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

@nanopore/fast-ctc-decode

v0.3.2

Published

Blitzing fast CTC decoding library.

Downloads

5

Readme

fast-ctc-decode

test-fast-ctc-decode PyPI version

Blitzing fast CTC decoding library.

$ pip install fast-ctc-decode
$ npm i @nanopore/fast-ctc-decode

Usage

Python

>>> from fast_ctc_decode import beam_search, viterbi_search
>>>
>>> alphabet = "NACGT"
>>> posteriors = np.random.rand(100, len(alphabet)).astype(np.float32)
>>>
>>> seq, path = viterbi_search(posteriors, alphabet)
>>> seq
'ACACTCGCAGCGCGATACGACTGATCGAGATATACTCAGTGTACACAGT'
>>>
>>> seq, path = beam_search(posteriors, alphabet, beam_size=5, beam_cut_threshold=0.1)
>>> seq
'ACACTCGCAGCGCGATACGACTGATCGAGATATACTCAGTGTACACAGT'

Node / Web

import init, { beam_search, viterbi_search } from 'fast-ctc';

const floatArr = [0.0, 0.4, 0.6, 0.0, 0.3, 0.7, 0.3, 0.3, 0.4, 0.4, 0.3, 0.3, 0.4, 0.3, 0.3, 0.3, 0.3, 0.4, 0.1, 0.4, 0.5, 0.1, 0.5, 0.4, 0.8, 0.1, 0.1, 0.1, 0.1, 0.8];
const alphabet = ["N","A","G"];
const beamSize = 5;
const beamCutThreshold = Number(0.0).toPrecision(2);
const collapseRepeats = true;
const shape = [10, 3];
const string = false;
const qBias = Number(0.0).toPrecision(2);
const qScale = Number(1.0).toPrecision(2);

// On web, note the base path will be your public folder
init('fast_ctc_decode_wasm_bg.wasm');

const viterbisearch = await beam_search(floatArr, alphabet, string, qScale, qBias, collapseRepeats, shape);

const beamsearch = await beam_search(floatArr, alphabet, beamSize, beamCutThreshold, collapseRepeats, shape);

console.log(viterbisearch); // GGAG
console.log(beamsearch); // GAGAG

Benchmark

| Implementation | Time (s) | URL | | -------------------- | -------- | --- | | Viterbi (Rust) | 0.0003 | nanoporetech/fast-ctc-decode | | Viterbi (Python) | 0.0022 | | | Beam Search (Rust) | 0.0033 | nanoporetech/fast-ctc-decode | | Beam Search (C++) | 0.1034 | parlance/ctcdecode | | Beam Search (Python) | 3.3337 | githubharald/CTCDecoder |

Developer Quickstart

Python

$ git clone https://github.com/nanoporetech/fast-ctc-decode.git
$ cd fast-ctc-decode
$ pip install --user maturin
$ make test

JavaScript / Node

npm i
npm test

Note: You'll need a recent rust compiler on your path to build the project.

By default, a fast (and less accurate) version of exponentiation is used for the 2D search. This can be disabled by passing --cargo-extra-args="--no-default-features" to maturin, which provides more accurate calculations but makes the 2D search take about twice as long.

Credits

The original 1D beam search implementation was developed by @usamec for deepnano-blitz.

The 2D beam search is based on @jordisr and @ihh work in their pair consensus decoding paper.

Licence and Copyright

(c) 2019 Oxford Nanopore Technologies Ltd.

fast-ctc-decode is distributed under the terms of the MIT License. If a copy of the License was not distributed with this file, You can obtain one at https://github.com/nanoporetech/fast-ctc-decode/

Research Release

Research releases are provided as technology demonstrators to provide early access to features or stimulate Community development of tools. Support for this software will be minimal and is only provided directly by the developers. Feature requests, improvements, and discussions are welcome and can be implemented by forking and pull requests. However much as we would like to rectify every issue and piece of feedback users may have, the developers may have limited resource for support of this software. Research releases may be unstable and subject to rapid iteration by Oxford Nanopore Technologies.