def test_vertex_eq(m = 5): np.random.seed(0) dom = BoxDomain(-np.ones(m), np.ones(m)) dom = dom.add_constraints(A_eq = np.ones(m), b_eq = [0]) Xhat = dom.sample(10) X0 = dom.sample(5) check_vertex_sample(dom, Xhat, X0)
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_point(m=3):
lb = 0 * np.ones(m)
ub = 1 * np.ones(m)
dom = BoxDomain(lb, ub)
assert dom.is_point == False
dom = BoxDomain(ub, ub)
assert dom.is_point == True
dom = BoxDomain(lb, ub)
dom = dom.add_constraints(A_eq=np.ones((1, m)), b_eq=[0])
assert dom.is_point == True
def no_test_lipschitz_sample(N = 5, m = 3): dom = BoxDomain(-np.ones(m), np.ones(m)) # Add an inequality constraint so some combinations aren't feasible dom = dom.add_constraints(A = np.ones((1,m)), b = np.ones(1)) Ls = [np.random.randn(1,m) for j in range(2)] # Limit the number of iterations to reduce computational cost X = psdr.lipschitz_sample(dom, N, Ls, maxiter = 3, jiggle = False) print(X) assert np.all(dom.isinside(X)) # Verify that each point is distinct in projections for L in Ls: y = L.dot(X.T).T print(y) assert np.min(pdist(y)) > 0, "points not distinct in projection"
def test_cheb(m=5):
lb = -np.ones(m)
ub = np.ones(m)
dom = BoxDomain(lb, ub)
A = np.ones((1, m))
b = np.zeros(1, )
dom2 = dom.add_constraints(A, b)
center, radius = dom2.chebyshev_center()
print center
print radius
assert dom2.isinside(center), "Center must be inside"
for i in range(100):
p = np.random.randn(m)
p /= np.linalg.norm(p)
assert dom2.extent(center, p) >= radius, "violated radius assumption"
def test_constraints(m=3):
np.random.seed(0)
dom = BoxDomain(-1 * np.ones(m), np.ones(m))
# Lower pyramid portion
dom_con = dom.add_constraints(A=np.ones((1, m)), b=np.ones(1))
# Convex hull describes the same space as dom_con
X = dom.sample_grid(2)
hull = ConvexHullDomain(X, A=dom_con.A, b=dom_con.b)
# Check that the same points are inside
X = dom.sample(100)
assert np.all(hull.isinside(X) == dom_con.isinside(X))
# Check sampling
X = hull.sample(100)
assert np.all(dom_con.isinside(X))