From 5c3b7ebdfd21b38f550642e0f02cf5112d2d1adb Mon Sep 17 00:00:00 2001 From: Mainak Jas Date: Sun, 10 Jun 2018 10:24:44 +0200 Subject: [PATCH] DOC updates --- doc/faq.rst | 23 +++-------------------- doc/index.rst | 4 ++-- 2 files changed, 5 insertions(+), 22 deletions(-) diff --git a/doc/faq.rst b/doc/faq.rst index b2e9d52d..ff43b2be 100644 --- a/doc/faq.rst +++ b/doc/faq.rst @@ -8,7 +8,7 @@ ICA solutions can be affected by high amplitude artifacts, therefore we recommend first using autoreject to detect the bad segments, then applying ICA, and finally interpolating the bad data:: - >>> ar = LocalAutorejectCV() + >>> ar = Autoreject() >>> ar.fit(epochs) >>> ica.fit(epochs[~ar.reject_log.bad_epochs_idx]) >>> ica.exclude = [5, 7] # exclude EOG components @@ -18,34 +18,17 @@ ICA, and finally interpolating the bad data:: Autoreject is not meant for eyeblink artifacts since it affects neighboring sensors. Indeed, a spatial filtering method like ICA is better suited for this. -How do I manually set the `n_interpolate` and `consensus_percs` parameter? +How do I manually set the `n_interpolate` and `consensus` parameter? -------------------------------------------------------------------------- If you do not want autoreject to select a parameter for you, simply pass it as a list of a single element:: - >>> ar = LocalAutorejectCV(n_interpolate=[1], consensus_percs=[0.6]) + >>> ar = Autoreject(n_interpolate=[1], consensus_percs=[0.6]) Note this will still run a cross-validation loop to generate the validation score. -What if I do not know the channel locations? --------------------------------------------- - -While autoreject will still work, the solution may not be optimal. The channel -locations are needed for generating augmented trials which is a necessary -ingredient of the algorithm. If you are working with EEG data, you can use MNE -to set a standard montage:: - - # code for setting montage - -Does autoreject also interpolate user-marked bad channels? ----------------------------------------------------------- - -No, autoreject ignores the bad channels in `epochs.info['bads']` by default. -However, it is possible to explicitly ask autoreject to work on all the channels -(including those marked as bad by the user) by using the `picks` argument. - Is it possible to get only bad sensor annotations and not interpolate? ---------------------------------------------------------------------- diff --git a/doc/index.rst b/doc/index.rst index 7cc9fd43..eac36a82 100644 --- a/doc/index.rst +++ b/doc/index.rst @@ -40,8 +40,8 @@ in your script: .. code:: python - >>> from autoreject import LocalAutoRejectCV - >>> ar = LocalAutoRejectCV() + >>> from autoreject import AutoReject + >>> ar = AutoReject() >>> epochs_clean = ar.fit_transform(epochs) # doctest: +SKIP This will automatically clean an `epochs` object read in using MNE-Python. To get the