old_contents: # -*- coding: utf-8 -*-
  '''
  Copyright (c) 2015 by Tobias Houska
  This file is part of Statistical Parameter Estimation Tool (SPOTPY).
  
  :author: Tobias Houska
  
  :paper: Houska, T., Kraft, P., Chamorro-Chavez, A. and Breuer, L.: 
  SPOTting Model Parameters Using a Ready-Made Python Package, 
  PLoS ONE, 10(12), e0145180, doi:10.1371/journal.pone.0145180, 2015.
  
  This package enables the comprehensive use of different Bayesian and Heuristic calibration 
  techniques in one Framework. It comes along with an algorithms folder for the 
  sampling and an analyser class for the plotting of results by the sampling.
  
  :dependencies: - Numpy >1.8 (http://www.numpy.org/) 
                 - Pandas >0.13 (optional) (http://pandas.pydata.org/)
                 - Matplotlib >1.4 (optional) (http://matplotlib.org/) 
                 - CMF (optional) (http://fb09-pasig.umwelt.uni-giessen.de:8000/)
                 - mpi4py (optional) (http://mpi4py.scipy.org/)
                 - pathos (optional) (https://pypi.python.org/pypi/pathos/)
                 - sqlite3 (optional) (https://pypi.python.org/pypi/sqlite3/)
  
                 :help: For specific questions, try to use the documentation website at:
                  http://fb09-pasig.umwelt.uni-giessen.de/spotpy/
  
  For general things about parameter optimization techniques have a look at:
  https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/tree/master/
  
  Pleas cite our paper, if you are using SPOTPY.
  '''
  from . import database
  from . import algorithms
  from . import analyser #Acitivate if you want to have the analyser imported by default (not recommended for High Performance Computing Clusters, because of dependencies on Matplotlib)
  from . import objectivefunctions
  from . import parameter
  from . import examples
  from . import signatures #Acitivate if you want to use hydrological signatures/indices as objective function
  from . import likelihood
  __version__ = '1.3.3'
  
new_contents: # -*- coding: utf-8 -*-
  '''
  Copyright (c) 2015 by Tobias Houska
  This file is part of Statistical Parameter Estimation Tool (SPOTPY).
  
  :author: Tobias Houska
  
  :paper: Houska, T., Kraft, P., Chamorro-Chavez, A. and Breuer, L.: 
  SPOTting Model Parameters Using a Ready-Made Python Package, 
  PLoS ONE, 10(12), e0145180, doi:10.1371/journal.pone.0145180, 2015.
  
  This package enables the comprehensive use of different Bayesian and Heuristic calibration 
  techniques in one Framework. It comes along with an algorithms folder for the 
  sampling and an analyser class for the plotting of results by the sampling.
  
  :dependencies: - Numpy >1.8 (http://www.numpy.org/) 
                 - Pandas >0.13 (optional) (http://pandas.pydata.org/)
                 - Matplotlib >1.4 (optional) (http://matplotlib.org/) 
                 - CMF (optional) (http://fb09-pasig.umwelt.uni-giessen.de:8000/)
                 - mpi4py (optional) (http://mpi4py.scipy.org/)
                 - pathos (optional) (https://pypi.python.org/pypi/pathos/)
                 - sqlite3 (optional) (https://pypi.python.org/pypi/sqlite3/)
  
                 :help: For specific questions, try to use the documentation website at:
                  http://fb09-pasig.umwelt.uni-giessen.de/spotpy/
  
  For general things about parameter optimization techniques have a look at:
  https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/tree/master/
  
  Pleas cite our paper, if you are using SPOTPY.
  '''
  from . import database
  from . import algorithms
  from . import analyser #Acitivate if you want to have the analyser imported by default (not recommended for High Performance Computing Clusters, because of dependencies on Matplotlib)
  from . import objectivefunctions
  from . import parameter
  from . import examples
  from . import signatures #Acitivate if you want to use hydrological signatures/indices as objective function
  from . import likelihoods
  __version__ = '1.3.3'
  
subject: Update __init__.py