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Showing content from https://github.com/dapperfu/Python-Simulink below:

dapperfu/Python-Simulink: Run Simulink models with Python using shared libraries.

Run your Simulink models & libraries in Python.

1. Running software-in-the-loop tests with Simulink becomes time consuming with Matlab & Simulink overhead. There are ways to reduce it (Model reference, etc) however nothing has shown to be as fast as a precompiled shared library.

2. Python has a very mature set of tools and packages to automate testing.

3. Testing can be distributed to machines without Matlab/Simulink licenses.

4. There are more and more Python developers. Being able to hand off a Simulink Library for further use there is a good feature.

1. Use Python and it's ecosystem to run complex Simulink models.
2. Use Python & pytest to run Software-in-the-Loop (SIL) tests on Simulink subsystems.
3. Give Simulink algorithms to developers without Matlab/Simulink licenses to use.
4. Use GitHub/GitLab actions and Python to automate testing in the cloud.
5. Start a programming language war at your company.

This repository is a set of instructions, with examples, on how to create a Pythonic wrapper for Simulink models. It is not a turnkey Python module to do this:

import simulinkdll
simulinkdll.run("my_model.slx")
do_stuff()

For a given library or model configuring the Python should only need done when the Simulink Parameters/Signals change. The end developer will then be able do a import simulink_model, but it takes development time.

1. Create a shared library in Simulink.
2. Create Python representations of all items in the header file.
3. Open the shared library (.dll, .so) in Python and run the model.

• For demonstrating minimal dll functionality and the steps required to run a model in Python.
• Demonstrate implementions of SimulinkGlobal vs ExportedGlobal in Simulink.Parameter and Simulink.Signal variables.

A simple discrete transfer function. Compiled with a 1st order low pass filter.

There are two example notebooks for Example 2.

1. Simple Example - A simple low-level ctypes wrapper.
2. Pythonic Example - Use Python syntactic sugar to create a high level TransferTF python class to interact with the model. Adds datalogging and pandas integration.

• Example 2 also contains sample pytest tests in the tests directory. This demonstrates how you can use pytest to test Simulink models. Sample test results are shown shown in Example2/test_results.md.

• Tests can be run on GitHub actions as well. An example of pipeline file is provided: .github/workflows/blank.yml.

  This is an example badge:

Adapted from Mathworks's Simulation of a Bouncing Ball

Running a Simulation in Simulink also has some overhead. By compiling the model to a shared library and executing it, this overhead is eliminated.

bouncing_ball_benchmark.m benchmarks the model by testing increasingly smaller time steps. The model was then compiled and tested in Python and the corresponding times are recorded below.

This project also serves as a proof of concept for using CI/CD devops techniques with Simulink Models. There is a Jenkinsfile that will build each of the examples and archive the artifacts:

• shared library (.dll)
• header files (.h)

Jenkins Pipeline screenshot:

Jenkins Artifacts screenshot:

• https://github.com/dapperfu/Python-Simulink/discussions

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