Circuit: automatic report creation#

This example shows how you can use PyAEDT to create reports automatically using a JSON file.

Perform required imports#

Perform required imports and set the local path to the path for PyAEDT.

import os
from IPython.display import Image
import pyaedt

# Set local path to path for PyAEDT
temp_folder = pyaedt.generate_unique_folder_name()
project_path = pyaedt.downloads.download_custom_reports(destination=temp_folder)

Launch AEDT#

Launch AEDT 2023 R2 in graphical mode. This example uses SI units.

desktopVersion = "2023.2"

Set non-graphical mode#

Set non-graphical mode. You can set non_graphical either to True or False. The Boolean parameter new_thread defines whether to create a new instance of AEDT or try to connect to an existing instance of it.

non_graphical = True
NewThread = True

Launch AEDT with Circuit#

Launch AEDT with Circuit. The pyaedt.Desktop class initializes AEDT and starts the specified version in the specified mode.

cir = pyaedt.Circuit(projectname=os.path.join(project_path, 'CISPR25_Radiated_Emissions_Example23R1.aedtz'),
                     non_graphical=non_graphical,
                     specified_version=desktopVersion,
                     new_desktop_session=True
                     )
cir.analyze()
Initializing new desktop!
C:\actions-runner\_work\_tool\Python\3.10.5\x64\lib\subprocess.py:1070: ResourceWarning: subprocess 8744 is still running
  _warn("subprocess %s is still running" % self.pid,

True

Create spectrum report#

Create a spectrum report. You can use a JSON file to create a simple setup or a fully customized one. The following code creates a simple setup and changes the JSON file to customize it. In a spectrum report, you can add limitilines and notes and edit axes, the grid, and the legend. You can create custom reports in non-graphical mode in AEDT 2023 R2 and later.

report1 = cir.post.create_report_from_configuration(os.path.join(project_path,'Spectrum_CISPR_Basic.json'))
out = cir.post.export_report_to_jpg(cir.working_directory, report1.plot_name)
Image(out)
<IPython.core.display.Image object>

Create spectrum report#

Every aspect of the report can be customized.

report1_full = cir.post.create_report_from_configuration(os.path.join(project_path,'Spectrum_CISPR_Custom.json'))
out = cir.post.export_report_to_jpg(cir.working_directory, report1_full.plot_name)
Image(out)
<IPython.core.display.Image object>

Create transient report#

Create a transient report. You can read and modify the JSON file before running the script. The following code modifies the traces before generating the report. You can create custom reports in non-graphical mode in AEDT 2023 R2 and later.

props = pyaedt.general_methods.read_json(os.path.join(project_path, 'Transient_CISPR_Custom.json'))

report2 = cir.post.create_report_from_configuration(input_dict=props, solution_name="NexximTransient")
out = cir.post.export_report_to_jpg(cir.working_directory, report2.plot_name)
Image(out)
<IPython.core.display.Image object>

Create transient report#

Property dictionary can be customized in any aspect and new report can be created easily. In this example the curve name is customized.

props["expressions"] = {"V(Battery)": {}, "V(U1_VDD)": {}}
props["plot_name"] = "Battery Voltage"
report3 = cir.post.create_report_from_configuration(input_dict=props, solution_name="NexximTransient")
out = cir.post.export_report_to_jpg(cir.working_directory, report3.plot_name)
Image(out)
<IPython.core.display.Image object>

Create eye diagram#

Create an eye diagram. If the JSON file contains an eye mask, you can create an eye diagram and fully customize it.

report4 = cir.post.create_report_from_configuration(os.path.join(project_path, 'EyeDiagram_CISPR_Basic.json'))
out = cir.post.export_report_to_jpg(cir.working_directory, report4.plot_name)
Image(out)
<IPython.core.display.Image object>

Create eye diagram#

You can create custom reports in non-graphical mode in AEDT 2023 R2 and later.

report4_full = cir.post.create_report_from_configuration(os.path.join(project_path, 'EyeDiagram_CISPR_Custom.json'))

out = cir.post.export_report_to_jpg(cir.working_directory, report4_full.plot_name)
Image(out)
<IPython.core.display.Image object>

This is how the spectrum looks like .. image:: Resources/spectrum_plot.png

Save project and close AEDT#

Save the project and close AEDT.

cir.save_project()
print("Project Saved in {}".format(cir.project_path))
cir.release_desktop()
Project Saved in D:/Temp/pyaedt_prj_H7K/custom_reports/

True

Total running time of the script: (1 minutes 1.207 seconds)

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