Repository files navigation

This software package contains a Barnes-Hut implementation of the t-SNE algorithm. The implementation is described inthis paper.

On Linux or OS X, compile the source using the following command:

g++ sptree.cpp tsne.cpp tsne_main.cpp -o bh_tsne -O2

The executable will be calledbh_tsne.

On Windows using Visual C++, do the following in your command line:

• Find thevcvars64.bat file in your Visual C++ installation directory. This file may be namedvcvars64.bat or something similar. For example:

  // Visual Studio 12  "C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin\amd64\vcvars64.bat"  // Visual Studio 2013 Express:  C:\VisualStudioExp2013\VC\bin\x86_amd64\vcvarsx86_amd64.bat

• Fromcmd.exe, go to the directory containing that .bat file and run it.

• Go tobhtsne directory and run:

  nmake -f Makefile.win all

The executable will be calledwindows\bh_tsne.exe.

The code comes with wrappers for Matlab and Python. These wrappers write your data to a file calleddata.dat, run thebh_tsne binary, and read the result fileresult.dat that the binary produces. There are also external wrappers available forTorch,R, andJulia. Writing your own wrapper should be straightforward; please refer to one of the existing wrappers for the format of the data and result files.

Demonstration of usage in Matlab:

filename= websave('mnist_train.mat','https://github.com/awni/cs224n-pa4/blob/master/Simple_tSNE/mnist_train.mat?raw=true');load(filename);numDims=2; pcaDims=50; perplexity=50; theta=.5; alg='svd';map= fast_tsne(digits',numDims,pcaDims,perplexity,theta,alg);gscatter(map(:,1), map(:,2),labels');

Demonstration of usage in Python:

importnumpyasnpimportbhtsnedata=np.loadtxt("mnist2500_X.txt",skiprows=1)embedding_array=bhtsne.run_bh_tsne(data,initial_dims=data.shape[1])

Usage:

python bhtsne.py [-h] [-d NO_DIMS] [-p PERPLEXITY] [-t THETA]                  [-r RANDSEED] [-n INITIAL_DIMS] [-v] [-i INPUT]                  [-o OUTPUT] [--use_pca] [--no_pca] [-m MAX_ITER]

Below are the various options the wrapper programbhtsne.py expects:

• -h, --help show this help message and exit
• -d NO_DIMS, --no_dims NO_DIMS
• -p PERPLEXITY, --perplexity PERPLEXITY
• -t THETA, --theta THETA
• -r RANDSEED, --randseed RANDSEED
• -n INITIAL_DIMS, --initial_dims INITIAL_DIMS
• -v, --verbose
• -i INPUT, --input INPUT: the input file, expects a TSV with the first row as the header.
• -o OUTPUT, --output OUTPUT: A TSV file having each row as thed dimensional embedding.
• --use_pca
• --no_pca
• -m MAX_ITER, --max_iter MAX_ITER