Commit 68eb0424 authored by Peter Wittek's avatar Peter Wittek

Migrated to GitLab

parent 5c6ff90f
......@@ -28,7 +28,7 @@ Version 1.7.1: 2016-10-02
- Fixed: macOS build works again.
Version 1.7.0: 2016-09-30
- New: Julia interface is available (https://github.com/peterwittek/Somoclu.jl).
- New: Julia interface is available (https://gitlab.com/peterwittek/Somoclu.jl).
- New: Method `get_surface_state` of the `Somoclu` object in Python calculates the activation map for all data instances.
- New: Method `view_activation_map` of the `Somoclu` object in Python allows plotting the activation map for the training data instances or for a new data instance.
- New: Method `view_similarity_matrix` of the `Somoclu` object in Python visualizes the similarity matrix of data points according to their distance to the nodes in the map.
......
......@@ -25,4 +25,4 @@ https://cran.r-project.org/web/packages/Rsomoclu/
This ensures that Depsy (http://depsy.org/) can aggregate the usage statistics of the library. All other users could cite the GitHub repository:
https://github.com/peterwittek/somoclu
https://gitlab.com/peterwittek/somoclu
......@@ -12,7 +12,7 @@ Key features:
* Both dense and sparse input data are supported.
* Large maps of several hundred thousand neurons are feasible.
* Integration with [Databionic ESOM Tools](http://databionic-esom.sourceforge.net/).
* [Python](https://somoclu.readthedocs.io/), [R](https://cran.r-project.org/web/packages/Rsomoclu/), [Julia](https://github.com/peterwittek/Somoclu.jl), and [MATLAB](https://github.com/peterwittek/somoclu/tree/master/src/MATLAB) interfaces for the dense CPU and GPU kernels.
* [Python](https://somoclu.readthedocs.io/), [R](https://cran.r-project.org/web/packages/Rsomoclu/), [Julia](https://gitlab.com/peterwittek/Somoclu.jl), and [MATLAB](https://gitlab.com/peterwittek/somoclu/tree/master/src/MATLAB) interfaces for the dense CPU and GPU kernels.
For more information, refer to the manuscript about the library [1].
......@@ -124,7 +124,7 @@ If the input file is sparse, but a dense kernel is invoked, Somoclu will execute
# Interfaces
[Python](https://somoclu.readthedocs.io/), [Julia](https://github.com/peterwittek/Somoclu.jl), [R](https://cran.r-project.org/web/packages/Rsomoclu/), and [MATLAB](https://github.com/peterwittek/somoclu/tree/master/src/MATLAB) interfaces are available for the dense CPU and GPU kernels. MPI and the sparse kernel are not support through the interfaces. For respective examples, see the folders in src.
[Python](https://somoclu.readthedocs.io/), [Julia](https://gitlab.com/peterwittek/Somoclu.jl), [R](https://cran.r-project.org/web/packages/Rsomoclu/), and [MATLAB](https://gitlab.com/peterwittek/somoclu/tree/master/src/MATLAB) interfaces are available for the dense CPU and GPU kernels. MPI and the sparse kernel are not support through the interfaces. For respective examples, see the folders in src.
The Python version is also available in [PyPI](https://pypi.python.org/pypi/somoclu). You can install it with
......@@ -136,7 +136,7 @@ Alternatively, it is also available on [conda-forge](https://github.com/conda-fo
Some pre-built binaries in the wheel format or Windows installer are provided at [PyPI Dowloads](https://pypi.python.org/pypi/somoclu#downloads), they are tested with [Anaconda](https://www.continuum.io/downloads) distributions. If you encounter errors like `ImportError: DLL load failed: The specified module could not be found` when `import somoclu`, you may need to use [Dependency Walker](http://www.dependencywalker.com/) as shown [here](http://stackoverflow.com/a/24704384/1136027) on `_somoclu_wrap.pyd` to find out missing DLLs and place them at the write place. Usually right version (32/64bit) of `vcomp90.dll, msvcp90.dll, msvcr90.dll` should be put to `C:\Windows\System32` or `C:\Windows\SysWOW64`.
The wheel binaries for macOS are compiled with the system `clang++`, which means by default it is not parallelized. To use the parallel version on Mac, you can either use the version in [conda-forge](https://github.com/conda-forge/somoclu-feedstock) or compile it from source with your favourite OpenMP-friendly compiler. To get it working with the GPU kernel, you might have to follow the instructions at the [Somoclu - Python Interface](https://github.com/peterwittek/somoclu/tree/master/src/Python).
