ansys.dpf.core.operators.math.expansion_psd#

class ansys.dpf.core.operators.math.expansion_psd(mode_shapes=None, static_shapes=None, rel_rel_covar_matrix=None, stat_stat_covar_matrix=None, rel_stat_covar_matrix=None, config=None, server=None)#

Bases: ansys.dpf.core.dpf_operator.Operator

Computes the PSD response for one-sigma solution.

Parameters:

  • mode_shapes (FieldsContainer) – Fields container containing the mode shapes from modal analysis file: mode shapes for dynamic and pseudo-static displacements

  • static_shapes (FieldsContainer, optional) – Fields container containing the static shapes (base excitations) from spectral analysis file

  • rel_rel_covar_matrix (FieldsContainer) – Fields container containing covariance matrices from a psd file: covariance matrix terms for displacement/velocity/acceleration mode-mode shapes

  • stat_stat_covar_matrix (FieldsContainer, optional) – Fields container containing covariance matrices from a psd file: covariance matrix terms for displacement/velocity/acceleration static-static shapes

  • rel_stat_covar_matrix (FieldsContainer, optional) – Fields container containing covariance matrices from a psd file: covariance matrix terms for displacement/velocity/acceleration mode-static shapes

Returns:

psd – PSD solution per label

Return type:

FieldsContainer

Examples

>>> from ansys.dpf import core as dpf

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

>>> # Make input connections
>>> my_mode_shapes = dpf.FieldsContainer()
>>> op.inputs.mode_shapes.connect(my_mode_shapes)
>>> my_static_shapes = dpf.FieldsContainer()
>>> op.inputs.static_shapes.connect(my_static_shapes)
>>> my_rel_rel_covar_matrix = dpf.FieldsContainer()
>>> op.inputs.rel_rel_covar_matrix.connect(my_rel_rel_covar_matrix)
>>> my_stat_stat_covar_matrix = dpf.FieldsContainer()
>>> op.inputs.stat_stat_covar_matrix.connect(my_stat_stat_covar_matrix)
>>> my_rel_stat_covar_matrix = dpf.FieldsContainer()
>>> op.inputs.rel_stat_covar_matrix.connect(my_rel_stat_covar_matrix)

>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.math.expansion_psd(
...     mode_shapes=my_mode_shapes,
...     static_shapes=my_static_shapes,
...     rel_rel_covar_matrix=my_rel_rel_covar_matrix,
...     stat_stat_covar_matrix=my_stat_stat_covar_matrix,
...     rel_stat_covar_matrix=my_rel_stat_covar_matrix,
... )

>>> # Get output data
>>> result_psd = op.outputs.psd()
_inputs#
_outputs#
static _spec() → ansys.dpf.core.operators.specification.Specification#
static 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

property inputs: InputsExpansionPsd#

Enables to connect inputs to the operator

Returns:

An instance of InputsExpansionPsd.

Return type:

inputs

property outputs: OutputsExpansionPsd#

Enables to get outputs of the operator by evaluating it

Returns:

An instance of OutputsExpansionPsd.

Return type:

outputs