fft_approx#

Autogenerated DPF operator classes.

class ansys.dpf.core.operators.math.fft_approx.fft_approx(time_scoping=None, mesh_scoping=None, entity_to_fit=None, component_number=None, first_derivative=None, second_derivative=None, fit_data=None, cutoff_fr=None, config=None, server=None)#

Computes the fitting curve using FFT filtering and cubic fitting in space (node i: x=time, y=data), with the possibility to compute the first and the second derivatives of the curve.

Parameters:

  • time_scoping (Scoping, optional) – A time scoping to rescope / split the fields container given as input.

  • mesh_scoping (Scoping or ScopingsContainer, optional) – A space (mesh entities) scoping (or scopings container) to rescope / split the fields container given as input.

  • entity_to_fit (FieldsContainer) – Data changing in time to be fitted.

  • component_number (int) – Component number as an integer, for example ‘0’ for x-displacement, ‘1’ for y-displacement, and so on.

  • first_derivative (bool) – Calculate the first derivative (bool). the default is false.

  • second_derivative (bool) – Calculate the second derivative (bool). the default is false.

  • fit_data (bool) – Calculate the fitted values (bool). the default is false

  • cutoff_fr (float or int, optional) – Cutoff frequency.

Examples

>>> from ansys.dpf import core as dpf

>>> # Instantiate operator
>>> op = dpf.operators.math.fft_approx()

>>> # Make input connections
>>> my_time_scoping = dpf.Scoping()
>>> op.inputs.time_scoping.connect(my_time_scoping)
>>> my_mesh_scoping = dpf.Scoping()
>>> op.inputs.mesh_scoping.connect(my_mesh_scoping)
>>> my_entity_to_fit = dpf.FieldsContainer()
>>> op.inputs.entity_to_fit.connect(my_entity_to_fit)
>>> my_component_number = int()
>>> op.inputs.component_number.connect(my_component_number)
>>> my_first_derivative = bool()
>>> op.inputs.first_derivative.connect(my_first_derivative)
>>> my_second_derivative = bool()
>>> op.inputs.second_derivative.connect(my_second_derivative)
>>> my_fit_data = bool()
>>> op.inputs.fit_data.connect(my_fit_data)
>>> my_cutoff_fr = float()
>>> op.inputs.cutoff_fr.connect(my_cutoff_fr)

>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.math.fft_approx(
...     time_scoping=my_time_scoping,
...     mesh_scoping=my_mesh_scoping,
...     entity_to_fit=my_entity_to_fit,
...     component_number=my_component_number,
...     first_derivative=my_first_derivative,
...     second_derivative=my_second_derivative,
...     fit_data=my_fit_data,
...     cutoff_fr=my_cutoff_fr,
... )

>>> # Get output data
>>> result_fitted_entity_y = op.outputs.fitted_entity_y()
>>> result_first_der_dy = op.outputs.first_der_dy()
>>> result_second_der_d2y = op.outputs.second_der_d2y()
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:

InputsFftApprox

property outputs#

Enables to get outputs of the operator by evaluating it

Returns:

outputs

Return type:

OutputsFftApprox

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.math.fft_approx.InputsFftApprox(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to connect user inputs to fft_approx operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> my_time_scoping = dpf.Scoping()
>>> op.inputs.time_scoping.connect(my_time_scoping)
>>> my_mesh_scoping = dpf.Scoping()
>>> op.inputs.mesh_scoping.connect(my_mesh_scoping)
>>> my_entity_to_fit = dpf.FieldsContainer()
>>> op.inputs.entity_to_fit.connect(my_entity_to_fit)
>>> my_component_number = int()
>>> op.inputs.component_number.connect(my_component_number)
>>> my_first_derivative = bool()
>>> op.inputs.first_derivative.connect(my_first_derivative)
>>> my_second_derivative = bool()
>>> op.inputs.second_derivative.connect(my_second_derivative)
>>> my_fit_data = bool()
>>> op.inputs.fit_data.connect(my_fit_data)
>>> my_cutoff_fr = float()
>>> op.inputs.cutoff_fr.connect(my_cutoff_fr)
property time_scoping#

Allows to connect time_scoping input to the operator.

A time scoping to rescope / split the fields container given as input.

Parameters:

my_time_scoping (Scoping) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> 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.

A space (mesh entities) scoping (or scopings container) to rescope / split the fields container given as input.

Parameters:

my_mesh_scoping (Scoping or ScopingsContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> op.inputs.mesh_scoping.connect(my_mesh_scoping)
>>> # or
>>> op.inputs.mesh_scoping(my_mesh_scoping)
property entity_to_fit#

Allows to connect entity_to_fit input to the operator.

Data changing in time to be fitted.

Parameters:

my_entity_to_fit (FieldsContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> op.inputs.entity_to_fit.connect(my_entity_to_fit)
>>> # or
>>> op.inputs.entity_to_fit(my_entity_to_fit)
property component_number#

Allows to connect component_number input to the operator.

Component number as an integer, for example ‘0’ for x-displacement, ‘1’ for y-displacement, and so on.

Parameters:

my_component_number (int) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> op.inputs.component_number.connect(my_component_number)
>>> # or
>>> op.inputs.component_number(my_component_number)
property first_derivative#

Allows to connect first_derivative input to the operator.

Calculate the first derivative (bool). the default is false.

Parameters:

my_first_derivative (bool) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> op.inputs.first_derivative.connect(my_first_derivative)
>>> # or
>>> op.inputs.first_derivative(my_first_derivative)
property second_derivative#

Allows to connect second_derivative input to the operator.

Calculate the second derivative (bool). the default is false.

Parameters:

my_second_derivative (bool) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> op.inputs.second_derivative.connect(my_second_derivative)
>>> # or
>>> op.inputs.second_derivative(my_second_derivative)
property fit_data#

Allows to connect fit_data input to the operator.

Calculate the fitted values (bool). the default is false

Parameters:

my_fit_data (bool) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> op.inputs.fit_data.connect(my_fit_data)
>>> # or
>>> op.inputs.fit_data(my_fit_data)
property cutoff_fr#

Allows to connect cutoff_fr input to the operator.

Cutoff frequency.

Parameters:

my_cutoff_fr (float or int) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> op.inputs.cutoff_fr.connect(my_cutoff_fr)
>>> # or
>>> op.inputs.cutoff_fr(my_cutoff_fr)
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.math.fft_approx.OutputsFftApprox(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to get outputs from fft_approx operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> # Connect inputs : op.inputs. ...
>>> result_fitted_entity_y = op.outputs.fitted_entity_y()
>>> result_first_der_dy = op.outputs.first_der_dy()
>>> result_second_der_d2y = op.outputs.second_der_d2y()
property fitted_entity_y#

Allows to get fitted_entity_y output of the operator

Returns:

my_fitted_entity_y

Return type:

FieldsContainer

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> # Connect inputs : op.inputs. ...
>>> result_fitted_entity_y = op.outputs.fitted_entity_y()
property first_der_dy#

Allows to get first_der_dy output of the operator

Returns:

my_first_der_dy

Return type:

FieldsContainer

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> # Connect inputs : op.inputs. ...
>>> result_first_der_dy = op.outputs.first_der_dy()
property second_der_d2y#

Allows to get second_der_d2y output of the operator

Returns:

my_second_der_d2y

Return type:

FieldsContainer

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.math.fft_approx()
>>> # Connect inputs : op.inputs. ...
>>> result_second_der_d2y = op.outputs.second_der_d2y()