def test_consistency():
# From standard example
# [ LowLevelRequest("EQ", 1, [1, 2]), LowLevelRequest("EQ", 1, [3, 4]), ...]
backend_request = BackendRequest(0)
Consistency.apply(block, backend_request)
assert backend_request.ll_requests == \
list(map(lambda x: LowLevelRequest("EQ", 1, [x, x+1]), range(1, 24, 2)))
# Different case
backend_request = BackendRequest(0)
f = Factor("a", ["b", "c", "d", "e"])
f_block = fully_cross_block([f], [f], [])
Consistency.apply(f_block, backend_request)
assert backend_request.ll_requests == \
list(map(lambda x: LowLevelRequest("EQ", 1, [x, x+1, x+2, x+3]), range(1, 16, 4)))
# Varied level lengths
backend_request = BackendRequest(0)
f1 = Factor("a", ["b", "c", "d"])
f2 = Factor("e", ["f"])
f_block = fully_cross_block([f1, f2], [f1, f2], [])
Consistency.apply(f_block, backend_request)
assert backend_request.ll_requests == [
LowLevelRequest("EQ", 1, [1, 2, 3]),
LowLevelRequest("EQ", 1, [4]),
LowLevelRequest("EQ", 1, [5, 6, 7]),
LowLevelRequest("EQ", 1, [8]),
LowLevelRequest("EQ", 1, [9, 10, 11]),
LowLevelRequest("EQ", 1, [12])
]
def test_derivation_with_general_window():
block = fully_cross_block([color, text, congruent_bookend], [color, text],
[])
# congruent bookend - yes
d = Derivation(16, [[0, 2], [1, 3]], congruent_bookend)
backend_request = BackendRequest(19)
d.apply(block, backend_request)
(expected_cnf, expected_fresh) = to_cnf_tseitin(
And([
Iff(17, Or([And([1, 3]), And([2, 4])])),
Iff(19, Or([And([13, 15]), And([14, 16])]))
]), 19)
assert backend_request.fresh == expected_fresh
assert backend_request.cnfs == [expected_cnf]
# congruent bookend - no
d = Derivation(17, [[0, 3], [1, 2]], congruent_bookend)
backend_request = BackendRequest(19)
d.apply(block, backend_request)
(expected_cnf, expected_fresh) = to_cnf_tseitin(
And([
Iff(18, Or([And([1, 4]), And([2, 3])])),
Iff(20, Or([And([13, 16]), And([14, 15])]))
]), 19)
assert backend_request.fresh == expected_fresh
assert backend_request.cnfs == [expected_cnf]
def test_derivation_with_multiple_transitions():
block = fully_cross_block(
[color, text, color_repeats_factor, text_repeats_factor],
[color, text], [])
# Text repeats derivation
d = Derivation(22, [[2, 6], [3, 7]], text_repeats_factor)
backend_request = BackendRequest(29)
d.apply(block, backend_request)
(expected_cnf, expected_fresh) = to_cnf_tseitin(
And([
Iff(23, Or([And([3, 7]), And([4, 8])])),
Iff(25, Or([And([7, 11]), And([8, 12])])),
Iff(27, Or([And([11, 15]), And([12, 16])]))
]), 29)
assert backend_request.fresh == expected_fresh
assert backend_request.cnfs == [expected_cnf]
# Text does not repeat derivation
d = Derivation(23, [[2, 7], [3, 6]], text_repeats_factor)
backend_request = BackendRequest(29)
d.apply(block, backend_request)
(expected_cnf, expected_fresh) = to_cnf_tseitin(
And([
Iff(24, Or([And([3, 8]), And([4, 7])])),
Iff(26, Or([And([7, 12]), And([8, 11])])),
Iff(28, Or([And([11, 16]), And([12, 15])]))
]), 29)
assert backend_request.fresh == expected_fresh
assert backend_request.cnfs == [expected_cnf]
def test_derivation_with_transition():
block = fully_cross_block([color, text, color_repeats_factor],
[color, text], [])
# Color repeats derivation
d = Derivation(16, [[0, 4], [1, 5]], color_repeats_factor)
backend_request = BackendRequest(23)
d.apply(block, backend_request)
(expected_cnf, expected_fresh) = to_cnf_tseitin(
And([
Iff(17, Or([And([1, 5]), And([2, 6])])),
Iff(19, Or([And([5, 9]), And([6, 10])])),
