code: def _embed_seq(X, Tau, D):
      N = len(X)
      if D * Tau > N:
          print("Cannot build such a matrix, because D * Tau > N")
          exit()
      if Tau < 1:
          print("Tau has to be at least 1")
          exit()
      Y = np.zeros((N - (D - 1) * Tau, D))
  
      for i in range(0, N - (D - 1) * Tau):
          for j in range(0, D):
              Y[i][j] = X[i + j * Tau]
      return Y
  
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 29 for calling a global function with example usage: _embed_seq(X, Tau, D) and returns: Y