dask: Data.reconstruct_sectioned_data

cf/__init__.py

@@ -185,7 +185,7 @@
     )
 
 # Check the version of dask
-_minimum_vn = "2022.03.0"
+_minimum_vn = "2022.6.0"
 if LooseVersion(dask.__version__) < LooseVersion(_minimum_vn):
     raise RuntimeError(
         f"Bad dask version: cf requires dask>={_minimum_vn}. "

cf/data/data.py

@@ -5914,73 +5914,6 @@ def concatenate_data(cls, data_list, axis):
             assert len(data_list) == 1
             return data_list[0]
 
-    @classmethod
-    def reconstruct_sectioned_data(cls, sections, cyclic=(), hardmask=None):
-        """Expects a dictionary of Data objects with ordering
-        information as keys, as output by the section method when called
-        with a Data object. Returns a reconstructed cf.Data object with
-        the sections in the original order.
-
-        :Parameters:
-
-            sections: `dict`
-                The dictionary of `Data` objects with ordering information
-                as keys.
-
-        :Returns:
-
-            `Data`
-                The resulting reconstructed Data object.
-
-        **Examples**
-
-        >>> d = cf.Data(numpy.arange(120).reshape(2, 3, 4, 5))
-        >>> x = d.section([1, 3])
-        >>> len(x)
-        8
-        >>> e = cf.Data.reconstruct_sectioned_data(x)
-        >>> e.equals(d)
-        True
-
-        """
-        ndims = len(list(sections.keys())[0])
-
-        for i in range(ndims - 1, -1, -1):
-            keys = sorted(sections.keys())
-            if i == 0:
-                if keys[0][i] is None:
-                    assert len(keys) == 1
-                    return tuple(sections.values())[0]
-                else:
-                    data_list = []
-                    for k in keys:
-                        data_list.append(sections[k])
-
-                    out = cls.concatenate_data(data_list, i)
-
-                    out.cyclic(cyclic)
-                    if hardmask is not None:
-                        out.hardmask = hardmask
-
-                    return out
-
-            if keys[0][i] is not None:
-                new_sections = {}
-                new_key = keys[0][:i]
-                data_list = []
-                for k in keys:
-                    if k[:i] == new_key:
-                        data_list.append(sections[k])
-                    else:
-                        new_sections[new_key] = cls.concatenate_data(
-                            data_list, axis=i
-                        )
-                        new_key = k[:i]
-                        data_list = [sections[k]]
-
-                new_sections[new_key] = cls.concatenate_data(data_list, i)
-                sections = new_sections
-
     def argmax(self, axis=None, unravel=False):
         """Return the indices of the maximum values along an axis.
 

cf/data/mixin/deprecations.py

@@ -922,3 +922,39 @@ def seterr(all=None, divide=None, over=None, under=None, invalid=None):
             "manipulations. This may change in the future (see "
             "https://github.com/dask/dask/issues/3245 for more details)."
         )
+
+    @classmethod
+    def reconstruct_sectioned_data(cls, sections, cyclic=(), hardmask=None):
+        """Expects a dictionary of Data objects with ordering
+        information as keys, as output by the section method when called
+        with a Data object. Returns a reconstructed cf.Data object with
+        the sections in the original order.
+
+        Deprecated at version TODODASK and is no longer available.
+
+        :Parameters:
+
+            sections: `dict`
+                The dictionary of `Data` objects with ordering information
+                as keys.
+
+        :Returns:
+
+            `Data`
+                The resulting reconstructed Data object.
+
+        **Examples**
+
+        >>> d = cf.Data(numpy.arange(120).reshape(2, 3, 4, 5))
+        >>> x = d.section([1, 3])
+        >>> len(x)
+        8
+        >>> e = cf.Data.reconstruct_sectioned_data(x)
+        >>> e.equals(d)
+        True
+
+        """
+        raise DeprecationError(
+            "Data method 'reconstruct_sectioned_data' has been deprecated "
+            "at version TODODASK and is no longer available"
+        )

cf/test/test_Data.py

@@ -2493,14 +2493,6 @@ def test_Data_section(self):
         self.assertEqual(key, (None, None, None))
         self.assertTrue(value.equals(d))
 
-    @unittest.skipIf(TEST_DASKIFIED_ONLY, "Needs reconstruct_sectioned_data")
-    def test_Data_reconstruct_sectioned_data(self):
-        if self.test_only and inspect.stack()[0][3] not in self.test_only:
-            return
-
-        # TODODASK: Write when Data.reconstruct_sectioned_data is
-        #           daskified
-
     @unittest.skipIf(TEST_DASKIFIED_ONLY, "no attr. 'partition_configuration'")
     def test_Data_count(self):
         if self.test_only and inspect.stack()[0][3] not in self.test_only:
@@ -2532,7 +2524,6 @@ def test_Data_exp(self):
             # self.assertTrue((d.array==c).all()) so need a
             # check which accounts for floating point calcs:
             np.testing.assert_allclose(d.array, c)
-        # --- End: for
 
         d = cf.Data(a, "m")
         with self.assertRaises(Exception):
@@ -3954,7 +3945,7 @@ def test_Data_soften_mask(self):
         d.soften_mask()
         self.assertFalse(d.hardmask)
         self.assertEqual(len(d.to_dask_array().dask.layers), 2)
-        
+
     def test_Data_compressed_array(self):
         import cfdm
 

requirements.txt

@@ -4,4 +4,4 @@ numpy>=1.22
 cfdm>=1.9.1.0, <1.9.2.0
 psutil>=0.6.0
 cfunits>=3.3.4
-dask>=2022.03.0
+dask>=2022.6.0