umap-js

library1.4.0jsnpmunverified

UMAP-JS is a JavaScript implementation of the Uniform Manifold Approximation and Projection (UMAP) algorithm, a popular dimension reduction technique for both visualization and general non-linear dimension reduction. Currently stable at version 1.4.0, the library offers synchronous, asynchronous, and step-by-step fitting methods, allowing for flexible integration into various application contexts. Key differentiators from the original Python implementation include the use of a random embedding to seed the optimization step, rather than a spectral embedding, which yields comparable results for smaller datasets but avoids complex eigenvalue/eigenvector computations in JavaScript. The library also lacks specialized functionality for angular distances or sparse data representations. Releases appear to follow an irregular schedule, with the last publish about two years ago, but the project is maintained by PAIR-code, indicating ongoing support.

ai-ml data

npm install umap-js

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INSTALL

IMPORT

SIG · UMAP-JS

umap-js

ai-mljavascriptv1.4.0

Install

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Import

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Disk

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Pass rate

0/ 6

Env Coverage0 / 6

glibc

18–22

musl

18–22

Install & Compatibility

Where this runs

tested against v? · npm install

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

node 18–226 runs

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glibc

node 18–226 runs

build_error

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

UMAP

✓ import { UMAP } from 'umap-js';

✗ const UMAP = require('umap-js');

The library primarily uses named exports. Direct CommonJS `require` for `UMAP` may not work as expected or might require destructuring.

UMAPParameters

✓ import { UMAP, UMAPParameters } from 'umap-js';

Type definition for constructor options when using TypeScript.

* as umapjs

✓ import * as umapjs from 'umap-js';

✗ const umapjs = require('umap-js');

Importing all exports into a namespace object.

Demonstrates initializing UMAP, generating sample data, performing synchronous dimension reduction, and transforming new data points.

import { UMAP } from 'umap-js'; // Generate some sample high-dimensional data const numSamples = 1000; const numDimensions = 10; const data: number[][] = []; for (let i = 0; i < numSamples; i++) { const sample: number[] = []; for (let j = 0; j < numDimensions; j++) { sample.push(Math.random() * 100); } data.push(sample); } // Initialize UMAP with custom parameters const umap = new UMAP({ nComponents: 2, // Reduce to 2 dimensions for visualization nNeighbors: 10, // Number of neighbors to consider minDist: 0.05, // Controls how tightly points are clustered together spread: 1.0 // Controls the overall scale of the embedding }); console.log('Starting UMAP fitting...'); // Perform synchronous fitting const embedding = umap.fit(data); console.log('UMAP fitting complete. First 5 embedded points:'); console.log(embedding.slice(0, 5)); // Example of transforming new data after fitting const additionalData = [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [10, 9, 8, 7, 6, 5, 4, 3, 2, 1]]; const transformedPoints = umap.transform(additionalData); console.log('Transformed additional points:'); console.log(transformedPoints);

Debug

Known issues

gotchaUMAP-JS differs from the Python UMAP implementation in key ways. It uses a random embedding to seed the optimization step, rather than a spectral embedding, due to the complexity of efficient eigenvalue/eigenvector computations in JavaScript. This can lead to comparable results for smaller datasets but may behave differently or have performance implications for very large or complex datasets where spectral initialization is advantageous.

fix

Be aware of these architectural differences when porting Python UMAP workflows or expecting identical behavior. Evaluate performance on your specific datasets.

affects: >=1.0.0

gotchaThe JavaScript port currently lacks specialized functionality for angular distances or sparse data representations, which are available in the Python UMAP library. Users requiring these features will need to implement them separately or preprocess their data accordingly.

fix

Preprocess sparse data into dense representations or calculate custom distance metrics if angular distances are critical for your application.

affects: >=1.0.0

gotchaWhile the 1.2.2 release fixed issues with the default import of `LM` (likely an internal component), reliance on undocumented or internal exports in older versions could have led to module resolution or runtime errors. It's best to stick to documented public APIs like `UMAP`.

fix

Always use the officially documented named imports, primarily `UMAP`. Avoid importing internal symbols which are subject to change without major version bumps.

affects: <1.2.2

Errors

Common errors & fixes

TypeError: UMAP is not a constructor

Attempting to use `require('umap-js')` without destructuring for named exports, or using a default import syntax for a named export.

fix

Ensure you are using named imports with ESM: `import { UMAP } from 'umap-js';` or proper destructuring for CJS: `const { UMAP } = require('umap-js');`.

Module not found: Can't resolve 'umap-js'

The `umap-js` package has not been installed or is not correctly listed in `package.json`.

fix

Install the package using your package manager: `npm install umap-js` or `yarn add umap-js`.

Upgrade

Version history

1.4.0latest on npm

Audit

Dependencies

No dependency data recorded yet.

Agent activity

23 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/PAIR-code/umap-js ↗

packagehttps://www.npmjs.com/package/umap-js ↗