def test__init__with_DataFrame_input_many_columns__with_values(self):
index = DatetimeIndex(
['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04'])
my_series = Series([0.4, 1.0, 0.7, 0.6], index=index)
df = DataFrame({TIME_SERIES_VALUES: my_series, "two": my_series})
ts = TimeSeries(df)
self.assertIsInstance(ts, TimeSeries)
def test__init__with_DataFrame_input_many_columns__without_values(self):
index = DatetimeIndex(
['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04'])
my_series = Series([0.4, 1.0, 0.7, 0.6], index=index)
df = DataFrame({"one": my_series, "two": my_series})
with self.assertRaises(AssertionError):
ts = TimeSeries(df)
def test__init__with_Series_input(self):
index = DatetimeIndex(
['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04'])
my_series = Series([0.4, 1.0, 0.7, 0.6], index=index)
ts = TimeSeries(my_series)
self.assertTrue(TIME_SERIES_VALUES in ts.series.columns)
self.assertIsInstance(ts, TimeSeries)
def test__init__with_DataFrame_input_single_column(self):
index = DatetimeIndex(
['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04'])
my_series = Series([0.4, 1.0, 0.7, 0.6], index=index)
df = DataFrame(data=my_series)
ts = TimeSeries(df)
self.assertTrue(TIME_SERIES_VALUES in ts.series.columns)
self.assertIsInstance(ts, TimeSeries)
def test__init__contains_metadata(self):
# Add some data
index = DatetimeIndex(
['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04'])
my_series = DataFrame([0.4, 1.0, 0.7, 0.6], index=index)
my_metadata = Metadata()
my_ts = TimeSeries(my_series, my_metadata)
# Check types
self.assertNotEqual(my_ts.metadata, None,
"The TimeSeries Metadata is probably None")
def test__init__has_right_types(self):
# Add some data
index = DatetimeIndex(
['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04'])
my_series = DataFrame([0.4, 1.0, 0.7, 0.6], index=index)
my_metadata = Metadata()
my_ts = TimeSeries(my_series, my_metadata)
# Check types
self.assertIsInstance(
my_ts.series, DataFrame,
"The TimeSeries series is not a Pandas DataFrame")
self.assertIsInstance(
my_ts.metadata, Metadata,
"The TimeSeries Metadata hasn't got the right type")
def test__to_text__without_metadata(self):
path = self.target_dir + "/to_text_without_metadata"
my_time_series = TimeSeries(self.my_series)
my_time_series.to_text(path)
data_csv_path = "{}/{}.{}".format(path, TIME_SERIES_FILENAME,
TIME_SERIES_EXT)
does_data_csv_exist = os_path.exists(data_csv_path)
self.assertTrue(does_data_csv_exist)
meta_json_path = "{}/{}.{}".format(path, METADATA_FILENAME,
METADATA_EXT)
does_meta_json_exist = os_path.exists(meta_json_path)
self.assertFalse(does_meta_json_exist)
def setUp(self) -> None:
# Create a time indexed series
index = DatetimeIndex(
['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04'])
self.my_series = Series([0.4, 1.0, 0.7, 0.6], index=index)
# Create metadata
my_unit = {"name": "power", "symbol": "W", "data_type": "float"}
my_coordinates = {"lat": 46.796611, "lon": 7.147563}
my_dict = {"unit": my_unit, "coordinates": my_coordinates}
self.my_metadata = Metadata(my_dict)
self.my_time_series = TimeSeries(self.my_series, self.my_metadata)
# Define a target directory
self.target_dir = "data/test-export"
def test_anomaly_generator():
from datetime import datetime
start_time = time.time()
print("---START DATASET CREATION---")
# data_reader = Reader('../../data/clean/ACS-F2/Dataset/*/*.xml')
data = pd.read_csv('./anomaly_generator_test_data.csv', index_col=0).T
data.drop('label', inplace=True)
tss = [datetime.fromtimestamp(int(x)) for x in data.index]
result = []
for i, v in data.iteritems():
v.index = tss[:len(v)]
result.append(TimeSeries(v))
tsd = TimeSeriesDataset(result)
anomaly_set = AnomalyGenerator(data=tsd, conf_file='test_config.ini')
anomaly_set.generate()
end_time = time.time()
print("Creation time of the dataset: {0:.3f} seconds.".format(end_time -
start_time))
def test__init__wrong_index_type(self):
values = Series([0.4, 1.0, 0.7, 0.6])
with self.assertRaises(AssertionError):
TimeSeries(values)
def test__init__has_values_as_column_name(self):
index = DatetimeIndex(
['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04'])
my_series = Series([0.4, 1.0, 0.7, 0.6], index=index)
ts = TimeSeries(my_series)
self.assertTrue(TIME_SERIES_VALUES in ts.series.columns)
def test__init__is_instance(self):
self.my_time_series = TimeSeries()
self.assertIsInstance(self.my_time_series, TimeSeries,
"The TimeSeries hasn't the right type")
def test__init__freq_is_infered(self):
index = DatetimeIndex(
['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04'])
my_series = Series([0.4, 1.0, 0.7, 0.6], index=index)
ts = TimeSeries(my_series)
self.assertEqual(infer_freq(index), ts.series.index.freq)
