mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-24 05:21:09 +00:00
20e98fcded
* fix assignment of a variable to itself * Fix unnecessary 'else' clause in loop * formatting and redundant reasignment fix * mark unreachable code with a TODO comment * fix variable defined multiple times * fix static method without static decorator * revert unintended autoformatting Co-authored-by: Christian Clauss <cclauss@me.com> * revert autoformatting issue * applied black autoformatting Co-authored-by: Christian Clauss <cclauss@me.com>
497 lines
16 KiB
Python
497 lines
16 KiB
Python
from collections import deque
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from math import floor
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from random import random
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from time import time
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# the default weight is 1 if not assigned but all the implementation is weighted
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class DirectedGraph:
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def __init__(self):
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self.graph = {}
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# adding vertices and edges
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# adding the weight is optional
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# handles repetition
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def add_pair(self, u, v, w=1):
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if self.graph.get(u):
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if self.graph[u].count([w, v]) == 0:
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self.graph[u].append([w, v])
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else:
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self.graph[u] = [[w, v]]
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if not self.graph.get(v):
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self.graph[v] = []
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def all_nodes(self):
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return list(self.graph)
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# handles if the input does not exist
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def remove_pair(self, u, v):
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if self.graph.get(u):
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for _ in self.graph[u]:
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if _[1] == v:
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self.graph[u].remove(_)
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# if no destination is meant the default value is -1
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def dfs(self, s=-2, d=-1):
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if s == d:
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return []
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stack = []
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visited = []
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if s == -2:
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s = list(self.graph)[0]
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stack.append(s)
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visited.append(s)
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ss = s
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while True:
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# check if there is any non isolated nodes
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if len(self.graph[s]) != 0:
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ss = s
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for node in self.graph[s]:
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if visited.count(node[1]) < 1:
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if node[1] == d:
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visited.append(d)
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return visited
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else:
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stack.append(node[1])
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visited.append(node[1])
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ss = node[1]
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break
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# check if all the children are visited
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if s == ss:
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stack.pop()
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if len(stack) != 0:
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s = stack[len(stack) - 1]
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else:
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s = ss
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# check if se have reached the starting point
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if len(stack) == 0:
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return visited
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# c is the count of nodes you want and if you leave it or pass -1 to the function
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# the count will be random from 10 to 10000
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def fill_graph_randomly(self, c=-1):
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if c == -1:
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c = floor(random() * 10000) + 10
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for i in range(c):
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# every vertex has max 100 edges
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for _ in range(floor(random() * 102) + 1):
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n = floor(random() * c) + 1
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if n != i:
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self.add_pair(i, n, 1)
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def bfs(self, s=-2):
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d = deque()
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visited = []
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if s == -2:
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s = list(self.graph)[0]
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d.append(s)
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visited.append(s)
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while d:
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s = d.popleft()
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if len(self.graph[s]) != 0:
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for node in self.graph[s]:
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if visited.count(node[1]) < 1:
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d.append(node[1])
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visited.append(node[1])
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return visited
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def in_degree(self, u):
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count = 0
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for x in self.graph:
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for y in self.graph[x]:
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if y[1] == u:
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count += 1
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return count
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def out_degree(self, u):
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return len(self.graph[u])
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def topological_sort(self, s=-2):
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stack = []
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visited = []
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if s == -2:
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s = list(self.graph)[0]
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stack.append(s)
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visited.append(s)
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ss = s
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sorted_nodes = []
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while True:
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# check if there is any non isolated nodes
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if len(self.graph[s]) != 0:
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ss = s
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for node in self.graph[s]:
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if visited.count(node[1]) < 1:
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stack.append(node[1])
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visited.append(node[1])
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ss = node[1]
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break
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# check if all the children are visited
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if s == ss:
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sorted_nodes.append(stack.pop())
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if len(stack) != 0:
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s = stack[len(stack) - 1]
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else:
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s = ss
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# check if se have reached the starting point
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if len(stack) == 0:
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return sorted_nodes
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def cycle_nodes(self):
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stack = []
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visited = []
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s = list(self.graph)[0]
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stack.append(s)
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visited.append(s)
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parent = -2
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indirect_parents = []
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ss = s
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on_the_way_back = False
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anticipating_nodes = set()
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while True:
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# check if there is any non isolated nodes
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if len(self.graph[s]) != 0:
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ss = s
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for node in self.graph[s]:
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if (
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visited.count(node[1]) > 0
