Skip to main content

High Performance TSNE implementations for python

Project description

PyPI - Version PyPI - Wheel Python 3.6 Python 3.6 Python 3.6

Python TSNE implementation utilizing openmp for performance

This is based on the 10XDev/tsne fork of L.J.P. van der Maaten BH-tSNE implementation.

It has fixes to allow this to run in Python 3 and performance has been significantly increased with OpenMP parallelism. (see: tsne-perf-test)

Note: While Scikit-learn v0.17 has a tsne implementation, this implementation performs significantly faster than scikit-learn's. If you need speed, use this.

Algorithms

Barnes-Hut-SNE

A python (cython) wrapper for Barnes-Hut-SNE aka fast-tsne.

We forked 10XDev's implementation and openmp enabled the code.

Installation

This library has been added to pypi as tsne-mp

pip install tsne-mp

It requires openmp support.

  • OSX - brew install libomp
  • linux - 'sudo apt-get install libgomp1'
  • Windows - Included with Visual Studio C++

Usage

Basic usage:

from tsne import bh_sne
X_2d = bh_sne(X)

Or, the wheels also contain an executable that can be used from the command-line as described in the original project.

Examples

More Information

See Barnes-Hut-SNE (2013), L.J.P. van der Maaten. It is available on arxiv.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

tsne_mp-0.1.13-cp37-cp37m-win_amd64.whl (103.8 kB view details)

Uploaded CPython 3.7mWindows x86-64

tsne_mp-0.1.13-cp37-cp37m-manylinux1_x86_64.whl (167.7 kB view details)

Uploaded CPython 3.7m

tsne_mp-0.1.13-cp37-cp37m-macosx_10_9_x86_64.whl (133.6 kB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

tsne_mp-0.1.13-cp36-cp36m-win_amd64.whl (104.5 kB view details)

Uploaded CPython 3.6mWindows x86-64

tsne_mp-0.1.13-cp36-cp36m-manylinux1_x86_64.whl (167.8 kB view details)

Uploaded CPython 3.6m

tsne_mp-0.1.13-cp36-cp36m-macosx_10_9_x86_64.whl (133.9 kB view details)

Uploaded CPython 3.6mmacOS 10.9+ x86-64

tsne_mp-0.1.13-cp35-cp35m-win_amd64.whl (101.2 kB view details)

Uploaded CPython 3.5mWindows x86-64

tsne_mp-0.1.13-cp35-cp35m-manylinux1_x86_64.whl (166.9 kB view details)

Uploaded CPython 3.5m

tsne_mp-0.1.13-cp35-cp35m-macosx_10_6_intel.whl (242.3 kB view details)

Uploaded CPython 3.5mmacOS 10.6+ Intel (x86-64, i386)

File details

Details for the file tsne_mp-0.1.13-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tsne_mp-0.1.13-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 103.8 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.6.6

File hashes

Hashes for tsne_mp-0.1.13-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 b303d61b0d761f7b3a07fdf3d5519cce4601b48769f7a51c9736dfb6c8521791
MD5 9130eb8ff263dd15afa7e7f1504ce589
BLAKE2b-256 d56605f7cf3b260af22e901fdb8bf3c0d6144259f41cdf05cf2150e500417489

See more details on using hashes here.

File details

Details for the file tsne_mp-0.1.13-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

  • Download URL: tsne_mp-0.1.13-cp37-cp37m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 167.7 kB
  • Tags: CPython 3.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.7.0

File hashes

Hashes for tsne_mp-0.1.13-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 89f13e23baaaa9b7665152079dfaf1285db041af8883f93235497ecfef976dc7
MD5 de0f46da7edb3623af4bcacd243332c0
BLAKE2b-256 68827c45c7d7ec3d02c518a1acce5d694e1ccd4ecff666b923036a82136ac477

See more details on using hashes here.

