Scalable energies2

make the Scaling Operator preserve the metric, such that one can temper the likelihood with: likelihood = likelihood.scale(scalar) without breaking the code.

nifty6/operators/scaling_operator.py

@@ -98,5 +98,18 @@ class ScalingOperator(EndomorphicOperator):
         return from_random(random_type="normal", domain=self._domain,
                            std=self._get_fct(from_inverse), dtype=dtype)
 
+    def __call__(self, other):
+        res = EndomorphicOperator.__call__(self, other)
+        if np.isreal(self._factor) and self._factor >= 0:
+            from ..linearization import Linearization
+            if isinstance(other, Linearization):
+                if other.metric is not None:
+                    from .sandwich_operator import SandwichOperator
+                    sqrt_fac = np.sqrt(self._factor)
+                    newop = ScalingOperator(other.metric.domain, sqrt_fac)
+                    met = SandwichOperator.make(newop, other.metric)
+                    res = res.add_metric(met)
+        return res
+
     def __repr__(self):
         return "ScalingOperator ({})".format(self._factor)