Categorization functions
========================

Submodule **pyiomica.categorizationFunctions**


Example of use of a function described in this module:

.. code-block:: python
   :emphasize-lines: 1-

    # import the package and its mudule Categorization functions
    import pyiomica as pio
    from pyiomica import categorizationFunctions as cf

    # Location of this example data
    dir = pio.ConstantPyIOmicaExamplesDirectory

    # Unzip sample data
    with pio.zipfile.ZipFile(pio.os.path.join(dir, 'SLV.zip'), "r") as zipFile:
        zipFile.extractall(path=dir)

    # Process sample dataset SLV Hourly 1 
    dataName = 'SLV_Hourly1TimeSeries'
    saveDir = pio.os.path.join('results', dataName, '')
    dataDir = pio.os.path.join(dir, 'SLV')
    df_data = pio.pd.read_csv(pio.os.path.join(dataDir, dataName + '.csv'), index_col=[0,1,2], header=0)
    cf.calculateTimeSeriesCategorization(df_data, dataName, saveDir, NumberOfRandomSamples = 10**4)
    cf.clusterTimeSeriesCategorization(dataName, saveDir)
    cf.visualizeTimeSeriesCategorization(dataName, saveDir)

One of the figures generated by ``visualizeTimeSeriesCategorization`` is shown below:

.. thumbnail:: https://raw.githubusercontent.com/gmiaslab/pyiomica/master/docs/examples/results/results%20SLV%20Delta/SLV_Delta_LAG1_AutocorrelationsBased_DendrogramHeatmap.png
    :title: Categorization example
    :alt: Cannot load this photo
    :align: center
    :width: 400px
    :height: 300px
    :download: false


.. automodule:: pyiomica.categorizationFunctions
    :members:
    :undoc-members:
    :show-inheritance: