def test_hour_truncation():
df = pd.DataFrame(
{
"date": [
"2020-01-07 12:12:00",
"2020-01-07 17:35:00",
"2020-01-07 14:55:00",
"2020-01-07 18:06:00",
"2020-01-08 04:40:00",
"2020-01-08 06:13:00",
"2020-01-08 03:23:00",
],
"id": [1, 1, 1, 1, 2, 2, 2],
}
)
frequency = "2H"
time_column_name = "date"
timeseries_identifiers_names = ["id"]
df[time_column_name] = pd.to_datetime(df[time_column_name]).dt.tz_localize(tz=None)
preparator = TimeseriesPreparator(
time_column_name=time_column_name,
frequency=frequency,
timeseries_identifiers_names=timeseries_identifiers_names,
max_timeseries_length=2,
)
dataframe_prepared = preparator._truncate_dates(df)
dataframe_prepared = preparator._sort(dataframe_prepared)
preparator._check_regular_frequency(dataframe_prepared)
dataframe_prepared = preparator._keep_last_dates(dataframe_prepared)
assert dataframe_prepared[time_column_name][0] == pd.Timestamp("2020-01-07 16:00:00")
assert dataframe_prepared[time_column_name][3] == pd.Timestamp("2020-01-08 06:00:00")
def test_day_truncation():
df = pd.DataFrame(
{
"date": [
"2021-01-01 12:17:42",
"2021-01-02 00:00:00",
"2021-01-03 12:46:00",
],
"id": [1, 1, 1],
}
)
frequency = "D"
time_column_name = "date"
timeseries_identifiers_names = ["id"]
df[time_column_name] = pd.to_datetime(df[time_column_name]).dt.tz_localize(tz=None)
preparator = TimeseriesPreparator(
time_column_name=time_column_name,
frequency=frequency,
timeseries_identifiers_names=timeseries_identifiers_names,
)
dataframe_prepared = preparator._truncate_dates(df)
dataframe_prepared = preparator._sort(dataframe_prepared)
preparator._check_regular_frequency(dataframe_prepared)
assert dataframe_prepared[time_column_name][0] == pd.Timestamp("2021-01-01")
assert dataframe_prepared[time_column_name][2] == pd.Timestamp("2021-01-03")
def test_semester_truncation():
df = pd.DataFrame(
{
"date": [
"2020-12-15",
"2021-06-28",
"2021-12-01",
],
"id": [1, 1, 1],
}
)
frequency = "6M"
time_column_name = "date"
timeseries_identifiers_names = ["id"]
df[time_column_name] = pd.to_datetime(df[time_column_name]).dt.tz_localize(tz=None)
preparator = TimeseriesPreparator(
time_column_name=time_column_name,
frequency=frequency,
timeseries_identifiers_names=timeseries_identifiers_names,
)
dataframe_prepared = preparator._truncate_dates(df)
dataframe_prepared = preparator._sort(dataframe_prepared)
preparator._check_regular_frequency(dataframe_prepared)
assert dataframe_prepared[time_column_name][0] == pd.Timestamp("2020-12-31")
assert dataframe_prepared[time_column_name][1] == pd.Timestamp("2021-06-30")
assert dataframe_prepared[time_column_name][2] == pd.Timestamp("2021-12-31")
def test_hour_truncation(self, time_column_name,
timeseries_identifiers_names, basic_config):
df = pd.DataFrame({
"date": [
"2020-01-07 12:12:00",
"2020-01-07 17:35:00",
"2020-01-07 14:55:00",
"2020-01-07 18:06:00",
"2020-01-08 04:40:00",
"2020-01-08 06:13:00",
"2020-01-08 03:23:00",
],
"id": [1, 1, 1, 1, 2, 2, 2],
"target": [1, 2, 3, 4, 5, 6, 7]
})
df[time_column_name] = pd.to_datetime(
df[time_column_name]).dt.tz_localize(tz=None)
dku_config = DecompositionConfig()
basic_config["frequency_step_hours"] = "2"
basic_config["frequency_unit"] = "H"
basic_config["season_length_H"] = 12
basic_config["long_format"] = True
