Noise contrastive data visualization
Project description
ncvis
NCVis is an efficient solution for data visualization. It uses HNSW for fast nearest neighbors graph construction and a parallel approach for building the graph embedding.
Installation
Conda [recommended]
You do not need to setup the environment if using conda, all dependencies are installed automatically.
$ conda install -c alartum ncvis
Pip
Important: be sure to have a compiler with OpenMP support. GCC has it by default, wich is not the case with clang. You may need to install llvm-openmp library beforehand.
- Install numpy and cython packages (compile-time dependencies):
$ pip install numpy cython
- Install ncvis package:
$ pip install ncvis
From source
- Install numpy and cython packages (compile-time dependencies):
$ pip install numpy cython
- Use Makefile, it will call pip for you
$ make wrapper
Using
import ncvis
vis = ncvis.NCVis()
Y = vis.fit_transform(X)
A more detailed example can be found here.
Project details
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