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

.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_plot_recover_events.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_plot_recover_events.py:


==================================================
Manually Recover Events Not Found by the Algorithm
==================================================
In this example, we use ``pd-parser`` to find photodiode events that
have corrupted pre-event baselines, photodiode plateaus or post-event
baselines but not corrupted onsets or offsets.
Note that it might be a good idea not to recover these events
as there might be noise in the data around this time.

.. GENERATED FROM PYTHON SOURCE LINES 11-16

.. code-block:: default


    # Authors: Alex Rockhill <aprockhill@mailbox.org>
    #
    # License: BSD (3-clause)








.. GENERATED FROM PYTHON SOURCE LINES 17-22

Simulate data and use it to make a raw object

We'll make an `mne.io.Raw` object so that we can save out some random
data with a photodiode event channel in it in fif format (a commonly used
electrophysiology data format).

.. GENERATED FROM PYTHON SOURCE LINES 22-82

.. code-block:: default

    import os.path as op
    import numpy as np
    import mock

    import mne
    from mne.utils import _TempDir

    import pd_parser
    from pd_parser.parse_pd import _load_data

    import matplotlib.pyplot as plt

    out_dir = _TempDir()

    # simulate photodiode data
    np.random.seed(29)
    n_events = 300
    # let's make our photodiode events on random uniform from 0.25 to 0.75 seconds
    n_secs_on = np.random.random(n_events) * 0.5 + 0.25
    raw, beh, events, _ = \
        pd_parser.simulate_pd_data(n_events=n_events, n_secs_on=n_secs_on,
                                   prop_corrupted=0.0)
    sfreq = np.round(raw.info['sfreq']).astype(int)

    # corrupt some events
    corrupted_indices = [8, 144, 234]
    amount = raw._data.max()
    fig, axes = plt.subplots(1, len(corrupted_indices), figsize=(8, 4))
    fig.suptitle('Corrupted Events')
    axes[0].set_ylabel('voltage')
    for j, i in enumerate(events[corrupted_indices, 0]):
        if j == 0:
            raw._data[0, i - sfreq // 5: i - sfreq // 10] = -amount
        elif j == 1:
            raw._data[0, i + sfreq // 4: i + sfreq // 3] = -amount
        else:
            raw._data[0, i + 3 * sfreq // 4: i + 5 * sfreq // 6] = amount
        axes[j].plot(np.linspace(-1, 2, 3 * sfreq),
                     raw._data[0, i - sfreq: i + sfreq * 2])
        axes[j].set_xlabel('time (s)')


    # make figure nicer
    fig.tight_layout()

    # make fake electrophysiology data
    info = mne.create_info(['ch1', 'ch2', 'ch3'], raw.info['sfreq'],
                           ['seeg'] * 3)
    raw2 = mne.io.RawArray(np.random.random((3, raw.times.size)) * 1e-6, info)
    raw.add_channels([raw2])
    raw.info['line_freq'] = 60  # for bids

    # add some offsets to the behavior so it's a bit more realistic
    offsets = np.random.randn(n_events) * 0.001
    beh['time'] = np.array(beh['time']) + offsets

    # save to disk as required by ``pd-parser``, raw needs to have a filename
    fname = op.join(out_dir, 'sub-1_task-mytask_raw.fif')
    raw.save(fname)




.. image-sg:: /auto_examples/images/sphx_glr_plot_recover_events_001.png
   :alt: Corrupted Events
   :srcset: /auto_examples/images/sphx_glr_plot_recover_events_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    Creating RawArray with float64 data, n_channels=1, n_times=2039600
        Range : 0 ... 2039599 =      0.000 ...  2039.599 secs
    Ready.
    Creating RawArray with float64 data, n_channels=3, n_times=2039600
        Range : 0 ... 2039599 =      0.000 ...  2039.599 secs
    Ready.
    Writing /tmp/tmp_mne_tempdir__n31r5wk/sub-1_task-mytask_raw.fif
    Closing /tmp/tmp_mne_tempdir__n31r5wk/sub-1_task-mytask_raw.fif
    [done]




.. GENERATED FROM PYTHON SOURCE LINES 83-91

Find the photodiode events relative to the behavioral timing of interest

This function will use the default parameters to find and align the
photodiode events, recovering the events that we just corrupted.

Note that the mock function mocks user input so when you run the example,
you want to delete that line and unindent the next line, and then provide
your own input depending on whether you want to keep the events or not.

.. GENERATED FROM PYTHON SOURCE LINES 91-96

.. code-block:: default


    with mock.patch('builtins.input', return_value='y'):
        pd_parser.parse_pd(fname, pd_event_name='Stim On', beh=beh, max_len=1.5,
                           pd_ch_names=['pd'], beh_key='time', recover=True)




.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_recover_events_002.png
         :alt: Alignment (First 10), Event Differences
         :srcset: /auto_examples/images/sphx_glr_plot_recover_events_002.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_recover_events_003.png
         :alt: Corrupted Event 8
         :srcset: /auto_examples/images/sphx_glr_plot_recover_events_003.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_recover_events_004.png
         :alt: Corrupted Event 144
         :srcset: /auto_examples/images/sphx_glr_plot_recover_events_004.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_recover_events_005.png
         :alt: Corrupted Event 234
         :srcset: /auto_examples/images/sphx_glr_plot_recover_events_005.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_recover_events_006.png
         :alt: Excluded Events, 8 recovered (not excluded), 144 recovered (not excluded), 234 recovered (not excluded)
         :srcset: /auto_examples/images/sphx_glr_plot_recover_events_006.png
         :class: sphx-glr-multi-img


