



"""simple docstring"""






from random import shuffle

import tensorflow as tf
from numpy import array




def 			snake_case		(		lowerCAmelCase_  ,						lowerCAmelCase_	)						->				List[Any]:
  _snake_case   	=      int(lowerCAmelCase_	)
  assert noofclusters < len(lowerCAmelCase_	)

  # Find out the dimensionality
  _snake_case   	=      len(vectors[0]	)

  # Will help select random centroids from among the available vectors
  _snake_case   	=      list(range(len(lowerCAmelCase_	)	)	)
  shuffle(lowerCAmelCase_	)

  # GRAPH OF COMPUTATION
  # We initialize a new graph and set it as the default during each run
  # of this algorithm. This ensures that as this function is called
  # multiple times, the default graph doesn't keep getting crowded with
  # unused ops and Variables from previous function calls.

  _snake_case   	=      tf.Graph()

  with graph.as_default():
    # SESSION OF COMPUTATION

    _snake_case   	=      tf.Session()

    ##CONSTRUCTING THE ELEMENTS OF COMPUTATION

    ##First lets ensure we have a Variable vector for each centroid,
    ##initialized to one of the vectors from the available data points
    _snake_case   	=      [
        tf.Variable(vectors[vector_indices[i]]	) for i in range(lowerCAmelCase_	)
    ]
    ##These nodes will assign the centroid Variables the appropriate
    ##values
    _snake_case   	=      tf.placeholder('''float64'''  ,						[dim]	)
    _snake_case   	=      []
    for centroid in centroids:
      cent_assigns.append(tf.assign(lowerCAmelCase_  ,						lowerCAmelCase_	)	)

    ##Variables for cluster assignments of individual vectors(initialized
    ##to 0 at first)
    _snake_case   	=      [tf.Variable(0	) for i in range(len(lowerCAmelCase_	)	)]
    ##These nodes will assign an assignment Variable the appropriate
    ##value
    _snake_case   	=      tf.placeholder('''int32'''	)
    _snake_case   	=      []
    for assignment in assignments:
      cluster_assigns.append(tf.assign(lowerCAmelCase_  ,						lowerCAmelCase_	)	)

    ##Now lets construct the node that will compute the mean
    # The placeholder for the input
    _snake_case   	=      tf.placeholder('''float'''  ,						[None, dim]	)
    # The Node/op takes the input and computes a mean along the 0th
    # dimension, i.e. the list of input vectors
    _snake_case   	=      tf.reduce_mean(lowerCAmelCase_  ,						0	)

    ##Node for computing Euclidean distances
    # Placeholders for input
    _snake_case   	=      tf.placeholder('''float'''  ,						[dim]	)
    _snake_case   	=      tf.placeholder('''float'''  ,						[dim]	)
    _snake_case   	=      tf.sqrt(tf.reduce_sum(tf.pow(tf.sub(lowerCAmelCase_  ,						lowerCAmelCase_	)  ,						2	)	)	)

    ##This node will figure out which cluster to assign a vector to,
    ##based on Euclidean distances of the vector from the centroids.
    # Placeholder for input
    _snake_case   	=      tf.placeholder('''float'''  ,						[noofclusters]	)
    _snake_case   	=      tf.argmin(lowerCAmelCase_  ,						0	)

    ##INITIALIZING STATE VARIABLES

    ##This will help initialization of all Variables defined with respect
    ##to the graph. The Variable-initializer should be defined after
    ##all the Variables have been constructed, so that each of them
    ##will be included in the initialization.
    _snake_case   	=      tf.initialize_all_variables()

    # Initialize all variables
    sess.run(lowerCAmelCase_	)

    ##CLUSTERING ITERATIONS

    # Now perform the Expectation-Maximization steps of K-Means clustering
    # iterations. To keep things simple, we will only do a set number of
    # iterations, instead of using a Stopping Criterion.
    _snake_case   	=      100
    for _ in range(lowerCAmelCase_	):
      ##EXPECTATION STEP
      ##Based on the centroid locations till last iteration, compute
      ##the _expected_ centroid assignments.
      # Iterate over each vector
      for vector_n in range(len(lowerCAmelCase_	)	):
        _snake_case   	=      vectors[vector_n]
        # Compute Euclidean distance between this vector and each
        # centroid. Remember that this list cannot be named
        #'centroid_distances', since that is the input to the
        # cluster assignment node.
        _snake_case   	=      [
            sess.run(lowerCAmelCase_  ,						feed_dict={va: vect, va: sess.run(lowerCAmelCase_	)}	)
            for centroid in centroids
        ]
        # Now use the cluster assignment node, with the distances
        # as the input
        _snake_case   	=      sess.run(
            lowerCAmelCase_  ,						feed_dict={centroid_distances: distances}	)
        # Now assign the value to the appropriate state variable
        sess.run(
            cluster_assigns[vector_n]  ,						feed_dict={assignment_value: assignment}	)

