[Neuroimaging] [ANN] MNE-Python 0.15
Satrajit Ghosh
satra at mit.edu
Mon Oct 23 12:26:43 EDT 2017
hello
congratulations. the documentation looks really nice!
cheers,
satra
On Fri, Oct 20, 2017 at 3:10 AM, Alexandre Gramfort <
alexandre.gramfort at inria.fr> wrote:
> Hi,
>
> We are very pleased to announce the new 0.15 release of MNE-Python. This
> release comes with new features, bug fixes, and many improvements to
> usability, visualization, and documentation.
>
> A few highlights
>
> ============
>
> -
>
> We reinvented our documentation. Our website now unifies tutorials,
> examples and background information into one coherent narrative structure
> while preserving context. Check it out
> <http://martinos.org/mne/stable/documentation.html>!
>
>
> -
>
> Add mne.decoding.cross_val_multiscore()
> <http://mne-tools.github.io/dev/generated/mne.decoding.cross_val_multiscore.html#mne.decoding.cross_val_multiscore>
> to allow scoring of multiple tasks, typically used with the new
> mne.decoding.SlidingEstimator
> <http://mne-tools.github.io/dev/generated/mne.decoding.SlidingEstimator.html#mne.decoding.SlidingEstimator>
> -
>
> Add mne.decoding.ReceptiveField
> <http://mne-tools.github.io/dev/generated/mne.decoding.ReceptiveField.html#mne.decoding.ReceptiveField>
> module for modeling neural responses to continuous stimulation
> -
>
> Add mne.decoding.SPoC
> <http://mne-tools.github.io/dev/generated/mne.decoding.SPoC.html#mne.decoding.SPoC>
> to fit and apply spatial filters based on continuous target variables
> -
>
> mne.io.Raw.plot()
> <http://mne-tools.github.io/dev/generated/mne.io.Raw.html#mne.io.Raw.plot>
> butterfly mode (toggled with ‘b’ key)
> -
>
> IO support for EGI MFF format
> -
>
> mne.fit_dipole()
> <http://mne-tools.github.io/dev/generated/mne.fit_dipole.html#mne.fit_dipole>
> confidence intervals, number of free parameters, and χ²
> -
>
> Add mne.VectorSourceEstimate
> <http://mne-tools.github.io/dev/generated/mne.VectorSourceEstimate.html#mne.VectorSourceEstimate>
> class which enables working with both source power and dipole orientations;
> use option pick_ori='vector' to mne.minimum_norm.apply_inverse()
> -
>
> New high-frequency somatosensory MEG dataset
> -
>
> Add unit-noise-gain beamformer and neural activity index (weight
> normalization) to LCMV beamformer with weight_norm parameter
> -
>
> Add filtering functions mne.Epochs.filter()
> <https://mne-tools.github.io/dev/generated/mne.Epochs.html#mne.Epochs.filter>
> and mne.Evoked.filter()
> <https://mne-tools.github.io/dev/generated/mne.Evoked.html#mne.Evoked.filter>,
> as well as pad argument to mne.io.Raw.filter()
> <https://mne-tools.github.io/dev/generated/mne.io.Raw.html#mne.io.Raw.filter>
> -
>
> Enable morphing between hemispheres with mne.compute_morph_matrix()
> <https://mne-tools.github.io/dev/generated/mne.compute_morph_matrix.html#mne.compute_morph_matrix>
> -
>
> Add interactive time cursor and category/amplitude status message in
> window for evoked plot
> -
>
> We exposed a rank parameter in mne.viz.evoked.plot_evoked_white()
> <http://martinos.org/mne/dev/generated/mne.viz.plot_evoked_white.html#mne.viz.plot_evoked_white>
> that allows for correcting the scaling of the visualization on the spot in
> cases where the rank estimate of the covariance is not accurate (for
> certain SSS’d data)
>
>
> Notable API changes
>
> ================
>
> -
>
> ICA channel names have now been reformatted to start from zero, e.g.
