def __set_l_sum(self, l, constraints):
l_sum = 0
for i in range(self.n - 1):
l_sum += l[i]
with gp.SignomialsEnabled():
constraints.append((l_sum >= self.length))
def get_pattern_constraints(X,
Y,
var_dict=None,
D_=None,
D=None,
d_attr=None,
c1=None,
c2=None):
def get_r(assignments):
r = 1
for attr, val in assignments:
key = (attr, val, D_)
r *= var_dict[key]
key = (attr, val, D)
r *= (1 / var_dict[key])
return r
rx = get_r(X)
ry = var_dict[(d_attr, D_)] / var_dict[(d_attr, D)]
ry *= get_r(Y)
constraints = []
with gpkit.SignomialsEnabled():
constraints.append(c1 * rx * ry - c2 * ry - rx * (ry**2) <= 1)
constraints.append(-c2 * rx * ry + c1 * ry - rx * (ry**2) <= 1)
return constraints
def test_persistence(self):
x = gpkit.Variable("x")
y = gpkit.Variable("y")
ymax = gpkit.Variable("y_{max}", 0.1)
with gpkit.SignomialsEnabled():
m = gpkit.Model(x, [x >= 1 - y, y <= ymax])
m.substitutions[ymax] = 0.2
self.assertAlmostEqual(m.localsolve(verbosity=0)["cost"], 0.8, 3)
m = gpkit.Model(x, [x >= 1 - y, y <= ymax])
self.assertAlmostEqual(m.localsolve(verbosity=0)["cost"], 0.9, 3)
"""Adapted from t_SP in tests/t_geometric_program.py"""
import gpkit
# Decision variables
x = gpkit.Variable('x')
y = gpkit.Variable('y')
# must enable signomials for subtraction
with gpkit.SignomialsEnabled():
constraints = [x >= 1 - y, y <= 0.1]
# create and solve the SP
m = gpkit.Model(x, constraints)
print m.localsolve(verbosity=0).summary()
assert abs(m.solution(x) - 0.9) < 1e-6
