on_property

class ansys.dpf.core.operators.scoping.on_property.on_property(requested_location=None, property_name=None, property_id=None, streams_container=None, data_sources=None, inclusive=None, config=None, server=None)

Provides a scoping at a given location based on a given property name and a property number.

available inputs:
  • requested_location (str)

  • property_name (str)

  • property_id (int)

  • streams_container (StreamsContainer) (optional)

  • data_sources (DataSources)

  • inclusive (int) (optional)

available outputs:
  • mesh_scoping (Scoping)

Examples

>>> from ansys.dpf import core as dpf
>>> # Instantiate operator
>>> op = dpf.operators.scoping.on_property()
>>> # Make input connections
>>> my_requested_location = str()
>>> op.inputs.requested_location.connect(my_requested_location)
>>> my_property_name = str()
>>> op.inputs.property_name.connect(my_property_name)
>>> my_property_id = int()
>>> op.inputs.property_id.connect(my_property_id)
>>> my_streams_container = dpf.StreamsContainer()
>>> op.inputs.streams_container.connect(my_streams_container)
>>> my_data_sources = dpf.DataSources()
>>> op.inputs.data_sources.connect(my_data_sources)
>>> my_inclusive = int()
>>> op.inputs.inclusive.connect(my_inclusive)
>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.scoping.on_property(requested_location=my_requested_location,property_name=my_property_name,property_id=my_property_id,streams_container=my_streams_container,data_sources=my_data_sources,inclusive=my_inclusive)
>>> # Get output data
>>> result_mesh_scoping = op.outputs.mesh_scoping()
static default_config()

Returns the default config for a given operator. This config can then be changed to the user needs and be used to instantiate the given operator

Parameters
  • name (str) – Name of the operator. For example ‘U’.

  • server (server.DPFServer, optional) – Server with channel connected to the remote or local instance. When None, attempts to use the the global server.

property inputs

Enables to connect inputs to the operator

Returns

inputs

Return type

InputsOnProperty

property outputs

Enables to get outputs of the operator by evaluationg it

Returns

outputs

Return type

OutputsOnProperty

property config

Returns a copy of the current config of the operator. To use the config that you modify, please use operator.config = new_config or create an operator with the new config as a parameter.

Returns

config

Return type

Config

connect(pin, inpt, pin_out=0)

Connect an input on the operator using a pin number.

Parameters

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.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
array([[0.59428386, 0.00201751, 0.0006032 ]])
get_output(pin=0, output_type=None)

Returns the output of the operator on the pin number.

Parameters
  • pin (int, optional) – Number of the output pin.

  • output_type (core.type enum, optional) – The requested type of the output.

run()

Evaluate this operator

class ansys.dpf.core.operators.scoping.on_property.InputsOnProperty(op: ansys.dpf.core.dpf_operator.Operator)

Intermediate class used to connect user inputs to on_property operator

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.scoping.on_property()
>>> my_requested_location = str()
>>> op.inputs.requested_location.connect(my_requested_location)
>>> my_property_name = str()
>>> op.inputs.property_name.connect(my_property_name)
>>> my_property_id = int()
>>> op.inputs.property_id.connect(my_property_id)
>>> my_streams_container = dpf.StreamsContainer()
>>> op.inputs.streams_container.connect(my_streams_container)
>>> my_data_sources = dpf.DataSources()
>>> op.inputs.data_sources.connect(my_data_sources)
>>> my_inclusive = int()
>>> op.inputs.inclusive.connect(my_inclusive)
property requested_location

Allows to connect requested_location input to the operator

  • pindoc: Nodal or Elemental location are expected

Parameters

my_requested_location (str,) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.scoping.on_property()
>>> op.inputs.requested_location.connect(my_requested_location)
>>> #or
>>> op.inputs.requested_location(my_requested_location)
property property_name

Allows to connect property_name input to the operator

  • pindoc: ex “mapdl_element_type”, “apdl_type_index”, “mapdl_type_id”, “material”, “apdl_section_id”, “apdl_real_id”, “shell_axi”, “volume_axi”…

Parameters

my_property_name (str,) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.scoping.on_property()
>>> op.inputs.property_name.connect(my_property_name)
>>> #or
>>> op.inputs.property_name(my_property_name)
property property_id

Allows to connect property_id input to the operator

Parameters

my_property_id (int,) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.scoping.on_property()
>>> op.inputs.property_id.connect(my_property_id)
>>> #or
>>> op.inputs.property_id(my_property_id)
property streams_container

Allows to connect streams_container input to the operator

Parameters

my_streams_container (StreamsContainer,) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.scoping.on_property()
>>> op.inputs.streams_container.connect(my_streams_container)
>>> #or
>>> op.inputs.streams_container(my_streams_container)
property data_sources

Allows to connect data_sources input to the operator

Parameters

my_data_sources (DataSources,) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.scoping.on_property()
>>> op.inputs.data_sources.connect(my_data_sources)
>>> #or
>>> op.inputs.data_sources(my_data_sources)
property inclusive

Allows to connect inclusive input to the operator

  • pindoc: If element scoping is requested on a nodal named selection, if inclusive == 1 then all the elements adjacent to the nodes ids in input are added, if inclusive == 0, only the elements which have all their nodes in the scoping are included

Parameters

my_inclusive (int,) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.scoping.on_property()
>>> op.inputs.inclusive.connect(my_inclusive)
>>> #or
>>> op.inputs.inclusive(my_inclusive)
connect(inpt)

Allows you to connect any input (an entity or an operator output) to any input pin of this operator.

The matching input type corresponding to the output is looked for.

Parameters

inpt (str, int, double, Field, FieldsContainer, Scoping, DataSources, MeshedRegion, ScopingsContainer, CyclicSupport, ..., Output, Outputs, Operator) – input of the operator

class ansys.dpf.core.operators.scoping.on_property.OutputsOnProperty(op: ansys.dpf.core.dpf_operator.Operator)

Intermediate class used to get outputs from on_property operator .. rubric:: Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.scoping.on_property()
>>> # Connect inputs : op.inputs. ...
>>> result_mesh_scoping = op.outputs.mesh_scoping()
property mesh_scoping

Allows to get mesh_scoping output of the operator

  • pindoc: Scoping

Returns

my_mesh_scoping

Return type

Scoping,

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.scoping.on_property()
>>> # Connect inputs : op.inputs. ...
>>> result_mesh_scoping = op.outputs.mesh_scoping()