def test_register():
bdb = bayeslite.bayesdb_open()
composer = Composer(n_samples=5)
bayeslite.bayesdb_register_metamodel(bdb, composer)
# Check if globally registered.
try:
bdb.sql_execute('''
SELECT * FROM bayesdb_metamodel WHERE name={}
'''.format(quote(composer.name()))).next()
except StopIteration:
pytest.fail('Composer not registered in bayesdb_metamodel.')
# Check all tables/triggers.
schema = [
('table', 'bayesdb_composer_cc_id'),
('table', 'bayesdb_composer_column_owner'),
('table', 'bayesdb_composer_column_toposort'),
('trigger', 'bayesdb_composer_column_toposort_check'),
('table', 'bayesdb_composer_column_parents'),
('table', 'bayesdb_composer_column_foreign_predictor'),
('trigger', 'bayesdb_composer_column_foreign_predictor_check')
]
for kind, name in schema:
try:
bdb.sql_execute('''
SELECT * FROM sqlite_master WHERE type={} AND name={}
'''.format(quote(kind), quote(name))).next()
except StopIteration:
pytest.fail('Missing from Composer schema: {}'.format((kind,name)))
bdb.close()
def test_register():
bdb = bayeslite.bayesdb_open()
composer = Composer(n_samples=5)
bayeslite.bayesdb_register_metamodel(bdb, composer)
# Check if globally registered.
try:
bdb.sql_execute('''
SELECT * FROM bayesdb_metamodel WHERE name={}
'''.format(quote(composer.name()))).next()
except StopIteration:
pytest.fail('Composer not registered in bayesdb_metamodel.')
# Check all tables/triggers.
schema = [('table', 'bayesdb_composer_cc_id'),
('table', 'bayesdb_composer_column_owner'),
('table', 'bayesdb_composer_column_toposort'),
('trigger', 'bayesdb_composer_column_toposort_check'),
('table', 'bayesdb_composer_column_parents'),
('table', 'bayesdb_composer_column_foreign_predictor'),
('trigger', 'bayesdb_composer_column_foreign_predictor_check')]
for kind, name in schema:
try:
bdb.sql_execute('''
SELECT * FROM sqlite_master WHERE type={} AND name={}
'''.format(quote(kind), quote(name))).next()
except StopIteration:
pytest.fail('Missing from Composer schema: {}'.format(
(kind, name)))
bdb.close()
def test_topological_sort():
# Acyclic graph should return a correct topo sort.
graph = {1:[], 2:[1], 3:[2,6], 4:[2], 5:[4], 6:[4,1]}
topo = Composer.topological_sort(graph)
for i in xrange(len(topo)):
node, parents = topo[i]
for n in topo[i+1:]:
assert n not in parents
# Cyclic graph should throw an error.
graph = {1:[], 2:[1], 3:[2,4,6], 4:[2], 5:[3,4], 6:[4,5,1]}
with pytest.raises(BLE):
topo = Composer.topological_sort(graph)
def test_topological_sort():
# Acyclic graph should return a correct topo sort.
graph = {1: [], 2: [1], 3: [2, 6], 4: [2], 5: [4], 6: [4, 1]}
topo = Composer.topological_sort(graph)
for i in xrange(len(topo)):
node, parents = topo[i]
for n in topo[i + 1:]:
assert n not in parents
# Cyclic graph should throw an error.
graph = {1: [], 2: [1], 3: [2, 4, 6], 4: [2], 5: [3, 4], 6: [4, 5, 1]}
with pytest.raises(BLE):
topo = Composer.topological_sort(graph)
from bdbcontrib.predictors import random_forest
from bdbcontrib.predictors import keplers_law
# Get output directory.
if len(sys.argv) < 2:
outdir = '.'
else:
outdir = sys.argv[1]
# Find the satellites file.
PATH_KEPLER = os.path.dirname(os.path.abspath(__file__))
PATH_EXAMPLES = os.path.dirname(PATH_KEPLER)
PATH_SATELLITES = os.path.join(PATH_EXAMPLES, 'satellites')
PATH_SATELLITES_CSV = os.path.join(PATH_SATELLITES, 'satellites.csv')
composer = Composer()
composer.register_foreign_predictor(keplers_law.KeplersLaw)
composer.register_foreign_predictor(random_forest.RandomForest)
if os.path.exists(os.path.join(outdir, 'kepler.bdb')):
os.remove(os.path.join(outdir, 'kepler.bdb'))
bdb = bayeslite.bayesdb_open(os.path.join(outdir, 'kepler.bdb'))
bayeslite.bayesdb_register_metamodel(bdb, composer)
bayeslite.bayesdb_read_csv_file(bdb, 'satellites', PATH_SATELLITES_CSV,
header=True, create=True)
bdbcontrib.query(bdb, '''
CREATE GENERATOR sat_kepler FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
def test_create_generator_schema():
bdb = bayeslite.bayesdb_open()
bayeslite.bayesdb_read_csv_file(bdb, 'satellites', PATH_SATELLITES_CSV,
header=True, create=True)
composer = Composer(n_samples=5)
bayeslite.bayesdb_register_metamodel(bdb, composer)
# Using crosscat and default to specify models should work.
bdb.execute('''
CREATE GENERATOR t1 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
crosscat (
Anticipated_Lifetime NUMERICAL, Contractor CATEGORICAL
)
);''')
assert bayeslite.core.bayesdb_has_generator(bdb, 't1_cc')
# IGNORE and GUESS(*) are forbidden and should crash.
with pytest.raises(AttributeError):
bdb.execute('''
CREATE GENERATOR t2 FOR satellites USING composer(
default (
GUESS(*), Country_of_Operator IGNORE,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
)
);''')
# Test unregistered foreign predictor.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t3 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Apogee_km NUMERICAL GIVEN Operator_Owner
)
);''')
# Unregistered foreign predictor should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t4 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Apogee_km NUMERICAL GIVEN Operator_Owner
)
);''')
