Resolve "(Learner1D) add possibility to use the direct neighbors in the loss"

Closes #119 (closed)

Currently works for one R^1 \to R^1

Still have to make it work for R^1 \to R^N

Also performance is actually quite good. As in: the learner slows down about 1.5 times. Going (on my laptop) from 3 seconds per 1000 points to 4.5 seconds per 1000 points.

Which, I believe, will be more than compensated by the fact that the chosen points are generally better

adaptive/learner/learner1D.py

@@ -59,7 +59,7 @@ def default_loss(interval, scale, function_values):
 
 def _loss_of_multi_interval(xs, ys):
     pts = list(zip(xs, ys))
-    N = len(pts)-2
+    N = len(pts) - 2
     return sum(volume(pts[i:i+3]) for i in range(N)) / N