code: def fisher_information(epochs, param=fisher_param):
      def fisher_info_1d(a, tau, de):
          # taken from pyeeg improvements
  
          mat = _embed_seq(a, tau, de)
          W = np.linalg.svd(mat, compute_uv=False)
          W /= sum(W)  # normalize singular values
          FI_v = (W[1:] - W[:-1]) ** 2 / W[:-1]
          return np.sum(FI_v)
  
      return [
          (
              "Tau_{}__DE_{}".format(par["Tau"], par["DE"]),
              np.apply_along_axis(
                  fisher_info_1d, 0, epochs, par["Tau"], par["DE"]
              ).ravel()[0],
          )
          for par in 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 41 for calling a global function with example usage: fisher_information(epochs, param) and returns: unknown, np