Signal-System 0.0.2

A package for signal and system simulation, design, analysis, and learning.

Signal & System

A Python package for Signal & System simulation, design, analysis, and learning.

Dependency & installation

Requirements

• Python version: 3.13
• Additional package dependencies include: NumPy, SciPy, Numba, PyTorch, Matplotlib, H5py, tqdm, and Click (detailed in pyproject.toml)

Installation

Before installation, create a Python virtual environment to manage dependencies and ensure a clean installation of the Signal & System package.

1. Create and activate a virtual environment: (One may use your preferred way to create a virtual environment. This tutorial uses Anaconda to manage environments.)

   # Change directory to your <working_directory>
   cd <working_directory>
   
   # Create a virtual environment of name <venv>
   # with Python version 3.13
   conda create --name <venv> python=3.13
   
   # Activate the virtual environment
   conda activate <venv>
   
   # Note: Exit the virtual environment
   conda deactivate
   

2. Install Package: (two methods)

   # Install directly from GitHub
   pip install git+https://github.com/hanson-hschang/Signal-System.git
   
   # Or clone and install
   git clone https://github.com/hanson-hschang/Signal-System.git
   cd Signal-System
   pip install .
   

Click me to expand/collapse developer environment setup

Developer environment setup

1. Clone and install development dependencies:

   git clone https://github.com/hanson-hschang/Signal-System.git
   cd Signal-System
   pip install -e ".[dev]"
   

2. Generate development requirements file:

   pip-compile pyproject.toml --extra=dev --output-file=requirements-dev.txt
   

3. Configure pre-commit hooks:

   pre-commit install
   

Development Tools

This project uses several tools for quality assurance:

• pre-commit: Git hooks for code quality checks
• pytest: Unit testing
• Black: Code formatting
• isort: Package import sorting
• mypy: Static type checking

Running Tests

# Standard test execution
pytest -c pyproject.toml

# Run tests with coverage report
pytest -c pyproject.toml --cov=src --cov-report=xml --cov-report=term

Code Style Guidelines

• Adherence to PEP 8 style guidelines
• Mandatory type hints for all functions and variables
• Documentation using numpydoc format specification

Format codebase:

# Upgrade Python syntax
pyupgrade --exit-zero-even-if-changed --py38-plus src/**/*.py

# Apply code formatting
black --config pyproject.toml ./

# Perform static type checking
mypy --config-file pyproject.toml ./

# Organize imports
isort --settings-path pyproject.toml ./

Example

Please refer to examples directory and learn how to use this Signal & System package. Three types of examples are provided:

• system provides various dynamic system simulations.
• control provides various control methods over dynamic systems.
• estimation provides various filtering and smoothing examples for different type of dynamic systems.

License

This project is released under the MIT License.

Contributing

1. Fork this repository
2. Create your feature branch (git checkout -b feat/amazing-feature)
3. Make your changes
4. Run the tests (pytest -c pyproject.toml)
5. Commit your changes (git commit -m "feat: Add some amazing feature")
6. Push to the feature branch (git push origin feat/amazing-feature)
7. Open a Pull Request