Skip to content
This repository has been archived by the owner on Jan 3, 2023. It is now read-only.
/ tmapr Public archive
forked from reymond-group/tmap

A very fast visualization library for large, high-dimensional data sets.

Notifications You must be signed in to change notification settings

domiden/tmapr

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

tmap

tmap is a very fast visualization library for large, high-dimensional data sets. Currently, tmap is available for Python. tmaps graph layouts are based on the OGDF library.

Tutorial and Documentation

See http://tmap.gdb.tools

Examples

Name Description
NIPS Conference Papers A tmap visualization showing the linguistic relationship between NIPS conference papers. view
Project Gutenberg A tmap visualization of the linguistic relationships between books and authors extracted from Project Gutenberg. view
MNIST A visualization of the well known MNIST data set. No further explanation needed. view
Fashion MNIST A visualization of a more fashionable variant of MNIST. view
Drugbank A tmap visualization of all drugs registered in Drugbank. view
RNAseq RNA sequencing data of tumor samples. Visualized using tmap. view
Flowcytometry Flowcytometry data visualized using tmap. view
MiniBooNE tmap data visualization of a particle detection physics experiment. view

Availability

Language Operating System Status
Python Linux Available
Windows Available1
macOS Available
R Unvailable2

1Works with WSL
2FOSS R developers wanted!

Installation

tmap is installed using the conda package manager. Don't have conda? Download miniconda.

conda install -c tmap tmap

We suggest using faerun to plot the data layed out by tmap. But you can of course also use matplotlib (which might be to slow for large data sets and doesn't provide interactive features).

pip install faerun
# pip install matplotlib

About

A very fast visualization library for large, high-dimensional data sets.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • C++ 94.8%
  • TeX 2.5%
  • Python 1.4%
  • C 0.5%
  • CMake 0.4%
  • CSS 0.2%
  • Other 0.2%