[Neuroimaging] [ANN] MNE 1.3 Release
Christopher Markiewicz
markiewicz at stanford.edu
Fri Jan 6 12:17:45 EST 2023
Congrats, MNE team!
Chris
________________________________
From: Neuroimaging <neuroimaging-bounces+markiewicz=stanford.edu at python.org> on behalf of Bertrand Thirion <bertrand.thirion at inria.fr>
Sent: Friday, January 6, 2023 12:14
To: neuroimaging at python.org <neuroimaging at python.org>
Subject: Re: [Neuroimaging] [ANN] MNE 1.3 Release
Congrats ! B
Le 06/01/2023 à 18:12, Alexandre Gramfort a écrit :
Hello everyone,
Just before xmas we released MNE-Python 1.3! 🎉 🎁 🎅
Please find a detailed list of changes and contributors below.
Congrts
All the best,
Your MNE Team.
A few highlights
============
* Mixed, cortical + discrete source spaces with fixed orientations are now allowed. (#11241<https://github.com/mne-tools/mne-python/issues/11241> by Jevri Hanna<https://github.com/jshanna100>)
* Add support for image_format='webp' to mne.Report<https://mne.tools/stable/generated/mne.Report.html#mne.Report> when using Matplotlib 3.6+, which can reduce file sizes by up to 50% compared to 'png'. The new default image_format='auto' will automatically use this format if it’s available on the system (#11359<https://github.com/mne-tools/mne-python/issues/11359> by Eric Larson<http://larsoner.com/>)
* Add mne.beamformer.apply_dics_tfr_epochs()<https://mne.tools/stable/generated/mne.beamformer.apply_dics_tfr_epochs.html#mne.beamformer.apply_dics_tfr_epochs> to apply a DICS beamformer to time-frequency resolved epochs (#11096<https://github.com/mne-tools/mne-python/issues/11096> by Alex Rockhill<https://github.com/alexrockhill/>)
* Check whether head radius (estimated from channel positions) is correct when reading EEGLAB data with read_raw_eeglab()<https://mne.tools/stable/generated/mne.io.read_raw_eeglab.html#mne.io.read_raw_eeglab> and read_epochs_eeglab()<https://mne.tools/stable/generated/mne.read_epochs_eeglab.html#mne.read_epochs_eeglab>. If head radius is not within likely values, warn informing about possible units mismatch and the new montage_units argument (#11283<https://github.com/mne-tools/mne-python/issues/11283> by Mikołaj Magnuski<https://github.com/mmagnuski>).
* Add support for a callable passed in combine for mne.time_frequency.AverageTFR.plot<https://mne.tools/stable/generated/mne.time_frequency.AverageTFR.html#mne.time_frequency.AverageTFR.plot> and mne.time_frequency.AverageTFR.plot_joint<https://mne.tools/stable/generated/mne.time_frequency.AverageTFR.html#mne.time_frequency.AverageTFR.plot_joint> (#11329<https://github.com/mne-tools/mne-python/issues/11329> by Mathieu Scheltienne<https://github.com/mscheltienne>)
Notable API changes
================
We have changed a few things that will require you to adjust your code.
