Sharedata

README.md

@@ -4,6 +4,7 @@ Iris
 [![Join the chat at https://gitter.im/SciTools/iris](https://badges.gitter.im/SciTools/iris.svg)](https://gitter.im/SciTools/iris?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
 [![Build Status](https://api.travis-ci.org/repositories/SciTools/iris.svg?branch=master)](https://travis-ci.org/SciTools/iris/branches)
 [![DOI](https://zenodo.org/badge/doi/10.5281/zenodo.51860.svg)](https://dx.doi.org/10.5281/zenodo.51860)
+[![Documentation for master branch ](https://img.shields.io/badge/docs-master-blue.svg)](https://scitools-docs.github.io/iris/master/index.html)
 
 (C) British Crown Copyright 2010 - 2017, Met Office
 

lib/iris/coords.py

@@ -521,14 +521,24 @@ def copy(self, points=None, bounds=None):
             raise ValueError('If bounds are specified, points must also be '
                              'specified')
 
-        new_coord = copy.deepcopy(self)
         if points is not None:
+            # We do not perform a deepcopy when we supply new points so as to
+            # not unncessarily copy the old points.
+
+            # Create a temp-coord to manage deep copying of a small array.
+            temp_coord = copy.copy(self)
+            temp_coord.bounds = None
+            # note: DataManager cannot be None or DataManager(None) for
+            # a deepcopy operation.
+            temp_coord._points_dm = DataManager(np.array((1,)))
+            new_coord = copy.deepcopy(temp_coord)
+            del(temp_coord)
             new_coord._points_dm = None
             new_coord.points = points
-            # Regardless of whether bounds are provided as an argument, new
-            # points will result in new bounds, discarding those copied from
-            # self.
+            # new points will result in new bounds.
             new_coord.bounds = bounds
+        else:
+            new_coord = copy.deepcopy(self)
 
         return new_coord
 

lib/iris/cube.py

@@ -781,6 +781,27 @@ def __init__(self, data, standard_name=None, long_name=None,
             for cell_measure, dims in cell_measures_and_dims:
                 self.add_cell_measure(cell_measure, dims)
 
+        # When True indexing may result in a view onto the original data array,
+        # to avoid unnecessary copying.
+        self._share_data = False
+
+    @property
+    def share_data(self):
+        """
+        Share cube data when slicing/indexing cube if True.
+        Setting this flag to True will realise the data payload,
+        if it is lazy, as lazy data cannot currently be shared across cubes.
+        """
+        return self._share_data
+
+    @share_data.setter
+    def share_data(self, value):
+        # If value is True: realise the data (if is hasn't already been) as
+        # sharing lazy data is not possible.
+        if value and self.has_lazy_data():
+            _ = self.data
+        self._share_data = bool(value)
+
     @property
     def metadata(self):
         """
@@ -2173,8 +2194,10 @@ def new_cell_measure_dims(cm_):
         dimension_mapping, data = iris.util._slice_data_with_keys(
             cube_data, keys)
 
-        # We don't want a view of the data, so take a copy of it.
-        data = deepcopy(data)
+        # We don't want a view of the data, so take a copy of it, unless
+        # self.share_data is True.
+        if not self.share_data:
+            data = deepcopy(data)
 
         # We can turn a masked array into a normal array if it's full.
         if ma.isMaskedArray(data):

lib/iris/tests/unit/cube/test_Cube.py

@@ -25,6 +25,7 @@
 
 from itertools import permutations
 
+import dask.array as da
 import numpy as np
 import numpy.ma as ma
 
@@ -66,6 +67,10 @@ def test_matrix(self):
         self.assertEqual(type(cube.data), np.ndarray)
         self.assertArrayEqual(cube.data, data)
 
+    def test_default_share_data(self):
+        cube = Cube(np.arange(1))
+        self.assertFalse(cube.share_data)
+
 
 class Test_extract(tests.IrisTest):
     def test_scalar_cube_exists(self):
@@ -1877,6 +1882,50 @@ def test_remove_cell_measure(self):
                          [[self.b_cell_measure, (0, 1)]])
 
 
+class Test_share_data(tests.IrisTest):
+    def test_setter_lazy_data(self):
+        cube = Cube(da.from_array(np.arange(6).reshape(2, 3), chunks=6))
+        cube.share_data = True
+        self.assertFalse(cube.has_lazy_data())
+        self.assertTrue(cube._share_data)
+
+    def test_setter_realised_data(self):
+        cube = Cube(np.arange(6).reshape(2, 3))
+        cube.share_data = True
+        self.assertFalse(cube.has_lazy_data())
+        self.assertTrue(cube._share_data)
+
+
+class Test___getitem__no_share_data(tests.IrisTest):
+    def test_lazy_array(self):
+        cube = Cube(da.from_array(np.arange(6).reshape(2, 3), chunks=6))
+        cube2 = cube[1:]
+        self.assertTrue(cube2.has_lazy_data())
+        cube.data
+        self.assertTrue(cube2.has_lazy_data())
+
+    def test_ndarray(self):
+        cube = Cube(np.arange(6).reshape(2, 3))
+        cube2 = cube[1:]
+        self.assertIsNot(cube.data.base, cube2.data.base)
+
+
+class Test___getitem__share_data(tests.IrisTest):
+    def test_lazy_array(self):
+        cube = Cube(da.from_array(np.arange(6).reshape(2, 3), chunks=6))
+        cube.share_data = True
+        cube2 = cube[1:]
+        self.assertFalse(cube.has_lazy_data())
+        self.assertFalse(cube2.has_lazy_data())
+        self.assertIs(cube.data.base, cube2.data.base)
+
+    def test_ndarray(self):
+        cube = Cube(np.arange(6).reshape(2, 3))
+        cube.share_data = True
+        cube2 = cube[1:]
+        self.assertIs(cube.data.base, cube2.data.base)
+
+
 class Test__getitem_CellMeasure(tests.IrisTest):
     def setUp(self):
         cube = Cube(np.arange(6).reshape(2, 3))