bkbit.models.anatomical_structure module

class bkbit.models.anatomical_structure.ANATOMICALDIRECTION(value)

Bases: str, Enum

A controlled vocabulary term defining axis direction in terms of anatomical direction.

anterior_to_posterior = 'anterior_to_posterior'

inferior_to_superior = 'inferior_to_superior'

left_to_right = 'left_to_right'

posterior_to_anterior = 'posterior_to_anterior'

superior_to_inferior = 'superior_to_inferior'

class bkbit.models.anatomical_structure.AnatomicalAnnotationSet(*, id: str, name: str, description: str, category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/AnatomicalAnnotationSet', 'AnS:AnatomicalAnnotationSet']] = ['AnS:AnatomicalAnnotationSet'], version: str, revision_of: str | None = None, parameterizes: str)

Bases: VersionedNamedThing

An anatomical annotation set is a versioned release of a set of anatomical annotations anchored in the same anatomical space that divides the space into distinct segments following some annotation criteria or parcellation scheme. For example, the anatomical annotation set of 3D image based reference atlases (e.g. Allen Mouse CCF) can be expressed as a set of label indices of single multi-valued image annotations or as a set of segmentation masks (ref: ILX:0777108, RRID:SCR_023499)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/AnatomicalAnnotationSet', 'AnS:AnatomicalAnnotationSet']]

description: str

id: str

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'https://w3id.org/my-org/anatomical-structure-schema', 'slot_usage': {'revision_of': {'any_of': [{'range': 'AnatomicalAnnotationSet'}, {'range': 'string'}], 'name': 'revision_of'}}})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'category': FieldInfo(annotation=List[Literal['https://w3id.org/my-org/anatomical-structure-schema/AnatomicalAnnotationSet', 'AnS:AnatomicalAnnotationSet']], required=False, default=['AnS:AnatomicalAnnotationSet'], json_schema_extra={'linkml_meta': {'alias': 'category', 'designates_type': True, 'domain_of': ['NamedThing'], 'is_class_field': True}}), 'description': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'description', 'domain_of': ['NamedThing']}}), 'id': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'id', 'domain_of': ['NamedThing']}}), 'name': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'name', 'domain_of': ['NamedThing']}}), 'parameterizes': FieldInfo(annotation=str, required=True, description='Reference to the anatomical space for which the anatomical annotation set is anchored', json_schema_extra={'linkml_meta': {'alias': 'parameterizes', 'any_of': [{'range': 'AnatomicalSpace'}, {'range': 'string'}], 'domain_of': ['AnatomicalAnnotationSet']}}), 'revision_of': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, json_schema_extra={'linkml_meta': {'alias': 'revision_of', 'any_of': [{'range': 'AnatomicalAnnotationSet'}, {'range': 'string'}], 'domain_of': ['VersionedNamedThing']}}), 'version': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'version', 'domain_of': ['VersionedNamedThing']}})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

name: str

parameterizes: str

revision_of: str | None

version: str

class bkbit.models.anatomical_structure.AnatomicalSpace(*, id: str, name: str, description: str, category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/AnatomicalSpace', 'AnS:AnatomicalSpace']] = ['AnS:AnatomicalSpace'], version: str, revision_of: str | None = None, measures: str)

Bases: VersionedNamedThing

An anatomical space is versioned release of a mathematical space with a defined mapping between the anatomical axes and the mathematical axes. An anatomical space may be defined by a reference image chosen as the biological reference for an anatomical structure of interest derived from a single or multiple specimens (ref: ILX:0777106, RRID:SCR_023499)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/AnatomicalSpace', 'AnS:AnatomicalSpace']]

description: str

id: str

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'https://w3id.org/my-org/anatomical-structure-schema', 'slot_usage': {'revision_of': {'any_of': [{'range': 'AnatomicalSpace'}, {'range': 'string'}], 'name': 'revision_of'}}})

measures: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'category': FieldInfo(annotation=List[Literal['https://w3id.org/my-org/anatomical-structure-schema/AnatomicalSpace', 'AnS:AnatomicalSpace']], required=False, default=['AnS:AnatomicalSpace'], json_schema_extra={'linkml_meta': {'alias': 'category', 'designates_type': True, 'domain_of': ['NamedThing'], 'is_class_field': True}}), 'description': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'description', 'domain_of': ['NamedThing']}}), 'id': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'id', 'domain_of': ['NamedThing']}}), 'measures': FieldInfo(annotation=str, required=True, description='Reference to the specific image dataset used to define the anatomical space.', json_schema_extra={'linkml_meta': {'alias': 'measures', 'any_of': [{'range': 'ImageDataset'}, {'range': 'string'}], 'domain_of': ['AnatomicalSpace']}}), 'name': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'name', 'domain_of': ['NamedThing']}}), 'revision_of': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, json_schema_extra={'linkml_meta': {'alias': 'revision_of', 'any_of': [{'range': 'AnatomicalSpace'}, {'range': 'string'}], 'domain_of': ['VersionedNamedThing']}}), 'version': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'version', 'domain_of': ['VersionedNamedThing']}})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

name: str

revision_of: str | None

version: str

class bkbit.models.anatomical_structure.ConfiguredBaseModel

Bases: BaseModel

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class bkbit.models.anatomical_structure.DISTANCEUNIT(value)

