Metadata-Version: 2.1
Name: gsa_framework
Version: 0.1
Summary: Generic framework for global sensitivity analysis
Home-page: https://github.com/aleksandra-kim/gsa_framework
Author: Aleksanda Kim
Author-email: aleksandra.kim@icloud.com
License: BSD-3-Clause
Description: # gsa_framework
        
        Basic project description
        
        ## Installation
        
        Details on how to install the package
        
        ## Contributing
        
        Details on how to contribute
        
        ## Developing
        
        Tests require `pytest` and `SALib`.
        
        # TODO
        
        1. Generate documentation using Sphinx:
            Numpy style docs: https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_numpy.html
            https://numpydoc.readthedocs.io/en/latest/format.html#documenting-classes
            https://docs.python-guide.org/writing/documentation/
            https://www.python.org/dev/peps/pep-0257/
        
        2. Implement parameterized LCA model based on presamples.
        
        3. Run remotely.
        
        4. Comment tests properly
        
        # Pre-commit hooks
        Source: https://pre-commit.com/
        
        1. ``pip`` or ``conda install pre-commit``
        
        2. Create ``.pre-commit-config.yaml`` and populate it with relevant repos
        
        3. run ``pre-commit install`` to set up the git hook scripts
        
        4. Update your hooks to the latest version automatically by running ``pre-commit autoupdate``
        
Platform: UNKNOWN
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Visualization
Description-Content-Type: text/markdown
