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classes adapter
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4 changed files with 212 additions and 25 deletions
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@ -5,8 +5,10 @@
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:maxdepth: 3
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api/index
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todo
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changelog
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```
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8
docs/todo.md
Normal file
8
docs/todo.md
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# TODO
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Important things that are not implemented yet!
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- {meth}`nwb_linkml.adapters.classes.ClassAdapter.handle_dtype` does not yet handle compound dtypes,
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leaving them as `AnyType` instead. This is fine for a first draft since they are used rarely within
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NWB, but we will need to handle them by making slots for each of the dtypes since they typically
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represent table-like data.
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@ -10,8 +10,6 @@ from nwb_linkml.maps import QUANTITY_MAP
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from nwb_linkml.maps.naming import camel_to_snake
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class ClassAdapter(Adapter):
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"""
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Abstract adapter to class-like things in linkml, holds methods common to
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@ -33,10 +31,24 @@ class ClassAdapter(Adapter):
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"""
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Build the basic class and attributes before adding any specific
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modifications for groups or datasets.
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The main distinction in behavior for this method is whether this class has a parent class -
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ie this is one of the anonymous nested child datasets or groups within another group.
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If the class has no parent, then...
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* Its name is inferred from its `neurodata_type_def`, fixed name, or `neurodata_type_inc` in that order
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* It is just built as normal class!
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* It will be indicated as a ``tree_root`` (which will primarily be used to invert the translation for write operations)
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If the class has a parent, then...
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* If it has a `neurodata_type_def` or `inc`, that will be used as its name, otherwise concatenate `parent__child`,
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eg. ``TimeSeries__TimeSeriesData``
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* A slot will also be made and returned with the BuildResult, which the parent will then have as one of its attributes.
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"""
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# Build this class
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#name = self._get_full_name()
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kwargs = {}
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if self.parent is not None:
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kwargs['name'] = self._get_full_name()
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@ -105,7 +117,6 @@ class ClassAdapter(Adapter):
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else:
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raise ValueError('Not sure what our name is!')
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return name
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def _get_attr_name(self) -> str:
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@ -113,19 +124,13 @@ class ClassAdapter(Adapter):
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Get the name to use as the attribute name,
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again distinct from the actual name of the instantiated object
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"""
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# return self._get_full_name()
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name = None
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if self.cls.neurodata_type_def:
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# name = camel_to_snake(self.cls.neurodata_type_def)
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if self.cls.neurodata_type_def is not None:
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name = self.cls.neurodata_type_def
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elif self.cls.name is not None:
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# we do have a unique name
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name = self.cls.name
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elif self.cls.neurodata_type_inc:
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# name = camel_to_snake(self.cls.neurodata_type_inc)
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elif self.cls.neurodata_type_inc is not None:
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name = self.cls.neurodata_type_inc
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if name is None:
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else:
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raise ValueError(f'Class has no name!: {self.cls}')
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return name
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@ -136,19 +141,13 @@ class ClassAdapter(Adapter):
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used to dodge name overlaps by snake-casing!
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again distinct from the actual name of the instantiated object
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"""
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# return self._get_full_name()
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name = None
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if self.cls.neurodata_type_def:
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name = camel_to_snake(self.cls.neurodata_type_def)
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# name = self.cls.neurodata_type_def
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elif self.cls.name is not None:
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# we do have a unique name
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name = self.cls.name
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elif self.cls.neurodata_type_inc:
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name = camel_to_snake(self.cls.neurodata_type_inc)
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# name = self.cls.neurodata_type_inc
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if name is None:
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else:
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raise ValueError(f'Class has no name!: {self.cls}')
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return name
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@ -167,7 +166,6 @@ class ClassAdapter(Adapter):
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# so we'll... uh... treat them as slots.
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# TODO
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return 'AnyType'
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#raise NotImplementedError('got distracted, need to implement')
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else:
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# flat dtype
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@ -4,11 +4,190 @@ import pytest
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from ..fixtures import linkml_schema_bare, linkml_schema, nwb_schema
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from nwb_linkml.adapters import DatasetAdapter, ClassAdapter
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from linkml_runtime.linkml_model import SlotDefinition
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from nwb_linkml.adapters import DatasetAdapter, ClassAdapter, GroupAdapter
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from nwb_schema_language import Group, Dataset, ReferenceDtype, CompoundDtype
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def test_build_base(nwb_schema):
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# simplest case, nothing special here
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# simplest case, nothing special here. Should be same behavior between dataset and group
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dset = DatasetAdapter(cls=nwb_schema.datasets['image'])
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base = dset.build_base()
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assert len(base.slots) == 0
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assert len(base.classes) == 1
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img = base.classes[0]
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assert img.name == "Image"
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# no parent class, tree_root shoudl be true
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assert img.tree_root
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assert len(img.attributes) == 3
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# now with parent class
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groups = GroupAdapter(cls=nwb_schema.groups['images'])
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dset.parent = groups
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base = dset.build_base()
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# we made a self-slot (will be tested elsewhere)
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assert len(base.slots) == 1
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assert len(base.classes) == 1
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img = base.classes[0]
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assert not img.tree_root
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assert len(img.attributes) == 3
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# now try adding an extra attribute
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slot = SlotDefinition(name="newslot", range="string")
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# should coerce single slot to a list within the method
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base = dset.build_base(extra_attrs=slot)
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assert len(base.slots) == 1
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assert len(base.classes) == 1