Iff(21, Or([And([9, 13]), And([10, 14])]))
]), 23)
assert backend_request.fresh == expected_fresh
assert backend_request.cnfs == [expected_cnf]
# Color does not repeat derivation
d = Derivation(17, [[0, 5], [1, 4]], color_repeats_factor)
backend_request = BackendRequest(23)
d.apply(block, backend_request)
(expected_cnf, expected_fresh) = to_cnf_tseitin(
And([
Iff(18, Or([And([1, 6]), And([2, 5])])),
Iff(20, Or([And([5, 10]), And([6, 9])])),
Iff(22, Or([And([9, 14]), And([10, 13])]))
]), 23)
assert backend_request.fresh == expected_fresh
assert backend_request.cnfs == [expected_cnf]
def test_derivation():
# Congruent derivation
d = Derivation(4, [[0, 2], [1, 3]], con_factor)
backend_request = BackendRequest(24)
d.apply(block, backend_request)
(expected_cnf, expected_fresh) = to_cnf_tseitin(
And([
Iff(5, Or([And([1, 3]), And([2, 4])])),
Iff(11, Or([And([7, 9]), And([8, 10])])),
Iff(17, Or([And([13, 15]), And([14, 16])])),
Iff(23, Or([And([19, 21]), And([20, 22])]))
]), 24)
assert backend_request.fresh == expected_fresh
assert backend_request.cnfs == [expected_cnf]
# Incongruent derivation
d = Derivation(5, [[0, 3], [1, 2]], con_factor)
backend_request = BackendRequest(24)
d.apply(block, backend_request)
(expected_cnf, expected_fresh) = to_cnf_tseitin(
And([
Iff(6, Or([And([1, 4]), And([2, 3])])),
Iff(12, Or([And([7, 10]), And([8, 9])])),
Iff(18, Or([And([13, 16]), And([14, 15])])),
Iff(24, Or([And([19, 22]), And([20, 21])]))
]), 24)
assert backend_request.fresh == expected_fresh
assert backend_request.cnfs == [expected_cnf]
def test_forbid():
f = Forbid(("color", "red"))
backend_request = BackendRequest(0)
f.apply(block, backend_request)
assert backend_request.cnfs == [And([-1, -7, -13, -19])]
f = Forbid(("congruent?", "con"))
backend_request = BackendRequest(0)
f.apply(block, backend_request)
assert backend_request.cnfs == [And([-5, -11, -17, -23])]
def test_exclude():
f = Exclude(color, get_level_from_name(color, "red"))
backend_request = BackendRequest(0)
f.apply(block, backend_request)
assert backend_request.cnfs == [And([-1, -7, -13, -19])]
f = Exclude(con_factor, get_level_from_name(con_factor, "con"))
backend_request = BackendRequest(0)
f.apply(block, backend_request)
assert backend_request.cnfs == [And([-5, -11, -17, -23])]
def test_fully_cross_with_uncrossed_simple_factors():
other = Factor('other', ['l1', 'l2'])
block = fully_cross_block([color, text, other], [color, text], [])
backend_request = BackendRequest(25)
FullyCross.apply(block, backend_request)
(expected_cnf, _) = to_cnf_tseitin(
And([
Iff(25, And([1, 3])),
Iff(26, And([1, 4])),
Iff(27, And([2, 3])),
Iff(28, And([2, 4])),
Iff(29, And([7, 9])),
Iff(30, And([7, 10])),
Iff(31, And([8, 9])),
Iff(32, And([8, 10])),
Iff(33, And([13, 15])),
Iff(34, And([13, 16])),
Iff(35, And([14, 15])),
Iff(36, And([14, 16])),
Iff(37, And([19, 21])),
Iff(38, And([19, 22])),
Iff(39, And([20, 21])),
Iff(40, And([20, 22]))
]), 41)
assert backend_request.fresh == 74
assert backend_request.cnfs == [expected_cnf]
assert backend_request.ll_requests == [
LowLevelRequest("GT", 0, [25, 29, 33, 37]),
LowLevelRequest("GT", 0, [26, 30, 34, 38]),
LowLevelRequest("GT", 0, [27, 31, 35, 39]),
LowLevelRequest("GT", 0, [28, 32, 36, 40])
]
def test_fully_cross_with_transition_in_design(design):
block = fully_cross_block(design, [color, text], [])
backend_request = BackendRequest(23)
FullyCross.apply(block, backend_request)
