fixing problem in remove seasonalty CUSUM

Summary:
We used to have a problem with seasonaluty definition in cusum:
on cusum level we map string to hours on daily basis
but on SeasnalHandler expect to recieve hour-based.
Fortunately their no using this property in 1D.
New test for SeasnaltyHandle was added

Differential Revision: D50120272

fbshipit-source-id: 287c0636a719ffbe4a0b21d0784513ef5c8989ad

kats/detectors/cusum_model.py

@@ -56,12 +56,6 @@
 NORMAL_TOLERENCE = 1  # number of window
 CHANGEPOINT_RETENTION: int = 7 * 24 * 60 * 60  # in seconds
 MAX_CHANGEPOINT = 10
-SEASON_PERIOD_FREQ_MAP: Dict[str, int] = {
-    "daily": 1,
-    "weekly": 7,
-    "monthly": 30,
-    "yearly": 365,
-}
 
 _log: logging.Logger = logging.getLogger("cusum_model")
 
@@ -197,7 +191,7 @@ def __init__(
         ] = CUSUMDefaultArgs.change_directions,
         score_func: Union[str, CusumScoreFunction] = DEFAULT_SCORE_FUNCTION,
         remove_seasonality: bool = CUSUMDefaultArgs.remove_seasonality,
-        season_period_freq: str = "daily",
+        season_period_freq: Union[str, int] = "daily",
         vectorized: Optional[bool] = None,
         adapted_pre_mean: Optional[bool] = None,
     ) -> None:
@@ -229,7 +223,7 @@ def __init__(
             else:
                 self.remove_seasonality: bool = remove_seasonality
 
-            self.season_period_freq: str = previous_model.get(
+            self.season_period_freq: Union[str, int] = previous_model.get(
                 "season_period_freq", "daily"
             )
 

kats/tests/utils/test_decomposition.py

@@ -12,7 +12,7 @@
 from kats.consts import TimeSeriesData
 from kats.data.utils import load_air_passengers, load_data
 from kats.detectors.residual_translation import KDEResidualTranslator
-from kats.utils.decomposition import TimeSeriesDecomposition
+from kats.utils.decomposition import SeasonalityHandler, TimeSeriesDecomposition
 from kats.utils.simulator import Simulator
 from scipy.stats import ks_2samp
 from statsmodels.tsa.seasonal import seasonal_decompose, STL
@@ -293,6 +293,17 @@ def test_plot(self) -> None:
 
         m.plot()
 
+    def test_seasnality_handler(self) -> None:
+        sh_data = SeasonalityHandler(
+            data=self.ts_data_daily, seasonal_period=24 * 60 * 60
+        )
+        historical_data = sh_data.remove_seasonality()
+        self.assertNotEqual(self.ts_data_daily, historical_data)
+
+        sh_data = SeasonalityHandler(data=self.ts_data_daily, seasonal_period="daily")
+        historical_data = sh_data.remove_seasonality()
+        self.assertNotEqual(self.ts_data_daily, historical_data)
+
     def test_multiplicative_assert(self) -> None:
         data_new = self.ts_data.to_dataframe().copy()
         data_new["y"] = -1.0 * data_new["y"]

kats/utils/decomposition.py

@@ -278,7 +278,7 @@ class SeasonalityHandler:
     SeasonalityHandler is a class that do timeseries STL decomposition for detecors
     Attributes:
         data: TimeSeriesData that need to be decomposed
-        seasonal_period: str, default value is 'daily'. Other possible values: 'hourly', 'weekly', 'biweekly', 'monthly', 'yearly'
+        seasonal_period: str, default value is 'daily'. Other possible values: 'hourly', 'weekly', 'biweekly', 'monthly', 'yearly' or integer which represent amoutn of seconds
 
     >>> # Example usage:
     >>> from kats.utils.simulator import Simulator
@@ -290,18 +290,18 @@ class SeasonalityHandler:
     """
 
     PERIOD_MAP: Dict[str, int] = {
-        "hourly": 1,
-        "daily": 24,
-        "weekly": 7 * 24,
-        "biweekly": 14 * 24,
-        "monthly": 30 * 24,
-        "yearly": 365 * 24,
+        "hourly": 1 * 60 * 60,
+        "daily": 24 * 60 * 60,
+        "weekly": 7 * 24 * 60 * 60,
+        "biweekly": 14 * 24 * 60 * 60,
+        "monthly": 30 * 24 * 60 * 60,
+        "yearly": 365 * 24 * 60 * 60,
     }
 
     def __init__(
         self,
         data: TimeSeriesData,
-        seasonal_period: str = "daily",
+        seasonal_period: Union[str, int] = "daily",
         ignore_irregular_freq: bool = False,
         **kwargs: Any,
     ) -> None:
@@ -312,11 +312,18 @@ def __init__(
 
         self.data = data
 
-        if seasonal_period not in SeasonalityHandler.PERIOD_MAP:
-            msg = "Invalid seasonal_period, possible values are 'hourly', 'daily', 'weekly', 'biweekly', 'monthly', and 'yearly'"
+        if isinstance(seasonal_period, str):
+            if seasonal_period not in SeasonalityHandler.PERIOD_MAP:
+                msg = "Invalid seasonal_period str value, possible values are integer or 'hourly', 'daily', 'weekly', 'biweekly', 'monthly', and 'yearly'"
+                logging.error(msg)
+                raise ParameterError(msg)
+            self.seasonal_period: int = SeasonalityHandler.PERIOD_MAP[seasonal_period]
+        elif type(seasonal_period) is int:
+            self.seasonal_period: int = seasonal_period
+        else:
+            msg = "Invalid seasonal_period type, possible values are integer or 'hourly', 'daily', 'weekly', 'biweekly', 'monthly', and 'yearly'"
             logging.error(msg)
             raise ParameterError(msg)
-        self.seasonal_period: int = SeasonalityHandler.PERIOD_MAP[seasonal_period]
 
         self.low_pass_jump_factor: float = kwargs.get("lpj_factor", 0.15)
         self.trend_jump_factor: float = kwargs.get("tj_factor", 0.15)
@@ -360,7 +367,7 @@ def __init__(
             raise DataIrregularGranularityError(IRREGULAR_GRANULARITY_ERROR)
 
         self.period: int = min(
-            int(self.seasonal_period * 60 * 60 / self.frequency.total_seconds()),
+            int(self.seasonal_period / self.frequency.total_seconds()),
             len(self.data) // 2,
         )