compute_invariant_terms_rbd#

Autogenerated DPF operator classes.

class ansys.dpf.core.operators.result.compute_invariant_terms_rbd.compute_invariant_terms_rbd(rom_matrices=None, mode_shapes=None, lumped_mass=None, model_data=None, center_of_mass=None, inertia_relief=None, model_size=None, field_coordinates=None, nod=None, constraint_mode_check=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

  • center_of_mass (FieldsContainer) –

  • inertia_relief (FieldsContainer) – Inertia matrix

  • model_size (float) – Model size

  • field_coordinates (Field) – Coordinates of all nodes

  • nod (default: None) –

  • constraint_mode_check (bool, optional) – If true, the orthogonality of the constraint modes are checked. default is false.

Examples

>>> from ansys.dpf import core as dpf

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

>>> # 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_center_of_mass = dpf.FieldsContainer()
>>> op.inputs.center_of_mass.connect(my_center_of_mass)
>>> my_inertia_relief = dpf.FieldsContainer()
>>> op.inputs.inertia_relief.connect(my_inertia_relief)
>>> my_model_size = float()
>>> op.inputs.model_size.connect(my_model_size)
>>> my_field_coordinates = dpf.Field()
>>> op.inputs.field_coordinates.connect(my_field_coordinates)
>>> my_nod = dpf.()
>>> op.inputs.nod.connect(my_nod)
>>> my_constraint_mode_check = bool()
>>> op.inputs.constraint_mode_check.connect(my_constraint_mode_check)

>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.result.compute_invariant_terms_rbd(
...     rom_matrices=my_rom_matrices,
...     mode_shapes=my_mode_shapes,
...     lumped_mass=my_lumped_mass,
...     model_data=my_model_data,
...     center_of_mass=my_center_of_mass,
...     inertia_relief=my_inertia_relief,
...     model_size=my_model_size,
...     field_coordinates=my_field_coordinates,
...     nod=my_nod,
...     constraint_mode_check=my_constraint_mode_check,
... )

>>> # Get output data
>>> result_model_data = op.outputs.model_data()
>>> result_center_of_mass = op.outputs.center_of_mass()
>>> result_inertia_relief = op.outputs.inertia_relief()
>>> result_model_size = op.outputs.model_size()
>>> result_master_node_coordinates = op.outputs.master_node_coordinates()
>>> result_v_trsf = op.outputs.v_trsf()
>>> result_k_mat = op.outputs.k_mat()
>>> result_mass_mat = op.outputs.mass_mat()
>>> result_c_mat = op.outputs.c_mat()
>>> result_rhs = op.outputs.rhs()
>>> result_dn = op.outputs.dn()
>>> result_dr_cross_n = op.outputs.dr_cross_n()
>>> result_drn = op.outputs.drn()
>>> result_dn_cross_n = op.outputs.dn_cross_n()
>>> result_dnx_y = op.outputs.dnx_y()
>>> result_dny_y = op.outputs.dny_y()
>>> result_dnz_y = op.outputs.dnz_y()
>>> result_dyx_n = op.outputs.dyx_n()
>>> result_dyy_n = op.outputs.dyy_n()
>>> result_dyz_n = op.outputs.dyz_n()
>>> result_dnxn = op.outputs.dnxn()
>>> result_dnyn = op.outputs.dnyn()
>>> result_dnzn = op.outputs.dnzn()
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:

InputsComputeInvariantTermsRbd

property outputs#

Enables to get outputs of the operator by evaluating it

Returns:

outputs

Return type:

OutputsComputeInvariantTermsRbd

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_rbd.InputsComputeInvariantTermsRbd(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to connect user inputs to compute_invariant_terms_rbd operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> 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_center_of_mass = dpf.FieldsContainer()
>>> op.inputs.center_of_mass.connect(my_center_of_mass)
>>> my_inertia_relief = dpf.FieldsContainer()
>>> op.inputs.inertia_relief.connect(my_inertia_relief)
>>> my_model_size = float()
>>> op.inputs.model_size.connect(my_model_size)
>>> my_field_coordinates = dpf.Field()
>>> op.inputs.field_coordinates.connect(my_field_coordinates)
>>> my_nod = dpf.()
>>> op.inputs.nod.connect(my_nod)
>>> my_constraint_mode_check = bool()
>>> op.inputs.constraint_mode_check.connect(my_constraint_mode_check)
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_rbd()
>>> 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_rbd()
>>> 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_rbd()
>>> 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_rbd()
>>> op.inputs.model_data.connect(my_model_data)
>>> # or
>>> op.inputs.model_data(my_model_data)
property center_of_mass#

Allows to connect center_of_mass input to the operator.

Parameters:

my_center_of_mass (FieldsContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> op.inputs.center_of_mass.connect(my_center_of_mass)
>>> # or
>>> op.inputs.center_of_mass(my_center_of_mass)
property inertia_relief#

Allows to connect inertia_relief input to the operator.

Inertia matrix

Parameters:

my_inertia_relief (FieldsContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> op.inputs.inertia_relief.connect(my_inertia_relief)
>>> # or
>>> op.inputs.inertia_relief(my_inertia_relief)
property model_size#

Allows to connect model_size input to the operator.

