def test_sampling_strategy_dict_over_sampling():
y = np.array([1] * 50 + [2] * 100 + [3] * 25)
sampling_strategy = {1: 70, 2: 140, 3: 70}
expected_msg = (r"After over-sampling, the number of samples \(140\) in"
r" class 2 will be larger than the number of samples in"
r" the majority class \(class #2 -> 100\)")
with warns(UserWarning, expected_msg):
check_sampling_strategy(sampling_strategy, y, "over-sampling")
def test_check_sampling_strategy_warning():
msg = "dict for cleaning methods is not supported"
with pytest.raises(ValueError, match=msg):
check_sampling_strategy({
1: 0,
2: 0,
3: 0
}, multiclass_target, "clean-sampling")
def test_check_sampling_strategy_error_wrong_string(sampling_strategy,
sampling_type, err_msg):
with pytest.raises(
ValueError,
match=("'{}' cannot be used with {}".format(
sampling_strategy, err_msg)),
):
check_sampling_strategy(sampling_strategy, np.array([1, 2, 3]),
sampling_type)
def test_sampling_strategy_check_order(sampling_strategy, sampling_type,
expected_result):
# We pass on purpose a non sorted dictionary and check that the resulting
# dictionary is sorted. Refer to issue #428.
y = np.array([1] * 50 + [2] * 100 + [3] * 25)
sampling_strategy_ = check_sampling_strategy(sampling_strategy, y,
sampling_type)
assert sampling_strategy_ == expected_result
def test_check_sampling_strategy_error():
with pytest.raises(ValueError, match="'sampling_type' should be one of"):
check_sampling_strategy("auto", np.array([1, 2, 3]), "rnd")
error_regex = "The target 'y' needs to have more than 1 class."
with pytest.raises(ValueError, match=error_regex):
check_sampling_strategy("auto", np.ones((10, )), "over-sampling")
error_regex = "When 'sampling_strategy' is a string, it needs to be one of"
with pytest.raises(ValueError, match=error_regex):
check_sampling_strategy("rnd", np.array([1, 2, 3]), "over-sampling")
def test_sampling_strategy_callable_args():
y = np.array([1] * 50 + [2] * 100 + [3] * 25)
multiplier = {1: 1.5, 2: 1, 3: 3}
def sampling_strategy_func(y, multiplier):
"""samples such that each class will be affected by the multiplier."""
target_stats = Counter(y)
return {
key: int(values * multiplier[key])
for key, values in target_stats.items()
}
sampling_strategy_ = check_sampling_strategy(sampling_strategy_func,
y,
"over-sampling",
multiplier=multiplier)
assert sampling_strategy_ == {1: 25, 2: 0, 3: 50}
def test_sampling_strategy_dict_error():
y = np.array([1] * 50 + [2] * 100 + [3] * 25)
sampling_strategy = {1: -100, 2: 50, 3: 25}
with pytest.raises(ValueError, match="in a class cannot be negative."):
check_sampling_strategy(sampling_strategy, y, "under-sampling")
sampling_strategy = {1: 45, 2: 100, 3: 70}
error_regex = ("With over-sampling methods, the number of samples in a"
" class should be greater or equal to the original number"
" of samples. Originally, there is 50 samples and 45"
" samples are asked.")
with pytest.raises(ValueError, match=error_regex):
check_sampling_strategy(sampling_strategy, y, "over-sampling")
error_regex = ("With under-sampling methods, the number of samples in a"
" class should be less or equal to the original number of"
" samples. Originally, there is 25 samples and 70 samples"
" are asked.")
with pytest.raises(ValueError, match=error_regex):
check_sampling_strategy(sampling_strategy, y, "under-sampling")
def test_check_sampling_strategy(sampling_strategy, sampling_type,
expected_sampling_strategy, target):
sampling_strategy_ = check_sampling_strategy(sampling_strategy, target,
sampling_type)
assert sampling_strategy_ == expected_sampling_strategy
def test_sampling_strategy_list_error_not_clean_sampling(sampling_method):
y = np.array([1] * 50 + [2] * 100 + [3] * 25)
with pytest.raises(ValueError, match="cannot be a list for samplers"):
sampling_strategy = [1, 2, 3]
check_sampling_strategy(sampling_strategy, y, sampling_method)
def test_sampling_strategy_float_error_not_binary():
y = np.array([1] * 50 + [2] * 100 + [3] * 25)
with pytest.raises(ValueError, match="the type of target is binary"):
sampling_strategy = 0.5
check_sampling_strategy(sampling_strategy, y, "under-sampling")
def test_sampling_strategy_float_error_not_in_range(sampling_strategy):
y = np.array([1] * 50 + [2] * 100)
with pytest.raises(ValueError, match="it should be in the range"):
check_sampling_strategy(sampling_strategy, y, "under-sampling")
def test_sampling_strategy_class_target_unknown(sampling_strategy,
sampling_method):
y = np.array([1] * 50 + [2] * 100 + [3] * 25)
with pytest.raises(ValueError, match="are not present in the data."):
check_sampling_strategy(sampling_strategy, y, sampling_method)
def test_check_sampling_strategy_float_error(ratio, y, type, err_msg):
with pytest.raises(ValueError, match=err_msg):
check_sampling_strategy(ratio, y, type)