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and node[1] != parent
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and indirect_parents.count(node[1]) > 0
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and not on_the_way_back
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):
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len_stack = len(stack) - 1
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while True and len_stack >= 0:
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if stack[len_stack] == node[1]:
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anticipating_nodes.add(node[1])
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break
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else:
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anticipating_nodes.add(stack[len_stack])
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len_stack -= 1
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if visited.count(node[1]) < 1:
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stack.append(node[1])
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visited.append(node[1])
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ss = node[1]
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break
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# check if all the children are visited
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if s == ss:
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stack.pop()
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on_the_way_back = True
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if len(stack) != 0:
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s = stack[len(stack) - 1]
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else:
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on_the_way_back = False
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indirect_parents.append(parent)
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parent = s
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s = ss
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# check if se have reached the starting point
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if len(stack) == 0:
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return list(anticipating_nodes)
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def has_cycle(self):
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stack = []
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visited = []
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s = list(self.graph)[0]
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stack.append(s)
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visited.append(s)
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parent = -2
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indirect_parents = []
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ss = s
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on_the_way_back = False
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anticipating_nodes = set()
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while True:
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# check if there is any non isolated nodes
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if len(self.graph[s]) != 0:
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ss = s
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for node in self.graph[s]:
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if (
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visited.count(node[1]) > 0
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and node[1] != parent
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and indirect_parents.count(node[1]) > 0
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and not on_the_way_back
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):
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len_stack_minus_one = len(stack) - 1
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while True and len_stack_minus_one >= 0:
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if stack[len_stack_minus_one] == node[1]:
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anticipating_nodes.add(node[1])
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break
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else:
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return True
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# TODO:The following code is unreachable.
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anticipating_nodes.add(stack[len_stack_minus_one])
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len_stack_minus_one -= 1
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if visited.count(node[1]) < 1:
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stack.append(node[1])
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visited.append(node[1])
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ss = node[1]
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break
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# check if all the children are visited
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if s == ss:
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stack.pop()
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on_the_way_back = True
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if len(stack) != 0:
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s = stack[len(stack) - 1]
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else:
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on_the_way_back = False
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indirect_parents.append(parent)
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parent = s
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s = ss
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# check if se have reached the starting point
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if len(stack) == 0:
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return False
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def dfs_time(self, s=-2, e=-1):
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begin = time()
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self.dfs(s, e)
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end = time()
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return end - begin
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def bfs_time(self, s=-2):
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begin = time()
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self.bfs(s)
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end = time()
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return end - begin
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class Graph:
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def __init__(self):
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self.graph = {}
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# adding vertices and edges
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# adding the weight is optional
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# handles repetition
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def add_pair(self, u, v, w=1):
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# check if the u exists
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if self.graph.get(u):
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# if there already is a edge
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if self.graph[u].count([w, v]) == 0:
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self.graph[u].append([w, v])
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else:
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# if u does not exist
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self.graph[u] = [[w, v]]
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# add the other way
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if self.graph.get(v):
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# if there already is a edge
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if self.graph[v].count([w, u]) == 0:
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self.graph[v].append([w, u])
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else:
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# if u does not exist
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self.graph[v] = [[w, u]]
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# handles if the input does not exist
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def remove_pair(self, u, v):
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if self.graph.get(u):
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for _ in self.graph[u]:
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if _[1] == v:
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self.graph[u].remove(_)
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# the other way round
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if self.graph.get(v):
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for _ in self.graph[v]:
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if _[1] == u:
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self.graph[v].remove(_)
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# if no destination is meant the default value is -1
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def dfs(self, s=-2, d=-1):
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if s == d:
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return []
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stack = []
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visited = []
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if s == -2:
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s = list(self.graph)[0]
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stack.append(s)
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visited.append(s)
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ss = s
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while True:
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# check if there is any non isolated nodes
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if len(self.graph[s]) != 0:
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ss = s
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for node in self.graph[s]:
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if visited.count(node[1]) < 1:
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if node[1] == d:
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visited.append(d)
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return visited
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else:
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stack.append(node[1])
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visited.append(node[1])
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ss = node[1]
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break
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# check if all the children are visited
