fixed issue with history slicing

src/enfobench/__version__.py

@@ -1 +1 @@
-__version__ = "0.7.0"
+__version__ = "0.7.1"

src/enfobench/core/dataset.py

@@ -149,7 +149,7 @@ def get_history(self, cutoff_date: pd.Timestamp) -> pd.DataFrame:
         """Returns the history of the target variable up to the cutoff date.
 
         The cutoff date is the timestamp when the forecast is made,
-        therefore it is included in the history.
+        therefore the cutoff_date is not included in the history.
 
         Args:
             cutoff_date: The cutoff date.
@@ -158,13 +158,14 @@ def get_history(self, cutoff_date: pd.Timestamp) -> pd.DataFrame:
             The history of the target variable up to the cutoff date.
         """
         self._check_cutoff_in_rage(cutoff_date)
-        return self._target[self._target.index <= cutoff_date]
+        return self._target[self._target.index < cutoff_date]
 
     def get_past_covariates(self, cutoff_date: pd.Timestamp) -> pd.DataFrame | None:
         """Returns the past covariates for the cutoff date.
 
-        The cutoff date is the timestamp when the forecast is made,
-        therefore it is included in the past covariates.
+        The cutoff date is the timestamp when the forecast is made.
+        As the covariates are weather parameters measured at the indicated timestamp,
+        the cutoff_date is included in the past covariates.
 
         Args:
             cutoff_date: The cutoff date.
@@ -181,8 +182,9 @@ def get_past_covariates(self, cutoff_date: pd.Timestamp) -> pd.DataFrame | None:
     def get_future_covariates(self, cutoff_date: pd.Timestamp) -> pd.DataFrame | None:
         """Returns the future covariates for the cutoff date.
 
-        The cutoff date is the timestamp when the forecast is made,
-        therefore it is not included in the future covariates.
+        The cutoff date is the timestamp when the forecast is made.
+        As the covariates are weather parameters measured at the indicated timestamp,
+        the cutoff_date is not included in the future covariates.
 
         Args:
             cutoff_date: The cutoff date.

tests/test_dataset/test_dataset.py

@@ -17,8 +17,8 @@ def test_get_history(helpers, resolution):
     assert isinstance(history.index, pd.DatetimeIndex)
     assert "y" in history.columns
     assert len(history.columns) == 1
-    assert cutoff_date in history.index
-    assert (history.index <= cutoff_date).all()
+    assert cutoff_date not in history.index
+    assert (history.index < cutoff_date).all()
 
 
 @pytest.mark.parametrize("resolution", ["15T", "30T", "1H"])

tests/test_evaluations/test_evaluate.py

@@ -26,15 +26,16 @@ def test_cross_validate_univariate_locally(helpers, model):
     assert "yhat" in forecasts.columns
 
     assert "timestamp" in forecasts.columns
-    assert (forecasts.timestamp > start_date).all()
-    assert forecasts.timestamp.iloc[-1] == end_date
+    assert (forecasts.timestamp >= start_date).all()
+    assert forecasts.timestamp.iloc[0] == start_date
 
     assert "cutoff_date" in forecasts.columns
     assert (start_date.time() == forecasts.cutoff_date.dt.time).all()
 
     for cutoff_date, forecast in forecasts.groupby("cutoff_date"):
         assert len(forecast) == 38 * 2  # 38 hours with half-hour series
-        assert (forecast.timestamp > cutoff_date).all()
+        assert forecast.timestamp.iloc[0] == cutoff_date
+        assert (forecast.timestamp >= cutoff_date).all()
 
     assert list(forecasts.cutoff_date.unique()) == list(
         pd.date_range(start="2020-02-01 10:00:00", end="2020-03-30 10:00:00", freq="1D", inclusive="both")

tests/test_evaluations/test_utils.py

@@ -170,4 +170,5 @@ def test_create_forecast_index(helpers, freq, horizon):
     assert isinstance(index, pd.DatetimeIndex)
     assert index.freq == history.index.freq
     assert len(index) == horizon
-    assert (index > cutoff_date).all()
+    assert index[0] == cutoff_date
+    assert (index >= cutoff_date).all()