When you execute a filter, the default behavior is to do the execution
on each partition of the data set independently. This code path is
followed even for non-partitioned data; the `DataSet` is wrapped in a
`PartitionedDataSet` of one partition.
Make performance logging a bit more clear by only giving one scoped log
for a basic `DataSet` and recording the number of partitions executed in
the log.
The version of `Filter::Execute` that takes a policy as an argument is now
deprecated. Filters are now able to specify their own fields and types,
which is often why you want to customize the policy for an execution. The
other reason is that you are compiling VTK-m into some other source that
uses a particular types of storage. However, there is now a mechanism in
the CMake configuration to allow you to provide a header that customizes
the "default" types used in filters. This is a much more convenient way to
compile filters for specific types.
One thing that filters were not able to do was to customize what cell sets
they allowed using. This allows filters to self-select what types of cell
sets they support (beyond simply just structured or unstructured). To
support this, the lists `SupportedCellSets`, `SupportedStructuredCellSets`,
and `SupportedUnstructuredCellSets` have been added to `Filter`. When you
apply a policy to a cell set, you now have to also provide the filter.
VTK-m now provides the following filters with the default policy
as part of the vtkm_filter library:
- CellAverage
- CleanGrid
- ClipWithField
- ClipWithImplicitFunction
- Contour
- ExternalFaces
- ExtractStructured
- PointAverage
- Threshold
- VectorMagnitude
By building these as a library we hope to provide faster compile
times for consumers of VTK-m when using common configurations.
The `MultiBlock` class has been renamed to `PartitionedDataSet`, and its API
has been refactored to refer to "partitions", rather than "blocks".
Additionally, the `AddBlocks` method has been changed to `AppendPartitions` to
more accurately reflect the operation performed. The associated
`AssignerMultiBlock` class has also been renamed to
`AssignerPartitionedDataSet`.
This change is motivated towards unifying VTK-m's data model with VTK. VTK has
started to move away from `vtkMultiBlockDataSet`, which is a hierarchical tree
of nested datasets, to `vtkPartitionedDataSet`, which is always a flat vector
of datasets used to assist geometry distribution in multi-process environments.
This simplifies traversal during processing and clarifies the intent of the
container: The component datasets are partitions for distribution, not
organizational groupings (e.g. materials).
Ref #405
Now that the dispatcher does its own TryExecute, filters do not need to
do that. This change requires all worklets called by filters to be able
to execute without knowing the device a priori.
Adding API to DataSet to `CopyStructure` from another dataset. This
copies the cellsets and coordinate systems while leaving the fields
unchanged.
CreateResult no longer copies all input fields to the output dataset
created.
Furthermore, if a Filter subclass doesn't provide `MapFieldOntoOutput`,
then the default implementation simply copies only the selected fields
to the output dataset.
This revamps Filter API to improve support for multiblock dataset and
distributed use-cases. Filters now operate on MultiBlock alone thus
`Filter::Execute(MultiBlock&)` is the primary method.
`Filter::Execute(DataSet*)` is only provided as an convenience that
internally puts the dataset into a MultiBlock and calls the primary
method.
Subclasses can provides PreExecute and PostExecute overrides to handle
init/reduction operations for filters with operating on multiple blocks.
Since blocks can be distributed, filters are expected to handle that as
well.
Subclasses can provide `PrepareForExecution(MultiBlock*..)` to customize
behavior for handling multiblock inputs. Default is to simply loop
over blocks.
This commit removes `vtkm::filter::Result`. All methods that used
`vtkm::filter::Result` simply change to use `vtkm::cont::Dataset` instead.
The utility API on `Result` that was used to add fields to the resulting
dataset is now available via `vtkm::filter::internal::CreateResult`.
Previously you passed a FieldSelection to Filter::Execute to specify
which fields to pass from input to output. There is no real reason for
this as other information about input and output fields are member
variables to Filter. This moves field selection as a member variable as
well. (This should also help confusion when updating old code to new to
prevent users from mistaking field passing with input fields.
Also added a few convenience constructors to FieldSelection so that you
can call Field::SetFieldsToPass() with just the string of what you want
to pass.
Filters now support executing on a dataset to produce a result dataset
with automatic mapping of fields to the output dataset. Fields to map
can be selected using `vtkm::filter::FieldSelection` class, which provides
constructors to map all or no fields, along with a selection of fields.
This updates all tests to use the new filter API.
