def test_solver(self):
# Frank-Wolfe from Algorithm 1 of Jaggi's paper
print 'test solver'
graph = np.loadtxt('data/braess_net.csv', delimiter=',', skiprows=1)
demand = np.loadtxt('data/braess_od.csv', delimiter=',', skiprows=1)
demand = np.reshape(demand, (1, 3))
f = solver(graph, demand, max_iter=300)
self.check(f, np.array([1., 1., 0., 1., 1.]), 1e-2)
# modify demand
demand[0, 2] = 0.5
f = solver(graph, demand)
self.check(f, np.array([.5, .0, .5, .0, .5]), 1e-8)
def test_solver(self):
# Frank-Wolfe from Algorithm 1 of Jaggi's paper
print 'test solver'
graph = np.loadtxt('data/braess_net.csv', delimiter=',', skiprows=1)
demand = np.loadtxt('data/braess_od.csv', delimiter=',', skiprows=1)
demand=np.reshape(demand, (1,3))
f = solver(graph, demand, max_iter=300)
self.check(f, np.array([1.,1.,0.,1.,1.]), 1e-2)
# modify demand
demand[0,2] = 0.5
f = solver(graph, demand)
self.check(f, np.array([.5,.0,.5,.0,.5]), 1e-8)
def test_solver_sioux_falls(self):
print 'test Frank-Wolfe on Sioux Falls'
graph = np.loadtxt('data/SiouxFalls_net.csv', delimiter=',', skiprows=1)
demand = np.loadtxt('data/SiouxFalls_od.csv', delimiter=',', skiprows=1)
demand[:,2] = demand[:,2] / 4000
f = solver(graph, demand, max_iter=1000)
results = np.loadtxt('data/SiouxFalls_results.csv')
self.check(f*4000, results, 1e-3)
def test_anaheim(self):
print 'test Frank-Wolfe on Anaheim'
graph = np.loadtxt('data/Anaheim_net.csv', delimiter=',', skiprows=1)
demand = np.loadtxt('data/Anaheim_od.csv', delimiter=',', skiprows=1)
demand[:, 2] = demand[:, 2] / 4000
f = solver(graph, demand, max_iter=1000)
# print f.shape
results = np.loadtxt('data/Anaheim_results.csv')
print np.linalg.norm(f * 4000 - results) / np.linalg.norm(results)
def test_anaheim(self):
print 'test Frank-Wolfe on Anaheim'
graph = np.loadtxt('data/Anaheim_net.csv', delimiter=',', skiprows=1)
demand = np.loadtxt('data/Anaheim_od.csv', delimiter=',', skiprows=1)
demand[:,2] = demand[:,2] / 4000
f = solver(graph, demand, max_iter=1000)
# print f.shape
results = np.loadtxt('data/Anaheim_results.csv')
print np.linalg.norm(f*4000 - results) / np.linalg.norm(results)
def test_solver_sioux_falls(self):
print 'test Frank-Wolfe on Sioux Falls'
graph = np.loadtxt('data/SiouxFalls_net.csv',
delimiter=',',
skiprows=1)
demand = np.loadtxt('data/SiouxFalls_od.csv',
delimiter=',',
skiprows=1)
demand[:, 2] = demand[:, 2] / 4000
f = solver(graph, demand, max_iter=1000)
results = np.loadtxt('data/SiouxFalls_results.csv')
self.check(f * 4000, results, 1e-3)
