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

@@ -86,7 +86,7 @@ def get_curvature_loss(area_factor=1, euclid_factor=0.02, horizontal_factor=0.02
     def curvature_loss(interval, neighbours, scale, function_values):
         triangle_loss_ = triangle_loss(interval, neighbours, scale, function_values)
         default_loss_ = default_loss(interval, scale, function_values)
-        dx = interval[1] - interval[0]
+        dx = interval[1] - interval[0] / scale[0]
         return (area_factor * (triangle_loss_**0.5)
                 + euclid_factor * old_loss
                 + horizontal_factor * dx)