def test_to_string(self):
eprint(">> Continuum.to_string(self)")
for i in range(self.__nb_unit_test):
c = Continuum()
self.assertEqual(c.to_string(), u"\u2205")
c = Continuum.random(self.__min_value, self.__max_value)
if c.is_empty():
self.assertEqual(c.to_string(), u"\u2205")
out = ""
if c.min_included():
out += "["
else:
out += "]"
out += str(c.get_min_value()) + "," + str(c.get_max_value())
if c.max_included():
out += "]"
else:
out += "["
self.assertEqual(c.to_string(), out)
self.assertEqual(c.__str__(), out)
self.assertEqual(c.__repr__(), out)
def random_system(self):
# generates variables/domains
nb_variables = random.randint(1, self.__max_variables)
variables = ["x"+str(var) for var in range(nb_variables)]
domains = [ Continuum.random(self.__min_value, self.__max_value, self.__min_domain_size) for var in variables ]
return variables, domains
def random_rule(self, variables, domains):
var = random.randint(0,len(variables)-1)
var_domain = domains[var]
val = Continuum.random(var_domain.get_min_value(), var_domain.get_max_value(), self.__min_continuum_size)
min_size = random.randint(0, len(variables))
max_size = random.randint(min_size, len(variables))
return ContinuumRule.random(var, val, variables, domains, min_size, max_size)
def test_static_random(self):
eprint(">> Continuum.random(min_value, max_value)")
for i in range(self.__nb_unit_test):
# Valid values
min = random.uniform(self.__min_value, self.__max_value)
max = random.uniform(min, self.__max_value)
c = Continuum.random(min, max)
self.assertTrue(c.get_min_value() >= min
and c.get_min_value() <= max)
self.assertTrue(isinstance(c.min_included(), bool))
self.assertFalse(c.is_empty())
# with min size
min_size = 0
while min_size == 0:
min_size = random.uniform(-100, 0)
self.assertRaises(ValueError, Continuum.random, min, max, min_size)
min_size = random.uniform(0, self.__max_value)
if min_size >= (max - min):
self.assertRaises(ValueError, Continuum.random, min, max,
min_size)
c = Continuum.random(min, max)
self.assertTrue(c.get_min_value() >= min
and c.get_min_value() <= max)
self.assertTrue(isinstance(c.min_included(), bool))
self.assertFalse(c.is_empty())
# Invalid values
min = random.uniform(self.__min_value, self.__max_value)
max = random.uniform(self.__min_value, min - 0.001)
self.assertRaises(ValueError, Continuum.random, min, max)
def random(head_variable, head_value, variables, domains, min_body_size,
max_body_size):
"""
Generates a valid continuum rule of given size randomly.
Args:
head_variable: int
id of the head variable
head_value: Continuum
range of values of the head variable
variables: list of String
labels of the variable of a dynamic system
domains: list of pairs of (int, Continuum)
domains of values of each variable
min_body_size: int
minimal number of conditions to appear in the generated rule
max_body_size: int
maximal number of conditions to appear in the generated rule
Returns: ContinuumRule
A random valid continuum rule
"""
if min_body_size > max_body_size:
raise ValueError(
"min_body_size must be inferior or equal to max_body_size")
if min_body_size > len(variables):
raise ValueError(
"min_body_size can't exceed the number of variables")
if max_body_size > len(variables):
raise ValueError(
"max_body_size can't exceed the number of variables")
size = random.randint(min_body_size, max_body_size)
locked = []
r = ContinuumRule(head_variable, head_value)
while r.size() < size:
var = random.randint(0, len(variables) - 1)
val = Continuum.random(domains[var].get_min_value(),
domains[var].get_max_value())
if var not in locked:
r.set_condition(var, val)
locked.append(var)
return r
def test_size(self):
eprint(">> Continuum.size(self)")
for i in range(self.__nb_unit_test):
# empty set
c = Continuum()
self.assertEqual(c.size(), 0.0)
# regular
c = Continuum.random(self.__min_value, self.__max_value)
if not c.is_empty():
self.assertEqual(c.size(),
c.get_max_value() - c.get_min_value())
def test_precision(self):
print(">> ContinuumLogicProgram.precision(expected, predicted)")
