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

.. only:: html

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

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

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

.. _sphx_glr_gallery_data_generation.py:


Generating and Visualizing Signal Data
======================================

This example demonstrates how to:
  1. Generate synthetic signals with up to 3 Gaussian pulses.
  2. Compute a Region of Interest (ROI) mask based on pulse positions.
  3. Visualize signals with peak positions, amplitudes, and the ROI mask.

We use:
  - ``generate_signal_dataset`` to create the signals.
  - ``compute_rois_from_signals`` to generate the ROI mask.
  - ``SignalPlotter`` to visualize the results.

.. GENERATED FROM PYTHON SOURCE LINES 18-20

Imports
-------

.. GENERATED FROM PYTHON SOURCE LINES 20-22

.. code-block:: Python

    from DeepPeak.signals import Kernel, SignalDatasetGenerator








.. GENERATED FROM PYTHON SOURCE LINES 23-29

Generate Synthetic Signal Dataset
---------------------------------

We generate a dataset with `NUM_PEAKS` Gaussian pulses per signal.
The peak amplitudes, positions, and widths are randomly chosen within
specified ranges.

.. GENERATED FROM PYTHON SOURCE LINES 29-48

.. code-block:: Python


    NUM_PEAKS = 3
    SEQUENCE_LENGTH = 200
    sample_count = 3

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

    dataset = generator.generate(
        signal_type=Kernel.GAUSSIAN,
        n_peaks=(1, NUM_PEAKS),
        amplitude=(1, 100),  # Amplitude range
        position=(0.1, 0.9),  # Peak position range
        width=(0.03, 0.05),  # Width range
        noise_std=0.1,  # Add some noise
        categorical_peak_count=False,
        compute_region_of_interest=True,
    )

    dataset.plot()



.. image-sg:: /gallery/images/sphx_glr_data_generation_001.png
   :alt: data generation
   :srcset: /gallery/images/sphx_glr_data_generation_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.492 seconds)


.. _sphx_glr_download_gallery_data_generation.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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