Advanced#

You can use PyAEDT for postprocessing of AEDT results to display graphics object and plot data.

Touchstone#

TouchstoneData class is based on scikit-rf package and allows advanced touchstone post-processing. The following methods allows to read and check touchstone files.

`TouchstoneData.get_insertion_loss_index`	Get all insertion losses.
`TouchstoneData.plot_insertion_losses`	Plot all insertion losses.
`TouchstoneData.plot`	Plot a list of curves.
`TouchstoneData.plot_return_losses`	Plot all return losses.
`TouchstoneData.get_mixed_mode_touchstone_data`	Transform network from single ended parameters to generalized mixed mode parameters.
`TouchstoneData.get_return_loss_index`	Get the list of all the Returnloss from a list of excitations.
`TouchstoneData.get_insertion_loss_index_from_prefix`	Get the list of all the Insertion Losses from prefix.
`TouchstoneData.get_next_xtalk_index`	Get the list of all the Near End XTalk a list of excitation.
`TouchstoneData.get_fext_xtalk_index_from_prefix`	Get the list of all the Far End XTalk from a list of excitations and a prefix that will be used to retrieve driver and receivers names.
`TouchstoneData.plot_next_xtalk_losses`	Plot all next crosstalk curves.
`TouchstoneData.plot_fext_xtalk_losses`	Plot all fext crosstalk curves.
`TouchstoneData.get_worst_curve`	Analyze a solution data object with multiple curves and find the worst curve.
`read_touchstone`	Load the contents of a Touchstone file into an NPort.
`check_touchstone_files`	Check passivity and causality for all Touchstone files included in the folder.
`find_touchstone_files`	Get all Touchstone files in a directory.

Here an example on how to use TouchstoneData class.

from ansys.aedt.core.visualization.advanced.touchstone_parser import TouchstoneData

ts1 = TouchstoneData(touchstone_file=os.path.join(test_T44_dir, "port_order_1234.s8p"))
assert ts1.get_mixed_mode_touchstone_data()
ts2 = TouchstoneData(touchstone_file=os.path.join(test_T44_dir, "port_order_1324.s8p"))
assert ts2.get_mixed_mode_touchstone_data(port_ordering="1324")

assert ts1.plot_insertion_losses(plot=False)
assert ts1.get_worst_curve(curve_list=ts1.get_return_loss_index(), plot=False)

Farfield#

PyAEDT offers sophisticated tools for advanced farfield post-processing. There are two complementary classes: FfdSolutionDataExporter and FfdSolutionData.

FfdSolutionDataExporter: Enables efficient export and manipulation of farfield data. It allows users to convert simulation results into a standard metadata format for further analysis, or reporting.
FfdSolutionData: Focuses on the direct access and processing of farfield solution data. It supports a comprehensive set of postprocessing operations, from visualizing radiation patterns to computing key performance metrics.

FfdSolutionData

Provides antenna far-field data.

This code shows how you can get the farfield data and perform some post-processing:

import ansys.aedt.core
from ansys.aedt.core.generic.farfield_visualization import FfdSolutionDataExporter
app = ansys.aedt.core.Hfss()
ffdata = app.get_antenna_data(frequencies=None,
                              setup="Setup1 : Sweep",
                              sphere="3D",
                              variations=None,
                              overwrite=False,
                              link_to_hfss=True,
                              export_touchstone=True)
incident_power = ffdata.incident_power
ffdata.plot_cut(primary_sweep="Theta", theta=0)
ffdata.plot_contour(polar=True)
ffdata.plot_3d(show_geometry=False)
app.release_desktop(False, False)

If you exported the farfield data previously, you can directly get the farfield data:

from ansys.aedt.core.generic.farfield_visualization import FfdSolutionData
input_file = r"path_to_ffd\pyaedt_antenna_metadata.json"
ffdata = FfdSolutionData(input_file)
incident_power = ffdata.incident_power
ffdata.plot_cut(primary_sweep="Theta", theta=0)
ffdata.plot_contour(polar=True)
ffdata.plot_3d(show_geometry=False)
app.release_desktop(False, False)

The following diagram shows both classes work. You can use them independently or from the get_antenna_data method.

If you have existing farfield data, or you want to export it manually, you can still use FfdSolutionData class.

Monostatic RCS#

PyAEDT offers sophisticated tools for advanced monostatic radar cross section (RCS) post-processing. There are three complementary classes: MonostaticRCSExporter, MonostaticRCSData, and MonostaticRCSPlotter.

MonostaticRCSExporter: Enables efficient export and manipulation of RCS data. It allows users to convert simulation results into a standard metadata format for further analysis, or reporting.
MonostaticRCSData: Focuses on the direct access and processing of RCS solution data. It supports a comprehensive set of postprocessing operations, from visualizing radiation patterns to computing key performance metrics.
MonostaticRCSPlotter: Focuses on the post-processing of RCS solution data.

`MonostaticRCSData`	Provides monostatic radar cross-section (RCS) data.
`MonostaticRCSPlotter`	Provides monostatic radar cross-section (RCS) plot functionalities.

This code shows how you can get the RCS data and perform some post-processing:

from ansys.aedt.core import Hfss
from ansys.aedt.core.visualization.advanced.rcs_visualization import MonostaticRCSPlotter
app = Hfss()
rcs_object = app.get_rcs_data()
rcs_plotter = MonostaticRCSPlotter(rcs_data=rcs_object.rcs_data)
rcs_plotter.plot_rcs()

If you exported the RCS data previously, you can directly get the RCS data:

from ansys.aedt.core.visualization.advanced.rcs_visualization import MonostaticRCSPlotter
from ansys.aedt.core.visualization.advanced.rcs_visualization import MonostaticRCSData
input_file = r"path_to_data\pyaedt_rcs_metadata.json"
rcs_data = MonostaticRCSData(input_file)
rcs_plotter = MonostaticRCSPlotter(rcs_data)
rcs_plotter.plot_cut()

The following diagram shows both classes work. You can use them independently or from the get_rcs_data method.

Heterogeneous data message#

Heterogeneous data message (HDM) is the file exported from SBR+ solver containing rays information. The following methods allows to read and plot rays information.

`hdm_plot.HDMPlotter`	Manages Hdm data to be plotted with `pyvista`.
`sbrplus.hdm_parser.Parser`	Parser class that loads an HDM-format export file from HFSS SBR+, interprets its header and its binary content.

Miscellaneous#

PyAEDT has additional advanced post-processing features:

`convert_nearfield_data`	Convert a near field data folder to hfss nfd file and link it to and file.
`parse_rdat_file`	Parse Ansys report '.rdat' file.
`nastran_to_stl`	Convert Nastran file into stl.
`simplify_stl`	Import and simplify a stl file using pyvista and fast-simplification.