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Commit b3a1517

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A Safari
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Added more functionality
Added topological sort, cycle detection and a function to report the nodes participating in cycles in graph(for a use case I myself needed ).
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‎graphs/Directed and Undirected (Weighted) Graph

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Original file line numberDiff line numberDiff line change
@@ -106,6 +106,133 @@ class DirectedGraph:
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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.keys())[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 __ in self.graph[s]:
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if visited.count(__[1]) < 1:
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stack.append(__[1])
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visited.append(__[1])
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ss =__[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.keys())[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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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 __ in self.graph[s]:
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if visited.count(__[1]) > 0 and __[1] != parent and indirect_parents.count(__[1]) > 0 and not on_the_way_back:
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l = len(stack) - 1
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while True and l >= 0:
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if stack[l] == __[1]:
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anticipating_nodes.add(__[1])
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break
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else:
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anticipating_nodes.add(stack[l])
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l -= 1
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if visited.count(__[1]) < 1:
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stack.append(__[1])
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visited.append(__[1])
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ss =__[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.keys())[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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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 __ in self.graph[s]:
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if visited.count(__[1]) > 0 and __[1] != parent and indirect_parents.count(__[1]) > 0 and not on_the_way_back:
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l = len(stack) - 1
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while True and l >= 0:
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if stack[l] == __[1]:
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anticipating_nodes.add(__[1])
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break
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else:
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return True
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anticipating_nodes.add(stack[l])
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l -= 1
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if visited.count(__[1]) < 1:
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stack.append(__[1])
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visited.append(__[1])
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ss =__[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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class Graph:
111238
def __init__(self):
@@ -214,3 +341,98 @@ class Graph:
214341
return visited
215342
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.keys())[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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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 __ in self.graph[s]:
361+
if visited.count(__[1]) > 0 and __[1] != parent and indirect_parents.count(__[1]) > 0 and not on_the_way_back:
362+
l = len(stack) - 1
363+
while True and l >= 0:
364+
if stack[l] == __[1]:
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anticipating_nodes.add(__[1])
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break
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else:
368+
anticipating_nodes.add(stack[l])
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l -= 1
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if visited.count(__[1]) < 1:
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stack.append(__[1])
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visited.append(__[1])
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ss =__[1]
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break
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376+
# check if all the children are visited
377+
if s == ss :
378+
stack.pop()
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on_the_way_back = True
380+
if len(stack) != 0:
381+
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
389+
if len(stack) == 0:
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return list(anticipating_nodes)
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392+
def has_cycle(self):
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stack = []
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visited = []
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s = list(self.graph.keys())[0]
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stack.append(s)
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visited.append(s)
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parent = -2
399+
indirect_parents = []
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ss = s
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anticipating_nodes = set()
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403+
while True:
404+
# check if there is any non isolated nodes
405+
if len(self.graph[s]) != 0:
406+
ss = s
407+
for __ in self.graph[s]:
408+
if visited.count(__[1]) > 0 and __[1] != parent and indirect_parents.count(__[1]) > 0 and not on_the_way_back:
409+
l = len(stack) - 1
410+
while True and l >= 0:
411+
if stack[l] == __[1]:
412+
anticipating_nodes.add(__[1])
413+
break
414+
else:
415+
return True
416+
anticipating_nodes.add(stack[l])
417+
l -= 1
418+
if visited.count(__[1]) < 1:
419+
stack.append(__[1])
420+
visited.append(__[1])
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ss =__[1]
422+
break
423+
424+
# check if all the children are visited
425+
if s == ss :
426+
stack.pop()
427+
on_the_way_back = True
428+
if len(stack) != 0:
429+
s = stack[len(stack) - 1]
430+
else:
431+
on_the_way_back = False
432+
indirect_parents.append(parent)
433+
parent = s
434+
s = ss
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436+
# check if se have reached the starting point
437+
if len(stack) == 0:
438+
return False

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