At the heart of Symphonic-Joules lies the acoustic energy density equation, which governs how sound carries energy through space:
A project that harmonizes the worlds of sound and energy through innovative computational approaches, providing tools and insights that bridge the gap between acoustics and physics.
graph LR
A[Audio Input<br/>WAV/MP3/FLAC] --> B[Signal Processing]
B --> C[Feature Extraction]
C --> D{Analysis Type}
D -->|Frequency| E[FFT/STFT]
D -->|Time| F[Waveform Analysis]
D -->|Energy| G[Acoustic Energy Calc]
E --> H[Energy Density Computation]
F --> H
G --> H
H --> I[Energy Output<br/>Joules/Watts]
I --> J[Visualization]
J --> K[Results Dashboard]
style A fill:#e1f5ff
style I fill:#fff4e1
style K fill:#e8f5e9
style H fill:#f3e5f5
This diagram illustrates the transformation pipeline from raw audio signals to quantified energy measurements.
Symphonic-Joules is an open-source project that explores the intersection of audio processing and energy calculations. Whether youβre working with sound waves, musical compositions, or energy transformations, this project aims to provide tools and insights that bridge the gap between acoustics and physics.
Mission: To create an extensible, scientifically-grounded framework for analyzing the energetic properties of sound and the sonic properties of energy systems.
Symphonic-Joules follows an interface-first philosophy, where API design drives implementation. Below is the intended API showcasing how users will interact with the framework:
from symphonic_joules import AudioSignal, EnergyCalculator
# Load and represent an audio signal
signal = AudioSignal.from_file("symphony.wav")
# Access signal properties
print(f"Duration: {signal.duration}s")
print(f"Sample Rate: {signal.sample_rate}Hz")
print(f"Channels: {signal.channels}")
# Calculate acoustic energy density
calculator = EnergyCalculator(
medium_density=1.225, # kg/mΒ³ (air at 20Β°C)
sound_speed=343.0 # m/s (air at 20Β°C)
)
# Compute energy metrics
energy_density = calculator.compute_energy_density(signal)
total_energy = calculator.compute_total_energy(signal)
power = calculator.compute_average_power(signal)
print(f"Energy Density: {energy_density:.6f} J/mΒ³")
print(f"Total Energy: {total_energy:.6f} J")
print(f"Average Power: {power:.6f} W")
# Advanced: Frequency-domain energy analysis
freq_energy = calculator.energy_spectrum(signal)
freq_energy.plot(title="Energy Distribution by Frequency")
This API is aspirational and drives our development roadmap.
joule command-line interface# 1. Clone the repository
git clone https://github.com/JaclynCodes/Symphonic-Joules.git
cd Symphonic-Joules
# 2. Create and activate a virtual environment (recommended)
python -m venv venv
# On Windows:
venv\Scripts\activate
# On Unix/macOS:
source venv/bin/activate
# 3. Install the package in development mode
pip install -e .
# 4. Install development dependencies (optional, for contributors)
pip install -e ".[dev]"
# Run the test suite to verify installation
python -m pytest tests/ -v
# Check package version (note: Python package uses underscores, not hyphens)
python -c "import symphonic_joules; print(symphonic_joules.__version__)"
For detailed installation instructions, troubleshooting, and platform-specific guidance, see docs/installation-setup.md.
Currently, Symphonic-Joules provides a Python API for audio and energy computations. The package is designed to be imported and used programmatically.
Note: The Python package name uses underscores (symphonic_joules) following Python naming conventions, while the repository and project name use hyphens (Symphonic-Joules).
# Import the package (note: use underscores in Python)
import symphonic_joules
# Check version
print(f"Symphonic-Joules v{symphonic_joules.__version__}")
# Future usage examples will include:
# - Loading and processing audio files
# - Computing energy transformations
# - Analyzing frequency domain properties
# - Visualizing acoustic and energetic data
A command-line interface (joule) is planned for future releases to provide easy access to core functionality:
# Planned CLI commands (coming soon):
# joule process-audio <input.wav> --output <output.wav>
# joule analyze-energy <audio-file>
# joule list-filters
# joule convert --format mp3 <input>
For more examples and tutorials, see docs/examples/ and docs/getting-started.md.
Symphonic-Joules employs a unique Documentation-as-Code approach where tests validate not just code functionality, but also documentation accuracy. This ensures our documentation never drifts from reality.
