:mod:`distancematrix.math_tricks`
=================================

.. py:module:: distancematrix.math_tricks


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   distancematrix.math_tricks.StreamingStats



Functions
~~~~~~~~~

.. autoapisummary::

   distancematrix.math_tricks.sliding_mean_std
   distancematrix.math_tricks.sliding_mean_var


.. function:: sliding_mean_std(series, m)

   Calculates the sliding mean and standard deviation over the series using a window of size m.
   The series should only contain finite values.

   :param series: 1D numpy array
   :param m: sliding window size
   :return: tuple of 2 arrays, each of size (len(series) - m + 1)


.. function:: sliding_mean_var(series, m)

   Calculates the sliding mean and variance over the series using a window of size m.
   The series should only contain finite values.

   :param series: 1D numpy array
   :param m: sliding window size
   :return: tuple of 2 arrays, each of size (len(series) - m + 1)


.. py:class:: StreamingStats(series, m)

   Bases: :class:`object`

   Class that tracks a data stream and corresponding mean and standard deviation of a window over this data.

   The data stream has to be updated by the user, after which the mean/std stream will be updated automatically.

   This class uses RingBuffers internally, so any old view (data, mean, std) should be considered unreliable
   after new data was pushed to this class.

   .. method:: append(self, data)


   .. method:: data(self)
      :property:


   .. method:: mean(self)
      :property:


   .. method:: std(self)
      :property: