code: def has_duplicate_max(x):
      """
      Checks if the maximum value of x is observed more than once
  
      :param x: the time series to calculate the feature of
      :type x: numpy.ndarray
      :return: the value of this feature
      :return type: bool
      """
      if not isinstance(x, (np.ndarray, pd.Series)):
          x = np.asarray(x)
      return np.sum(x == np.max(x)) >= 2
  
imports: import pandas
  import numpy
  from statsmodels.tsa.stattools import acf, adfuller, pacf
  import itertools
  from statsmodels.tsa.ar_model import AR
  from scipy.signal import cwt, find_peaks_cwt, ricker, welch
  from scipy.stats import linregress
  import scipy.stats
  from scipy.stats import kurtosis
  from scipy.stats import skew
  import numpy
  from scipy import signal, integrate
  from scipy.interpolate import interp1d
  import math
  from statsmodels.tools.sm_exceptions import MissingDataError
  from numpy.linalg import LinAlgError
label_desc: Use image node_id 10 for calling a global function with example usage: has_duplicate_max(x) and returns: unknown