(expected_cnf, _) = to_cnf_tseitin(
And([
Iff(23, And([1, 3])),
Iff(24, And([1, 4])),
Iff(25, And([2, 3])),
Iff(26, And([2, 4])),
Iff(27, And([5, 7])),
Iff(28, And([5, 8])),
Iff(29, And([6, 7])),
Iff(30, And([6, 8])),
Iff(31, And([9, 11])),
Iff(32, And([9, 12])),
Iff(33, And([10, 11])),
Iff(34, And([10, 12])),
Iff(35, And([13, 15])),
Iff(36, And([13, 16])),
Iff(37, And([14, 15])),
Iff(38, And([14, 16]))
]), 39)
assert backend_request.fresh == 72
assert backend_request.cnfs == [expected_cnf]
assert backend_request.ll_requests == [
LowLevelRequest("GT", 0, [23, 27, 31, 35]),
LowLevelRequest("GT", 0, [24, 28, 32, 36]),
LowLevelRequest("GT", 0, [25, 29, 33, 37]),
LowLevelRequest("GT", 0, [26, 30, 34, 38])
]
def test_fully_cross_with_constraint():
(expected_cnf, _) = to_cnf_tseitin(
And([
Iff(25, And([1, 3])),
Iff(26, And([1, 4])),
Iff(27, And([2, 3])),
Iff(28, And([2, 4])),
Iff(29, And([7, 9])),
Iff(30, And([7, 10])),
Iff(31, And([8, 9])),
Iff(32, And([8, 10])),
Iff(33, And([13, 15])),
Iff(34, And([13, 16])),
Iff(35, And([14, 15])),
Iff(36, And([14, 16])),
Iff(37, And([19, 21])),
Iff(38, And([19, 22])),
Iff(39, And([20, 21])),
Iff(40, And([20, 22]))
]), 41)
backend_request = BackendRequest(25)
FullyCross.apply(block, backend_request)
assert backend_request.fresh == 74
assert backend_request.cnfs == [expected_cnf]
assert backend_request.ll_requests == [
LowLevelRequest("GT", 0, [25, 29, 33, 37]),
LowLevelRequest("GT", 0, [26, 30, 34, 38]),
LowLevelRequest("GT", 0, [27, 31, 35, 39]),
LowLevelRequest("GT", 0, [28, 32, 36, 40])
]
def test_fully_cross_simple():
block = fully_cross_block([color, text], [color, text], [])
(expected_cnf, _) = to_cnf_tseitin(
And([
Iff(17, And([1, 3])),
Iff(18, And([1, 4])),
Iff(19, And([2, 3])),
Iff(20, And([2, 4])),
Iff(21, And([5, 7])),
Iff(22, And([5, 8])),
Iff(23, And([6, 7])),
Iff(24, And([6, 8])),
Iff(25, And([9, 11])),
Iff(26, And([9, 12])),
Iff(27, And([10, 11])),
Iff(28, And([10, 12])),
Iff(29, And([13, 15])),
Iff(30, And([13, 16])),
Iff(31, And([14, 15])),
Iff(32, And([14, 16]))
]), 33)
backend_request = BackendRequest(17)
FullyCross.apply(block, backend_request)
assert backend_request.fresh == 66
assert backend_request.cnfs == [expected_cnf]
assert backend_request.ll_requests == [
LowLevelRequest("GT", 0, [17, 21, 25, 29]),
LowLevelRequest("GT", 0, [18, 22, 26, 30]),
LowLevelRequest("GT", 0, [19, 23, 27, 31]),
LowLevelRequest("GT", 0, [20, 24, 28, 32])
]
def test_consistency_with_transition_first_and_uneven_level_lengths():
color3 = Factor("color3", ["red", "blue", "green"])
yes_fn = lambda colors: colors[0] == colors[1] == colors[2]
no_fn = lambda colors: not yes_fn(colors)
color3_repeats_factor = Factor("color3 repeats?", [
DerivedLevel("yes", Window(yes_fn, [color3], 3, 1)),
DerivedLevel("no", Window(no_fn, [color3], 3, 1))
])
block = fully_cross_block([color3_repeats_factor, color3, text],
[color3, text], [])
backend_request = BackendRequest(0)
Consistency.apply(block, backend_request)
assert backend_request.ll_requests == [
LowLevelRequest("EQ", 1, [1, 2, 3]),
LowLevelRequest("EQ", 1, [4, 5]),
LowLevelRequest("EQ", 1, [6, 7, 8]),
LowLevelRequest("EQ", 1, [9, 10]),
LowLevelRequest("EQ", 1, [11, 12, 13]),
LowLevelRequest("EQ", 1, [14, 15]),
LowLevelRequest("EQ", 1, [16, 17, 18]),
LowLevelRequest("EQ", 1, [19, 20]),
LowLevelRequest("EQ", 1, [21, 22, 23]),
LowLevelRequest("EQ", 1, [24, 25]),
LowLevelRequest("EQ", 1, [26, 27, 28]),
