Metadata-Version: 2.1
Name: grakel
Version: 0.1a6
Summary: A scikit-learn compatible library for graph kernels
Home-page: https://ysig.github.io/GraKeL/
Author: Ioannis Siglidis [LiX / DaSciM]
Author-email: y.siglidis@gmail.com
License: BSD
Project-URL: Documentation, https://ysig.github.io/GraKeL/
Project-URL: Send us Feedback!, http://www.lix.polytechnique.fr/dascim/contact/
Project-URL: Source, https://github.com/ysig/GraKeL/
Project-URL: Tracker, https://github.com/ysig/GraKeL/issues
Description: # GraKeL: A library for graph kernels
        
        **GraKeL** is a library compatible with the project of [scikit-learn](http://scikit-learn.org/)
        
        Installation
        =================
        
        The GraKeL library requires:
        
        * Python (>=2.7, >=3.5)
        * NumPy (>=1.8.2)
        * SciPy (>=0.13.3)
        * Cython (>=0.27.3)
        * cvxopt (>=1.2.0) [optional: lovasz]
        * future (>=0.16.0) (for python 2.7)
        
        
        Installing Dependencies
        -----------------------
        
        You can install the dependencies as follows:
        
        ```shell
        $ pip install extension>=extension_version
        ```
        
        or
        
        ```shell
        $ pip install -r requirements.txt
        ```
        
        Installing the *development-version*
        ------------------------------------
        
        To install the *development-version* using [**pip**](https://pypi.org/project/grakel-dev) execute:
        
        ```shell
        $ pip install grakel-dev
        ```
        
        Getting Started
        ===============
        Two pointers to get you started:
        
        
        Testing
        =======
        You first need to build the package's c++ extensions
        locally by executing:
        ```shell
        $ python setup.py build_ext -i
        ```
        
        To test the package, execute:
        ```shell
        $ nosetests
        ```
        
        For executing unit_tests or use a testing-interface for testing the `kernel` module:
        ```shell
        $ python  grakel/tests/test_kernels.py --help
        usage: test_kernels.py [-h] [--verbose] [--problematic] [--slow]
                               [--ignore_warnings] [--dataset DATASET] [--normalize]
                               [--develop | --all | --main]
        
        A test file for all kernels
        
        optional arguments:
          -h, --help         show this help message and exit
          --verbose          print kernels with their outputs on stdout
          --problematic      allow execution of problematic test cases in development
          --slow             allow execution of slow test cases in development
          --ignore_warnings  ignore warnings produced by kernel executions
          --dataset DATASET  chose the datset you want the tests to be executed
          --normalize        normalize the kernel output
          --develop          execute only tests connected with current development
          --all              execute all tests
          --main             execute the main tests [default]
        
        ```
        
        For testing `graph_kernels`:
        ```shell
        $ python grakel/tests/test_graph_kernel.py --help
        usage: test_graph_kernels.py [-h] [--verbose] [--problematic] [--slow]
                                     [--normalize] [--ignore_warnings]
                                     [--dataset DATASET] [--develop | --all | --main]
        
        A test file for all kernels
        
        optional arguments:
          -h, --help         show this help message and exit
          --verbose          print kernels with their outputs on stdout
          --problematic      allow execution of problematic test cases in development
          --slow             allow execution of slow test cases in development
          --normalize        normalize the kernel output
          --ignore_warnings  ignore warnings produced by kernel executions
          --dataset DATASET  chose the datset you want the tests to be executed
          --develop          execute only tests connected with current development
          --all              execute all tests
          --main             execute the main tests [default]
        
        ```
        
        And for testing the `Graph` class:
        ```shell
        $ python grakel/tests/test_graph.py --help
        usage: test_graph.py [-h] [--verbose] [--ignore_warnings]
        
        A test file for all `Graph` type objects
        
        optional arguments:
          -h, --help         show this help message and exit
          --verbose          verbose outputs on stdout
          --ignore_warnings  ignore warnings produced by kernel executions
        ```
        You can also execute the kernel test locally through a *test-main-function* as
        
        ```shell
        $ python -m grakel.tests
        ```
        
        Contributing
        ============
        To learn how to integrate your own kernel and how to contribute to the GraKeL project, please read the sections *Write your own kernel* and *Contributing* in the [Documentation][doc], respectively.
        
        [doc]: https://ysig.github.io/GraKeL/dev/
        [examples]: https://ysig.github.io/GraKeL/dev/auto_examples/index.html
        
        License
        =======
        GraKeL comes with a __BSD 3-clause__ license (as with scikit-learn).
        It contains the C++ source code of [BLISS](http://www.tcs.hut.fi/Software/bliss) (a library for graph isomorphism) which is __LGPL__ licensed.
        Futhermore its optional dependency in the package of [cvxopt](https://cvxopt.org/) (a tool for solving convex-optimization problems) comes with a __GPL__ license.
        
        Citation
        ========
        If you use GraKeL in a scientific publication, please cite our paper:
        
        ```
        @article{siglidis2018grakel,
          title={GraKeL: A Graph Kernel Library in Python},
          author={Siglidis, Giannis and Nikolentzos, Giannis and Limnios, Stratis and Giatsidis, Christos and Skianis, Konstantinos and Vazirgiannis, Michalis},
          journal={arXiv preprint arXiv:1806.02193},
          year={2018}
        }
        ```
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: C
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, <4
Description-Content-Type: text/markdown
Provides-Extra: lovasz