> "ICA000", to match indexing schemes in mne.preprocessing.ICA
> <http://mne-tools.github.io/dev/generated/mne.preprocessing.ICA.html#mne.preprocessing.ICA>
> -
>
> Add skip_by_annotation to mne.io.Raw.filter()
> <https://mne-tools.github.io/dev/generated/mne.io.Raw.html#mne.io.Raw.filter>
> to process data concatenated with e.g. mne.concatenate_raws()
> <https://mne-tools.github.io/dev/generated/mne.concatenate_raws.html#mne.concatenate_raws>
> separately
> -
>
> Add new filtering mode fir_design='firwin' (default in the next 0.16
> release) that gets improved attenuation using fewer samples compared to
> fir_design='firwin2' (default in 0.15)
> -
>
> Add mne.beamformer.make_lcmv()
> <http://mne-tools.github.io/dev/generated/mne.beamformer.make_lcmv.html#mne.beamformer.make_lcmv>
> and mne.beamformer.apply_lcmv()
> <http://mne-tools.github.io/dev/generated/mne.beamformer.apply_lcmv.html#mne.beamformer.apply_lcmv>,
> mne.beamformer.apply_lcmv_epochs()
> <http://mne-tools.github.io/dev/generated/mne.beamformer.apply_lcmv_epochs.html#mne.beamformer.apply_lcmv_epochs>,
> and mne.beamformer.apply_lcmv_raw()
> <http://mne-tools.github.io/dev/generated/mne.beamformer.apply_lcmv_raw.html#mne.beamformer.apply_lcmv_raw>
> to enable the separate computation and application of LCMV beamformer
> weights
> -
>
> mne.set_eeg_reference()
> <http://mne-tools.github.io/dev/generated/mne.set_eeg_reference.html#mne.set_eeg_reference>
> and related methods (e.g. mne.io.Raw.set_eeg_reference()
> <http://mne-tools.github.io/dev/generated/mne.io.Raw.html#mne.io.Raw.set_eeg_reference>)
> have a new argument projection, which if set to False directly applies
> an average reference instead of adding an SSP projector
> -
>
> mne.find_events()
> <http://mne-tools.github.io/dev/generated/mne.find_events.html#mne.find_events>
> mask_type parameter will change from 'not_and' to 'and' d
> -
>
> picks parameter in mne.beamformer.lcmv()
> <http://mne-tools.github.io/dev/generated/mne.beamformer.lcmv.html#mne.beamformer.lcmv>,
> mne.beamformer.lcmv_epochs()
> <http://mne-tools.github.io/dev/generated/mne.beamformer.lcmv_epochs.html#mne.beamformer.lcmv_epochs>,
> mne.beamformer.lcmv_raw()
> <http://mne-tools.github.io/dev/generated/mne.beamformer.lcmv_raw.html#mne.beamformer.lcmv_raw>,
> mne.beamformer.tf_lcmv()
> <http://mne-tools.github.io/dev/generated/mne.beamformer.tf_lcmv.html#mne.beamformer.tf_lcmv>
> and mne.beamformer.rap_music()
> <http://mne-tools.github.io/dev/generated/mne.beamformer.rap_music.html#mne.beamformer.rap_music>
> is now deprecated
> -
>
> The keyword argument frequencies has been deprecated in favor of freqs
> in various time-frequency functions, e.g.
> mne.time_frequency.tfr_array_morlet()
> <http://mne-tools.github.io/dev/generated/mne.time_frequency.tfr_array_morlet.html#mne.time_frequency.tfr_array_morlet>
> -
>
> Deprecate force_fixed and surf_ori in mne.read_forward_solution()
> <http://mne-tools.github.io/dev/generated/mne.read_forward_solution.html#mne.read_forward_solution>
> -
>
> The behavior of 'mean_flip' label-flipping in
> mne.extract_label_time_course()
> <https://mne-tools.github.io/dev/generated/mne.extract_label_time_course.html#mne.extract_label_time_course>
> and related functions has been changed such that the flip, instead of
> having arbitrary sign, maximally aligns in the positive direction of the
> normals of the label
>
>
> For a full list of improvements and API changes, see:
>
> http://martinos.org/mne/stable/whats_new.html#version-0-15
>
> 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_news
>
> Regards,
>
> The MNE-Python developers
>
> People who contributed to this release (in alphabetical order):
>
> * akshay0724
>
> * Alejandro Weinstein
>
> * Alexander Rudiuk
>
> * Alexandre Barachant
>
> * Alexandre Gramfort
>
> * Andrew Dykstra
>
> * Britta Westner
>
> * Chris Bailey
>
> * Chris Holdgraf
>
> * Christian Brodbeck
>
> * Christopher Holdgraf
>
> * Clemens Brunner
>
> * Cristóbal Moënne-Loccoz
>
> * Daniel McCloy
>
> * Daniel Strohmeier
>
> * Denis A. Engemann
>
> * Emily P. Stephen
>
> * Eric Larson
>
> * Fede Raimondo
>
> * Jaakko Leppakangas
>
> * Jean-Baptiste Schiratti
>
> * Jean-Remi King
>
> * Jesper Duemose Nielsen
>
> * Joan Massich
>
> * Jon Houck
>
> * Jona Sassenhagen
>
> * Jussi Nurminen
>
> * Laetitia Grabot
>
> * Laura Gwilliams
>
> * Luke Bloy
>
> * Lukáš Hejtmánek
>
> * Mainak Jas
>
> * Marijn van Vliet
>
> * Mathurin Massias
>
> * Matt Boggess
>
> * Mikolaj Magnuski
>
> * Nicolas Barascud
>
> * Nicole Proulx
>
> * Phillip Alday
>
> * Ramonapariciog Apariciogarcia
>
> * Robin Tibor Schirrmeister
>
> * Rodrigo Hübner
>
> * S. M. Gutstein
>
> * Simon Kern
>
> * Teon Brooks
>
> * Yousra Bekhti
>
>
>
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>
>
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