old_contents: """
  .. _ex-read-neo:
  
  How to use data in neural ensemble (NEO) format
  ================================================
  
  This example shows how to create an MNE-Python `~mne.io.Raw` object from data
  in the `neural ensemble <http://neuralensemble.org/neo/>`__ format. For general
  information on creating MNE-Python's data objects from NumPy arrays, see
  :ref:`tut-creating-data-structures`.
  """
  
  # %%
  
  import neo
  import mne
  
  # %%
  # This example uses NEO's ``ExampleIO`` object for creating fake data. The data
  # will be all zeros, so the plot won't be very interesting, but it should
  # demonstrate the steps to using NEO data. For actual data and different file
  # formats, consult the NEO documentation.
  
  reader = neo.io.ExampleIO('fakedata.nof')
  block = reader.read(lazy=False)[0]  # get the first block
  segment = block.segments[0]         # get data from first (and only) segment
  signals = segment.analogsignals[0]  # get first (multichannel) signal
  
  data = signals.rescale('V').magnitude.T
  sfreq = signals.sampling_rate.magnitude
  ch_names = [f'Neo {(idx + 1):02}' for idx in range(signals.shape[1])]
  ch_types = ['eeg'] * len(ch_names)  # if not specified, type 'misc' is assumed
  
  info = mne.create_info(ch_names=ch_names, ch_types=ch_types, sfreq=sfreq)
  raw = mne.io.RawArray(data, info)
  raw.plot(show_scrollbars=False)
  
new_contents: """
  .. _ex-read-neo:
  
  How to use data in neural ensemble (NEO) format
  ================================================
  
  This example shows how to create an MNE-Python `~mne.io.Raw` object from data
  in the `neural ensemble <https://neo.readthedocs.io>`__ format. For general
  information on creating MNE-Python's data objects from NumPy arrays, see
  :ref:`tut-creating-data-structures`.
  """
  
  # %%
  
  import neo
  import mne
  
  # %%
  # This example uses NEO's ``ExampleIO`` object for creating fake data. The data
  # will be all zeros, so the plot won't be very interesting, but it should
  # demonstrate the steps to using NEO data. For actual data and different file
  # formats, consult the NEO documentation.
  
  reader = neo.io.ExampleIO('fakedata.nof')
  block = reader.read(lazy=False)[0]  # get the first block
  segment = block.segments[0]         # get data from first (and only) segment
  signals = segment.analogsignals[0]  # get first (multichannel) signal
  
  data = signals.rescale('V').magnitude.T
  sfreq = signals.sampling_rate.magnitude
  ch_names = [f'Neo {(idx + 1):02}' for idx in range(signals.shape[1])]
  ch_types = ['eeg'] * len(ch_names)  # if not specified, type 'misc' is assumed
  
  info = mne.create_info(ch_names=ch_names, ch_types=ch_types, sfreq=sfreq)
  raw = mne.io.RawArray(data, info)
  raw.plot(show_scrollbars=False)
  
subject: Fix neo link [skip actions] [skip azp] [circle linkcheck] (#10191)