def test_box(m=10):
dom = BoxDomain(-np.ones(m), np.ones(m))
assert len(dom) == m
x = dom.corner(np.ones(m))
assert np.all(np.isclose(x, np.ones(m)))
A = np.ones((1, m))
b = np.zeros(1)
dom2 = dom.add_constraints(A_eq=A, b_eq=b)
x = dom2.sample()
assert np.isclose(np.dot(A, x), b)
def test_bad_scaling():
# TODO: This fails with ub = 1e7
# This is mainly due to solver tolerances
lb = [-1, 1e7]
ub = [1, 2e7]
dom1 = BoxDomain(lb=lb, ub=ub)
dom2 = LinQuadDomain(lb=lb, ub=ub, verbose=True)
# Check quality of solution
p = np.ones(len(dom1))
# this calls an algebraic formula
x1 = dom1.corner(p)
# whereas this calls a linear program
x2 = dom2.corner(p)
for x1_, x2_, lb_, ub_ in zip(x1, x2, dom2.lb, dom2.ub):
print("x1:%+15.15e x2:%+15.15e delta:%+15.15e; lb: %+5.2e ub: %+5.2e" %
(x1_, x2_, np.abs(x1_ - x2_), lb_, ub_))
assert np.all(np.isclose(x1, x2, rtol=1e-4, atol=1e-4))
def test_bad_scaling():
# TODO: This fails with ub = 1e7
# This is mainly due to solver tolerances
lb = [-1, 1e7]
ub = [1, 2e7]
dom1 = BoxDomain(lb=lb, ub=ub)
dom2 = LinQuadDomain(lb=lb, ub=ub)
# Check quality of solution
p = np.ones(len(dom1))
x1 = dom1.corner(p)
x2 = dom2.corner(p,
verbose=True,
solver='ECOS',
abstol=4e-10,
reltol=1e-14,
feastol=1e-14,
max_iters=500)
for x1_, x2_, lb_, ub_ in zip(x1, x2, dom2.lb, dom2.ub):
print "x1:%+15.15e x2:%+15.15e delta:%+15.15e; lb: %+5.2e ub: %+5.2e" % (
x1_, x2_, np.abs(x1_ - x2_), lb_, ub_)
assert np.all(np.isclose(x1, x2))
def test_corner(m=10): dom = BoxDomain(-np.ones(m), np.ones(m)) assert len(dom) == m x = dom.corner(np.ones(m)) assert np.all(np.isclose(x, np.ones(m)))