# Registered foreign predictor should work.
composer.register_foreign_predictor(random_forest.RandomForest)
bdb.execute('''
CREATE GENERATOR t5 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Eccentricity NUMERICAL
),
random_forest (
Apogee_km NUMERICAL GIVEN Operator_Owner
)
);''')
# Wrong stattype in predictor should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t6 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Apogee_km RADIAL GIVEN Operator_Owner
)
);''')
# Missing GIVEN keyword should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t6 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Apogee_km NUMERICAL, Operator_Owner
)
);''')
# Missing conditions in random forest conditions should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t7 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Apogee_km NUMERICAL GIVEN Operator_Owner
)
);''')
# Test duplicate declarations.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t7 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Class_of_orbit CATEGORICAL GIVEN Operator_Owner
)
);''')
# Arbitrary DAG with foreign predictors.
composer.register_foreign_predictor(multiple_regression.MultipleRegression)
bdb.execute('''
CREATE GENERATOR t8 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
),
random_forest (
Apogee_km NUMERICAL GIVEN Operator_Owner, Users
),
multiple_regression (
Eccentricity NUMERICAL GIVEN Apogee_km, Users, Perigee_km
)
);''')
# Duplicate declarations in foreign predictors should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t9 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Perigee_km NUMERICAL GIVEN Purpose
),
multiple_regression (
Perigee_km NUMERICAL GIVEN Operator_Owner
)
);''')
# MML for default models should work.
bdb.execute('''
CREATE GENERATOR t10 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Apogee_km NUMERICAL
)
random_forest (
Perigee_km NUMERICAL GIVEN Purpose
)
multiple_regression (
Eccentricity NUMERICAL GIVEN Operator_Owner, Class_of_orbit
)
DEPENDENT(Apogee_km, Perigee_km, Purpose),
INDEPENDENT(Country_of_Operator, Purpose)
);''')
# MML for foreign predictors should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t11 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL,
Apogee_km NUMERICAL
),
random_forest (
Perigee_km NUMERICAL GIVEN Purpose
),
multiple_regression (
Eccentricity NUMERICAL GIVEN Operator_Owner, Class_of_orbit
)
DEPENDENT(Apogee_km, Eccentricity, Country_of_Operator),
INDEPENDENT(Perigee_km, Purpose)
);''')
# Test full generator.
composer.register_foreign_predictor(keplers_law.KeplersLaw)
bdb.execute('''
CREATE GENERATOR t12 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL,
Launch_Mass_kg NUMERICAL, Dry_Mass_kg NUMERICAL,
Power_watts NUMERICAL, Date_of_Launch NUMERICAL,
Contractor CATEGORICAL,
Country_of_Contractor CATEGORICAL, Launch_Site CATEGORICAL,
Launch_Vehicle CATEGORICAL,
Source_Used_for_Orbital_Data CATEGORICAL,
longitude_radians_of_geo NUMERICAL,
Inclination_radians NUMERICAL,
),
random_forest (
Type_of_Orbit CATEGORICAL
GIVEN Apogee_km, Perigee_km,
Eccentricity, Period_minutes, Launch_Mass_kg,
Power_watts, Anticipated_Lifetime, Class_of_orbit
),
keplers_law (
Period_minutes NUMERICAL
GIVEN Perigee_km, Apogee_km
),
multiple_regression (
Anticipated_Lifetime NUMERICAL
GIVEN Dry_Mass_kg, Power_watts, Launch_Mass_kg, Contractor
),
DEPENDENT(Apogee_km, Perigee_km, Eccentricity),
INDEPENDENT(Country_of_Operator, longitude_radians_of_geo)
);''')
bdb.close()
def test_composer_integration__ci_slow():
# But currently difficult to seperate these tests into smaller tests because
# of their sequential nature. We will still test all internal functions
# with different regimes of operation.
# SETUP
# -----
# Dataset.
bdb = bayeslite.bayesdb_open()
bayeslite.bayesdb_read_csv_file(bdb, 'satellites', PATH_SATELLITES_CSV,
header=True, create=True)
bdbcontrib.nullify(bdb, 'satellites', 'NaN')
# Composer.
composer = Composer(n_samples=5)
composer.register_foreign_predictor(
multiple_regression.MultipleRegression)
composer.register_foreign_predictor(keplers_law.KeplersLaw)
composer.register_foreign_predictor(random_forest.RandomForest)
# Use complex generator for interesting test cases.
bayeslite.bayesdb_register_metamodel(bdb, composer)
bdb.execute('''
CREATE GENERATOR t1 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL,
Launch_Mass_kg NUMERICAL, Dry_Mass_kg NUMERICAL,
Power_watts NUMERICAL, Date_of_Launch NUMERICAL,
Contractor CATEGORICAL,
Country_of_Contractor CATEGORICAL, Launch_Site CATEGORICAL,
Launch_Vehicle CATEGORICAL,
Source_Used_for_Orbital_Data CATEGORICAL,
longitude_radians_of_geo NUMERICAL,
Inclination_radians NUMERICAL,
),
random_forest (
Type_of_Orbit CATEGORICAL
GIVEN Apogee_km, Perigee_km,
Eccentricity, Period_minutes, Launch_Mass_kg,
Power_watts, Anticipated_Lifetime, Class_of_orbit
),
keplers_law (
Period_minutes NUMERICAL
GIVEN Perigee_km, Apogee_km
),
multiple_regression (
Anticipated_Lifetime NUMERICAL
GIVEN Dry_Mass_kg, Power_watts, Launch_Mass_kg,
Contractor
),
DEPENDENT(Apogee_km, Perigee_km, Eccentricity),
DEPENDENT(Contractor, Country_of_Contractor),
INDEPENDENT(Country_of_Operator, Date_of_Launch)
);''')
# ----------------------
# TEST INITIALIZE MODELS
# ----------------------
bdb.execute('INITIALIZE 2 MODELS FOR t1')
