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import unittest, os
from cvxopt import matrix, normal, setseed
from cvxopt.modeling import op, variable, dot, max, sum
class TestModeling(unittest.TestCase):
def test_exceptions(self):
with self.assertRaises(TypeError):
x = variable(0)
def test_case1(self):
x = variable()
y = variable()
c1 = ( 2*x+y <= 3 )
c2 = ( x+2*y <= 3 )
c3 = ( x >= 0 )
c4 = ( y >= 0 )
lp1 = op(-4*x-5*y, [c1,c2,c3,c4])
print(repr(x))
print(str(x))
print(repr(lp1))
print(str(lp1))
lp1.solve()
print(repr(x))
print(str(x))
self.assertTrue(lp1.status == 'optimal')
def test_case2(self):
x = variable(2)
A = matrix([[2.,1.,-1.,0.], [1.,2.,0.,-1.]])
b = matrix([3.,3.,0.,0.])
c = matrix([-4.,-5.])
ineq = ( A*x <= b )
lp2 = op(dot(c,x), ineq)
lp2.solve()
self.assertAlmostEqual(lp2.objective.value()[0], -9.0, places=4)
def test_case3(self):
m, n = 500, 100
setseed(100)
A = normal(m,n)
b = normal(m)
x1 = variable(n)
lp1 = op(max(abs(A*x1-b)))
lp1.solve()
self.assertTrue(lp1.status == 'optimal')
x2 = variable(n)
lp2 = op(sum(abs(A*x2-b)))
lp2.solve()
self.assertTrue(lp2.status == 'optimal')
x3 = variable(n)
lp3 = op(sum(max(0, abs(A*x3-b)-0.75, 2*abs(A*x3-b)-2.25)))
lp3.solve()
self.assertTrue(lp3.status == 'optimal')
def test_loadfile(self):
lp = op()
lp.fromfile(os.path.join(os.path.dirname(__file__),"boeing2.mps"))
lp.solve()
self.assertTrue(lp.status == 'optimal')
if __name__ == '__main__':
unittest.main()
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