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_tseitin_rep_iff():
from sweetpea.logic import __tseitin_rep, _Cache
clauses = []
cache = _Cache(3)
# Make sure return is correct and value was cached.
assert __tseitin_rep(Iff(1, 2), clauses, cache) == 3
assert cache.get(str(Iff(1, 2))) == 3
# Make sure equivalence clauses were added.
assert Or([ 1, 2, 3 ]) in clauses
assert Or([Not(1), Not(2), 3 ]) in clauses
assert Or([ 1, Not(2), Not(3)]) in clauses
assert Or([Not(1), 2, Not(3)]) in clauses
# Don't duplicate clauses when the cache was already populated.
clauses = []
cache = _Cache(3)
# Prewarm the cache.
assert cache.get(str(Iff(1, 2))) == 3
assert __tseitin_rep(Iff(1, 2), clauses, cache) == 3
# Make sure no clauses were added.
assert clauses == []
def test_to_cnf_switching():
formula = Or([
And([3, 4]),
And([Not(2), Or([1, 5])])
])
expected_cnf = And([
Or([3, Not(6)]),
Or([4, Not(6)]),
Or([1, 5, 6]),
Or([Not(2), 6])
])
assert to_cnf_switching(formula, 6) == (expected_cnf, 7)
formula = And([
Iff(1, And([2, 3])),
Iff(4, And([5, 6]))
])
expected_cnf = And([
Or([1, Not(2), Not(3)]),
Or([Not(1), 2]),
Or([Not(1), 3]),
Or([4, Not(5), Not(6)]),
Or([Not(4), 5]),
Or([Not(4), 6])
])
assert to_cnf_switching(formula, 7) == (expected_cnf, 7)
def test_eliminate_iff():
from sweetpea.logic import __eliminate_iff
# P <-> Q ==> (P v ~Q) ^ (~P v Q)
assert __eliminate_iff(Iff(1, 2)) == And([Or([1, Not(2)]), Or([Not(1), 2])])
assert __eliminate_iff(Iff(1, And([2, 3]))) == And([
Or([1, Not(And([2, 3]))]),
Or([Not(1), And([2, 3])])
])
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_to_cnf_naive():
assert to_cnf_naive(1, 2) == (And([1]), 2)
assert to_cnf_naive(And([1]), 2) == (And([1]), 2)
assert to_cnf_naive(And([1, 2]), 3) == (And([1, 2]), 3)
assert to_cnf_naive(Or([1, 2]), 3) == (And([Or([1, 2])]), 3)
assert to_cnf_naive(Or([1, And([2, 3])]),
4) == (And([Or([1, 2]), Or([1, 3])]), 4)
formula = And([Iff(1, And([2, 3])), Iff(4, And([5, 6]))])
expected_cnf = And([
Or([1, Not(2), Not(3)]),
Or([Not(1), 2]),
Or([Not(1), 3]),
Or([4, Not(5), Not(6)]),
Or([Not(4), 5]),
Or([Not(4), 6])
])
assert to_cnf_switching(formula, 7) == (expected_cnf, 7)
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 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_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 __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 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]
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_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_three_factors():
(expected_cnf, _) = to_cnf_tseitin(
And([
Iff(65, And([3, 5, 7])),
Iff(66, And([3, 5, 8])),
Iff(67, And([3, 6, 7])),
Iff(68, And([3, 6, 8])),
Iff(69, And([4, 5, 7])),
Iff(70, And([4, 5, 8])),
Iff(71, And([4, 6, 7])),
Iff(72, And([4, 6, 8])),
Iff(73, And([11, 13, 15])),
Iff(74, And([11, 13, 16])),
Iff(75, And([11, 14, 15])),
Iff(76, And([11, 14, 16])),
Iff(77, And([12, 13, 15])),
Iff(78, And([12, 13, 16])),
Iff(79, And([12, 14, 15])),
Iff(80, And([12, 14, 16])),
Iff(81, And([19, 21, 23])),
Iff(82, And([19, 21, 24])),
Iff(83, And([19, 22, 23])),
Iff(84, And([19, 22, 24])),
Iff(85, And([20, 21, 23])),
Iff(86, And([20, 21, 24])),
Iff(87, And([20, 22, 23])),
Iff(88, And([20, 22, 24])),
Iff(89, And([27, 29, 31])),
Iff(90, And([27, 29, 32])),
Iff(91, And([27, 30, 31])),
Iff(92, And([27, 30, 32])),
Iff(93, And([28, 29, 31])),
Iff(94, And([28, 29, 32])),
Iff(95, And([28, 30, 31])),
Iff(96, And([28, 30, 32])),
Iff(97, And([35, 37, 39])),
Iff(98, And([35, 37, 40])),
Iff(99, And([35, 38, 39])),
Iff(100, And([35, 38, 40])),
Iff(101, And([36, 37, 39])),
Iff(102, And([36, 37, 40])),
Iff(103, And([36, 38, 39])),
Iff(104, And([36, 38, 40])),
Iff(105, And([43, 45, 47])),
Iff(106, And([43, 45, 48])),
Iff(107, And([43, 46, 47])),
Iff(108, And([43, 46, 48])),
Iff(109, And([44, 45, 47])),
Iff(110, And([44, 45, 48])),
Iff(111, And([44, 46, 47])),
Iff(112, And([44, 46, 48])),
Iff(113, And([51, 53, 55])),
Iff(114, And([51, 53, 56])),
Iff(115, And([51, 54, 55])),
Iff(116, And([51, 54, 56])),
Iff(117, And([52, 53, 55])),
Iff(118, And([52, 53, 56])),
Iff(119, And([52, 54, 55])),
Iff(120, And([52, 54, 56])),
Iff(121, And([59, 61, 63])),
Iff(122, And([59, 61, 64])),
Iff(123, And([59, 62, 63])),
Iff(124, And([59, 62, 64])),
Iff(125, And([60, 61, 63])),
Iff(126, And([60, 61, 64])),
Iff(127, And([60, 62, 63])),
Iff(128, And([60, 62, 64])),
]), 129)
backend_request = BackendRequest(65)
FullyCross.apply(block, backend_request)
assert backend_request.fresh == 258
assert backend_request.cnfs == [expected_cnf]
assert backend_request.ll_requests == [
LowLevelRequest("GT", 0, [65, 73, 81, 89, 97, 105, 113, 121]),
LowLevelRequest("GT", 0, [66, 74, 82, 90, 98, 106, 114, 122]),
LowLevelRequest("GT", 0, [67, 75, 83, 91, 99, 107, 115, 123]),
LowLevelRequest("GT", 0, [68, 76, 84, 92, 100, 108, 116, 124]),
LowLevelRequest("GT", 0, [69, 77, 85, 93, 101, 109, 117, 125]),
LowLevelRequest("GT", 0, [70, 78, 86, 94, 102, 110, 118, 126]),
LowLevelRequest("GT", 0, [71, 79, 87, 95, 103, 111, 119, 127]),
LowLevelRequest("GT", 0, [72, 80, 88, 96, 104, 112, 120, 128])
]
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_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_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])
]
