mt_metadata.features.striding_window_coherence
==============================================

.. py:module:: mt_metadata.features.striding_window_coherence


Classes
-------

.. autoapisummary::

   mt_metadata.features.striding_window_coherence.StridingWindowCoherence


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

.. py:class:: StridingWindowCoherence(**data)

   Bases: :py:obj:`mt_metadata.features.coherence.Coherence`


   Computes coherence for each sub-window (FFT window) across the time series.
   Returns a 2D array: (window index, frequency).


   .. py:attribute:: subwindow
      :type:  Annotated[mt_metadata.processing.window.Window, Field(default_factory=Window, description='The window used for the subwindow coherence calculation.', json_schema_extra={'units': None, 'required': False, 'examples': ['hann', 'hamming', 'blackman']})]


   .. py:method:: set_defaults(data)
      :classmethod:



   .. py:method:: set_subwindow_from_window(fraction=0.2)

      Set the subwindow as a fraction of the main window.



   .. py:method:: compute(ts_1, ts_2, parallel = False)

      For each main window (length self.window.num_samples, stride self.window.num_samples_advance),
      compute coherence using the subwindow parameters (self.subwindow) within that main window.
      :returns: 1D array of frequencies
                coherences: 2D array (n_main_windows, n_frequencies)
      :rtype: frequencies