[Mne_analysis] [ANN] MNE-Python 0.14

Fri Mar 24 06:55:01 EDT 2017

Hi Buddy,

Wonderful work, you guys truly rocks!!!!!

See you in NYC on Monday.

Best,

Sheraz

> Hi,
>
> We are pleased to announce the new 0.14 release of MNE-Python. As usual
> this release comes with new features, bug fixes, and many improvements to
> usability, visualization, and documentation.
>
> A few highlights
>
> ============
>
>    -
>
>    We have added I/O support for Artemis123
>    <http://martinos.org/mne/stable/generated/mne.io.read_raw_artemis123.html>
>    infant/toddler MEG data
>    -
>
>    We no longer require MNE-C for BEM and scalp processing steps
>    -
>
>    Interactive annotation
>    <http://martinos.org/mne/stable/generated/mne.Annotations.html> mode is
>    now available in raw plotting
>    -
>
>    Dipole locations can now be visualized with MRI slice overlay
>    <http://martinos.org/mne/stable/auto_tutorials/plot_dipole_fit.html>
>    -
>
>    Add minimum-phase filtering option in mne.io.Raw.filter()
>    <http://martinos.org/mne/stable/generated/mne.io.Raw.html#mne.io.Raw.filter>
>    -
>
>    New mne.datasets.visual_92_categories
>    <http://martinos.org/mne/stable/python_reference.html#module-mne.datasets.visual_92_categories>
>    dataset with an example of Representational Similarity Analysis (RSA)
>    <http://martinos.org/mne/stable/auto_examples/decoding/decoding_rsa.html#sphx-glr-auto-examples-decoding-decoding-rsa-py>
>
>
> Notable API changes
>
> ================
>
>    -
>
>    Fix bug with DICS and LCMV (functions mne.beamformer.lcmv
>    <http://martinos.org/mne/stable/generated/mne.beamformer.lcmv.html> and
>    mne.beamformer.dics
>    <http://martinos.org/mne/stable/generated/mne.beamformer.dics.html>)
>    where regularization was done improperly. The default reg=0.01 has been
>    changed to reg=0.05
>    -
>
>    The filtering functions band_pass_filter, band_stop_filter,
>    low_pass_filter, and high_pass_filter have been deprecated in favor of
>    mne.filter.filter_data
>    <http://martinos.org/mne/stable/generated/mne.filter.filter_data.html>
>    -
>
>    mne.decoding.Scaler
>    <http://martinos.org/mne/stable/generated/mne.decoding.Scaler.html> now
>    scales each channel independently using data from all time points
> (epochs
>    and times) instead of scaling all channels for each time point. It also
> now
>    accepts parameter scalings to determine the data scaling method
> (default is
>    None to use static channel-type-based scaling)
>    -
>
>    The default tmax=60. In mne.io.Raw.plot_psd
>    <http://martinos.org/mne/stable/generated/mne.io.Raw.html?highlight=plot_psd#mne.io.Raw.plot_psd>
>    will change to tmax=np.inf in 0.15
>    -
>
>    The mne.decoding.LinearModel
>    <http://martinos.org/mne/stable/generated/mne.decoding.LinearModel.html#mne.decoding.LinearModel>
>    class will no longer support plot_filters and plot_patterns, use
>    mne.EvokedArray
>    <http://martinos.org/mne/stable/generated/mne.EvokedArray.html> with
>    mne.decoding.get_coef
>    <http://martinos.org/mne/stable/generated/mne.decoding.get_coef.html>
>    instead
>    -
>
>    Made functions mne.time_frequency.tfr_array_multitaper
>    <http://martinos.org/mne/stable/generated/mne.time_frequency.tfr_array_multitaper.html>,
>    mne.time_frequency.tfr_array_morlet
>    <http://martinos.org/mne/stable/generated/mne.time_frequency.tfr_array_morlet.html>,
>    mne.time_frequency.tfr_array_stockwell
>    <http://martinos.org/mne/stable/generated/mne.time_frequency.tfr_array_stockwell.html>,
>    mne.time_frequency.psd_array_multitaper
>    <http://martinos.org/mne/stable/generated/mne.time_frequency.psd_array_multitaper.html>
>    and mne.time_frequency.psd_array_welch
>    <http://martinos.org/mne/stable/generated/mne.time_frequency.psd_array_welch.html>
>    public to allow computing TFRs and PSDs on numpy arrays
>    -
>
>    mne.preprocessing.ICA.fit
>    <http://martinos.org/mne/stable/generated/mne.preprocessing.ICA.html#mne.preprocessing.ICA.fit>
>    now rejects data annotated bad by default when working with Raw.
>
>
> For a full list of improvements and API changes, see:
>
> http://martinos.org/mne/stable/whats_new.html#version-0-14
>
> To install the latest release the following command should do the job:
>
> pip install --upgrade --user mne
>
> As usual we welcome your bug reports, feature requests, critiques, and
>
> contributions.
>
> Some links:
>
> - https://github.com/mne-tools/mne-python (code + readme on how to
> install)
>
> - http://martinos.org/mne/stable/ (full MNE documentation)
>
> Follow us on Twitter: https://twitter.com/mne_python
>
> Regards,
>
> The MNE-Python developers
>
> People who contributed to this release  (in alphabetical order):
>
> * Alexander Rudiuk
>
> * Alexandre Gramfort
>
> * Annalisa Pascarella
>
> * Antti Rantala
>
> * Asish Panda
>
> * Burkhard Maess
>
> * Chris Holdgraf
>
> * Christian Brodbeck
>
> * CristÃ³bal MoÃ«nne-Loccoz
>
> * Daniel McCloy
>
> * Denis A. Engemann
>
> * Eric Larson
>
> * Erkka Heinila
>
> * Hermann Sonntag
>
> * Jaakko Leppakangas
>
> * Jakub Kaczmarzyk
>
> * Jean-Remi King
>
> * Jon Houck
>
> * Jona Sassenhagen
>
> * Jussi Nurminen
>
> * Keith Doelling
>
> * Leonardo S. Barbosa
>
> * Lorenz Esch
>
> * Lorenzo Alfine
>
> * Luke Bloy
>
> * Mainak Jas
>
> * Marijn van Vliet
>
> * Matt Boggess
>
> * Matteo Visconti
>
> * Mikolaj Magnuski
>
> * Niklas Wilming
>
> * Paul Pasler
>
> * Richard HÃ¶chenberger
>
> * Sheraz Khan
>
> * Stefan Repplinger
>
> * Teon Brooks
>
> * Yaroslav Halchenko
> _______________________________________________
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> Mne_analysis at nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis

-------------------------
Sheraz Khan, M.Eng, Ph.D.
Instructor in Neurology

Athinoula A. Martinos Center for Biomedical Imaging
Massachusetts General Hospital
Harvard Medical School

McGovern Institute for Brain Research
Massachusetts Institute of Technology

Tel:   +1 617-643-5634
Fax:   +1 617-948-5966
Email: sheraz at nmr.mgh.harvard.edu
       sheraz at mit.edu
Web:   http://sheraz.mit.edu