# Check number of models.
df = bdbcontrib.describe_generator_models(bdb, 't1')
assert len(df) == 2
df = bdbcontrib.describe_generator_models(bdb, 't1_cc')
assert len(df) == 2
# -------------------
# TEST ANALYZE MODELS
# -------------------
bdb.execute('ANALYZE t1 FOR 2 ITERATIONS WAIT;')
# Check number of iterations of composer.
df = bdbcontrib.describe_generator_models(bdb, 't1')
for index, modelno, iterations in df.itertuples():
assert iterations == 2
# Check number of iterations of composer_cc.
df = bdbcontrib.describe_generator_models(bdb, 't1_cc')
for index, modelno, iterations in df.itertuples():
assert iterations == 2
# ----------------------------------
# TEST COLUMN DEPENDENCE PROBABILITY
# ----------------------------------
# Special 0/1 regimes.
# Local with a INDEPENDENT local should be 0.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Date_of_Launch
WITH Country_of_Operator FROM t1 LIMIT 1
''')
assert curs.next()[0] == 0
# Local with a DEPENDENT local should be 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Perigee_km WITH Eccentricity
FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Apogee_km WITH Eccentricity
FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1
# Foreign with a local parent should be 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Period_minutes WITH Apogee_km
FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Anticipated_Lifetime WITH Power_watts
FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Foreign with a foreign parent should be 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Type_of_Orbit WITH
Anticipated_Lifetime FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Foreign with a local non-parent DEPENDENT with local parent should be 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Period_minutes WITH
Eccentricity FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Foreign with foreign sharing common direct ancestor should be 1.
# Launch_Mass_kg is the common parent.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Anticipated_Lifetime WITH
Type_of_Orbit FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Foreign with a foreign sharing a common DEPENDENT ancestor should be 1.
# Eccentricity is a parent of Type_of_orbit, and is dependent
# with Period_minutes through DEPENDENT(Apogee_km, Perigee_km, Eccentricity)
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Period_minutes WITH
Type_of_Orbit FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Column with itself should be 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Anticipated_Lifetime WITH
Anticipated_Lifetime FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Unknown [0,1] regimes.
# Foreign with a local of unknown relation with parents.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Anticipated_Lifetime WITH
longitude_radians_of_geo FROM t1 LIMIT 1
''')
assert 0 <= curs.next()[0] <= 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Period_minutes WITH
longitude_radians_of_geo FROM t1 LIMIT 1
''')
assert 0 <= curs.next()[0] <= 1.
# Foreign with a foreign of unknown ancestry relation.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Anticipated_Lifetime WITH
Period_minutes FROM t1 LIMIT 1
''')
assert 0 <= curs.next()[0] <= 1.
# ----------------------------------
# TEST SIMULATE
# ----------------------------------
# Crash tests for various code paths. Quality of simulations ignored.
# Joint local.
curs = bdb.execute('''
SIMULATE Power_watts, Launch_Mass_kg FROM t1 LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Forward simulate foreign.
curs = bdb.execute('''
SIMULATE Period_minutes FROM t1 GIVEN Apogee_km = 1000, Perigee_km = 980
LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Forward simulate foreign with missing parents.
curs = bdb.execute('''
SIMULATE Anticipated_Lifetime FROM t1 GIVEN Dry_Mass_kg = 2894,
Launch_Mass_kg = 1730 LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Joint simulate foreign with parents, and missing parents.
curs = bdb.execute('''
SIMULATE Type_of_Orbit, Eccentricity FROM t1 GIVEN Dry_Mass_kg = 2894,
Launch_Mass_kg = 1730 LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Joint simulate foreign with non-parents.
curs = bdb.execute('''
SIMULATE Period_minutes, Eccentricity FROM t1 GIVEN Apogee_km = 38000
LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Simulate joint local conditioned on two foreigns.
curs = bdb.execute('''
SIMULATE Country_of_Operator, Inclination_radians FROM t1
GIVEN Period_minutes = 1432, Anticipated_Lifetime = 5 LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Simulate joint foreign conditioned on third foreign.
curs = bdb.execute('''
SIMULATE Period_minutes, Anticipated_Lifetime FROM t1
GIVEN Type_of_Orbit = 'Deep Highly Eccentric' LIMIT 2
''')
assert len(curs.fetchall()) == 2
# Simulate foreign conditioned on itself.
curs = bdb.execute('''
SIMULATE Period_minutes, Apogee_km FROM t1
GIVEN Period_minutes = 102 LIMIT 2
''')
assert [s[0] for s in curs] == [102] * 2
# -----------------------------
# TEST COLUMN VALUE PROBABILITY
# -----------------------------
# Crash tests for various code path. Quality of logpdf ignored.
# Conditional local.
curs = bdb.execute('''
ESTIMATE PROBABILITY OF Power_watts = 800 GIVEN (Perigee_km = 980,
Launch_Mass_kg = 890) FROM t1 LIMIT 1;
''')
assert 0. <= curs.next()[0]
# Unconditional foreign
curs = bdb.execute('''
ESTIMATE PROBABILITY OF Period_minutes = 1020 FROM t1 LIMIT 1;
''')
assert 0. <= curs.next()[0]
# Conditional foreign on parent and non-parents.
curs = bdb.execute('''
ESTIMATE PROBABILITY OF Period_minutes = 1020 GIVEN
(Apogee_km = 38000, Eccentricity = 0.03) FROM t1 LIMIT 1;
''')
assert 0 <= curs.next()[0]
# Conditional foriegn on foreign.
curs = bdb.execute('''
ESTIMATE PROBABILITY OF Anticipated_Lifetime = 4.09 GIVEN
(Class_of_Orbit = 'LEO', Purpose='Astrophysics',
Period_minutes = 1436) FROM t1 LIMIT 1;
''')
assert 0. <= curs.next()[0]
# Categorical foreign should be less than 1.
curs = bdb.execute('''
ESTIMATE PROBABILITY OF Type_of_Orbit = 'Polar' FROM t1 LIMIT 1;
''')
assert curs.next()[0] <= 1.
