def knapsack(self, max_weight_percent, stateCount):
state, weights, values = self.generate_test_state(stateCount, "KS")
initial = Knapsack(weights, values, max_weight_percent)
problem = DiscreteOpt(length=stateCount,
fitness_fn=initial,
maximize=True)
problem.set_state(state)
return problem
def test_knapsack_weight_gt_max():
"""Test Knapsack fitness function for case where total weight is
greater than the maximum"""
weights = [10, 5, 2, 8, 15]
values = [1, 2, 3, 4, 5]
max_weight_pct = 0.4
state = np.array([1, 0, 2, 1, 0])
assert Knapsack(weights, values, max_weight_pct).evaluate(state) == 0
def test_knapsack_weight_lt_max():
"""Test Knapsack fitness function for case where total weight is less
than the maximum"""
weights = [10, 5, 2, 8, 15]
values = [1, 2, 3, 4, 5]
max_weight_pct = 0.6
state = np.array([1, 0, 2, 1, 0])
calculated_weights = Knapsack(weights, values, max_weight_pct).evaluate(state)
assert calculated_weights == 11