z = max(dist)
s = sorted(dist)
centers, edges = solve_kcenter(m, n, d, k, s, known_g)
print "Centers:", centers
print "Edges:", edges
#print [((i,j),d[i,j]) for (i,j) in edges]
opt = max([d[i, j] for (i, j) in edges])
print "Opt = ", opt
class_counter = np.zeros(len(centers), dtype=int)
acc = 0
#if known_g:
for e in edges:
l = centers.index(e[1])
if label[e[0]] == l and known_g:
acc = acc + 1
class_counter[l] = class_counter[l] + 1
if known_g:
acc = (1.0 * acc) / n
print 'acc =', acc
elapsed_time = time.time() - start
print 'time:', elapsed_time
write_to_file("out-pcenter", opt, centers, edges, n, k, known_g,
class_counter, acc, elapsed_time)
z = max(dist)
s = sorted(dist)
centers, edges = solve_kcenter(m, n, d, k, s, known_g)
print "Centers:", centers
print "Edges:", edges
#print [((i,j),d[i,j]) for (i,j) in edges]
opt = max([d[i,j] for (i,j) in edges])
print "Opt = ", opt
class_counter = np.zeros(len(centers), dtype = int)
acc = 0
#if known_g:
for e in edges:
l = centers.index(e[1])
if label[e[0]] == l and known_g:
acc = acc+1
class_counter[l] = class_counter[l]+1
if known_g:
acc = (1.0*acc)/n
print 'acc =', acc
elapsed_time = time.time() - start
print 'time:', elapsed_time
write_to_file("out-pcenter", opt, centers, edges, n, k, known_g, class_counter, acc, elapsed_time)
model.optimize()
x, y = model.__data
edges = [(i, j) for (i, j) in x if x[i, j].X > 0]
centers = [j for j in y if y[j].X > 0]
print "Opt =", model.ObjVal
allocation = np.zeros(n)
print "Centers:", centers
print "Edges:", edges
class_counter = np.zeros(len(centers), dtype=int)
acc = 0
#if known_g:
for e in edges:
l = centers.index(e[1])
if label[e[0]] == l and known_g:
acc = acc + 1
class_counter[l] = class_counter[l] + 1
if known_g:
acc = (1.0 * acc) / n
print 'acc =', acc
elapsed_time = time.time() - start
print 'time:', elapsed_time
write_to_file("out-pmedian", model.ObjVal, centers, edges, n, k, known_g,
class_counter, acc, elapsed_time)
model.optimize()
x,y = model.__data
edges = [(i,j) for (i,j) in x if x[i,j].X > 0]
centers = [j for j in y if y[j].X > 0]
print "Opt =", model.ObjVal
allocation = np.zeros(n)
print "Centers:", centers
print "Edges:", edges
class_counter = np.zeros(len(centers), dtype = int)
acc = 0
#if known_g:
for e in edges:
l = centers.index(e[1])
if label[e[0]] == l and known_g:
acc = acc+1
class_counter[l] = class_counter[l]+1
if known_g:
acc = (1.0*acc)/n
print 'acc =', acc
elapsed_time = time.time() - start
print 'time:', elapsed_time
write_to_file("out-pmedian", model.ObjVal, centers, edges, n, k, known_g, class_counter, acc, elapsed_time)
