def test_comp_creation_with_factory_method():
d = Domain("d", "", ["R", "G"])
v1 = Variable("v1", d)
v2 = Variable("v2", d)
c1 = constraint_from_str("c1", "10 if v1 == v2 else 0", [v1, v2])
graph = build_computation_graph(None, constraints=[c1], variables=[v1, v2])
comp_node = graph.computation("c1")
algo_def = AlgorithmDef.build_with_default_param("maxsum")
comp_def = ComputationDef(comp_node, algo_def)
comp = build_computation(comp_def)
assert comp is not None
assert comp.name == "c1"
assert comp.factor == c1
comp_node = graph.computation("v1")
algo_def = AlgorithmDef.build_with_default_param("maxsum")
comp_def = ComputationDef(comp_node, algo_def)
comp = build_computation(comp_def)
assert comp is not None
assert comp.name == "v1"
assert comp.variable.name == "v1"
assert comp.factors == ["c1"]
def test_density_two_var_one_factor():
dcop = DCOP('test', 'min')
d1 = Domain('d1', '--', [1, 2, 3])
v1 = Variable('v1', d1)
v2 = Variable('v2', d1)
dcop += 'c1', '0.5 * v1 + v2', [v1, v2]
g = build_computation_graph(dcop)
assert g.density() == 4 / 6
def test_one_var_one_factor():
dcop = DCOP('test', 'min')
d1 = Domain('d1', '--', [1, 2, 3])
v1 = Variable('v1', d1)
dcop += 'c1', '0.5 * v1', [v1]
g = build_computation_graph(dcop)
assert len(g.links) == 1
assert len(g.nodes) == 2
def test_api_distribute_dsa_adhoc():
from pydcop.computations_graph import factor_graph
from pydcop.distribution import adhoc
from pydcop.algorithms import dsa
dcop = dcop_graphcoloring_3()
agents = create_agents('a', [1, 2, 3], capacity=100)
dcop._agents_def = agents
cg = factor_graph.build_computation_graph(dcop)
dist = adhoc.distribute(cg,
dcop.agents.values(),
computation_memory=dsa.computation_memory,
communication_load=dsa.communication_load)
assert dist.is_hosted(['v1', 'v2', 'v3'])
def test_api_distribute_maxsum_ilp_compref():
from pydcop.computations_graph import factor_graph
from pydcop.distribution import ilp_compref
from pydcop.algorithms import maxsum
dcop = dcop_graphcoloring_3()
agents = create_agents('a', range(1, 4), capacity=100)
dcop._agents_def = agents
cg = factor_graph.build_computation_graph(dcop)
dist = ilp_compref.distribute(cg,
dcop.agents.values(),
computation_memory=maxsum.computation_memory,
communication_load=maxsum.communication_load)
assert dist.is_hosted(['v1', 'v2', 'v3'])
def test_api_distribute_dsa_oneagent():
from pydcop.computations_graph import factor_graph
from pydcop.distribution import oneagent
from pydcop.algorithms import dsa
dcop = dcop_graphcoloring_3()
# 5 constraints and 3 variable => 8 computations : we need 8 agents
agents = create_agents('a', range(1, 9), capacity=100)
dcop._agents_def = agents
cg = factor_graph.build_computation_graph(dcop)
dist = oneagent.distribute(cg,
dcop.agents.values(),
computation_memory=dsa.computation_memory,
communication_load=dsa.communication_load)
assert dist.is_hosted(
['v1', 'v2', 'v3', 'cost_1', 'cost_2', 'cost_3', 'c2', 'c1'])
for agt in agents:
assert len(dist.computations_hosted(agt)) == 1
type: intention
function: 1 if v1 == v2 else 0
diff_2_3:
type: intention
function: 1 if v3 == v2 else 0
agents:
a1:
capacity: 100
a2:
capacity: 100
a3:
capacity: 100
a4:
capacity: 100
a5:
capacity: 100
"""
dcop = load_dcop(dcop_yaml)
cg = build_computation_graph(dcop)
mapping = distribute(cg, dcop.agents)
agents = deploy_on_local_agents(cg, mapping)
results, _, _ = synchronous_single_run(agents)
print("FINISHED ! " + str(results))
