def test_run_many_merge_moves_trueModel_random(self):
LP, SS = self.getSuffStatsPrepForMerge(self.hmodel)
PRNG = np.random.RandomState(0)
mergeKwArgs = dict(mergename='random')
a, b, c, MTracker = MergeMove.run_many_merge_moves(self.hmodel,
self.Data, SS,
nMergeTrials=100, randstate=PRNG,
**mergeKwArgs)
assert MTracker.nTrial == SS.K * (SS.K-1)/2
assert MTracker.nSuccess == 0
def test_run_many_merge_moves_removes_duplicates(self):
''' Verify run_many_merge_moves method on duplicated model
produces a new model with K=Ktrue components (duplicates gone)
'''
PRNG = np.random.RandomState(12345)
newModel, newSS, ev, MTracker = MergeMove.run_many_merge_moves(
self.dupModel, self.Data, self.dupSS, nMergeTrials=6,
randstate=PRNG)
assert newSS.K == self.SS.K
assert newModel.allocModel.K == self.SS.K
assert newModel.obsModel.K == self.SS.K
def test_run_many_merge_moves_trueModel_random(self):
LP, SS = self.getSuffStatsPrepForMerge(self.hmodel)
PRNG = np.random.RandomState(0)
mergeKwArgs = dict(mergename='random')
a, b, c, MTracker = MergeMove.run_many_merge_moves(self.hmodel,
self.Data,
SS,
nMergeTrials=100,
randstate=PRNG,
**mergeKwArgs)
assert MTracker.nTrial == SS.K * (SS.K - 1) / 2
assert MTracker.nSuccess == 0
def test_run_many_merge_moves_changes_nothing_on_true_model(self):
''' Verify run_many_merge_moves method on true model
produces a new model with K=Ktrue components (no merges accepted)
'''
PRNG = np.random.RandomState(12345)
newModel, newSS, ev, MTracker = MergeMove.run_many_merge_moves(
self.hmodel, self.Data, self.SS, nMergeTrials=100, randstate=PRNG)
assert newSS.K == self.SS.K
assert newModel.allocModel.K == self.SS.K
assert newModel.obsModel.K == self.SS.K
assert MTracker.nSuccess == 0
K = self.SS.K
assert MTracker.nTrial == K * (K - 1) / 2
def test_run_many_merge_moves_dupModel_random(self):
self.MakeModelWithDuplicatedComps()
LP, SS = self.getSuffStatsPrepForMerge(self.dupModel)
PRNG = np.random.RandomState(0)
mergeKwArgs = dict(mergename='random')
a, b, c, MTracker = MergeMove.run_many_merge_moves(self.dupModel,
self.Data, SS,
nMergeTrials=100, randstate=PRNG,
**mergeKwArgs)
assert MTracker.nSuccess == 4
assert (0,4) in MTracker.acceptedOrigIDs
assert (1,5) in MTracker.acceptedOrigIDs
assert (2,6) in MTracker.acceptedOrigIDs
assert (3,7) in MTracker.acceptedOrigIDs
def test_run_many_merge_moves_removes_duplicates(self):
''' Verify run_many_merge_moves method on duplicated model
produces a new model with K=Ktrue components (duplicates gone)
'''
PRNG = np.random.RandomState(12345)
newModel, newSS, ev, MTracker = MergeMove.run_many_merge_moves(
self.dupModel,
self.Data,
self.dupSS,
nMergeTrials=6,
randstate=PRNG)
assert newSS.K == self.SS.K
assert newModel.allocModel.K == self.SS.K
assert newModel.obsModel.K == self.SS.K
def test_run_many_merge_moves_changes_nothing_on_true_model(self):
''' Verify run_many_merge_moves method on true model
produces a new model with K=Ktrue components (no merges accepted)
'''
PRNG = np.random.RandomState(12345)
newModel, newSS, ev, MTracker = MergeMove.run_many_merge_moves(
self.hmodel, self.Data, self.SS, nMergeTrials=100,
randstate=PRNG)
assert newSS.K == self.SS.K
assert newModel.allocModel.K == self.SS.K
assert newModel.obsModel.K == self.SS.K
assert MTracker.nSuccess == 0
K = self.SS.K
assert MTracker.nTrial == K * (K-1)/2
def test_run_many_merge_moves_dupModel_random(self):
self.MakeModelWithDuplicatedComps()
LP, SS = self.getSuffStatsPrepForMerge(self.dupModel)
PRNG = np.random.RandomState(0)
mergeKwArgs = dict(mergename='random')
a, b, c, MTracker = MergeMove.run_many_merge_moves(self.dupModel,
self.Data,
SS,
nMergeTrials=100,
randstate=PRNG,
**mergeKwArgs)
assert MTracker.nSuccess == 4
assert (0, 4) in MTracker.acceptedOrigIDs
assert (1, 5) in MTracker.acceptedOrigIDs
assert (2, 6) in MTracker.acceptedOrigIDs
assert (3, 7) in MTracker.acceptedOrigIDs