# Query inconsistent with evidence should be 0.
curs = bdb.execute('''
ESTIMATE PROBABILITY OF "Type_of_Orbit" = 'Polar'
GIVEN ("Type_of_Orbit" = 'Deep Highly Eccentric') FROM t1 LIMIT 1;
''')
assert curs.next()[0] == 0.
# In theory, query consistent with evidence should be 1, but this is very
# hard to ensure due to stochastic sampling giving different estimates of
# P(Y), once in joint and once in marginal Monte Carlo estimation.
# -----------------------
# TEST MUTUAL INFORMATION
# -----------------------
# Two local columns.
curs = bdb.execute('''
ESTIMATE MUTUAL INFORMATION OF Country_of_Contractor WITH
longitude_radians_of_geo USING 5 SAMPLES FROM t1 LIMIT 1;
''')
# XXX Small sample sizes non-deterministically produce negative MI
assert -1 <= curs.next()[0]
# One local and one foreign column.
curs = bdb.execute('''
ESTIMATE MUTUAL INFORMATION OF Period_minutes WITH
longitude_radians_of_geo USING 5 SAMPLES FROM t1 LIMIT 1;
''')
# XXX This non-deterministically fails when sample sizes are small
# assert 0. <= curs.next()[0]
assert float("-inf") <= curs.next()[0]
# Two foreign columns.
curs = bdb.execute('''
ESTIMATE MUTUAL INFORMATION OF Period_minutes WITH
Anticipated_Lifetime USING 5 SAMPLES FROM t1 LIMIT 1;
''')
# XXX This non-deterministically fails when sample sizes are small
# assert 0. <= curs.next()[0]
assert float("-inf") <= curs.next()[0]
# -----------------------
# TEST PREDICT CONFIDENCE
# -----------------------
# Continuous local column.
curs = bdb.execute('''
INFER EXPLICIT PREDICT Dry_Mass_kg CONFIDENCE c FROM t1 LIMIT 1;
''')
assert curs.next()[1] >= 0.
# Discrete local column with no children.
curs = bdb.execute('''
INFER EXPLICIT PREDICT Purpose CONFIDENCE c FROM t1 LIMIT 1;
''')
assert 0 <= curs.next()[1] <= 1
# Discrete local column with children.
curs = bdb.execute('''
INFER EXPLICIT PREDICT Contractor CONFIDENCE c FROM t1 LIMIT 1;
''')
assert 0 <= curs.next()[1] <= 1
# Continuous foreign columns.
curs = bdb.execute('''
INFER EXPLICIT PREDICT Period_minutes CONFIDENCE c FROM t1 LIMIT 1;
''')
assert curs.next()[1] >= 0.
# Discrete foreign column.
curs = bdb.execute('''
INFER EXPLICIT PREDICT Type_of_Orbit CONFIDENCE c FROM t1 LIMIT 1;
''')
assert 0 <= curs.next()[1] <= 1
bdb.close()
def test_drop_generator():
bdb = bayeslite.bayesdb_open()
# Initialize the database
bayeslite.bayesdb_read_csv_file(bdb, 'satellites', PATH_SATELLITES_CSV,
header=True, create=True)
composer = Composer(n_samples=5)
bayeslite.bayesdb_register_metamodel(bdb, composer)
composer.register_foreign_predictor(random_forest.RandomForest)
composer.register_foreign_predictor(multiple_regression.MultipleRegression)
composer.register_foreign_predictor(keplers_law.KeplersLaw)
bdb.execute('''
CREATE GENERATOR t1 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL,
Launch_Mass_kg NUMERICAL, Dry_Mass_kg NUMERICAL,
Power_watts NUMERICAL, Date_of_Launch NUMERICAL,
Contractor CATEGORICAL,
Country_of_Contractor CATEGORICAL, Launch_Site CATEGORICAL,
Launch_Vehicle CATEGORICAL,
Source_Used_for_Orbital_Data CATEGORICAL,
longitude_radians_of_geo NUMERICAL,
Inclination_radians NUMERICAL,
),
random_forest (
Type_of_Orbit CATEGORICAL
GIVEN Apogee_km, Perigee_km,
Eccentricity, Period_minutes, Launch_Mass_kg,
Power_watts, Anticipated_Lifetime, Class_of_orbit
),
keplers_law (
Period_minutes NUMERICAL
GIVEN Perigee_km, Apogee_km
),
multiple_regression (
Anticipated_Lifetime NUMERICAL
GIVEN Dry_Mass_kg, Power_watts, Launch_Mass_kg,
Contractor
),
DEPENDENT(Apogee_km, Perigee_km, Eccentricity),
DEPENDENT(Contractor, Country_of_Contractor),
INDEPENDENT(Country_of_Operator, Date_of_Launch)
);''')
generator_id = bayeslite.core.bayesdb_get_generator(bdb, 't1')
schema = [
('table', 'bayesdb_composer_cc_id'),
('table', 'bayesdb_composer_column_owner'),
('table', 'bayesdb_composer_column_toposort'),
('table', 'bayesdb_composer_column_parents'),
('table', 'bayesdb_composer_column_foreign_predictor'),
]
# Iterate through tables before dropping.
for _, name in schema:
bdb.sql_execute('''
SELECT * FROM {} WHERE generator_id=?
