

'''simple docstring'''







from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm
def    UpperCAmelCase__     (   UpperCAmelCase__,							UpperCAmelCase__					)      ->      float:
       return math.sqrt(sum(pow(a - b,							2					) for a, b in zip(UpperCAmelCase__,							UpperCAmelCase__					)					)					)
def    UpperCAmelCase__     (   UpperCAmelCase__,							UpperCAmelCase__					)      ->      list[list[list[float] | float]]:

       if dataset.ndim != value_array.ndim:
              A_						       =   (
                  """Wrong input data's dimensions... """
                  F'''dataset : {dataset.ndim}, value_array : {value_array.ndim}'''
              )
              raise ValueError(UpperCAmelCase__					)

       try:
              if dataset.shape[1] != value_array.shape[1]:
                     A_						       =   (
                         """Wrong input data's shape... """
                         F'''dataset : {dataset.shape[1]}, value_array : {value_array.shape[1]}'''
                     )
                     raise ValueError(UpperCAmelCase__					)
       except IndexError:
              if dataset.ndim != value_array.ndim:
                     raise TypeError("""Wrong shape"""					)

       if dataset.dtype != value_array.dtype:
              A_						       =   (
                  """Input data have different datatype... """
                  F'''dataset : {dataset.dtype}, value_array : {value_array.dtype}'''
              )
              raise TypeError(UpperCAmelCase__					)

       A_						       =   []

       for value in value_array:
              A_						       =   euclidean(UpperCAmelCase__,							dataset[0]					)
              A_						       =   dataset[0].tolist()

              for dataset_value in dataset[1:]:
                     A_						       =   euclidean(UpperCAmelCase__,							UpperCAmelCase__					)

                     if dist > temp_dist:
                            A_						       =   temp_dist
                            A_						       =   dataset_value.tolist()

              answer.append([vector, dist]					)

       return answer
def    UpperCAmelCase__     (   UpperCAmelCase__,							UpperCAmelCase__					)      ->      float:
       return np.dot(UpperCAmelCase__,							UpperCAmelCase__					) / (norm(UpperCAmelCase__					) * norm(UpperCAmelCase__					))


if __name__ == "__main__":
      import doctest

      doctest.testmod()



'''simple docstring'''







from bisect import bisect
from itertools import accumulate
def    UpperCAmelCase__     (   UpperCAmelCase__,							UpperCAmelCase__,							UpperCAmelCase__,							UpperCAmelCase__					)      ->      Dict:
       A_						       =   sorted(zip(UpperCAmelCase__,							UpperCAmelCase__					),							key=lambda UpperCAmelCase__					: x[0] / x[1],							reverse=UpperCAmelCase__					)
       A_       ,      A_						       =   [i[0] for i in r], [i[1] for i in r]
       A_						       =   list(accumulate(UpperCAmelCase__					)					)
       A_						       =   bisect(UpperCAmelCase__,							UpperCAmelCase__					)
       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()
