def test_droppop_with_metamodels():
with test_core.t1() as (bdb, _population_id, _generator_id):
distinctive_name = 'frobbledithorpequack'
bdb.execute('create metamodel %s for p1 using crosscat' %
(distinctive_name, ))
with pytest.raises(bayeslite.BQLError):
try:
bdb.execute('drop population p1')
except bayeslite.BQLError as e:
assert 'metamodels' in str(e)
assert distinctive_name in str(e)
raise
def test_mutinf_smoke(seed):
with test_core.t1(seed=seed) as (bdb, population_id, _generator_id):
def checkmi(n, q, *p):
i = 0
for r in bdb.sql_execute(q, *p):
assert len(r) == 1
assert isinstance(r[0], float)
i += 1
assert i == n, '%r =/= %r' % (i, n)
bdb.execute('initialize 10 models for p1_cc')
checkmi(
10, '''
select mi from bql_mutinf
where population_id = ?
and target_vars = '[1]'
and reference_vars = '[2]'
''', (population_id, ))
bdb.execute('initialize 11 models if not exists for p1_cc')
checkmi(
11, '''
select mi from bql_mutinf
where population_id = ?
and target_vars = '[1]'
and reference_vars = '[2]'
and conditions = '{"3": 42}'
''', (population_id, ))
bdb.execute('initialize 12 models if not exists for p1_cc')
checkmi(
12, '''
select mi from bql_mutinf
where population_id = ?
and target_vars = '[1]'
and reference_vars = '[2]'
and nsamples = 2
''', (population_id, ))
bdb.execute('initialize 13 models if not exists for p1_cc')
checkmi(
13, '''
select mi from bql_mutinf
where population_id = ?
and target_vars = '[1]'
and reference_vars = '[2]'
and conditions = '{"3": 42}'
and nsamples = 2
''', (population_id, ))
def test_sessions_error_metamodel():
with test_core.t1() as (bdb, _generator_id):
bayeslite.bayesdb_register_metamodel(bdb, ErroneousMetamodel())
bdb.execute('''
CREATE GENERATOR t1_err FOR t1
USING erroneous(age NUMERICAL)
''')
tr = sescap.SessionOrchestrator(bdb)
cursor = bdb.execute('''
ESTIMATE PREDICTIVE PROBABILITY OF age FROM t1_err
''')
with pytest.raises(Boom):
cursor.fetchall()
#tr._start_new_session()
assert tr._check_error_entries(tr.session_id) > 0
def test_sessions_no_errors():
with test_core.analyzed_bayesdb_population(test_core.t1(),
10, None, max_seconds=1) as (bdb, population_id, generator_id):
tr = sescap.SessionOrchestrator(bdb)
# simple query
cursor = bdb.execute('''
SELECT age, weight FROM t1
WHERE label = 'frotz'
ORDER BY weight
''')
cursor.fetchall()
# add a metamodel and do a query
cursor = bdb.execute('''
ESTIMATE PREDICTIVE PROBABILITY OF age FROM p1
''')
cursor.fetchall()
# there should be no error entries in the previous session
#tr._start_new_session()
assert tr._check_error_entries(tr.session_id) == 0
