.. _`Piecewise Aggregation Analysis (PAA)`:

.. _`com.sympathyfordata.timeseriesanalysis.piecewise_aggregation_analysis`:

Piecewise Aggregation Analysis (PAA)
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.. image:: paa.svg
   :width: 48


Applies the Piecewise Aggregation Analysis (PAA) algorithm on a table, treating each column as a single time-series. Splits the time-series into a number of bins and returns the aggregate within each bin. Typical choice of aggregate function is the average.





Definition
::::::::::


Input ports
...........

    **input**  table
        input


Output ports
............

    **output**  table
        output




Configuration
.............

    **Aggregate** (aggregate)
        Selects aggregate function to apply to each bin
    **Output bin number** (bin_numbers)
        Generates one column for row in the input data containing the bin number that row was given (without padding)
    **Bins** (bins)
        Number of output bins or number of samples per bin
    **Fixed bin size** (fixed)
        Uses bins of a fixed size instead of a fixed number of bins.
    **Binning method** (inclusion)
        Method for determining the value selection for each bin

        uneven : allows a different number of value in each bin if input length is not a multiple of bins

        pad-first : pads the input data with copies of the first value

        pad-last : pads the input data with copies of the last value

        overlapping : guarantees that all bins have the same

        number of samples but samples may fit multiple bins
    **Output indices** (indices)
        Outputs two columns with the start/stop index for each bin. Indices start at zero.Stop index is the first row that is NOT included in the given bin







Examples
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* :download:`select_intervals.syx </Examples/Time Series/select_intervals.syx>`




Implementation
..............

.. automodule:: node_paa_sax
    :noindex:

.. class:: PiecewiseAggregationAnalysis
    :noindex: