def test_constraint_ancestors(op):
x, y = Var(), Var()
constr = op(x + y, 1)
variables = constr.get_variables()
assert x in variables
assert y in variables
assert Var() not in variables
def test_solving_trivial_two_var_problem():
bip = Knapsack(capacity=3)
bip.add_var(Var(), weight=1, value=1)
bip.add_var(Var(), weight=1, value=1)
bip.solve()
assert all([v.value == 1 for v in bip.variables])
assert bip.optimal_value == 2
def test_get_terms():
x = Var()
y = 5 - 2 * x
z = y + 4
family = z.terms
assert x in family
assert Var() not in family
def test_knapsack_with_negative_values():
bip = Knapsack(capacity=10)
bip.add_var(Var(), weight=4, value=-2)
bip.add_var(Var(), weight=20, value=5)
bip.solve()
assert [v.value for v in bip.variables] == [0, 0]
assert bip.optimal_value == 0
def test_with_offsets():
x, y = Var(), Var()
bip = InequalityConstrained(objective=2 * x + 3 * y + 5,
constraint=x + y + 1 <= 2)
bip.solve()
assert x.value == 0
assert y.value == 1
assert bip.optimal_value == 8
def test_knapsack_with_negative_values_neg_weights():
bip = Knapsack(capacity=10)
x, y = Var(), Var()
bip.add_var(x, weight=15, value=-2)
bip.add_var(y, weight=-5, value=5)
bip.solve()
assert [x.value, y.value] == [0, 1]
assert bip.optimal_value == 5
def test_solving_nontrivial_two_var_problem():
bip = Knapsack(capacity=3)
bip.add_var(Var(), weight=4, value=5)
bip.add_var(Var(), weight=1, value=1)
bip.solve()
assert bip.variables[0].value == 0
assert bip.variables[1].value == 1
assert bip.optimal_value == 1
def test_solving_two_var_problem_with_negative_weights():
bip = Knapsack(capacity=3)
x, y = Var(), Var()
bip.add_var(x, weight=-4, value=5)
bip.add_var(y, weight=1, value=1)
bip.solve()
assert x.value == 1
assert y.value == 1
assert bip.optimal_value == 6
def test_solving_nontrivial_four_var_problem():
bip = Knapsack(capacity=14)
bip.add_var(Var(), weight=5, value=8)
bip.add_var(Var(), weight=7, value=11)
bip.add_var(Var(), weight=4, value=6)
bip.add_var(Var(), weight=3, value=4)
bip.solve()
values = [v.value for v in bip.variables]
assert values == [0, 1, 1, 1]
assert bip.optimal_value == 21
def test_trivial_solves():
x, y = Var(), Var()
bip = InequalityConstrained(objective=2 * x + 3 * y, constraint=x + y <= 1)
bip.solve()
assert x.value == 0
assert y.value == 1
x, y = Var(), Var()
bip = InequalityConstrained(objective=2 * x + 3 * y, constraint=x + y >= 1)
bip.solve()
assert x.value == 1
assert y.value == 1
def test_inversion():
x = Var()
y = 3 * x
y.set_value(9)
np.testing.assert_almost_equal(x.value, 3)
x = Var()
y = 3 * x + 6
y.set_value(9)
np.testing.assert_almost_equal(x.value, 1)
x, z = Var(), Var()
y = 3 * x + z
with pytest.raises(ValueError):
y.set_value(9)
def test_solving_nontrivial_eight_var_problem():
bip = Knapsack(capacity=104)
for weight, value in zip([25, 35, 45, 5, 25, 3, 2, 2],
[350, 400, 450, 20, 70, 8, 5, 5]):
bip.add_var(Var(), weight=weight, value=value)
bip.solve()
values = [v.value for v in bip.variables]
assert values == [1, 0, 1, 1, 1, 0, 1, 1]
assert bip.optimal_value == 900
def test_var_has_value():
x = Var()
assert x.value == None
def test_derived_var_value_cascade_right():
x = Var('x')
y = x - 1
y.set_value(1)
assert x.value == 2
def test_derived_var_value_cascade_left():
x = Var('x')
y = 1 - x
y.set_value(1)
assert x.value == 0
def test_adding_variables():
bip = Knapsack(capacity=3)
bip.add_var(Var(), weight=1, value=1)
def test_init_with_kwargs():
x, y = Var(), Var()
InequalityConstrained(objective=2 * x + 3 * y, constraint=x + y <= 1)
def test_var_set_value():
x = Var()
x.set_value(1)
assert x.value == 1
def test_downstream_variable_setting():
x = Var()
y = 5 - 2 * x
z = y + 4
z.set_value(10)
np.testing.assert_almost_equal(x.value, -0.5)
def test_terms():
x, y = Var(), Var()
exp = x + y
assert x in exp.terms
assert y in exp.terms
assert Var() not in exp.terms
def test_var_initializes_with_name():
x = Var('x')
assert x.name == 'x'
def test_add_same_terms():
x = Var()
y = 3 * x + 5 * x - 3
assert len(y.terms) == 1
assert y.coefs == [8]
assert y.offset == -3