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

.. only:: html

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

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

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

.. _sphx_glr__auto_examples_plot_trc_to_fif.py:


==============================
Convert TRC file to mne format
==============================

Here we convert a trc file recorded with a Micromed system to fif, the common
format used in mne framework.

.. GENERATED FROM PYTHON SOURCE LINES 9-14

.. code-block:: Python


    # Author: Etienne de Montalivet <etienne.demontalivet@protonmail.com>
    #
    # License: BSD-3-Clause








.. GENERATED FROM PYTHON SOURCE LINES 15-21

.. code-block:: Python


    from micromed_io.to_mne import create_mne_from_micromed_recording
    from pathlib import Path

    fname = Path("../data/sample.TRC")
    mne_raw = create_mne_from_micromed_recording(fname)




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

 .. code-block:: none

    WARNING:root:MKR channel(s) is not close to 50mV. If no trigger received, then data are corrupted.
    Creating RawArray with float64 data, n_channels=14, n_times=349632
        Range : 0 ... 349631 =      0.000 ...   170.718 secs
    Ready.




.. GENERATED FROM PYTHON SOURCE LINES 22-23

Info from trc file is parsed and stored in mne.Info

.. GENERATED FROM PYTHON SOURCE LINES 23-24

.. code-block:: Python

    mne_raw.info





.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <details open>
        <summary><strong>General</strong></summary>
        <table class="table table-hover table-striped table-sm table-responsive small">
            <tr>
                <th>Measurement date</th>
            
                <td>November 06, 2023  14:35:06 GMT</td>
            
            </tr>
            <tr>
                <th>Experimenter</th>
            
                <td>Unknown</td>
            
            </tr>
            <tr>
                <th>Participant</th>
            
            
                <td>Chb</td>
            
            
            </tr>
        </table>
        </details>
        <details open>
            <summary><strong>Channels</strong></summary>
            <table class="table table-hover table-striped table-sm table-responsive small">
                <tr>
                    <th>Digitized points</th>
                
                    <td>Not available</td>
                
                </tr>
                <tr>
                    <th>Good channels</th>
                    <td>14 EEG</td>
                </tr>
                <tr>
                    <th>Bad channels</th>
                    <td>None</td>
                </tr>
                <tr>
                    <th>EOG channels</th>
                    <td>Not available</td>
                </tr>
                <tr>
                    <th>ECG channels</th>
                    <td>Not available</td>
                </tr>
            </table>
            </details>
            <details open>
                <summary><strong>Data</strong></summary>
                <table class="table table-hover table-striped table-sm table-responsive small">
                
                    <tr>
                        <th>Sampling frequency</th>
                        <td>2048.00 Hz</td>
                    </tr>
                
                
                    <tr>
                        <th>Highpass</th>
                        <td>0.00 Hz</td>
                    </tr>
                
                
                    <tr>
                        <th>Lowpass</th>
                        <td>1024.00 Hz</td>
                    </tr>
                
                
                
                
                </table>
                </details>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 25-28

As you see, markers sent by serial connection to Micromed are
parsed from the trc file and stored as mne.Annotations
scalings: 7e-3 comes from Micromed +/- 3.2mV

.. GENERATED FROM PYTHON SOURCE LINES 28-29

.. code-block:: Python

    mne_raw.plot(scalings=7e-3, duration=20, start=20)



.. image-sg:: /_auto_examples/images/sphx_glr_plot_trc_to_fif_001.png
   :alt: plot trc to fif
   :srcset: /_auto_examples/images/sphx_glr_plot_trc_to_fif_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    Using matplotlib as 2D backend.

    <MNEBrowseFigure size 800x800 with 4 Axes>




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

   **Total running time of the script:** (0 minutes 2.144 seconds)


.. _sphx_glr_download__auto_examples_plot_trc_to_fif.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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