docs: def corr_coeff(x1, x2, t, tau1, tau2):
      """Compute lagged correlation coefficient for two time series."""
      dt = t[1] - t[0]
      tau = np.arange(tau1, tau2+dt, dt)
      rho = np.zeros(len(tau))
      for n in range(len(tau)):
          i = np.abs(int(tau[n]/dt))
          if tau[n] >= 0: # Positive lag, push x2 forward in time
              seg2 = x2[0:-1-i]
              seg1 = x1[i:-1]
          elif tau[n] < 0: # Negative lag, push x2 back in time
              seg1 = x1[0:-i-1]
              seg2 = x2[i:-1]
          seg1 = seg1 - seg1.mean()
          seg2 = seg2 - seg2.mean()
          rho[n] = np.mean(seg1*seg2)/seg1.std()/seg2.std()
      return tau, rho