nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation.

Overview

Build Status

Build status

Documentation Status

nptsne

nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation and HSNE modelling.

For more detail see the documentation for the current release - 1.1.0

Currently python 3.6, 3.7, and 3.8 are supported on Windows, Mac and Linux using cibuildwheel

Demo software using nptsne

Can be downloaded from DOI

Building

The requirements.txt and the pyproject.toml contain the list of build requirements.

  • Add the biovault conan remote (for prebuilt packages):
conan remote add conan-biovault http://cytosplore.lumc.nl:8081/artifactory/api/conan/conan-local

Development build & install using python

pip install -v -e .

This will automatically create a build subdirectory build the bindings and create an .egg-link file in the current python environment.

On Windows a _nptsne.sln file will be present under the build directory

Alternative manual Windows build

  • Make a build directory below the HDILib project root. For example: ./_build_release or ./_build_debug (when using conan the source directories are shared but separate build directories should be used for release and debug.)
  • In the python environment (with conan and cmake accessible) cd to the build directory and issue the following (for VisualStudio 2017):
cmake .. -G "Visual Studio 15 2017 Win64" -DCMAKE_BUILD_TYPE=Release -DNPTSNE_BUILD_WITH_CONAN=ON
(*Note: this assumes that the build dir is one level down from the project root.
The default of NPTSNE_BUILD_WITH_CONAN is OFF*)
  • If all goes well Conan will have installed the dependencies in its cache and created the required defines for the Cmake configuration. Open the .sln in VisualStudio and build ALL_BUILD for Release or Debug matching the CMAKE_BUILD_TYPE. On Windows the result of the build are three *.lib files
Owner
Biomedical Visual Analytics Unit LUMC - TU Delft
Biomedical Visual Analytics Unit LUMC - TU Delft
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