class_docstr: the Schwartz type 1 stochastic process
  
  :math::
  dx_t = \kappa (\mu - \ln x_t) x_t dt + \sigma x_tdW \
  
  The Schwartz type 1 process is a log of the Ornstein-Uhlenbeck stochastic
  process.
class_docstr_tok: ["the","Schwartz","type","1","stochastic","process",":","math",":",":","dx_t","=","\\kappa","(","\\mu","-","\\ln","x_t",")","x_t","dt","+","\\sigma","x_tdW","\\","The","Schwartz","type","1","process","is","a","log","of","the","Ornstein-Uhlenbeck","stochastic","process","."]
code: def _exactstd(self, expnt):
      return self.sigma * np.sqrt(
          (1 - expnt * expnt) / 2.0 / self.kappa
      )
  
imports: import numpy
  from scipy import stats, signal
  import matplotlib.pyplot
label_desc: Use image node_id 3 for calling the SchwartzOne obj's underlying member method code with example usage: obj._exactstd(expnt) and returns: unknown