'''.format(quote(name)), (generator_id,)).next()
# Drop generator and ensure table lookups with generator_id throw error.
bdb.execute('DROP GENERATOR t1')
for _, name in schema:
with pytest.raises(StopIteration):
bdb.sql_execute('''
SELECT * FROM {} WHERE generator_id=?
'''.format(quote(name)), (generator_id,)).next()
assert not bayeslite.core.bayesdb_has_generator(bdb, 't1')
assert not bayeslite.core.bayesdb_has_generator(bdb, 't1_cc')
bdb.close()
def test_register_foreign_predictor():
bdb = bayeslite.bayesdb_open()
composer = Composer(n_samples=5)
bayeslite.bayesdb_register_metamodel(bdb, composer)
# Register valid predictors.
composer.register_foreign_predictor(random_forest.RandomForest)
composer.register_foreign_predictor(multiple_regression.MultipleRegression)
composer.register_foreign_predictor(keplers_law.KeplersLaw)
# Register duplicates.
with pytest.raises(BLE):
composer.register_foreign_predictor(keplers_law.KeplersLaw)
with pytest.raises(BLE):
composer.register_foreign_predictor(
multiple_regression.MultipleRegression)
with pytest.raises(BLE):
composer.register_foreign_predictor(random_forest.RandomForest)
# Register invalid predictors.
with pytest.raises(AssertionError):
composer.register_foreign_predictor(None)
with pytest.raises(AssertionError):
composer.register_foreign_predictor('bans')
from bdbcontrib.predictors import random_forest
from bdbcontrib.predictors import keplers_law
# Get output directory.
if len(sys.argv) < 2:
outdir = '.'
else:
outdir = sys.argv[1]
# Find the satellites file.
PATH_KEPLER = os.path.dirname(os.path.abspath(__file__))
PATH_EXAMPLES = os.path.dirname(PATH_KEPLER)
PATH_SATELLITES = os.path.join(PATH_EXAMPLES, 'satellites')
PATH_SATELLITES_CSV = os.path.join(PATH_SATELLITES, 'satellites.csv')
composer = Composer()
composer.register_foreign_predictor(keplers_law.KeplersLaw)
composer.register_foreign_predictor(random_forest.RandomForest)
if os.path.exists(os.path.join(outdir, 'kepler.bdb')):
os.remove(os.path.join(outdir, 'kepler.bdb'))
bdb = bayeslite.bayesdb_open(os.path.join(outdir, 'kepler.bdb'))
bayeslite.bayesdb_register_metamodel(bdb, composer)
bayeslite.bayesdb_read_csv_file(bdb,
'satellites',
PATH_SATELLITES_CSV,
header=True,
create=True)
bdbcontrib.query(
def test_create_generator_schema():
bdb = bayeslite.bayesdb_open()
bayeslite.bayesdb_read_csv_file(bdb,
'satellites',
PATH_SATELLITES_CSV,
header=True,
create=True)
composer = Composer(n_samples=5)
bayeslite.bayesdb_register_metamodel(bdb, composer)
# Using crosscat and default to specify models should work.
bdb.execute('''
CREATE GENERATOR t1 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
crosscat (
Anticipated_Lifetime NUMERICAL, Contractor CATEGORICAL
)
);''')
assert bayeslite.core.bayesdb_has_generator(bdb, 't1_cc')
# IGNORE and GUESS(*) are forbidden and should crash.
with pytest.raises(AttributeError):
bdb.execute('''
CREATE GENERATOR t2 FOR satellites USING composer(
default (
GUESS(*), Country_of_Operator IGNORE,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
)
);''')
# Test unregistered foreign predictor.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t3 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Apogee_km NUMERICAL GIVEN Operator_Owner
)
);''')
# Unregistered foreign predictor should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t4 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Apogee_km NUMERICAL GIVEN Operator_Owner
)
);''')
# Registered foreign predictor should work.
composer.register_foreign_predictor(random_forest.RandomForest)
bdb.execute('''
CREATE GENERATOR t5 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Eccentricity NUMERICAL
),
random_forest (
Apogee_km NUMERICAL GIVEN Operator_Owner
)
);''')
# Wrong stattype in predictor should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t6 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Apogee_km RADIAL GIVEN Operator_Owner
)
);''')
# Missing GIVEN keyword should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t6 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Apogee_km NUMERICAL, Operator_Owner
)
);''')
# Missing conditions in random forest conditions should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t7 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Apogee_km NUMERICAL GIVEN Operator_Owner
)
);''')
# Test duplicate declarations.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t7 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Class_of_orbit CATEGORICAL GIVEN Operator_Owner
)
);''')
# Arbitrary DAG with foreign predictors.
composer.register_foreign_predictor(multiple_regression.MultipleRegression)
bdb.execute('''
CREATE GENERATOR t8 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
),
random_forest (
Apogee_km NUMERICAL GIVEN Operator_Owner, Users
),
multiple_regression (
Eccentricity NUMERICAL GIVEN Apogee_km, Users, Perigee_km
)
);''')
# Duplicate declarations in foreign predictors should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t9 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL
),
random_forest (
Perigee_km NUMERICAL GIVEN Purpose
),
multiple_regression (
Perigee_km NUMERICAL GIVEN Operator_Owner
)
);''')
# MML for default models should work.
bdb.execute('''
CREATE GENERATOR t10 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Apogee_km NUMERICAL
)
random_forest (
Perigee_km NUMERICAL GIVEN Purpose
)
multiple_regression (
Eccentricity NUMERICAL GIVEN Operator_Owner, Class_of_orbit
)
DEPENDENT(Apogee_km, Perigee_km, Purpose),
INDEPENDENT(Country_of_Operator, Purpose)
);''')
