Remove loops for 'hughes' and 'chiaverini' (they vectorize 3d arrays …

…already). Add handling of wrong input in method 'from_DCM()'.

ahrs/common/quaternion.py

@@ -2588,29 +2588,31 @@ def from_DCM(self, DCM: np.ndarray, method: str='chiaverini', inplace: bool = Tr
         array([0.94371436, 0.26853582, 0.14487813, 0.12767944])
 
         """
+        # Handle input
+        if method.lower() not in ['chiaverini', 'hughes', 'itzhack', 'sarabandi', 'shepperd']:
+            raise ValueError(f"Method '{method}' not available. Options are: 'chiaverini', 'hughes', 'itzhack', 'sarabandi', and 'shepperd'.")
+        _assert_iterables(DCM, 'Direction Cosine Matrices')
+        # Allocate local quaternion array
         quaternion_array = np.zeros((DCM.shape[0], 4))
         try:
             if method.lower() == 'hughes':
-                for i, R in enumerate(DCM):
-                    quaternion_array[i] = hughes(R)
+                quaternion_array = hughes(DCM)
             if method.lower() == 'chiaverini':
-                for i, R in enumerate(DCM):
-                    quaternion_array[i] = chiaverini(R)
+                quaternion_array = chiaverini(DCM)
             if method.lower() == 'shepperd':
                 for i, R in enumerate(DCM):
                     quaternion_array[i] = shepperd(R)
             if method.lower() == 'itzhack':
                 version = kw.get('version', 3)
                 for i, R in enumerate(DCM):
                     quaternion_array[i] = itzhack(R, version=version)
-                q = itzhack(self.A, version=kw.get('version', 3))
             if method.lower() == 'sarabandi':
                 threshold = kw.get('threshold', 0.0)
                 for i, R in enumerate(DCM):
                     quaternion_array[i] = sarabandi(R, eta=threshold)
         except RuntimeWarning:
             failed_DCM = DCM[i]
-            msg = f"Method '{method}' failed at DCM:\n{failed_DCM}\n"
+            msg = f"Method '{method}' failed at DCM[{i}]:\n{failed_DCM}\n"
             raise RuntimeError(msg)
         quaternion_array /= np.linalg.norm(quaternion_array, axis=1)[:, None]
         if inplace: