"""simple docstring"""
import numpy as np




class   __snake_case			:



      def __init__(		self       ,     lowercase=5       ,     lowercase=5)      ->     Optional[Any]:





        '''simple docstring'''





        a__:	Dict     				=      depth
        a__:	List[str]     				=      0
        a__:	Tuple     				=      None
        a__:	Dict     				=      None
        a__:	Optional[Any]     				=      min_leaf_size
        a__:	Tuple     				=      None



      def     lowerCamelCase_  (		self       ,     lowercase       ,     lowercase)      ->     Tuple:





        '''simple docstring'''





        if labels.ndim != 1:
          print('Error: Input labels must be one dimensional')

        return np.mean((labels - prediction) ** 2)



      def     lowerCamelCase_  (		self       ,     lowercase       ,     lowercase)      ->     Optional[int]:





        '''simple docstring'''





        if x.ndim != 1:
          print('Error: Input data set must be one dimensional')
          return
        if len(lowercase) != len(lowercase):
          print('Error: X and y have different lengths')
          return
        if y.ndim != 1:
          print('Error: Data set labels must be one dimensional')
          return

        if len(lowercase) < 2 * self.min_leaf_size:
          a__:	int     				=      np.mean(lowercase)
          return

        if self.depth == 1:
          a__:	List[str]     				=      np.mean(lowercase)
          return

        a__:	List[str]     				=      0
        a__:	Any     				=      self.mean_squared_error(lowercase       ,     np.mean(lowercase)) * 2
        for i in range(len(lowercase)):
          if len(x[:i]) < self.min_leaf_size:
            continue
          elif len(x[i:]) < self.min_leaf_size:
            continue
          else:
            a__:	List[str]     				=      self.mean_squared_error(x[:i]       ,     np.mean(y[:i]))
            a__:	List[Any]     				=      self.mean_squared_error(x[i:]       ,     np.mean(y[i:]))
            a__:	List[Any]     				=      error_left + error_right
            if error < min_error:
              a__:	Tuple     				=      i
              a__:	List[Any]     				=      error

        if best_split != 0:
          a__:	Optional[Any]     				=      x[:best_split]
          a__:	List[str]     				=      y[:best_split]
          a__:	Optional[Any]     				=      x[best_split:]
          a__:	str     				=      y[best_split:]

          a__:	Tuple     				=      x[best_split]
          a__:	Union[str, Any]     				=      DecisionTree(
              depth=self.depth - 1       ,     min_leaf_size=self.min_leaf_size)
          a__:	Optional[int]     				=      DecisionTree(
              depth=self.depth - 1       ,     min_leaf_size=self.min_leaf_size)
          self.left.train(lowercase       ,     lowercase)
          self.right.train(lowercase       ,     lowercase)
        else:
          a__:	Dict     				=      np.mean(lowercase)

        return



      def     lowerCamelCase_  (		self       ,     lowercase)      ->     Optional[Any]:





        '''simple docstring'''





        if self.prediction is not None:
          return self.prediction
        elif self.left or self.right is not None:
          if x >= self.decision_boundary:
            return self.right.predict(lowercase)
          else:
            return self.left.predict(lowercase)
        else:
          print('Error: Decision tree not yet trained')
          return None







class   __snake_case			:



      @staticmethod
      def     lowerCamelCase_  (		lowercase       ,     lowercase)      ->     Dict:





        '''simple docstring'''





        a__:	Tuple     				=      float(0)
        for label in labels:
          squared_error_sum += (label - prediction) ** 2

        return float(squared_error_sum / labels.size)







def 		__a  (      )      ->Optional[Any]:
  a__:	Dict     				=      np.arange(-1.0						,	1.0						,	0.005  )
  a__:	Optional[Any]     				=      np.sin(_SCREAMING_SNAKE_CASE  )

  a__:	Tuple     				=      DecisionTree(depth=10						,	min_leaf_size=10  )
  tree.train(_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )

  a__:	int     				=      (np.random.rand(10  ) * 2) - 1
  a__:	List[Any]     				=      np.array([tree.predict(_SCREAMING_SNAKE_CASE  ) for x in test_cases]  )
  a__:	Tuple     				=      np.mean((predictions - test_cases) ** 2  )

  print('Test values: ' + str(_SCREAMING_SNAKE_CASE  )  )
  print('Predictions: ' + str(_SCREAMING_SNAKE_CASE  )  )
  print('Average error: ' + str(_SCREAMING_SNAKE_CASE  )  )


if __name__ == "__main__":
 main()
 import doctest

 doctest.testmod(name='mean_squarred_error', verbose=True)







from __future__ import annotations

from typing import Generic, TypeVar

UpperCamelCase__			=    TypeVar("T")
class       _lowerCAmelCase (			Generic[T]      ):






			"""simple docstring"""





			def __init__(					self						:							int      ,  lowercase						:							T )    ->       Union[str, Any]:
									"""simple docstring"""







									__lowercase											=					data  # Assign data
									__lowercase											=					None  # Initialize next as null
									__lowercase											=					None  # Initialize prev as null





class       _lowerCAmelCase (			Generic[T]      ):






			"""simple docstring"""





			def __init__(					self						:							Any )    ->       None:
									"""simple docstring"""







									__lowercase											=					None





			def 		snake_case__      (					self						:							str      ,  lowercase						:							T )    ->       None:
									"""simple docstring"""







									if self.head is None:
															__lowercase											=					Node(lowercase )
									else:
															__lowercase											=					Node(lowercase )
															__lowercase											=					new_node
															__lowercase											=					self.head
															__lowercase											=					None
															__lowercase											=					new_node





			def 		snake_case__      (					self						:							Optional[Any] )    ->       T | None:
									"""simple docstring"""







									if self.head is None:
															return None
									else:
															assert self.head is not None
															__lowercase											=					self.head.data
															__lowercase											=					self.head.next
															if self.head is not None:
																					__lowercase											=					None
															return temp





			def 		snake_case__      (					self						:							Optional[Any] )    ->       T | None:
									"""simple docstring"""







									return self.head.data if self.head is not None else None





			def __len__(					self						:							List[str] )    ->       int:
									"""simple docstring"""







									__lowercase											=					self.head
									__lowercase											=					0
									while temp is not None:
															count += 1
															__lowercase											=					temp.next
									return count





			def 		snake_case__      (					self						:							Optional[Any] )    ->       bool:
									"""simple docstring"""







									return self.head is None







			def 		snake_case__      (					self						:							Optional[Any] )    ->       None:
									"""simple docstring"""







									print("""stack elements are:""" )
									__lowercase											=					self.head
									while temp is not None:
															print(temp.data      ,  end="""->""" )
															__lowercase											=					temp.next


# Code execution starts here
if __name__ == "__main__":
			# Start with the empty stack
			UpperCamelCase__			=    Stack()

			# Insert 4 at the beginning. So stack becomes 4->None
			print("Stack operations using Doubly LinkedList")
			stack.push(4)

			# Insert 5 at the beginning. So stack becomes 4->5->None
			stack.push(5)

			# Insert 6 at the beginning. So stack becomes 4->5->6->None
			stack.push(6)

			# Insert 7 at the beginning. So stack becomes 4->5->6->7->None
			stack.push(7)

			# Print the stack
			stack.print_stack()

			# Print the top element
			print("\nTop element is ", stack.top())

			# Print the stack size
			print("Size of the stack is ", len(stack))

			# pop the top element
			stack.pop()

			# pop the top element
			stack.pop()

			# two elements have now been popped off
			stack.print_stack()

			# Print True if the stack is empty else False
			print("\nstack is empty:", stack.is_empty())





