[Mne_analysis] MNE-Python 1.2 released

[Dan McCloy]

        External Email - Use Caution        

Yesterday we released MNE-Python version 1.2, available now on PyPI (https://secure-web.cisco.com/1-J1Erw64cy7mc1y3uDVWKatG1Pz3GK0HJsPvE3yddyF_mvhfMk4tfNHKZKRPz324E6PI83FVUxGRb4xs8bnrygTCEWsmfxj_0TMFzGz9qkWvbHrxyDrVFvaKc033sSBhqkWWrZcSAQU_LaUDUJtmNUcBlIoL8DpvXs2VEuD2zXc6NMEGWz5SAz7Dx7tV9sl9aQ2UD958iiILKvDDg6TAfnAiW-Unxj0gG77vdbSA7FM9GTxHqa-QB2enBiqzn4Mu14g791RydjQ3uUFmaBRBoQqnW7mR18yN-xUJqL2qTERTtUK6OB-j7wTXCHiKl0FzZQSXATao1lov5ICP05EyLA/https%3A%2F%2Fpypi.org%2Fproject%2Fmne%2F1.2.0%2F) and conda-forge.

This release includes contributions from 30 contributors including **11 first-time contributors**: Andrew Quinn, Chetan Gohil, Daniel Carlström Schad, Dominik Wetzel, Hüseyin Orkun Elmas, Julius Welzel, Mats van Es, Moritz Gerster, Sebastiaan Mathot, Sena Er, and luzpaz. Thanks all!

Notable changes:

- new option to compute forward solutions using symmetric BEM method via OpenMEEG (https://secure-web.cisco.com/1106S2YLHk37CzOjcBSQboSleFcjOPORtHZiACJzriWR1YTNdHl8qxNgBImbRtD6BN6C9Tq3sF98rFUwhFmExZk6jyJttBqnN4ZL_kesGh59WsglpA6i3VDJwG5-w2u5JhrLK0k8gx9HBZZoJOC_RDryUby_6BSQrnhG0BacqZuinla3zBL7d0AwVYf0HurBtWoAmrEXgnsvbfsAyuiHM9NzyWQLJpJbttuT7mZkhz-GOuPm5Iy5CI6Dw0sqBrvz60Vs_VBmfm5suK07Ldjhruak61BBjSBc2kp0lhpOmoowg6j9No4DnObK2S2frlwg7W481G2l-aqeefXXBQ9cS-A/https%3A%2F%2Fopenmeeg.github.io%2F)

- new classes Spectrum and EpochsSpectrum created via new methods Raw.compute_psd(), Epochs.compute_psd(), and Evoked.compute_psd(). These replace the functions psd_welch() and psd_multitaper() which are now deprecated.

- new method for ICA objects: get_explained_variance_ratio()

- cross-talk and point-spread can now be computed for vector and volume-vector source estimates

- new class EOGRegression and corresponding example https://secure-web.cisco.com/1eLNlx9UiPbybDENTnkqOJ_XD9_9-q_Jn2j3LD89G0Q8Y7EirwMgrqrJ8zmCEBOprhdz5tm7bReURWaPan7F34NwSizWTLCNvSLYz5sLXsydsCdr7VYzjNXaSAnSnszpBNEtHcmzkf8hVyHieMcb-SVtUgS4R9FvY5-fgNFa6nZMBhonQC4qw-_NgJiFHkGhv8-C8DpjLaLGn3QQm76uAoTgPlbBfCEy7uP7m_HhYddl5uBcb0lqGMB2KmrTLbf9Yice6G4fFy61aWsSUGnuTJEtuasF4p163LpmvB0j7oRqnOK_EarsGZdg5mXuwLxWVaclCVJ4RnPODQsJOOlsYIw/https%3A%2F%2Fmne.tools%2Fstable%2Fauto_examples%2Fpreprocessing%2Feog_regression.html

- common average referencing is now possible with ECoG, sEEG, and DBS data

- parameter standardization for functions and methods that generate topomaps. Most prominently, colormap limits "vmin" and "vmax" are replaced by a tuple "vlim", and the "title" parameter is deprecated (use matplotlib's ax.set_title() or fig.suptitle() instead).

