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Internal representation (units)

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.. NOTE: part of this file is included in doc/manual/io.rst and

   doc/overview/implementation.rst. Changes here are reflected there. If you

   want to link to this content, link to :ref:`manual-units` for the manual or

   :ref:`units` for the implementation page. The next line is a target for

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Irrespective of the units used in your manufacturer's format, when importing

data, MNE-Python will always convert measurements to the same standard units.

Thus the in-memory representation of data are always in:

- Volts (eeg, eog, seeg, emg, ecg, bio, ecog, dbs)

- Teslas (magnetometers)

- Teslas/meter (gradiometers)

- Amperes*meter (dipole fits, minimum-norm estimates, etc.)

- Moles/liter ("molar"; fNIRS data: oxyhemoglobin (hbo), deoxyhemoglobin (hbr))

- Arbitrary units (various derived unitless quantities)

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Note, however, that most MNE-Python plotting functions will scale the data when

plotted to yield nice-looking axis annotations in a sensible range; for

example, :meth:`mne.io.Raw.plot_psd` will convert teslas to femtoteslas (fT)

and volts to microvolts (µV) when plotting MEG and EEG data.

The units used in internal data representation are particularly important to

remember when extracting data from MNE-Python objects and manipulating it

outside MNE-Python (e.g., when using methods like :meth:`~mne.io.Raw.get_data`

or :meth:`~mne.Epochs.to_data_frame` to convert data to :class:`NumPy arrays

<numpy.ndarray>` or :class:`Pandas DataFrames <pandas.DataFrame>` for analysis

or plotting with other Python modules).