compute_invariant_terms_motion#

Autogenerated DPF operator classes.

class ansys.dpf.core.operators.result.compute_invariant_terms_motion.compute_invariant_terms_motion(rom_matrices=None, mode_shapes=None, lumped_mass=None, model_data=None, field_coordinates=None, nod=None, config=None, server=None)#

Set the required data for the invariant terms computation (reduced matrices, lumped mass matrix, modes …)

Parameters:

  • rom_matrices (FieldsContainer) – Fieldscontainers containing the reduced matrices

  • mode_shapes (FieldsContainer) – Fieldscontainers containing the mode shapes, which are cst and nor for the cms method

  • lumped_mass (FieldsContainer) – Fieldscontainers containing the lumped mass

  • model_data (FieldsContainer) – Data describing the finite element model

  • field_coordinates (Field) – Coordinates of all nodes

  • nod (default: None) –

Examples

>>> from ansys.dpf import core as dpf

>>> # Instantiate operator
>>> op = dpf.operators.result.compute_invariant_terms_motion()

>>> # Make input connections
>>> my_rom_matrices = dpf.FieldsContainer()
>>> op.inputs.rom_matrices.connect(my_rom_matrices)
>>> my_mode_shapes = dpf.FieldsContainer()
>>> op.inputs.mode_shapes.connect(my_mode_shapes)
>>> my_lumped_mass = dpf.FieldsContainer()
>>> op.inputs.lumped_mass.connect(my_lumped_mass)
>>> my_model_data = dpf.FieldsContainer()
>>> op.inputs.model_data.connect(my_model_data)
>>> my_field_coordinates = dpf.Field()
>>> op.inputs.field_coordinates.connect(my_field_coordinates)
>>> my_nod = dpf.()
>>> op.inputs.nod.connect(my_nod)

>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.result.compute_invariant_terms_motion(
...     rom_matrices=my_rom_matrices,
...     mode_shapes=my_mode_shapes,
...     lumped_mass=my_lumped_mass,
...     model_data=my_model_data,
...     field_coordinates=my_field_coordinates,
...     nod=my_nod,
... )

>>> # Get output data
>>> result_model_data = op.outputs.model_data()
>>> result_mode_shapes = op.outputs.mode_shapes()
>>> result_lumped_mass = op.outputs.lumped_mass()
>>> result_field_coordinates_and_euler_angles = op.outputs.field_coordinates_and_euler_angles()
>>> result_nod = op.outputs.nod()
>>> result_used_node_index = op.outputs.used_node_index()
>>> result_eigenvalue = op.outputs.eigenvalue()
>>> result_translational_mode_shape = op.outputs.translational_mode_shape()
>>> result_rotational_mode_shape = op.outputs.rotational_mode_shape()
>>> result_invrt_1 = op.outputs.invrt_1()
>>> result_invrt_2 = op.outputs.invrt_2()
>>> result_invrt_3 = op.outputs.invrt_3()
>>> result_invrt_4 = op.outputs.invrt_4()
>>> result_invrt_5 = op.outputs.invrt_5()
>>> result_invrt_6 = op.outputs.invrt_6()
>>> result_invrt_7 = op.outputs.invrt_7()
>>> result_invrt_8 = op.outputs.invrt_8()
static 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.

property inputs#

Enables to connect inputs to the operator

Returns:

inputs

Return type:

InputsComputeInvariantTermsMotion

property outputs#

Enables to get outputs of the operator by evaluating it

Returns:

outputs

Return type:

OutputsComputeInvariantTermsMotion

property config#

Copy of the operator’s current configuration.

You can modify the copy of the configuration and then use operator.config = new_config or instantiate an operator with the new configuration as a parameter.

For information on an operator’s options, see the documentation for that operator.

Returns:

Copy of the operator’s current configuration.

Return type:

ansys.dpf.core.config.Config

Examples

Modify the copy of an operator’s configuration and set it as current config of the operator.

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.add()
>>> config_add = op.config
>>> config_add.set_work_by_index_option(True)
>>> op.config = config_add
connect(pin, inpt, pin_out=0)#

Connect an input on the operator using a pin number.

Parameters:

  • pin (int) – Number of the input pin.

  • inpt (str, int, double, bool, list[int], list[float], Field, FieldsContainer, Scoping,) –

  • ScopingsContainer – Operator, os.PathLike Object to connect to.

  • MeshedRegion – Operator, os.PathLike Object to connect to.

  • MeshesContainer – Operator, os.PathLike Object to connect to.

  • DataSources – Operator, os.PathLike Object to connect to.

  • CyclicSupport – Operator, os.PathLike Object to connect to.

  • dict – Operator, os.PathLike Object to connect to.

  • Outputs – Operator, os.PathLike Object to connect to.

  • pin_out (int, optional) – If the input is an operator, the output pin of the input operator. The default is 0.

