isinstance(loaded_tests, dict)
assert 'test_data' in loaded_tests
assert 'tests' in loaded_tests
def test_load_tests_from_s3():
tests = load_tests_from_s3('simple_model_test.pkl')
assert isinstance(tests, list)
assert len(tests) == 1
test = tests[0]
assert isinstance(test, StatementCheckingTest)
'--chemical_disease',
help='Path to ctd chemical disease statements pkl',
required=True)
parser.add_argument('-cg',
'--chemical_gene',
help='Path to ctd chemical gene statements pkl',
required=True)
parser.add_argument('-gd',
'--gene_disease',
help='Path to ctd gene disease statements pkl',
required=True)
args = parser.parse_args()
# Load model statements and tests
model_stmts, _ = get_assembled_statements('covid19')
curated_tests, _ = load_tests_from_s3('covid19_curated_tests')
if isinstance(curated_tests, dict): # if descriptions were added
curated_tests = curated_tests['tests']
mitre_tests, _ = load_tests_from_s3('covid19_mitre_tests')
if isinstance(mitre_tests, dict): # if descriptions were added
mitre_tests = mitre_tests['tests']
all_test_stmts = [test.stmt for test in curated_tests] + \
[test.stmt for test in mitre_tests]
# Load CTD statements
chem_dis_stmts = ac.load_statements(args.chemical_disease)
chem_gene_stmts = ac.load_statements(args.chemical_gene)
gene_dis_stmts = ac.load_statements(args.gene_disease)
all_ctd_stmts = chem_dis_stmts + chem_gene_stmts + gene_dis_stmts
# Collect most frequents gene groundings for model statements and
