t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections
https://doi.org/10.1109/TVCG.2020.2986996
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55 lines
2.1 KiB
55 lines
2.1 KiB
# t-viSNE #
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This Git repository contains the code that accompanies a research publication so-called "t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections". The details of the experiments and the research outcome are described in [this paper](https://arxiv.org/abs/2002.06910).
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**Note:** This repository is a version of t-SNE modified to support ongoing research. It may be slightly slower than the original. If you're just trying to run t-SNE, check the original repository that we forked from.
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# Installation #
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On Linux or OS X, compile the source using the following command:
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```
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g++ sptree.cpp tsne.cpp tsne_main.cpp -o bh_tsne -O2
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```
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The executable will be called `bh_tsne`.
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On Windows using Visual C++, do the following in your command line:
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- Find the `vcvars64.bat` file in your Visual C++ installation directory. This file may be named `vcvars64.bat` or something similar. For example:
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```
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// Visual Studio 12
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"C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin\amd64\vcvars64.bat"
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// Visual Studio 2013 Express:
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C:\VisualStudioExp2013\VC\bin\x86_amd64\vcvarsx86_amd64.bat
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```
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- From `cmd.exe`, go to the directory containing that .bat file and run it.
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- Go to `bhtsne` directory and run:
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```
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nmake -f Makefile.win all
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```
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The executable will be called `windows\bh_tsne.exe`.
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# Usage #
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The code comes with wrappers for Matlab and Python. These wrappers write your data to a file called `data.dat`, run the `bh_tsne` binary, and read the result file `result.dat` that the binary produces. There are also external wrappers available for [Torch](https://github.com/clementfarabet/manifold), [R](https://github.com/jkrijthe/Rtsne), and [Julia](https://github.com/zhmz90/BHTsne.jl). Writing your own wrapper should be straightforward; please refer to one of the existing wrappers for the format of the data and result files.
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Demonstration of usage in Python:
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```
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# first terminal: hosting the visualization side (client)
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python3 -m http.server # for Python3
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#or
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python -m SimpleHTTPServer 8000 # for Python2
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# second terminal: hosting the computational side (server)
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FLASK_APP=tsneGrid.py flask run
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```
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# t-viSNE
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