some changes and relaxed newton

nifty/minimization/line_searching/line_search.py

@@ -24,7 +24,7 @@ from nifty import LineEnergy
 
 
 class LineSearch(Loggable, object):
-    """Class for finding a step size.
+    """Class for determining the optimal step size along some descent direction.
     
     Initialize the line search procedure which can be used by a specific line
     search method. Its finds the step size in a specific direction in the

nifty/minimization/quasi_newton_minimizer.py

@@ -26,18 +26,16 @@ from .line_searching import LineSearchStrongWolfe
 
 
 class QuasiNewtonMinimizer(Loggable, object):
-    """A Class used by other minimization methods to find local minimum.
+    """A class used by other minimization methods to find a local minimum.
     
-    Quasi-Newton methods are used to find local minima or maxima of a function
-    by approximating the Jacobian or Hessian matrix at every iteration. The 
-    class performs general steps(gets the gradient, descend direction, step 
-    size and checks the conergence) which can be used then by a specific 
-    minimization method.
+    Descent minimization methods are used to find a local minimum of a scalar function
+    by following a descent direction. This class implements the minimization procedure,
+    the descent direction has to be implemented separately.
     
     Parameters
     ----------
     line_searcher : callable
-        Function which finds the step size into the descent direction. (default:
+        Function which finds the step size in descent direction. (default:
         LineSearchStrongWolfe())
     callback : function, *optional*
         Function f(energy, iteration_number) specified by the user to print 
@@ -94,7 +92,7 @@ class QuasiNewtonMinimizer(Loggable, object):
         """Runs the minimization on the provided Energy class.
 
         Accepts the NIFTY Energy class which describes our system and it runs 
-        the minimization to find the minimum/maximum of the system.
+        the minimization to find the minimum of the system.
         
         Parameters
         ----------
@@ -104,7 +102,7 @@ class QuasiNewtonMinimizer(Loggable, object):
 
         Returns
         -------
-        x : field
+        x : Field
             Latest `energy` of the minimization.
         convergence : integer
             Latest convergence level indicating whether the minimization

nifty/minimization/relaxed_newton.py

@@ -51,12 +51,26 @@ class RelaxedNewton(QuasiNewtonMinimizer):
         self.line_searcher.prefered_initial_step_size = 1.
 
     def _get_descend_direction(self, energy):
+        """ Calculates the descent direction according to a Newton scheme.
+        The descent direction is determined by weighting the gradient at the
+        current parameter position with the inverse local curvature, provided by the
+        Energy object.
+
+        Parameters
+        ----------
+        energy : Energy
+            The energy object providing implementations of the to be minimized function,
+            its gradient and curvature.
+
+        Returns
+        -------
+        out : Field
+           Returns the descent direction with proposed step length. In a quadratic
+            potential this corresponds to the optimal step.
+
+        """
         gradient = energy.gradient
         curvature = energy.curvature
         descend_direction = curvature.inverse_times(gradient)
         return descend_direction * -1
-        #norm = descend_direction.norm()
-#        if norm != 1:
-#            return descend_direction / -norm
-#        else:
-#            return descend_direction * -1
+