Model size

Parameters:

my_model_size (float) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> op.inputs.model_size.connect(my_model_size)
>>> # or
>>> op.inputs.model_size(my_model_size)
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_rbd()
>>> 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_rbd()
>>> op.inputs.nod.connect(my_nod)
>>> # or
>>> op.inputs.nod(my_nod)
property constraint_mode_check#

Allows to connect constraint_mode_check input to the operator.

If true, the orthogonality of the constraint modes are checked. default is false.

Parameters:

my_constraint_mode_check (bool) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> op.inputs.constraint_mode_check.connect(my_constraint_mode_check)
>>> # or
>>> op.inputs.constraint_mode_check(my_constraint_mode_check)
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_rbd.OutputsComputeInvariantTermsRbd(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to get outputs from compute_invariant_terms_rbd operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_model_data = op.outputs.model_data()
>>> result_center_of_mass = op.outputs.center_of_mass()
>>> result_inertia_relief = op.outputs.inertia_relief()
>>> result_model_size = op.outputs.model_size()
>>> result_master_node_coordinates = op.outputs.master_node_coordinates()
>>> result_v_trsf = op.outputs.v_trsf()
>>> result_k_mat = op.outputs.k_mat()
>>> result_mass_mat = op.outputs.mass_mat()
>>> result_c_mat = op.outputs.c_mat()
>>> result_rhs = op.outputs.rhs()
>>> result_dn = op.outputs.dn()
>>> result_dr_cross_n = op.outputs.dr_cross_n()
>>> result_drn = op.outputs.drn()
>>> result_dn_cross_n = op.outputs.dn_cross_n()
>>> result_dnx_y = op.outputs.dnx_y()
>>> result_dny_y = op.outputs.dny_y()
>>> result_dnz_y = op.outputs.dnz_y()
>>> result_dyx_n = op.outputs.dyx_n()
>>> result_dyy_n = op.outputs.dyy_n()
>>> result_dyz_n = op.outputs.dyz_n()
>>> result_dnxn = op.outputs.dnxn()
>>> result_dnyn = op.outputs.dnyn()
>>> result_dnzn = op.outputs.dnzn()
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_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_model_data = op.outputs.model_data()
property center_of_mass#

Allows to get center_of_mass output of the operator

Returns:

my_center_of_mass

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_center_of_mass = op.outputs.center_of_mass()
property inertia_relief#

Allows to get inertia_relief output of the operator

Returns:

my_inertia_relief

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_inertia_relief = op.outputs.inertia_relief()
property model_size#

Allows to get model_size output of the operator

Returns:

my_model_size

Return type:

PropertyField

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_model_size = op.outputs.model_size()
property master_node_coordinates#

Allows to get master_node_coordinates output of the operator

Return type:

my_master_node_coordinates

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_master_node_coordinates = op.outputs.master_node_coordinates()
property v_trsf#

Allows to get v_trsf output of the operator

Return type:

my_v_trsf

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_v_trsf = op.outputs.v_trsf()
property k_mat#

Allows to get k_mat output of the operator

Returns:

my_k_mat

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_k_mat = op.outputs.k_mat()
property mass_mat#

Allows to get mass_mat output of the operator

Returns:

my_mass_mat

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_mass_mat = op.outputs.mass_mat()
property c_mat#

Allows to get c_mat output of the operator

Returns:

my_c_mat

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_c_mat = op.outputs.c_mat()
property rhs#

Allows to get rhs output of the operator

Returns:

my_rhs

Return type:

Field

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_rhs = op.outputs.rhs()
property dn#

Allows to get dn output of the operator

Return type:

my_dn

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dn = op.outputs.dn()
property dr_cross_n#

Allows to get dr_cross_n output of the operator

Return type:

my_dr_cross_n

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dr_cross_n = op.outputs.dr_cross_n()
property drn#

Allows to get drn output of the operator

Return type:

my_drn

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_drn = op.outputs.drn()
property dn_cross_n#

Allows to get dn_cross_n output of the operator

Return type:

my_dn_cross_n

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dn_cross_n = op.outputs.dn_cross_n()
property dnx_y#

Allows to get dnx_y output of the operator

Return type:

my_dnx_y

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dnx_y = op.outputs.dnx_y()
property dny_y#

Allows to get dny_y output of the operator

Return type:

my_dny_y

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dny_y = op.outputs.dny_y()
property dnz_y#

Allows to get dnz_y output of the operator

Return type:

my_dnz_y

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dnz_y = op.outputs.dnz_y()
property dyx_n#

Allows to get dyx_n output of the operator

Return type:

my_dyx_n

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dyx_n = op.outputs.dyx_n()
property dyy_n#

Allows to get dyy_n output of the operator

Return type:

my_dyy_n

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dyy_n = op.outputs.dyy_n()
property dyz_n#

Allows to get dyz_n output of the operator

Return type:

my_dyz_n

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dyz_n = op.outputs.dyz_n()
property dnxn#

Allows to get dnxn output of the operator

Return type:

my_dnxn

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dnxn = op.outputs.dnxn()
property dnyn#

Allows to get dnyn output of the operator

Return type:

my_dnyn

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dnyn = op.outputs.dnyn()
property dnzn#

Allows to get dnzn output of the operator

Return type:

my_dnzn

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_invariant_terms_rbd()
>>> # Connect inputs : op.inputs. ...
>>> result_dnzn = op.outputs.dnzn()