def test_gauss_seidel_2(self):
print 'test gauss_seidel 2'
g1,g2,d1,d2 = braess_heterogeneous(.25, .25)
fs = gauss_seidel([g1,g2], [d1,d2], solver_2)
a = np.array([[.125,.25],[.125,.0],[.0, .25],[.125, .0],[.125, .25]])
self.check(fs, a, 1e-3)
g1,g2,d1,d2 = braess_heterogeneous(1., 1.)
a = np.array([[.5,.5],[.5,.5],[.0, .0],[.5, .5],[.5, .5]])
fs = gauss_seidel([g1,g2], [d1,d2], solver_2)
self.check(fs, a, 1e-3)
g1,g2,d1,d2 = braess_heterogeneous(.75, .75)
fs = gauss_seidel([g1,g2], [d1,d2], solver_2, max_iter=200)
a = np.array([[.375, .625],[.375, .125],[.0, .5],[.375, .125],[.375, .625]])
self.check(fs, a, 1e-3)
def I210_parametric_study(alphas):
# load the network and its properties
g_r, d, node, feat = load_I210_modified()
# modify the costs on non routed network
g_nr, small_capacity = multiply_cognitive_cost(g_r, feat, 3000., 100.)
#divide the demand by 4000 to computationally optimize
d[:,2] = d[:,2] / 4000.
for alpha in alphas:
if alpha == 0.0:
print 'non-routed = 1.0, routed = 0.0'
f_nr = solver_3(g_nr, d, max_iter=1000, stop=1e-3)
fs=np.zeros((f_nr.shape[0],2))
fs[:,0]=f_nr
elif alpha == 1.0:
print 'non-routed = 0.0, routed = 1.0'
f_r = solver_3(g_r, d, max_iter=1000, stop=1e-3)
fs=np.zeros((f_r.shape[0],2))
fs[:,1]=f_r
else:
print 'non-routed = {}, routed = {}'.format(1-alpha, alpha)
d_nr, d_r = heterogeneous_demand(d, alpha)
fs = gauss_seidel([g_nr,g_r], [d_nr,d_r], solver_3, max_iter=1000, \
stop=1e-3, stop_cycle=1e-3, q=50, past=20)
np.savetxt('data/I210_modified/test_{}.csv'.format(int(alpha*100)), fs, \
delimiter=',', header='f_nr,f_r')
def test_gauss_seidel_3(self):
print 'test gauss_seidel 3'
g1,g2,d1,d2 = braess_heterogeneous(.25, .25)
fs = gauss_seidel([g1,g2], [d1,d2], solver_3)
a = np.array([[.125,.25],[.125,.0],[.0, .25],[.125, .0],[.125, .25]])
#print fs
#print a
self.check(fs, a, 1e-3)
g1,g2,d1,d2 = braess_heterogeneous(1., 1.)
a = np.array([[.5,.5],[.5,.5],[.0, .0],[.5, .5],[.5, .5]])
fs = gauss_seidel([g1,g2], [d1,d2], solver_3)
self.check(fs, a, 1e-3)
g1,g2,d1,d2 = braess_heterogeneous(.75, .75)
fs = gauss_seidel([g1,g2], [d1,d2], solver_3, q=50)
a = np.array([[.375, .625],[.375, .125],[.0, .5],[.375, .125],[.375, .625]])
self.check(fs, a, 1e-3)
def I210_parametric_study(alphas):
# load the network and its properties
g_r, d, node, feat = load_I210_modified()
# modify the costs on non routed network
g_nr, small_capacity = multiply_cognitive_cost(g_r, feat, 3000., 100.)
#divide the demand by 4000 to computationally optimize
d[:, 2] = d[:, 2] / 4000.
for alpha in alphas:
if alpha == 0.0:
print 'non-routed = 1.0, routed = 0.0'
f_nr = solver_3(g_nr, d, max_iter=1000, stop=1e-3)
fs = np.zeros((f_nr.shape[0], 2))
fs[:, 0] = f_nr
elif alpha == 1.0:
print 'non-routed = 0.0, routed = 1.0'
f_r = solver_3(g_r, d, max_iter=1000, stop=1e-3)
fs = np.zeros((f_r.shape[0], 2))
fs[:, 1] = f_r
else:
print 'non-routed = {}, routed = {}'.format(1 - alpha, alpha)
d_nr, d_r = heterogeneous_demand(d, alpha)
fs = gauss_seidel([g_nr,g_r], [d_nr,d_r], solver_3, max_iter=1000, \
stop=1e-3, stop_cycle=1e-3, q=50, past=20)
np.savetxt('data/I210_modified/test_{}.csv'.format(int(alpha*100)), fs, \
delimiter=',', header='f_nr,f_r')
def braess_parametric_study():
'''
parametric study of heterogeneous game on the Braess network
'''
g1, g2, d1, d2 = braess_heterogeneous(.0, 1.5)
fs = solver_2(g1, d1, display=1)
print '.0, 1.5'
np.savetxt('data/braess/test_1.csv', fs, delimiter=',')
g1, g2, d1, d2 = braess_heterogeneous(.5, 1.)
fs = gauss_seidel([g1, g2], [d1, d2], solver_2, display=1)
print '.5, 1.'
np.savetxt('data/braess/test_2.csv', fs, delimiter=',')
g1, g2, d1, d2 = braess_heterogeneous(.75, .75)
fs = gauss_seidel([g1, g2], [d1, d2], solver_2, display=1)
print '.75, .75'
np.savetxt('data/braess/test_3.csv', fs, delimiter=',')
g1, g2, d1, d2 = braess_heterogeneous(1., .5)
fs = gauss_seidel([g1, g2], [d1, d2], solver_2, display=1)
print '1., .5'
np.savetxt('data/braess/test_4.csv', fs, delimiter=',')
g1, g2, d1, d2 = braess_heterogeneous(1.5, .0)
fs = solver_2(g2, d2, display=1)
print '1.5, .0'
np.savetxt('data/braess/test_5.csv', fs, delimiter=',')
