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https://github.com/TheAlgorithms/Python.git
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actions/checkout@v2 (#1643)
* actions/checkout@v2 https://github.com/actions/checkout/releases * fixup! Format Python code with psf/black push
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parent
1b3985837f
commit
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2
.github/workflows/directory_writer.yml
vendored
2
.github/workflows/directory_writer.yml
vendored
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@ -6,7 +6,7 @@ jobs:
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build:
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build:
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runs-on: ubuntu-latest
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runs-on: ubuntu-latest
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steps:
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steps:
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- uses: actions/checkout@v1
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- uses: actions/checkout@v2
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- uses: actions/setup-python@v1
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- uses: actions/setup-python@v1
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with:
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with:
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python-version: 3.x
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python-version: 3.x
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@ -8,7 +8,7 @@ from math import * # noqa: F401, F403
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from sympy import diff
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from sympy import diff
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def newton_raphson(func: str, a: int, precision: int=10 ** -10) -> float:
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def newton_raphson(func: str, a: int, precision: int = 10 ** -10) -> float:
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""" Finds root from the point 'a' onwards by Newton-Raphson method
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""" Finds root from the point 'a' onwards by Newton-Raphson method
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>>> newton_raphson("sin(x)", 2)
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>>> newton_raphson("sin(x)", 2)
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3.1415926536808043
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3.1415926536808043
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@ -3,8 +3,10 @@ import sys
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import cryptomath_module as cryptomath
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import cryptomath_module as cryptomath
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SYMBOLS = (r""" !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`"""
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SYMBOLS = (
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r"""abcdefghijklmnopqrstuvwxyz{|}~""")
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r""" !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`"""
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r"""abcdefghijklmnopqrstuvwxyz{|}~"""
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)
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def main():
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def main():
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@ -1,6 +1,8 @@
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'''
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"""
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A binary search Tree
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A binary search Tree
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'''
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"""
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class Node:
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class Node:
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def __init__(self, value, parent):
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def __init__(self, value, parent):
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self.value = value
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self.value = value
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@ -13,16 +15,11 @@ class Node:
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if self.left is None and self.right is None:
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if self.left is None and self.right is None:
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return str(self.value)
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return str(self.value)
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return pformat(
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return pformat({"%s" % (self.value): (self.left, self.right)}, indent=1,)
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{
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"%s"
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% (self.value): (self.left, self.right)
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},
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indent=1,
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)
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class BinarySearchTree:
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class BinarySearchTree:
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def __init__(self, root = None):
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def __init__(self, root=None):
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self.root = root
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self.root = root
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def __str__(self):
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def __str__(self):
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@ -32,10 +29,10 @@ class BinarySearchTree:
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return str(self.root)
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return str(self.root)
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def __reassign_nodes(self, node, newChildren):
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def __reassign_nodes(self, node, newChildren):
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if(newChildren is not None): # reset its kids
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if newChildren is not None: # reset its kids
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newChildren.parent = node.parent
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newChildren.parent = node.parent
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if(node.parent is not None): # reset its parent
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if node.parent is not None: # reset its parent
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if(self.is_right(node)): # If it is the right children
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if self.is_right(node): # If it is the right children
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node.parent.right = newChildren
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node.parent.right = newChildren
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else:
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else:
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node.parent.left = newChildren
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node.parent.left = newChildren
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@ -55,10 +52,10 @@ class BinarySearchTree:
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new_node = Node(value, None) # create a new Node
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new_node = Node(value, None) # create a new Node
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if self.empty(): # if Tree is empty
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if self.empty(): # if Tree is empty
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self.root = new_node # set its root
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self.root = new_node # set its root
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else: # Tree is not empty
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else: # Tree is not empty
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parent_node = self.root # from root
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parent_node = self.root # from root
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while True: # While we don't get to a leaf
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while True: # While we don't get to a leaf
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if value < parent_node.value: # We go left
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if value < parent_node.value: # We go left
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if parent_node.left == None:
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if parent_node.left == None:
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parent_node.left = new_node # We insert the new node in a leaf
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parent_node.left = new_node # We insert the new node in a leaf
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break
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break
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@ -87,43 +84,47 @@ class BinarySearchTree:
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node = node.left if value < node.value else node.right
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node = node.left if value < node.value else node.right
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return node
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return node
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def get_max(self, node = None):
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def get_max(self, node=None):
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"""
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"""
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We go deep on the right branch
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We go deep on the right branch
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"""
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"""
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if node is None:
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if node is None:
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node = self.root
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node = self.root
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if not self.empty():
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if not self.empty():
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while(node.right is not None):
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while node.right is not None:
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node = node.right
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node = node.right
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return node
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return node
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def get_min(self, node = None):
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def get_min(self, node=None):
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"""
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"""
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We go deep on the left branch
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We go deep on the left branch
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"""
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"""
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if(node is None):
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if node is None:
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node = self.root
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node = self.root
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if(not self.empty()):
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if not self.empty():
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node = self.root
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node = self.root
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while(node.left is not None):
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while node.left is not None:
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node = node.left
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node = node.left
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return node
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return node
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def remove(self, value):
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def remove(self, value):
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node = self.search(value) # Look for the node with that label
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node = self.search(value) # Look for the node with that label
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if(node is not None):
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if node is not None:
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if(node.left is None and node.right is None): # If it has no children
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if node.left is None and node.right is None: # If it has no children
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self.__reassign_nodes(node, None)
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self.__reassign_nodes(node, None)
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node = None
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node = None
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elif(node.left is None): # Has only right children
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elif node.left is None: # Has only right children
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self.__reassign_nodes(node, node.right)
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self.__reassign_nodes(node, node.right)
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elif(node.right is None): # Has only left children
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elif node.right is None: # Has only left children
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self.__reassign_nodes(node, node.left)
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self.__reassign_nodes(node, node.left)
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else:
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else:
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tmpNode = self.get_max(node.left) # Gets the max value of the left branch
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tmpNode = self.get_max(
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node.left
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) # Gets the max value of the left branch
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self.remove(tmpNode.value)
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self.remove(tmpNode.value)
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node.value = tmpNode.value # Assigns the value to the node to delete and keesp tree structure
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node.value = (
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tmpNode.value
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) # Assigns the value to the node to delete and keesp tree structure
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def preorder_traverse(self, node):
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def preorder_traverse(self, node):
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if node is not None:
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if node is not None:
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yield from self.preorder_traverse(node.left)
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yield from self.preorder_traverse(node.left)
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yield from self.preorder_traverse(node.right)
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yield from self.preorder_traverse(node.right)
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def traversal_tree(self, traversalFunction = None):
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def traversal_tree(self, traversalFunction=None):
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"""
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"""
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This function traversal the tree.
