text: from precise.skatertools.syntheticdata.miscellaneous import create_correlated_dataset
  from precise.skaters.covariance.runemp import run_emp_pcov_d0
  from pprint import pprint
  from precise.skaters.covarianceutil.covfunctions import cov_to_corrcoef
  from precise.skaters.covarianceutil.statemutations import both_cov
  
  # Basic example of running empirical sample correlation
  
  if __name__=='__main__':
      ys = create_correlated_dataset(n=500)
      s = {}
      for y in ys:
          x, x_cov, s = run_emp_pcov_d0(s=s, y=y)  # <---
      s = both_cov(s)  # <--- Peek in the state and converts scov to pcov
      scorr = cov_to_corrcoef(s['scov'])
      pprint(scorr)    # Sample correlation
  