LowLevelRequest("EQ", 1, [29, 30]),
LowLevelRequest("EQ", 1, [31, 32]),
LowLevelRequest("EQ", 1, [33, 34]),
LowLevelRequest("EQ", 1, [35, 36]),
LowLevelRequest("EQ", 1, [37, 38])
]
def apply_to_backend_request(self,
block: Block,
level: Tuple[Factor, Union[SimpleLevel, DerivedLevel]],
backend_request: BackendRequest
) -> None:
sublists = self._build_variable_sublists(block, level, self.k)
implications = []
# Handle the regular cases (1 => 2 ^ ... ^ n ^ ~n+1)
trim = len(sublists) if self.k > 1 else len(sublists) - 1
for idx, l in enumerate(sublists[:trim]):
if idx > 0:
p_list = [Not(sublists[idx-1][0]), l[0]]
p = And(p_list) if len(p_list) > 1 else p_list[0]
else:
p = l[0]
if idx < len(sublists) - 1:
q_list = cast(List[Any], l[1:]) + [Not(sublists[idx+1][-1])]
q = And(q_list) if len(q_list) > 1 else q_list[0]
else:
q = And(l[1:]) if len(l[1:]) > 1 else l[self.k - 1]
implications.append(If(p, q))
# Handle the tail
if len(sublists[-1]) > 1:
tail = sublists[-1]
tail.reverse()
for idx in range(len(tail) - 1):
implications.append(If(l[idx], l[idx + 1]))
(cnf, new_fresh) = block.cnf_fn(And(implications), backend_request.fresh)
backend_request.cnfs.append(cnf)
backend_request.fresh = new_fresh
def test_exclude_with_three_derived_levels():
color_list = ["red", "green", "blue"]
color = Factor("color", color_list)
text = Factor("text", color_list)
def count_diff(colors, texts):
changes = 0
if (colors[0] != colors[1]): changes += 1
if (texts[0] != texts[1]): changes += 1
return changes
def make_k_diff_level(k):
def k_diff(colors, texts):
return count_diff(colors, texts) == k
return DerivedLevel(str(k), Transition(k_diff, [color, text]))
changed = Factor(
"changed",
[make_k_diff_level(0),
make_k_diff_level(1),
make_k_diff_level(2)])
exclude_constraint = Exclude(changed, get_level_from_name(changed, "2"))
design = [color, text, changed]
crossing = [color, text]
block = fully_cross_block(design, crossing, [exclude_constraint])
backend_request = BackendRequest(0)
exclude_constraint.apply(block, backend_request)
assert backend_request.cnfs == [
And([-57, -60, -63, -66, -69, -72, -75, -78])
]
def __desugar(block: Block) -> BackendRequest:
fresh = 1 + block.variables_per_sample()
backend_request = BackendRequest(fresh)
for c in block.constraints:
c.apply(block, backend_request)
return backend_request
def test_consistency_with_multiple_transitions(design):
block = fully_cross_block(design, [color, text], [])
backend_request = BackendRequest(0)
Consistency.apply(block, backend_request)
assert backend_request.ll_requests == \
list(map(lambda x: LowLevelRequest("EQ", 1, [x, x+1]), range(1, 28, 2)))
def test_exclude_with_transition():
block = fully_cross_block([color, text, color_repeats_factor],
[color, text], [])
c = Exclude(color_repeats_factor,
get_level_from_name(color_repeats_factor, "yes"))
backend_request = BackendRequest(0)
c.apply(block, backend_request)
assert backend_request.cnfs == [And([-17, -19, -21])]
def test_exclude_with_general_window():
block = fully_cross_block([color, text, congruent_bookend], [color, text],
[])
c = Exclude(congruent_bookend, get_level_from_name(congruent_bookend,
"yes"))
backend_request = BackendRequest(0)
c.apply(block, backend_request)
assert backend_request.cnfs == [And([-17, -19])]
def test_consistency_with_transition(design):
block = fully_cross_block(design, [color, text], [])
backend_request = BackendRequest(0)
Consistency.apply(block, backend_request)
