JA

JAMA4JS – Linear Algebra for JavaScript

Hacker News

JAMA4JS – Linear Algebra for JavaScript

Released a translation from Java to JS of the NIST created JAMA linear algebra library (with verification tests and example) Last updated in 2012, the original implementation (Java) can be found at: https://math.nist.gov/javanumerics/jama/ The (JS) translation can be found at: https://github.com/conceptualGabrielPutnam/JAMA4JS The translation passes all verification tests and can perform: Cholesky, LU, QR, SVD, symmetric/non-symmetric decomposition as well as being used for solving least squares and nonsingular systems. Thanks to: Ronald F. Boisvert, Bruce Miller, Roldan Pozo, Karin Remington, Joe Hicklin, Cleve Moler, and Peter Webb for creating the original implementation.

Share card

Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
21%21% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Ve
Vectorious – Linear algebra in JavaScript34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Vectorious – Linear algebra in JavaScript

Hacker News1
Li
Linear regression in JavaScript using QR decomposition on ndarrays32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Linear regression in JavaScript using QR decomposition on ndarrays

Hacker News3
Pr
Promises in JavaScript41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Promises in JavaScript

Hacker News1
Ja
Javascript Keylogger54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Javascript Keylogger

Hacker News1
Iv
Ivy - Bound JavaScript54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Ivy - Bound JavaScript

Hacker News1
a
a refreshing JavaScript datepicker54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

a refreshing JavaScript datepicker

Hacker News2
Ja
Javascript constructor overloading54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Javascript constructor overloading

Hacker News2
Se
Sets in JavaScript36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Sets in JavaScript

Hacker News2
A
A Drip of JavaScript52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A Drip of JavaScript

Hacker News31
I
I converted libmp3lame to JavaScript59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I converted libmp3lame to JavaScript

Hacker News3