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a guest Feb 16th, 2019 70 Never
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  1. def snv(input_data):
  2.  
  3.     # Define a new array and populate it with the corrected data  
  4.     data_snv = np.zeros_like(input_data)
  5.     for i in range(input_data.shape[0]):
  6.  
  7.         # Apply correction
  8.         data_snv[i,:] = (input_data[i,:] - np.mean(input_data[i,:])) / np.std(input_data[i,:])
  9.  
  10.     return data_snv
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