Skip to main content

SpKit: Signal Processing ToolKit

Project description

Signal Processing toolkit

Links: Homepage | Documentation | Github | PyPi - project | _ Installation: pip install spkit


CircleCI Documentation Status License: MIT PyPI version fury.io PyPI pyversions GitHub release PyPI format PyPI implementation HitCount GitHub commit activity Percentage of issues still open PyPI download month PyPI download week

Generic badge Ask Me Anything !

PyPI - Downloads

DOI


Installation

Requirement: numpy, matplotlib, scipy.stats, scikit-learn, seaborn

with pip

pip install spkit

update with pip

pip install spkit --upgrade

New in 0.0.9.7:

MEA Processing Toolkit

New in 0.0.9.5:

MEA Processing Toolkit

  • sp.mea

Geometrical Functions

  • sp.gemetry

More on signal processing

  • sp.core

Statistics

  • sp.stats

For updated list of contents and documentation check github or Documentation

List of all functions

Signal Processing Techniques

Information Theory functions

for real valued signals

  • Entropy

    • Shannon entropy
    • Rényi entropy of order α, Collision entropy,
    • Joint entropy
    • Conditional entropy
    • Mutual Information
    • Cross entropy
    • Kullback–Leibler divergence
    • Spectral Entropy
    • Approximate Entropy
    • Sample Entropy
    • Permutation Entropy
    • SVD Entropy
  • Plot histogram with optimal bin size

  • Computation of optimal bin size for histogram using FD-rule

  • Compute bin_width with various statistical measures

  • Plot Venn Diagram- joint distribuation and normalized entropy values

Dispersion Entropy --for time series (physiological signals)

  • Dispersion Entropy (Advanced) - for time series signal
    • Dispersion Entropy
    • Dispersion Entropy - multiscale
    • Dispersion Entropy - multiscale - refined

Matrix Decomposition

  • SVD
  • ICA using InfoMax, Extended-InfoMax, FastICA & Picard

Continuase Wavelet Transform

  • Gauss wavelet
  • Morlet wavelet
  • Gabor wavelet
  • Poisson wavelet
  • Maxican wavelet
  • Shannon wavelet

Discrete Wavelet Transform

  • Wavelet filtering
  • Wavelet Packet Analysis and Filtering

Basic Filtering

  • Removing DC/ Smoothing for multi-channel signals
  • Bandpass/Lowpass/Highpass/Bandreject filtering for multi-channel signals

Biomedical Signal Processing

MEA Processing Toolkit

Artifact Removal Algorithm

Analysis and Synthesis Models

  • DFT Analysis & Synthesis
  • STFT Analysis & Synthesis
  • Sinasodal Model - Analysis & Synthesis
    • to decompose a signal into sinasodal wave tracks
  • f0 detection

Ramanajum Methods for period estimation

  • Period estimation for a short length sequence using Ramanujam Filters Banks (RFB)
  • Minizing sparsity of periods

Fractional Fourier Transform

  • Fractional Fourier Transform
  • Fast Fractional Fourier Transform

Machine Learning models - with visualizations

  • Logistic Regression
  • Naive Bayes
  • Decision Trees
  • DeepNet (to be updated)

Linear Feedback Shift Register

  • pylfsr

Cite As

@software{nikesh_bajaj_2021_4710694,
  author       = {Nikesh Bajaj},
  title        = {Nikeshbajaj/spkit: 0.0.9.4},
  month        = apr,
  year         = 2022,
  publisher    = {Zenodo},
  version      = {0.0.9.4},
  doi          = {10.5281/zenodo.4710694},
  url          = {https://doi.org/10.5281/zenodo.4710694}
}

Contacts:

Imperial College London


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

spkit-0.0.9.6.8.tar.gz (1.6 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

spkit-0.0.9.6.8-py3-none-any.whl (1.6 MB view details)

Uploaded Python 3

File details

Details for the file spkit-0.0.9.6.8.tar.gz.

File metadata

  • Download URL: spkit-0.0.9.6.8.tar.gz
  • Upload date:
  • Size: 1.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.5

File hashes

Hashes for spkit-0.0.9.6.8.tar.gz
Algorithm Hash digest
SHA256 4c5680ce4f2aca635415e764011362f8bfd2e48b13cc981c526e00375d7ef0bb
MD5 ee9b0caf4adca16e15684acc9b447925
BLAKE2b-256 ec797d3b65be5047a9fb7eece2247444d0969a4b194a3803bb8e308b7eaa3309

See more details on using hashes here.

File details

Details for the file spkit-0.0.9.6.8-py3-none-any.whl.

File metadata

  • Download URL: spkit-0.0.9.6.8-py3-none-any.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.5

File hashes

Hashes for spkit-0.0.9.6.8-py3-none-any.whl
Algorithm Hash digest
SHA256 40bd73bf75566227cd6c5b2546c36be4fc30e07677b92c81030ae3b0073c6041
MD5 2b09c3ed7223c4bdeb37896a44d9bc6c
BLAKE2b-256 39862bda513fe12afc303af77327a380c06a9b2c699a1323c0da3b5c4e604730

See more details on using hashes here.

Supported by

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