Background and Problem Description:
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). 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:
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:
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:
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.
My Question:
Do I have the right idea, here, if not the right implementation? More to the point, how can I fix this? Also, is it necessary to keep a separate domains dictionary? Or could we make domain a property of each node in the graph?
My Code:
Here's the solve function where this code is called:
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:
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:
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
Data and Example for which the Code is Failing:
The example graph I'm using can be found here.
The function for reading the data:
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:
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