self.assertEqual(ContinuumLogicProgram.precision([],[]), 1.0)
# Equal programs
for i in range(self.__nb_unit_test):
variables, domains = self.random_system()
nb_states = random.randint(1,100)
expected = []
predicted = []
for j in range(nb_states):
s1 = [ random.uniform(d.get_min_value(),d.get_max_value()) for d in domains ]
s2 = [ random.uniform(d.get_min_value(),d.get_max_value()) for d in domains ]
s2_ = [ Continuum.random(d.get_min_value(), d.get_max_value()) for d in domains ]
expected.append( (s1,s2) )
predicted.append( (s1,s2_) )
precision = ContinuumLogicProgram.precision(expected, predicted)
error = 0
for j in range(len(expected)):
s1, s2 = expected[j]
s1_, s2_ = predicted[j]
for k in range(len(s2)):
if not s2_[k].includes(s2[k]):
error += 1
total = nb_states * len(variables)
self.assertEqual( precision, 1.0 - (error / total) )
#eprint("precision: ", precision)
# error of size
state_id = random.randint(0, len(expected)-1)
modif = random.randint(1,len(expected[state_id]))
expected[state_id] = ( expected[state_id][0][:-modif], expected[state_id][1] )
self.assertRaises(ValueError, ContinuumLogicProgram.precision, expected, predicted)
def test___init__(self):
print(">> ContinuumLogicProgram.__init__(self, variables, domains, rules)")
for i in range(self.__nb_unit_test):
variables, domains = self.random_system()
rules = []
for j in range(random.randint(0,self.__nb_rules)):
r = self.random_rule(variables, domains)
rules.append(r)
p = ContinuumLogicProgram(variables, domains, rules)
self.assertEqual(p.get_variables(), variables)
self.assertEqual(p.get_domains(), domains)
self.assertEqual(p.get_rules(), rules)
modif = random.randint(1,len(variables))
self.assertRaises(ValueError, ContinuumLogicProgram, variables, domains[:-modif], rules)
for var in range(0, modif):
domains.append(Continuum.random(self.__min_value, self.__max_value, self.__min_domain_size))
self.assertRaises(ValueError, ContinuumLogicProgram, variables, domains, rules)
def test_set_upper_bound(self):
eprint(">> Continuum.set_upper_bound(self, value, included)")
for i in range(self.__nb_unit_test):
# Empty set
c = Continuum()
self.assertRaises(TypeError, c.set_upper_bound, "string", True)
self.assertRaises(TypeError, c.set_upper_bound, "string", False)
self.assertRaises(TypeError, c.set_upper_bound, 0.5, 10)
value = random.uniform(self.__min_value, self.__max_value)
# extend with exclusion gives empty set, mistake expected from user
# or both min and max will be changed and constructor must be used
self.assertRaises(ValueError, c.set_upper_bound, value, False)
c.set_upper_bound(value, True)
# Empty set to one value interval
self.assertEqual(c, Continuum(value, value, True, True))
# Regular continuum
# over min value
c = Continuum.random(self.__min_value, self.__max_value)
value = random.uniform(self.__min_value, c.get_min_value())
while value == c.get_min_value():
value = random.uniform(self.__min_value, c.get_min_value())
self.assertRaises(ValueError, c.set_upper_bound, value, True)
self.assertRaises(ValueError, c.set_upper_bound, value, False)
# on min value
c = Continuum.random(self.__min_value, self.__max_value)
c_old = c.copy()
value = c.get_min_value()
if not c.max_included() or not c.min_included():
c.set_upper_bound(value, False)
self.assertEqual(c,
Continuum()) # continuum reduced to empty set
else:
c.set_upper_bound(value, True)
self.assertEqual(c.get_max_value(), value)
self.assertEqual(c.max_included(), True)
self.assertEqual(c.get_max_value(), c.get_min_value())
self.assertEqual(c.get_min_value(), c_old.get_min_value())
self.assertEqual(c.min_included(), c_old.min_included())
# other valid value
c = Continuum.random(self.__min_value, self.__max_value)
c_old = c.copy()
value = random.uniform(c.get_min_value(), self.__max_value)
while value == c.get_min_value():
value = random.uniform(c.get_min_value(), self.__max_value)
c.set_upper_bound(value, True)
self.assertEqual(c.get_max_value(), value)
self.assertEqual(c.max_included(), True)
c = Continuum.random(self.__min_value, self.__max_value)
c_old = c.copy()