The wheel binaries for macOS are compiled with the system `clang++`, which means by default it is not parallelized. To use the parallel version on Mac, you can either use the version in [conda-forge](https://github.com/conda-forge/somoclu-feedstock) or compile it from source with your favourite OpenMP-friendly compiler. To get it working with the GPU kernel, you might have to follow the instructions at the [Somoclu - Python Interface](https://gitlab.com/peterwittek/somoclu/tree/master/src/Python).
The R version is available on CRAN. You can install it with
......@@ -146,13 +146,13 @@ To get it working with the GPU kernel, download the source zip file and specify
R CMD INSTALL src/Rsomoclu_version.tar.gz --configure-args=/path/to/cuda
The Julia version is available on [GitHub](https://github.com/peterwittek/Somoclu.jl). The standard `Pkg.add("Somoclu")` should work.
The Julia version is available on [GitHub](https://gitlab.com/peterwittek/Somoclu.jl). The standard `Pkg.add("Somoclu")` should work.
For using the MATLAB toolbox, install SOM-Toolbox following the instructions at [ilarinieminen/SOM-Toolbox](https://github.com/ilarinieminen/SOM-Toolbox) and define the location of your MATLAB install to the configure script:
./configure --without-mpi --with-matlab=/usr/local/MATLAB/R2014a
For the GPU kernel, specify the location of your CUDA library for the configure script. More detailed instructions are in the [MATLAB source folder](https://github.com/peterwittek/somoclu/tree/master/src/MATLAB).
For the GPU kernel, specify the location of your CUDA library for the configure script. More detailed instructions are in the [MATLAB source folder](https://gitlab.com/peterwittek/somoclu/tree/master/src/MATLAB).
# Compilation & Installation
......
......@@ -2,9 +2,9 @@ Version: 1.7.5
Maintainer: ShichaoGao<xgdgsc at gmail.com>
URL: http://peterwittek.github.io/somoclu/
URL: http://gitlab.com/peterwittek/somoclu/
BugReports: https://github.com/peterwittek/somoclu/issues
BugReports: https://gitlab.com/peterwittek/somoclu/issues
License: GPL-3
......@@ -57,7 +57,7 @@ and set environment using:
before running ``./configure`` .
Then follow the instructions at https://github.com/peterwittek/somoclu to build somoclu itself.
Then follow the instructions at https://gitlab.com/peterwittek/somoclu to build somoclu itself.
Building Mex Extension on macOS:
......
......@@ -17,7 +17,7 @@ The documentation is available on `Read the Docs <https://somoclu.readthedocs.io
Usage
-----
A simple example is below. For more example, please refer to the `documentation <https://somoclu.readthedocs.io/>`_ and a more thorough ipython notebook example at `Somoclu in Python.ipynb <http://nbviewer.ipython.org/github/peterwittek/ipython-notebooks/blob/master/Somoclu%20in%20Python.ipynb>`_.
A simple example is below. For more example, please refer to the `documentation <https://somoclu.readthedocs.io/>`_ and a more thorough ipython notebook example at `Somoclu in Python.ipynb <http://nbviewer.ipython.org/gitlab/peterwittek/notebooks/blob/master/Somoclu%20in%20Python.ipynb>`_.
::
......@@ -83,7 +83,7 @@ If the ``CUDAHOME`` variable is set, the usual install command will build and in
Build with CUDA support on Windows:
--------------------------------------
You should first follow the instructions to `build the Windows binary <https://github.com/peterwittek/somoclu>`_ with ``HAVE_MPI`` and ``CLI`` disabled with the same version Visual Studio as your Python is built with.(Since currently Python is built by VS2008 by default and CUDA v6.5 removed VS2008 support, you may use CUDA 6.0 with VS2008 or find a Python prebuilt with VS2010. And remember to install VS2010 or Windows SDK7.1 to get the option in Platform Toolset if you use VS2013.) The recommended configuration is VS2010 Platform Toolset with Python 3.4. Then you should copy the .obj files generated in the release build path to the ``Python\somoclu\src`` folder.
