示例#1
0
def test_row_column_predictive_probability(exname, rowid, colno):
    if exname == "t0" and colno > 1:
        pytest.skip("Not enough columns in t0.")
    if exname.startswith("t1_sub") and colno > 1:
        pytest.skip("Not enough columns in %s." % (exname,))
    with analyzed_bayesdb_generator(examples[exname](), 1, 1) as (bdb, generator_id):
        if rowid == 0:
            rowid = bayesdb_maxrowid(bdb, generator_id)
        bqlfn.bql_row_column_predictive_probability(bdb, generator_id, None, rowid, colno)
        sql = "select bql_row_column_predictive_probability(?, NULL, ?, ?)"
        bdb.sql_execute(sql, (generator_id, rowid, colno)).fetchall()
示例#2
0
def test_row_column_predictive_probability(exname, rowid, colno):
    if exname == 't0' and colno > 1:
        pytest.skip('Not enough columns in t0.')
    if exname.startswith('t1_sub') and colno > 1:
        pytest.skip('Not enough columns in %s.' % (exname, ))
    with analyzed_bayesdb_generator(examples[exname](), 1, 1) \
            as (bdb, generator_id):
        if rowid == 0: rowid = bayesdb_maxrowid(bdb, generator_id)
        bqlfn.bql_row_column_predictive_probability(bdb, generator_id, None,
                                                    rowid, colno)
        sql = 'select bql_row_column_predictive_probability(?, NULL, ?, ?)'
        bdb.sql_execute(sql, (generator_id, rowid, colno)).fetchall()
示例#3
0
def test_row_column_predictive_probability(exname, rowid, colno):
    if exname == 't0' and colno > 1:
        pytest.skip('Not enough columns in t0.')
    if exname.startswith('t1_sub') and colno > 1:
        pytest.skip('Not enough columns in %s.' % (exname,))
    with analyzed_bayesdb_population(examples[exname](), 1, 1) \
            as (bdb, population_id, generator_id):
        if rowid == 0:
            rowid = bayesdb_maxrowid(bdb, population_id)
        targets = json.dumps([colno])
        constraints = json.dumps([])
        bqlfn.bql_row_column_predictive_probability(
            bdb, population_id, None, None, rowid, targets, constraints)
        bdb.sql_execute('''
            select bql_row_column_predictive_probability(
                ?, NULL, NULL, ?, \'%s\', \'%s\')
            ''' % (targets, constraints), (population_id, rowid)
        ).fetchall()
示例#4
0
def test_row_column_predictive_probability(exname, rowid, colno):
    if exname == 't0' and colno > 1:
        pytest.skip('Not enough columns in t0.')
    if exname.startswith('t1_sub') and colno > 1:
        pytest.skip('Not enough columns in %s.' % (exname,))
    with analyzed_bayesdb_population(examples[exname](), 1, 1) \
            as (bdb, population_id, _generator_id):
        if rowid == 0:
            rowid = bayesdb_maxrowid(bdb, population_id)
        targets = json.dumps([colno])
        constraints = json.dumps([])
        bqlfn.bql_row_column_predictive_probability(
            bdb, population_id, None, None, rowid, targets, constraints)
        bdb.sql_execute('''
            select bql_row_column_predictive_probability(
                ?, NULL, NULL, ?, \'%s\', \'%s\')
            ''' % (targets, constraints), (population_id, rowid)
        ).fetchall()