def snv(input_data):

    # Define a new array and populate it with the corrected data
    data_snv = np.zeros_like(input_data)
    for i in range(input_data.shape[0]):

        # Apply correction
        data_snv[i,:] = (input_data[i,:] - np.mean(input_data[i,:])) / np.std(input_data[i,:])

    return data_snv