value = random.uniform(c.get_min_value(), self.__max_value)
while value == c.get_min_value():
value = random.uniform(c.get_min_value(), self.__max_value)
c.set_upper_bound(value, False)
self.assertEqual(c.get_max_value(), value)
self.assertEqual(c.max_included(), False)
def test__eq__(self):
eprint(">> Continuum.__eq__(self, continuum)")
for i in range(self.__nb_unit_test):
# emptyset
c = Continuum()
self.assertTrue(Continuum() == Continuum())
self.assertTrue(c == Continuum())
self.assertTrue(c == c)
self.assertFalse(Continuum() != Continuum())
self.assertFalse(c != Continuum())
self.assertFalse(c != c)
c = Continuum.random(self.__min_value, self.__max_value)
self.assertTrue(c == c)
self.assertFalse(c != c)
self.assertEqual(c == Continuum(), c.is_empty())
c_ = Continuum.random(self.__min_value, self.__max_value)
if c.is_empty() and c_.is_empty():
self.assertTrue(c == c_)
self.assertTrue(c != c_)
if c.is_empty() != c_.is_empty():
self.assertFalse(c == c_)
self.assertTrue(c != c_)
if c.get_min_value() != c_.get_min_value():
self.assertFalse(c == c_)
self.assertTrue(c != c_)
if c.get_max_value() != c_.get_max_value():
self.assertFalse(c == c_)
self.assertTrue(c != c_)
if c.min_included() != c_.min_included():
self.assertFalse(c == c_)
self.assertTrue(c != c_)
if c.max_included() != c_.max_included():
self.assertFalse(c == c_)
self.assertTrue(c != c_)
# exaustive modifications
if not c.is_empty():
c_ = c.copy()
value = random.uniform(1, 100)
c_.set_lower_bound(c.get_min_value() - value, True)
self.assertFalse(c == c_)
self.assertTrue(c != c_)
c_.set_lower_bound(c.get_min_value() - value, False)
self.assertFalse(c == c_)
self.assertTrue(c != c_)
c_ = c.copy()
c_.set_lower_bound(c.get_min_value(), not c.min_included())
self.assertFalse(c == c_)
self.assertTrue(c != c_)
c_ = c.copy()
value = random.uniform(1, 100)
c_.set_upper_bound(c.get_min_value() + value, True)
self.assertFalse(c == c_)
self.assertTrue(c != c_)
c_.set_upper_bound(c.get_min_value() + value, False)
self.assertFalse(c == c_)
self.assertTrue(c != c_)
c_ = c.copy()
c_.set_upper_bound(c.get_max_value(), not c.max_included())
self.assertFalse(c == c_)
self.assertTrue(c != c_)
# different type
self.assertFalse(c == "test")
self.assertFalse(c == 0)
self.assertFalse(c == True)
self.assertFalse(c == [])
def test_intersects(self):
eprint(">> Continuum.intersects(self, continuum)")
for i in range(self.__nb_unit_test):
c = Continuum.random(self.__min_value, self.__max_value)
c_ = Continuum()
# emptyset
self.assertFalse(c.intersects(c_))
self.assertFalse(c_.intersects(c))
self.assertFalse(c_.intersects(c_))
# stricly before
c = Continuum.random(self.__min_value, self.__max_value)
c_ = Continuum.random(c.get_min_value() - 100, c.get_min_value())
self.assertFalse(c.intersects(c_))
self.assertFalse(c_.intersects(c))
# touching on lower bound
c = Continuum.random(self.__min_value, self.__max_value)
c_ = Continuum.random(c.get_min_value() - 100, c.get_min_value())
c_.set_upper_bound(c.get_min_value(), True)
self.assertEqual(c.intersects(c_), c.min_included())
self.assertEqual(c_.intersects(c), c.min_included())
c_.set_upper_bound(c.get_min_value(), False)
self.assertFalse(c.intersects(c_))
self.assertFalse(c_.intersects(c))
# strictly after
c = Continuum.random(self.__min_value, self.__max_value)
c_ = Continuum.random(c.get_max_value(), c.get_max_value() + 100)
self.assertFalse(c.intersects(c_))
self.assertFalse(c_.intersects(c))
# touching on lower bound
c = Continuum.random(self.__min_value, self.__max_value)
c_ = Continuum.random(c.get_max_value(), c.get_max_value() + 100)
c_.set_lower_bound(c.get_max_value(), True)
self.assertEqual(c.intersects(c_), c.max_included())
self.assertEqual(c_.intersects(c), c.max_included())
c_.set_lower_bound(c.get_max_value(), False)
self.assertFalse(c.intersects(c_))
self.assertFalse(c_.intersects(c))
# same (not empty)
c = Continuum.random(self.__min_value, self.__max_value)
while c.is_empty():
c = Continuum.random(self.__min_value, self.__max_value)
self.assertTrue(c.includes(c))