File details

Details for the file tsne_mp-0.1.13-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: tsne_mp-0.1.13-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 133.6 kB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.7.0

File hashes

Hashes for tsne_mp-0.1.13-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e66113589e0d32cad761f59900ef84c76fb21c5b0681368d889f613c50bf996c
MD5 a718769849e51d0af998d175ca95eedb
BLAKE2b-256 91d46ad415128c0c31f57484f7019bdd5b594ffcc667bb43cde708c9eb48b898

See more details on using hashes here.

File details

Details for the file tsne_mp-0.1.13-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tsne_mp-0.1.13-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 104.5 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.6.6

File hashes

Hashes for tsne_mp-0.1.13-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 f2fdea39424eb5c314e36809c2788f24e63c1650db2416dcf2ee63efaea14d6c
MD5 6c99eeb57bfc8e80b725fb8e12367a5c
BLAKE2b-256 b98d4f788d45e468ce6771b9bde9b880f369aee876f4e7823c1cf98a317173f7

See more details on using hashes here.

File details

Details for the file tsne_mp-0.1.13-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

  • Download URL: tsne_mp-0.1.13-cp36-cp36m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 167.8 kB
  • Tags: CPython 3.6m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.7.0

File hashes

Hashes for tsne_mp-0.1.13-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 93398182d5997fd414c0c79ff516fad59ea2014c684f6dd78361cd032049edb2
MD5 df934a2f07e2fda0c23ca44e3e21aac6
BLAKE2b-256 2bbda01f08bb844987e80296059ce6a399f8abecc362753f6abe75fccb5adcf8

See more details on using hashes here.

File details

Details for the file tsne_mp-0.1.13-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: tsne_mp-0.1.13-cp36-cp36m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 133.9 kB
  • Tags: CPython 3.6m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.7.0

File hashes

Hashes for tsne_mp-0.1.13-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 3f9f203dc49bf2b4149c45e2043c21809d42623f484beacf31273f0f8d05775a
MD5 3fa00564c22b09a629e129f33e740a4c
BLAKE2b-256 a089e22e4504b29aaa9018922e0eec1067bce33f94c8b8d1b6c6aa0c918418d0

See more details on using hashes here.

File details

Details for the file tsne_mp-0.1.13-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tsne_mp-0.1.13-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 101.2 kB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.6.6

File hashes

Hashes for tsne_mp-0.1.13-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 3ac951045f5a7c6db6932136045ab3135cdc8e7bcece3f2be37cd7754efa72e3
MD5 145c8e24125a73e445ab04ea5e4618d2
BLAKE2b-256 4be1c5833419ae690fd15a7d434d5d4778e49a3bd8e5f743de0a35f4a1d49ea8

See more details on using hashes here.

File details

Details for the file tsne_mp-0.1.13-cp35-cp35m-manylinux1_x86_64.whl.

File metadata

  • Download URL: tsne_mp-0.1.13-cp35-cp35m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 166.9 kB
  • Tags: CPython 3.5m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.7.0

File hashes

Hashes for tsne_mp-0.1.13-cp35-cp35m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 82b43fd3b60f553502fc8979f5f1d84eedd56c99fbf49b4795661b0fc32259b7
MD5 82a97c03353fcd2a7d7d79c5b6a4e247
BLAKE2b-256 c4ad373fdd7c437ddf2fbe2f2de79abe19e97079c62ad16fc8e41bf5d1b2aa6a

See more details on using hashes here.

File details

Details for the file tsne_mp-0.1.13-cp35-cp35m-macosx_10_6_intel.whl.

File metadata

  • Download URL: tsne_mp-0.1.13-cp35-cp35m-macosx_10_6_intel.whl
  • Upload date:
  • Size: 242.3 kB
  • Tags: CPython 3.5m, macOS 10.6+ Intel (x86-64, i386)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.7.0

File hashes

Hashes for tsne_mp-0.1.13-cp35-cp35m-macosx_10_6_intel.whl
Algorithm Hash digest
SHA256 90bfde9aa987641f00c5572300928fd51d603cef45f5c66365fb385abc42239a
MD5 f329a2224e839c67b9dcdc4c72801d5e
BLAKE2b-256 fb38a82ff23115513c71a34aa733b10a8631d9ab0f80574c847b5c6c13f25462

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page