def test_aggregation_call(self):
data = np.random.random((10, 4))
data[:, 0] = np.arange(0, 10)
data[:, 1] = np.arange(10, 20)
data.flags.writeable = False
expected_param = np.zeros((2, 9, 2))
expected_param[0, :, 0] = np.arange(0, 9)
expected_param[0, :, 1] = np.arange(10, 19)
expected_param[1, :, 0] = np.arange(1, 10)
expected_param[1, :, 1] = np.arange(11, 20)
expected_data = np.full((10, 4 + 2), fill_value=np.nan)
expected_data[:, :4] = data
expected_data[-2:, 4:] = 9
agg = DummyAggreagor(sequence=9,
generate=[
InputOutputField(inputField='abc',
outputField='hello'),
InputOutputField(inputField='xyz',
outputField='world'),
])
input_format = StandardDataFormat(
timestamps=helper_data.generate_timestamps(10,
samples=data.shape[0]),
labels=['abc', 'xyz', 'aaa', 'bbb'],
data=data)
result = agg.process(input_format)
assert_array_equal(agg.grouped_data, expected_param)
self.assertEqual(result.labels,
['abc', 'xyz', 'aaa', 'bbb', 'hello', 'world'])
assert_array_equal(result.data, expected_data)
def test_no_outliers(self):
data = np.array([[10, 30], [12, 25]], dtype="float64")
data.flags.writeable = False
input_data = StandardDataFormat(
labels=['a', 'b'],
data=data,
timestamps=helper_data.generate_timestamps(2, 2))
# noinspection PyArgumentList
configs: List[InputOutputLimits] = [InputOutputLimits(inputField="a")]
result = OutlierRemover(generate=configs)._process2d(input_data)
assert_array_equal(data, result.data)
def test_min_outlier(self):
data = np.array([[10, 30], [12, 25]], dtype="float64")
data.flags.writeable = False
input_data = StandardDataFormat(
labels=['a', 'b'],
data=data,
timestamps=helper_data.generate_timestamps(2, 2))
limits = [{'inputField': 'b', 'min': 28}]
result_expected = data.copy()
result_expected[1, 1] = np.nan
result = OutlierRemover(generate=limits)._process2d(input_data)
assert_array_equal(result_expected, result.data)
def test_standard_case(self):
data = np.array([
[23, 55],
[21, 52],
[np.nan, 52],
[23, np.nan],
])
data.flags.writeable = False
result_excepted = data[:2]
process_data = StandardDataFormat(
data=data,
labels=['a', 'b'],
timestamps=helper_data.generate_timestamps(2, samples=4))
result = NanRemover()._process2d(process_data)
assert_array_equal(result_excepted, result.data)
def test_standard_case(self):
data = np.array([[11, 20], [12, 21], [13, 22], [14, 20], [15, 20],
[16, 20], [17, 20], [18, 20]],
dtype='float')
result_expected = np.array(
[[11, 20], [12, 21], [13, 22], [14, 20], [15, 20], [16, 20],
[17, np.nan], [18, np.nan]],
dtype='float')
processor_data = StandardDataFormat(
timestamps=helper_data.generate_timestamps(samples=data.shape[0]),
labels=helper_data.get_labels(2),
data=data)
processor_data_result = FreezedValueRemover(
max_freezed_values=3)._process2d(processor_data)
assert_array_equal(result_expected, processor_data_result.data)