Metadata-Version: 2.1
Name: caddie
Version: 0.1.5
Summary: Information-Theoretic Causal Inference on Discrete Data
Home-page: https://github.com/kailashbuki/caddie
Author: Kailash Budhathoki
Author-email: kailash.buki@gmail.com
License: MIT License
Description: Caddie
        -------
        
        Caddie is a collection of bivariate discrete causal inference methods based on information-theoretic Additive Noise Models (ANM) and MDL-based instantiation of Algorithmic Independence of Conditionals (AIC).
        
        Caddie Module Installation
        ----------------------------
        
        The recommended way to install the `caddie` module is to simply use `pip`:
        
        ```console
        $ pip install caddie
        ```
        Caddie officially supports Python >= 3.6.
        
        How to use caddie?
        ------------------
        ```pycon
        >>> X = [1] * 1000
        >>> Y = [-1] * 1000
        >>> from caddie import cisc
        >>> cisc.cisc(X, Y)                                                       # CISC
        (0.0, 0.0)
        >>> from caddie import anm, measures
        >>> anm.fit_anm_both_dir(X, Y, measures.StochasticComplexity)             # CRISP
        (0.0, 0.0)
        >>> anm.fit_anm_both_dir(X, Y, measures.ChiSquaredTest)                   # DR
        (1.0, 1.0)
        >>> anm.fit_anm_both_dir(X, Y, measures.ShannonEntropy)                   # ACID
        (0.0, 0.0)
        >>> from caddie import simulations
        >>> simulations.simulate_decision_rate_against_data_type('/results/dir/') # for decision rate vs data type plots
        ...
        >>> simulations.simulate_accuracy_against_sample_size('/results/dir/')    # for accuracy/decidability vs sample size plots
        ...
        ```
        
        How to cite the paper?
        ----------------------
        Todo: Add the citation to thesis.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
