fixes

demos/bernoulli_demo.py

@@ -73,7 +73,7 @@ if __name__ == '__main__':
 
     # Minimize the Hamiltonian
     H = ift.Hamiltonian(likelihood, ic_sampling)
-    H = ift.EnergyAdapter(position, H)
+    H = ift.EnergyAdapter(position, H, want_metric=True)
     # minimizer = ift.L_BFGS(ic_newton)
     H, convergence = minimizer(H)
 

demos/getting_started_2.py

@@ -93,7 +93,7 @@ if __name__ == '__main__':
 
     # Minimize the Hamiltonian
     H = ift.Hamiltonian(likelihood)
-    H = ift.EnergyAdapter(position, H)
+    H = ift.EnergyAdapter(position, H, want_metric=True)
     H, convergence = minimizer(H)
 
     # Plot results

demos/polynomial_fit.py

@@ -87,14 +87,14 @@ N = ift.DiagonalOperator(ift.from_global_data(d_space, var))
 IC = ift.GradientNormController(tol_abs_gradnorm=1e-8)
 likelihood = ift.GaussianEnergy(d, N)(R)
 Ham = ift.Hamiltonian(likelihood, IC)
-H = ift.EnergyAdapter(params, Ham)
+H = ift.EnergyAdapter(params, Ham, want_metric=True)
 
 # Minimize
 minimizer = ift.NewtonCG(IC)
 H, _ = minimizer(H)
 
 # Draw posterior samples
-metric = Ham(ift.Linearization.make_var(H.position)).metric
+metric = Ham(ift.Linearization.make_var(H.position, want_metric=True)).metric
 samples = [metric.draw_sample(from_inverse=True) + H.position
            for _ in range(N_samples)]
 

nifty5/minimization/energy_adapter.py

@@ -12,6 +12,7 @@ class EnergyAdapter(Energy):
         super(EnergyAdapter, self).__init__(position)
         self._op = op
         self._constants = constants
+        self._want_metric = want_metric
         if len(self._constants) == 0:
             tmp = self._op(Linearization.make_var(self._position, want_metric))
         else:
@@ -25,7 +26,8 @@ class EnergyAdapter(Energy):
         self._metric = tmp._metric
 
     def at(self, position):
-        return EnergyAdapter(position, self._op, self._constants)
+        return EnergyAdapter(position, self._op, self._constants,
+                             self._want_metric)
 
     @property
     def value(self):