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

 .. code-block:: none

    Reading in /tmp/tmp_mne_tempdir__n31r5wk/sub-1_task-mytask_raw.fif
    Opening raw data file /tmp/tmp_mne_tempdir__n31r5wk/sub-1_task-mytask_raw.fif...
        Range : 0 ... 2039599 =      0.000 ...  2039.599 secs
    Ready.
    Reading 0 ... 2039599  =      0.000 ...  2039.599 secs...
    Finding photodiode events

      0%|          | 0/606 [00:00<?, ?it/s]
    100%|##########| 606/606 [00:00<00:00, 7220.86it/s]
    301 up-deflection photodiode candidate events found
    Checking best alignments

      0%|          | 0/300 [00:00<?, ?it/s]
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    Best alignment is with the first behavioral event shifted 0.00 s relative to the first synchronization event and has errors: min -3.82 ms, q1 -1.00 ms, med -0.02 ms, q3 0.89 ms, max 3.73 ms, 2 missed events
    Excluding events that have zero close synchronization events or more than one synchronization event within `max_len` time
    8 recovered (not excluded)
    144 recovered (not excluded)
    234 recovered (not excluded)




.. GENERATED FROM PYTHON SOURCE LINES 97-107

Find cessations of the photodiode deflections

Since we manually intervened for the onsets, on those same trials, we'll
have to manually intervene for the offsets.

On the documentation webpage, this is example is not interactive,
but if you download it as a jupyter notebook and run it or copy the code
into a console running python (ipython recommended), you can see how to
interact with the window to accept or reject the recovered events by
following the instructions.

.. GENERATED FROM PYTHON SOURCE LINES 107-112

.. code-block:: default


    # reject the two false deflections in the middle of the second event
    with mock.patch('builtins.input', side_effect=['n'] * 2 + ['y'] * 2):
        pd_parser.add_pd_off_events(fname, max_len=1.5, off_event_name='Stim Off')




.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_recover_events_007.png
         :alt: Corrupted Event 8
         :srcset: /auto_examples/images/sphx_glr_plot_recover_events_007.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_recover_events_008.png
         :alt: Corrupted Event 144
         :srcset: /auto_examples/images/sphx_glr_plot_recover_events_008.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_recover_events_009.png
         :alt: Corrupted Event 144
         :srcset: /auto_examples/images/sphx_glr_plot_recover_events_009.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_recover_events_010.png
         :alt: Corrupted Event 234
         :srcset: /auto_examples/images/sphx_glr_plot_recover_events_010.png
         :class: sphx-glr-multi-img


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

 .. code-block:: none

    Reading in /tmp/tmp_mne_tempdir__n31r5wk/sub-1_task-mytask_raw.fif
    Opening raw data file /tmp/tmp_mne_tempdir__n31r5wk/sub-1_task-mytask_raw.fif...
        Range : 0 ... 2039599 =      0.000 ...  2039.599 secs
    Ready.
    Reading 0 ... 2039599  =      0.000 ...  2039.599 secs...
    Finding photodiode events

      0%|          | 0/606 [00:00<?, ?it/s]
    100%|##########| 606/606 [00:00<00:00, 6930.14it/s]
    301 up-deflection photodiode candidate events found
    8 recovered but discarded
    144 recovered (not excluded)
    234 recovered (not excluded)
    Overwriting existing file.




.. GENERATED FROM PYTHON SOURCE LINES 113-116

Check the results

Finally, we'll check that the recovered events and the original events match.

.. GENERATED FROM PYTHON SOURCE LINES 116-129

.. code-block:: default


    annot = _load_data(fname)[0]
    raw.set_annotations(annot)
    events2, event_id = mne.events_from_annotations(raw)
    on_events = events2[events2[:, 2] == event_id['Stim On']]
    print(f'Original: {events[corrupted_indices, 0]}\n'
          f'Recovered: {on_events[corrupted_indices, 0]}')

    off_events = events2[events2[:, 2] == event_id['Stim Off']]
    original_off = events[corrupted_indices, 0] + \
        np.round(n_secs_on[corrupted_indices] * raw.info['sfreq']).astype(int)
    print(f'Original off: {original_off}\n'
          f'Recovered off: {off_events[corrupted_indices, 0]}')




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

 .. code-block:: none

    Reading in /tmp/tmp_mne_tempdir__n31r5wk/sub-1_task-mytask_raw.fif
    Opening raw data file /tmp/tmp_mne_tempdir__n31r5wk/sub-1_task-mytask_raw.fif...
        Range : 0 ... 2039599 =      0.000 ...  2039.599 secs
    Ready.
    Used Annotations descriptions: ['Stim Off', 'Stim On']
    Original: [  65602  989660 1595483]
    Recovered: [  65601  989659 1595482]
    Original off: [  66236  990198 1596131]
    Recovered off: [  73495  997039 1603414]





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

   **Total running time of the script:** ( 0 minutes  15.498 seconds)


.. _sphx_glr_download_auto_examples_plot_recover_events.py:

.. only:: html

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


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

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

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

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


.. only:: html

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

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