[Mne_analysis] [ANN] MNE-Python 0.14

[Alexandre Gramfort]

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

* Cristóbal Moënne-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 Höchenberger

* Sheraz Khan

* Stefan Repplinger

* Teon Brooks

* Yaroslav Halchenko
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