      ##MAXIMIZATION STEP
      # Based on the expected state computed from the Expectation Step,
      # compute the locations of the centroids so as to maximize the
      # overall objective of minimizing within-cluster Sum-of-Squares
      for cluster_n in range(lowerCAmelCase_	):
        # Collect all the vectors assigned to this cluster
        _snake_case   	=      [
            vectors[i]
            for i in range(len(lowerCAmelCase_	)	)
            if sess.run(assignments[i]	) == cluster_n
        ]
        # Compute new centroid location
        _snake_case   	=      sess.run(
            lowerCAmelCase_  ,						feed_dict={mean_input: array(lowerCAmelCase_	)}	)
        # Assign value to appropriate variable
        sess.run(
            cent_assigns[cluster_n]  ,						feed_dict={centroid_value: new_location}	)

        # Return centroids and assignments
    _snake_case   	=      sess.run(lowerCAmelCase_	)
    _snake_case   	=      sess.run(lowerCAmelCase_	)
    return centroids, assignments









from collections.abc import Iterable
from typing import Any




class A    :






      def __init__(   self		:	Dict     ,  lowercase_		:	int | None = None					)   ->		int:
             """simple docstring"""




             _lowerCamelCase			:						List[Any]            =value
             _lowerCamelCase			:						Node | None            =None  # Added in order to delete a node easier
             _lowerCamelCase			:						Node | None            =None
             _lowerCamelCase			:						Node | None            =None






      def __repr__(   self		:	Dict					)   ->		str:
             """simple docstring"""




             from pprint import pformat

             if self.left is None and self.right is None:
                    return str(self.value					)
             return pformat({F'''{self.value}''': (self.left, self.right)}     ,  indent=1					)




class A    :






      def __init__(   self		:	Union[str, Any]     ,  lowercase_		:	Node | None = None					)   ->		int:
             """simple docstring"""




             _lowerCamelCase			:						Optional[int]            =root






      def __str__(   self		:	Tuple					)   ->		str:
             """simple docstring"""




             return str(self.root					)






      def 			lowerCamelCase			(   self		:	Optional[Any]     ,  lowercase_		:	Node     ,  lowercase_		:	Node | None					)   ->		None:
             """simple docstring"""




             if new_children is not None:  # reset its kids
                    _lowerCamelCase			:						Optional[int]            =node.parent
             if node.parent is not None:  # reset its parent
                    if self.is_right(lowercase_					):  # If it is the right children
                           _lowerCamelCase			:						int            =new_children
                    else:
                           _lowerCamelCase			:						Dict            =new_children
             else:
                    _lowerCamelCase			:						Tuple            =new_children






      def 			lowerCamelCase			(   self		:	Optional[Any]     ,  lowercase_		:	Node					)   ->		bool:
             """simple docstring"""




             if node.parent and node.parent.right:
                    return node == node.parent.right
             return False






      def 			lowerCamelCase			(   self		:	int					)   ->		bool:
             """simple docstring"""




             return self.root is None






      def 			lowerCamelCase			(   self		:	List[Any]     ,  lowercase_		:	Union[str, Any]					)   ->		None:
             """simple docstring"""




             _lowerCamelCase			:						Optional[Any]            =Node(lowercase_					)  # create a new Node
             if self.empty():  # if Tree is empty
                    _lowerCamelCase			:						Union[str, Any]            =new_node  # set its root
             else:  # Tree is not empty
                    _lowerCamelCase			:						Optional[int]            =self.root  # from root
                    if parent_node is None:
                           return
                    while True:  # While we don't get to a leaf
                           if value < parent_node.value:  # We go left
                                  if parent_node.left is None:
                                         _lowerCamelCase			:						Optional[int]            =new_node  # We insert the new node in a leaf
                                         break
                                  else:
                                         _lowerCamelCase			:						Optional[Any]            =parent_node.left
                           else:
                                  if parent_node.right is None:
                                         _lowerCamelCase			:						Optional[Any]            =new_node
                                         break
                                  else:
                                         _lowerCamelCase			:						Optional[int]            =parent_node.right
                    _lowerCamelCase			:						Optional[Any]            =parent_node






      def 			lowerCamelCase			(   self		:	Any     ,  *lowercase_		:	Union[str, Any]					)   ->		None:
             """simple docstring"""




             for value in values:
                    self.__insert(lowercase_					)






      def 			lowerCamelCase			(   self		:	Optional[int]     ,  lowercase_		:	List[Any]					)   ->		Node | None:
             """simple docstring"""




