Metadata-Version: 1.1
Name: nmb-eeg
Version: 1.0
Summary: Power spectra of pure EEG from two temporarily paralysed subjects from Whitham et al 2007
Home-page: https://github.com/berndporr/nmb_eeg
Author: Bernd Porr
Author-email: bernd.porr@glasgow.ac.uk
License: GPL 3.0
Description: Pure EEG power during paralysis
        ===============================
        
        Power spectra of pure EEG from two temporarily paralysed subjects.
        
        Data from (Fig 1, B-traces):
        
        `Scalp electrical recording during paralysis: Quantitative evidence that
        EEG frequencies above 20 Hz are contaminated by EMG
        Emma M. Whitham, Kenneth J. Pope, Sean P. Fitzgibbon, Trent Lewis,
        C. Richard Clark, Stephen Loveless, Marita Broberg, Angus Wallace,
        Dylan DeLosAngeles, Peter Lillie, Andrew Hardy, Rik.
        Clinical Neurophysiology Volume 118, Issue 8, August 2007,
        Pages 1877-1888. <https://www.sciencedirect.com/science/article/abs/pii/S1388245707001988>`_
        
        Please cite as "Data from ..." as outlined above. This has been advised by Elsevier's Copyrights Coordinator.
        
        
        Usage
        -----
        
        To obtain the average PSD over all experiments just use
        the default constructor::
        
          p = NMB_EEG_From_WhithamEtAl()
        
        
        If you want to extract the PSD of dataset one do::
        
          p = NMB_EEG_From_WhithamEtAl(1)
        
        
        Obtain the power spectral density in V^2/Hz use::
        
          psd = p.EEGVariance(f)
        
        where `f` can be either a single frequency or a numpy array.
        The lowest permitted frequency is
        `f_signal_min` and the highest `f_signal_max`.
        
        The total power of the entire frequency range from `f_signal_min` to `f_signal_max` is::
        
          totalEEGPower = p.totalEEGPower()
        
        
        Because `EEGVariance(f)` accepts a numpy array plotting the spectrum is simply::
        
          f = np.linspace(p.f_signal_min,p.f_signal_max,100)
          plt.plot(f,p.EEGVariance(f))
        
        
        
        Usage example
        -------------
        
        Run::
        
          plot_paralysed_EEG_PSD.py
        
        from the github page: https://github.com/berndporr/nmb_eeg
        
        
        Credit
        ------
        
        Bernd Porr <bernd.porr@glasgow.ac.uk>
        
        
        
        .. image:: https://zenodo.org/badge/529194569.svg
           :target: https://zenodo.org/badge/latestdoi/529194569
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
