.. _`Continuous wavelet transform`:

.. _`com.sympathyfordata.timeseriesanalysis.continous_wavelet_transform`:

Continuous wavelet transform
````````````````````````````

.. image:: fourier.svg
   :width: 48


Decompose a signal into multiple different scales/frequencies and show how that frequency component of the signal varies over time.




Documentation
:::::::::::::

Continuous Wavelet Transform (CWT) is similar to
:ref:`Short Time Fourier Transform<com.sympathyfordata.timeseriesanalysis.spectral_transform>`
in that it reveals the frequency contents of a signal, and also shows how
that frequency content changes over time.


Definition
::::::::::


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

    **time domain**  table
        time domain


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

    **wavelet domain**  table
        wavelet domain




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

    **Rescale output** (rescale)
        Multiplies each scale output with 1/scale as a normalization
    **Number of scales** (scales)
        Number of scale values to generate, always start at scale 1
    **Wavelet** (wavelet)
        Selects wavelet to apply





Related nodes
.............

* :ref:`com.sympathyfordata.timeseriesanalysis.frequency_transform`

* :ref:`com.sympathyfordata.timeseriesanalysis.spectral_transform`




Examples
........

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




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

.. automodule:: node_wavelets
    :noindex:

.. class:: ContinuousWaveletTransform
    :noindex: