Added quantile interval score

src/scores/continuous/interval_impl.py

@@ -6,20 +6,20 @@
 import xarray as xr
 
 from scores.functions import apply_weights
-from scores.typing import FlexibleDimensionTypes, XarrayLike
+from scores.typing import FlexibleDimensionTypes
 from scores.utils import check_dims, gather_dimensions
 
 
 def quantile_interval_score(  # pylint: disable=R0914
-    fcst_lower_qtile: XarrayLike,
-    fcst_upper_qtile: XarrayLike,
-    obs: XarrayLike,
+    fcst_lower_qtile: xr.DataArray,
+    fcst_upper_qtile: xr.DataArray,
+    obs: xr.DataArray,
     lower_qtile_level: float,
     upper_qtile_level: float,
     *,  # Force keywords arguments to be keyword-only
     reduce_dims: Optional[FlexibleDimensionTypes] = None,
     preserve_dims: Optional[FlexibleDimensionTypes] = None,
-    weights: Optional[XarrayLike] = None,
+    weights: Optional[xr.DataArray] = None,
 ) -> xr.Dataset:
     """
     Calculates the qauntile interval score for interval forecasts. This score penalizes
@@ -65,9 +65,10 @@ def quantile_interval_score(  # pylint: disable=R0914
         estimation", J. Amer. Stat. Assoc., Vol. 102 No. 477 (2007), pp. 359--378,
         Corollary 5.2.
     """
+
     if not 0 < lower_qtile_level < upper_qtile_level < 1:
         raise ValueError(
-            "Expected 0 < lower_qtile_level < upper_qtile_level < 1. But got"
+            "Expected 0 < lower_qtile_level < upper_qtile_level < 1. But got "
             f"lower_qtile_level = {lower_qtile_level} and upper_qtile_level = {upper_qtile_level}"
         )
     # Check fcst_lower_qtile and fcst_upper_qtile have the same dimension