Metadata-Version: 2.1
Name: pyprimal
Version: 0.0.0
Summary: PYthon package PaRametric sImplex Method for spArse Learning
Home-page: https://github.com/ShenQianli/primal
Author: Qianli Shen
Author-email: shenqianli@pku.edu.cn
Maintainer: Qianli Shen
Maintainer-email: shenqianli@pku.edu.cn
License: GPL-3.0
Description: # PYPRIMAL
        
        
        **PYPRIMAL**: **PY**thon package **P**a**R**ametric s**I**mplex **M**ethod for sp**A**rse **L**earning
        
        
        Requirements
        ------------
        
        - Linux or MacOS
        
        
        Installation
        ------------
        
        Install from source file (Github) with Makefile:
        
        - Clone ``primal.git`` via ``git clone --recurse-submodules https://github.com/ShenQianli/primal.git``
        - Make sure you have [setuptools](https://pypi.python.org/pypi/setuptools)  
        - Run ``make Pyinstall`` command.
        
        
        Install from source file (Github) with CMAKE:
        
        - Clone ``primal.git`` via ``git clone --recurse-submodules https://github.com/ShenQianli/primal.git``
        - Make sure you have [setuptools](https://pypi.python.org/pypi/setuptools) 
        - Build the source file first via the ``cmake`` with ``CMakeLists.txt`` in the root directory. (You will see a ``.so`` or ``.dylib`` file under ``(root)/lib/`` )
        - Run ``cd python-package; sudo python setup.py install`` command.
        
        
        Install from PyPI:
        
        - ``pip install pyprimal``
        - **Note**: Owing to the setting on different OS, our distribution might not be working in your environment (especially in **Windows**). Thus please build from source.
        
        You can test if the package has been successfully installed by:
        
        ```python
        import pyprimal
        pyprimal.test()
        
        ```
        
        Usage
        -----
        
        ```python
        from pyprimal import SparseSVM
        x = [[1,2,3], [4,5,6], [7,8,9]]
        y = [-1, 1, 1]
        solver = SparseSVM(x, y)
        solver.train()
        result = solver.coef()
        solver.plot()
        solver.plot('regpath')
        ```
        
        See [tutorial](https://github.com/ShenQianli/primal/blob/master/tutorials/tutorial.ipynb)
        
        
        Copy Right
        ----------
        
        Author: Qianli Shen, Zichong Li  
        Maintainer: Qianli Shen <shenqianli@pku.edu.cn>
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Description-Content-Type: text/markdown