# Because the color_repeats_factor doesn't apply to the first trial, (there isn't a previous trial
# to compare to) the variables only go up to 22.
assert backend_request.ll_requests == \
list(map(lambda x: LowLevelRequest("EQ", 1, [x, x+1]), range(1, 22, 2)))
def apply(block: MultipleCrossBlock, backend_request: BackendRequest) -> None:
# Treat each crossing seperately, and repeat the same process as fullycross
for c in block.crossing:
fresh = backend_request.fresh
# Step 1: Get a list of the trials that are involved in the crossing.
crossing_size = max(block.min_trials, block.crossing_size())
crossing_trials = list(filter(lambda t: all(map(lambda f: f.applies_to_trial(t),
c)),
range(1, block.trials_per_sample() + 1)))
crossing_trials = crossing_trials[:crossing_size]
# Step 2: For each trial, cross all levels of all factors in the crossing.
crossing_factors = list(map(lambda t: (list(product(*[block.factor_variables_for_trial(f, t) for f in c]))), crossing_trials))
# Step 3: For each trial, cross all levels of all design-only factors in the crossing.
design_factors = cast(List[List[List[int]]], [])
design_factors = list(map(lambda _: [], crossing_trials))
for f in list(filter(lambda f: f not in c and not f.has_complex_window, block.design)):
for i, t in enumerate(crossing_trials):
design_factors[i].append(block.factor_variables_for_trial(f, t))
design_combinations = cast(List[List[Tuple[int, ...]]], [])
design_combinations = list(map(lambda l: list(product(*l)), design_factors))
# Step 4: For each trial, combine each of the crossing factors with all of the design-only factors.
crossings = cast(List[List[List[Tuple[int, ...]]]], [])
for i, t in enumerate(crossing_trials):
crossings.append(list(map(lambda c: [c] + design_combinations[i], crossing_factors[i])))
# Step 5: Remove crossings that are not possible.
# From here on ignore all values other than the first in every list.
crossings = block.filter_excluded_derived_levels(crossings)
# Step 6: Allocate additional variables to represent each crossing.
num_state_vars = list(map(lambda c: len(c), crossings))
state_vars = list(range(fresh, fresh + sum(num_state_vars)))
fresh += sum(num_state_vars)
# Step 7: Associate each state variable with its crossing.
flattened_crossings = list(chain.from_iterable(crossings))
iffs = list(map(lambda n: Iff(state_vars[n], And([*flattened_crossings[n][0]])), range(len(state_vars))))
# Step 8: Constrain each crossing to occur in only one trial.
states = list(chunk(state_vars, block.crossing_size()))
transposed = cast(List[List[int]], list(map(list, zip(*states))))