basic_config["timeseries_identifiers"] = timeseries_identifiers_names
dku_config.add_parameters(basic_config, list(df.columns))
preparator = TimeseriesPreparator(dku_config, max_timeseries_length=2)
dataframe_prepared = preparator._truncate_dates(df)
dataframe_prepared = preparator._sort(dataframe_prepared)
preparator._check_regular_frequency(dataframe_prepared)
dataframe_prepared = preparator._keep_last_dates(dataframe_prepared)
assert dataframe_prepared[time_column_name][0] == pd.Timestamp(
"2020-01-07 16:00:00")
assert dataframe_prepared[time_column_name][3] == pd.Timestamp(
"2020-01-08 06:00:00")
def test_week_sunday_truncation():
df = pd.DataFrame(
{
"date": [
"2021-01-03 12:12:00",
"2021-01-05 17:35:00",
"2021-01-15 14:55:00",
],
"id": [1, 1, 1],
}
)
frequency = "W-SUN"
time_column_name = "date"
timeseries_identifiers_names = ["id"]
df[time_column_name] = pd.to_datetime(df[time_column_name]).dt.tz_localize(tz=None)
preparator = TimeseriesPreparator(
time_column_name=time_column_name,
frequency=frequency,
timeseries_identifiers_names=timeseries_identifiers_names,
max_timeseries_length=2,
)
dataframe_prepared = preparator._truncate_dates(df)
dataframe_prepared = preparator._sort(dataframe_prepared)
preparator._check_regular_frequency(dataframe_prepared)
dataframe_prepared = preparator._keep_last_dates(dataframe_prepared)
assert dataframe_prepared[time_column_name][0] == pd.Timestamp("2021-01-10")
assert dataframe_prepared[time_column_name][1] == pd.Timestamp("2021-01-17")
def test_minutes_truncation(self, time_column_name, basic_config):
df = pd.DataFrame({
"date": [
"2021-01-01 12:17:42",
"2021-01-01 12:30:00",
"2021-01-01 12:46:00",
],
"id": [1, 1, 1],
"target": [1, 2, 3]
})
dku_config = DecompositionConfig()
basic_config["frequency_step_minutes"] = "15"
basic_config["frequency_unit"] = "min"
basic_config["season_length_min"] = 4
dku_config.add_parameters(basic_config, list(df.columns))
df[time_column_name] = pd.to_datetime(
df[time_column_name]).dt.tz_localize(tz=None)
preparator = TimeseriesPreparator(dku_config)
dataframe_prepared = preparator._truncate_dates(df)
dataframe_prepared = preparator._sort(dataframe_prepared)
preparator._check_regular_frequency(dataframe_prepared)
assert dataframe_prepared[time_column_name][0] == pd.Timestamp(
"2021-01-01 12:15:00")
assert dataframe_prepared[time_column_name][2] == pd.Timestamp(
"2021-01-01 12:45:00")
def test_year_truncation(self, time_column_name,
timeseries_identifiers_names, basic_config):
df = pd.DataFrame({
"date": [
"2020-12-31",
"2021-12-15",
"2022-12-01",
],
"id": [1, 1, 1],
"target": [1, 2, 3]
})
dku_config = DecompositionConfig()
basic_config["frequency_unit"] = "12M"
basic_config["season_length_12M"] = 4
basic_config["long_format"] = True
basic_config["timeseries_identifiers"] = timeseries_identifiers_names
basic_config["season_length_12M"] = 4
dku_config.add_parameters(basic_config, list(df.columns))
preparator = TimeseriesPreparator(dku_config)
df[time_column_name] = pd.to_datetime(
df[time_column_name]).dt.tz_localize(tz=None)
dataframe_prepared = preparator._truncate_dates(df)
dataframe_prepared = preparator._sort(dataframe_prepared)
preparator._check_regular_frequency(dataframe_prepared)
assert dataframe_prepared[time_column_name][0] == pd.Timestamp(
"2020-12-31")
