Fix mask broadcasting for numpy where in add_constraints

The switch from xarray's where() to numpy's where() broke dimension-aware
broadcasting. A 1D mask with shape (10,) was being broadcast to (1, 10)
instead of (10, 1), applying to the wrong dimension.

Fix: Explicitly broadcast mask to match data.labels shape before using np.where.

Author: FBumann

linopy/model.py

@@ -750,6 +750,9 @@ def add_constraints(
             assert set(mask.dims).issubset(data.dims), (
                 "Dimensions of mask not a subset of resulting labels dimensions."
             )
+            # Broadcast mask to match data shape for correct numpy where behavior
+            if mask.shape != data.labels.shape:
+                mask, _ = xr.broadcast(mask, data.labels)
 
         # Auto-mask based on null expressions or NaN RHS (use numpy for speed)
         if self.auto_mask: