def test_t1_predict(rowid, colno, confidence):
with analyzed_bayesdb_population(t1(), 1, 1) as (bdb, pop_id, gen_id):
if rowid == 0: rowid = bayesdb_maxrowid(bdb, pop_id)
bqlfn.bql_predict(bdb, pop_id, None, None, rowid, colno, confidence,
None)
def test_t1_predict(rowid, colno, confidence):
with analyzed_bayesdb_generator(t1(), 1, 1) as (bdb, generator_id):
if rowid == 0: rowid = bayesdb_maxrowid(bdb, generator_id)
bqlfn.bql_predict(bdb, generator_id, None, colno, rowid, confidence)
def test_t1_predict(rowid, colno, confidence):
with analyzed_bayesdb_generator(t1(), 1, 1) as (bdb, generator_id):
if rowid == 0: rowid = bayesdb_maxrowid(bdb, generator_id)
bqlfn.bql_predict(bdb, generator_id, None, colno, rowid, confidence)
def test_t1_predict(rowid, colno, confidence):
with analyzed_bayesdb_population(t1(), 1, 1) as (bdb, pop_id, gen_id):
if rowid == 0: rowid = bayesdb_maxrowid(bdb, pop_id)
bqlfn.bql_predict(
bdb, pop_id, None, None, rowid, colno, confidence, None)