omega#

Autogenerated DPF operator classes.

class ansys.dpf.core.operators.result.omega.omega(time_scoping=None, mesh_scoping=None, streams_container=None, data_sources=None, mesh=None, region_scoping=None, qualifiers1=None, qualifiers2=None, config=None, server=None)#

Read Turbulent Specific Dissipation Rate (omega) by calling the readers defined by the datasources.

Parameters:

time_scoping (Scoping or int or float or Field, optional) – Time/freq values (use doubles or field), time/freq set ids (use ints or scoping) or time/freq step ids (use scoping with timefreq_steps location) required in output. to specify time/freq values at specific load steps, put a field (and not a list) in input with a scoping located on “timefreq_steps”. linear time freq intrapolation is performed if the values are not in the result files and the data at the max time or freq is taken when time/freqs are higher than available time/freqs in result files.
mesh_scoping (ScopingsContainer or Scoping, optional) – Nodes or elements scoping required in output. the output fields will be scoped on these node or element ids. to figure out the ordering of the fields data, look at their scoping ids as they might not be ordered as the input scoping was. the scoping’s location indicates whether nodes or elements are asked for. using scopings container allows you to split the result fields container into domains
streams_container (StreamsContainer, optional) – Result file container allowed to be kept open to cache data
data_sources (DataSources) – Result file path container, used if no streams are set
mesh (MeshedRegion or MeshesContainer, optional) – Prevents from reading the mesh in the result files
region_scoping (Scoping or int, optional) – Region id (integer) or vector of region ids (vector) or region scoping (scoping) of the model (region corresponds to zone for fluid results or part for lsdyna results).
qualifiers1 (dict, optional) – (for fluid results only) labelspace with combination of zone, phases or species ids
qualifiers2 (dict, optional) – (for fluid results only) labelspace with combination of zone, phases or species ids

Returns:

fields_container

Return type:

FieldsContainer

Examples

>>> from ansys.dpf import core as dpf

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

>>> # Make input connections
>>> my_time_scoping = dpf.Scoping()
>>> op.inputs.time_scoping.connect(my_time_scoping)
>>> my_mesh_scoping = dpf.ScopingsContainer()
>>> op.inputs.mesh_scoping.connect(my_mesh_scoping)
>>> 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_mesh = dpf.MeshedRegion()
>>> op.inputs.mesh.connect(my_mesh)
>>> my_region_scoping = dpf.Scoping()
>>> op.inputs.region_scoping.connect(my_region_scoping)
>>> my_qualifiers1 = dict()
>>> op.inputs.qualifiers1.connect(my_qualifiers1)
>>> my_qualifiers2 = dict()
>>> op.inputs.qualifiers2.connect(my_qualifiers2)

>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.result.omega(
...     time_scoping=my_time_scoping,
...     mesh_scoping=my_mesh_scoping,
...     streams_container=my_streams_container,
...     data_sources=my_data_sources,
...     mesh=my_mesh,
...     region_scoping=my_region_scoping,
...     qualifiers1=my_qualifiers1,
...     qualifiers2=my_qualifiers2,
... )

>>> # Get output data
>>> result_fields_container = op.outputs.fields_container()

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:: InputsOmega

property outputs#

Enables to get outputs of the operator by evaluating it

Returns:: outputs
Return type:: OutputsOmega

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.omega.InputsOmega(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to connect user inputs to omega operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.omega()
>>> my_time_scoping = dpf.Scoping()
>>> op.inputs.time_scoping.connect(my_time_scoping)
>>> my_mesh_scoping = dpf.ScopingsContainer()
>>> op.inputs.mesh_scoping.connect(my_mesh_scoping)
>>> 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_mesh = dpf.MeshedRegion()
>>> op.inputs.mesh.connect(my_mesh)
>>> my_region_scoping = dpf.Scoping()
>>> op.inputs.region_scoping.connect(my_region_scoping)
>>> my_qualifiers1 = dict()
>>> op.inputs.qualifiers1.connect(my_qualifiers1)
>>> my_qualifiers2 = dict()
>>> op.inputs.qualifiers2.connect(my_qualifiers2)

property time_scoping#

Allows to connect time_scoping input to the operator.

Time/freq values (use doubles or field), time/freq set ids (use ints or scoping) or time/freq step ids (use scoping with timefreq_steps location) required in output. to specify time/freq values at specific load steps, put a field (and not a list) in input with a scoping located on “timefreq_steps”. linear time freq intrapolation is performed if the values are not in the result files and the data at the max time or freq is taken when time/freqs are higher than available time/freqs in result files.

Parameters:: my_time_scoping (Scoping or int or float or Field) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.omega()
>>> op.inputs.time_scoping.connect(my_time_scoping)
>>> # or
>>> op.inputs.time_scoping(my_time_scoping)

property mesh_scoping#

Allows to connect mesh_scoping input to the operator.

Nodes or elements scoping required in output. the output fields will be scoped on these node or element ids. to figure out the ordering of the fields data, look at their scoping ids as they might not be ordered as the input scoping was. the scoping’s location indicates whether nodes or elements are asked for. using scopings container allows you to split the result fields container into domains

Parameters:: my_mesh_scoping (ScopingsContainer or Scoping) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.omega()
>>> op.inputs.mesh_scoping.connect(my_mesh_scoping)
>>> # or
>>> op.inputs.mesh_scoping(my_mesh_scoping)

property streams_container#

Allows to connect streams_container input to the operator.

Result file container allowed to be kept open to cache data

Parameters:: my_streams_container (StreamsContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.omega()
>>> 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.

Result file path container, used if no streams are set

Parameters:: my_data_sources (DataSources) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.omega()
>>> op.inputs.data_sources.connect(my_data_sources)
>>> # or
>>> op.inputs.data_sources(my_data_sources)

property mesh#

Allows to connect mesh input to the operator.

Prevents from reading the mesh in the result files

Parameters:: my_mesh (MeshedRegion or MeshesContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.omega()
>>> op.inputs.mesh.connect(my_mesh)
>>> # or
>>> op.inputs.mesh(my_mesh)

property region_scoping#

Allows to connect region_scoping input to the operator.

Region id (integer) or vector of region ids (vector) or region scoping (scoping) of the model (region corresponds to zone for fluid results or part for lsdyna results).

Parameters:: my_region_scoping (Scoping or int) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.omega()
>>> op.inputs.region_scoping.connect(my_region_scoping)
>>> # or
>>> op.inputs.region_scoping(my_region_scoping)

property qualifiers1#

Allows to connect qualifiers1 input to the operator.

(for fluid results only) labelspace with combination of zone, phases or species ids

Parameters:: my_qualifiers1 (dict) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.omega()
>>> op.inputs.qualifiers1.connect(my_qualifiers1)
>>> # or
>>> op.inputs.qualifiers1(my_qualifiers1)

property qualifiers2#

Allows to connect qualifiers2 input to the operator.

(for fluid results only) labelspace with combination of zone, phases or species ids

Parameters:: my_qualifiers2 (dict) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.omega()
>>> op.inputs.qualifiers2.connect(my_qualifiers2)
>>> # or
>>> op.inputs.qualifiers2(my_qualifiers2)

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.omega.OutputsOmega(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to get outputs from omega operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.omega()
>>> # Connect inputs : op.inputs. ...
>>> result_fields_container = op.outputs.fields_container()

property fields_container#

Allows to get fields_container output of the operator

Returns:: my_fields_container
Return type:: FieldsContainer

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.omega()
>>> # Connect inputs : op.inputs. ...
>>> result_fields_container = op.outputs.fields_container()