# smaller
c_ = Continuum.random(c.get_min_value(), c.get_max_value())
while c_.get_min_value() == c.get_min_value() and c_.get_max_value(
) == c.get_max_value():
c_ = Continuum.random(c.get_min_value(), c.get_max_value())
self.assertTrue(c.intersects(c_))
self.assertTrue(c_.intersects(c))
# bigger
c_ = Continuum.random(c.get_min_value() - 100,
c.get_max_value() + 100)
while c_.get_min_value() >= c.get_min_value() or c_.get_max_value(
) <= c.get_max_value():
c_ = Continuum.random(c.get_min_value() - 100,
c.get_max_value() + 100)
#eprint(c.to_string())
#eprint(c_.to_string())
self.assertTrue(c.intersects(c_))
self.assertTrue(c_.intersects(c))
def test_includes(self):
eprint(">> Continuum.includes(self, element)")
for i in range(self.__nb_unit_test):
# bad argument type
c = Continuum.random(self.__min_value, self.__max_value)
self.assertRaises(TypeError, c.includes, "test")
# float argument
#----------------
# empty set includes nothing
c = Continuum()
value = random.uniform(self.__min_value, self.__max_value)
self.assertFalse(c.includes(value))
c = Continuum.random(self.__min_value, self.__max_value)
# Before min
value = c.get_min_value()
while value == c.get_min_value():
value = random.uniform(c.get_min_value() - 100.0,
c.get_min_value())
self.assertFalse(c.includes(value))
# on min bound
self.assertEqual(c.includes(c.get_min_value()), c.min_included())
# Inside
value = c.get_min_value()
while value == c.get_min_value() or value == c.get_max_value():
value = random.uniform(c.get_min_value(), c.get_max_value())
self.assertTrue(c.includes(value))
# on max bound
self.assertEqual(c.includes(c.get_max_value()), c.max_included())
# after max bound
value = c.get_max_value()
while value == c.get_max_value():
value = random.uniform(c.get_max_value(),
c.get_max_value() + 100.0)
self.assertFalse(c.includes(value))
# int argument
#--------------
# empty set includes nothing
c = Continuum()
value = random.randint(int(self.__min_value),
int(self.__max_value))
self.assertFalse(c.includes(value))
c = Continuum.random(self.__min_value, self.__max_value)
while int(c.get_max_value()) - int(c.get_min_value()) <= 1:
min = random.uniform(self.__min_value, self.__max_value)
max = random.uniform(min, self.__max_value)
c = Continuum.random(min, max)
#eprint(c.to_string())
# Before min
value = random.randint(int(c.get_min_value() - 100),
int(c.get_min_value()) - 1)
self.assertFalse(c.includes(value))
# on min bound
self.assertEqual(c.includes(c.get_min_value()), c.min_included())
# Inside
value = random.randint(
int(c.get_min_value()) + 1,
int(c.get_max_value()) - 1)
#eprint(value)
self.assertTrue(c.includes(value))
# on max bound
self.assertEqual(c.includes(c.get_max_value()), c.max_included())
# after max bound
value = random.randint(
int(c.get_max_value()) + 1, int(c.get_max_value() + 100))
self.assertFalse(c.includes(value))
# continuum argument
#--------------------
# 0) c is empty set
c = Continuum()
c_ = Continuum()
self.assertTrue(c.includes(c_)) # empty set VS empty set
c_ = Continuum.random(self.__min_value, self.__max_value)
while c_.is_empty():
c_ = Continuum.random(self.__min_value, self.__max_value)
self.assertFalse(c.includes(c_)) # empty set VS non empty
# 1) c is non empty
c = Continuum.random(self.__min_value, self.__max_value)
self.assertTrue(c.includes(Continuum())) # non empty VS empty set
self.assertTrue(c.includes(c)) # includes itself
# 1.1) Lower bound over
c_ = Continuum.random(c.get_min_value(), self.__max_value)
while c_.is_empty():
c_ = Continuum.random(c.get_min_value(), self.__max_value)
value = c.get_min_value()
while value == c.get_min_value():
value = random.uniform(c.get_min_value() - 100,
c.get_min_value())
c_.set_lower_bound(value, random.choice([True, False]))
self.assertFalse(c.includes(c_))
# 1.2) on min bound
c_ = Continuum.random(c.get_min_value(), self.__max_value)
while c_.is_empty():
c_ = Continuum.random(c.get_min_value(), self.__max_value)
c_.set_lower_bound(c.get_min_value(), random.choice([True, False]))
