♻️🩹 Renamed overwrite_{model|global}_dimension to force_{model|global…

…}_dimension

So they won't conflict with the method which has the same name

glotaran/model/dataset_model.py

@@ -70,8 +70,8 @@ def has_global_megacomplexes(self) -> bool:
 
     def get_model_dimension(self) -> str:
         """Returns the dataset model's model dimension."""
-        if self.overwrite_model_dimension is not None:
-            return self.overwrite_model_dimension
+        if self.force_model_dimension is not None:
+            return self.force_model_dimension
         if not hasattr(self, "_model_dimension"):
             if not self.has_megacomplexes():
                 raise ValueError(f"No megacomplex set for dataset model '{self.label}'")
@@ -106,8 +106,8 @@ def overwrite_model_dimension(self, model_dimension: str) -> None:
     # e.g. in FLIM, x, y dimension may get 'flattened' to a MultiIndex 'pixel'
     def get_global_dimension(self) -> str:
         """Returns the dataset model's global dimension."""
-        if self.overwrite_global_dimension is not None:
-            return self.overwrite_global_dimension
+        if self.force_global_dimension is not None:
+            return self.force_global_dimension
         if not hasattr(self, "_global_dimension"):
             if self.has_global_model():
                 if isinstance(self.global_megacomplex[0], str):

glotaran/model/model.py

@@ -35,8 +35,8 @@
 
 default_dataset_properties = {
     "clp_guidance": {"type": str, "allow_none": True},
-    "overwrite_model_dimension": {"type": str, "allow_none": True},
-    "overwrite_global_dimension": {"type": str, "allow_none": True},
+    "force_model_dimension": {"type": str, "allow_none": True},
+    "force_global_dimension": {"type": str, "allow_none": True},
     "group": {"type": str, "default": "default"},
     "megacomplex": {"type": List[str], "allow_none": True},
     "megacomplex_scale": {"type": List[Parameter], "allow_none": True},