def test_file_storage_save():
meta = StorageMeta()
storage = BatchStorageFile(meta, directory="test")
X = np.array([1, 2, 3])
y = np.array([0, 0, 0])
filename = storage.save(X, y)
assert os.path.isfile(filename)
def test_file_storage_load():
meta = StorageMeta()
storage = BatchStorageFile(meta, directory="test")
X = np.array([1, 2, 3])
y = np.array([0, 0, 0])
storage.save(X, y)
X_data, y_data = storage.load(0)
assert np.array_equal(X_data, X)
assert np.array_equal(y_data, y)
def file_builder_factory(feature_set,
look_back,
look_forward,
batch_size,
directory=None,
batch_seconds=1,
stride=1,
validation_split=0,
pseudo_stratify=False,
stratify_nbatch_groupings=20,
n_workers=None,
seed=None,
normalize=True,
custom_transforms=None,
session_norm_filter=None,
verbose=False):
storage_meta = StorageMeta(validation_split=validation_split)
storage = BatchStorageFile(storage_meta, directory=directory)
translate = Translate(feature_set, look_back, look_forward,
batch_seconds, stride, normalize, verbose,
custom_transforms, session_norm_filter)
return Builder(storage=storage,
translate=translate,
batch_size=batch_size,
pseudo_stratify=pseudo_stratify,
stratify_nbatch_groupings=stratify_nbatch_groupings,
verbose=verbose,
seed=seed,
n_workers=n_workers)
def test_file_storage_metadata_val():
meta = StorageMeta(validation_split=1.0)
storage = BatchStorageFile(meta, directory="test")
X = np.array([1, 2, 3])
y = np.array([0, 0, 0])
storage.save(X, y)
storage.save_meta({})
params = storage.load_meta()
assert len(params["val_ids"]) == 1
assert params["val_map"][params["val_ids"][0]] == "IDv_0"
assert len(params["train_ids"]) == 0
def test_file_storage_directory():
meta = StorageMeta()
storage = BatchStorageFile(meta, directory="test")
tools.eq_(storage.directory, "test")
assert os.path.exists("test"), True
def test_load_empty_file_meta():
BatchStorageFile(StorageMeta(), directory="test").load_meta()