[Neuroimaging] [ANN] MNE-Python 0.23

Wed Apr 28 05:39:48 EDT 2021

Hello everyone,

We are very pleased to announce the new 0.23 release of MNE-Python! 🎈🎈🎈

This release includes 72 pull requests merged as part of our New Developers
Code Sprint in March, and more than a dozen additional contributions from
those new developers after the code sprint.

Big thanks to all who participated! 😍🙏👩🏽‍💻
<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#A-few-highlights>A few highlights
<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#General-infos>General infos

   - The MNE team has started offering regular fortnightly “office ours” on
   Discord to answer user questions. The next office hour will take place this
   Friday at 16:00 UTC. Come say “Hi!” at https://discord.gg/2hF3V4yT9Q
   - The community has now moved to a new forum to answer users’ questions
   and make announcements (e.g., when office hours will be) at
   https://mne.discourse.group/.
   - The documentation at https://mne.tools now features a new theme. We
   are continuously working to improve layout, usability, and accessibility of
   our documentation. If you discover anything you don’t like, that just
   doesn’t work for you, or that might present a barrier to some users, please
   do reach out to us! We’re looking forward to receiving your feedback.

<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#Usability>Usability

   - Gone is the 15-character limitation for channel names when writing
   FIFF files.
   - Raw, Epochs, and Info objects now have a beautiful tabular
   representation in Jupyter Notebooks.
   - Ever wanted to add Annotations to individual channels? This is now
   possible with the new ch_names parameter.
   - Annotations can now be exported to a pandas DataFramevia
   Annotations.to_data_frame().
   - Interested in summary descriptive statistics for all your channels?
   Have a look at the new Raw.describe().
   - Epochs and Evoked now allow you to easily apply transformations to
   their data using the brand-new apply_function() method.
   - Epochs metadata can now be generated automatically from events using
   mne.epochs.make_metadata().
   - Raw.get_data() now has a units parameter to return data in the desired
   unit.

<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#Visualization>Visualization

   - Dark mode! 🦉 Source estimate plots can now detect the operating
   system theme preferences and will apply a dark theme automatically if the
   OS is currently in dark mode. Dark mode can also be activated manually via
   the theme parameter of mne.viz.Brain.
   - Much improved interactive 3D plots in Jupyter Notebooks. (We’re still
   trying to get Jupyter Lab to work nicely as well – it currently behaves
   rather erratically, though!)
   - The new silhouette parameter of mne.viz.Brain can be used to display
   sharp edges and to improve perception.

<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#Source-imaging>Source imaging

   - New method mne.Dipole.to_mni() for more convenient conversion from
   Dipole.pos to MNI.
   - We have a new infant template MRI dataset downloader,
   mne.datasets.fetch_infant_template().
   - Add digitizer information to mne.io.read_raw_egi().
   - We now allow reading digitization from files other than *.fif in the
   coregistration GUI.
   - We managed to speed up mne.inverse_sparse.tf_mixed_norm() using
   STFT/ISTFT linearity.

<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#Data-reading-and-writing>Data
reading and writing

   - Moving over from EEGLAB? No problem! We’ve added support for reading
   new (2021) EEGLAB file format.
   - Moving back to EEGLAB? No problem either! You can now export Raw and
   Epochs to the EEGLAB format, thanks to the new export() methods and the
   eeglabio <https://github.com/jackz314/eeglabio> package.
   - mne.channels.read_custom_montage() got more versatile! It now supports
   CSV, TSV, and XYZ support formats.
   - StarStim / enobio NEDF files can now be read via mne.io.read_raw_nedf()
   .

<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#Channel-types>Channel types

   - There is now a new dbs channel type for deep brain stimulation
   recordings.

<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#Notable-API-changes>Notable API
changes

   - mne.beamformer.tf_dics() has been deprecated
   - The default of real_filter=False in mne.beamformer.make_dics() will
   change to True in the next version of MNE-Python.
   - mne.io.anonymize_info() now also anonymizes the sex and hand fields
   when keep_his=False.
   - Evoked objects have gained a new baseline attribute that is
   automatically assembled based on the baseline of the averaged Epochs.
   - mne.read_selection() has been deprecated in favor of
   mne.read_vectorview_selection().
   - Fitting ICA on baseline-corrected Epochs, and / or applying it on
   baseline-corrected Epochs or Evoked data will now display a warning.

<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#Full-changelog>Full changelog

For a full list of improvements and API changes, see:

https://mne.tools/stable/whats_new.html#version-0-23

Find the full documentation at https://mne.tools/
<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#Installing-the-new-release>Installing
the new release

Since quite a few things – including dependencies – have changed, we
recommend creating a new environment with a “fresh” installation. Please
follow the installation instructions on our website:

https://mne.tools/stable/install/mne_python.html
<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#Feedback>Feedback

As usual, we welcome your bug reports, feature requests, critiques, and
contributions. Development takes place on GitHub. If you would like to
contribute, star the project, or just take a peek at the code, visit
https://github.com/mne-tools/mne-python.

You may follow us on Twitter: https://twitter.com/mne_news

We hope you will enjoy the new features and many, many small improvements
we have added, and are looking forward to receiving your feedback.

Stay safe and take care!

The MNE-Python developers
<https://hackmd.io/vp4CQoASQCCfhUQFW-lUXQ#Contributors>Contributors

MNE-Python is a community-driven project. We are always very happy to
welcome new contributors of code and documentation! 41 people contributed
to this release, and 11 of them contributed for the very first time – thank
you so much for your time and effort, we truly appreciate it!

This is the list of contributors in alphabetical order (first-time
contributors marked with a “+”):

   - Adam Li
   - Alex Rockhill
   - Alexandre Gramfort
   - Ana Radanovic
   - Andres Rodriguez +
   - Anna Padee +
   - Apoorva Karekal +
   - Britta Westner
   - Catalina Magalvan
   - Christian Brodbeck
   - Christian Mista
   - Christian O’Reilly
   - Christina Zhao
   - Christopher J. Bailey
   - Clemens Brunner
   - Cora Kim +
   - Daniel McCloy
   - Denis A. Engemann
   - Dominik Welke +
   - Eduard Ort
   - Enrico Varano +
   - Eric Larson
   - Erica Peterson +
   - Evgenii Kalenkovich
   - Felix Klotzsche +
   - Giorgio Marinato
   - Guillaume Favelier
   - Jack Zhang+
   - Jean-Remi King
   - Johann Benerradi
   - Joris Van den Bossche
   - Judy D Zhu +
   - Liberty Hamilton
   - Luke Bloy
   - Maggie Clarke +
   - Mainak Jas
   - Manorama Kadwani
   - Marijn van Vliet
   - Martin Schulz
   - Matt Sanderson +
   - Matteo Anelli +
   - Nicolas Gensollen
   - Ram Pari +
   - Richard Höchenberger
   - Richard Koehler +
   - Robert Luke
   - Rotem Falach +
   - Sebastien Treguer
   - Silvia Cotroneo +
   - Stefan Appelhoff
   - Steven Bierer
   - Sumalyo Datta +
   - Timon Merk
   - Tristan Stenner
   - Valerii Chirkov+
   - Victoria Peterson
   - Yu-Han Luo
   - Zhi Zhang +
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://mail.python.org/pipermail/neuroimaging/attachments/20210428/184301dc/attachment.html>