Metadata-Version: 2.1
Name: ennemi
Version: 1.0.0a1
Summary: Easy-to-use Nearest Neighbor Estimation of Mutual Information
Home-page: https://polsys.github.io/ennemi/
Author: Petri Laarne
Author-email: petri.laarne@helsinki.fi
License: MIT
Project-URL: Documentation, https://polsys.github.io/ennemi/
Project-URL: Source, https://github.com/polsys/ennemi/
Project-URL: Issues, https://github.com/polsys/ennemi/issues
Description: This package implements the estimation of mutual information (MI) between
        two continuous variables using a nearest-neighbor algorithm
        ([Kraskov et al. 2004](https://dx.doi.org/10.1103/PhysRevE.69.066138)).
        Mutual information is an information-theoretical measure of
        dependency between two variables.
        
        The interface is minimal and aimed at practical data analysis:
        
        - Support for masking and time lags between variables
        - Conditional MI with arbitrary-dimensional conditioning variables
        - Normalization of MI to correlation coefficient scale
        - Optional integration with `pandas` data frame types (no install-time dependency)
        - Optimized algorithm and parallel processing of multiple estimation tasks
        
        This package depends only on NumPy.
        Support for Python 3.6+ on the latest macOS, Ubuntu and Windows versions
        is officially tested.
        
        This project is still in **alpha** status and interface changes are possible.
        For more information on theoretical background and usage, please see the
        [documentation](https://polsys.github.io/ennemi).
        If you encounter any problems or have suggestions, please file an issue!
        
        ---
        
        This package has been developed at
        [Institute for Atmospheric and Earth System Research (INAR)](https://www.helsinki.fi/en/inar-institute-for-atmospheric-and-earth-system-research),
        University of Helsinki.
        
Keywords: information-theory entropy mutual-information data-analysis scientific
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Typing :: Typed
Requires-Python: ~=3.6
Description-Content-Type: text/markdown
