def colour_node_with_highest_degree(graph, working_graph, colour, visualization=None):
node = utils.get_node_wih_highest_degree(working_graph, utils.Colours.grey)
# When all left nodes are already coloured
if node is None:
node = utils.get_node_wih_highest_degree(graph, utils.Colours.grey, graph.neighbors(working_graph.nodes()[0]))
if visualization is not None:
visualization.snapshot(graph, working_graph)
graph.node[node]['colour'] = colour
working_graph.remove_nodes_from(set(working_graph.nodes()).intersection(graph.neighbors(node)))
if visualization is not None:
visualization.snapshot(graph, working_graph)
return
if visualization is not None:
working_graph.node[node]['colour'] = utils.Colours.black
visualization.snapshot(graph, working_graph)
graph.node[node]['colour'] = colour
utils.delete_node_and_neighbors(working_graph, node)
if visualization is not None:
visualization.snapshot(graph, working_graph)
def simultaneous_greedy(graph, filename=None):
"""
Solves problem using greedy algorithm, but in contrast to greedy.greedy colouring
both colours is simultaneous. Returns None if solution does not exist.
If filename is not None, takes snapshots after each node is coloured and generates visualization.
Result is saved in <filename>.gif
:return: networkx.Graph
"""
# Check if solution exist
for node in graph.nodes():
if graph.degree(node) == 0:
return None
working_graph_red = graph.copy()
working_graph_blue = graph.copy()
# colour node of first degree and thier neighbour
for node in graph.nodes(data=True):
node_id = node[0]
if graph.degree(node_id) == 1:
neighbour_id = graph.neighbors(node_id)[0]
if graph.node[neighbour_id]['colour'] == utils.Colours.red:
graph.node[node_id]['colour'] = utils.Colours.blue
utils.delete_node_and_neighbors(working_graph_blue, node_id)
elif graph.node[neighbour_id]['colour'] == utils.Colours.blue:
graph.node[node_id]['colour'] = utils.Colours.red
utils.delete_node_and_neighbors(working_graph_red, node_id)
else:
graph.node[node_id]['colour'] = utils.Colours.blue
utils.delete_node_and_neighbors(working_graph_blue, node_id)
graph.node[neighbour_id]['colour'] = utils.Colours.red
utils.delete_node_and_neighbors(working_graph_red, neighbour_id)
visualization = None
if filename is not None:
visualization = utils.GraphVisualization(3)
visualization.snapshot(graph, working_graph_red, working_graph_blue)
while working_graph_red.number_of_nodes() > 0 or working_graph_blue.number_of_nodes() > 0:
if working_graph_red.number_of_nodes() > 0:
colour_node_with_highest_degree(graph, working_graph_blue, working_graph_red, utils.Colours.red, visualization)
if working_graph_blue.number_of_nodes() > 0:
colour_node_with_highest_degree(graph, working_graph_red, working_graph_blue, utils.Colours.blue, visualization)
if visualization is not None:
visualization.generate_gif(filename)
return graph
