semvec/pypi-packages huggingface dataset:
pydecomposer 1.1.5
A tool for advanced signal decomposition using VMD and CEEMDAN
Requires Python: >=3.7
Keywords: signal decomposition vmd ceemdan

# 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>*.
ot-arhmm 0.3.1
Toolkit for analyzing optical tweezer data using an autoregressive hidden Markov Model.
Requires Python: >=3.8

# OT arHMM

Code to fit optical tweezer data with autoregressive hidden Markov Models.

See [ot-arhmm.readthedocs.io](https://ot-arhmm.readthedocs.io) for instructions on how to use this package.

Developed by Brian Dawes in the Kamenetska research group at Boston University.