





"""simple docstring"""


def 					lowercase__    (					)					->		list[list[int]]:




      """simple docstring"""

      return [list(range(1_000 - i		,-1_000 - i		,-1			)			) for i in range(1_000			)]


lowerCamelCase__				  =   generate_large_matrix()
lowerCamelCase__				  =   (
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)




def 					lowercase__    (					lowercase_			)					->		None:




      """simple docstring"""

      assert all(row == sorted(lowercase_		,reverse=lowercase_			) for row in grid			)
      assert all(list(lowercase_			) == sorted(lowercase_		,reverse=lowercase_			) for col in zip(*lowercase_			)			)




def 					lowercase__    (					lowercase_			)					->		int:




      """simple docstring"""

      _UpperCamelCase      :	Optional[Any]						=       0
      _UpperCamelCase      :	str						=       len(lowercase_			) - 1

      # Edge cases such as no values or all numbers are negative.
      if not array or array[0] < 0:
            return 0

      while right + 1 > left:
            _UpperCamelCase      :	Dict						=       (left + right) // 2
            _UpperCamelCase      :	str						=       array[mid]

            # Num must be negative and the index must be greater than or equal to 0.
            if num < 0 and array[mid - 1] >= 0:
                  return mid

            if num >= 0:
                  _UpperCamelCase      :	Optional[Any]						=       mid + 1
            else:
                  _UpperCamelCase      :	List[Any]						=       mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
      return len(lowercase_			)




def 					lowercase__    (					lowercase_			)					->		int:




      """simple docstring"""

      _UpperCamelCase      :	Any						=       0
      _UpperCamelCase      :	List[str]						=       len(grid[0]			)

      for i in range(len(lowercase_			)			):
            _UpperCamelCase      :	List[str]						=       find_negative_index(grid[i][:bound]			)
            total += bound
      return (len(lowercase_			) * len(grid[0]			)) - total




def 					lowercase__    (					lowercase_			)					->		int:




      """simple docstring"""

      return len([number for row in grid for number in row if number < 0]			)




def 					lowercase__    (					lowercase_			)					->		int:




      """simple docstring"""

      _UpperCamelCase      :	List[Any]						=       0
      for row in grid:
            for i, number in enumerate(lowercase_			):
                  if number < 0:
                        total += len(lowercase_			) - i
                        break
      return total




def 					lowercase__    (					)					->		None:




      """simple docstring"""

      from timeit import timeit

      print("Running benchmarks"			)
      _UpperCamelCase      :	List[str]						=       (
          "from __main__ import count_negatives_binary_search, "
          "count_negatives_brute_force, count_negatives_brute_force_with_break, grid"
      )
      for func in (
          "count_negatives_binary_search",  # took 0.7727 seconds
          "count_negatives_brute_force_with_break",  # took 4.6505 seconds
          "count_negatives_brute_force",  # took 12.8160 seconds
      ):
            _UpperCamelCase      :	List[str]						=       timeit(F'''{func}(grid=grid)'''		,setup=lowercase_		,number=500			)
            print(F'''{func}() took {time:0.4f} seconds'''			)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  benchmark()







"""simple docstring"""


import math



class      __SCREAMING_SNAKE_CASE    :







  '''simple docstring'''


  def    __SCREAMING_SNAKE_CASE				(		self   :       Any					,   __a   :       list[list[float]]					,   __a   :       list[int]	)		->				int:
        _UpperCamelCase      :	List[Any]						=       0.0
        _UpperCamelCase      :	Union[str, Any]						=       0.0
        for i in range(len(__a	)	):
              da += math.pow((sample[i] - weights[0][i])					,   2	)
              da += math.pow((sample[i] - weights[1][i])					,   2	)
              return 0 if da > da else 1
        return 0


  def    __SCREAMING_SNAKE_CASE				(		self   :       Optional[Any]					,   __a   :       list[list[int | float]]					,   __a   :       list[int]					,   __a   :       int					,   __a   :       float	)		->				list[list[int | float]]:
        for i in range(len(__a	)	):
              weights[j][i] += alpha * (sample[i] - weights[j][i])
        return weights





def 					lowercase__    (					)					->		None:




      """simple docstring"""

      _UpperCamelCase      :	Optional[int]						=       [[1, 1, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0], [0, 0, 1, 1]]

      # weight initialization ( n, C )
      _UpperCamelCase      :	List[str]						=       [[0.2, 0.6, 0.5, 0.9], [0.8, 0.4, 0.7, 0.3]]

      # training
      _UpperCamelCase      :	List[Any]						=       SelfOrganizingMap()
      _UpperCamelCase      :	int						=       3
      _UpperCamelCase      :	List[Any]						=       0.5

      for _ in range(lowercase_			):
            for j in range(len(lowercase_			)			):
                  # training sample
                  _UpperCamelCase      :	int						=       training_samples[j]

                  # Compute the winning vector
                  _UpperCamelCase      :	Tuple						=       self_organizing_map.get_winner(lowercase_		,lowercase_			)

                  # Update the winning vector
                  _UpperCamelCase      :	int						=       self_organizing_map.update(lowercase_		,lowercase_		,lowercase_		,lowercase_			)

    # classify test sample
      _UpperCamelCase      :	Optional[int]						=       [0, 0, 0, 1]
      _UpperCamelCase      :	Dict						=       self_organizing_map.get_winner(lowercase_		,lowercase_			)

      # results
      print(F'''Clusters that the test sample belongs to : {winner}'''			)
      print(F'''Weights that have been trained : {weights}'''			)


# running the main() function
if __name__ == "__main__":
  main()
