

_SCREAMING_SNAKE_CASE  :						Tuple         =    """Alexander Joslin"""

import operator as op

from .stack import Stack
def        UpperCAmelCase_     (		_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					{'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-''': op.sub}

     SCREAMING_SNAKE_CASE__					=					Stack()
     SCREAMING_SNAKE_CASE__					=					Stack()

     for i in equation:
          if i.isdigit():
               # RULE 1
               operand_stack.push(int(_A       )       )
          elif i in operators:
               # RULE 2
               operator_stack.push(_A       )
          elif i == ")":
               # RULE 4
               SCREAMING_SNAKE_CASE__					=					operator_stack.peek()
               operator_stack.pop()
               SCREAMING_SNAKE_CASE__					=					operand_stack.peek()
               operand_stack.pop()
               SCREAMING_SNAKE_CASE__					=					operand_stack.peek()
               operand_stack.pop()

               SCREAMING_SNAKE_CASE__					=					operators[opr](_A   ,	_A       )
               operand_stack.push(_A       )

    # RULE 5
     return operand_stack.peek()


if __name__ == "__main__":
   _SCREAMING_SNAKE_CASE  :						int         =    """(5 + ((4 * 2) * (2 + 3)))"""
   # answer = 45
   print(F"{equation} = {dijkstras_two_stack_algorithm(equation)}")





import math






class  UpperCAmelCase__	:






  """simple docstring"""


  def    lowercase_	(							self		:	int			,     __lowerCamelCase		:	list[list[float]]			,     __lowerCamelCase		:	list[int]      )	->							int:
       SCREAMING_SNAKE_CASE__					=					0.0
       SCREAMING_SNAKE_CASE__					=					0.0
       for i in range(len(__lowerCamelCase      )      ):
            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    lowercase_	(							self		:	Optional[int]			,     __lowerCamelCase		:	list[list[int | float]]			,     __lowerCamelCase		:	list[int]			,     __lowerCamelCase		:	int			,     __lowerCamelCase		:	float      )	->							list[list[int | float]]:
       for i in range(len(__lowerCamelCase      )      ):
            weights[j][i] += alpha * (sample[i] - weights[j][i])
       return weights



def        UpperCAmelCase_     (		):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					[[1, 1, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0], [0, 0, 1, 1]]

     # weight initialization ( n, C )
     SCREAMING_SNAKE_CASE__					=					[[0.2, 0.6, 0.5, 0.9], [0.8, 0.4, 0.7, 0.3]]

     # training
     SCREAMING_SNAKE_CASE__					=					SelfOrganizingMap()
     SCREAMING_SNAKE_CASE__					=					3
     SCREAMING_SNAKE_CASE__					=					0.5

     for _ in range(_A       ):
          for j in range(len(_A       )       ):
               # training sample
               SCREAMING_SNAKE_CASE__					=					training_samples[j]

               # Compute the winning vector
               SCREAMING_SNAKE_CASE__					=					self_organizing_map.get_winner(_A   ,	_A       )

               # Update the winning vector
               SCREAMING_SNAKE_CASE__					=					self_organizing_map.update(_A   ,	_A   ,	_A   ,	_A       )

    # classify test sample
     SCREAMING_SNAKE_CASE__					=					[0, 0, 0, 1]
     SCREAMING_SNAKE_CASE__					=					self_organizing_map.get_winner(_A   ,	_A       )

     # 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()