# We Use n < 2 rather than n = 1 here because they may exclude some levels from the crossing.
# This ensures that there won't be duplicates, while still allowing some to be missing.
# backend_request.ll_requests += list(map(lambda l: LowLevelRequest("LT", 2, l), transposed))
backend_request.ll_requests += list(map(lambda l: LowLevelRequest("GT", 0, l), transposed))
(cnf, new_fresh) = block.cnf_fn(And(iffs), fresh)
backend_request.cnfs.append(cnf)
backend_request.fresh = new_fresh
def build_backend_request(self) -> BackendRequest:
fresh = 1 + self.variables_per_sample()
backend_request = BackendRequest(fresh)
from sweetpea.constraints import MinimumTrials
for c in self.constraints:
if isinstance(c, MinimumTrials):
continue
c.apply(self, backend_request)
return backend_request
def __apply_derivation(self, block: Block, backend_request: BackendRequest) -> None:
trial_size = block.variables_per_trial()
cross_size = block.trials_per_sample()
iffs = []
for n in range(cross_size):
or_clause = Or(list(And(list(map(lambda x: x + (n * trial_size) + 1, l))) for l in self.dependent_idxs))
iffs.append(Iff(self.derived_idx + (n * trial_size) + 1, or_clause))
(cnf, new_fresh) = block.cnf_fn(And(iffs), backend_request.fresh)
backend_request.cnfs.append(cnf)
backend_request.fresh = new_fresh
def build_backend_request(self) -> BackendRequest:
"""Apply all constraints to build a :class:`.BackendRequest`. Formerly
known as ``__desugar``.
"""
fresh = 1 + self.variables_per_sample()
backend_request = BackendRequest(fresh)
from sweetpea.constraints import MinimumTrials
for c in self.constraints:
if isinstance(c, MinimumTrials):
continue
c.apply(self, backend_request)
return backend_request
def apply_to_backend_request(self, block: Block, level: Tuple[Factor, Union[SimpleLevel, DerivedLevel]],
backend_request: BackendRequest) -> None:
# Request sublists for k+1 to allow us to determine the transition
sublists = self._build_variable_sublists(block, level, self.k + 1)
implications = []
if sublists:
# Starting corner case
implications.append(If(sublists[0][0], And(sublists[0][1:-1])))
for sublist in sublists:
implications.append(If(And([Not(sublist[0]), sublist[1]]), And(sublist[2:])))
# Ending corner case
implications.append(If(sublists[-1][-1], And(sublists[-1][1:-1])))
(cnf, new_fresh) = block.cnf_fn(And(implications), backend_request.fresh)
backend_request.cnfs.append(cnf)
backend_request.fresh = new_fresh
def test_derivation_with_unusual_order():
d = Derivation(0, [[4, 2], [5, 3]], congruency)
backend_request = BackendRequest(64)
d.apply(block, backend_request)
(expected_cnf, expected_fresh) = to_cnf_tseitin(
And([
Iff(1, Or([And([5, 3]), And([6, 4])])),
Iff(9, Or([And([13, 11]), And([14, 12])])),
Iff(17, Or([And([21, 19]), And([22, 20])])),
Iff(25, Or([And([29, 27]), And([30, 28])])),
Iff(33, Or([And([37, 35]), And([38, 36])])),
Iff(41, Or([And([45, 43]), And([46, 44])])),
Iff(49, Or([And([53, 51]), And([54, 52])])),
Iff(57, Or([And([61, 59]), And([62, 60])])),
]), 64)
assert backend_request.fresh == expected_fresh
assert backend_request.cnfs == [expected_cnf]
def __apply_derivation_with_complex_window(self, block: Block, backend_request: BackendRequest) -> None:
trial_size = block.variables_per_trial()
trial_count = block.trials_per_sample()
iffs = []
f = self.factor
window = f.levels[0].window
t = 0
for n in range(trial_count):
if not f.applies_to_trial(n + 1):
continue
num_levels = len(f.levels)
get_trial_size = lambda x: trial_size if x < block.grid_variables() else len(block.decode_variable(x+1)[0].levels)
or_clause = Or(list(And(list(map(lambda x: x + (t * window.stride * get_trial_size(x) + 1), l))) for l in self.dependent_idxs))
iffs.append(Iff(self.derived_idx + (t * num_levels) + 1, or_clause))
t += 1
