code: def main(readcsv=pd_read_csv):
      data_path = Path(__file__).parent / "data" / "batch"
      infile = data_path / "normalization.csv"
  
      # configure a covariance object
      try:
          algo = d4p.normalization_zscore(doScale=True)
      except NameError:
          algo = d4p.normalization_zscore()
  
      # let's provide a file directly, not a table/array
      result1 = algo.compute(str(infile))
  
      # We can also load the data ourselfs and provide the numpy array
      data = readcsv(infile)
      result2 = algo.compute(data)
  
      # covariance result objects provide correlation, covariance and mean
      assert np.allclose(result1.normalizedData, result2.normalizedData)
  
      return result1
  
imports: from pathlib import Path
  import numpy
  from readcsv import pd_read_csv
  import daal4py
label_desc: Use image node_id 1 for calling a global function with example usage: main(readcsv) and returns: result1