code: def svd_entropy(epochs, param=svd_param):
      axis = 0
  
      final = []
      for par in param:
  
          def svd_entropy_1d(X, Tau, DE):
              Y = _embed_seq(X, Tau, DE)
              W = np.linalg.svd(Y, compute_uv=0)
              W /= sum(W)  # normalize singular values
              return -1 * np.sum(W * np.log(W))
  
          Tau = par["Tau"]
          DE = par["DE"]
  
          final.append(
              np.apply_along_axis(
                  svd_entropy_1d, axis, epochs, Tau, DE
              ).ravel()[0]
          )
  
      return [
          ('Tau_"{}"__De_{}"'.format(par["Tau"], par["DE"]), final[en])
          for en, par in enumerate(param)
      ]
  
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 30 for calling a global function with example usage: svd_entropy(epochs, param) and returns: unknown, unknown