introducing constants_sampling for MPI paralllel KL

nifty5/minimization/kl_energy.py

@@ -45,16 +45,20 @@ class KL_Energy_MPI(Energy):
                  h,
                  nsamp,
                  constants=[],
+                 constants_samples=None,
                  _samples=None,
                  want_metric=False):
         super(KL_Energy_MPI, self).__init__(position)
         self._h = h
         self._nsamp = nsamp
         self._constants = constants
+        if constants_samples is None:
+            constants_samples = constants
+        self._constants_samples = constants_samples
         self._want_metric = want_metric
         if _samples is None:
             lo, hi = _shareRange(nsamp, ntask, rank)
-            met = h(Linearization.make_var(position, True)).metric
+            met = h(Linearization.make_partial_var(position, constants_samples, True)).metric
             _samples = []
             for i in range(lo, hi):
                 np.random.seed(i)
@@ -73,7 +77,7 @@ class KL_Energy_MPI(Energy):
 
     def at(self, position):
         return KL_Energy_MPI(position, self._h, self._nsamp, self._constants,
-                             self._samples, self._want_metric)
+                             self._constants_samples, self._samples, self._want_metric)
 
     @property
     def value(self):