ENH: Add support for cross generalization for time_gen

@dengemann @agramfort

This is work in progress, I will let you know when to review it.

Thanks!
Yes

> On 8 oct. 2014, at 19:07, J-R King <notifications@github.com> wrote:
> 
> In mne/decoding/time_gen.py:
> 
> > +
> > +        # Initialize values: Note that this is not an array as the testing
> > +        # times per training time need not be regular
> > +        scores = [[]] * len(self.test_times['slices'])
> > +
> > +        # Loop across training/testing times
> > +        for t_train, slices in enumerate(self.test_times['slices']):
> > +            n_time = len(slices)
> > +            # Loop across testing times
> > +            scores[t_train] = [0] * n_time
> > +            for t, indices in enumerate(slices):
> > +                # Scores across trials
> > +                scores[t_train][t] = _scorer(self.y_true,
> > +                                             self.y_pred[t_train][t],
> > +                                             scorer)
> > +        self.scores = scores
> and self.train_times_, self.test_times_, self.cv_ etc?
> 
> —
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