Remove deepcopies when slicing or manipulating cubes

lib/iris/analysis/maths.py

@@ -1,4 +1,4 @@
-# (C) British Crown Copyright 2010 - 2013, Met Office
+# (C) British Crown Copyright 2010 - 2014, Met Office
 #
 # This file is part of Iris.
 #
@@ -536,7 +536,9 @@ def _math_op_common(cube, operation_function, new_unit, in_place=False):
         new_cube = cube
         operation_function(new_cube.data, out=new_cube.data)
     else:
-        new_cube = cube.copy(data=operation_function(cube.data))
+        # use a slice to shallow copy the cube
+        new_cube = cube[:]
+        new_cube.data = operation_function(cube.data)
     iris.analysis.clear_phenomenon_identity(new_cube)
     new_cube.units = new_unit
     return new_cube

lib/iris/coords.py

@@ -431,7 +431,9 @@ def copy(self, points=None, bounds=None):
             raise ValueError('If bounds are specified, points must also be '
                              'specified')
 
-        new_coord = copy.deepcopy(self)
+        new_coord = copy.copy(self)
+        new_coord.attributes = copy.deepcopy(self.attributes)
+        new_coord.coord_system = copy.deepcopy(self.coord_system)
         if points is not None:
             # Explicitly not using the points property as we don't want the
             # shape the new points to be constrained by the shape of

lib/iris/cube.py

@@ -551,7 +551,7 @@ def __init__(self, data, standard_name=None, long_name=None,
 
         if data_manager is not None:
             self._data = data
-            self._data_manager = data_manager
+            self._data_manager = copy.deepcopy(data_manager)
         else:
             if isinstance(data, np.ndarray):
                 self._data = data
@@ -1760,22 +1760,17 @@ def __getitem__(self, keys):
                 data = self.data[first_slice]
         else:
             if use_data_proxy:
-                data = copy.deepcopy(self._data)
+                data = self._data
                 data_manager = copy.deepcopy(self._data_manager)
             else:
-                data = copy.deepcopy(self.data)
+                data = self.data
 
         for other_slice in slice_gen:
             if use_data_proxy:
                 data, data_manager = data_manager.getitem(data, other_slice)
             else:
                 data = data[other_slice]
 
-        # We don't want a view of the numpy array, so take a copy of it if
-        # it's not our own (this applies to proxy "empty data" arrays too)
-        if not data.flags['OWNDATA']:
-            data = data.copy()
-
         # We can turn a masked array into a normal array if it's full.
         if isinstance(data, ma.core.MaskedArray):
             if ma.count_masked(data) == 0:
@@ -2012,10 +2007,9 @@ def transpose(self, new_order=None):
         elif len(new_order) != self.data.ndim:
             raise ValueError('Incorrect number of dimensions.')
 
-        # The data needs to be copied, otherwise this view of the transposed
-        # data will not be contiguous. Ensure not to assign via the cube.data
-        # setter property since we are reshaping the cube payload in-place.
-        self._data = np.transpose(self.data, new_order).copy()
+        # Ensure not to assign via the cube.data setter property since we are
+        # reshaping the cube payload in-place.
+        self._data = np.transpose(self.data, new_order)
 
         dim_mapping = {src: dest for dest, src in enumerate(new_order)}