Code Implementation β Documentation β Automated Tests β Validation
β β
βββββββββββββββββ Feedback Loop ββββββββββββββββββ
Our test suite includes meta-tests that validate documentation itself:
# From tests/test_readme_validation.py
class TestREADMEStructure:
"""Validates README has required sections"""
def test_has_overview_section(self, readme_content):
assert '## Overview' in readme_content
def test_has_dependencies_section(self, readme_content):
assert '## Dependencies' in readme_content
class TestTestCountAccuracy:
"""Ensures documented test counts match actual implementation"""
def test_total_test_count_is_accurate(self, readme_content, actual_test_count):
# Extracts test count from README and compares with actual
documented_count = extract_test_count(readme_content)
assert documented_count == actual_test_count
# Run documentation validation tests
python -m pytest tests/test_readme_validation.py -v
# Run all tests including documentation checks
python -m pytest tests/ -v
This testing philosophy ensures Symphonic-Joules maintains the highest standards of technical rigor and scientific accuracy.
For comprehensive test documentation, see tests/README.md.
Symphonic-Joules/
βββ .github/ # GitHub workflows, issue templates, and CI/CD
β βββ workflows/ # CI/CD workflow definitions
β β βββ iteration-status-emails.yml # Automated status notifications
β βββ ISSUE_TEMPLATE/ # Issue templates
βββ docs/ # Comprehensive documentation
β βββ getting-started.md # Getting started guide
β βββ installation-setup.md # Detailed installation
β βββ api-reference.md # API documentation
β βββ architecture.md # System architecture
β βββ performance-optimization.md # Performance tips
β βββ test-performance-guide.md # Testing best practices
β βββ iteration-email-setup.md # Email notification setup
β βββ january-2026-progress.md # Iteration progress dashboard
β βββ faq.md # Frequently asked questions
β βββ examples/ # Code examples and tutorials
βββ src/ # Source code
β βββ symphonic_joules/ # Main package
β βββ __init__.py # Package initialization
β βββ audio.py # Audio processing module
β βββ energy.py # Energy calculations module
β βββ utils.py # Utility functions
βββ tests/ # Test suite (pytest)
β βββ workflows/ # Workflow tests
β βββ *.py # Test modules
βββ CHANGELOG.md # Project changelog
βββ CONTRIBUTING.md # Contribution guidelines
βββ LICENSE # MIT License
βββ README.md # This file
βββ pytest.ini # Pytest configuration
βββ requirements.txt # Project dependencies
βββ ruff.toml # Ruff linter configuration
βββ setup.py # Package setup script
Symphonic-Joules uses pytest for comprehensive testing. Tests ensure code quality, correctness, and prevent regressions.
# Run all tests
python -m pytest tests/ -v
# Run tests with coverage report
python -m pytest tests/ --cov=symphonic_joules --cov-report=html
# Run specific test file
python -m pytest tests/test_readme_validation.py -v
# Run tests matching a pattern
python -m pytest tests/ -k "test_documentation" -v
For more details on testing best practices, see docs/test-performance-guide.md.
We welcome contributions from developers, musicians, physicists, and anyone interested in the intersection of sound and energy!
git checkout -b feature/your-feature-namepytestRead the full Contributing Guidelines for detailed information.
Our development follows a three-phase approach aligned with scientific methodology:
Goal: Establish robust infrastructure and scientific foundations
AudioSignal class implementationEnergyCalculator class implementationDeliverable: A solid foundation ready for scientific computation
Goal: Implement core acoustic and energy analysis capabilities
w = pΒ²/(2ΟcΒ²) + ΟvΒ²/2Deliverable: Scientifically validated energy analysis from audio signals
Goal: Enable intuitive exploration of acoustic energy data
joule)
joule analyze <audio-file> - Quick energy analysisjoule visualize <audio-file> - Generate visualizationsjoule compare <file1> <file2> - Comparative analysisDeliverable: Complete toolkit for acoustic energy exploration
Future Directions:
Progress Tracking: See our Project Board for real-time development status.
The name βSymphonic-Joulesβ reflects our mission to harmonize:
Our core equation, w = pΒ² / (2ΟcΒ²) + ΟvΒ² / 2, represents the total energy density in an acoustic field:
This equation reveals a profound truth: sound is energy in motion, distributed between compression/rarefaction (potential) and particle movement (kinetic).
This project explores:
All physics calculations are:
We stand on the shoulders of giants in acoustics and physics.
Comprehensive documentation is available in the docs/ directory:
We are committed to providing a welcoming and inclusive environment. Please:
This project is licensed under the MIT License - see the LICENSE file for details.