Examples

Compute the minimum of displacement by chaining the "U" and "min_max_fc" operators.

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> data_src = dpf.DataSources(examples.find_multishells_rst())
>>> disp_op = dpf.operators.result.displacement()
>>> disp_op.inputs.data_sources(data_src)
>>> max_fc_op = dpf.operators.min_max.min_max_fc()
>>> max_fc_op.inputs.connect(disp_op.outputs)
>>> max_field = max_fc_op.outputs.field_max()
>>> max_field.data
DPFArray([[0.59428386, 0.00201751, 0.0006032 ]]...
connect_operator_as_input(pin, op)#

Connects an operator as an input on a pin. :type pin: :param pin: Number of the output pin. The default is 0. :type pin: int :type op: :param op: Requested type of the output. The default is None. :type op: ansys.dpf.core.dpf_operator.Operator

eval(pin=None)#

Evaluate this operator.

Parameters:

pin (int) – Number of the output pin. The default is None.

Returns:

output – Returns the first output of the operator by default and the output of a given pin when specified. Or, it only evaluates the operator without output.

Return type:

FieldsContainer, Field, MeshedRegion, Scoping

Examples

Use the eval method.

>>> from ansys.dpf import core as dpf
>>> import ansys.dpf.core.operators.math as math
>>> from ansys.dpf.core import examples
>>> data_src = dpf.DataSources(examples.find_multishells_rst())
>>> disp_op = dpf.operators.result.displacement()
>>> disp_op.inputs.data_sources(data_src)
>>> normfc = math.norm_fc(disp_op).eval()
get_output(pin=0, output_type=None)#

Retrieve the output of the operator on the pin number.

To activate the progress bar for server version higher or equal to 3.0, use my_op.progress_bar=True

Parameters:

  • pin (int, optional) – Number of the output pin. The default is 0.

  • output_type (ansys.dpf.core.common.types, type, optional) – Requested type of the output. The default is None.

Returns:

Output of the operator.

Return type:

type

static operator_specification(op_name, server=None)#

Documents an Operator with its description (what the Operator does), its inputs and outputs and some properties

property progress_bar: bool#

With this property, the user can choose to print a progress bar when the operator’s output is requested, default is False

run()#

Evaluate this operator.

property specification#

Returns the Specification (or documentation) of this Operator

Return type:

Specification

class ansys.dpf.core.operators.result.compute_invariant_terms_motion.InputsComputeInvariantTermsMotion(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to connect user inputs to compute_invariant_terms_motion operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> my_rom_matrices = dpf.FieldsContainer()
>>> op.inputs.rom_matrices.connect(my_rom_matrices)
>>> my_mode_shapes = dpf.FieldsContainer()
>>> op.inputs.mode_shapes.connect(my_mode_shapes)
>>> my_lumped_mass = dpf.FieldsContainer()
>>> op.inputs.lumped_mass.connect(my_lumped_mass)
>>> my_model_data = dpf.FieldsContainer()
>>> op.inputs.model_data.connect(my_model_data)
>>> my_field_coordinates = dpf.Field()
>>> op.inputs.field_coordinates.connect(my_field_coordinates)
>>> my_nod = dpf.()
>>> op.inputs.nod.connect(my_nod)
property rom_matrices#

Allows to connect rom_matrices input to the operator.

Fieldscontainers containing the reduced matrices

Parameters:

my_rom_matrices (FieldsContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> op.inputs.rom_matrices.connect(my_rom_matrices)
>>> # or
>>> op.inputs.rom_matrices(my_rom_matrices)
property mode_shapes#

Allows to connect mode_shapes input to the operator.

Fieldscontainers containing the mode shapes, which are cst and nor for the cms method

Parameters:

my_mode_shapes (FieldsContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> op.inputs.mode_shapes.connect(my_mode_shapes)
>>> # or
>>> op.inputs.mode_shapes(my_mode_shapes)
property lumped_mass#

Allows to connect lumped_mass input to the operator.

Fieldscontainers containing the lumped mass

Parameters:

my_lumped_mass (FieldsContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> op.inputs.lumped_mass.connect(my_lumped_mass)
>>> # or
>>> op.inputs.lumped_mass(my_lumped_mass)
property model_data#

Allows to connect model_data input to the operator.

Data describing the finite element model

Parameters:

my_model_data (FieldsContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> op.inputs.model_data.connect(my_model_data)
>>> # or
>>> op.inputs.model_data(my_model_data)
property field_coordinates#

Allows to connect field_coordinates input to the operator.

Coordinates of all nodes

Parameters:

my_field_coordinates (Field) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> op.inputs.field_coordinates.connect(my_field_coordinates)
>>> # or
>>> op.inputs.field_coordinates(my_field_coordinates)
property nod#

Allows to connect nod input to the operator.

