.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "tutorials/widgets/plot_4_peaks_gallery.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_tutorials_widgets_plot_4_peaks_gallery.py>`
        to download the full example code.

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

.. _sphx_glr_tutorials_widgets_plot_4_peaks_gallery.py:


Peaks Widgets Gallery
=====================

Some widgets are useful before sorting and works with the "peaks" given by the detect_peaks()
function.

They are useful to check drift before running sorters.

.. GENERATED FROM PYTHON SOURCE LINES 11-16

.. code-block:: Python


    import matplotlib.pyplot as plt

    import spikeinterface.full as si








.. GENERATED FROM PYTHON SOURCE LINES 17-19

First, let's download a simulated dataset
from the repo 'https://gin.g-node.org/NeuralEnsemble/ephy_testing_data'

.. GENERATED FROM PYTHON SOURCE LINES 19-24

.. code-block:: Python


    local_path = si.download_dataset(remote_path="mearec/mearec_test_10s.h5")
    rec, sorting = si.read_mearec(local_path)









.. GENERATED FROM PYTHON SOURCE LINES 25-26

Let's filter and detect peaks on it

.. GENERATED FROM PYTHON SOURCE LINES 26-45

.. code-block:: Python


    from spikeinterface.sortingcomponents.peak_detection import detect_peaks

    rec_filtred = si.bandpass_filter(recording=rec, freq_min=300.0, freq_max=6000.0, margin_ms=5.0)
    print(rec_filtred)
    peaks = detect_peaks(
        recording=rec_filtred,
        method="locally_exclusive",
        peak_sign="neg",
        detect_threshold=6,
        exclude_sweep_ms=0.3,
        radius_um=100,
        noise_levels=None,
        random_chunk_kwargs={},
        chunk_memory="10M",
        n_jobs=1,
        progress_bar=True,
    )





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    BandpassFilterRecording: 32 channels - 32.0kHz - 1 segments - 320,000 samples - 10.00s 
                             float32 dtype - 39.06 MiB
    /home/docs/checkouts/readthedocs.org/user_builds/spikeinterface/checkouts/3072/src/spikeinterface/core/job_tools.py:103: UserWarning: `n_jobs` is not set so parallel processing is disabled! To speed up computations, it is recommended to set n_jobs either globally (with the `spikeinterface.set_global_job_kwargs()` function) or locally (with the `n_jobs` argument). Use `spikeinterface.set_global_job_kwargs?` for more information about job_kwargs.
      warnings.warn(

    noise_level:   0%|          | 0/20 [00:00<?, ?it/s]
    noise_level:  15%|#5        | 3/20 [00:00<00:00, 24.96it/s]
    noise_level:  30%|###       | 6/20 [00:00<00:00, 24.88it/s]
    noise_level:  45%|####5     | 9/20 [00:00<00:00, 24.94it/s]
    noise_level:  60%|######    | 12/20 [00:00<00:00, 24.88it/s]
    noise_level:  75%|#######5  | 15/20 [00:00<00:00, 24.85it/s]
    noise_level:  90%|######### | 18/20 [00:00<00:00, 24.87it/s]
    noise_level: 100%|##########| 20/20 [00:00<00:00, 24.89it/s]

    detect peaks using locally_exclusive:   0%|          | 0/5 [00:00<?, ?it/s]
    detect peaks using locally_exclusive:  20%|##        | 1/5 [00:00<00:02,  1.58it/s]
    detect peaks using locally_exclusive:  40%|####      | 2/5 [00:01<00:01,  1.61it/s]
    detect peaks using locally_exclusive:  60%|######    | 3/5 [00:01<00:00,  2.50it/s]
    detect peaks using locally_exclusive:  80%|########  | 4/5 [00:01<00:00,  3.37it/s]
    detect peaks using locally_exclusive: 100%|##########| 5/5 [00:01<00:00,  3.25it/s]




.. GENERATED FROM PYTHON SOURCE LINES 46-47

peaks is a numpy 1D array with structured dtype that contains several fields:

.. GENERATED FROM PYTHON SOURCE LINES 47-52

.. code-block:: Python


    print(peaks.dtype)
    print(peaks.shape)
    print(peaks.dtype.fields.keys())





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    [('sample_index', '<i8'), ('channel_index', '<i8'), ('amplitude', '<f8'), ('segment_index', '<i8')]
    (749,)
    dict_keys(['sample_index', 'channel_index', 'amplitude', 'segment_index'])




.. GENERATED FROM PYTHON SOURCE LINES 53-55

This "peaks" vector can be used in several widgets, for instance
plot_peak_activity()

.. GENERATED FROM PYTHON SOURCE LINES 55-60

.. code-block:: Python


    si.plot_peak_activity(recording=rec_filtred, peaks=peaks)

    plt.show()




.. image-sg:: /tutorials/widgets/images/sphx_glr_plot_4_peaks_gallery_001.png
   :alt: Probe - 32ch - 1shanks
   :srcset: /tutorials/widgets/images/sphx_glr_plot_4_peaks_gallery_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 61-62

can be also animated with bin_duration_s=1.

.. GENERATED FROM PYTHON SOURCE LINES 62-67

.. code-block:: Python


    si.plot_peak_activity(recording=rec_filtred, peaks=peaks, bin_duration_s=1.0)


    plt.show()



.. image-sg:: /tutorials/widgets/images/sphx_glr_plot_4_peaks_gallery_002.png
   :alt: Probe - 32ch - 1shanks
   :srcset: /tutorials/widgets/images/sphx_glr_plot_4_peaks_gallery_002.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 3.608 seconds)


.. _sphx_glr_download_tutorials_widgets_plot_4_peaks_gallery.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: plot_4_peaks_gallery.ipynb <plot_4_peaks_gallery.ipynb>`

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

      :download:`Download Python source code: plot_4_peaks_gallery.py <plot_4_peaks_gallery.py>`

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

      :download:`Download zipped: plot_4_peaks_gallery.zip <plot_4_peaks_gallery.zip>`


.. only:: html

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

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