Merge branch 'master' into dependabot/pip/requirements/pyvista-0.41.1

.github/workflows/ci.yml

@@ -120,6 +120,7 @@ jobs:
           cname: ${{ env.DOCUMENTATION_CNAME }}
           token: ${{ secrets.GITHUB_TOKEN }}
           doc-artifact-name: HTML-doc-ansys-dpf-core.zip
+          decompress-artifact: true
 
   examples:
     if: startsWith(github.head_ref, 'master') || github.event.action == 'ready_for_review' || !github.event.pull_request.draft

.github/workflows/ci_release.yml

@@ -184,11 +184,6 @@ jobs:
     needs: [style, tests, docs, examples, retro_232, retro_231, retro_222, retro_221, gate, docker_tests]
     runs-on: ubuntu-latest
     steps:
-      - name: "Set up Python"
-        uses: actions/setup-python@v4.6.0
-        with:
-          python-version: 3.9
-
       - name: "Download artifacts"
         uses: actions/download-artifact@v3
 
@@ -204,12 +199,3 @@ jobs:
             ./**/*.zip
           draft: true
           generate_release_notes: true
-
-#      - name: "Upload to Test PyPi"  # Change TOKEN
-#        run: |
-#          pip install twine
-#          twine upload --repository testpypi --skip-existing ./**/*.whl
-#          twine upload --repository testpypi --skip-existing ./**/*.tar.gz
-#        env:
-#          TWINE_USERNAME: __token__
-#          TWINE_PASSWORD: ${{ secrets.TEST_PYPI_API_TOKEN }}

.github/workflows/docs.yml

@@ -180,5 +180,5 @@ jobs:
         uses: actions/upload-artifact@v3
         with:
           name: HTML-doc-${{env.PACKAGE_NAME}}.zip
-          path: docs/build/html
+          path: HTML-doc-${{env.PACKAGE_NAME}}.zip
         if: always()

.github/workflows/releaser.yml

@@ -39,16 +39,21 @@ jobs:
           file: HTML-doc-ansys-dpf-core.zip
           token: ${{ secrets.GITHUB_TOKEN }}
 
-#      - name: "Unzip HTML Documentation"
-#        shell: bash
-#        run: |
-#          unzip HTML-doc-ansys-dpf-core.zip -d documentation-html
-#          chmod -R 777 documentation-html
-#        if: always()
+      - name: "List downloaded assets"
+        shell: bash
+        run: |
+          ls
+
+      - name: "Upload artifact"
+        uses: actions/upload-artifact@v3
+        with:
+          name: HTML-doc-ansys-dpf-core.zip
+          path: HTML-doc-ansys-dpf-core.zip
 
       - name: "Deploy the stable documentation"
         uses: ansys/actions/doc-deploy-stable@v4
         with:
           cname: ${{ env.DOCUMENTATION_CNAME }}
           token: ${{ secrets.GITHUB_TOKEN }}
           doc-artifact-name: HTML-doc-ansys-dpf-core.zip
+          decompress-artifact: true

README.md

@@ -10,7 +10,7 @@
 [![cov](https://codecov.io/gh/ansys/pydpf-core/branch/master/graph/badge.svg)](https://codecov.io/gh/ansys/pydpf-core)
 [![codacy](https://app.codacy.com/project/badge/Grade/61b6a519aea64715ad1726b3955fcf98)](https://www.codacy.com/gh/ansys/pydpf-core/dashboard?utm_source=github.com&utm_medium=referral&utm_content=ansys/pydpf-core&utm_campaign=Badge_Grade)
 
-The Data Processing Framework (DPF) provides numerical simulation 
+Ansys Data Processing Framework (DPF) provides numerical simulation 
 users and engineers with a toolbox for accessing and transforming simulation 
 data. With DPF, you can perform complex preprocessing or postprocessing of
 large amounts of simulation data within a simulation workflow.
@@ -27,8 +27,8 @@ The latest version of DPF supports Ansys solver result files for:
 - Fluent (`.cas/dat.h5`, `.flprj`)
 - CFX (`.cad/dat.cff`, `.flprj`)
 
-See the `PyDPF-Core main page <https://dpf.docs.pyansys.com/version/stable/index.html>`_
-for more information on compatibility.
+For more information on compatibility, see the `main page <https://dpf.docs.pyansys.com/version/stable/index.html>`_
+of the PDF-Core documentation.
 
 Using the many DPF operators that are available, you can manipulate and
 transform this data. You can also chain operators together to create simple
@@ -47,12 +47,30 @@ The ``ansys.dpf.core`` package provides a Python interface to DPF, enabling
 rapid postprocessing of a variety of Ansys file formats and physics solutions
 without ever leaving the Python environment.
 
