run

class ansys.dpf.core.operators.result.run.run(mapdl_exe_path=None, working_dir=None, number_of_processes=None, data_sources=None, config=None, server=None)

Solve in mapdl a dat/inp file and returns a datasources with the rst file.

available inputs:
  • mapdl_exe_path (str) (optional)

  • working_dir (str) (optional)

  • number_of_processes (int) (optional)

  • data_sources (DataSources)

available outputs:
  • data_sources (DataSources)

Examples

>>> from ansys.dpf import core as dpf
>>> # Instantiate operator
>>> op = dpf.operators.result.run()
>>> # Make input connections
>>> my_mapdl_exe_path = str()
>>> op.inputs.mapdl_exe_path.connect(my_mapdl_exe_path)
>>> my_working_dir = str()
>>> op.inputs.working_dir.connect(my_working_dir)
>>> my_number_of_processes = int()
>>> op.inputs.number_of_processes.connect(my_number_of_processes)
>>> my_data_sources = dpf.DataSources()
>>> op.inputs.data_sources.connect(my_data_sources)
>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.result.run(mapdl_exe_path=my_mapdl_exe_path,working_dir=my_working_dir,number_of_processes=my_number_of_processes,data_sources=my_data_sources)
>>> # Get output data
>>> result_data_sources = op.outputs.data_sources()
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

InputsRun

property outputs

Enables to get outputs of the operator by evaluationg it

Returns

outputs

Return type

OutputsRun

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.result.run.InputsRun(op: ansys.dpf.core.dpf_operator.Operator)

Intermediate class used to connect user inputs to run operator

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.run()
>>> my_mapdl_exe_path = str()
>>> op.inputs.mapdl_exe_path.connect(my_mapdl_exe_path)
>>> my_working_dir = str()
>>> op.inputs.working_dir.connect(my_working_dir)
>>> my_number_of_processes = int()
>>> op.inputs.number_of_processes.connect(my_number_of_processes)
>>> my_data_sources = dpf.DataSources()
>>> op.inputs.data_sources.connect(my_data_sources)
property mapdl_exe_path

Allows to connect mapdl_exe_path input to the operator

Parameters

my_mapdl_exe_path (str,) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.run()
>>> op.inputs.mapdl_exe_path.connect(my_mapdl_exe_path)
>>> #or
>>> op.inputs.mapdl_exe_path(my_mapdl_exe_path)
property working_dir

Allows to connect working_dir input to the operator

Parameters

my_working_dir (str,) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.run()
>>> op.inputs.working_dir.connect(my_working_dir)
>>> #or
>>> op.inputs.working_dir(my_working_dir)
property number_of_processes

Allows to connect number_of_processes input to the operator

  • pindoc: Set the number of MPI processes used for resolution (default is 2)

Parameters

my_number_of_processes (int,) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.run()
>>> op.inputs.number_of_processes.connect(my_number_of_processes)
>>> #or
>>> op.inputs.number_of_processes(my_number_of_processes)
property data_sources

Allows to connect data_sources input to the operator

  • pindoc: data sources containing the input file.

Parameters

my_data_sources (DataSources,) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.run()
>>> op.inputs.data_sources.connect(my_data_sources)
>>> #or
>>> op.inputs.data_sources(my_data_sources)
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.result.run.OutputsRun(op: ansys.dpf.core.dpf_operator.Operator)

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

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.run()
>>> # Connect inputs : op.inputs. ...
>>> result_data_sources = op.outputs.data_sources()
property data_sources

Allows to get data_sources output of the operator

Returns

my_data_sources

Return type

DataSources,

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.run()
>>> # Connect inputs : op.inputs. ...
>>> result_data_sources = op.outputs.data_sources()