Bases: str, Enum

An enumeration.

meter = 'm'

micrometer = 'um'

millimeter = 'mm'

class bkbit.models.anatomical_structure.ImageDataset(*, id: str, name: str, description: str, category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ImageDataset', 'AnS:ImageDataset']] = ['AnS:ImageDataset'], version: str, revision_of: str | None = None, x_direction: ANATOMICALDIRECTION | None = None, y_direction: ANATOMICALDIRECTION | None = None, z_direction: ANATOMICALDIRECTION | None = None, x_size: Annotated[int | None, Ge(ge=1)] = None, y_size: Annotated[int | None, Ge(ge=1)] = None, z_size: Annotated[int | None, Ge(ge=1)] = None, x_resolution: float | None = None, y_resolution: float | None = None, z_resolution: float | None = None, unit: DISTANCEUNIT | None = None)

Bases: VersionedNamedThing

An image dataset is versioned release of a multidimensional regular grid of measurements and metadata required for a morphological representation of an entity such as an anatomical structure (ref: OBI_0003327, RRID:SCR_006266)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ImageDataset', 'AnS:ImageDataset']]

description: str

id: str

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'https://w3id.org/my-org/anatomical-structure-schema', 'slot_usage': {'revision_of': {'any_of': [{'range': 'ImageDataset'}, {'range': 'string'}], 'name': 'revision_of'}}})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'category': FieldInfo(annotation=List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ImageDataset', 'AnS:ImageDataset']], required=False, default=['AnS:ImageDataset'], json_schema_extra={'linkml_meta': {'alias': 'category', 'designates_type': True, 'domain_of': ['NamedThing'], 'is_class_field': True}}), 'description': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'description', 'domain_of': ['NamedThing']}}), 'id': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'id', 'domain_of': ['NamedThing']}}), 'name': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'name', 'domain_of': ['NamedThing']}}), 'revision_of': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, json_schema_extra={'linkml_meta': {'alias': 'revision_of', 'any_of': [{'range': 'ImageDataset'}, {'range': 'string'}], 'domain_of': ['VersionedNamedThing']}}), 'unit': FieldInfo(annotation=Union[DISTANCEUNIT, NoneType], required=False, default=None, description='A controlled vocabulary attribute defining the length unit of the x, y, and z  resolution values.', json_schema_extra={'linkml_meta': {'alias': 'unit', 'domain_of': ['ImageDataset']}}), 'version': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'version', 'domain_of': ['VersionedNamedThing']}}), 'x_direction': FieldInfo(annotation=Union[ANATOMICALDIRECTION, NoneType], required=False, default=None, description='A controlled vocabulary attribute defining the x axis direction in terms of anatomical  direction.', json_schema_extra={'linkml_meta': {'alias': 'x_direction', 'domain_of': ['ImageDataset']}}), 'x_resolution': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='The resolution (length / pixel) in along the x axis (numerical value part).', json_schema_extra={'linkml_meta': {'alias': 'x_resolution', 'domain_of': ['ImageDataset'], 'structured_pattern': {'syntax': '{PositiveFloat}'}}}), 'x_size': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='The number of pixels/voxels (size) along the x axis.', json_schema_extra={'linkml_meta': {'alias': 'x_size', 'domain_of': ['ImageDataset']}}, metadata=[Ge(ge=1)]), 'y_direction': FieldInfo(annotation=Union[ANATOMICALDIRECTION, NoneType], required=False, default=None, description='A controlled vocabulary attribute defining the y axis direction in terms of anatomical  direction.', json_schema_extra={'linkml_meta': {'alias': 'y_direction', 'domain_of': ['ImageDataset']}}), 'y_resolution': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='The resolution (length / pixel) in along the y axis (numerical value part).', json_schema_extra={'linkml_meta': {'alias': 'y_resolution', 'domain_of': ['ImageDataset'], 'structured_pattern': {'syntax': '{PositiveFloat}'}}}), 'y_size': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='The number of pixels/voxels (size) along the y axis.', json_schema_extra={'linkml_meta': {'alias': 'y_size', 'domain_of': ['ImageDataset']}}, metadata=[Ge(ge=1)]), 'z_direction': FieldInfo(annotation=Union[ANATOMICALDIRECTION, NoneType], required=False, default=None, description='A controlled vocabulary attribute defining the z axis direction in terms of anatomical  direction.', json_schema_extra={'linkml_meta': {'alias': 'z_direction', 'domain_of': ['ImageDataset']}}), 'z_resolution': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='The resolution (length / pixel) in along the z axis (numerical value part).', json_schema_extra={'linkml_meta': {'alias': 'z_resolution', 'domain_of': ['ImageDataset'], 'structured_pattern': {'syntax': '{PositiveFloat}'}}}), 'z_size': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='The number of pixels/voxels (size) along the y axis.', json_schema_extra={'linkml_meta': {'alias': 'z_size', 'domain_of': ['ImageDataset']}}, metadata=[Ge(ge=1)])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

