import numpy as np

from numpy.typing import ArrayLike

from typing import List, Union

def normalize(

input_data: List[float],

calibration_data: Union[List[float], ArrayLike],

) -> List[float]:

"""normalizes by dividing by `calibration_data` and also applies SNV_transform"""

input_data = np.asarray(input_data)

calibration_data = np.asarray(calibration_data)

# scale by calibration measurement

data_rescaled = input_data / calibration_data

data_snv = SNV_transform(data_rescaled)

return list(data_snv)

def SNV_transform(data: Union[ArrayLike, List[float]]) -> List[float]:

# the following is an SNV transform

# Subtract the mean and divide by the standarddiviation

return list((np.asarray(data) - np.mean(data)) / np.std(data))

def list_to_string(data: List[float]) -> str:

return " ".join([f"{i:.7f}" for i in data])