visualization.rst

Visualization (:py:mod:`violin.visualize_violin`)

VIOLIN's visualization function creates a visual summary of the VIOLIN output, incuding total score, evidence score, and match score distributions.

The visualization function includes a filtering option, which can help the user make choices on how to use the VIOLIN output. Visualization can be filtered by three possible metrics:

1. "%x" : Returns the top X% of LEEs, by Total Score
2. "Se>y" : Returns all LEEs with an Evidence Score greater than Y
3. "St>z" : Returns all LEEs with a Total Score grater than Z

• When visualizing the total output, this function shows the score distributions by classification, as well as the classification distribution
• When visualizing output of a single classification, the classification distribution is replaced by the number of LEEs given that classification
• When subcategories are identified in the Kind Score definition, additional plots of subcategory distribution are included

Functions

.. currentmodule:: visualize_violin

.. autofunction:: visualize

Dependencies

Python: pandas and matplotlib libraries

VIOLIN: none

Example output

Visualizing the total output

visualize(match_dict, kind_dict, 'RA2_sub_TotalOutput.csv', filter_opt='100%')

Visualizing subcategories:

kind_dict ={"strong corroboration" : 2,
            "weak corroboration1" : 1,
            "weak corroboration2" : 3,
            "weak corroboration3" : 5,
            "hanging extension" : 40,
            "full extension" : 41,
            "internal extension" : 42,
            "specification" : 30,
            "dir contradiction" : 10,
            "sign contradiction" : 11,
            "att contradiction" : 12,
            "flagged1" : 20,
            "flagged2" : 21,
            "flagged3" : 22}
visualize(match_dict, kind_dict, 'RA2_sub_TotalOutput.csv', filter_opt='100%')

Visualizing an individual category (extensions)

visualize(match_dict, kind_dict, 'RA2_sub_extensions.csv', filter_opt='100%')