if not c.min_included() and c_.min_included(): # one value over
self.assertFalse(c.includes(c_))
# 1.3) upper bound over
c_ = Continuum.random(self.__min_value, c.get_max_value())
while c_.is_empty():
c_ = Continuum.random(self.__min_value, c.get_max_value())
value = c.get_max_value()
while value == c.get_max_value():
value = random.uniform(c.get_max_value(),
c.get_max_value() + 100)
c_.set_upper_bound(value, random.choice([True, False]))
self.assertFalse(c.includes(c_))
# 1.4) on upper bound
c_ = Continuum.random(self.__min_value, c.get_max_value())
while c_.is_empty():
c_ = Continuum.random(self.__min_value, c.get_max_value())
c_.set_upper_bound(c.get_max_value(), random.choice([True, False]))
if not c.max_included() and c_.max_included(): # one value over
self.assertFalse(c.includes(c_))
# 1.5) inside
min = c.get_min_value()
while min == c.get_min_value():
min = random.uniform(c.get_min_value(), c.get_max_value())
max = c.get_max_value()
while max == c.get_max_value():
max = random.uniform(min, c.get_max_value())
c_ = Continuum(min, max, random.choice([True, False]),
random.choice([True, False]))
self.assertTrue(c.includes(c_))
self.assertFalse(c_.includes(c))
def test_least_revision(self):
eprint(">> ACEDIA.least_revision(rule, state_1, state_2)")
for i in range(self.__nb_unit_test):
variables, domains = self.random_system()
state_1 = self.random_state(variables, domains)
state_2 = self.random_state(variables, domains)
# not matching
#--------------
rule = self.random_rule(variables, domains)
while rule.matches(state_1):
rule = self.random_rule(variables, domains)
self.assertRaises(ValueError, ACEDIA.least_revision, rule, state_1,
state_2)
# matching
#--------------
rule = self.random_rule(variables, domains)
while not rule.matches(state_1):
rule = self.random_rule(variables, domains)
head_var = rule.get_head_variable()
target_val = state_2[rule.get_head_variable()]
# Consistent
head_value = Continuum()
while not head_value.includes(target_val):
head_value = Continuum.random(
domains[head_var].get_min_value(),
domains[head_var].get_max_value())
rule.set_head_value(head_value)
self.assertRaises(ValueError, ACEDIA.least_revision, rule, state_1,
state_2)
# Empty set head
rule.set_head_value(Continuum())
LR = ACEDIA.least_revision(rule, state_1, state_2)
lg = rule.copy()
lg.set_head_value(Continuum(target_val, target_val, True, True))
self.assertTrue(lg in LR)
nb_valid_revision = 1
for var, val in rule.get_body():
state_value = state_1[var]
# min rev
ls = rule.copy()
new_val = val.copy()
new_val.set_lower_bound(state_value, False)
if not new_val.is_empty():
ls.set_condition(var, new_val)
self.assertTrue(ls in LR)
nb_valid_revision += 1
# max rev
ls = rule.copy()
new_val = val.copy()
new_val.set_upper_bound(state_value, False)
if not new_val.is_empty():
ls.set_condition(var, new_val)
self.assertTrue(ls in LR)
nb_valid_revision += 1
self.assertEqual(len(LR), nb_valid_revision)
#eprint(nb_valid_revision)
# usual head
head_value = Continuum.random(domains[head_var].get_min_value(),
domains[head_var].get_max_value())
while head_value.includes(target_val):
head_value = Continuum.random(
domains[head_var].get_min_value(),
domains[head_var].get_max_value())
rule.set_head_value(head_value)
LR = ACEDIA.least_revision(rule, state_1, state_2)
lg = rule.copy()
head_value = lg.get_head_value()
if target_val <= head_value.get_min_value():
head_value.set_lower_bound(target_val, True)
else:
head_value.set_upper_bound(target_val, True)
lg.set_head_value(head_value)
self.assertTrue(lg in LR)
nb_valid_revision = 1
for var, val in rule.get_body():
state_value = state_1[var]
# min rev
ls = rule.copy()
new_val = val.copy()
new_val.set_lower_bound(state_value, False)
if not new_val.is_empty():
ls.set_condition(var, new_val)
self.assertTrue(ls in LR)
nb_valid_revision += 1
# max rev
ls = rule.copy()
new_val = val.copy()
new_val.set_upper_bound(state_value, False)
if not new_val.is_empty():
ls.set_condition(var, new_val)
self.assertTrue(ls in LR)
nb_valid_revision += 1
self.assertEqual(len(LR), nb_valid_revision)