-## Documentation
+## Documentation and issues
 
-Visit the [DPF-Core Documentation](https://dpfdocs.pyansys.com) for
-comprehensive information on this library. See the
-[Examples](https://dpfdocs.pyansys.com/version/stable/examples/index.html)
-for how-to information.
+Documentation for the latest stable release of PyPDF-Core is hosted at
+[DPF-Core documentation](https://dpf.docs.pyansys.com/version/stable/).
+
+In the upper right corner of the documentation's title bar, there is an option for switching from
+viewing the documentation for the latest stable release to viewing the documentation for the
+development version or previously released versions.
+
+In the upper right corner of the documentation's title bar, there is an option for switching from
+viewing the documentation for the latest stable release to viewing the documentation for the
+development version or previously released versions.
+
+You can also [view](https://cheatsheets.docs.pyansys.com/pydpf-core_cheat_sheet.png) or
+[download](https://cheatsheets.docs.pyansys.com/pydpf-core_cheat_sheet.pdf) the
+PyDPF-Core cheat sheet. This one-page reference provides syntax rules and commands
+for using PyDPF-Core.
+
+On the [PyDPF-Core Issues](https://github.com/ansys/pydpf-core/issues) page,
+you can create issues to report bugs and request new features. On the
+[PyDPF-Core Discussions](https://github.com/ansys/pydpf-core/discussions) page or the {Discussions](https://discuss.ansys.com/)
+page on the Ansys Developer portal, you can post questions, share ideas, and get community feedback. 
+
+To reach the project support team, email [pyansys.core@ansys.com](mailto:pyansys.core@ansys.com).
 
 ## Installation
 

docs/source/conf.py

@@ -86,6 +86,10 @@
     "sphinx_gallery.gen_gallery",
 ]
 
+typehints_defaults = "comma"
+typehints_use_signature = True
+simplify_optional_unions = False
+
 # Intersphinx mapping
 intersphinx_mapping = {
     "pyvista": ("https://docs.pyvista.org/", None),

docs/source/index.rst

@@ -153,6 +153,28 @@ It is independent of the Ansys installer.
 
 - `C++ solver reader plugin <https://astonishing-hyacinth-e64.notion.site/How-to-write-a-new-solver-reader-as-a-DPF-s-plugin-bd2d2a3cf51f47ef9e70df45d64f89cb>`_
 
+Documentation and issues
+------------------------
+Documentation for the latest stable release of PyDPF-Core is hosted at `PyDPF-Core documentation
+<https://dpf.docs.pyansys.com/version/stable/>`_.
+
+In the upper right corner of the documentation's title bar, there is an option for switching from
+viewing the documentation for the latest stable release to viewing the documentation for the
+development version or previously released versions.
+
+You can also `view <https://cheatsheets.docs.pyansys.com/pydpf-core_cheat_sheet.png>`_ or
+`download <https://cheatsheets.docs.pyansys.com/pydpf-core_cheat_sheet.pdf>`_ the
+PyDPF-Core cheat sheet. This one-page reference provides syntax rules and commands
+for using PyDPF-Core. 
+
+On the `PyDPF-Core Issues <https://github.com/ansys/pydpf-core/issues>`_ page,
+you can create issues to report bugs and request new features. On the `PyDPF-Core Discussions
+<https://github.com/ansys/pydpf-core/discussions>`_ page or the `Discussions <https://discuss.ansys.com/>`_
+page on the Ansys Developer portal, you can post questions, share ideas, and get community feedback. 
+
+To reach the project support team, email `pyansys.core@ansys.com <pyansys.core@ansys.com>`_.
+
+
 - :ref:`user_guide_custom_operators`
 
 

src/ansys/dpf/core/any.py

@@ -19,7 +19,7 @@ class Any:
 
     Parameters
     ----------
-    any : ctypes.c_void_p, ansys.grpc.dpf.any_pb2.Any message, optional  # noqa: E501
+    any_dpf : ctypes.c_void_p, ansys.grpc.dpf.any_pb2.Any message, optional
     server : DPFServer, optional
         Server with channel connected to the remote or local instance.
         The default is ``None``, in which case an attempt is made to use the

src/ansys/dpf/core/operators/filter/__init__.py

@@ -7,6 +7,7 @@
 from .field_low_pass_fc import field_low_pass_fc 
 from .field_signed_high_pass import field_signed_high_pass 
 from .field_signed_high_pass_fc import field_signed_high_pass_fc 
+from .filtering_max_over_time import filtering_max_over_time 
 from .scoping_band_pass import scoping_band_pass 
 from .scoping_high_pass import scoping_high_pass 
 from .scoping_low_pass import scoping_low_pass 

src/ansys/dpf/core/operators/filter/abc_weightings.py

@@ -22,6 +22,11 @@ class abc_weightings(Operator):
         computed, 1 the b-weigting is
         computed and 2 the c-weightings is
         computed.
+    shape_by_tf_scoping : bool
+        If this pin is set to true, each field of the
+        input fields container is defined by
+        time freq scoping and not by ids.
+        default is false
 
