def test_geweke_iid_gaussian():
with bayeslite.bayesdb_open(builtin_metamodels=False) as bdb:
bayeslite.bayesdb_register_metamodel(bdb, gauss.StdNormalMetamodel())
kl_est = geweke.geweke_kl(bdb, "std_normal",
[['column', 'numerical']], ['column'],
[(1,0), (2,0)], 2, 2, 2, 2)
assert kl_est == (2, 0, 0)
def test_geweke_nig_normal():
with bayeslite.bayesdb_open(builtin_metamodels=False) as bdb:
nig = normal.NIGNormalMetamodel(seed=1)
bayeslite.bayesdb_register_metamodel(bdb, nig)
(ct, kl, error) = geweke.geweke_kl(bdb, "nig_normal",
[['column', 'numerical']], ['column'],
[(1,0), (2,0)], 2, 2, 2, 2)
assert ct == 2
assert 0 < kl and kl < 10 # KL should be positive
assert 0 < error and error < 10 # KL error estimate too
def test_geweke_nig_normal():
with bayeslite.bayesdb_open(builtin_metamodels=False) as bdb:
nig = normal.NIGNormalMetamodel(seed=1)
bayeslite.bayesdb_register_metamodel(bdb, nig)
(ct, kl, error) = geweke.geweke_kl(bdb, "nig_normal",
[['column', 'numerical']],
['column'], [(1, 0),
(2, 0)], 2, 2, 2, 2)
assert ct == 2
assert 0 < kl and kl < 10 # KL should be positive
assert 0 < error and error < 10 # KL error estimate too
def test_geweke_catches_nig_normal_bug__ci_slow():
with bayeslite.bayesdb_open(builtin_metamodels=False) as bdb:
bayeslite.bayesdb_register_metamodel(bdb, DoctoredNIGNormal(seed=1))
cells = [(i,0) for i in range(4)]
for chain_ct in (0, 1, 5):
(ct, kl, error) = geweke.geweke_kl(bdb, "nig_normal",
[['column', 'numerical']], ['column'], cells,
200, 200, chain_ct, 3000)
if chain_ct == 0:
assert ct == 3000
assert 0 < kl and kl < 0.1
assert 0 < error and error < 0.05
else:
assert ct == 3000
assert kl > 5
assert 0 < error and error < 4
def test_geweke_catches_nig_normal_bug__ci_slow():
with bayeslite.bayesdb_open(builtin_metamodels=False) as bdb:
bayeslite.bayesdb_register_metamodel(bdb, DoctoredNIGNormal(seed=1))
cells = [(i, 0) for i in range(4)]
for chain_ct in (0, 1, 5):
(ct, kl, error) = geweke.geweke_kl(bdb, "nig_normal",
[['column', 'numerical']],
['column'], cells, 200, 200,
chain_ct, 3000)
if chain_ct == 0:
assert ct == 3000
assert 0 < kl and kl < 0.1
assert 0 < error and error < 0.05
else:
assert ct == 3000
assert kl > 5
assert 0 < error and error < 4
def test_geweke_nig_normal_seriously__ci_slow():
# Note: The actual assertions in this test and the next one were
# dervied heuristically by inspecting a fuller (and costlier to
# compute) tableau of values of geweke.geweke_kl and deciding the
# aggregate impression was "probably no bug" (resp. "definitely
# bug"). The assertions constitute an attempt to capture the most
# salient features that give that impression.
with bayeslite.bayesdb_open(builtin_metamodels=False) as bdb:
nig = normal.NIGNormalMetamodel(seed=1)
bayeslite.bayesdb_register_metamodel(bdb, nig)
cells = [(i,0) for i in range(4)]
for chain_ct in (0, 1, 5):
(ct, kl, error) = geweke.geweke_kl(bdb, "nig_normal",
[['column', 'numerical']], ['column'], cells,
200, 200, chain_ct, 3000)
assert ct == 3000
assert 0 < kl and kl < 0.1
assert 0 < error and error < 0.05
def test_geweke_nig_normal_seriously__ci_slow():
# Note: The actual assertions in this test and the next one were
# dervied heuristically by inspecting a fuller (and costlier to
# compute) tableau of values of geweke.geweke_kl and deciding the
# aggregate impression was "probably no bug" (resp. "definitely
# bug"). The assertions constitute an attempt to capture the most
# salient features that give that impression.
with bayeslite.bayesdb_open(builtin_metamodels=False) as bdb:
nig = normal.NIGNormalMetamodel(seed=1)
bayeslite.bayesdb_register_metamodel(bdb, nig)
cells = [(i, 0) for i in range(4)]
for chain_ct in (0, 1, 5):
(ct, kl, error) = geweke.geweke_kl(bdb, "nig_normal",
[['column', 'numerical']],
['column'], cells, 200, 200,
chain_ct, 3000)
assert ct == 3000
assert 0 < kl and kl < 0.1
assert 0 < error and error < 0.05
def test_geweke_troll():
with bayeslite.bayesdb_open(builtin_metamodels=False) as bdb:
bayeslite.bayesdb_register_metamodel(bdb, troll.TrollMetamodel())
kl_est = geweke.geweke_kl(bdb, "troll_rng", [['column', 'numerical']],
['column'], [(1,0)], 2, 2, 2, 2)
assert kl_est == (2, 0, 0)
def test_geweke_iid_gaussian():
with bayeslite.bayesdb_open(builtin_metamodels=False) as bdb:
bayeslite.bayesdb_register_metamodel(bdb, gauss.StdNormalMetamodel())
kl_est = geweke.geweke_kl(bdb, "std_normal", [['column', 'numerical']],
['column'], [(1, 0), (2, 0)], 2, 2, 2, 2)
assert kl_est == (2, 0, 0)
def test_geweke_troll():
with bayeslite.bayesdb_open(builtin_metamodels=False) as bdb:
bayeslite.bayesdb_register_metamodel(bdb, troll.TrollMetamodel())
kl_est = geweke.geweke_kl(bdb, "troll_rng", [['column', 'numerical']],
['column'], [(1, 0)], 2, 2, 2, 2)
assert kl_est == (2, 0, 0)
