Skip to main content

A tool for advanced signal decomposition using VMD and CEEMDAN

Project description

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:

pip install pycomposer

Usage

Here's a quick example of how to use PyComposer:

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()

Documentation

For more detailed information about the API and its usage, please refer to the full documentation.

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 file for details.

Contact

For any issues or questions, please contact <yc2349@ac.ic.uk.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pydecomposer-1.1.4.tar.gz (9.1 kB view details)

Uploaded Source

Built Distribution

pydecomposer-1.1.4-py3-none-any.whl (9.7 kB view details)

Uploaded Python 3

File details

Details for the file pydecomposer-1.1.4.tar.gz.

File metadata

  • Download URL: pydecomposer-1.1.4.tar.gz
  • Upload date:
  • Size: 9.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.9.19

File hashes

Hashes for pydecomposer-1.1.4.tar.gz
Algorithm Hash digest
SHA256 89c0d7a49110850cfd569736d9192e2f5cbb9417015684e78b552f01099f423c
MD5 45331247f5dddb814938406addca9900
BLAKE2b-256 13832761201c61985ada3e9c5a675059b96344219636bfc820d8b73ae7a53c84

See more details on using hashes here.

File details

Details for the file pydecomposer-1.1.4-py3-none-any.whl.

File metadata

File hashes

Hashes for pydecomposer-1.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 65d429e07dc0ee120afd0168b8b066692b0f96ff70ba986001ad915eb277ad58
MD5 f808c3a67c536fbecfd4943ea3bab8ba
BLAKE2b-256 bc09083c9fe783010476b3fbcf3fe66c871625a4248adaacedd69b0e7426e688

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page