* In mne.time_frequency.dpss_windows()<https://mne.tools/stable/generated/mne.time_frequency.dpss_windows.html#mne.time_frequency.dpss_windows>, interpolating is deprecated (nowadays SciPy’s computations are fast enough for large N without interpolation). This affects parameters interp_from and interp_kind. Two new parameters of the underlying SciPy dpss()<https://scipy.github.io/devdocs/reference/generated/scipy.signal.windows.dpss.html#scipy.signal.windows.dpss> function are also exposed: sym (for choosing symmetric vs. periodic windows) and norm (window normalization method). (#11293<https://github.com/mne-tools/mne-python/issues/11293> by Daniel McCloy<http://dan.mccloy.info/>)
* In mne.decoding.CSP.plot_patterns()<https://mne.tools/stable/generated/mne.decoding.CSP.html#mne.decoding.CSP.plot_patterns>, mne.decoding.CSP.plot_filters()<https://mne.tools/stable/generated/mne.decoding.CSP.html#mne.decoding.CSP.plot_filters>, mne.preprocessing.ICA.plot_components()<https://mne.tools/stable/generated/mne.preprocessing.ICA.html#mne.preprocessing.ICA.plot_components>, and mne.viz.plot_ica_components()<https://mne.tools/stable/generated/mne.viz.plot_ica_components.html#mne.viz.plot_ica_components>, the parameters vmin and vmax are deprecated in favor of vlim, for consistency with other topomap-plotting functions and methods (#11371<https://github.com/mne-tools/mne-python/issues/11371> by Daniel McCloy<http://dan.mccloy.info/>)
* In mne.decoding.CSP.plot_patterns()<https://mne.tools/stable/generated/mne.decoding.CSP.html#mne.decoding.CSP.plot_patterns> and mne.decoding.CSP.plot_filters()<https://mne.tools/stable/generated/mne.decoding.CSP.html#mne.decoding.CSP.plot_filters> the titleparameter is deprecated and will be removed in version 1.4 (#11371<https://github.com/mne-tools/mne-python/issues/11371> by Daniel McCloy<http://dan.mccloy.info/>)
* The APIs of mne.preprocessing.ICA.plot_components()<https://mne.tools/stable/generated/mne.preprocessing.ICA.html#mne.preprocessing.ICA.plot_components> and mne.viz.plot_ica_components()<https://mne.tools/stable/generated/mne.viz.plot_ica_components.html#mne.viz.plot_ica_components>gained new parameters show_names, extrapolate, border, size, cnorm, cbar_fmt, axes, nrows, ncols, for consistency with other topomap-plotting functions and methods (#11371<https://github.com/mne-tools/mne-python/issues/11371> by Daniel McCloy<http://dan.mccloy.info/>)
* The APIs of mne.decoding.CSP.plot_patterns()<https://mne.tools/stable/generated/mne.decoding.CSP.html#mne.decoding.CSP.plot_patterns> and mne.decoding.CSP.plot_filters()<https://mne.tools/stable/generated/mne.decoding.CSP.html#mne.decoding.CSP.plot_filters>gained new parameters extrapolate, border, cnorm, axes, nrows, ncols, for consistency with other topomap-plotting functions and methods (#11371<https://github.com/mne-tools/mne-python/issues/11371> by Daniel McCloy<http://dan.mccloy.info/>)
Full list of API changes:
https://mne.tools/stable/whats_new.html#api-changes
Full changelog
===========
For a full list of improvements and API changes, see:
https://mne.tools/stable/whats_new.html
Find the full documentation at https://mne.tools/<https://mne.tools/stable/index.html>
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
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 and on mastodon https://fosstodon.org/@mne
We hope you will enjoy the new features and many, many small improvements we have added, and are looking forward to receiving your feedback.
The MNE-Python developers
Contributors
==========
MNE-Python is a community-driven project. We are always very happy to welcome new contributors of code and documentation! 29 people contributed to this release – and 13 were first-timers! Thank you all so very much for your time and effort, we truly appreciate it!
Release contributors (+ are first time contributors):
* Alex Rockhill
* Alexandre Gramfort
* Britta Westner
* Carlos de la Torre+
* Daniel Hasegan+
* Daniel McCloy
* Dinara Issagaliyeva+
* Enzo Altamiranda+
* Eric Brayet+
* Eric Larson
* Erkka Heinila
* Felix Klotzsche
* Hakimeh Aslsardroud+
* Jennifer Behnke+
* Jevri Hanna
* Lukas Hecker
* Mark Alexander Henney+
* Mathieu Scheltienne
* Mauricio Cespedes+
* Mikołaj Magnuski
* Moritz Gerster
* Omer Shubi+
* Pavel Navratil+
* Richard Höchenberger
* Santeri Ruuskanen+
* Stefan Appelhoff
* Timon Merk
* Tom Ma+
* Toomas Erik Anijärv+
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