code: def _evaluate(self,x):
          '''
          Returns the level of the function at each value in x as the minimum among
          all of the functions.  Only called internally by HARKinterpolator1D.__call__.
          '''
          if _isscalar(x):
              y = np.nanmin([f(x) for f in self.functions])
          else:
              m = len(x)
              fx = np.zeros((m,self.funcCount))
              for j in range(self.funcCount):
                  fx[:,j] = self.functions[j](x)
              y = np.nanmin(fx,axis=1)
          return f _evaluate(self,x):
          '''
          Returns the level of the function at each value in x as the minimum among
          all of the functions.  Only called internally by HARKinterpolator1D.__call__.
          '''
          if _isscalar(x):
              y = np.nanmin([f(x) for f in self.functions])
          else:
              m = len(x)
              fx = np.zeros((m,self.funcCount))
              for j in range(self.funcCount):
                  fx[:,j] = self.functions[j](x)
              y = np.nanmin(fx,axis=1)
          return y
docs: Returns the level of the function at each value in x as the minimum among
          all of the functions.  Only called internally by HARKinterpolator1D.__call__.