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

.. only:: html

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

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

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

.. _sphx_glr_gallery_non_maximum_suppression.py:


Non-Maximum Suppression for Gaussian Pulse Detection
====================================================

This example demonstrates the use of the NonMaximumSuppression class to detect
Gaussian pulses in a one-dimensional signal. It generates a synthetic dataset
of Gaussian pulses, applies the non-maximum suppression algorithm, and plots
the results.

.. GENERATED FROM PYTHON SOURCE LINES 10-33

.. code-block:: Python


    from DeepPeak.algorithms import NonMaximumSuppression
    from DeepPeak.signals import Kernel, SignalDatasetGenerator

    NUM_PEAKS = 3
    SEQUENCE_LENGTH = 400

    gaussian_width = 0.03

    generator = SignalDatasetGenerator(n_samples=1, sequence_length=SEQUENCE_LENGTH)

    dataset = generator.generate(
        signal_type=Kernel.GAUSSIAN,
        n_peaks=(3, 3),
        amplitude=(10, 300),  # Amplitude range
        position=(0.3, 0.7),  # Peak position range
        width=gaussian_width,  # Width range
        noise_std=2,  # Add some noise
        categorical_peak_count=False,
    )

    dataset.plot()




.. image-sg:: /gallery/images/sphx_glr_non_maximum_suppression_001.png
   :alt: non maximum suppression
   :srcset: /gallery/images/sphx_glr_non_maximum_suppression_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 34-35

Configure and run the detector

.. GENERATED FROM PYTHON SOURCE LINES 35-45

.. code-block:: Python

    peak_locator = NonMaximumSuppression(
        gaussian_sigma=0.003,
        threshold="auto",
        maximum_number_of_pulses=5,
        kernel_truncation_radius_in_sigmas=3,
    )

    peak_locator.run(time_samples=dataset.x_values, signal=dataset.signals.squeeze())

    peak_locator.plot()



.. image-sg:: /gallery/images/sphx_glr_non_maximum_suppression_002.png
   :alt: Equal-width Gaussian pulse detection (coarse)
   :srcset: /gallery/images/sphx_glr_non_maximum_suppression_002.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.377 seconds)


.. _sphx_glr_download_gallery_non_maximum_suppression.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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