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This function traversal the tree.
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You can pass a function to traversal the tree as needed by client code
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You can pass a function to traversal the tree as needed by client code
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"""
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"""
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if(traversalFunction is None):
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if traversalFunction is None:
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return self.preorder_traverse(self.root)
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return self.preorder_traverse(self.root)
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else:
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else:
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return traversalFunction(self.root)
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return traversalFunction(self.root)
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def postorder(curr_node):
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def postorder(curr_node):
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"""
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"""
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postOrder (left, right, self)
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postOrder (left, right, self)
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nodeList = postorder(curr_node.left) + postorder(curr_node.right) + [curr_node]
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nodeList = postorder(curr_node.left) + postorder(curr_node.right) + [curr_node]
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return nodeList
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return nodeList
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def binary_search_tree():
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def binary_search_tree():
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r'''
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r"""
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Example
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Example
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8
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8
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/ \
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/ \
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Traceback (most recent call last):
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Traceback (most recent call last):
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...
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...
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IndexError: Warning: Tree is empty! please use another.
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IndexError: Warning: Tree is empty! please use another.
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'''
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"""
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testlist = (8, 3, 6, 1, 10, 14, 13, 4, 7)
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testlist = (8, 3, 6, 1, 10, 14, 13, 4, 7)
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t = BinarySearchTree()
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t = BinarySearchTree()
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for i in testlist:
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for i in testlist:
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# Prints all the elements of the list in order traversal
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# Prints all the elements of the list in order traversal
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print(t)
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print(t)
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if(t.search(6) is not None):
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if t.search(6) is not None:
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print("The value 6 exists")
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print("The value 6 exists")
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else:
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else:
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print("The value 6 doesn't exist")
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print("The value 6 doesn't exist")
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if(t.search(-1) is not None):
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if t.search(-1) is not None:
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print("The value -1 exists")
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print("The value -1 exists")
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else:
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else:
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print("The value -1 doesn't exist")
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print("The value -1 doesn't exist")
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if(not t.empty()):
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if not t.empty():
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print("Max Value: ", t.get_max().value)
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print("Max Value: ", t.get_max().value)
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print("Min Value: ", t.get_min().value)
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print("Min Value: ", t.get_min().value)
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t.remove(i)
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t.remove(i)
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print(t)
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print(t)
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二叉搜索树 = binary_search_tree
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二叉搜索树 = binary_search_tree
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if __name__ == "__main__":
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if __name__ == "__main__":
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import doctest
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import doctest
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doctest.testmod()
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doctest.testmod()
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binary_search_tree()
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binary_search_tree()
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# A complete working Python program to demonstrate all
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# A complete working Python program to demonstrate all
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# stack operations using a doubly linked list
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# stack operations using a doubly linked list
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class Node:
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class Node:
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def __init__(self, data):
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def __init__(self, data):
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self.data = data # Assign data
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self.data = data # Assign data
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self.next = None # Initialize next as null
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self.next = None # Initialize next as null
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self.prev = None # Initialize prev as null
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self.prev = None # Initialize prev as null
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class Stack:
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class Stack:
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"""
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"""
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stack elements are:
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stack elements are:
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2->1->0->
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2->1->0->
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"""
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"""
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def __init__(self):
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def __init__(self):
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self.head = None
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self.head = None
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print("stack elements are:")
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print("stack elements are:")
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temp = self.head
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temp = self.head
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while temp is not None:
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while temp is not None:
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print(temp.data, end ="->")
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print(temp.data, end="->")
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temp = temp.next
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temp = temp.next
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# Code execution starts here
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# Code execution starts here
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if __name__=='__main__':
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if __name__ == "__main__":
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# Start with the empty stack
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# Start with the empty stack
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stack = Stack()
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stack = Stack()
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return table[n]
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return table[n]
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if __name__ == "__main__":
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if __name__ == "__main__":
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import doctest
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import doctest
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@ -111,7 +111,7 @@ def simpson_integration(function, a: float, b: float, precision: int = 4) -> flo
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for i in range(1, N_STEPS):
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for i in range(1, N_STEPS):
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a1 = a + h * i
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a1 = a + h * i
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result += function(a1) * (4 if i%2 else 2)
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result += function(a1) * (4 if i % 2 else 2)
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result *= h / 3
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result *= h / 3
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return round(result, precision)
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return round(result, precision)
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