 
     Examples
@@ -36,19 +41,27 @@ class abc_weightings(Operator):
     >>> op.inputs.fields_container.connect(my_fields_container)
     >>> my_weighting_type = int()
     >>> op.inputs.weighting_type.connect(my_weighting_type)
+    >>> my_shape_by_tf_scoping = bool()
+    >>> op.inputs.shape_by_tf_scoping.connect(my_shape_by_tf_scoping)
 
     >>> # Instantiate operator and connect inputs in one line
     >>> op = dpf.operators.filter.abc_weightings(
     ...     fields_container=my_fields_container,
     ...     weighting_type=my_weighting_type,
+    ...     shape_by_tf_scoping=my_shape_by_tf_scoping,
     ... )
 
     >>> # Get output data
     >>> result_weightings = op.outputs.weightings()
     """
 
     def __init__(
-        self, fields_container=None, weighting_type=None, config=None, server=None
+        self,
+        fields_container=None,
+        weighting_type=None,
+        shape_by_tf_scoping=None,
+        config=None,
+        server=None,
     ):
         super().__init__(name="abc_weightings", config=config, server=server)
         self._inputs = InputsAbcWeightings(self)
@@ -57,6 +70,8 @@ def __init__(
             self.inputs.fields_container.connect(fields_container)
         if weighting_type is not None:
             self.inputs.weighting_type.connect(weighting_type)
+        if shape_by_tf_scoping is not None:
+            self.inputs.shape_by_tf_scoping.connect(shape_by_tf_scoping)
 
     @staticmethod
     def _spec():
@@ -81,6 +96,15 @@ def _spec():
         computed and 2 the c-weightings is
         computed.""",
                 ),
+                2: PinSpecification(
+                    name="shape_by_tf_scoping",
+                    type_names=["bool"],
+                    optional=False,
+                    document="""If this pin is set to true, each field of the
+        input fields container is defined by
+        time freq scoping and not by ids.
+        default is false""",
+                ),
             },
             map_output_pin_spec={
                 0: PinSpecification(
@@ -142,6 +166,8 @@ class InputsAbcWeightings(_Inputs):
     >>> op.inputs.fields_container.connect(my_fields_container)
     >>> my_weighting_type = int()
     >>> op.inputs.weighting_type.connect(my_weighting_type)
+    >>> my_shape_by_tf_scoping = bool()
+    >>> op.inputs.shape_by_tf_scoping.connect(my_shape_by_tf_scoping)
     """
 
     def __init__(self, op: Operator):
@@ -150,6 +176,10 @@ def __init__(self, op: Operator):
         self._inputs.append(self._fields_container)
         self._weighting_type = Input(abc_weightings._spec().input_pin(1), 1, op, -1)
         self._inputs.append(self._weighting_type)
+        self._shape_by_tf_scoping = Input(
+            abc_weightings._spec().input_pin(2), 2, op, -1
+        )
+        self._inputs.append(self._shape_by_tf_scoping)
 
     @property
     def fields_container(self):
@@ -194,6 +224,29 @@ def weighting_type(self):
         """
         return self._weighting_type
 
+    @property
+    def shape_by_tf_scoping(self):
+        """Allows to connect shape_by_tf_scoping input to the operator.
+
+        If this pin is set to true, each field of the
+        input fields container is defined by
+        time freq scoping and not by ids.
+        default is false
+
+        Parameters
+        ----------
+        my_shape_by_tf_scoping : bool
+
+        Examples
+        --------
+        >>> from ansys.dpf import core as dpf
+        >>> op = dpf.operators.filter.abc_weightings()
+        >>> op.inputs.shape_by_tf_scoping.connect(my_shape_by_tf_scoping)
+        >>> # or
+        >>> op.inputs.shape_by_tf_scoping(my_shape_by_tf_scoping)
+        """
+        return self._shape_by_tf_scoping
+
 
 class OutputsAbcWeightings(_Outputs):
     """Intermediate class used to get outputs from