(cnf, new_fresh) = block.cnf_fn(And(iffs), backend_request.fresh)
backend_request.cnfs.append(cnf)
backend_request.fresh = new_fresh
def test_consistency_with_general_window():
design = [color, text, congruent_bookend]
crossing = [color, text]
block = fully_cross_block(design, crossing, [])
backend_request = BackendRequest(0)
Consistency.apply(block, backend_request)
assert backend_request.ll_requests == [
LowLevelRequest("EQ", 1, [1, 2]),
LowLevelRequest("EQ", 1, [3, 4]),
LowLevelRequest("EQ", 1, [5, 6]),
LowLevelRequest("EQ", 1, [7, 8]),
LowLevelRequest("EQ", 1, [9, 10]),
LowLevelRequest("EQ", 1, [11, 12]),
LowLevelRequest("EQ", 1, [13, 14]),
LowLevelRequest("EQ", 1, [15, 16]),
LowLevelRequest("EQ", 1, [17, 18]),
LowLevelRequest("EQ", 1, [19, 20])
]
def test_fully_cross_with_transition_in_crossing():
direction = Factor("direction", ["up", "down"])
block = fully_cross_block([direction, color, color_repeats_factor],
[direction, color_repeats_factor], [])
backend_request = BackendRequest(29)
FullyCross.apply(block, backend_request)
(expected_cnf, _) = to_cnf_tseitin(
And([
Iff(29, And([5, 21])),
Iff(30, And([5, 22])),
Iff(31, And([6, 21])),
Iff(32, And([6, 22])),
Iff(33, And([9, 23])),
Iff(34, And([9, 24])),
Iff(35, And([10, 23])),
Iff(36, And([10, 24])),
Iff(37, And([13, 25])),
Iff(38, And([13, 26])),
Iff(39, And([14, 25])),
Iff(40, And([14, 26])),
Iff(41, And([17, 27])),
Iff(42, And([17, 28])),
Iff(43, And([18, 27])),
Iff(44, And([18, 28])),
]), 45)
assert backend_request.fresh == 78
assert backend_request.cnfs == [expected_cnf]
assert backend_request.ll_requests == [
LowLevelRequest("GT", 0, [29, 33, 37, 41]),
LowLevelRequest("GT", 0, [30, 34, 38, 42]),
LowLevelRequest("GT", 0, [31, 35, 39, 43]),
LowLevelRequest("GT", 0, [32, 36, 40, 44])
]
def test_exclude_with_reduced_crossing():
color = Factor("color", ["red", "blue", "green"])
text = Factor("text", ["red", "blue"])
def illegal_stimulus(color, text):
return color == "green" and text == "blue"
def legal_stimulus(color, text):
return not illegal_stimulus(color, text)
stimulus_configuration = Factor("stimulus configuration", [
DerivedLevel("legal", WithinTrial(legal_stimulus, [color, text])),
DerivedLevel("illegal", WithinTrial(illegal_stimulus, [color, text]))
])
c = Exclude(stimulus_configuration,
get_level_from_name(stimulus_configuration, "illegal"))
block = fully_cross_block([color, text, stimulus_configuration],
[color, text], [c],
require_complete_crossing=False)
backend_request = BackendRequest(0)
c.apply(block, backend_request)
assert backend_request.cnfs == [And([-7, -14, -21, -28, -35])]
def test_derivation_with_three_level_transition():
f = Factor("f", ["a", "b", "c"])
f_transition = Factor("transition", [
DerivedLevel("aa",
Transition(lambda c: c[0] == "a" and c[1] == "a", [f])),
DerivedLevel("ab",
Transition(lambda c: c[0] == "a" and c[1] == "b", [f])),
DerivedLevel("ac",
Transition(lambda c: c[0] == "a" and c[1] == "c", [f])),
DerivedLevel("ba",
Transition(lambda c: c[0] == "b" and c[1] == "a", [f])),
DerivedLevel("bb",
Transition(lambda c: c[0] == "b" and c[1] == "b", [f])),
DerivedLevel("bc",
Transition(lambda c: c[0] == "b" and c[1] == "c", [f])),
DerivedLevel("ca",
Transition(lambda c: c[0] == "c" and c[1] == "a", [f])),
DerivedLevel("cb",
Transition(lambda c: c[0] == "c" and c[1] == "b", [f])),
DerivedLevel("cc",
Transition(lambda c: c[0] == "c" and c[1] == "c", [f])),
])
block = fully_cross_block([f, f_transition], [f], [])
# a-a derivation
d = Derivation(9, [[0, 3]], f_transition)
backend_request = BackendRequest(28)
d.apply(block, backend_request)
(expected_cnf, expected_fresh) = to_cnf_tseitin(
And([Iff(10, Or([And([1, 4])])),
Iff(19, Or([And([4, 7])]))]), 28)
assert backend_request.fresh == expected_fresh
assert backend_request.cnfs == [expected_cnf]