code: def simOnePrd(self):
          '''
          Simulate one period of the fashion victom model for this type.  Each
          agent receives an idiosyncratic preference shock and chooses whether to
          change styles (using the optimal decision rule).
  
          Parameters
          ----------
          none
  
          Returns
          -------
          none
          '''
          pNow    = self.pNow
          sPrev   = self.sNow
          J2Pprob = self.switchFuncJock(pNow)
          P2Jprob = self.switchFuncPunk(pNow)
          Shks    = self.RNG.rand(self.pop_size)
          J2P     = np.logical_and(sPrev == 0,Shks < J2Pprob)
          P2J     = np.logical_and(sPrev == 1,Shks < P2Jprob)
          sNow    = copy(sPrev)
          sNow[J2P] = 1
          sNow[P2J] = 0
          self.sNow = sNof simOnePrd(self):
          '''
          Simulate one period of the fashion victom model for this type.  Each
          agent receives an idiosyncratic preference shock and chooses whether to
          change styles (using the optimal decision rule).
  
          Parameters
          ----------
          none
  
          Returns
          -------
          none
          '''
          pNow    = self.pNow
          sPrev   = self.sNow
          J2Pprob = self.switchFuncJock(pNow)
          P2Jprob = self.switchFuncPunk(pNow)
          Shks    = self.RNG.rand(self.pop_size)
          J2P     = np.logical_and(sPrev == 0,Shks < J2Pprob)
          P2J     = np.logical_and(sPrev == 1,Shks < P2Jprob)
          sNow    = copy(sPrev)
          sNow[J2P] = 1
          sNow[P2J] = 0
          self.sNow = sNow
docs: Simulate one period of the fashion victom model for this type.  Each
          agent receives an idiosyncratic preference shock and chooses whether to
          change styles (using the optimal decision rule).
  
          Parameters
          ----------
          none
  
          Returns
          -------
          none