from __future__ import annotations



def   __A		(			_A							,				_A					):



 """simple docstring"""


 __a       =  sorted(numsa + numsa					)
 __a       ,     __a       =  divmod(len(_A					)							,				2					)
 if mod == 1:
  return all_numbers[div]
 else:
  return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 SCREAMING_SNAKE_CASE :	Optional[int]							     =		[float(x) for x in input("""Enter the elements of first array: """).split()]
 SCREAMING_SNAKE_CASE :	Union[str, Any]							     =		[float(x) for x in input("""Enter the elements of second array: """).split()]
 print(f'''The median of two arrays is: {median_of_two_arrays(array_a, array_a)}''')



def   __A		(			_A					):



 """simple docstring"""


 __a       =  []
 for data in source_data:
  for i, el in enumerate(_A					):
   if len(_A					) < i + 1:
    data_lists.append([]					)
   data_lists[i].append(float(_A					)					)
 return data_lists



def   __A		(			_A							,				_A					):



 """simple docstring"""


 __a       =  []
 for dlist, weight in zip(_A							,				_A					):
  __a       =  min(_A					)
  __a       =  max(_A					)

  __a       =  []
  # for weight 0 score is 1 - actual score
  if weight == 0:
   for item in dlist:
    try:
     score.append(1 - ((item - mind) / (maxd - mind))					)
    except ZeroDivisionError:
     score.append(1					)

  elif weight == 1:
   for item in dlist:
    try:
     score.append((item - mind) / (maxd - mind)					)
    except ZeroDivisionError:
     score.append(0					)

        # weight not 0 or 1
  else:
   __a       =  f"""Invalid weight of {weight:f} provided"""
   raise ValueError(_A					)

  score_lists.append(_A					)

 return score_lists



def   __A		(			_A					):



 """simple docstring"""


 __a       =  [0 for i in range(len(score_lists[0]					)					)]

 for slist in score_lists:
  for j, ele in enumerate(_A					):
   __a       =  final_scores[j] + ele

 return final_scores






def   __A		(			_A							,				_A					):



 """simple docstring"""


 __a       =  get_data(_A					)
 __a       =  calculate_each_score(_A							,				_A					)
 __a       =  generate_final_scores(_A					)

 # append scores to source data
 for i, ele in enumerate(_A					):
  source_data[i].append(_A					)

 return source_data


