Iluise/hot fixes (ecmwf#1209)

* fix froct

* fix 1150

Author: iluise

packages/evaluate/src/weathergen/evaluate/clim_utils.py

@@ -128,6 +128,10 @@ def align_clim_data(
             timestamp = target_data.valid_time.values[sample_mask][0]
             # Prepare climatology data for each sample
             matching_time_idx = match_climatology_time(timestamp, clim_data)
+
+            if matching_time_idx is None:
+                continue
+
             prepared_clim_data = (
                 clim_data.data.isel(
                     time=matching_time_idx,
@@ -209,7 +213,7 @@ def get_climatology(reader, da_tars, stream: str) -> xr.Dataset | None:
 
     aligned_clim_data = None
 
-    if clim_data_path:
+    if clim_data_path is not None:
         clim_data = xr.open_dataset(clim_data_path)
         _logger.info("Aligning climatological data with target structure...")
         aligned_clim_data = align_clim_data(da_tars, clim_data)

packages/evaluate/src/weathergen/evaluate/io_reader.py

@@ -495,10 +495,10 @@ def __init__(self, eval_cfg: dict, run_id: str, private_paths: dict | None = Non
         )
 
         if not self.fname_zarr.exists() or not self.fname_zarr.is_dir():
-            _logger.error(f"Zarr file {self.fname_zarr} does not exist or is not a directory.")
-            raise FileNotFoundError(
-                f"Zarr file {self.fname_zarr} does not exist or is not a directory."
-            )
+            _logger.error(f"Zarr file {self.fname_zarr} does not exist.")
+            # raise FileNotFoundError(
+            #     f"Zarr file {self.fname_zarr} does not exist or is not a directory."
+            # )
 
     def get_inference_config(self):
         """
@@ -626,6 +626,8 @@ def get_data(
                         pred = bbox.apply_mask(pred)
 
                     npoints = len(target.ipoint)
+                    pps.append(npoints)
+
                     if npoints == 0:
                         _logger.info(
                             f"Skipping {stream} sample {sample} forecast step: {fstep}. "
@@ -649,7 +651,6 @@ def get_data(
 
                     da_tars_fs.append(target.squeeze())
                     da_preds_fs.append(pred.squeeze())
-                    pps.append(npoints)
 
                 if len(da_tars_fs) > 0:
                     fsteps_final.append(fstep)
@@ -692,6 +693,7 @@ def get_data(
 
                     da_tars.append(da_tars_fs)
                     da_preds.append(da_preds_fs)
+
                     if return_counts:
                         points_per_sample.loc[{"forecast_step": fstep}] = np.array(pps)
 

packages/evaluate/src/weathergen/evaluate/score.py

@@ -307,7 +307,9 @@ def get_score(
             group_names = list(next(iter(grouped_args.values())).groups.keys())
             results = []
             for name in group_names:
-                group_slice = {k: v[name] for k, v in grouped_args.items()}
+                group_slice = {
+                    k: (v[name] if v is not None else v) for k, v in grouped_args.items()
+                }
                 res = f(**group_slice)
                 # Add coordinate for concatenation
                 res = res.expand_dims({group_by_coord: [name]})