assert dataframe_prepared[time_column_name][1] == pd.Timestamp(
"2021-12-31")
assert dataframe_prepared[time_column_name][2] == pd.Timestamp(
"2022-12-31")
def test_week_sunday_truncation(self, time_column_name,
timeseries_identifiers_names,
basic_config):
df = pd.DataFrame({
"date": [
"2021-01-03 12:12:00",
"2021-01-05 17:35:00",
"2021-01-15 14:55:00",
],
"id": [1, 1, 1],
"target": [1, 2, 3]
})
dku_config = DecompositionConfig()
basic_config["frequency_unit"] = "W"
basic_config["frequency_end_of_week"] = "SUN"
basic_config["season_length_W"] = 7
basic_config["long_format"] = True
basic_config["timeseries_identifiers"] = timeseries_identifiers_names
dku_config.add_parameters(basic_config, list(df.columns))
preparator = TimeseriesPreparator(dku_config, max_timeseries_length=2)
df[time_column_name] = pd.to_datetime(
df[time_column_name]).dt.tz_localize(tz=None)
dataframe_prepared = preparator._truncate_dates(df)
dataframe_prepared = preparator._sort(dataframe_prepared)
preparator._check_regular_frequency(dataframe_prepared)
dataframe_prepared = preparator._keep_last_dates(dataframe_prepared)
assert dataframe_prepared[time_column_name][0] == pd.Timestamp(
"2021-01-10")
assert dataframe_prepared[time_column_name][1] == pd.Timestamp(
"2021-01-17")
def test_business_day_truncation(self, time_column_name,
timeseries_identifiers_names,
basic_config):
df = pd.DataFrame({
"date": [
"2021-01-04 12:17:42",
"2021-01-05 00:00:00",
"2021-01-06 12:46:00",
],
"id": [1, 1, 1],
"target": [1, 2, 3]
})
dku_config = DecompositionConfig()
basic_config["frequency_unit"] = "B"
basic_config["season_length_B"] = 5
basic_config["long_format"] = True
basic_config["timeseries_identifiers"] = timeseries_identifiers_names
dku_config.add_parameters(basic_config, list(df.columns))
preparator = TimeseriesPreparator(dku_config)
df[time_column_name] = pd.to_datetime(
df[time_column_name]).dt.tz_localize(tz=None)
dataframe_prepared = preparator._truncate_dates(df)
dataframe_prepared = preparator._sort(dataframe_prepared)
preparator._check_regular_frequency(dataframe_prepared)
assert dataframe_prepared[time_column_name][0] == pd.Timestamp(
"2021-01-04")
assert dataframe_prepared[time_column_name][2] == pd.Timestamp(
"2021-01-06")
def test_duplicate_dates(self, time_column_name,
timeseries_identifiers_names, basic_config):
df = pd.DataFrame({
"date": [
"2021-01-01 12:12:00",
"2021-01-01 17:35:00",
"2021-01-02 14:55:00",
],
"id": [1, 1, 1],
"target": [1, 2, 3]
})
dku_config = DecompositionConfig()
basic_config["frequency"] = "D"
dku_config.add_parameters(basic_config, list(df.columns))
df[time_column_name] = pd.to_datetime(
df[time_column_name]).dt.tz_localize(tz=None)
preparator = TimeseriesPreparator(dku_config)
with pytest.raises(ValueError):
_ = preparator._truncate_dates(df)
def test_duplicate_dates():
df = pd.DataFrame(
{
"date": [
"2021-01-01 12:12:00",
"2021-01-01 17:35:00",
"2021-01-02 14:55:00",
],
"id": [1, 1, 1],
}
)
frequency = "D"
time_column_name = "date"
timeseries_identifiers_names = ["id"]
df[time_column_name] = pd.to_datetime(df[time_column_name]).dt.tz_localize(tz=None)
preparator = TimeseriesPreparator(
time_column_name=time_column_name,
frequency=frequency,
)
with pytest.raises(ValueError):
dataframe_prepared = preparator._truncate_dates(df)