# PyDecomposer
PyDecomposer is a Python package for advanced signal decomposition using Variational Mode Decomposition (VMD) and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN).
## Features
- Decompose signals using VMD and CEEMDAN
- Automatically adjust the number of Intrinsic Mode Functions (IMFs)
- Classify IMFs into high-frequency and low-frequency components
- Visualize decomposed signals and IMFs
## Installation
You can install PyComposer using pip:
```bash
pip install pydecomposer
```
## Usage
Here's a quick example of how to use PyComposer:
```python
import numpy as np
from pydecomposer import DecompositionModel
# Generate a sample signal
t = np.linspace(0, 1, 1000)
signal = np.sin(2*np.pi*10*t) + 0.5*np.sin(2*np.pi*50*t)
# Create a DecompositionModel instance
model = DecompositionModel()
# Execute the decomposition
model.run(signal)
# Get the decomposed signals
high_freq, medium_freq, low_freq, residual = model.get_signals()
```
## GitHub
For more detailed information please visit the GitHub Repo [full documentation](https://github.com/gems-yc4923/PyDecomposer).
## Dependencies
- numpy
- matplotlib
- vmdpy
- EntropyHub
- PyEMD
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## License
This project is licensed under the Apache License, Version 2.0 - see the [LICENSE](LICENSE) file for details.
## Contact
For any issues or questions, please contact <*<yc2349@ac.ic.uk>*.
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"description": "# PyDecomposer\n\nPyDecomposer is a Python package for advanced signal decomposition using Variational Mode Decomposition (VMD) and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN).\n\n## Features\n\n- Decompose signals using VMD and CEEMDAN\n- Automatically adjust the number of Intrinsic Mode Functions (IMFs)\n- Classify IMFs into high-frequency and low-frequency components\n- Visualize decomposed signals and IMFs\n\n## Installation\n\nYou can install PyComposer using pip:\n\n```bash\npip install pydecomposer\n```\n\n## Usage\n\nHere's a quick example of how to use PyComposer:\n\n```python\nimport numpy as np\nfrom pydecomposer import DecompositionModel\n\n# Generate a sample signal\nt = np.linspace(0, 1, 1000)\nsignal = np.sin(2*np.pi*10*t) + 0.5*np.sin(2*np.pi*50*t)\n\n# Create a DecompositionModel instance\nmodel = DecompositionModel()\n\n# Execute the decomposition\nmodel.run(signal)\n\n# Get the decomposed signals\nhigh_freq, medium_freq, low_freq, residual = model.get_signals()\n\n```\n\n## GitHub\n\nFor more detailed information please visit the GitHub Repo [full documentation](https://github.com/gems-yc4923/PyDecomposer).\n\n## Dependencies\n\n- numpy\n- matplotlib\n- vmdpy\n- EntropyHub\n- PyEMD\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n## License\n\nThis project is licensed under the Apache License, Version 2.0 - see the [LICENSE](LICENSE) file for details.\n\n## Contact\n\nFor any issues or questions, please contact <*<yc2349@ac.ic.uk>*.\n",
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