[英]Recursion: how to avoid Python set changed set during iteration RuntimeError
I have some code that solves the graph coloring problem (broadly defined as the problem of assigning "colors" to an undirected graph, making sure that no two vertices connected by an edge have the same color). 我有一些代码可以解决图形着色问题(广泛定义为将“颜色”分配给无向图的问题,确保没有两个由边连接的顶点具有相同的颜色)。 I'm trying to implement a solution using constraint propagation to improve on the efficiency of a standard recursive backtracking algorithm, but am running into the following error: 我正在尝试使用约束传播来实现解决方案,以提高标准递归回溯算法的效率,但遇到以下错误:
File "C:\Users\danisg\Desktop\coloring\Solver.py",
line 99, in solve
for color in self.domains[var]:
RuntimeError: Set changed size during iteration
Here, for each vertex, I keep a set
of possible particular values for that particular vertex: 这里,对于每个顶点,我为该特定顶点保留一set
可能的特定值:
self.domains = { var: set(self.colors) for var in self.vars }
After I make an assignment, I propagate this constraint to the neighboring domains, to limit the search space: 在我进行赋值后,我将此约束传播到相邻域,以限制搜索空间:
for key in node.neighbors: # list of keys corresponding to adjacent vertices
if color in self.domains[key]: # remove now to prune possible choices
self.domains[key].remove(color)
This isn't where the actual error is thrown (in my code, I indicate where the problem is in a try-except
block), but may be the source of the problem. 这不是抛出实际错误的地方(在我的代码中,我指出问题在try-except
块中的位置),但可能是问题的根源。
Do I have the right idea, here, if not the right implementation? 我是否有正确的想法,如果不是正确的实施? More to the point, how can I fix this? 更重要的是,我该如何解决这个问题? Also, is it necessary to keep a separate domains
dictionary? 另外,是否有必要保留单独的domains
字典? Or could we make domain
a property of each node in the graph? 或者我们可以使domain
成为图中每个节点的属性吗?
Here's the solve
function where this code is called: 这是调用此代码的solve
函数:
def solve(self):
uncolored = [var for var in self.vars if self.map[var].color == None]
if len(uncolored) == 0:
return True
var = min(uncolored, key = lambda x: len(self.domains[var]))
node = self.map[var]
old = { var: set(self.domains[var]) for var in self.vars }
for color in self.domains[var]:
if not self._valid(var, color):
continue
self.map[var].color = color
for key in node.neighbors:
if color in self.domains[key]:
self.domains[key].remove(color)
try:
if self.solve():
return True
except:
print('happening now')
self.map[var].color = None
self.domains = old
return False
My implementation uses a Node
object: 我的实现使用Node
对象:
class Solver:
class Node:
def __init__(self, var, neighbors, color = None, domain = set()):
self.var = var
self.neighbors = neighbors
self.color = color
self.domain = domain
def __str__(self):
return str((self.var, self.color))
def __init__(self, graph, K):
self.vars = sorted( graph.keys(), key = lambda x: len(graph[x]), reverse = True ) # sort by number of links; start with most constrained
self.colors = range(K)
self.map = { var: self.Node(var, graph[var]) for var in self.vars }
self.domains = { var: set(self.colors) for var in self.vars }
Here are two other functions that are used/are helpful: 以下是其他两个使用/有用的功能:
def validate(self):
for var in self.vars:
node = self.map[var]
for key in node.neighbors:
if node.color == self.map[key].color:
return False
return True
def _valid(self, var, color):
node = self.map[var]
for key in node.neighbors:
if self.map[key].color == None:
continue
if self.map[key].color == color:
return False
return True
The example graph I'm using can be found here . 我正在使用的示例图可以在这里找到。
The function for reading the data: 读取数据的功能:
def read_and_make_graph(input_data):
lines = input_data.split('\n')
first_line = lines[0].split()
node_count = int(first_line[0])
edge_count = int(first_line[1])
graph = {}
for i in range(1, edge_count + 1):
line = lines[i]
parts = line.split()
node, edge = int(parts[0]), int(parts[1])
if node in graph:
graph[node].add(edge)
if edge in graph:
graph[edge].add(node)
if node not in graph:
graph[node] = {edge}
if edge not in graph:
graph[edge] = {node}
return graph
It should be called as follows: 应该如下调用:
file_location = 'C:\\Users\\danisg\\Desktop\\coloring\\data\\gc_50_3'
input_data_file = open(file_location, 'r')
input_data = ''.join(input_data_file.readlines())
input_data_file.close()
graph = read_and_make_graph(input_data)
solver = Solver(graph, 6) # a 6 coloring IS possible
print(solver.solve()) # True if we solved; False if we didn't
I think the problem is here: 我认为问题在于:
for color in self.domains[var]:
if not self._valid(var, color):
continue
self.map[var].color = color
for key in node.neighbors:
if color in self.domains[key]:
self.domains[key].remove(color) # This is potentially bad.
if key == var
when self.domains[key].remove(color)
is called, you change the size of the set you're currently iterating over. 如果key == var
当self.domains[key].remove(color)
则更改当前正在迭代的集合的大小。 You can avoid this by using 你可以通过使用避免这种情况
for color in self.domains[var].copy():
Using copy() will allow you to iterate over a copy of the set, while removing items from the original. 使用copy()将允许您迭代集合的副本,同时从原始项目中删除项目。
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