update checking for grid_shape

floris/type_dec.py

@@ -193,22 +193,20 @@ def validate_5DArray_shape(instance, attribute: Attribute, value: np.ndarray) ->
             N wind directions x N wind speeds x N turbines x N grid points x N grid points.
     """
     if not isinstance(value, np.ndarray):
-        print(type(value))
         raise TypeError(f"`{attribute.name}` is not a valid NumPy array type.")
 
     # Don't fail on the initialized empty array
     if value.size == 0:
         return
 
-    grid = instance.grid_resolution
-    shape = (instance.n_wind_directions, instance.n_wind_speeds, instance.n_turbines, grid, grid)
-    if value.shape != shape:
+    if value.shape != instance.grid_shape:
         broadcast_shape = (
             instance.n_wind_directions, instance.n_wind_speeds, instance.n_turbines, 1, 1
         )
         if value.shape != broadcast_shape:
             raise ValueError(
-                f"`{attribute.name}` should have shape: {shape}; not shape: {value.shape}"
+                f"`{attribute.name}` should have shape: {instance.grid_shape}; not shape: "
+                f"{value.shape}"
             )
 
 

tests/type_dec_unit_test.py

@@ -62,14 +62,23 @@ class ArrayValidatorDemoClass(ValidateMixin):
     n_wind_directions: int = field(default=3)
     n_wind_speeds: int = field(default=4)
     n_turbines: int = field(default=10)
-    grid_resolution: int = field(default=3)
+    grid_shape: tuple[int, int, int, int, int] = field(init=False)
     three_dim_starts_as_one: NDArrayFloat = field(
         factory=lambda: np.array([]), validator=validate_3DArray_shape
     )
     five_dimensions_provided: NDArrayFloat = array_5D_field
     three_dimensions_provided: NDArrayFloat = array_3D_field
     mixed_dimensions_provided: NDArrayFloat = array_mixed_dim_field
 
+    def set_grid(self, grid_resolution: int):
+        self.grid_shape = (
+            self.n_wind_directions,
+            self.n_wind_speeds,
+            self.n_turbines,
+            grid_resolution,
+            grid_resolution
+        )
+
 
 def test_as_dict():
     # Non-initialized attributes should not be exported
@@ -154,6 +163,7 @@ def test_array_validators():
 
     # Check initialization works
     demo = ArrayValidatorDemoClass()
+    demo.set_grid(3)
     demo.validate()
 
     # Check assignment with correct shape: 3 x 4 x 10 (x 3 x 3)