def check_variant(variant): times = list(range(5)) consumption = lambda t: t * 1.5 p = Producer(name='Producer') c = Consumer(consumption, variant) cl = Cluster(p, c, resource=RESOURCE, name='Cluster') prob = fs.Problem() prob.add_constraints(chain(*(cl.constraints(t) for t in times))) prob.objective = fs.Minimize(sum(p.cost(t) for t in times)) solution = default_solver.solve(prob) for t in times: c.activity(t).take_value(solution) p.activity(t).take_value(solution) for t in times: assert approx(p.production[RESOURCE](t).value, consumption(t)) assert approx(c.consumption[RESOURCE](t).value, consumption(t))
def test_state_vars(): times = list(range(1, 4)) consumption = lambda t: t * 1.5 p = Producer(name='Producer') c = Consumer(consumption, name='Consumer') cl = Cluster(p, c, resource=RESOURCE, name='Cluster') prob = fs.Problem() prob.add_constraints(chain(*(cl.constraints(t) for t in times))) prob.objective = fs.Minimize(sum(p.cost(t) for t in times)) solution = default_solver.solve(prob) for t, part in product(times, cl.parts()): for v in part.state_variables(t): v.take_value(solution) for t in times: assert approx(p.production[RESOURCE](t).value, consumption(t)) assert approx(c.consumption[RESOURCE](t).value, consumption(t))
def test_state_vars(): times = list(range(1,4)) consumption = lambda t: t * 1.5 p = Producer(name='Producer') c = Consumer(consumption, name='Consumer') cl = Cluster(p, c, resource=RESOURCE, name='Cluster') prob = fs.Problem() prob.add_constraints(chain(*(cl.constraints(t) for t in times))) prob.objective = fs.Minimize(sum(p.cost(t) for t in times)) solution = default_solver.solve(prob) for t, part in product(times, cl.parts()): for v in part.state_variables(t): v.take_value(solution) for t in times: assert approx(p.production[RESOURCE](t).value, consumption(t)) assert approx(c.consumption[RESOURCE](t).value, consumption(t))