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.
- Returns:
model_data (PropertyField) – Data describing the finite element model
center_of_mass (Field) – Center of mass of the body
inertia_relief (Field) – Inertia matrix
model_size (PropertyField)
master_node_coordinates
v_trsf – Translational and rotational shape functions
k_mat (Field)
mass_mat (Field)
c_mat (Field)
rhs (Field)
dn
dr_cross_n
drn
dn_cross_n
dnx_y
dny_y
dnz_y
dyx_n
dyy_n
dyz_n
dnxn
dnyn
dnzn
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:
- property outputs#
Enables to get outputs of the operator by evaluating it
- Returns:
outputs
- Return type:
- 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:
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 isNone
. :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:
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 isNone
.
- 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:
- 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:
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:
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:
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:
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:
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:
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:
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:
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()