opentsne

library1.0.4pypypi✓ verified 90d ago

Extensible, parallel implementations of t-SNE for visualizing high-dimensional data. Supports multiple affinity models (e.g., multiscale mixture), optimization via Barnes-Hut or FIt-SNE, and out-of-sample embedding. Current version 1.0.4, requires Python >=3.9, with low release cadence (major/minor every few years).

ai-ml data

pip install opentsne

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · OPENTSNE

opentsne

ai-mlpythonv1.0.4

Install

9.6s avg

Import

4127ms

Disk

291MB

Pass rate

4/ 10

Env Coverage4 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.0.4 · pip install

no network on importno background threads

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

glibc

py 3.10

✕ build_error

✓ 9s

py 3.11

✕ build_error

✓ 9.65s

py 3.12

✕ build_error

✓ 9.85s

py 3.13

✕ build_error

✓ 9.9s

py 3.9

✕ build_error

291MB installed

● package 291MB

Code

Verified usage

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

TSNE

✓ from openTSNE import TSNE

✗ from opentsne import TSNE

Library uses camelCase 'openTSNE' as package name, not lowercase.

TSNEEmbedding

✓ from openTSNE import TSNEEmbedding

Affinity

✓ from openTSNE.affinity import Affinity

MultiscaleMixture

✓ from openTSNE.affinity import MultiscaleMixture

Default affinity model since v0.6.2.

Basic t-SNE embedding using default multiscale mixture affinity.

from openTSNE import TSNE from sklearn.datasets import load_iris import numpy as np iris = load_iris() X = iris.data y = iris.target # Initialize with default parameters (multiscale perplexity = [50, 500]) tsne = TSNE(random_state=42, verbose=False) embedding = tsne.fit(X) print(embedding.shape) # (150, 2)

opentsne --version

Debug

Known issues

breakingIn openTSNE v0.6.0, the API changed: affinities are no longer passed to TSNE constructor; use `affinities` parameter in `.fit()` method instead. Also, `TSNE` no longer accepts `affinities` at construction; custom affinities must be passed to `.fit()`.

fix

Pass affinities via `tsne.fit(X, affinities=my_affinity)` instead of `TSNE(affinities=...)`.

affects: >=0.6.0

breakingThe default affinity model changed from `PerplexityBasedNN` with a single perplexity to `MultiscaleMixture` with two perplexities (50 and 500) in v0.6.2. Results may differ from previous versions if not explicitly specifying perplexity.

fix

To replicate old behavior, use `TSNE(perplexity=30, affinities='perplexity')`.

affects: >=0.6.2

breakingPython 3.6 support dropped in v1.0.1, and Python 3.9+ required starting v1.0.2. Older Python versions will fail to install.

fix

Use Python >=3.9 for openTSNE >=1.0.2.

affects: >=1.0.2

Errors

Common errors & fixes

AttributeError: module 'openTSNE' has no attribute 'TSNE'

Importing with wrong case; the package name is 'openTSNE' but the module is also 'openTSNE', so `import openTSNE` works, but `from openTSNE import TSNE` is needed. Common mistake: using `import opentsne` (lowercase) which is not a standard alias.

fix

Use `from openTSNE import TSNE` or `import openTSNE as tsne`.

ImportError: cannot import name 'TSNEEmbedding' from 'openTSNE'

TSNEEmbedding is not directly importable from the top-level openTSNE; it resides in the `openTSNE.embedding` submodule in older versions, but in v1.x it is available from `openTSNE` directly. This error occurs when using an older version and trying the new import path.

fix

For openTSNE >=1.0.0: `from openTSNE import TSNEEmbedding`. For older versions (0.x): `from openTSNE.embedding import TSNEEmbedding`.

ValueError: The 'perplexity' parameter must be an integer or a list of integers.

openTSNE v0.6.2+ expects multiscale perplexity as a list (default [50, 500]) but passing a single float or integer incorrectly can trigger this error.

fix

Pass `perplexity=30` for single perplexity, or `perplexity=[50, 500]` for multiscale.

Upgrade

Version history

1.0.4latest on PyPI · released Oct 27, 2025

Audit

Dependencies

numpyrequiredCore dependency for array operations

scipyrequiredSparse matrix and distance computations

scikit-learnoptionalOptional for spectral initialization and metrics

annoyrequiredDefault nearest neighbor search (bundled)

pynndescentoptionalAlternative nearest neighbor search

numbaoptionalOptional accelerator for gradient computations (not used by default since v0.4.0)

Agent activity

7 hits · last 30 days

node

Anthropic

Resources

githubhttps://github.com/pavlin-policar/openTSNE ↗

packagehttps://pypi.org/project/opentsne/ ↗

homepagehttps://opentsne.readthedocs.io ↗

docshttps://opentsne.readthedocs.io/ ↗