def template_graph_coloring(filename,
alpha,
eps,
steps,
time,
title=None,
tolerance=0.1,
threshold_steps=10):
if (title is None): title = filename
graph = read_graph(filename)
network = hysteresisgcolor(graph.data, alpha, eps)
output_dynamic = network.simulate(steps, time)
draw_dynamics(output_dynamic.time,
output_dynamic.output,
x_title="Time",
y_title="State")
clusters = output_dynamic.allocate_clusters(tolerance, threshold_steps)
for index in range(0, len(clusters)):
print("Color #", index, ": ", clusters[index])
coloring_map = output_dynamic.allocate_map_coloring(
tolerance, threshold_steps)
draw_graph(graph, coloring_map)
def template_graph_coloring(positive_weight, negative_weight, filename, reduction = None, title = None):
if (title is None): title = filename;
print("\nGraph Coloring: ", title);
graph = read_graph(filename);
network = syncgcolor(graph.data, positive_weight, negative_weight, reduction);
analyser = network.process(order = 0.999, solution = solve_type.FAST, collect_dynamic = True);
sync.sync_visualizer.show_output_dynamic(analyser);
clusters = analyser.allocate_color_clusters();
for index in range(0, len(clusters)):
print("Color #", index, ": ", clusters[index]);
coloring_map = analyser.allocate_map_coloring();
print("Number colors: ", max(coloring_map));
draw_graph(graph, coloring_map);
# Check validity of colors
for index_node in range(len(graph.data)):
color_neighbors = [ coloring_map[index] for index in range(len(graph.data[index_node])) if graph.data[index_node][index] != 0 and index_node != index];
#print(index_node, map_coloring[index_node], color_neighbors, assigned_colors, map_coloring, "\n\n");
if (coloring_map[index_node] in color_neighbors):
print("Warining: Incorrect coloring");
return;
def template_graph_coloring(positive_weight, negative_weight, filename, reduction = None, title = None):
if (title is None): title = filename;
print("\nGraph Coloring: ", title);
graph = read_graph(filename);
network = syncgcolor(graph.data, positive_weight, negative_weight, reduction);
analyser = network.process(order = 0.999, solution = solve_type.FAST, collect_dynamic = True);
sync.sync_visualizer.show_output_dynamic(analyser);
clusters = analyser.allocate_color_clusters();
for index in range(0, len(clusters)):
print("Color #", index, ": ", clusters[index]);
coloring_map = analyser.allocate_map_coloring();
print("Number colors: ", max(coloring_map));
draw_graph(graph, coloring_map);
# Check validity of colors
for index_node in range(len(graph.data)):
color_neighbors = [ coloring_map[index] for index in range(len(graph.data[index_node])) if graph.data[index_node][index] != 0 and index_node != index];
#print(index_node, map_coloring[index_node], color_neighbors, assigned_colors, map_coloring, "\n\n");
if (coloring_map[index_node] in color_neighbors):
print("Warining: Incorrect coloring");
return;
def template_graph_coloring(filename):
graph = read_graph(filename)
dsatur_instance = dsatur(graph.data)
dsatur_instance.process()
coloring = dsatur_instance.get_colors()
print("Number colors: ", max(coloring))
draw_graph(graph, coloring)
def template_graph_coloring(filename):
graph = read_graph(filename);
dsatur_instance = dsatur(graph.data);
dsatur_instance.process();
coloring = dsatur_instance.get_colors();
print("Number colors: ", max(coloring));
draw_graph(graph, coloring);
def template_graph_coloring(filename, alpha, eps, steps, time, title = None, tolerance = 0.1):
if (title is None): title = filename;
graph = read_graph(filename);
network = hysteresisgcolor(graph.data, alpha, eps);
(t, dyn) = network.simulate(steps, time);
draw_dynamics(t, dyn, x_title = "Time", y_title = "State");
clusters = network.get_clusters(tolerance);
for index in range(0, len(clusters)):
print("Color #", index, ": ", clusters[index]);
coloring_map = network.get_map_coloring(tolerance);
draw_graph(graph, coloring_map);
def template_graph_coloring(filename, alpha, eps, steps, time, title = None, tolerance = 0.1, threshold_steps = 10):
if (title is None): title = filename;
graph = read_graph(filename);
network = hysteresisgcolor(graph.data, alpha, eps);
output_dynamic = network.simulate(steps, time);
draw_dynamics(output_dynamic.time, output_dynamic.output, x_title = "Time", y_title = "State");
clusters = output_dynamic.allocate_clusters(tolerance, threshold_steps);
for index in range(0, len(clusters)):
print("Color #", index, ": ", clusters[index]);
coloring_map = output_dynamic.allocate_map_coloring(tolerance, threshold_steps);
draw_graph(graph, coloring_map);
def template_graph_coloring(filename,
alpha,
eps,
steps,
time,
title=None,
tolerance=0.1):
if (title is None): title = filename
graph = read_graph(filename)
network = hysteresisgcolor(graph.data, alpha, eps)
(t, dyn) = network.simulate(steps, time)
draw_dynamics(t, dyn, x_title="Time", y_title="State")
clusters = network.get_clusters(tolerance)
for index in range(0, len(clusters)):
print("Color #", index, ": ", clusters[index])
coloring_map = network.get_map_coloring(tolerance)
draw_graph(graph, coloring_map)
