npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

poly-peach

v0.5.1

Published

A targeted pitch-detection library for node in the browser

Downloads

3

Readme

Pipeline Status

Poly Peach

A targeted polyphonic pitch detection library for Javascript.

Given a set of specific musical notes to listen for, this algorithm detects when they're present in an audio sample.

Implementation

The algorithm works by calculating the FFT of an audio sample and aggregating the signal strengths for frequency bandwidths of each musical note.

Then, for each note it's listening for, it calculates the notes corresponding to the first N harmonics, and compares an expected signature for these notes to the sample.

If the error is below a given threshold, then the note is reported as found.

Development

The package is structured in three parts:

  1. The C++ code that quickly calculates the Fast Fourier Transformation to construct musical note frequency spectrum.
  2. The Emscripten wrapper to convert the C++ code to WASM.
  3. The Node.js code to present a high-level interface.

Build:

To compile the C++ and WASM wrapper, run:

./build.sh

Run tests:

npm run test

or:

mocha

mocha -g 'test name'

To publish:

tsc
npm login
npm publish