[Mne_analysis] [ANN] MNE-Python 0.3 release

[Alexandre Gramfort]

Hi,

A few months after the last release of MNE-python, I am pleased to announce
the new 0.3 release.

This release comes with bug fixes and new features.
See the summary below.

Some work as been done to improve the documentation with a new tutorial:

https://martinos.org/mne/python_tutorial.html

and class/functions reference page:

https://martinos.org/mne/python_reference.html

to find out more rapidly what's available.

A usual we welcome bug reports, feature requests and even more contributions.

Some links;

- http://martinos.org/mne (full MNE documentation with the Python examples)
- https://github.com/mne-tools/mne-python (code + readme on how to install)

Regards,
Alex Gramfort for the MNE-Python developers


Changelog
~~~~~~~~~

   - Sign flip computation for robust label average of signed values
by Alex Gramfort

   - Reading and writing of .w files by Martin Luessi.

   - Support for modifying Raw object and allow raw data preloading
with memory mapping by Martin Luessi and Alex Gramfort

   - Support of arithmetic of Evoked data (useful to concatenate
between runs and compute contrasts) by Alex Gramfort

   - Support for computing sensor space data from a source estimate
using an MNE forward solution by Martin Luessi.

   - Support of arithmetic of Covariance by Alex Gramfort

   - Write BEM surfaces in Python  by Alex Gramfort

   - Filtering operations and apply_function interface for Raw object
by Martin Luessi.

   - Support for complex valued raw fiff files and computation of
analytic signal for Raw object by Martin Luessi.

   - Write inverse operators (surface and volume) by Alex Gramfort

   - Covariance matrix computation with multiple event types by Martin Luessi.

   - New tutorial in the documentation and new classes and functions
reference page by Alex Gramfort

Authors
~~~~~~~

The committer list for this release is the following (preceded by number
of commits):

   * 80  Alexandre Gramfort
   * 51  Martin Luessi