FIX Autoreject -> AutoReject + cosmits

doc/faq.rst

@@ -10,24 +10,25 @@ ICA, and finally interpolating the bad data.
 
 To ignore bad segments using autoreject (local), we could do::
 
-	>>> ar = Autoreject()
-	>>> _, reject_log = ar.fit(epochs).transform(epochs)
-	>>> ica.fit(epochs[~reject_log.bad_epochs_idx])
+	>>> ar = AutoReject()
+	>>> _, reject_log = ar.fit(epochs).transform(epochs, return_log=True)
+	>>> ica.fit(epochs[~reject_log.bad_epochs])
 
 or use autoreject (global)::
 
 	>>> reject = get_rejection_threshold(epochs)
 	>>> ica.fit(epochs, reject=reject)
 
-Then, we can apply ICA::
+This option can be more preferred if we would like to fit ICA on the raw
+data, and not on the epochs. After this, we can apply ICA::
 
 	>>> ica.exclude = [5, 7]  # exclude EOG components
 	>>> ica.transform(epochs)
 
 Finally, autoreject could be applied to clean the data::
 
-	>>> ar = Autoreject()
-	>>> epochs_clean = ar.fit(epochs).transform(epochs)
+	>>> ar = AutoReject()
+	>>> epochs_clean = ar.fit_transform(epochs)
 
 Autoreject is not meant for eyeblink artifacts since it affects neighboring
 sensors. Indeed, a spatial filtering method like ICA is better suited for this.
@@ -38,7 +39,7 @@ 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 = Autoreject(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.
@@ -49,6 +50,6 @@ Is it possible to get only bad sensor annotations and not interpolate?
 Yes! Simply do::
 
 	>>> ar.fit(epochs)
-	>>> ar.get_reject_log(epochs)
+	>>> reject_log = ar.get_reject_log(epochs)
 
 No need to run `ar.transform(epochs)` in this case.