



def    _lowerCAmelCase  (	A__:      list[list[float]]						):


    '''simple docstring'''


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




def    _lowerCAmelCase  (	A__:      list[list[float]]						,		A__:      list[int]						):


    '''simple docstring'''


    UpperCAmelCase      =       []
    for dlist, weight in zip(__UpperCAmelCase						,		__UpperCAmelCase						):
        UpperCAmelCase      =       min(__UpperCAmelCase						)
        UpperCAmelCase      =       max(__UpperCAmelCase						)

        UpperCAmelCase      =       []
        # 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:
            UpperCAmelCase      =       F"""Invalid weight of {weight:f} provided"""
            raise ValueError(__UpperCAmelCase						)

        score_lists.append(__UpperCAmelCase						)

    return score_lists




def    _lowerCAmelCase  (	A__:      list[list[float]]						):


    '''simple docstring'''


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

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

    return final_scores




def    _lowerCAmelCase  (	A__:      list[list[float]]						,		A__:      list[int]						):


    '''simple docstring'''


    UpperCAmelCase      =       get_data(__UpperCAmelCase						)
    UpperCAmelCase      =       calculate_each_score(__UpperCAmelCase						,		__UpperCAmelCase						)
    UpperCAmelCase      =       generate_final_scores(__UpperCAmelCase						)

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

    return source_data












"""simple docstring"""





from random import randint
from tempfile import TemporaryFile

import numpy as np



def   a    (     __UpperCAmelCase      :    Optional[Any]      ,   __UpperCAmelCase      :    Optional[int]      ,   __UpperCAmelCase      :    Optional[int]  )    ->							int:
						__magic_name__:	Optional[int]							=       0
						if start < end:
												__magic_name__:	Union[str, Any]							=       randint(__UpperCAmelCase      ,   __UpperCAmelCase  )
												__magic_name__:	int							=       a[end]
												__magic_name__:	Optional[int]							=       a[pivot]
												__magic_name__:	Tuple							=       temp

												__magic_name__,			__magic_name__:	int							=       _in_place_partition(__UpperCAmelCase      ,   __UpperCAmelCase      ,   __UpperCAmelCase  )
												count += _in_place_quick_sort(__UpperCAmelCase      ,   __UpperCAmelCase      ,   p - 1  )
												count += _in_place_quick_sort(__UpperCAmelCase      ,   p + 1      ,   __UpperCAmelCase  )
						return count



def   a    (     __UpperCAmelCase      :    Optional[Any]      ,   __UpperCAmelCase      :    str      ,   __UpperCAmelCase      :    List[Any]  )    ->							Union[str, Any]:
						__magic_name__:	Union[str, Any]							=       0
						__magic_name__:	str							=       randint(__UpperCAmelCase      ,   __UpperCAmelCase  )
						__magic_name__:	Optional[int]							=       a[end]
						__magic_name__:	Optional[int]							=       a[pivot]
						__magic_name__:	Optional[int]							=       temp
						__magic_name__:	Dict							=       start - 1
						for index in range(__UpperCAmelCase      ,   __UpperCAmelCase  ):
												count += 1
												if a[index] < a[end]:  # check if current val is less than pivot value
																		__magic_name__:	List[Any]							=       new_pivot_index + 1
																		__magic_name__:	Any							=       a[new_pivot_index]
																		__magic_name__:	int							=       a[index]
																		__magic_name__:	Union[str, Any]							=       temp

						__magic_name__:	List[Any]							=       a[new_pivot_index + 1]
						__magic_name__:	Union[str, Any]							=       a[end]
						__magic_name__:	Dict							=       temp
						return new_pivot_index + 1, count


__lowerCamelCase							=  TemporaryFile()
__lowerCamelCase							=  1_00  # 1000 elements are to be sorted


__lowerCamelCase		,					__lowerCamelCase							=  0, 1  # mean and standard deviation
__lowerCamelCase							=  np.random.normal(mu, sigma, p)
np.save(outfile, X)
print('The array is')
print(X)


outfile.seek(0)  # using the same array
__lowerCamelCase							=  np.load(outfile)
__lowerCamelCase							=  len(M) - 1
__lowerCamelCase							=  _in_place_quick_sort(M, 0, r)

print(
    'No of Comparisons for 100 elements selected from a standard normal distribution'
    'is :'
)

print(z)



