





from random import randint
from tempfile import TemporaryFile

import numpy as np





def   lowerCAmelCase_				( __a			,					__a			,					__a	)  ->	Any:







  """simple docstring"""





  lowerCamelCase__:   Optional[Any]    						=0
  if start < end:
    lowerCamelCase__:   Tuple    						=randint(__lowerCAmelCase			,					__lowerCAmelCase	)
    lowerCamelCase__:   Union[str, Any]    						=a[end]
    lowerCamelCase__:   List[Any]    						=a[pivot]
    lowerCamelCase__:   int    						=temp

    lowerCamelCase__:   Union[str, Any]    						=_in_place_partition(__lowerCAmelCase			,					__lowerCAmelCase			,					__lowerCAmelCase	)
    count += _in_place_quick_sort(__lowerCAmelCase			,					__lowerCAmelCase			,					p - 1	)
    count += _in_place_quick_sort(__lowerCAmelCase			,					p + 1			,					__lowerCAmelCase	)
  return count





def   lowerCAmelCase_				( __a			,					__a			,					__a	)  ->	Union[str, Any]:







  """simple docstring"""





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

  lowerCamelCase__:   Optional[Any]    						=a[new_pivot_index + 1]
  lowerCamelCase__:   Optional[Any]    						=a[end]
  lowerCamelCase__:   Tuple    						=temp
  return new_pivot_index + 1, count


__A             =       TemporaryFile()
__A             =       100  # 1000 elements are to be sorted


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


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

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







print(z)








from bisect import bisect
from itertools import accumulate





def   lowerCAmelCase_				( __a			,					__a			,					__a			,					__a	)  ->	List[Any]:







  """simple docstring"""





  lowerCamelCase__:   str    						=sorted(zip(__a			,					__a	)			,					key=lambda __a	: x[0] / x[1]			,					reverse=__a	)
  lowerCamelCase__						,      lowerCamelCase__:   str    						=[i[0] for i in r], [i[1] for i in r]
  lowerCamelCase__:   Tuple    						=list(accumulate(__a	)	)
  lowerCamelCase__:   Any    						=bisect(__a			,					__a	)
  return (
      0
      if k == 0
      else sum(vl[:k]	) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
      if k != n
      else sum(vl[:k]	)
  )


if __name__ == "__main__":
     import doctest

     doctest.testmod()

