run
#
- class ansys.dpf.core.operators.result.run.run(mapdl_exe_path=None, working_dir=None, number_of_processes=None, data_sources=None, server_mode=None, config=None, server=None)#
Bases:
ansys.dpf.core.dpf_operator.Operator
Solve in mapdl a dat/inp file and returns a datasources with the rst file.
- Parameters:
mapdl_exe_path (str, optional)
working_dir (str, optional)
number_of_processes (int, optional) – Set the number of MPI processes used for resolution (default is 2)
data_sources (DataSources) – data sources containing the input file.
server_mode (bool, optional) – used when a user includes commands in the input file allowing to launch DPF server inside MAPDL to interact with MAPDL using DPF client API
- Returns:
data_sources (DataSources) – returns the data source if the server_mode pin is not set to yes
ip (str) – returns the Ip if the server_mode pin is set to yes
port (str) – returns a port when the server mode pin is set to yes
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) >>> my_server_mode = bool() >>> op.inputs.server_mode.connect(my_server_mode)
>>> # 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, ... server_mode=my_server_mode, ... )
>>> # Get output data >>> result_data_sources = op.outputs.data_sources() >>> result_ip = op.outputs.ip() >>> result_port = op.outputs.port()
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. |
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.result.run import run
Property detail#
- property run.inputs: InputsRun#
Enables to connect inputs to the operator
- Returns:
An instance of InputsRun.
- Return type:
inputs
- property run.outputs: OutputsRun#
Enables to get outputs of the operator by evaluating it
- Returns:
An instance of OutputsRun.
- Return type:
outputs
- property run.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 run.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:
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 run.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 run.specification#
Returns the Specification (or documentation) of this Operator.
- Return type:
Attribute detail#
- run.name = None#
Method detail#
- static run.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
- run.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 ]]...
- run.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
.
- run.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
- run.__del__()#
Delete this instance.
- run.__str__()#
Describe the entity.
- Returns:
Description of the entity.
- Return type:
str
- run.run()#
Evaluate this operator.
- run.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.find_multishells_rst()) >>> disp_op = dpf.operators.result.displacement() >>> disp_op.inputs.data_sources(data_src) >>> normfc = math.norm_fc(disp_op).eval()
- run.__add__(fields_b)#
Add two fields or two fields containers.
- Returns:
add
- Return type:
operators.math.add_fc
- run.__sub__(fields_b)#
Subtract two fields or two fields containers.
- Returns:
minus
- Return type:
operators.math.minus_fc
- run.__pow__(value)#
Raise each element of a field or a fields container to power 2.
- run.__mul__(value)#
Multiply two fields or two fields containers.
- Returns:
mul
- Return type:
operators.math.generalized_inner_product_fc
- static run.operator_specification(op_name, server=None)#
Documents an Operator with its description (what the Operator does),its inputs and outputs and some properties.
- run.__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).