def testBorderCases(self):
n = random.randint(1, 10 ^ 3)
print(f'n: {n}')
capacity = random.randint(0, 2 * (10 ^ 6))
print(f'capacity: {capacity}')
weights = list()
values = list()
for i in range(n):
weight = random.randint(0, 2 * (10 ^ 6))
value = random.randint(1, 2 * (10 ^ 6))
weights.append(weight)
values.append(value)
opt_value = get_optimal_value(capacity, values, weights)
print("{:.4f}".format(opt_value))
self.testBorderCases()
def test_with_capacity_and_three_items_of_larger_total_weight(self):
self.assertAlmostEqual(180.0000,
get_optimal_value(50, [20, 50, 30],
[60, 100, 120]),
places=4)
def test_with_capacity_and_two_items_of_lesser_total_weight(self):
self.assertAlmostEqual(160.0000,
get_optimal_value(50, [10, 20], [60, 100]),
places=4)
def test_with_capacity_and_one_item_of_larger_total_weight(self):
self.assertAlmostEqual(166.6667,
get_optimal_value(10, [30], [500]),
places=3)
def test_with_zero_capacity_and_weights_and_values(self):
self.assertEqual(0., get_optimal_value(0, [1], [10]))
self.assertEqual(0., get_optimal_value(0, [1, 2, 3], [10, 20, 30]))
def test_with_zero_capacity_and_empty_weights_and_empty_values(self):
self.assertEqual(0., get_optimal_value(0, [], []))
def test_with_unbalanced_weights_and_values(self):
get_optimal_value(0, [1], [1, 2, 3])
def test_get_optimal_value_2():
assert (int(get_optimal_value(10,[500],[30])) == 166)
def test_with_preceeding_lower_bound_among_values(self):
get_optimal_value(0, [], [1, -1, 3])
def test_with_preceeding_lower_bound_value(self):
get_optimal_value(0, [], [-1])
Input:
3 50
60 20
100 50
120 30
Output:
180.0000
To achieve the value 180, we take the first item and the third item into the bag.
Sample 2.
Input:
1 10
500 30
Output:
166.6667
Here, we just take one third of the only available item.
"""
from fractional_knapsack import get_optimal_value
from test.asserts import assert_equal
assert_equal(
"0.0000",
"{:.4f}".format(get_optimal_value(0, [20, 50, 30],
[60, 100, 120])), "zero capacity")
assert_equal(
"180.0000",
"{:.4f}".format(get_optimal_value(50, [20, 50, 30],
[60, 100, 120])), "sample 1")
assert_equal("166.6667", "{:.4f}".format(get_optimal_value(10, [30], [500])),
"sample 2")
from fractional_knapsack import get_optimal_value
assert get_optimal_value(capacity=50,
weights=[20, 50, 30],
values=[60, 100, 120]) == 180
assert get_optimal_value(capacity=10, weights=[30], values=[100]) == 166.667
def test_get_optimal_value_3():
assert (int(get_optimal_value(1000,[500],[30])) == 500)
def test_with_preceeding_lower_bound_capacity(self):
get_optimal_value(-1, [], [])
def test_with_non_empty_weights_and_empty_values(self):
get_optimal_value(0, [1], [])
def test_get_optimal_value(capacity, weights, values, expected):
assert get_optimal_value(capacity, weights, values) == expected
def test_get_optimal_value_1():
assert (get_optimal_value(50,[60,100,120],[20,50,30]) == 180)