def test_select_and_send_random_value_when_starting():
# When starting, a DSA computation select a random value and send it to
# all neighbors
v1 = Variable('v1', [0, 1, 2, 3, 4])
v2 = Variable('v2', [0, 1, 2, 3, 4])
v3 = Variable('v3', [0, 1, 2, 3, 4])
@AsNAryFunctionRelation(v1, v2, v3)
def c1(v1_, v2_, v3_):
return abs(v1_ - v2_ + v3_)
node = VariableComputationNode(v1, [c1])
comp_def = ComputationDef(node,
AlgorithmDef.build_with_default_param('dsa'))
computation = DsaComputation(comp_def=comp_def)
message_sender = MagicMock()
computation.message_sender = message_sender
computation.start()
assert computation.current_value in v1.domain
expected_message = DsaMessage(computation.current_value)
print("message_sender.mock_calls", message_sender.mock_calls)
message_sender.assert_has_calls([
call('v1', 'v2', expected_message, None, None),
call('v1', 'v3', expected_message, None, None)
],
any_order=True)
def test_1_unary_constraint(self):
variable = Variable('a', [0, 1, 2, 3, 4])
c1 = UnaryFunctionRelation('c1', variable, lambda x: abs(x - 2))
computation = DsaComputation(variable, [c1], comp_def=MagicMock())
val, sum_costs = computation._compute_best_value()
self.assertEqual(val, [2])
self.assertEqual(sum_costs, 0)
def test_2_unary_constraints(self):
variable = Variable('a', [0, 1, 2, 3, 4])
c1 = UnaryFunctionRelation('c1', variable, lambda x: abs(x - 3))
c2 = UnaryFunctionRelation('c1', variable, lambda x: abs(x - 1) * 2)
computation = DsaComputation(variable, [c1, c2], comp_def=MagicMock())
val, sum_costs = computation._compute_best_value()
print(val, sum_costs)
self.assertEqual(val, [1])
self.assertEqual(sum_costs, 2)
def test_1_binary_constraint(self):
v1 = Variable('v1', [0, 1, 2, 3, 4])
v2 = Variable('v2', [0, 1, 2, 3, 4])
@AsNAryFunctionRelation(v1, v2)
def c1(v1_, v2_):
return abs(v1_ - v2_)
computation = DsaComputation(v1, [c1], comp_def=MagicMock())
computation._neighbors_values = {'v1': 1}
val, sum_costs = computation._compute_best_value()
self.assertEqual(val, [1])
self.assertEqual(sum_costs, 0)
def test_footprint_on_computation_object():
v1 = Variable('v1', [0, 1, 2, 3, 4])
v2 = Variable('v2', [0, 1, 2, 3, 4])
c1 = relation_from_str('c1', '0 if v1 == v2 else 1', [v1, v2])
n1 = VariableComputationNode(v1, [c1])
n2 = VariableComputationNode(v2, [c1])
comp_def = ComputationDef(
n1, AlgorithmDef.build_with_default_param('dsa', mode='min'))
c = DsaComputation(comp_def)
# Must fix unit size otherwise the tests fails when we change the default
# value
dsa.UNIT_SIZE = 1
footprint = c.footprint()
assert footprint == 1
def test_build_computation_max_mode():
v1 = Variable('v1', [0, 1, 2, 3, 4])
n1 = VariableComputationNode(v1, [])
comp_def = ComputationDef(
n1, AlgorithmDef.build_with_default_param('dsa', mode='max'))
c = DsaComputation(comp_def)
assert c.mode == 'max'
def test_2_unary_constraint_means_no_neighbors(self):
variable = Variable('a', [0, 1, 2, 3, 4])
c1 = UnaryFunctionRelation('c1', variable, lambda x: abs(x - 3))
c2 = UnaryFunctionRelation('c1', variable, lambda x: abs(x - 1) * 2)
computation = DsaComputation(variable, [c1, c2], comp_def=MagicMock())
