old_contents: '''
  Created on 27 Jul. 2011
  
  This file illustrated the use the EMA classes for a model in Excel.
  
  It used the excel file provided by
  `A. Sharov <http://home.comcast.net/~sharov/PopEcol/lec10/fullmod.html>`_
  
  This excel file implements a simple predator prey model.
  
  .. codeauthor:: jhkwakkel <j.h.kwakkel (at) tudelft (dot) nl>
  '''
  from ema_workbench import (RealParameter, TimeSeriesOutcome, ema_logging,
                             perform_experiments)
  
  from ema_workbench.connectors.excel import ExcelModel
  from ema_workbench.em_framework.evaluators import MultiprocessingEvaluator
  
  
  if __name__ == "__main__":
      ema_logging.log_to_stderr(level=ema_logging.INFO)
  
      model = ExcelModel("predatorPrey", wd="./models/excelModel",
                         model_file='excel example.xlsx')
      model.uncertainties = [RealParameter("K2", 0.01, 0.2),  # we can refer to a cell in the normal way
                             # we can also use named cells
                             RealParameter("KKK", 450, 550),
                             RealParameter("rP", 0.05, 0.15),
                             RealParameter("aaa", 0.00001, 0.25),
                             RealParameter("tH", 0.45, 0.55),
                             RealParameter("kk", 0.1, 0.3)]
  
      # specification of the outcomes
      model.outcomes = [TimeSeriesOutcome("B4:B1076"),  # we can refer to a range in the normal way
                        TimeSeriesOutcome("P_t")]  # we can also use named range
  
      # name of the sheet
      model.sheet = "Sheet1"
  
      with MultiprocessingEvaluator(model) as evaluator:
          results = perform_experiments(model, 100, reporting_interval=1,
                                        evaluator=evaluator)
  
new_contents: '''
  Created on 27 Jul. 2011
  
  This file illustrated the use the EMA classes for a model in Excel.
  
  It used the excel file provided by
  `A. Sharov <http://home.comcast.net/~sharov/PopEcol/lec10/fullmod.html>`_
  
  This excel file implements a simple predator prey model.
  
  .. codeauthor:: jhkwakkel <j.h.kwakkel (at) tudelft (dot) nl>
  '''
  from ema_workbench import (RealParameter, TimeSeriesOutcome, ema_logging,
                             perform_experiments)
  
  from ema_workbench.connectors.excel import ExcelModel
  from ema_workbench.em_framework.evaluators import MultiprocessingEvaluator
  
  
  if __name__ == "__main__":
      ema_logging.log_to_stderr(level=ema_logging.INFO)
  
      model = ExcelModel("predatorPrey", wd="./models/excelModel",
                         model_file='excel example.xlsx')
      model.uncertainties = [RealParameter("K2", 0.01, 0.2),  # we can refer to a cell in the normal way
                             # we can also use named cells
                             RealParameter("KKK", 450, 550),
                             RealParameter("rP", 0.05, 0.15),
                             RealParameter("aaa", 0.00001, 0.25),
                             RealParameter("tH", 0.45, 0.55),
                             RealParameter("kk", 0.1, 0.3)]
  
      # specification of the outcomes
      model.outcomes = [TimeSeriesOutcome("B4:B1076"),  # we can refer to a range in the normal way
                        TimeSeriesOutcome("P_t")]  # we can also use named range
  
      # name of the sheet
      model.default_sheet = "Sheet1"
  
      with MultiprocessingEvaluator(model) as evaluator:
          results = perform_experiments(model, 100, reporting_interval=1,
                                        evaluator=evaluator)
  
subject: Update excel_example.py