updated weighting arg in docstrings

nci · Oct 20, 2023 · d611bd5 · d611bd5
1 parent 3652256
commit d611bd5
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Showing 2 changed files with 8 additions and 8 deletions.
diff --git a/src/scores/continuous/standard_impl.py b/src/scores/continuous/standard_impl.py
@@ -37,8 +37,8 @@ def mse(
             the squared error at each point (i.e. single-value comparison
             against observed), and the forecast and observed dimensions
             must match precisely.
-        weights: Not yet implemented. Allow weighted averaging (e.g. by
-            area, by latitude, by population, custom)
+        weights: Optionally provide an array for weighted averaging (e.g. by area, by latitude,
+            by population, custom)
 
     Returns:
         Union[xr.Dataset, xr.DataArray, pd.Dataframe, pd.Series]: An object containing
@@ -98,8 +98,8 @@ def rmse(
             the absolute error at each point (i.e. single-value comparison
             against observed), and the forecast and observed dimensions
             must match precisely.
-      weights: Not yet implemented. Allow weighted averaging (e.g. by
-          area, by latitude, by population, custom)
+        weights: Optionally provide an array for weighted averaging (e.g. by area, by latitude,
+            by population, custom)
 
     Returns:
         An object containing
@@ -144,9 +144,8 @@ def mae(
             as the forecast, and the errors will be the absolute error at each
             point (i.e. single-value comparison against observed), and the
             forecast and observed dimensions must match precisely.
-        weights:
-            Not yet implemented. Allow weighted averaging (e.g. by area, by
-            latitude, by population, custom).
+        weights: Optionally provide an array for weighted averaging (e.g. by area, by latitude,
+            by population, custom)
 
     Returns:
         By default an xarray DataArray containing

diff --git a/src/scores/probability/crps_impl.py b/src/scores/probability/crps_impl.py
@@ -249,7 +249,8 @@ def crps_cdf(
             by taking the mean.
         reduce_dims (Tuple[str]): dimensions to reduce in the output by taking the mean. All other dimensions are
             preserved.
-        weights: Not yet implemented. Allow weighted averaging (e.g. by area, by latitude, by population, custom)
+        weights: Optionally provide an array for weighted averaging (e.g. by area, by latitude,
+            by population, custom)
         include_components (bool): if True, include the under and over forecast components of
             the score in the returned dataset.