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img = base.classes[0]
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assert len(img.attributes) == 4
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assert img.attributes['newslot'] is slot
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def test_get_attr_name():
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"""Name method used by parentless classes"""
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cls = Dataset(neurodata_type_def='MyClass', doc='a class')
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adapter = DatasetAdapter(cls=cls)
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# type_defs get their original name
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assert adapter._get_attr_name() == 'MyClass'
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# explicit names get that name, but only if there is no type_def
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adapter.cls.name = 'MyClassName'
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assert adapter._get_attr_name() == 'MyClass'
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adapter.cls.neurodata_type_def = None
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assert adapter._get_attr_name() == 'MyClassName'
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# if neither, use the type inc
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adapter.cls.neurodata_type_inc = 'MyThirdName'
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assert adapter._get_attr_name() == 'MyClassName'
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adapter.cls.name = None
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assert adapter._get_attr_name() == 'MyThirdName'
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# if none are present, raise a value error
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adapter.cls.neurodata_type_inc = None
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with pytest.raises(ValueError):
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adapter._get_attr_name()
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def test_get_full_name():
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"""Name used by child classes"""
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cls = Dataset(neurodata_type_def='Child', doc='a class')
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parent = GroupAdapter(cls=Group(neurodata_type_def='Parent', doc='a class'))
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adapter = DatasetAdapter(cls=cls, parent=parent)
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# if child has its own type_def, use that
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assert adapter._get_full_name() == 'Child'
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# same thing with type_inc
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adapter.cls.neurodata_type_def = None
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adapter.cls.neurodata_type_inc = 'ChildInc'
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assert adapter._get_full_name() == 'ChildInc'
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# if it just has a name, it gets concatenated with its parents
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adapter.cls.neurodata_type_inc = None
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adapter.cls.name = 'ChildName'
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assert adapter._get_full_name() == 'Parent__ChildName'
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# this should work at any depth of nesting if the parent is not an independently defined class
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grandparent = GroupAdapter(cls=Group(neurodata_type_def='Grandparent', doc='a class'))
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parent.cls.neurodata_type_def = None
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parent.cls.name = 'ParentName'
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parent.parent = grandparent
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assert adapter._get_full_name() == 'Grandparent__ParentName__ChildName'
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# if it has none, raise value error
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adapter.cls.name = None
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with pytest.raises(ValueError):
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adapter._get_full_name()
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def test_self_slot():
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"""
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Slot that represents ourselves to our parent
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Quantity map is tested elsewhere
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"""
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cls = Dataset(neurodata_type_def='ChildClass', doc='a class', quantity='?')
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parent = GroupAdapter(cls=Group(neurodata_type_def='Parent', doc='a class'))
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adapter = DatasetAdapter(cls=cls, parent=parent)
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# base case - snake case a type def
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slot = adapter.build_self_slot()
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assert slot.name == 'child_class'
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assert slot.range == 'ChildClass' == adapter._get_full_name()
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# this should be the slot that gets build with the build_base method
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base = adapter.build_base()
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assert len(base.slots) == 1
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assert base.slots[0] == slot
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# if class has a unique name, use that without changing, but only if no type_def
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adapter.cls.name = "FixedName"
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slot = adapter.build_self_slot()
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assert slot.name == 'child_class'
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adapter.cls.neurodata_type_def = None
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slot = adapter.build_self_slot()
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assert slot.name == 'FixedName'
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assert slot.range == adapter._get_full_name()
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# type_inc works the same as type_def, but only if name and type_def are None
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adapter.cls.neurodata_type_inc = 'IncName'
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slot = adapter.build_self_slot()
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assert slot.name == 'FixedName'
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adapter.cls.name = None
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slot = adapter.build_self_slot()
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assert slot.name == 'inc_name'
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assert slot.range == adapter._get_full_name()
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# if we have nothing, raise value error
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adapter.cls.neurodata_type_inc = None
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with pytest.raises(ValueError):
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adapter.build_self_slot()
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def test_name_slot():
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"""Classes with a fixed name should name slot with a fixed value"""
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# no name
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cls = DatasetAdapter(cls=Dataset(neurodata_type_def='MyClass', doc='a class'))
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slot = cls.build_name_slot()
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assert slot.name == 'name'
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assert slot.required
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assert slot.range == 'string'
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assert slot.identifier
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assert slot.ifabsent is None
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assert slot.equals_string is None
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cls.cls.name = 'FixedName'
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slot = cls.build_name_slot()
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assert slot.name == 'name'
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assert slot.required
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assert slot.range == 'string'
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assert slot.identifier
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assert slot.ifabsent == 'string(FixedName)'
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assert slot.equals_string == 'FixedName'
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def test_handle_dtype(nwb_schema):
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"""
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Dtypes should be translated from nwb schema language to linkml
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Dtypes are validated by the nwb_schema_language classes, so we don't do that here
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"""
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cls = DatasetAdapter(cls=Dataset(neurodata_type_def='MyClass', doc='a class'))
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reftype = ReferenceDtype(target_type='TargetClass', reftype='reference')
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compoundtype = [
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CompoundDtype(name='field_a', doc='field a!', dtype='int32'),
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CompoundDtype(name='field_b', doc='field b!', dtype='text'),
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CompoundDtype(name="reference", doc="reference!", dtype=reftype)
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]
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assert cls.handle_dtype(reftype) == 'TargetClass'
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assert cls.handle_dtype(None) == 'AnyType'
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assert cls.handle_dtype([]) == 'AnyType'
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# handling compound types is currently TODO
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assert cls.handle_dtype(compoundtype) == 'AnyType'
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assert cls.handle_dtype('int32') == 'int32'
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#pdb.set_trace()
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pass
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