- new channel types "temperature" and "gsr" (galvanic skin response)

The full changelog is available here: https://secure-web.cisco.com/1_DvHX04MJ6zz00nOmK-Yzuvonp7VgwOGHESZRgT04xZek71eDlP6DOXvUpYDeeHSb5tbfJfRK1Rx8_zzuYCXieDpivcMVNApr7gLalnLpS5VRu8si0myP62wHTzuy0U9sthz-gy-R6CVMJ7l4KN6ogBsDim78anQVDp17xRDUL1TTNNKhXfgIfav4LYrfoGRM9kZSrVq7LRo92akFd_TlTgQvVtSPEssUC8ZC4REQVVaQigJKTyj7xIxYFsXgvaOocBUh49-_yB7IfhfI3mDhPxVQlUHew_TSDK-Ur_MyEqsm8wzp17nmp8-qXha87fZxHewkWpH8C6SUIP4ZyOFRg/https%3A%2F%2Fmne.tools%2Fdev%2Fwhats_new.html%23version-1-2-0-2022-10-11

As always, please feel free to ask usage questions on our Discourse forum (https://secure-web.cisco.com/1FZjkOKu1MlGjIXcipUnGcALAdlSdJ4knXQlx0PJI0HbX_HDpcNMsuI2PNl2yen7B3a9r47xlNFQVm9dMLveuJZzh5c-eU6y6ruQ5d_QzJfnNF-IaNDGVSmA6gmBTb58FnBvlNddKA60gCpAizJhhpb47NuP-1SEV6XxOL6MABGujzzOBpKS8Ze_FyUXACV3zcQx1-ND8ig2AjFU7iGJlSjxIGoZoHLBAgNYRg1GgrjAElZRmQzmvLlFw-pgKvELmlhvnXqeX748FSD6-D8d_wxdDDUIg__zMVqiJnuLfW_D_ufnqtc-_sw1BsBHGuXur__QU59mU9PxTNYLnUX0xzw/https%3A%2F%2Fmne.discourse.group) or during bi-weekly office hours on our Discord server (https://secure-web.cisco.com/1VixGxvR51gEyF5tSiHtkYcKDw_sLVRXvxLI69b4t4twXDIL7BokcIvkBh6Zf0imufAkLBFOjRIjtxkE_tSFQDRq8szYcX6pBvGFEj4oOU6ldT7veoZObIk76y9KGiRgwtGC-cOSikNTDEFAxtfiqEPs_QzKwoI7Rofk_sEod8uWmcgrzUi1YHlCdWLC8UHFctlpguEkanOoWFjSIxKqddcxbRpLaMMWUsi_tejlgv82aIXy6qMo3_gYIXFxmJtFbY_eWjO0ijoBBhwBNItBGlnbHmEgFwC3DZJ9Vo9St6RVuaFJCdMlMggsoTqMsNrowP4iS19-4wWxzmgxStOtMjA/https%3A%2F%2Fdiscord.gg%2FrKfvxTuATa), and report bugs and feature requests on our GitHub repository (https://secure-web.cisco.com/18scX2iGFArh9qrMZ9IW1Ia5awvRfq30vrbqiVl5OYNWzkuWKi1IzdK9rJK7itRm4Ij4Un7yci-Gp1sInDKEfjNHY9Kw-BwK8xx04Vq2_I8NW-RmzZRnLBrjWySLlFOP2enTSvrkb90BfNDBQzNNU1EoosLACRenfwAdRlbr1TcO2YJB9eNLfOtpO5aJP-K9yJmCYvfVLBUStyLYOoNsAN_6QsWZaAbSSAAYrcHdakmZbqcXvGBKs07WR3Wz7v7LfYt-PKXYtwePsPNzNd2XhxUUgQx4QmF4XQ-PdPyvcxDoUC0KwqG_uVZ8FfSRF3NZpnW6dzVNGVXlWBdyaRAu0rw/https%3A%2F%2Fgithub.com%2Fmne-tools%2Fmne-python%2Fissues%2Fnew%2Fchoose).

-- dan
Daniel McCloy
https://secure-web.cisco.com/1ZoecI8me8wWI9fO--ZHaFFCpO27l0ubgYiwRDbHxLyb030mqpfN4MNOvptBg8XJsSY1iUTLS1Y4O9e4Q2kwHNtbFlZgPQd21u_Y3DUNxJ0xKMUyr5zJqpHyxayg77uJ_Nj46enIYPEF6qYUlEMejXI7mAWznXVq-Zaxf8iQoM6xYjsKqHP2mY3Lu1fSW43AuD7sYiykLiDhDeegn0P2E_ro4Q-RsvPVJTtCesak5lJD61Kr8hjOh0QNUZMAdGw5IFM6yP8OLobs5ld8dV8KsQyzldz1PhSzNojWX4rphc08ig5_97PYc7rttlCQB62q8T8a9thG1F7RZRgIcTvsTLA/https%3A%2F%2Fdan.mccloy.info
Research Scientist
Institute for Learning and Brain Sciences
University of Washington