You should first follow the instructions to `build the Windows binary <https://gitlab.com/peterwittek/somoclu>`_ with ``HAVE_MPI`` and ``CLI`` disabled with the same version Visual Studio as your Python is built with.(Since currently Python is built by VS2008 by default and CUDA v6.5 removed VS2008 support, you may use CUDA 6.0 with VS2008 or find a Python prebuilt with VS2010. And remember to install VS2010 or Windows SDK7.1 to get the option in Platform Toolset if you use VS2013.) The recommended configuration is VS2010 Platform Toolset with Python 3.4. Then you should copy the .obj files generated in the release build path to the ``Python\somoclu\src`` folder.
Then modify the environment variable ``CUDA_PATH`` or ``win_cuda_dir`` in ``setup.py`` to your CUDA path and run the install command
......
*************************
Download and Installation
*************************
The package is available in the `Python Package Index <https://pypi.python.org/pypi/somoclu/>`_, containing the source, documentation, and examples. The latest development version is available on `GitHub <https://github.com/peterwittek/somoclu>`_.
The package is available in the `Python Package Index <https://pypi.python.org/pypi/somoclu/>`_, containing the source, documentation, and examples. The latest development version is available on `GitHub <https://gitlab.com/peterwittek/somoclu>`_.
Dependencies
============
......@@ -9,7 +9,7 @@ The module requires `Numpy <http://www.numpy.org/>`_ and `matplotlib <http://www
On Linux and macOS, you need a standard C++ compile chain, for instance, GCC, ICC and clang are known to work.
On Windows, having ``MSVCP90.DLL`` and ``VCOMP90.DLL`` is usually sufficient. See `this issue <https://github.com/peterwittek/somoclu/issues/28#issuecomment-238419778>`_ if you have problems.
On Windows, having ``MSVCP90.DLL`` and ``VCOMP90.DLL`` is usually sufficient. See `this issue <https://gitlab.com/peterwittek/somoclu/issues/28#issuecomment-238419778>`_ if you have problems.
Installation
------------
......@@ -29,7 +29,7 @@ If you want the latest git version, clone the repository, make the Python target
::
$ git clone https://github.com/peterwittek/somoclu.git
$ git clone https://gitlab.com/peterwittek/somoclu.git
$ cd somoclu
$ ./autogen.sh
$ ./configure
......@@ -48,7 +48,7 @@ If the ``CUDAHOME`` variable is set, the usual install command will build and in
Build with CUDA support on Windows:
--------------------------------------
You should first follow the instructions to `build the Windows binary <https://github.com/peterwittek/somoclu>`_ with MPI disabled with the same version Visual Studio as your Python is built with.(Since currently Python is built by VS2008 by default and CUDA v6.5 removed VS2008 support, you may use CUDA 6.0 with VS2008 or find a Python prebuilt with VS2010. And remember to install VS2010 or Windows SDK7.1 to get the option in Platform Toolset if you use VS2013.) Then you should copy the .obj files generated in the release build path to the Python/src folder.
You should first follow the instructions to `build the Windows binary <https://gitlab.com/peterwittek/somoclu>`_ with MPI disabled with the same version Visual Studio as your Python is built with.(Since currently Python is built by VS2008 by default and CUDA v6.5 removed VS2008 support, you may use CUDA 6.0 with VS2008 or find a Python prebuilt with VS2010. And remember to install VS2010 or Windows SDK7.1 to get the option in Platform Toolset if you use VS2013.) Then you should copy the .obj files generated in the release build path to the Python/src folder.
Then modify the win_cuda_dir in setup.py to your CUDA path and run the install command
......
......@@ -8,8 +8,8 @@ Suggests:
[email protected]: c(person(given = "Peter", family = "Wittek", role = c("aut"), email = ""),
person(given = "Shichao", family = "Gao", role = c("cre"), email = "[email protected]"))
Description: Somoclu is a massively parallel implementation of self-organizing maps. It exploits multicore CPUs and it can be accelerated by CUDA. The topology of the map can be planar or toroid and the grid of neurons can be rectangular or hexagonal .
URL: http://peterwittek.github.io/somoclu/
BugReports: https://github.com/peterwittek/somoclu/issues
URL: http://gitlab.com/peterwittek/somoclu/
BugReports: https://gitlab.com/peterwittek/somoclu/issues
License: GPL-3
Packaged: 2014-03-16 16:55:16 UTC;
Author: Peter Wittek [aut], Shichao Gao [cre]
......
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