def test_create_agents_from_range():
agts = create_agents("a",
range(20),
default_route=2,
default_hosting_costs=7)
assert isinstance(agts["a08"], AgentDef)
assert len(agts) == 20
def test_api_solve_dsa():
dcop = dcop_graphcoloring_3()
# Agents
dcop.add_agents(create_agents('a', [1, 2, 3], capacity=50))
assignment = solve(dcop, 'dsa', 'adhoc', timeout=3)
def test_dcop_add_agents_from_dict():
dcop = DCOP()
agts = create_agents('a', [1, 2, 3])
dcop.add_agents(agts)
assert dcop.agent('a1').name == 'a1'
assert dcop.agent('a2').name == 'a2'
assert dcop.agent('a3').name == 'a3'
def test_api_solve_dpop():
dcop = dcop_graphcoloring_3()
# Agents
dcop.add_agents(create_agents('a', [1, 2, 3], capacity=50))
assignment = solve(dcop, 'dpop', 'oneagent', timeout=3)
assert assignment['v1'] == 'R'
assert assignment['v2'] == 'G'
assert assignment['v3'] == 'R'
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_solve_max(toy_pb):
variables, constraints = toy_pb
dcop = DCOP(name="toy",
variables={v.name: v
for v in variables},
constraints={c.name: c
for c in constraints},
objective="max")
dcop.add_agents(create_agents("a", [1, 2, 3, 4]))
assignment = solve(dcop, "syncbb", "oneagent")
# Note: this is supposed to be exactly the same pb as bellow
assert assignment == {"vA": "G", "vB": "R", "vC": "R", "vD": "G"}
def test_solve_min(toy_pb):
variables, constraints = toy_pb
dcop = DCOP(name="toy",
variables={v.name: v
for v in variables},
constraints={c.name: c
for c in constraints},
objective="min")
dcop.add_agents(create_agents("a", [1, 2, 3, 4]))
assignment = solve(dcop, "syncbb", "oneagent")
# Note: this is exactly the same pb as in the file bellow
# dcop = load_dcop_from_file(["/pyDcop/tests/instances/graph_coloring_tuto.yaml"])
assert assignment == {"vA": "G", "vB": "G", "vC": "G", "vD": "G"}
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
def test_create_agents_with_capacity():
agts = create_agents("a", range(20), capacity=100)
assert isinstance(agts["a18"], AgentDef)
assert agts["a05"].capacity == 100
assert len(agts) == 20
def test_api_create_several_agents():
agents = create_agents('a', [1, 2, 3])
assert agents['a1'].name == 'a1'
assert 'a3' in agents