Parameters:

my_nod –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> op.inputs.nod.connect(my_nod)
>>> # or
>>> op.inputs.nod(my_nod)
connect(inpt)#

Connect any input (an entity or an operator output) to any input pin of this operator. Searches for the input type corresponding to the output.

Parameters:

  • inpt (str, int, double, bool, list[int], list[float], Field, FieldsContainer, Scoping,) –

  • ScopingsContainer (E501) – Input of the operator.

  • MeshedRegion (E501) – Input of the operator.

  • MeshesContainer (E501) – Input of the operator.

  • DataSources (E501) – Input of the operator.

  • CyclicSupport (E501) – Input of the operator.

  • Outputs (E501) – Input of the operator.

  • noqa (os.PathLike #) – Input of the operator.

class ansys.dpf.core.operators.result.compute_invariant_terms_motion.OutputsComputeInvariantTermsMotion(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to get outputs from compute_invariant_terms_motion operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_model_data = op.outputs.model_data()
>>> result_mode_shapes = op.outputs.mode_shapes()
>>> result_lumped_mass = op.outputs.lumped_mass()
>>> result_field_coordinates_and_euler_angles = op.outputs.field_coordinates_and_euler_angles()
>>> result_nod = op.outputs.nod()
>>> result_used_node_index = op.outputs.used_node_index()
>>> result_eigenvalue = op.outputs.eigenvalue()
>>> result_translational_mode_shape = op.outputs.translational_mode_shape()
>>> result_rotational_mode_shape = op.outputs.rotational_mode_shape()
>>> result_invrt_1 = op.outputs.invrt_1()
>>> result_invrt_2 = op.outputs.invrt_2()
>>> result_invrt_3 = op.outputs.invrt_3()
>>> result_invrt_4 = op.outputs.invrt_4()
>>> result_invrt_5 = op.outputs.invrt_5()
>>> result_invrt_6 = op.outputs.invrt_6()
>>> result_invrt_7 = op.outputs.invrt_7()
>>> result_invrt_8 = op.outputs.invrt_8()
property model_data#

Allows to get model_data output of the operator

Returns:

my_model_data

Return type:

PropertyField

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_model_data = op.outputs.model_data()
property mode_shapes#

Allows to get mode_shapes output of the operator

Returns:

my_mode_shapes

Return type:

FieldsContainer

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_mode_shapes = op.outputs.mode_shapes()
property lumped_mass#

Allows to get lumped_mass output of the operator

Returns:

my_lumped_mass

Return type:

FieldsContainer

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_lumped_mass = op.outputs.lumped_mass()
property field_coordinates_and_euler_angles#

Allows to get field_coordinates_and_euler_angles output of the operator

Returns:

my_field_coordinates_and_euler_angles

Return type:

FieldsContainer

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_field_coordinates_and_euler_angles = op.outputs.field_coordinates_and_euler_angles()
property nod#

Allows to get nod output of the operator

Return type:

my_nod

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_nod = op.outputs.nod()
property used_node_index#

Allows to get used_node_index output of the operator

Return type:

my_used_node_index

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_used_node_index = op.outputs.used_node_index()
property eigenvalue#

Allows to get eigenvalue output of the operator

Return type:

my_eigenvalue

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_eigenvalue = op.outputs.eigenvalue()
property translational_mode_shape#

Allows to get translational_mode_shape output of the operator

Return type:

my_translational_mode_shape

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_translational_mode_shape = op.outputs.translational_mode_shape()
property rotational_mode_shape#

Allows to get rotational_mode_shape output of the operator

Return type:

my_rotational_mode_shape

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_rotational_mode_shape = op.outputs.rotational_mode_shape()
property invrt_1#

Allows to get invrt_1 output of the operator

Returns:

my_invrt_1

Return type:

float

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_invrt_1 = op.outputs.invrt_1()
property invrt_2#

Allows to get invrt_2 output of the operator

Return type:

my_invrt_2

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_invrt_2 = op.outputs.invrt_2()
property invrt_3#

Allows to get invrt_3 output of the operator

Return type:

my_invrt_3

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_invrt_3 = op.outputs.invrt_3()
property invrt_4#

Allows to get invrt_4 output of the operator

Return type:

my_invrt_4

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_invrt_4 = op.outputs.invrt_4()
property invrt_5#

Allows to get invrt_5 output of the operator

Return type:

my_invrt_5

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_invrt_5 = op.outputs.invrt_5()
property invrt_6#

Allows to get invrt_6 output of the operator

Return type:

my_invrt_6

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_invrt_6 = op.outputs.invrt_6()
property invrt_7#

Allows to get invrt_7 output of the operator

Return type:

my_invrt_7

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_invrt_7 = op.outputs.invrt_7()
property invrt_8#

Allows to get invrt_8 output of the operator

Return type:

my_invrt_8

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_motion()
>>> # Connect inputs : op.inputs. ...
>>> result_invrt_8 = op.outputs.invrt_8()