             if self.empty():
                    raise IndexError('Warning: Tree is empty! please use another.'					)
             else:
                    _lowerCamelCase			:						int            =self.root
                    # use lazy evaluation here to avoid NoneType Attribute error
                    while node is not None and node.value is not value:
                           _lowerCamelCase			:						Dict            =node.left if value < node.value else node.right
                    return node






      def 			lowerCamelCase			(   self		:	Tuple     ,  lowercase_		:	Node | None = None					)   ->		Node | None:
             """simple docstring"""




             if node is None:
                    if self.root is None:
                           return None
                    _lowerCamelCase			:						Union[str, Any]            =self.root

             if not self.empty():
                    while node.right is not None:
                           _lowerCamelCase			:						Optional[int]            =node.right
             return node






      def 			lowerCamelCase			(   self		:	Optional[Any]     ,  lowercase_		:	Node | None = None					)   ->		Node | None:
             """simple docstring"""




             if node is None:
                    _lowerCamelCase			:						Union[str, Any]            =self.root
             if self.root is None:
                    return None
             if not self.empty():
                    _lowerCamelCase			:						Optional[int]            =self.root
                    while node.left is not None:
                           _lowerCamelCase			:						List[Any]            =node.left
             return node






      def 			lowerCamelCase			(   self		:	Tuple     ,  lowercase_		:	int					)   ->		None:
             """simple docstring"""




             _lowerCamelCase			:						List[str]            =self.search(lowercase_					)  # Look for the node with that label
             if node is not None:
                    if node.left is None and node.right is None:  # If it has no children
                           self.__reassign_nodes(lowercase_     ,  lowercase_					)
                    elif node.left is None:  # Has only right children
                           self.__reassign_nodes(lowercase_     ,  node.right					)
                    elif node.right is None:  # Has only left children
                           self.__reassign_nodes(lowercase_     ,  node.left					)
                    else:
                           _lowerCamelCase			:						List[str]            =self.get_max(
                               node.left					)  # Gets the max value of the left branch
                           self.remove(tmp_node.value					)  # type: ignore
                           _lowerCamelCase			:						Union[str, Any]            =(
                               tmp_node.value  # type: ignore
                           )  # Assigns the value to the node to delete and keep tree structure






      def 			lowerCamelCase			(   self		:	str     ,  lowercase_		:	Node | None					)   ->		Iterable:
             """simple docstring"""




             if node is not None:
                    yield node  # Preorder Traversal
                    yield from self.preorder_traverse(node.left					)
                    yield from self.preorder_traverse(node.right					)






      def 			lowerCamelCase			(   self		:	str     ,  lowercase_		:	Dict=None					)   ->		Any:
             """simple docstring"""




             if traversal_function is None:
                    return self.preorder_traverse(self.root					)
             else:
                    return traversal_function(self.root					)






      def 			lowerCamelCase			(   self		:	Union[str, Any]     ,  lowercase_		:	list     ,  lowercase_		:	Node | None					)   ->		None:
             """simple docstring"""




             if node:
                    self.inorder(lowercase_     ,  node.left					)
                    arr.append(node.value					)
                    self.inorder(lowercase_     ,  node.right					)






      def 			lowerCamelCase			(   self		:	Union[str, Any]     ,  lowercase_		:	int     ,  lowercase_		:	Node					)   ->		int:
             """simple docstring"""




             _lowerCamelCase			:						list[int]            =[]
             self.inorder(lowercase_     ,  lowercase_					)  # append all values to list using inorder traversal
             return arr[k - 1]




def       a_ (       SCREAMING_SNAKE_CASE__   : Node | None	):
       '''simple docstring'''





       _lowerCamelCase			:						int            =[]
       if curr_node is not None:
              _lowerCamelCase			:						List[Any]            =postorder(curr_node.left	) + postorder(curr_node.right	) + [curr_node]
       return node_list




def       a_ (       ):
       '''simple docstring'''





       _lowerCamelCase			:						Optional[int]            =(8, 3, 6, 1, 10, 14, 13, 4, 7)
       _lowerCamelCase			:						int            =BinarySearchTree()
       for i in testlist:
              t.insert(SCREAMING_SNAKE_CASE__	)

       # Prints all the elements of the list in order traversal
       print(SCREAMING_SNAKE_CASE__	)

       if t.search(6	) is not None:
              print('The value 6 exists'	)
       else:
              print('The value 6 doesn\'t exist'	)

       if t.search(-1	) is not None:
              print('The value -1 exists'	)
       else:
              print('The value -1 doesn\'t exist'	)

       if not t.empty():
              print('Max Value: '						,     t.get_max().value	)  # type: ignore
              print('Min Value: '						,     t.get_min().value	)  # type: ignore

       for i in testlist:
              t.remove(SCREAMING_SNAKE_CASE__	)
              print(SCREAMING_SNAKE_CASE__	)


if __name__ == "__main__":
 import doctest

 doctest.testmod(verbose=True)


