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https://github.com/TheAlgorithms/Python.git
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Merge pull request #30 from akshaysharma096/master
Traversal algorithms for Binary Tree.
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commit
28a7381933
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@ -11,6 +11,7 @@ python bogosort.py
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from __future__ import print_function
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import random
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def bogosort(collection):
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"""Pure implementation of the bogosort algorithm in Python
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:param collection: some mutable ordered collection with heterogeneous
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@ -28,13 +29,13 @@ def bogosort(collection):
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def isSorted(collection):
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if len(collection) < 2:
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return True
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for i in range(len(collection)-1):
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if collection[i] > collection[i+1]:
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for i in range(len(collection) - 1):
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if collection[i] > collection[i + 1]:
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return False
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return True
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while not isSorted(collection):
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random.shuffle(collection)
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random.shuffle(collection)
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return collection
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if __name__ == '__main__':
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@ -9,6 +9,7 @@ python3 -m doctest -v bubble_sort.py
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For manual testing run:
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python bubble_sort.py
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"""
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from __future__ import print_function
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@ -12,6 +12,7 @@ python heap_sort.py
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from __future__ import print_function
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def heapify(unsorted, index, heap_size):
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largest = index
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left_index = 2 * index + 1
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@ -26,6 +27,7 @@ def heapify(unsorted, index, heap_size):
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unsorted[largest], unsorted[index] = unsorted[index], unsorted[largest]
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heapify(unsorted, largest, heap_size)
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def heap_sort(unsorted):
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'''
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Pure implementation of the heap sort algorithm in Python
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@ -44,7 +46,7 @@ def heap_sort(unsorted):
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[-45, -5, -2]
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'''
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n = len(unsorted)
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for i in range(n//2 - 1, -1, -1):
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for i in range(n // 2 - 1, -1, -1):
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heapify(unsorted, i, n)
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for i in range(n - 1, 0, -1):
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unsorted[0], unsorted[i] = unsorted[i], unsorted[0]
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@ -30,8 +30,9 @@ def insertion_sort(collection):
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[-45, -5, -2]
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"""
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for index in range(1, len(collection)):
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while 0 < index and collection[index] < collection[index-1]:
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collection[index], collection[index-1] = collection[index-1], collection[index]
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while 0 < index and collection[index] < collection[index - 1]:
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collection[index], collection[
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index - 1] = collection[index - 1], collection[index]
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index -= 1
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return collection
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@ -17,7 +17,7 @@ def selection_sort(collection):
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:param collection: some mutable ordered collection with heterogeneous
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comparable items inside
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:return: the same collection ordered by ascending
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Examples:
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>>> selection_sort([0, 5, 3, 2, 2])
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@ -29,7 +29,7 @@ def selection_sort(collection):
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>>> selection_sort([-2, -5, -45])
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[-45, -5, -2]
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"""
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length = len(collection)
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for i in range(length):
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least = i
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@ -17,31 +17,30 @@ def shell_sort(collection):
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:param collection: Some mutable ordered collection with heterogeneous
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comparable items inside
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:return: the same collection ordered by ascending
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>>> shell_sort([0, 5, 3, 2, 2])
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[0, 2, 2, 3, 5]
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>>> shell_sort([])
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[]
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>>> shell_sort([-2, -5, -45])
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>>> shell_sort([-2, -5, -45])
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[-45, -5, -2]
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"""
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# Marcin Ciura's gap sequence
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gaps = [701, 301, 132, 57, 23, 10, 4, 1]
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for gap in gaps:
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i = gap
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while i < len(collection):
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temp = collection[i]
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j = i
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while j >= gap and collection[j-gap] > temp:
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while j >= gap and collection[j - gap] > temp:
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collection[j] = collection[j - gap]
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j -= gap
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collection[j] = temp
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i += 1
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return collection
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if __name__ == '__main__':
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105
traverals/binary_tree_traversals.py
Normal file
105
traverals/binary_tree_traversals.py
Normal file
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@ -0,0 +1,105 @@
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"""
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This is pure python implementation of tree traversal algorithms
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"""
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import queue
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class TreeNode:
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def __init__(self, data):
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self.data = data
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self.right = None
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self.left = None
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def build_tree():
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print("Enter the value of the root node: ", end="")
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data = eval(input())
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if data < 0:
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return None
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else:
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q = queue.Queue()
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tree_node = TreeNode(data)
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q.put(tree_node)
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while not q.empty():
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node_found = q.get()
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print("Enter the left node of %s: " % node_found.data, end="")
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left_data = eval(input())
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if left_data >= 0:
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left_node = TreeNode(left_data)
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node_found.left = left_node
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q.put(left_node)
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print("Enter the right node of %s: " % node_found.data, end="")
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right_data = eval(input())
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if right_data >= 0:
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right_node = TreeNode(right_data)
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node_found.right = right_node
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q.put(right_node)
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return tree_node
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def pre_order(node):
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if not node:
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return
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print(node.data, end=" ")
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pre_order(node.left)
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pre_order(node.right)
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def in_order(node):
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if not node:
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return
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pre_order(node.left)
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print(node.data, end=" ")
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pre_order(node.right)
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def post_order(node):
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if not node:
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return
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post_order(node.left)
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post_order(node.right)
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print(node.data, end=" ")
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def level_order(node):
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if not node:
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return
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q = queue.Queue()
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q.put(node)
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while not q.empty():
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node_dequeued = q.get()
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print(node_dequeued.data, end=" ")
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if node_dequeued.left:
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q.put(node_dequeued.left)
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if node_dequeued.right:
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q.put(node_dequeued.right)
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if __name__ == '__main__':
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import sys
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print("\n********* Binary Tree Traversals ************\n")
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# For python 2.x and 3.x compatibility: 3.x has not raw_input builtin
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# otherwise 2.x's input builtin function is too "smart"
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if sys.version_info.major < 3:
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input_function = raw_input
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else:
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input_function = input
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node = build_tree()
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print("\n********* Pre Order Traversal ************")
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pre_order(node)
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print("\n******************************************\n")
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print("\n********* In Order Traversal ************")
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in_order(node)
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print("\n******************************************\n")
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print("\n********* Post Order Traversal ************")
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post_order(node)
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print("\n******************************************\n")
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print("\n********* Level Order Traversal ************")
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level_order(node)
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print("\n******************************************\n")
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