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davidhassell · Sep 6, 2023 · 82efa8b · 82efa8b
1 parent 229e383
commit 82efa8b
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Showing 21 changed files with 804 additions and 428 deletions.
diff --git a/cf/__init__.py b/cf/__init__.py
@@ -264,6 +264,7 @@
     FullArray,
     GatheredArray,
     NetCDFArray,
+    PointTopologyArray,
     RaggedContiguousArray,
     RaggedIndexedArray,
     RaggedIndexedContiguousArray,

diff --git a/cf/cfimplementation.py b/cf/cfimplementation.py
@@ -32,6 +32,7 @@
     CFANetCDFArray,
     GatheredArray,
     NetCDFArray,
+    PointTopologyArray,
     RaggedContiguousArray,
     RaggedIndexedArray,
     RaggedIndexedContiguousArray,
@@ -175,6 +176,7 @@ def initialise_CFANetCDFArray(
     CellConnectivityArray=CellConnectivityArray,
     GatheredArray=GatheredArray,
     NetCDFArray=NetCDFArray,
+    PointTopologyArray=PointTopologyArray,
     RaggedContiguousArray=RaggedContiguousArray,
     RaggedIndexedArray=RaggedIndexedArray,
     RaggedIndexedContiguousArray=RaggedIndexedContiguousArray,
@@ -229,6 +231,7 @@ def implementation():
      'Data': cf.data.data.Data,
      'GatheredArray': cf.data.array.gatheredarray.GatheredArray,
      'NetCDFArray': cf.data.array.netcdfarray.NetCDFArray,
+     'PointTopologyArray': <class 'cf.data.array.pointtopologyarray.PointTopologyArray'>,
      'RaggedContiguousArray': cf.data.array.raggedcontiguousarray.RaggedContiguousArray,
      'RaggedIndexedArray': cf.data.array.raggedindexedarray.RaggedIndexedArray,
      'RaggedIndexedContiguousArray': cf.data.array.raggedindexedcontiguousarray.RaggedIndexedContiguousArray,

diff --git a/cf/data/array/__init__.py b/cf/data/array/__init__.py
@@ -4,6 +4,7 @@
 from .fullarray import FullArray
 from .gatheredarray import GatheredArray
 from .netcdfarray import NetCDFArray
+from .pointtopologyarray import PointTopologyArray
 from .raggedcontiguousarray import RaggedContiguousArray
 from .raggedindexedarray import RaggedIndexedArray
 from .raggedindexedcontiguousarray import RaggedIndexedContiguousArray

diff --git a/cf/data/array/boundsfromnodesarray.py b/cf/data/array/boundsfromnodesarray.py
@@ -11,20 +11,15 @@ class BoundsFromNodesArray(
     Container,
     cfdm.BoundsFromNodesArray,
 ):
-    """An underlying gathered array.
+    """An array of cell bounds defined by UGRID node coordinates.
 
-    TODOUGRID
+    The UGRID node coordinates contain the locations of the nodes of
+    the domain topology. In UGRID, the bounds of edge, face and volume
+    cells may be defined by the these locations in conjunction with a
+    mapping from from each cell boundary vertex to its corresponding
+    coordinate value.
 
-    Compression by gathering combines axes of a multidimensional array
-    into a new, discrete axis whilst omitting the missing values and
-    thus reducing the number of values that need to be stored.
-
-    The information needed to uncompress the data is stored in a "list
-    variable" that gives the indices of the required points.
-
-    See CF section 8.2. "Lossless Compression by Gathering".
-
-    .. versionadded:: TODOUGRIDVER
+    .. versionadded:: UGRIDVER
 
     """
 
@@ -33,91 +28,7 @@ def __repr__(self):
 
         x.__repr__() <==> repr(x)
 
