def test_model_composition_units(self):
class Above(Model):
"""A simple upper bound on x
Lower Unbounded
---------------
x
"""
def setup(self):
x = self.x = Variable("x", "ft")
x_max = Variable("x_{max}", 1, "yard")
self.cost = 1 / x
return [x <= x_max]
class Below(Model):
"""A simple lower bound on x
Upper Unbounded
---------------
x
"""
def setup(self):
x = self.x = Variable("x", "m")
x_min = Variable("x_{min}", 1, "cm")
self.cost = x
return [x >= x_min]
a, b = Above(), Below()
concatm = Model(a.cost * b.cost, [a, b])
concat_cost = concatm.solve(verbosity=0)["cost"]
almostequal = self.assertAlmostEqual
yard, cm = gpkit.ureg("yard"), gpkit.ureg("cm")
ft, meter = gpkit.ureg("ft"), gpkit.ureg("m")
if not isinstance(a["x"].key.units, str):
almostequal(a.solve(verbosity=0)["cost"], ft / yard, 5)
almostequal(b.solve(verbosity=0)["cost"], cm / meter, 5)
almostequal(cm / yard, concat_cost, 5)
NamedVariables.reset_modelnumbers()
a1, b1 = Above(), Below()
self.assertEqual(a1["x"].key.lineage, (("Above", 0), ))
m = Model(a1["x"], [a1, b1, b1["x"] == a1["x"]])
sol = m.solve(verbosity=0)
if not isinstance(a1["x"].key.units, str):
almostequal(sol["cost"], cm / ft, 5)
a1, b1 = Above(), Below()
self.assertEqual(a1["x"].key.lineage, (("Above", 1), ))
m = Model(b1["x"], [a1, b1, b1["x"] == a1["x"]])
sol = m.solve(verbosity=0)
if not isinstance(b1["x"].key.units, str):
almostequal(sol["cost"], cm / meter, 5)
self.assertIn(a1["x"], sol["variables"])
self.assertIn(b1["x"], sol["variables"])
self.assertNotIn(a["x"], sol["variables"])
self.assertNotIn(b["x"], sol["variables"])
def monte_carlo_results(m,
progress=None,
out=None,
sol=None,
quiet=False,
seed=246):
NamedVariables.reset_modelnumbers()
np.random.seed(seed=seed)
monte_up = [{
k.name: stats.truncnorm.rvs(-3, 3, loc=1, scale=(k.key.orig_pr / 300.))
for k in m.substitutions if k.pr
} for _ in range(N)]
try:
if sol is None:
sol = m.localsolve(verbosity=0)
if out:
with out:
print("Fuel consumption: %i lbs" %
sol("W_f").to("lbf").magnitude)
elif not quiet:
print("Fuel consumption: %i lbs" % sol("W_f").to("lbf").magnitude)
except Exception:
return (None, None)
else:
failures = 0
for var in m.varkeys:
if var.fix:
m.substitutions[var] = sol["variables"][var.name]
if var.margin:
m.substitutions[var] = 1
m.pop()
for i, subs in enumerate(monte_up):
m.substitutions.update(subs)
try:
# assert not does_it_fail(sol, W_W_coeff1)
# UNCOMMENT THE ABOVE AND COMMENT OUT THE BELOW TO SPEED UP
m.solve(verbosity=0)
except Exception:
failures += 1
if progress:
progress.value = i / N
if out:
with out:
print(" Failure rate: % 2.1f%% " %
(100 * failures / float(N)))
elif not quiet:
print(" Failure rate: % 2.1f%% " % (100 * failures / float(N)))
return (sol("W_f").to("lbf").magnitude, 100 * failures / float(N))
def test_small_named_signomial(self):
x = Variable('x')
z = Variable('z')
local_ndig = 4
nonzero_adder = 0.1 # TODO: support reaching zero, issue #348
with SignomialsEnabled():
J = 0.01 * (x - 1)**2 + nonzero_adder
with NamedVariables("SmallSignomial"):
m = Model(z, [z >= J])
sol = m.localsolve(verbosity=0)
self.assertAlmostEqual(sol['cost'], nonzero_adder, local_ndig)
self.assertAlmostEqual(sol('x'), 0.98725425, self.ndig)
def test_small_named_signomial(self):
x = Variable("x")
z = Variable("z")
local_ndig = 4
nonzero_adder = 0.1
with SignomialsEnabled():
J = 0.01 * (x - 1)**2 + nonzero_adder
with NamedVariables("SmallSignomial"):
m = Model(z, [z >= J])
sol = m.localsolve(verbosity=0, solver=self.solver)
self.assertAlmostEqual(sol["cost"], nonzero_adder, local_ndig)
self.assertAlmostEqual(sol("x"), 0.98725425, self.ndig)