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feature/filter #691

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merged 6 commits into from
Mar 6, 2023
Merged

feature/filter #691

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fe0566e
fix broken test
rhayes777 Mar 6, 2023
e24072d
format
rhayes777 Mar 6, 2023
41def0b
permit single type instead of tuple as argument
rhayes777 Mar 6, 2023
ad4f0eb
excluded classes
rhayes777 Mar 6, 2023
2f0d3da
more testing
rhayes777 Mar 6, 2023
8bbf30d
docs
rhayes777 Mar 6, 2023
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22 changes: 20 additions & 2 deletions autofit/mapper/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -422,8 +422,26 @@ def values(self):
def __len__(self):
return len(self.values())

def as_model(self, model_classes=tuple()):
def as_model(
self,
model_classes: Union[type, Iterable[type]] = tuple(),
excluded_classes: Union[type, Iterable[type]] = tuple(),
):
"""
Convert this instance to a model

Parameters
----------
model_classes
The classes to convert to models
excluded_classes
The classes to exclude from conversion

Returns
-------
A model
"""

from autofit.mapper.prior_model.abstract import AbstractPriorModel

return AbstractPriorModel.from_instance(self, model_classes)
return AbstractPriorModel.from_instance(self, model_classes, excluded_classes,)
6 changes: 6 additions & 0 deletions autofit/mapper/model_object.py
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Original file line number Diff line number Diff line change
Expand Up @@ -121,6 +121,12 @@ def from_dict(d):
instance = TuplePrior()
elif type_ == "dict":
return {key: ModelObject.from_dict(value) for key, value in d.items()}
elif type_ == "instance":
d.pop("type")
cls = get_class(d.pop("class_path"))
return cls(
**{key: ModelObject.from_dict(value) for key, value in d.items()}
)
else:
try:
return Prior.from_dict(d)
Expand Down
37 changes: 27 additions & 10 deletions autofit/mapper/prior_model/abstract.py
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Original file line number Diff line number Diff line change
Expand Up @@ -444,9 +444,7 @@ def assert_no_assertions(obj):
try:
item = copy.copy(source)
if isinstance(item, dict):
from autofit.mapper.prior_model.collection import (
Collection,
)
from autofit.mapper.prior_model.collection import Collection

item = Collection(item)
for attribute in path:
Expand Down Expand Up @@ -1008,13 +1006,20 @@ def random_instance(self, ignore_prior_limits=False):

@staticmethod
@DynamicRecursionCache()
def from_instance(instance, model_classes=tuple()):
def from_instance(
instance,
model_classes: Union[type, Iterable[type]] = tuple(),
exclude_classes: Union[type, Iterable[type]] = tuple(),
):
"""
Recursively create an prior object model from an object model.
Recursively create a prior object model from an object model.

Parameters
----------
model_classes
A tuple of classes that should be converted to a prior model
exclude_classes
A tuple of classes that should not be converted to a prior model
instance
A dictionary, list, class instance or model instance
Returns
Expand All @@ -1024,12 +1029,18 @@ def from_instance(instance, model_classes=tuple()):
"""
from autofit.mapper.prior_model import collection

if isinstance(instance, exclude_classes):
return instance
if isinstance(instance, (Prior, AbstractPriorModel)):
return instance
elif isinstance(instance, list):
result = collection.Collection(
[
AbstractPriorModel.from_instance(item, model_classes=model_classes)
AbstractPriorModel.from_instance(
item,
model_classes=model_classes,
exclude_classes=exclude_classes,
)
for item in instance
]
)
Expand All @@ -1042,14 +1053,18 @@ def from_instance(instance, model_classes=tuple()):
result,
key,
AbstractPriorModel.from_instance(
value, model_classes=model_classes
value,
model_classes=model_classes,
exclude_classes=exclude_classes,
),
)
elif isinstance(instance, dict):
result = collection.Collection(
{
key: AbstractPriorModel.from_instance(
value, model_classes=model_classes
value,
model_classes=model_classes,
exclude_classes=exclude_classes,
)
for key, value in instance.items()
}
Expand All @@ -1064,15 +1079,17 @@ def from_instance(instance, model_classes=tuple()):
instance.__class__,
**{
key: AbstractPriorModel.from_instance(
value, model_classes=model_classes
value,
model_classes=model_classes,
exclude_classes=exclude_classes,
)
for key, value in instance.__dict__.items()
if key != "cls"
},
)
except AttributeError:
return instance
if any([isinstance(instance, cls) for cls in model_classes]):
if isinstance(instance, model_classes):
return result.as_model()
return result

Expand Down
140 changes: 33 additions & 107 deletions test_autofit/mapper/model/test_json.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,54 +5,37 @@

import autofit as af

@pytest.fixture(
name="model_dict"
)

