Internal representation (units)

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)

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).