diff --git a/mpiplayground.py b/mpiplayground.py
index 7079146..0bfa046 100644
--- a/mpiplayground.py
+++ b/mpiplayground.py
@@ -1,84 +1,83 @@
 # DKFZ
 #
 #
 # Copyright (c) German Cancer Research Center,
 # Division of Medical Image Computing.
 # All rights reserved.
 #
 # This software is distributed WITHOUT ANY WARRANTY; without
 # even the implied warranty of MERCHANTABILITY or FITNESS FOR
 # A PARTICULAR PURPOSE.
 #
 # See LICENSE
 
 # A hyppopy minimal example optimizing a simple demo function f(x,y) = x**2+y**2
 
 # import the HyppopyProject class keeping track of inputs
 from hyppopy.BlackboxFunction import BlackboxFunction
 from hyppopy.HyppopyProject import HyppopyProject
 from hyppopy.solvers.RandomsearchSolver import RandomsearchSolver
 from hyppopy.solvers.GridsearchSolver import GridsearchSolver
 from hyppopy.solvers.MPISolverWrapper import MPISolverWrapper
 from hyppopy.MPIBlackboxFunction import MPIBlackboxFunction
 
 # To configure the Hyppopy solver we use a simple nested dictionary with two obligatory main sections,
 # hyperparameter and settings. The hyperparameter section defines your searchspace. Each hyperparameter
 # is again a dictionary with:
 #
 # - a domain ['categorical', 'uniform', 'normal', 'loguniform']
 # - the domain data [left bound, right bound] and
 # - a type of your domain ['str', 'int', 'float']
 #
 # The settings section has two subcategories, solver and custom. The first contains settings for the solver,
 # here 'max_iterations' - is the maximum number of iteration.
 #
 # The custom section allows defining custom parameter. An entry here is transformed to a member variable of the
 # HyppopyProject class. These can be useful when implementing new solver classes or for control your hyppopy script.
 # Here we use it as a solver switch to control the usage of our solver via the config. This means with the script
 # below your can try out every solver by changing use_solver to 'optunity', 'randomsearch', 'gridsearch',...
 # It can be used like so: project.custom_use_plugin (see below) If using the gridsearch solver, max_iterations is
 # ignored, instead each hyperparameter must specifiy a number of samples additionally to the range like so:
 # 'data': [0, 1, 100] which means sampling the space from 0 to 1 in 100 intervals.
 
 config = {
     "hyperparameter": {
         "x": {
             "domain": "normal",
             "data": [-10.0, 10.0],
             "type": float,
             "frequency": 10
         },
         "y": {
             "domain": "uniform",
             "data": [-10.0, 10.0],
             "type": float,
             "frequency": 10
         }
     },
     "max_iterations": 500
 }
 
 project = HyppopyProject(config=config)
 
 
 # The user defined loss function
 def my_loss_function(params):
     x = params['x']
     y = params['y']
     return x**2+y**3
 
 
-bb = BlackboxFunction(blackbox_func=my_loss_function)
 solver = MPISolverWrapper(GridsearchSolver(project))
-blackbox = MPIBlackboxFunction(blackbox_func=bb)
+blackbox = MPIBlackboxFunction(blackbox_func=my_loss_function)
 solver.blackbox = blackbox
 
 solver.run()
 
 df, best = solver.get_results()
 
 if solver.is_master() is True:  # TODO: Find better solution. At the moment it is printed for every worker in the End.
     print("\n")
     print("*" * 100)
     print("Best Parameter Set:\n{}".format(best))
     print("*" * 100)