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Stochastic Neighbor and Crowd Kernel (SNaCK) embeddings: Quick and dirty visualization of large-scale datasets via concept embeddings

Project description

Stochastic Neighbor and Crowd Kernel (SNaCK) embedding
======================================================
Quick and dirty visualization of large-scale datasets via concept embeddings

Installation
============
The following platforms are supported:
- Python 2.7 on Linux
- Binary packages available on Conda
- Source packages available from Pip
- Python 2.7 on OSX
- Binary packages for Yosemite available on Conda
- Source packages available from Pip (Homebrew-GCC required)

Linux: Install from Conda
-------------------------
Just run:
$ conda install -c https://conda.anaconda.org/gcr snack

Mac OS X: Install from Conda
----------------------------
TODO.

Linux: Install from Pip
-----------------------
Just run:
$ pip install snack

You need to install Python 2.7, Numpy, and Cython. You also need a
working compiler, CBLAS, and the Python development headers, which are
installable from your distribution's package manager.

To install SNaCK on a clean Ubuntu Trusty x64 system, run:

# sudo aptitude install \
build-essential \
python-dev \
libblas3 \
libblas-dev \
python-virtualenv
$ virtualenv venv; source venv/bin/activate
$ pip install numpy
$ pip install cython
$ pip install snack

OS X: Install from Pip and Homebrew
-----------------------------------
If you are on Mac OS X, you must install the real "not-clang" version
of gcc because it has OpenMP support. At the time of writing, clang
does not support OpenMP, and Apple has unhelpfully symlinked clang to
`/usr/bin/gcc`. This is not sufficient.

Using Apple-provided GCC is NOT supported. If `gcc-5 --version`
contains the string `clang` anywhere in its output, you do not have
the correct version of gcc.

Using Apple-provided Python is NOT supported.

The recommended installation method on OS X is with Homebrew:

$ brew install gcc
$ brew install python
$ virtualenv venv; source venv/bin/activate
$ pip install numpy
$ pip install cython
$ pip install snack

You may need to edit `setup.py` and change `GCC_VERSION` to point to
the correct version, if you are not using `/usr/local/bin/gcc-5`.


Just build without installing
-----------------------------

To simply build Snack without installing it, run:

$ python setup.py build_ext --inplace

This builds `snack/_snack.so`. You can move the `snack` folder to your
project's directory and then `import snack`. This should work as long
as the `snack` folder is inside your current directory.

How to use
----------

Examples
--------

See also
--------

Project details


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