update generated code

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

@@ -222,6 +222,7 @@
 from .run import run 
 from .smisc import smisc 
 from .specific_heat import specific_heat 
+from .spectrum_data import spectrum_data 
 from .static_pressure import static_pressure 
 from .stiffness_matrix_energy import stiffness_matrix_energy 
 from .strain_eqv_as_mechanical import strain_eqv_as_mechanical 

src/ansys/dpf/core/operators/result/spectrum_data.py

@@ -0,0 +1,184 @@
+"""
+spectrum_data
+=============
+Autogenerated DPF operator classes.
+"""
+from warnings import warn
+from ansys.dpf.core.dpf_operator import Operator
+from ansys.dpf.core.inputs import Input, _Inputs
+from ansys.dpf.core.outputs import Output, _Outputs
+from ansys.dpf.core.operators.specification import PinSpecification, Specification
+
+
+class spectrum_data(Operator):
+    """Read participation factors from mode file.
+
+    Parameters
+    ----------
+    data_sources : DataSources
+        Data_sources (must contain at least one mode
+        file).
+
+
+    Examples
+    --------
+    >>> from ansys.dpf import core as dpf
+
+    >>> # Instantiate operator
+    >>> op = dpf.operators.result.spectrum_data()
+
+    >>> # Make input connections
+    >>> my_data_sources = dpf.DataSources()
+    >>> op.inputs.data_sources.connect(my_data_sources)
+
+    >>> # Instantiate operator and connect inputs in one line
+    >>> op = dpf.operators.result.spectrum_data(
+    ...     data_sources=my_data_sources,
+    ... )
+
+    >>> # Get output data
+    >>> result_participation_factors = op.outputs.participation_factors()
+    """
+
+    def __init__(self, data_sources=None, config=None, server=None):
+        super().__init__(name="spectrum_data", config=config, server=server)
+        self._inputs = InputsSpectrumData(self)
+        self._outputs = OutputsSpectrumData(self)
+        if data_sources is not None:
+            self.inputs.data_sources.connect(data_sources)
+
+    @staticmethod
+    def _spec():
+        description = """Read participation factors from mode file."""
+        spec = Specification(
+            description=description,
+            map_input_pin_spec={
+                4: PinSpecification(
+                    name="data_sources",
+                    type_names=["data_sources"],
+                    optional=False,
+                    document="""Data_sources (must contain at least one mode
+        file).""",
+                ),
+            },
+            map_output_pin_spec={
+                0: PinSpecification(
+                    name="participation_factors",
+                    type_names=["fields_container"],
+                    optional=False,
+                    document="""Fields container containing participation
+        factors.""",
+                ),
+            },
+        )
+        return spec
+
+    @staticmethod
+    def default_config(server=None):
+        """Returns the default config of the operator.
+
+        This config can then be changed to the user needs and be used to
+        instantiate the operator. The Configuration allows to customize
+        how the operation will be processed by the operator.
+
+        Parameters
+        ----------
+        server : server.DPFServer, optional
+            Server with channel connected to the remote or local instance. When
+            ``None``, attempts to use the global server.
+        """
+        return Operator.default_config(name="spectrum_data", server=server)
+
+    @property
+    def inputs(self):
+        """Enables to connect inputs to the operator
+
+        Returns
+        --------
+        inputs : InputsSpectrumData
+        """
+        return super().inputs
+
+    @property
+    def outputs(self):
+        """Enables to get outputs of the operator by evaluating it
+
+        Returns
+        --------
+        outputs : OutputsSpectrumData
+        """
+        return super().outputs
+
+
+class InputsSpectrumData(_Inputs):
+    """Intermediate class used to connect user inputs to
+    spectrum_data operator.
+
+    Examples
+    --------
+    >>> from ansys.dpf import core as dpf
+    >>> op = dpf.operators.result.spectrum_data()
+    >>> my_data_sources = dpf.DataSources()
+    >>> op.inputs.data_sources.connect(my_data_sources)
+    """
+
+    def __init__(self, op: Operator):
+        super().__init__(spectrum_data._spec().inputs, op)
+        self._data_sources = Input(spectrum_data._spec().input_pin(4), 4, op, -1)
+        self._inputs.append(self._data_sources)
+
+    @property
+    def data_sources(self):
+        """Allows to connect data_sources input to the operator.
+
+        Data_sources (must contain at least one mode
+        file).
+
+        Parameters
+        ----------
+        my_data_sources : DataSources
+
+        Examples
+        --------
+        >>> from ansys.dpf import core as dpf
+        >>> op = dpf.operators.result.spectrum_data()
+        >>> op.inputs.data_sources.connect(my_data_sources)
+        >>> # or
+        >>> op.inputs.data_sources(my_data_sources)
+        """
+        return self._data_sources
+
+
+class OutputsSpectrumData(_Outputs):
+    """Intermediate class used to get outputs from
+    spectrum_data operator.
+
+    Examples
+    --------
+    >>> from ansys.dpf import core as dpf
+    >>> op = dpf.operators.result.spectrum_data()
+    >>> # Connect inputs : op.inputs. ...
+    >>> result_participation_factors = op.outputs.participation_factors()
+    """
+
+    def __init__(self, op: Operator):
+        super().__init__(spectrum_data._spec().outputs, op)
+        self._participation_factors = Output(spectrum_data._spec().output_pin(0), 0, op)
+        self._outputs.append(self._participation_factors)
+
+    @property
+    def participation_factors(self):
+        """Allows to get participation_factors output of the operator
+
+        Returns
+        ----------
+        my_participation_factors : FieldsContainer
+
+        Examples
+        --------
+        >>> from ansys.dpf import core as dpf
+        >>> op = dpf.operators.result.spectrum_data()
+        >>> # Connect inputs : op.inputs. ...
+        >>> result_participation_factors = op.outputs.participation_factors()
+        """  # noqa: E501
+        return self._participation_factors