-        .. versionadded:: TODOUGRIDVER
+        .. versionadded:: UGRIDVER
 
         """
         return super().__repr__().replace("<", "<CF ", 1)
-
-
-#    def to_dask_array(self, chunks="auto"):
-#        """Convert the data to a `dask` array.
-#
-#        .. versionadded:: TODOUGRIDVER
-#
-#        :Parameters:
-#
-#            chunks: `int`, `tuple`, `dict` or `str`, optional
-#                Specify the chunking of the returned dask array.
-#
-#                Any value accepted by the *chunks* parameter of the
-#                `dask.array.from_array` function is allowed.
-#
-#                The chunk sizes implied by *chunks* for a dimension that
-#                has been fragmented are ignored and replaced with values
-#                that are implied by that dimensions fragment sizes.
-#
-#        :Returns:
-#
-#            `dask.array.Array`
-#                The `dask` array representation.
-#
-#        """
-#        from functools import partial
-#
-#        import dask.array as da
-#        from dask import config
-#        from dask.array.core import getter, normalize_chunks
-#        from dask.base import tokenize
-#
-#        name = (f"{self.__class__.__name__}-{tokenize(self)}",)
-#
-#        dtype = self.dtype
-#
-#        context = partial(config.set, scheduler="synchronous")
-#
-#        compressed_dimensions = self.compressed_dimensions()
-#        conformed_data = self.conformed_data()
-#
-#        # If possible, convert the compressed data to a dask array
-#        # that doesn't support concurrent reads. This prevents
-#        # "compute called by compute" failures problems at compute
-#        # time.
-#        #
-#        # TODO: This won't be necessary if this is refactored so that
-#        #       the compressed data is part of the same dask graph as
-#        #       the compressed subarrays.
-#        conformed_data = {
-#            k: self._lock_file_read(v) for k, v in conformed_data.items()
-#        }
-#
-#        # Get the (cfdm) subarray class
-#        Subarray = self.get_Subarray()
-#        subarray_name = Subarray().__class__.__name__
-#
-#        # Set the chunk sizes for the dask array
-#        chunks = self.subarray_shapes(chunks)
-#        chunks = normalize_chunks(
-#            self.subarray_shapes(chunks),
-#            shape=self.shape,
-#            dtype=dtype,
-#        )
-#
-#        dsk = {}
-#        for u_indices, u_shape, c_indices, chunk_location in zip(
-#            *self.subarrays(chunks)
-#        ):
-#            subarray = Subarray(
-#                indices=c_indices,
-#                shape=u_shape,
-#                compressed_dimensions=compressed_dimensions,
-#                context_manager=context,
-#                **conformed_data,
-#            )
-#
-#            key = f"{subarray_name}-{tokenize(subarray)}"
-#            dsk[key] = subarray
-#
-#            dsk[name + chunk_location] = (getter, key, Ellipsis, False, False)
-#
-#        # Return the dask array
-#        return da.Array(dsk, name[0], chunks=chunks, dtype=dtype)
diff --git a/cf/data/array/cellconnectivityarray.py b/cf/data/array/cellconnectivityarray.py
@@ -11,20 +11,17 @@ class CellConnectivityArray(
     Container,
     cfdm.CellConnectivityArray,
 ):
-    """An underlying gathered array.
+    """A connectivity array derived from a UGRID connectivity variable.
 
-    TODOUGRID
+    A UGRID connectivity variable contains indices which map each cell
+    to its neighbours, as found in a UGRID "edge_edge_connectivty",
+    "face_face_connectivty", or "volume_volume_connectivty" variable.
 
-    Compression by gathering combines axes of a multidimensional array
-    into a new, discrete axis whilst omitting the missing values and
-    thus reducing the number of values that need to be stored.
+    The connectivity array has one more column than the corresponding
+    UGRID variable. The extra column, in the first position, contains
+    the identifier for each cell.
 
-    The information needed to uncompress the data is stored in a "list
-    variable" that gives the indices of the required points.
-
-    See CF section 8.2. "Lossless Compression by Gathering".
-
-    .. versionadded:: TODOUGRIDVER
+    .. versionadded:: UGRIDVER
 
     """
 
@@ -33,7 +30,7 @@ def __repr__(self):
 
         x.__repr__() <==> repr(x)
 
-        .. versionadded:: TODOUGRIDVER
+        .. versionadded:: UGRIDVER
 
         """
         return super().__repr__().replace("<", "<CF ", 1)
diff --git a/cf/data/array/gatheredarray.py b/cf/data/array/gatheredarray.py
@@ -32,86 +32,91 @@ def __repr__(self):
         """
         return super().__repr__().replace("<", "<CF ", 1)
 
