extract_scoping#
- class ansys.dpf.core.operators.utility.extract_scoping.extract_scoping(field_or_fields_container=None, requested_location=None, config=None, server=None)#
Bases:
ansys.dpf.core.dpf_operator.OperatorTakes a field type object, mesh or a collection of them and extracts its scoping or scopings container.
Inputs#
- field_or_fields_container: Field or FieldsContainer or PropertyField or
PropertyFieldsContainer or CustomTypeField or CustomTypeFieldsContainer or StringField or Scoping or ScopingsContainer or MeshedRegion or MeshesContainer, optional
- requested_location: int, optional
If input 0 is a mesh or a meshes_container, the operator returns the nodes scoping, possible locations are: Nodal(default) or Elemental
Outputs#
mesh_scoping: Scoping or ScopingsContainer
Examples
>>> from ansys.dpf import core as dpf
>>> # Instantiate operator >>> op = dpf.operators.utility.extract_scoping()
>>> # Make input connections >>> my_field_or_fields_container = dpf.Field() >>> op.inputs.field_or_fields_container.connect(my_field_or_fields_container) >>> my_requested_location = int() >>> op.inputs.requested_location.connect(my_requested_location)
>>> # Instantiate operator and connect inputs in one line >>> op = dpf.operators.utility.extract_scoping( ... field_or_fields_container=my_field_or_fields_container, ... requested_location=my_requested_location, ... )
>>> # Get output data >>> result_mesh_scoping = op.outputs.mesh_scoping()
Overview#
Connect an input on the operator using a pin number. |
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Connect an operator as an input on a pin. |
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Retrieve the output of the operator on the pin number. |
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Evaluate this operator. |
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Evaluate this operator. |
Enables to connect inputs to the operator |
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Enables to get outputs of the operator by evaluating it |
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Enable or disable progress bar display when requesting the operator’s output. |
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Copy of the operator’s current configuration. |
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Retrieve the unique identifier of the operator. |
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Returns the Specification (or documentation) of this Operator. |
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Return the changelog of this operator. |
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Return the current version of the operator. |
Returns the default config of the operator. |
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Documents an Operator with its description (what the Operator does),its inputs and outputs and some properties. |
Delete this instance. |
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Describe the entity. |
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Add two fields or two fields containers. |
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Subtract two fields or two fields containers. |
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Raise each element of a field or a fields container to power 2. |
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Multiply two fields or two fields containers. |
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Perform division with another operator or a scalar. |
Import detail#
from ansys.dpf.core.operators.utility.extract_scoping import extract_scoping
Property detail#
- property extract_scoping.inputs: InputsExtractScoping#
Enables to connect inputs to the operator
- Returns:
An instance of InputsExtractScoping.
- Return type:
inputs
- property extract_scoping.outputs: OutputsExtractScoping#
Enables to get outputs of the operator by evaluating it
- Returns:
An instance of OutputsExtractScoping.
- Return type:
outputs
- property extract_scoping.progress_bar: bool#
Enable or disable progress bar display when requesting the operator’s output.
With this property, the user can choose to print a progress bar when the operator’s output is requested, default is False
- property extract_scoping.config#
Copy of the operator’s current configuration.
You can modify the copy of the configuration and then use
operator.config = new_configor 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
- property extract_scoping.id: int#
Retrieve the unique identifier of the operator.
This property returns the unique ID associated with the operator. This property is lazily initialized.
- Returns:
The unique identifier of the operator.
- Return type:
int
Notes
Property available with server’s version starting at 10.0.
- property extract_scoping.specification#
Returns the Specification (or documentation) of this Operator.
- Return type:
- property extract_scoping.changelog: ansys.dpf.core.changelog.Changelog#
Return the changelog of this operator.
Requires DPF 11.0 (2026 R1) or above.
- Returns:
Changelog of the operator.
- Return type:
changelog
- property extract_scoping.version: packaging.version.Version#
Return the current version of the operator.
Requires DPF 11.0 (2026 R1) or above.
Attribute detail#
- extract_scoping.name = None#
Method detail#
- static extract_scoping.default_config(server: ansys.dpf.core.server_types.AnyServerType = None) ansys.dpf.core.config.Config#
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 with channel connected to the remote or local instance. When
None, attempts to use the global server.- Returns:
A new Config instance equivalent to the default config for this operator.
- Return type:
config
- extract_scoping.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 ]]...
- extract_scoping.connect_operator_as_input(pin, op)#
Connect an operator as an input on a pin.
- Parameters:
pin (int) – Number of the output pin. The default is
0.op (
ansys.dpf.core.dpf_operator.Operator) – Requested type of the output. The default isNone.
- extract_scoping.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
- extract_scoping.__del__()#
Delete this instance.
- extract_scoping.__str__()#
Describe the entity.
- Returns:
Description of the entity.
- Return type:
str
- extract_scoping.run()#
Evaluate this operator.
- extract_scoping.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
evalmethod.>>> 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()
- extract_scoping.__add__(fields_b)#
Add two fields or two fields containers.
- Returns:
add
- Return type:
operators.math.add_fc
- extract_scoping.__sub__(fields_b)#
Subtract two fields or two fields containers.
- Returns:
minus
- Return type:
operators.math.minus_fc
- extract_scoping.__pow__(value)#
Raise each element of a field or a fields container to power 2.
- extract_scoping.__mul__(value)#
Multiply two fields or two fields containers.
- Returns:
mul
- Return type:
operators.math.generalized_inner_product_fc
- static extract_scoping.operator_specification(op_name, server=None)#
Documents an Operator with its description (what the Operator does),its inputs and outputs and some properties.
- extract_scoping.__truediv__(inpt)#
Perform division with another operator or a scalar.
This method allows the use of the division operator (/) between an Operator instance and either another Operator or a scalar value (float).