Future Actions
==============

.. warning:: This list of things to do could be also logged using github issues.

.. warning:: Think about the combination therapy resistance index (or activity index).
             It is kind of an spectrum of activity that counts the number of species
             (or genera) that can be treated when a combination therapy is applied.

.. warning:: Reformat names in all the ``.csv`` files. Also create a sample dataset
    with microbiology data to be loaded automatically using the ``pyamr`` module. The
    file must contain the following columns:

    .. note: We are ignoring the ``OrgPieceCounter``

    ======================= =============================================================
    Column Name             Description
    ======================= =============================================================
    ``date_sample``         The date the sample was taken (datetime64[ns])
    ``date_outcome``        The date the outcome was available (or last edited)
    ``patient_id``          The anonymised patient id
    ``lab_number``          The laboratory number associated to the test.
    ``order_name``          The order type (e.g. sputum, urine, ...)
    ``order_code``          The order code
    ``order_description``   The order description (at the moment is called specimen type)
    ``microorganism_name``
    ``microorganism_code``
    ``antimicrobial_name``
    ``antimicrobial_code``
    ``sensitivity_method``
    ``sensitivity``
    ``mic``                 The Minimum Inhibitory Concentration
    ``reported``            The result was reported to clinicians (selective reporting)
    ``genus_name``
    ``specie_name``
    ``gram_type``           Microorganism classification based on cell wall.
    ``antimicrobial_class``
    ======================= =============================================================

    Also note that it would be very useful to find open source databases with all
    this information already available. In addition, they might contain other relevant
    information: (i) organisms grouped by shape, (ii) organisms group by ....
    (iii) antimicrobials grouped by ...

    .. note:: We are ignoring the OrgPieceCounter.



.. LINK1: https://www.statsmodels.org/stable/examples/notebooks/generated/robust_models_0.html

.. warning:: Computing ``SART`` using Robust Regression. `[1] <https://www.statsmodels.org/stable/examples/notebooks/generated/robust_models_0.html>`_


.. warning:: ``CSV``

    Generate big csv files with the main outcomes (freq, sari, sart, asai, ...)

.. warning:: ``HTML``

    Create HTML files that based on the information contained in the CSV file,
    allows to dynamically explore different organism and antimicrobial pairs,
    different order codes, ...

.. warning:: ``ANIMATION``

    Create animations that based on the information contained in the CSV file,
    displays the evolution of the aforementioned AMR statistics in time. Similar
    examples seen in.... d3.js?

.. warning:: ``LATEX``

    Generate automatically from the data the latex/html tables and graphs describing
    the Antimicrobial Spectrum of Activity Index - ``ASAI`` - (see example below). For
    more information check out the PhD thesis (Chapter 4).

    .. image:: ../_static/imgs/todo-asai-table.png
       :align: center
       :alt: ASAI

.. warning:: ``LATEX``

    Generate automatically from the data the latex/html tables and graphs describing
    the Single Antimicrobial Resistance Trend - ``SART`` - (see example below). For
    more information check out the PhD thesis (Chapter 4).

    .. image:: ../_static/imgs/todo-sart-table.png
       :align: center
       :alt: SART