-    def to_dask_array(self, chunks="auto"):
-        """Convert the data to a `dask` array.
-
-        .. versionadded:: 3.14.0
-
-        :Parameters:
-
-            chunks: `int`, `tuple`, `dict` or `str`, optional
-                Specify the chunking of the returned dask array.
-
-                Any value accepted by the *chunks* parameter of the
-                `dask.array.from_array` function is allowed.
-
-                The chunk sizes implied by *chunks* for a dimension that
-                has been fragmented are ignored and replaced with values
-                that are implied by that dimensions fragment sizes.
-
-        :Returns:
-
-            `dask.array.Array`
-                The `dask` array representation.
-
-        """
-        from functools import partial
-
-        import dask.array as da
-        from dask import config
-        from dask.array.core import getter, normalize_chunks
-        from dask.base import tokenize
-
-        name = (f"{self.__class__.__name__}-{tokenize(self)}",)
-
-        dtype = self.dtype
-
-        context = partial(config.set, scheduler="synchronous")
-
-        compressed_dimensions = self.compressed_dimensions()
-        conformed_data = self.conformed_data()
-        compressed_data = conformed_data["data"]
-        uncompressed_indices = conformed_data["uncompressed_indices"]
-
-        # If possible, convert the compressed data to a dask array
-        # that doesn't support concurrent reads. This prevents
-        # "compute called by compute" failures problems at compute
-        # time.
-        #
-        # TODO: This won't be necessary if this is refactored so that
-        #       the compressed data is part of the same dask graph as
-        #       the compressed subarrays.
-        compressed_data = self._lock_file_read(compressed_data)
-
-        # Get the (cfdm) subarray class
-        Subarray = self.get_Subarray()
-        subarray_name = Subarray().__class__.__name__
-
-        # Set the chunk sizes for the dask array
-        chunks = self.subarray_shapes(chunks)
-        chunks = normalize_chunks(
-            self.subarray_shapes(chunks),
-            shape=self.shape,
-            dtype=dtype,
-        )
-
-        dsk = {}
-        for u_indices, u_shape, c_indices, chunk_location in zip(
-            *self.subarrays(chunks)
-        ):
-            subarray = Subarray(
-                data=compressed_data,
-                indices=c_indices,
-                shape=u_shape,
-                compressed_dimensions=compressed_dimensions,
-                uncompressed_indices=uncompressed_indices,
-                context_manager=context,
-            )
-
-            key = f"{subarray_name}-{tokenize(subarray)}"
-            dsk[key] = subarray
-
-            dsk[name + chunk_location] = (getter, key, Ellipsis, False, False)
-
-        # Return the dask array
-        return da.Array(dsk, name[0], chunks=chunks, dtype=dtype)
+    def subarray_parameters(self):
+        """TODOUGRID"""
+        return {}
+
+
+#    def to_dask_array(self, chunks="auto"):
+#        """Convert the data to a `dask` array.
+#
+#        .. versionadded:: 3.14.0
+#
+#        :Parameters:
+#
+#            chunks: `int`, `tuple`, `dict` or `str`, optional
+#                Specify the chunking of the returned dask array.
+#
+#                Any value accepted by the *chunks* parameter of the
+#                `dask.array.from_array` function is allowed.
+#
+#                The chunk sizes implied by *chunks* for a dimension that
+#                has been fragmented are ignored and replaced with values
+#                that are implied by that dimensions fragment sizes.
+#
+#        :Returns:
+#
+#            `dask.array.Array`
+#                The `dask` array representation.
+#
+#        """
+#        from functools import partial
+#
+#        import dask.array as da
+#        from dask import config
+#        from dask.array.core import getter, normalize_chunks
+#        from dask.base import tokenize
+#
+#        name = (f"{self.__class__.__name__}-{tokenize(self)}",)
+#
+#        dtype = self.dtype
+#
+#        context = partial(config.set, scheduler="synchronous")
+#
+#        compressed_dimensions = self.compressed_dimensions()
+#        conformed_data = self.conformed_data()
+#        compressed_data = conformed_data["data"]
+#        uncompressed_indices = conformed_data["uncompressed_indices"]
+#
+#        # If possible, convert the compressed data to a dask array
+#        # that doesn't support concurrent reads. This prevents
+#        # "compute called by compute" failures problems at compute
+#        # time.
+#        #
+#        # TODO: This won't be necessary if this is refactored so that
+#        #       the compressed data is part of the same dask graph as
+#        #       the compressed subarrays.
+#        compressed_data = self._lock_file_read(compressed_data)
+#
+#        # Get the (cfdm) subarray class
+#        Subarray = self.get_Subarray()
+#        subarray_name = Subarray().__class__.__name__
+#
+#        # Set the chunk sizes for the dask array
+#        #        chunks = self.subarray_shapes(chunks)
+#        chunks = normalize_chunks(
+#            self.subarray_shapes(chunks),
+#            shape=self.shape,
+#            dtype=dtype,
+#        )
+#
+#        dsk = {}
+#        for u_indices, u_shape, c_indices, chunk_location in zip(
+#            *self.subarrays(chunks)
+#        ):
+#            subarray = Subarray(
+#                data=compressed_data,
+#                indices=c_indices,
+#                shape=u_shape,
+#                compressed_dimensions=compressed_dimensions,
+#                uncompressed_indices=uncompressed_indices,
+#                context_manager=context,
+#            )
+#
+#            key = f"{subarray_name}-{tokenize(subarray)}"
+#            dsk[key] = subarray
+#
+#            dsk[name + chunk_location] = (getter, key, Ellipsis, False, False)
+#
+#        # Return the dask array
+#        return da.Array(dsk, name[0], chunks=chunks, dtype=dtype)
diff --git a/cf/data/array/mixin/__init__.py b/cf/data/array/mixin/__init__.py
@@ -2,4 +2,5 @@
 from .compressedarraymixin import CompressedArrayMixin
 from .filearraymixin import FileArrayMixin
 from .mesharraymixin import MeshArrayMixin
-from .raggedarraymixin import RaggedArrayMixin
+
+# from .raggedarraymixin import RaggedArrayMixin