def test_BPlanner_makePlanAtBatch_someDisqualifiedForPrevFailures(K=10):
SS = SuffStatBag(K=K)
SS.setField('N', np.arange(K), dims='K')
SSbatch = SS.copy()
# Do the same test, while eliminating some uids
MoveRecordsByUID = defaultdict(lambda: defaultdict(int))
for uid in [0, 6, 9]:
MoveRecordsByUID[uid]['b_nFail'] = 1
MoveRecordsByUID[uid]['b_nFailRecent'] = 1
MoveRecordsByUID[uid]['b_batchIDsWhoseProposalFailed'] = set([0])
for b_minNumAtomsForTargetComp in [2, 5, K]:
BArgs['b_minNumAtomsForTargetComp'] = b_minNumAtomsForTargetComp
MovePlans = selectCompsForBirthAtCurrentBatch(
SS=SS,
SSbatch=SSbatch,
MovePlans=dict(),
MoveRecordsByUID=MoveRecordsByUID,
**BArgs)
nChosen = len(MovePlans['b_targetUIDs'])
nFailPerUID = list()
for uid in SS.uids:
bIDs = MoveRecordsByUID[uid]['b_batchIDsWhoseProposalFailed']
if isinstance(bIDs, set):
nFailPerUID.append(len(bIDs))
else:
nFailPerUID.append(0)
nFailPerUID = np.asarray(nFailPerUID)
nExpected = np.sum(
np.logical_and(SS.N >= b_minNumAtomsForTargetComp,
nFailPerUID < 1))
assert nChosen == nExpected
def test_BPlanner_makePlanAtBatch_noPrevFailures(K=10):
SS = SuffStatBag(K=K)
SS.setField('N', np.arange(K), dims='K')
SSbatch = SS.copy()
for b_minNumAtomsForTargetComp in [2, 5, K]:
BArgs['b_minNumAtomsForTargetComp'] = b_minNumAtomsForTargetComp
MovePlans = selectCompsForBirthAtCurrentBatch(
SS=SS, SSbatch=SSbatch, MovePlans=dict(), **BArgs)
nChosen = len(MovePlans['b_targetUIDs'])
assert nChosen == np.sum(SS.N >= b_minNumAtomsForTargetComp)
def test_BPlanner_makePlanAtBatch_someDQForPrevFailuresWithOtherBatches(K=20):
print('')
SS = SuffStatBag(K=K)
SS.setField('N', np.arange(K), dims='K')
SSbatch = SS.copy()
# Select some subset of uids to be disqualified
PRNG = np.random.RandomState(11)
dqUIDs = PRNG.choice(K, size=3, replace=False)
otherfailUIDs = PRNG.choice(K, size=3, replace=False)
# Do the same test, while eliminating some uids
MoveRecordsByUID = defaultdict(lambda: defaultdict(int))
for uid in dqUIDs:
MoveRecordsByUID[uid]['b_nFail'] = 1
MoveRecordsByUID[uid]['b_nFailRecent'] = 1
MoveRecordsByUID[uid]['b_batchIDsWhoseProposalFailed'] = set([0])
print('PREV FAIL AT THIS BATCH: uid ', uid)
for uid in otherfailUIDs:
if uid in dqUIDs:
continue
MoveRecordsByUID[uid]['b_nFail'] = 1
MoveRecordsByUID[uid]['b_nFailRecent'] = 1
MoveRecordsByUID[uid]['b_batchIDsWhoseProposalFailed'] = set([1])
print('PREV FAIL AT ANOTHER BATCH: uid ', uid)
for b_minNumAtomsForTargetComp in [2, 5, 10, K]:
BArgs['b_minNumAtomsForTargetComp'] = b_minNumAtomsForTargetComp
MovePlans = selectCompsForBirthAtCurrentBatch(
SS=SS,
SSbatch=SSbatch,
MovePlans=dict(),
MoveRecordsByUID=MoveRecordsByUID,
**BArgs)
nChosen = len(MovePlans['b_targetUIDs'])
nFailPerUID = list()
for uid in SS.uids:
bIDs = MoveRecordsByUID[uid]['b_batchIDsWhoseProposalFailed']
if isinstance(bIDs, set) and 0 in bIDs:
nFailPerUID.append(len(bIDs))
else:
nFailPerUID.append(0)
nFailPerUID = np.asarray(nFailPerUID)
nExpected = np.sum(
np.logical_and(SS.N >= b_minNumAtomsForTargetComp,
nFailPerUID < 1))
assert nChosen == nExpected