# MML for foreign predictors should crash.
with pytest.raises(BLE):
bdb.execute('''
CREATE GENERATOR t11 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL,
Apogee_km NUMERICAL
),
random_forest (
Perigee_km NUMERICAL GIVEN Purpose
),
multiple_regression (
Eccentricity NUMERICAL GIVEN Operator_Owner, Class_of_orbit
)
DEPENDENT(Apogee_km, Eccentricity, Country_of_Operator),
INDEPENDENT(Perigee_km, Purpose)
);''')
# Test full generator.
composer.register_foreign_predictor(keplers_law.KeplersLaw)
bdb.execute('''
CREATE GENERATOR t12 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL,
Launch_Mass_kg NUMERICAL, Dry_Mass_kg NUMERICAL,
Power_watts NUMERICAL, Date_of_Launch NUMERICAL,
Contractor CATEGORICAL,
Country_of_Contractor CATEGORICAL, Launch_Site CATEGORICAL,
Launch_Vehicle CATEGORICAL,
Source_Used_for_Orbital_Data CATEGORICAL,
longitude_radians_of_geo NUMERICAL,
Inclination_radians NUMERICAL,
),
random_forest (
Type_of_Orbit CATEGORICAL
GIVEN Apogee_km, Perigee_km,
Eccentricity, Period_minutes, Launch_Mass_kg,
Power_watts, Anticipated_Lifetime, Class_of_orbit
),
keplers_law (
Period_minutes NUMERICAL
GIVEN Perigee_km, Apogee_km
),
multiple_regression (
Anticipated_Lifetime NUMERICAL
GIVEN Dry_Mass_kg, Power_watts, Launch_Mass_kg, Contractor
),
DEPENDENT(Apogee_km, Perigee_km, Eccentricity),
INDEPENDENT(Country_of_Operator, longitude_radians_of_geo)
);''')
bdb.close()
def test_composer_integration__ci_slow():
# But currently difficult to seperate these tests into smaller tests because
# of their sequential nature. We will still test all internal functions
# with different regimes of operation.
# SETUP
# -----
# Dataset.
bdb = bayeslite.bayesdb_open()
bayeslite.bayesdb_read_csv_file(bdb,
'satellites',
PATH_SATELLITES_CSV,
header=True,
create=True)
bdbcontrib.bql_utils.nullify(bdb, 'satellites', 'NaN')
# Composer.
composer = Composer(n_samples=5)
composer.register_foreign_predictor(multiple_regression.MultipleRegression)
composer.register_foreign_predictor(keplers_law.KeplersLaw)
composer.register_foreign_predictor(random_forest.RandomForest)
# Use complex generator for interesting test cases.
bayeslite.bayesdb_register_metamodel(bdb, composer)
bdb.execute('''
CREATE GENERATOR t1 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL,
Launch_Mass_kg NUMERICAL, Dry_Mass_kg NUMERICAL,
Power_watts NUMERICAL, Date_of_Launch NUMERICAL,
Contractor CATEGORICAL,
Country_of_Contractor CATEGORICAL, Launch_Site CATEGORICAL,
Launch_Vehicle CATEGORICAL,
Source_Used_for_Orbital_Data CATEGORICAL,
longitude_radians_of_geo NUMERICAL,
Inclination_radians NUMERICAL,
),
random_forest (
Type_of_Orbit CATEGORICAL
GIVEN Apogee_km, Perigee_km,
Eccentricity, Period_minutes, Launch_Mass_kg,
Power_watts, Anticipated_Lifetime, Class_of_orbit
),
keplers_law (
Period_minutes NUMERICAL
GIVEN Perigee_km, Apogee_km
),
multiple_regression (
Anticipated_Lifetime NUMERICAL
GIVEN Dry_Mass_kg, Power_watts, Launch_Mass_kg,
Contractor
),
DEPENDENT(Apogee_km, Perigee_km, Eccentricity),
DEPENDENT(Contractor, Country_of_Contractor),
INDEPENDENT(Country_of_Operator, Date_of_Launch)
);''')
# ----------------------
# TEST INITIALIZE MODELS
# ----------------------
bdb.execute('INITIALIZE 2 MODELS FOR t1')
# Check number of models.
df = describe_generator_models(bdb, 't1')
assert len(df) == 2
df = describe_generator_models(bdb, 't1_cc')
assert len(df) == 2
# -------------------
# TEST ANALYZE MODELS
# -------------------
bdb.execute('ANALYZE t1 FOR 2 ITERATIONS WAIT;')
# Check number of iterations of composer.
df = describe_generator_models(bdb, 't1')
for index, modelno, iterations in df.itertuples():
assert iterations == 2
# Check number of iterations of composer_cc.
df = describe_generator_models(bdb, 't1_cc')
for index, modelno, iterations in df.itertuples():
assert iterations == 2
# ----------------------------------
# TEST COLUMN DEPENDENCE PROBABILITY
# ----------------------------------
# Special 0/1 regimes.
# Local with a INDEPENDENT local should be 0.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Date_of_Launch
WITH Country_of_Operator FROM t1 LIMIT 1
''')
assert curs.next()[0] == 0
# Local with a DEPENDENT local should be 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Perigee_km WITH Eccentricity
FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Apogee_km WITH Eccentricity
FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1
# Foreign with a local parent should be 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Period_minutes WITH Apogee_km
FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Anticipated_Lifetime WITH Power_watts
FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Foreign with a foreign parent should be 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Type_of_Orbit WITH
Anticipated_Lifetime FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Foreign with a local non-parent DEPENDENT with local parent should be 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Period_minutes WITH
Eccentricity FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Foreign with foreign sharing common direct ancestor should be 1.
# Launch_Mass_kg is the common parent.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Anticipated_Lifetime WITH
Type_of_Orbit FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Foreign with a foreign sharing a common DEPENDENT ancestor should be 1.
