def bql_row_column_predictive_probability(bdb, population_id, generator_id,
rowid, colno):
value = core.bayesdb_population_cell_value(bdb, population_id, rowid,
colno)
if value is None:
return None
# Retrieve all other values in the row.
row_values = core.bayesdb_population_row_values(bdb, population_id, rowid)
variable_numbers = core.bayesdb_variable_numbers(bdb, population_id, None)
# Build the constraints and query from rowid, using a fresh rowid.
fresh_rowid = core.bayesdb_population_fresh_row_id(bdb, population_id)
query = [(colno, value)]
constraints = [(col, value)
for (col, value) in zip(variable_numbers, row_values)
if (value is not None) and (col != colno)]
def generator_predprob(generator_id):
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
return metamodel.logpdf_joint(bdb, generator_id, fresh_rowid, query,
constraints, None)
generator_ids = _retrieve_generator_ids(bdb, population_id, generator_id)
predprobs = map(generator_predprob, generator_ids)
r = logmeanexp(predprobs)
return ieee_exp(r)
def test_t1_simulate(colnos, constraints, numpredictions):
if len(colnos) == 0:
# No need to try this or confirm it fails gracefully --
# nothing should be trying it anyway, and bayeslite_simulate
# is not exposed to users of the bayeslite API.
return
with analyzed_bayesdb_population(t1(), 1, 1) \
as (bdb, population_id, generator_id):
if constraints is not None:
rowid = 1 # XXX Avoid hard-coding this.
# Can't use t1_rows[0][i] because not all t1-based tables
# use the same column indexing -- some use a subset of the
# columns.
#
# XXX Automatically test the correct exception.
constraints = [
(i,
core.bayesdb_population_cell_value(bdb, population_id, rowid,
i)) for i in constraints
if i not in colnos
]
bqlfn.bayesdb_simulate(bdb,
population_id,
None,
None,
constraints,
colnos,
numpredictions=numpredictions)
def bql_row_column_predictive_probability(bdb, population_id, generator_id,
rowid, colno):
value = core.bayesdb_population_cell_value(
bdb, population_id, rowid, colno)
if value is None:
return None
def generator_predprob(generator_id):
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
return metamodel.logpdf_joint(
bdb, generator_id, [(rowid, colno, value)], [], None)
generator_ids = [generator_id] if generator_id is not None else \
core.bayesdb_population_generators(bdb, population_id)
predprobs = map(generator_predprob, generator_ids)
r = logmeanexp(predprobs)
return ieee_exp(r)
def test_t1_column_value_probability(colno, rowid):
with analyzed_bayesdb_population(t1(), 1, 1) \
as (bdb, population_id, generator_id):
if rowid == 0:
rowid = bayesdb_maxrowid(bdb, population_id)
value = core.bayesdb_population_cell_value(bdb, population_id, rowid,
colno)
bqlfn.bql_column_value_probability(bdb, population_id, None, None,
colno, value)
table_name = core.bayesdb_population_table(bdb, population_id)
var = core.bayesdb_variable_name(bdb, population_id, None, colno)
qt = bql_quote_name(table_name)
qv = bql_quote_name(var)
sql = '''
select bql_column_value_probability(?, NULL, NULL, ?,
(select %s from %s where rowid = ?))
''' % (qv, qt)
bdb.sql_execute(sql, (population_id, colno, rowid)).fetchall()
def test_t1_column_value_probability(colno, rowid):
with analyzed_bayesdb_population(t1(), 1, 1) \
as (bdb, population_id, generator_id):
if rowid == 0:
rowid = bayesdb_maxrowid(bdb, population_id)
value = core.bayesdb_population_cell_value(
bdb, population_id, rowid, colno)
bqlfn.bql_column_value_probability(
bdb, population_id, None, None, colno, value)
table_name = core.bayesdb_population_table(bdb, population_id)
var = core.bayesdb_variable_name(bdb, population_id, None, colno)
qt = bql_quote_name(table_name)
qv = bql_quote_name(var)
sql = '''
select bql_column_value_probability(?, NULL, NULL, ?,
(select %s from %s where rowid = ?))
''' % (qv, qt)
bdb.sql_execute(sql, (population_id, colno, rowid)).fetchall()
def test_t1_simulate(colnos, constraints, numpredictions):
if len(colnos) == 0:
# No need to try this or confirm it fails gracefully --
# nothing should be trying it anyway, and bayeslite_simulate
# is not exposed to users of the bayeslite API.
return
with analyzed_bayesdb_population(t1(), 1, 1) \
as (bdb, population_id, generator_id):
if constraints is not None:
rowid = 1 # XXX Avoid hard-coding this.
# Can't use t1_rows[0][i] because not all t1-based tables
# use the same column indexing -- some use a subset of the
# columns.
#
# XXX Automatically test the correct exception.
constraints = [
(i, core.bayesdb_population_cell_value(
bdb, population_id, rowid, i))
for i in constraints
if i not in colnos
]
bqlfn.bayesdb_simulate(bdb, population_id, None, None, constraints,
colnos, numpredictions=numpredictions)
def retrieve_values(colnos):
values = [
core.bayesdb_population_cell_value(bdb, population_id, rowid,
colno) for colno in colnos
]
return [(c, v) for (c, v) in zip(colnos, values) if v is not None]
def retrieve_values(colnos):
values = [
core.bayesdb_population_cell_value(bdb, population_id, rowid, colno)
for colno in colnos
]
return [(c,v) for (c,v) in zip (colnos, values) if v is not None]
