def _make_children(grid_id):
return [
db.Fit(id=f"child_{grid_id}_{i}",
instance=af.Gaussian(centre=i),
model=af.Model(af.Gaussian, centre=float(-i)),
max_log_likelihood=grid_id + i) for i in range(10)
]
def test_query_before(
self,
aggregator,
grid_fit,
session
):
session.add(
db.Fit(
id="grid2",
is_grid_search=True,
instance=Gaussian(
centre=2
)
)
)
session.flush()
parent_aggregator = aggregator.query(
aggregator.is_grid_search & (aggregator.centre == 1)
)
result, = parent_aggregator.fits
assert result is grid_fit
child_aggregator = parent_aggregator.children()
results = child_aggregator.fits
assert len(results) == 10
results = aggregator.query(
aggregator.is_grid_search & (aggregator.centre == 2)
).children().fits
assert len(results) == 0
def test_embedded_query(
session,
aggregator
):
model_1 = db.Fit(
id="model_1",
instance=af.Collection(
gaussian=m.Gaussian(
centre=1
)
),
info={"info": 3}
)
model_2 = db.Fit(
id="model_2",
instance=af.Collection(
gaussian=m.Gaussian(
centre=2
)
),
info={"info": 4}
)
session.add_all([
model_1,
model_2
])
result = aggregator.query(
aggregator.centre == 0
)
assert result == []
result = aggregator.query(
aggregator.gaussian.centre == 1
)
assert result == [model_1]
result = aggregator.query(
aggregator.gaussian.centre == 2
)
assert result == [model_2]
def make_gaussian_0(session):
gaussian_0 = db.Fit(id="gaussian_0",
instance=af.Gaussian(centre=1),
info={"info": 1},
is_complete=True,
unique_tag="zero")
session.add(gaussian_0)
session.commit()
return gaussian_0
def make_grid_fit(children):
return db.Fit(
id="grid",
is_grid_search=True,
children=children,
instance=Gaussian(
centre=1
)
)
def make_children():
return [
db.Fit(
id=f"child_{i}",
instance=Gaussian(
centre=i
)
)
for i in range(10)
]
def make_gaussian_none(
session
):
gaussian_none = db.Fit(
id="gaussian_none",
instance=af.Gaussian(
centre=None
)
)
session.add(gaussian_none)
session.commit()
return gaussian_none
def test_set_and_retrieve(
session
):
fit = db.Fit()
fit.named_instances[
"one"
] = af.Gaussian()
assert isinstance(
fit.named_instances[
"one"
],
af.Gaussian
)
def test_query(
session
):
fit = db.Fit(
id="test_query"
)
fit.named_instances[
"one"
] = af.Gaussian()
session.add(fit)
session.commit()
fit, = db.Fit.all(
session
)
assert isinstance(
fit.named_instances[
"one"
],
af.Gaussian
)
def test_fit():
assert db.Fit(info={"info": 1}).id != db.Fit(info={"info": 2}).id
def make_gaussian_1():
return db.Fit(id="gaussian_1",
instance=m.Gaussian(centre=1),
info={"info": 1},
is_complete=True,
unique_tag="one")
def make_gaussian_2():
return db.Fit(id="gaussian_2",
instance=m.Gaussian(centre=2),
info={"info": 2},
is_complete=False,
unique_tag="two")
def make_grid_fit_2():
return db.Fit(id="grid2",
unique_tag="grid_fit_2",
is_grid_search=True,
children=_make_children(2),
instance=af.Gaussian(centre=2))
def make_fit():
return db.Fit(id="id", info={"key": "value"})