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","."]
docstr: uses exact solution for log of process
          
docstr_tok: ["uses","exact","solution","for","log","of","process"]
code: def exactprocess(self, xzero, nobs, ddt=1.0, nrepl=2):
      """uses exact solution for log of process"""
      lnxzero = np.log(xzero)
      lnx = super(self.__class__, self).exactprocess(
          xzero, nobs, ddt=ddt, nrepl=nrepl
      )
      return np.exp(lnx)
  
imports: import numpy
  from scipy import stats, signal
  import matplotlib.pyplot
label_desc: Use image node_id 4 for calling the SchwartzOne obj's underlying member method code with example usage: obj.exactprocess(xzero, nobs, ddt, nrepl) and returns: np