DOC updates

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?
 ----------------------------------------------------------------------
 

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