@pytest.fixture(name="model_dict")
def make_model_dict():
return {
"type": "model",
"class_path": "autofit.example.model.Gaussian",
"centre": {'lower_limit': 0.0, 'type': 'Uniform', 'upper_limit': 2.0},
"normalization": {'lower_limit': 0.0, 'type': 'Uniform', 'upper_limit': 1.0},
"sigma": {'lower_limit': 0.0, 'type': 'Uniform', 'upper_limit': 1.0},
"centre": {"lower_limit": 0.0, "type": "Uniform", "upper_limit": 2.0},
"normalization": {"lower_limit": 0.0, "type": "Uniform", "upper_limit": 1.0},
"sigma": {"lower_limit": 0.0, "type": "Uniform", "upper_limit": 1.0},
}


@pytest.fixture(
name="instance_dict"
)
@pytest.fixture(name="instance_dict")
def make_instance_dict():
return {
"type": "instance",
"class_path": "autofit.example.model.Gaussian",
"centre": 0.0,
"normalization": 0.1,
"sigma": 0.01
"sigma": 0.01,
}


@pytest.fixture(
name="collection_dict"
)
def make_collection_dict(
model_dict
):
return {
"gaussian": model_dict,
"type": "collection"
}
@pytest.fixture(name="collection_dict")
def make_collection_dict(model_dict):
return {"gaussian": model_dict, "type": "collection"}


@pytest.fixture(
name="model"
)
@pytest.fixture(name="model")
def make_model():
return af.Model(
af.Gaussian,
centre=af.UniformPrior(
upper_limit=2.0
)
)
return af.Model(af.Gaussian, centre=af.UniformPrior(upper_limit=2.0))


class TestTuple:
Expand All @@ -61,118 +44,61 @@ def test_tuple_prior(self):
tuple_prior.tup_0 = 0
tuple_prior.tup_1 = 1

result = af.Model.from_dict(
tuple_prior.dict()
)
assert isinstance(
result,
af.TuplePrior
)
result = af.Model.from_dict(tuple_prior.dict())
assert isinstance(result, af.TuplePrior)

def test_model_with_tuple(self):
tuple_model = af.Model(af.m.MockWithTuple)
tuple_model.instance_from_prior_medians()
model_dict = tuple_model.dict()

model = af.Model.from_dict(
model_dict
)
model = af.Model.from_dict(model_dict)
instance = model.instance_from_prior_medians()
assert instance.tup == (0.5, 0.5)


class TestFromDict:
def test_model_from_dict(
self,
model_dict
):
model = af.Model.from_dict(
model_dict
)
def test_model_from_dict(self, model_dict):
model = af.Model.from_dict(model_dict)
assert model.cls == af.Gaussian
assert model.prior_count == 3
assert model.centre.upper_limit == 2.0

def test_instance_from_dict(
self,
instance_dict
):
instance = af.Model.from_dict(
instance_dict
)
assert isinstance(
instance,
af.Gaussian
)
def test_instance_from_dict(self, instance_dict):
instance = af.Model.from_dict(instance_dict)
assert isinstance(instance, af.Gaussian)
assert instance.centre == 0.0
assert instance.normalization == 0.1
assert instance.sigma == 0.01

def test_collection_from_dict(
self,
collection_dict
):
collection = af.Model.from_dict(
collection_dict
)
assert isinstance(
collection,
af.Collection
)
def test_collection_from_dict(self, collection_dict):
collection = af.Model.from_dict(collection_dict)
assert isinstance(collection, af.Collection)
assert len(collection) == 1


class TestToDict:
def test_model_priors(
self,
model,
model_dict
):
def test_model_priors(self, model, model_dict):
assert model.dict() == model_dict

def test_model_floats(
self,
instance_dict
):
model = af.Model(
af.Gaussian,
centre=0.0,
normalization=0.1,
sigma=0.01
)
def test_model_floats(self, instance_dict):
model = af.Model(af.Gaussian, centre=0.0, normalization=0.1, sigma=0.01)

assert model.dict() == instance_dict

def test_collection(
self,
model,
collection_dict
):
collection = af.Collection(
gaussian=model
)
def test_collection(self, model, collection_dict):
collection = af.Collection(gaussian=model)
assert collection.dict() == collection_dict

def test_collection_instance(
self,
instance_dict
):
collection = af.Collection(
gaussian=af.Gaussian()
)
assert collection.dict() == {
"gaussian": instance_dict,
"type": "collection"
}
def test_collection_instance(self, instance_dict):
collection = af.Collection(gaussian=af.Gaussian())
assert collection.dict() == {"gaussian": instance_dict, "type": "collection"}


class TestFromJson:

def test__from_json(self, model_dict):

model = af.Model.from_dict(
model_dict
)
model = af.Model.from_dict(model_dict)

model_file = Path(__file__).parent / "model.json"

Expand All @@ -190,4 +116,4 @@ def test__from_json(self, model_dict):
assert model.prior_count == 3
assert model.centre.upper_limit == 2.0

os.remove(model_file)
os.remove(model_file)
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