def check_write_logger(tmpdir, log_file):
if log_file is not None:
log_fp = os.path.join(tmpdir, log_file)
else:
log_fp = None
settings = ASReviewSettings(mode="simulate", model="nb",
query_strategy="rand_max",
balance_strategy="simple")
n_records = 6
n_half = int(n_records/2)
start_labels = np.full(n_records, np.nan, dtype=np.int)
labels = np.zeros(n_records, dtype=np.int)
labels[::2] = np.ones(n_half, dtype=np.int)
methods = np.full((n_records), "initial")
methods[2::] = np.full((int(n_records-2)), "random")
methods[2::2] = np.full((int((n_records-2)/2)), "max")
with open_logger(log_fp) as logger:
logger.add_settings(settings)
logger.set_labels(start_labels)
current_labels = np.copy(start_labels)
for i in range(n_records):
query_i = int(i/2)
proba = None
if i >= 2 and (i % 2) == 0:
proba = np.random.rand(n_records)
logger.add_classification([i], [labels[i]], [methods[i]], query_i)
if proba is not None:
logger.add_proba(np.arange(i+1, n_records), np.arange(i+1),
proba, query_i)
current_labels[i] = labels[i]
logger.set_labels(current_labels)
check_logger(logger, i, query_i, labels, methods, proba)
def test_read_dict_logger():
with open_logger(None) as logger:
assert isinstance(logger, DictLogger)
def test_read_hdf5_logger():
log_fp = Path("test", "log_files", "test_1_inst.h5")
with open_logger(str(log_fp)) as logger:
assert isinstance(logger, HDF5Logger)
def test_read_json_logger():
log_fp = Path("test", "log_files", "test_1_inst.json")
with open_logger(str(log_fp)) as logger:
assert isinstance(logger, JSONLogger)