# Eccentricity is a parent of Type_of_orbit, and is dependent
# with Period_minutes through DEPENDENT(Apogee_km, Perigee_km, Eccentricity)
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Period_minutes WITH
Type_of_Orbit FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Column with itself should be 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Anticipated_Lifetime WITH
Anticipated_Lifetime FROM t1 LIMIT 1
''')
assert curs.next()[0] == 1.
# Unknown [0,1] regimes.
# Foreign with a local of unknown relation with parents.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Anticipated_Lifetime WITH
longitude_radians_of_geo FROM t1 LIMIT 1
''')
assert 0 <= curs.next()[0] <= 1.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Period_minutes WITH
longitude_radians_of_geo FROM t1 LIMIT 1
''')
assert 0 <= curs.next()[0] <= 1.
# Foreign with a foreign of unknown ancestry relation.
curs = bdb.execute('''
ESTIMATE DEPENDENCE PROBABILITY OF Anticipated_Lifetime WITH
Period_minutes FROM t1 LIMIT 1
''')
assert 0 <= curs.next()[0] <= 1.
# ----------------------------------
# TEST SIMULATE
# ----------------------------------
# Crash tests for various code paths. Quality of simulations ignored.
# Joint local.
curs = bdb.execute('''
SIMULATE Power_watts, Launch_Mass_kg FROM t1 LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Forward simulate foreign.
curs = bdb.execute('''
SIMULATE Period_minutes FROM t1 GIVEN Apogee_km = 1000, Perigee_km = 980
LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Forward simulate foreign with missing parents.
curs = bdb.execute('''
SIMULATE Anticipated_Lifetime FROM t1 GIVEN Dry_Mass_kg = 2894,
Launch_Mass_kg = 1730 LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Joint simulate foreign with parents, and missing parents.
curs = bdb.execute('''
SIMULATE Type_of_Orbit, Eccentricity FROM t1 GIVEN Dry_Mass_kg = 2894,
Launch_Mass_kg = 1730 LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Joint simulate foreign with non-parents.
curs = bdb.execute('''
SIMULATE Period_minutes, Eccentricity FROM t1 GIVEN Apogee_km = 38000
LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Simulate joint local conditioned on two foreigns.
curs = bdb.execute('''
SIMULATE Country_of_Operator, Inclination_radians FROM t1
GIVEN Period_minutes = 1432, Anticipated_Lifetime = 5 LIMIT 2;
''')
assert len(curs.fetchall()) == 2
# Simulate joint foreign conditioned on third foreign.
curs = bdb.execute('''
SIMULATE Period_minutes, Anticipated_Lifetime FROM t1
GIVEN Type_of_Orbit = 'Deep Highly Eccentric' LIMIT 2
''')
assert len(curs.fetchall()) == 2
# Simulate foreign conditioned on itself.
curs = bdb.execute('''
SIMULATE Period_minutes, Apogee_km FROM t1
GIVEN Period_minutes = 102 LIMIT 2
''')
assert [s[0] for s in curs] == [102] * 2
# -----------------------------
# TEST COLUMN VALUE PROBABILITY
# -----------------------------
# Crash tests for various code path. Quality of logpdf ignored.
# Conditional local.
curs = bdb.execute('''
ESTIMATE PROBABILITY OF Power_watts = 800 GIVEN (Perigee_km = 980,
Launch_Mass_kg = 890) FROM t1 LIMIT 1;
''')
assert 0. <= curs.next()[0]
# Unconditional foreign
curs = bdb.execute('''
ESTIMATE PROBABILITY OF Period_minutes = 1020 FROM t1 LIMIT 1;
''')
assert 0. <= curs.next()[0]
# Conditional foreign on parent and non-parents.
curs = bdb.execute('''
ESTIMATE PROBABILITY OF Period_minutes = 1020 GIVEN
(Apogee_km = 38000, Eccentricity = 0.03) FROM t1 LIMIT 1;
''')
assert 0 <= curs.next()[0]
# Conditional foriegn on foreign.
curs = bdb.execute('''
ESTIMATE PROBABILITY OF Anticipated_Lifetime = 4.09 GIVEN
(Class_of_Orbit = 'LEO', Purpose='Astrophysics',
Period_minutes = 1436) FROM t1 LIMIT 1;
''')
assert 0. <= curs.next()[0]
# Categorical foreign should be less than 1.
curs = bdb.execute('''
ESTIMATE PROBABILITY OF Type_of_Orbit = 'Polar' FROM t1 LIMIT 1;
''')
assert curs.next()[0] <= 1.
# Query inconsistent with evidence should be 0.
curs = bdb.execute('''
ESTIMATE PROBABILITY OF "Type_of_Orbit" = 'Polar'
GIVEN ("Type_of_Orbit" = 'Deep Highly Eccentric') FROM t1 LIMIT 1;
''')
assert curs.next()[0] == 0.
# In theory, query consistent with evidence should be 1, but this is very
# hard to ensure due to stochastic sampling giving different estimates of
# P(Y), once in joint and once in marginal Monte Carlo estimation.
# -----------------------
# TEST MUTUAL INFORMATION
# -----------------------
# Two local columns.
curs = bdb.execute('''
ESTIMATE MUTUAL INFORMATION OF Country_of_Contractor WITH
longitude_radians_of_geo USING 5 SAMPLES FROM t1 LIMIT 1;
''')
# XXX Small sample sizes non-deterministically produce negative MI
assert -1 <= curs.next()[0]
# One local and one foreign column.
curs = bdb.execute('''
ESTIMATE MUTUAL INFORMATION OF Period_minutes WITH
longitude_radians_of_geo USING 5 SAMPLES FROM t1 LIMIT 1;
''')
# XXX This non-deterministically fails when sample sizes are small
# assert 0. <= curs.next()[0]
assert float("-inf") <= curs.next()[0]
# Two foreign columns.
curs = bdb.execute('''
ESTIMATE MUTUAL INFORMATION OF Period_minutes WITH
Anticipated_Lifetime USING 5 SAMPLES FROM t1 LIMIT 1;
''')
# XXX This non-deterministically fails when sample sizes are small
# assert 0. <= curs.next()[0]
assert float("-inf") <= curs.next()[0]
# -----------------------
# TEST PREDICT CONFIDENCE
# -----------------------
# Continuous local column.
curs = bdb.execute('''
INFER EXPLICIT PREDICT Dry_Mass_kg CONFIDENCE c FROM t1 LIMIT 1;
''')
assert curs.next()[1] >= 0.
