.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/numpy_integration.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_numpy_integration.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_numpy_integration.py:


NumPy integration
=================

It is possible to easily go between numpy and apytypes and therefore also use plotting tools like Matplotlib in an integrated manner.

Consider the example from https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.convolve.html implemented using fixed-point arithmetic

.. GENERATED FROM PYTHON SOURCE LINES 10-25

.. code-block:: Python


    import numpy as np
    from scipy import signal
    from apytypes import APyFixedArray, convolve
    import matplotlib.pyplot as plt

    sig = np.repeat([0.0, 1.0, 0.0], 100)
    sig_fx = APyFixedArray.from_float(sig, 12, 2)

    win = signal.windows.hann(50)
    win_fx = APyFixedArray.from_float(win, 10, 2)

    filtered = signal.convolve(sig, win, mode="same") / sum(win)
    filtered_fx = convolve(sig_fx, win_fx, mode="same") / sum(win_fx)








.. GENERATED FROM PYTHON SOURCE LINES 26-27

The results can then be plotted in Matplotlib

.. GENERATED FROM PYTHON SOURCE LINES 27-43

.. code-block:: Python


    fig, (ax_orig, ax_win, ax_filt) = plt.subplots(3, 1, sharex=True)
    ax_orig.plot(sig)
    ax_orig.plot(sig_fx)
    ax_orig.set_title("Original pulse")
    ax_orig.margins(0, 0.1)
    ax_win.plot(win)
    ax_win.plot(win_fx)
    ax_win.set_title("Filter impulse response")
    ax_win.margins(0, 0.1)
    ax_filt.plot(filtered)
    ax_filt.plot(filtered_fx)
    ax_filt.set_title("Filtered signal")
    ax_filt.margins(0, 0.1)
    fig.tight_layout()
    fig.show()



.. image-sg:: /examples/images/sphx_glr_numpy_integration_001.png
   :alt: Original pulse, Filter impulse response, Filtered signal
   :srcset: /examples/images/sphx_glr_numpy_integration_001.png
   :class: sphx-glr-single-img






.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.549 seconds)


.. _sphx_glr_download_examples_numpy_integration.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: numpy_integration.ipynb <numpy_integration.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: numpy_integration.py <numpy_integration.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: numpy_integration.zip <numpy_integration.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_