is_cyclic#
Autogenerated DPF operator classes.
- class ansys.dpf.core.operators.metadata.is_cyclic.is_cyclic(streams_container=None, data_sources=None, config=None, server=None)#
Read if the model is cyclic form the result file.
- Parameters
streams_container (StreamsContainer, optional) – Streams (result file container) (optional)
data_sources (DataSources) – If the stream is null then we need to get the file path from the data sources
Examples
>>> from ansys.dpf import core as dpf
>>> # Instantiate operator >>> op = dpf.operators.metadata.is_cyclic()
>>> # Make input connections >>> 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)
>>> # Instantiate operator and connect inputs in one line >>> op = dpf.operators.metadata.is_cyclic( ... streams_container=my_streams_container, ... data_sources=my_data_sources, ... )
>>> # Get output data >>> result_file_path = op.outputs.file_path()
- 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 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 evaluationg 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 create an operator with the new configuration as a parameter.- Returns
Copy of the operator’s current configuration.
- Return type
- 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 of int, list of doubles,) –
- Field, FieldsContainer, Scoping, ScopingsContainer, MeshedRegion,
MeshesContainer, DataSources, 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.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 ]])
- 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.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
, optional) – Requested type of the output. The default isNone
.
- Returns
Output of the operator.
- Return type
type
- static operator_specification(op_name, server=None)#
Put the grpc spec message in self._spec
- 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.
- class ansys.dpf.core.operators.metadata.is_cyclic.InputsIsCyclic(op: ansys.dpf.core.dpf_operator.Operator)#
Intermediate class used to connect user inputs to is_cyclic operator.
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.metadata.is_cyclic() >>> 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)
- property streams_container#
Allows to connect streams_container input to the operator.
Streams (result file container) (optional)
- Parameters
my_streams_container (StreamsContainer) –
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.metadata.is_cyclic() >>> 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.
If the stream is null then we need to get the file path from the data sources
- Parameters
my_data_sources (DataSources) –
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.metadata.is_cyclic() >>> op.inputs.data_sources.connect(my_data_sources) >>> # or >>> op.inputs.data_sources(my_data_sources)
- 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, Field, FieldsContainer, Scoping,) –
- DataSources, MeshedRegion, ScopingsContainer, CyclicSupport,
…, Output, Outputs, Operator, os.PathLike
Input of the operator.
- class ansys.dpf.core.operators.metadata.is_cyclic.OutputsIsCyclic(op: ansys.dpf.core.dpf_operator.Operator)#
Intermediate class used to get outputs from is_cyclic operator.
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.metadata.is_cyclic() >>> # Connect inputs : op.inputs. ... >>> result_file_path = op.outputs.file_path()
- property file_path#
Allows to get file_path output of the operator
- Returns
my_file_path
- Return type
str
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.metadata.is_cyclic() >>> # Connect inputs : op.inputs. ... >>> result_file_path = op.outputs.file_path()