code: def cov(x, lag=0):
      if lag >= x.shape[0]:
          raise ValueError(
              "Not enough observations to compute autocovariance"
          )
      else:
          x1 = x[lag : x.shape[0]]
          x2 = x[0 : (x.shape[0] - lag)]
          return (
              np.sum((x1 - np.mean(x)) * (x2 - np.mean(x)))
              / x1.shape[0]
          )
  
imports: import numpy
  from math import sqrt
label_desc: Use image node_id 1 for calling a global function with example usage: cov(x, lag) and returns: unknown