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https://github.com/autistic-symposium/master-algorithms-py.git
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trees organized
This commit is contained in:
Mari Wahl
parent
28b84cef65
commit
52752fb931
16 changed files with 262 additions and 689 deletions
src/trees
215
src/trees/binary_tree.py
Normal file → Executable file
215
src/trees/binary_tree.py
Normal file → Executable file
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@ -1,43 +1,23 @@
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#!/usr/bin/python
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__author__ = "Mari Wahl"
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__email__ = "marina.w4hl@gmail.com"
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__author__ = "bt3"
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class Node(object):
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''' Implementation of a binary tree and its properties. For example, the following bt:
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def __init__(self, item=None,):
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1 ---> level 0
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2 3 ---> level 1
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4 5 ---> level 2
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6 7 ---> level 3
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8 9 ---> level 4
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has the following properties:
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- SIZE OR NUMBER OF NODES: n = 9
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- NUMBER OF BRANCHES OR INTERNAL NODES: b = n-1 = 8
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- VALUE OF ROOT = 1
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- MAX_DEPTH OR HEIGHT: h = 4
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- IS BALANCED? NO
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- IS BST? NO
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'''
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class NodeBT(object):
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def __init__(self, item=None, level=0):
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self.item = item
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self.level = level
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self.left = None
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self.right = None
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def __repr__(self):
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return '{}'.format(self.item)
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def _addNextNode(self, value, level_here=1):
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new_node = NodeBT(value, level_here)
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def _add(self, value):
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new_node = Node(value)
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if not self.item:
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self.item = new_node
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elif not self.left:
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@ -45,162 +25,93 @@ class NodeBT(object):
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elif not self.right:
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self.right = new_node
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else:
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self.left = self.left._addNextNode(value, level_here+1)
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return self ## this is important, because the node return to the main
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self.left = self.left._add(value)
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return self
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def _searchForNode(self, value):
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def _search(self, value):
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if self.item == value:
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return self
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else:
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found = None
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if self.left:
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found = self.left._searchForNode(value)
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if self.right:
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found = found or self.right._searchForNode(value)
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return found
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return True # or self
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found = False # or False, thats diff from BST
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if self.left:
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found = self.left._search(value)
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if self.right:
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found = found or self.right._search(value)
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return found
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def _isLeaf(self):
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return not self.right and not self.left
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def _getMaxHeight(self):
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''' Get the max height at the node, O(n)'''
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levelr, levell = 0, 0
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if self.right:
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levelr = self.right._getMaxHeight() + 1
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if self.left:
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levell = self.left._getMaxHeight() + 1
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return max(levelr, levell)
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def _getMinHeight(self, level=0):
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''' Get the min height at the node, O(n)'''
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levelr, levell = -1, -1
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if self.right:
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levelr = self.right._getMinHeight(level +1)
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if self.left:
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levell = self.left._getMinHeight(level +1)
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return min(levelr, levell) + 1
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def _isBalanced(self):
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''' Find whether the tree is balanced, by calculating heights first, O(n2) '''
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if self._getMaxHeight() - self._getMinHeight() < 2:
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return False
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else:
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if self._isLeaf():
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return True
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elif self.left and self.right:
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return self.left._isBalanced() and self.right._isBalanced()
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elif not self.left and self.right:
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return self.right._isBalanced()
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elif not self.right and self.left:
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return self.left._isBalanced()
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def _isBST(self, mintree=None, maxtree=None):
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''' Find whether the tree is a BST, inorder '''
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if self.item:
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if not mintree:
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mintree = self.item
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if not maxtree:
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maxtree = self.item
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if self._isLeaf():
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return True
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elif self.left:
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if self.left.item < self.item and mintree > self.left.item:
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mintree = self.left.item
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return self.left._isBST(mintree, maxtree)
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else:
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return False
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elif self.right:
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if self.right.item > self.item and maxtree < self.right.item:
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maxtree = self.right.item
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return self.right._isBST(mintree, maxtree)
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else:
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return False
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else:
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print('Tree is empty')
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class BinaryTree(object):
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class BT(object):
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def __init__(self):
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self.root = None
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def addNode(self, value):
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def add(self, value):
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if not self.root:
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self.root = NodeBT(value)
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self.root = Node(value)
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else:
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self.root._addNextNode(value)
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self.root._add(value)
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def isLeaf(self, value):
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node = self.root._searchForNode(value)
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if node:
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return node._isLeaf()
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else:
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print "Node not found."
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def getNodeLevel(self, item):
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node = self.root._searchForNode(item)
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if node:
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return node.level
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else:
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print('Node not found')
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def isRoot(self, value):
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return self.root.item == value
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def getHeight(self):
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return self.root._getMaxHeight()
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def isBalanced(self):
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return self.root._isBalanced()
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def isBST(self):
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return self.root._isBST()
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def preorder(self):
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def printPreorder(self):
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current = self.root
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nodes, stack = [], []
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while stack or current:
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if current:
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nodes.append(current.item) # thats what change
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nodes.append(current.item) # this is what change
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stack.append(current)
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current = current.left
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else:
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current = stack.pop()
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current = current.right
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return nodes
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print nodes
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def printInorder(self):
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current = self.root
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nodes, stack = [], []
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while stack or current:
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if current:
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stack.append(current)
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current = current.left
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else:
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current = stack.pop()
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nodes.append(current.item) # this is what change
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current = current.right
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print nodes
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def search(self, value):
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if self.root:
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return self.root._search(value)
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if __name__ == '__main__':
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bt = BinaryTree()
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bt = BT()
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print "Adding nodes 1 to 10 in the tree..."
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for i in range(1, 10):
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bt.addNode(i)
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print "Is 8 a leaf? ", bt.isLeaf(8)
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print "Whats the level of node 8? ", bt.getNodeLevel(8)
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print "Is node 10 a root? ", bt.isRoot(10)
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print "Is node 1 a root? ", bt.isRoot(1)
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print "Whats the tree height? ", bt.getHeight()
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print "Is this tree BST? ", bt.isBST()
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print "Is this tree balanced? ", bt.isBalanced()
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print (bt.preorder())
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for i in range(1, 11):
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bt.add(i)
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print
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print "Searching for nodes 16 and 6"
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print bt.search(16)
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print bt.search(6)
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print
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print "Printing preorder..."
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bt.printPreorder()
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print "Printing Inorder..."
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bt.printInorder()
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