Only returns 1D dataset as normalizers

xsocs/io/XsocsH5.py

@@ -250,29 +250,28 @@ class XsocsH5(XsocsH5Base):
 
     @_process_entry
     def normalizers(self, entry):
-        """Returns dataset in measurement that might be used to normalize data
+        """Returns names of dataset in measurement that can be used to normalize data
 
-        It returns names of scalar values and 1D datasets with same number
-        of elements as images that are available in the measurement group
+        It returns names of 1D datasets with same number of elements as images
+        that are available in the measurement group.
 
-        :return: Dictionary of {name: data} that might be normalizers
-        :rtype: collections.OrderedDict
+        :return: List of dataset names in measurement that might be normalizers
+        :rtype: List[str]
         """
-        normalizers = OrderedDict()
+        normalizers = []
 
         nb_images = self.n_images(entry)
 
         path = self.measurement_tpl.format(entry) + '/'
         with self._get_file() as h5_file:
             for name, node in h5_file[path].items():
-                if isinstance(node, _h5py.Dataset) and node.dtype.kind in 'iuf':
+                if (isinstance(node, _h5py.Dataset) and
+                        node.dtype.kind in 'iuf' and
+                        node.ndim == 1 and
+                        node.shape[0] == nb_images):
                     # Only get (u)int and float datasets
-                    if node.ndim == 0:
-                        # single scalar, make an array of it
-                        normalizers[name] = _np.array([node[()]] * nb_images)
-                    elif node.ndim == 1 and node.shape[0] == nb_images:
-                        # same number of values as number of images
-                        normalizers[name] = node[()]
+                    # with same number of values as number of images
+                    normalizers.append(name)
 
         return normalizers