Giter Site home page Giter Site logo

gabepoel / ml-peak-tracker Goto Github PK

View Code? Open in Web Editor NEW
2.0 1.0 0.0 2.18 MB

Library for finding Lorentzian distributions using machine learning.

Python 99.97% Shell 0.03%
resonant-ultrasound-spectroscopy elasticity machine-learning symmetry-measurements rus

ml-peak-tracker's Introduction

Lorentzian Peak Finder (now with MaChInE lEaRnInG!)

A python library for finding, fitting to, and tracking Lorentzian peaks from RUS or other measurements. Usage and documentation can be found in the wiki. Tutorials and demo data is available in releases.

Note that throughout the library, the definition of Lorentzians used is the following.

eq1

Where the individual terms are as below.

eq2

Installing

Note that none of the installation methods download nor install the pre-made Lorentzian models. You need to get those separately. Please see Lorentzian Models for more information.

The recommended installation method is from pypi.

pip install peak-finder

But, you can also install directly from this git repository. These releases might not always be stable.

pip3 install git+https://github.com/GabePoel/ML-Peak-Tracker#egg=peak_finder --user

Or, if you only want to install the deltas, you can also clone this repository locally and then install using the included local_install.sh script. Navigate into the cloned repository and then run the following command.

sh ./peak_finder/local_install.sh

ml-peak-tracker's People

Contributors

gabepoel avatar

Stargazers

 avatar  avatar

Watchers

 avatar

ml-peak-tracker's Issues

Module 'lorentzian_models' not found

Hi,
I've tried installing with pip a couple times, deleting the install and clearing the wheel when this error comes up, and have tried to install this module with github.
image
Am using Python 3.10 so not sure that's an issue, but it seems like most of the machine learning stuff does not come up as a module attribute even though I can import the peak_finder library. Let me know if I can supply any more information/this is still an active project!

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.