def test_split_data_shuffle_false_first_val_fold():
X, y = data_gen()
indices = split_data(X, shuffle=False)
ind_val, ind_train = next(indices)
assert np.array_equal(
ind_val, np.arange(34)
), "`shuffle=False` doesn't work in split_data for the first validation fold"
def test_split_data_stopiteration_error():
X, y = data_gen()
indices = split_data(X, shuffle=False)
next(indices)
next(indices)
next(indices)
with pytest.raises(StopIteration):
next(indices)
def test_split_data_shuffle_false_last_val_fold():
X, y = data_gen()
indices = split_data(X, shuffle=False)
next(indices)
next(indices)
ind_val, ind_train = next(indices)
assert np.array_equal(ind_val,
np.arange(67, 100)), "`shuffle=False` doesn't work in split_data for the validation fold"
def test_split_data_stopiteration_error():
X, y = data_gen()
indices = split_data(X, shuffle=False)
next(indices)
next(indices)
next(indices)
with pytest.raises(StopIteration):
next(indices)
def test_split_data_shuffle_true():
X, y = data_gen()
indices = split_data(X, shuffle=True)
ind_val, ind_train = next(indices)
assert not np.array_equal(ind_val, np.arange(34)), "`shuffle=True` doesn't work in split_data"
def test_split_data_output_is_generator():
X, y = data_gen()
indices = split_data(X, shuffle=False)
assert isinstance(indices, types.GeneratorType), "split_data output should be a generator"
def test_split_data_shuffle_true():
X, y = data_gen()
indices = split_data(X, shuffle=True)
ind_val, ind_train = next(indices)
assert not np.array_equal(
ind_val, np.arange(34)), "`shuffle=True` doesn't work in split_data"
def test_split_data_output_is_generator():
X, y = data_gen()
indices = split_data(X, shuffle=False)
assert isinstance(
indices,
types.GeneratorType), "split_data output should be a generator"