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 templateTestColoring(self, filename):
graph = read_graph(filename);
dsatur_intance = dsatur(graph.data);
dsatur_intance.process();
map_coloring = dsatur_intance.get_colors();
# Check number of colors
assigned_colors = set(map_coloring);
# Check validity of color numbers
for color_number in range(1, len(assigned_colors) + 1, 1):
assert color_number in assigned_colors;
# Check validity of colors
for index_node in range(len(graph.data)):
color_neighbors = [ map_coloring[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");
assert map_coloring[index_node] not in color_neighbors;
def templateTestColoring(self, filename):
graph = read_graph(filename);
dsatur_intance = dsatur(graph.data);
dsatur_intance.process();
map_coloring = dsatur_intance.get_colors();
# Check number of colors
assigned_colors = set(map_coloring);
# Check validity of color numbers
for color_number in range(1, len(assigned_colors) + 1, 1):
assert color_number in assigned_colors;
# Check validity of colors
for index_node in range(len(graph.data)):
color_neighbors = [ map_coloring[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");
assert map_coloring[index_node] not in color_neighbors;
def _get_LB(sol: "AngularGraphSolution", solution_type):
graph = sol.graph
if solution_type == "local_min_sum":
try:
return _get_LB.local_min_sum_lbs[graph.id]
except KeyError:
lb = max(get_lower_bounds(graph))
_get_LB.local_min_sum_lbs[graph.id] = lb
return lb
if solution_type == "min_sum":
try:
return _get_LB.min_sum_lbs[graph.id]
except KeyError:
lb = sum(get_lower_bounds(graph))
_get_LB.min_sum_lbs[graph.id] = lb
return lb
if solution_type == "makespan":
try:
lb = _get_LB.makespan_lbs[graph.id]
except KeyError:
from solver.coloring_solver import Coloring_CP_Solver
from pyclustering.gcolor.dsatur import dsatur
if graph.edge_amount < 40:
solver = Coloring_CP_Solver()
colors = solver.solve(graph)
else:
dsatur_instance = dsatur(graph.ad_matrix)
dsatur_instance.process()
colors = dsatur_instance.get_colors()
lb = ((math.ceil(math.log2(max(colors))) - 2) / 2) * 90
_get_LB.makespan_lbs[graph.id] = lb
if sol.makespan and lb > sol.makespan:
log_c_number = math.ceil(sol.makespan * 2 / 90) + 2
lb2 = ((math.ceil(log_c_number) - 2) / 2) * 90
if lb > lb2:
_get_LB.makespan_lbs[graph.id] = lb2
lb = lb2
return lb
def optim_and_save(keys, mat, overwrite):
if len(mat) == 0:
print("No course in this training programme!")
return
opti = dsatur(mat)
opti.process()
color_indices = opti.get_colors()
print(color_indices, max(color_indices))
color_set = get_color_set(
os.path.join(settings.BASE_DIR, 'misc', 'colors.json'),
max(color_indices))
for mi in range(len(keys)):
cbg = color_set[color_indices[mi] - 1]
try:
mod_disp = ModuleDisplay.objects.get(module=keys[mi])
if overwrite:
mod_disp.color_bg = cbg
mod_disp.color_txt = compute_luminance(cbg)
mod_disp.save()
except ObjectDoesNotExist:
mod_disp = ModuleDisplay(module=keys[mi],
color_bg=cbg,
color_txt=compute_luminance(cbg))
mod_disp.save()
def solve_dsatur(graph: Graph):
dsatur_instance = dsatur(graph.ad_matrix)
dsatur_instance.process()
coloring = dsatur_instance.get_colors()
return coloring
