def test_fit_multiple(self):
item = Item(weight1=10)
backpack = Backpack()
backpack.add_item(item)
constraint = FastMaxItemValue(lambda x: x.weight1, 50, "Test Rule")
results = constraint.test(backpack)
expect(results.fit_multiple) == 5
def test_bang_for_buck(self):
item = Item(weight1=10, value=2)
backpack = Backpack()
backpack.add_item(item)
constraint = FastMaxItemValue(lambda x: x.weight1, 50, "Test Rule")
results = constraint.test(backpack)
expect(results.bang_for_buck) == 10
def test_constraint_heuristic_with_one_constraint(self):
item1 = Item(weight1=100, value=1)
item2 = Item(weight1=5, value=4)
item3 = Item(weight1=5, value=5)
constraints = [
FastMaxItemValue(lambda x: x.weight1, 20, "Max Item Weight 1"),
]
backpack = Backpack(constraints)
backpack.pack(3, [item1, item2, item3])
expect(backpack.items) == [item3, item2, item3]
def test_passes_lower_bound(self):
starting_results = AllTestResults()
starting_results.update_constraint(
WeightedAverageTargetResults("WAT1", True, 94.46, 9351.54, 99))
backpack = Backpack(items=range(0, 99),
test_results=starting_results,
target_item_count=200)
backpack.add_item(Item(weight10=100))
target = WeightedAverageTarget("WAT1", lambda x: x.weight10, 100, 20,
2)
results = target.test(backpack)
expect(results.passes) is True
expect(float("{0:.4f}".format(results.result))) == 94.5154
def test_fails_upper_bound(self):
starting_results = AllTestResults()
starting_results.update_constraint(
WeightedAverageTargetResults("WAT1", True, 105.545, 10448.955, 99))
backpack = Backpack(items=range(0, 99),
test_results=starting_results,
target_item_count=200)
backpack.add_item(Item(weight10=101))
target = WeightedAverageTarget("WAT1", lambda x: x.weight10, 100, 20,
2)
results = target.test(backpack)
expect(results.passes) is False
expect(float("{0:.4f}".format(results.result))) == 105.4995
def test_fails(self):
item = Item(weight1=25.1)
max_value_results = MaxValueResult(
True, {item: {
'pass': True,
'total': 25.1
}}, "Test Rule")
results = AllTestResults()
results.update_constraint(max_value_results)
backpack = Backpack(test_results=results)
backpack.add_item(item)
constraint = FastMaxItemValue(lambda x: x.weight1, 50, "Test Rule")
new_max_value_results = constraint.test(backpack)
expect(new_max_value_results.passes) == False
def test_demand_heuristic_with_one_demand(self):
item1 = Item(weight1=100, value=1)
item2 = Item(weight1=5, value=4)
item3 = Item(weight1=5, value=5)
demands = [
FastMinTotalValue(lambda x: x.weight1, 20, "Min Item Weight 1"),
]
backpack = Backpack(demands=demands)
backpack.pack(3, [item1, item2, item3])
expect(backpack.items) == [
item1, # Top quartile progress towards demand, passes the demand minimum
item3, # No longer constrained - most bang for buck
item3
] # No longer constrained - most bang for buck
def test_pack(self):
target_number_of_items = 500
items = create_random_items(500)
constraints = [
FastMaxItemValue(lambda x: x.weight1, 50, "Max Item Weight 1"),
FastMaxItemValue(lambda x: x.weight2, 20, "Max Item Weight 2"),
FastMaxItemValue(lambda x: x.weight3, 20, "Max Item Weight 3"),
FastMaxItemValue(lambda x: x.weight4, 200, "Max Item Weight 4"),
FastMaxItemValue(lambda x: x.weight5, 500, "Max Item Weight 5"),
WeightedAverageTarget("Weighted Average Target 10",
lambda x: x.weight10, 98.25, 1, 0.1)
]
demands = [
FastMinTotalValue(lambda x: x.weight6, 100, "Min Total Weight 6"),
FastMinTotalValue(lambda x: x.weight7, 150, "Min Total Weight 7"),
FastMinTotalValue(lambda x: x.weight8, 200, "Min Total Weight 8"),
FastMinTotalValue(lambda x: x.weight9, 1000, "Min Total Weight 9"),
]
backpack = Backpack(constraints, demands=demands)
backpack.pack(target_number_of_items, items)
expect(len(backpack.items)) == target_number_of_items
expect(backpack.test_results.for_test("Max Item Weight 1").total) <= 50
expect(backpack.test_results.for_test("Max Item Weight 2").total) <= 20
expect(backpack.test_results.for_test("Max Item Weight 3").total) <= 20
expect(
backpack.test_results.for_test("Max Item Weight 4").total) <= 200
expect(
backpack.test_results.for_test("Max Item Weight 5").total) <= 500
98.15 <= expect(
backpack.test_results.for_test(
"Weighted Average Target 10").result) <= 98.35
expect(
backpack.test_results.for_test("Min Total Weight 6").total) >= 500
expect(
backpack.test_results.for_test("Min Total Weight 7").total) >= 1000
expect(
backpack.test_results.for_test("Min Total Weight 8").total) >= 2000
expect(
backpack.test_results.for_test("Min Total Weight 9").total) >= 50
def test_progress_to_demand(self):
backpack = Backpack()
backpack.add_item(Item(weight1=2))
demand = FastMinTotalValue(lambda x: x.weight1, 5, "Test Rule")
results = demand.test(backpack)
expect(results.progress_to_demand) == 0.4
def test_fails(self):
backpack = Backpack()
backpack.add_item(Item(weight1=9))
demand = FastMinTotalValue(lambda x: x.weight1, 10, "Test Rule")
results = demand.test(backpack)
expect(results.passes) == False
def test_passes(self):
backpack = Backpack()
backpack.add_item(Item(weight1=10))
constraint = FastMaxItemValue(lambda x: x.weight1, 10, "Test Rule")
results = constraint.test(backpack)
expect(results.passes) == True
def test_fails(self):
item2 = Item(weight1=25.1)
backpack = Backpack(items=[Item(weight1=50), item2, item2])
constraint = MaxItemValue(lambda x: x.weight1, 50)
results = constraint.test(backpack)
expect(results.passes) == False
def test_passes(self):
backpack = Backpack(items=[Item(weight1=10)])
constraint = MaxItemValue(lambda x: x.weight1, 10)
results = constraint.test(backpack)
expect(results.passes) == True