old_contents: '''
  Created on Nov 14, 2012
  
  @author: dstrauss
  
  Simple routine to do optimization over 3D! 
  
  '''
  
  
  import numpy as np
  D = {'solverType':'contrastX', 'flavor':'TE3D', 'numRuns':2, 'expt':'huge', 'numProcs':1}
  
  
  def getMyVars(parseNumber, D):
      '''routine to return the parameters to test at the current iteration.'''
      
      
      # D['rho'] = 0.00001
      # D['xi'] = 1e-9
      D['freqs'] = np.array([1e3])
      D['inc'] = np.array([75*np.pi/180])
      D['bkgNo'] =  0
      D['numProcs'] = 1
      D['maxIter'] = 2
      D['lmb'] = 1e-13
      
      return D
new_contents: '''
  Created on Nov 14, 2012
  
  @author: dstrauss
  
  Simple routine to do optimization over 3D! 
  
  '''
  
  
  import numpy as np
  D = {'solverType':'contrastX', 'flavor':'TE3D', 'numRuns':2, 'expt':'huge', 'numProcs':1}
  
  
  def getMyVars(parseNumber, D):
      '''routine to return the parameters to test at the current iteration.'''
      
      
      # D['rho'] = 0.00001
      # D['xi'] = 1e-9
      D['freqs'] = np.array([1e3])
      D['inc'] = np.array([75*np.pi/180])
      D['bkgNo'] =  0
      D['numProcs'] = 1
      if parseNumber == 0:
          D['maxIter'] = 1
      else:
          D['maxIter'] = 2
          
      D['lmb'] = 1e-13
      
      return D
subject: split for 1 and 2 iterations!.