make_for_each_range#
Autogenerated DPF operator classes.
- class ansys.dpf.core.operators.utility.make_for_each_range.make_for_each_range(try_generate_iterable=None, iterable=None, operator_to_iterate=None, pin_index=None, valueA=None, valueB=None, valueC1=None, valueC2=None, config=None, server=None)#
Generate a range that can be consumed by the for_each operator
- Parameters:
try_generate_iterable (bool, optional) – If true, already iterable values connected in pin 3 like vectors, scoping, timefreqsupport, containers and datasources are split to iterate on it (default is true)
iterable (optional) – Iterable object, generated by make_for_each_range oeprator, that can be combined with the one currently generated.
operator_to_iterate (Operator) – Operator that must be reconnected with the range values.
pin_index (int) –
valueA (default:
None
) –valueB (default:
None
) –valueC1 (default:
None
) –valueC2 (default:
None
) –
- Return type:
output
Examples
>>> from ansys.dpf import core as dpf
>>> # Instantiate operator >>> op = dpf.operators.utility.make_for_each_range()
>>> # Make input connections >>> my_try_generate_iterable = bool() >>> op.inputs.try_generate_iterable.connect(my_try_generate_iterable) >>> my_iterable = dpf.() >>> op.inputs.iterable.connect(my_iterable) >>> my_operator_to_iterate = dpf.Operator() >>> op.inputs.operator_to_iterate.connect(my_operator_to_iterate) >>> my_pin_index = int() >>> op.inputs.pin_index.connect(my_pin_index) >>> my_valueA = dpf.() >>> op.inputs.valueA.connect(my_valueA) >>> my_valueB = dpf.() >>> op.inputs.valueB.connect(my_valueB) >>> my_valueC1 = dpf.() >>> op.inputs.valueC1.connect(my_valueC1) >>> my_valueC2 = dpf.() >>> op.inputs.valueC2.connect(my_valueC2)
>>> # Instantiate operator and connect inputs in one line >>> op = dpf.operators.utility.make_for_each_range( ... try_generate_iterable=my_try_generate_iterable, ... iterable=my_iterable, ... operator_to_iterate=my_operator_to_iterate, ... pin_index=my_pin_index, ... valueA=my_valueA, ... valueB=my_valueB, ... valueC1=my_valueC1, ... valueC2=my_valueC2, ... )
>>> # Get output data >>> result_output = op.outputs.output()
- 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:
- property outputs#
Enables to get outputs of the operator by evaluating 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 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
- 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 isNone
. :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:
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 isNone
.
- 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:
- class ansys.dpf.core.operators.utility.make_for_each_range.InputsMakeForEachRange(op: ansys.dpf.core.dpf_operator.Operator)#
Intermediate class used to connect user inputs to make_for_each_range operator.
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.utility.make_for_each_range() >>> my_try_generate_iterable = bool() >>> op.inputs.try_generate_iterable.connect(my_try_generate_iterable) >>> my_iterable = dpf.() >>> op.inputs.iterable.connect(my_iterable) >>> my_operator_to_iterate = dpf.Operator() >>> op.inputs.operator_to_iterate.connect(my_operator_to_iterate) >>> my_pin_index = int() >>> op.inputs.pin_index.connect(my_pin_index) >>> my_valueA = dpf.() >>> op.inputs.valueA.connect(my_valueA) >>> my_valueB = dpf.() >>> op.inputs.valueB.connect(my_valueB) >>> my_valueC1 = dpf.() >>> op.inputs.valueC1.connect(my_valueC1) >>> my_valueC2 = dpf.() >>> op.inputs.valueC2.connect(my_valueC2)
- property try_generate_iterable#
Allows to connect try_generate_iterable input to the operator.
If true, already iterable values connected in pin 3 like vectors, scoping, timefreqsupport, containers and datasources are split to iterate on it (default is true)
- Parameters:
my_try_generate_iterable (bool) –
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.utility.make_for_each_range() >>> op.inputs.try_generate_iterable.connect(my_try_generate_iterable) >>> # or >>> op.inputs.try_generate_iterable(my_try_generate_iterable)
- property iterable#
Allows to connect iterable input to the operator.
Iterable object, generated by make_for_each_range oeprator, that can be combined with the one currently generated.
- Parameters:
my_iterable –
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.utility.make_for_each_range() >>> op.inputs.iterable.connect(my_iterable) >>> # or >>> op.inputs.iterable(my_iterable)
- property operator_to_iterate#
Allows to connect operator_to_iterate input to the operator.
Operator that must be reconnected with the range values.
- Parameters:
my_operator_to_iterate (Operator) –
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.utility.make_for_each_range() >>> op.inputs.operator_to_iterate.connect(my_operator_to_iterate) >>> # or >>> op.inputs.operator_to_iterate(my_operator_to_iterate)
- property pin_index#
Allows to connect pin_index input to the operator.
- Parameters:
my_pin_index (int) –
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.utility.make_for_each_range() >>> op.inputs.pin_index.connect(my_pin_index) >>> # or >>> op.inputs.pin_index(my_pin_index)
- property valueA#
Allows to connect valueA input to the operator.
- Parameters:
my_valueA –
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.utility.make_for_each_range() >>> op.inputs.valueA.connect(my_valueA) >>> # or >>> op.inputs.valueA(my_valueA)
- property valueB#
Allows to connect valueB input to the operator.
- Parameters:
my_valueB –
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.utility.make_for_each_range() >>> op.inputs.valueB.connect(my_valueB) >>> # or >>> op.inputs.valueB(my_valueB)
- property valueC1#
Allows to connect valueC1 input to the operator.
- Parameters:
my_valueC1 –
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.utility.make_for_each_range() >>> op.inputs.valueC1.connect(my_valueC1) >>> # or >>> op.inputs.valueC1(my_valueC1)
- property valueC2#
Allows to connect valueC2 input to the operator.
- Parameters:
my_valueC2 –
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.utility.make_for_each_range() >>> op.inputs.valueC2.connect(my_valueC2) >>> # or >>> op.inputs.valueC2(my_valueC2)
- 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.utility.make_for_each_range.OutputsMakeForEachRange(op: ansys.dpf.core.dpf_operator.Operator)#
Intermediate class used to get outputs from make_for_each_range operator.
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.utility.make_for_each_range() >>> # Connect inputs : op.inputs. ... >>> result_output = op.outputs.output()
- property output#
Allows to get output output of the operator
- Return type:
my_output
Examples
>>> from ansys.dpf import core as dpf >>> op = dpf.operators.utility.make_for_each_range() >>> # Connect inputs : op.inputs. ... >>> result_output = op.outputs.output()