self.assertEqual(len(computation._neighbors), 0)
def test_build_computation_default_params():
v1 = Variable('v1', [0, 1, 2, 3, 4])
n1 = VariableComputationNode(v1, [])
comp_def = ComputationDef(n1, AlgorithmDef.build_with_default_param('dsa'))
c = DsaComputation(comp_def)
assert c.mode == 'min'
assert c.variant == 'B'
assert c.stop_cycle == 0
assert c.probability == 0.7
def test_repr_dsa_class():
variable = Variable('a', [0, 1, 2, 3, 4])
c1 = UnaryFunctionRelation('c1', variable, lambda x: abs(x - 2))
computation = DsaComputation(
ComputationDef(VariableComputationNode(variable, [c1]),
AlgorithmDef.build_with_default_param('dsa')))
assert repr(computation) == "dsa.DsaComputation(a)"
def test_mode_is_min(self):
v1 = Variable('v1', [0, 1, 2, 3, 4])
v2 = Variable('v2', [0, 1, 2, 3, 4])
v3 = Variable('v3', [0, 1, 2, 3, 4])
@AsNAryFunctionRelation(v1, v2)
def c1(v1_, v2_):
return abs(v1_ - v2_)
@AsNAryFunctionRelation(v1, v3)
def c2(v1_, v3_):
return abs(v1_ - v3_)
computation = DsaComputation(v1, [c1, c2], comp_def=MagicMock())
c, b = computation._compute_boundary([c1, c2])
self.assertEqual(c, [c1, c2])
self.assertEqual(b, 0)
def test_1_unary_constraint_means_no_neighbors():
variable = Variable('a', [0, 1, 2, 3, 4])
c1 = UnaryFunctionRelation('c1', variable, lambda x: abs(x - 2))
node = VariableComputationNode(variable, [c1])
comp_def = ComputationDef(node,
AlgorithmDef.build_with_default_param('dsa'))
computation = DsaComputation(comp_def=comp_def)
assert len(computation.neighbors) == 0
def test_3ary_constraint_2_neighbors(self):
v1 = Variable('v1', [0, 1, 2, 3, 4])
v2 = Variable('v2', [0, 1, 2, 3, 4])
v3 = Variable('v3', [0, 1, 2, 3, 4])
@AsNAryFunctionRelation(v1, v2, v3)
def c1(v1_, v2_, v3_):
return abs(v1_ - v2_ + v3_)
computation = DsaComputation(v1, [c1], comp_def=MagicMock())
self.assertEqual(len(computation._neighbors), 2)
def test_2_binary_constraint_one_neighbors(self):
v1 = Variable('v1', [0, 1, 2, 3, 4])
v2 = Variable('v2', [0, 1, 2, 3, 4])
@AsNAryFunctionRelation(v1, v2)
def c1(v1_, v2_):
return abs(v1_ - v2_)
@AsNAryFunctionRelation(v1, v2)
def c2(v1_, v2_):
return abs(v1_ + v2_)
computation = DsaComputation(v1, [c1, c2], comp_def=MagicMock())
self.assertEqual(len(computation._neighbors), 1)
def test_3ary_constraint_2_neighbors():
v1 = Variable('v1', [0, 1, 2, 3, 4])
v2 = Variable('v2', [0, 1, 2, 3, 4])
v3 = Variable('v3', [0, 1, 2, 3, 4])
@AsNAryFunctionRelation(v1, v2, v3)
def c1(v1_, v2_, v3_):
return abs(v1_ - v2_ + v3_)
node = VariableComputationNode(v1, [c1])
comp_def = ComputationDef(node,
AlgorithmDef.build_with_default_param('dsa'))
computation = DsaComputation(comp_def=comp_def)
assert len(computation.neighbors) == 2
def test_build_computation_with_params():
v1 = Variable('v1', [0, 1, 2, 3, 4])
n1 = VariableComputationNode(v1, [])
comp_def = ComputationDef(
n1,
AlgorithmDef.build_with_default_param('dsa',
mode='max',
params={
'variant': 'C',
'stop_cycle': 10,
'probability': 0.5
}))
c = DsaComputation(comp_def)
assert c.mode == 'max'
assert c.variant == 'C'
assert c.stop_cycle == 10
assert c.probability == 0.5