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if s == ss:
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stack.pop()
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if len(stack) != 0:
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s = stack[len(stack) - 1]
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else:
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s = ss
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# check if se have reached the starting point
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if len(stack) == 0:
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return visited
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# c is the count of nodes you want and if you leave it or pass -1 to the function
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# the count will be random from 10 to 10000
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def fill_graph_randomly(self, c=-1):
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if c == -1:
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c = floor(random() * 10000) + 10
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for i in range(c):
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# every vertex has max 100 edges
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for _ in range(floor(random() * 102) + 1):
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n = floor(random() * c) + 1
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if n != i:
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self.add_pair(i, n, 1)
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def bfs(self, s=-2):
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d = deque()
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visited = []
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if s == -2:
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s = list(self.graph)[0]
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d.append(s)
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visited.append(s)
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while d:
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s = d.popleft()
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if len(self.graph[s]) != 0:
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for node in self.graph[s]:
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if visited.count(node[1]) < 1:
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d.append(node[1])
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visited.append(node[1])
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return visited
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def degree(self, u):
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return len(self.graph[u])
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def cycle_nodes(self):
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stack = []
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visited = []
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s = list(self.graph)[0]
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stack.append(s)
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visited.append(s)
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parent = -2
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indirect_parents = []
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ss = s
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on_the_way_back = False
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anticipating_nodes = set()
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while True:
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# check if there is any non isolated nodes
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if len(self.graph[s]) != 0:
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ss = s
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for node in self.graph[s]:
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if (
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visited.count(node[1]) > 0
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and node[1] != parent
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and indirect_parents.count(node[1]) > 0
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and not on_the_way_back
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):
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len_stack = len(stack) - 1
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while True and len_stack >= 0:
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if stack[len_stack] == node[1]:
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anticipating_nodes.add(node[1])
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break
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else:
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anticipating_nodes.add(stack[len_stack])
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len_stack -= 1
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if visited.count(node[1]) < 1:
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stack.append(node[1])
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visited.append(node[1])
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ss = node[1]
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break
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# check if all the children are visited
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if s == ss:
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stack.pop()
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on_the_way_back = True
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if len(stack) != 0:
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s = stack[len(stack) - 1]
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else:
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on_the_way_back = False
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indirect_parents.append(parent)
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parent = s
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s = ss
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# check if se have reached the starting point
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if len(stack) == 0:
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return list(anticipating_nodes)
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def has_cycle(self):
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stack = []
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visited = []
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s = list(self.graph)[0]
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stack.append(s)
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visited.append(s)
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parent = -2
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indirect_parents = []
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ss = s
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on_the_way_back = False
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anticipating_nodes = set()
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while True:
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# check if there is any non isolated nodes
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if len(self.graph[s]) != 0:
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ss = s
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for node in self.graph[s]:
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if (
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visited.count(node[1]) > 0
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and node[1] != parent
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and indirect_parents.count(node[1]) > 0
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and not on_the_way_back
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):
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len_stack_minus_one = len(stack) - 1
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while True and len_stack_minus_one >= 0:
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if stack[len_stack_minus_one] == node[1]:
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anticipating_nodes.add(node[1])
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break
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else:
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return True
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# TODO: the following code is unreachable
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# is this meant to be called in the else ?
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anticipating_nodes.add(stack[len_stack_minus_one])
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len_stack_minus_one -= 1
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if visited.count(node[1]) < 1:
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stack.append(node[1])
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visited.append(node[1])
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ss = node[1]
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break
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# check if all the children are visited
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if s == ss:
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stack.pop()
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on_the_way_back = True
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if len(stack) != 0:
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s = stack[len(stack) - 1]
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else:
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on_the_way_back = False
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indirect_parents.append(parent)
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parent = s
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s = ss
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# check if se have reached the starting point
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if len(stack) == 0:
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return False
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def all_nodes(self):
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return list(self.graph)
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def dfs_time(self, s=-2, e=-1):
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begin = time()
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self.dfs(s, e)
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end = time()
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return end - begin
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def bfs_time(self, s=-2):
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begin = time()
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self.bfs(s)
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end = time()
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return end - begin
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