# Discrete local column with no children.
curs = bdb.execute('''
INFER EXPLICIT PREDICT Purpose CONFIDENCE c FROM t1 LIMIT 1;
''')
assert 0 <= curs.next()[1] <= 1
# Discrete local column with children.
curs = bdb.execute('''
INFER EXPLICIT PREDICT Contractor CONFIDENCE c FROM t1 LIMIT 1;
''')
assert 0 <= curs.next()[1] <= 1
# Continuous foreign columns.
curs = bdb.execute('''
INFER EXPLICIT PREDICT Period_minutes CONFIDENCE c FROM t1 LIMIT 1;
''')
assert curs.next()[1] >= 0.
# Discrete foreign column.
curs = bdb.execute('''
INFER EXPLICIT PREDICT Type_of_Orbit CONFIDENCE c FROM t1 LIMIT 1;
''')
assert 0 <= curs.next()[1] <= 1
bdb.close()
def test_drop_generator():
bdb = bayeslite.bayesdb_open()
# Initialize the database
bayeslite.bayesdb_read_csv_file(bdb,
'satellites',
PATH_SATELLITES_CSV,
header=True,
create=True)
composer = Composer(n_samples=5)
bayeslite.bayesdb_register_metamodel(bdb, composer)
composer.register_foreign_predictor(random_forest.RandomForest)
composer.register_foreign_predictor(multiple_regression.MultipleRegression)
composer.register_foreign_predictor(keplers_law.KeplersLaw)
bdb.execute('''
CREATE GENERATOR t1 FOR satellites USING composer(
default (
Country_of_Operator CATEGORICAL, Operator_Owner CATEGORICAL,
Users CATEGORICAL, Purpose CATEGORICAL,
Class_of_orbit CATEGORICAL, Perigee_km NUMERICAL,
Apogee_km NUMERICAL, Eccentricity NUMERICAL,
Launch_Mass_kg NUMERICAL, Dry_Mass_kg NUMERICAL,
Power_watts NUMERICAL, Date_of_Launch NUMERICAL,
Contractor CATEGORICAL,
Country_of_Contractor CATEGORICAL, Launch_Site CATEGORICAL,
Launch_Vehicle CATEGORICAL,
Source_Used_for_Orbital_Data CATEGORICAL,
longitude_radians_of_geo NUMERICAL,
Inclination_radians NUMERICAL,
),
random_forest (
Type_of_Orbit CATEGORICAL
GIVEN Apogee_km, Perigee_km,
Eccentricity, Period_minutes, Launch_Mass_kg,
Power_watts, Anticipated_Lifetime, Class_of_orbit
),
keplers_law (
Period_minutes NUMERICAL
GIVEN Perigee_km, Apogee_km
),
multiple_regression (
Anticipated_Lifetime NUMERICAL
GIVEN Dry_Mass_kg, Power_watts, Launch_Mass_kg,
Contractor
),
DEPENDENT(Apogee_km, Perigee_km, Eccentricity),
DEPENDENT(Contractor, Country_of_Contractor),
INDEPENDENT(Country_of_Operator, Date_of_Launch)
);''')
generator_id = bayeslite.core.bayesdb_get_generator(bdb, 't1')
schema = [
('table', 'bayesdb_composer_cc_id'),
('table', 'bayesdb_composer_column_owner'),
('table', 'bayesdb_composer_column_toposort'),
('table', 'bayesdb_composer_column_parents'),
('table', 'bayesdb_composer_column_foreign_predictor'),
]
# Iterate through tables before dropping.
for _, name in schema:
bdb.sql_execute(
'''
SELECT * FROM {} WHERE generator_id=?
'''.format(quote(name)), (generator_id, )).next()
# Drop generator and ensure table lookups with generator_id throw error.
bdb.execute('DROP GENERATOR t1')
for _, name in schema:
with pytest.raises(StopIteration):
bdb.sql_execute(
'''
SELECT * FROM {} WHERE generator_id=?
'''.format(quote(name)), (generator_id, )).next()
assert not bayeslite.core.bayesdb_has_generator(bdb, 't1')
assert not bayeslite.core.bayesdb_has_generator(bdb, 't1_cc')
bdb.close()
def test_register_foreign_predictor():
bdb = bayeslite.bayesdb_open()
composer = Composer(n_samples=5)
bayeslite.bayesdb_register_metamodel(bdb, composer)
# Register valid predictors.
composer.register_foreign_predictor(random_forest.RandomForest)
composer.register_foreign_predictor(multiple_regression.MultipleRegression)
composer.register_foreign_predictor(keplers_law.KeplersLaw)
# Register duplicates.
with pytest.raises(BLE):
composer.register_foreign_predictor(keplers_law.KeplersLaw)
with pytest.raises(BLE):
composer.register_foreign_predictor(
multiple_regression.MultipleRegression)
with pytest.raises(BLE):
composer.register_foreign_predictor(random_forest.RandomForest)
# Register invalid predictors.
with pytest.raises(AssertionError):
composer.register_foreign_predictor(None)
with pytest.raises(AssertionError):
composer.register_foreign_predictor('bans')