name: str

revision_of: str | None

unit: DISTANCEUNIT | None

version: str

x_direction: ANATOMICALDIRECTION | None

x_resolution: float | None

x_size: int | None

y_direction: ANATOMICALDIRECTION | None

y_resolution: float | None

y_size: int | None

z_direction: ANATOMICALDIRECTION | None

z_resolution: float | None

z_size: int | None

class bkbit.models.anatomical_structure.LinkMLMeta(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=Dict[str, Any], required=False, default={})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

root: Dict[str, Any]

class bkbit.models.anatomical_structure.NamedThing(*, id: str, name: str, description: str, category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/NamedThing', 'AnS:NamedThing']] = ['AnS:NamedThing'])

Bases: ConfiguredBaseModel

Core base entity for Anatomical Structure schema representing an entity with an identifier name and description.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/NamedThing', 'AnS:NamedThing']]

description: str

id: str

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'abstract': True, 'from_schema': 'https://w3id.org/my-org/anatomical-structure-core-schema'})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'category': FieldInfo(annotation=List[Literal['https://w3id.org/my-org/anatomical-structure-schema/NamedThing', 'AnS:NamedThing']], required=False, default=['AnS:NamedThing'], json_schema_extra={'linkml_meta': {'alias': 'category', 'designates_type': True, 'domain_of': ['NamedThing'], 'is_class_field': True}}), 'description': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'description', 'domain_of': ['NamedThing']}}), 'id': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'id', 'domain_of': ['NamedThing']}}), 'name': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'name', 'domain_of': ['NamedThing']}})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

name: str

class bkbit.models.anatomical_structure.ParcellationAnnotation(*, part_of_anatomical_annotation_set: str, internal_identifier: str, voxel_count: Annotated[int | None, Ge(ge=0)] = None)

Bases: ConfiguredBaseModel

A parcellation annotation defines a specific segment of an anatomical space denoted by an internal identifier and is a unique and exclusive member of a versioned release anatomical annotation set. For example, in the case where the anatomical annotation set is a single multi-value image mask (e.g. Allen Mouse CCF), a specific annotation corresponds to a specific label index (internal identifier) in the mask.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

internal_identifier: str

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'https://w3id.org/my-org/anatomical-structure-schema'})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'internal_identifier': FieldInfo(annotation=str, required=True, description='An identifier that uniquely denotes a specific parcellation annotation within the context of an anatomical annotation set', json_schema_extra={'linkml_meta': {'alias': 'internal_identifier', 'domain_of': ['ParcellationAnnotation']}}), 'part_of_anatomical_annotation_set': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'part_of_anatomical_annotation_set', 'any_of': [{'range': 'AnatomicalAnnotationSet'}, {'range': 'string'}], 'domain_of': ['ParcellationAnnotation']}}), 'voxel_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='The number of voxels (3D pixels) spanned by the parcellation annotation (optional).', json_schema_extra={'linkml_meta': {'alias': 'voxel_count', 'domain_of': ['ParcellationAnnotation']}}, metadata=[Ge(ge=0)])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

part_of_anatomical_annotation_set: str

voxel_count: int | None

class bkbit.models.anatomical_structure.ParcellationAnnotationTermMap(*, subject_parcellation_annotation: ParcellationAnnotation | str, subject_parcellation_term: str)

Bases: ConfiguredBaseModel

The parcellation annotation term map table defines the relationship between parcellation annotations and parcellation terms. A parcellation term is uniquely denoted by a parcellation term identifier and the parcellation terminology it belongs to. A parcellation term can be spatially parameterized by the union of one or more parcellation annotations within a versioned release of an anatomical annotation set. For example, annotations defining individual cortical layers in cortical region R (R1, R2/3, R4, etc) can be combined to define the parent region R.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'https://w3id.org/my-org/anatomical-structure-schema'})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'subject_parcellation_annotation': FieldInfo(annotation=Union[ParcellationAnnotation, str], required=True, description='Reference to the parcellation annotation that is the subject of the association.', json_schema_extra={'linkml_meta': {'alias': 'subject_parcellation_annotation', 'any_of': [{'range': 'ParcellationAnnotation'}, {'range': 'string'}], 'domain_of': ['ParcellationAnnotationTermMap']}}), 'subject_parcellation_term': FieldInfo(annotation=str, required=True, description='Reference to the parcellation term that is the subject of the association.', json_schema_extra={'linkml_meta': {'alias': 'subject_parcellation_term', 'any_of': [{'range': 'ParcellationTerm'}, {'range': 'string'}], 'domain_of': ['ParcellationColorAssignment', 'ParcellationAnnotationTermMap']}})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

subject_parcellation_annotation: ParcellationAnnotation | str

subject_parcellation_term: str

class bkbit.models.anatomical_structure.ParcellationAtlas(*, id: str, name: str, description: str, category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationAtlas', 'AnS:ParcellationAtlas']] = ['AnS:ParcellationAtlas'], version: str, revision_of: str | None = None, has_anatomical_space: str, has_anatomical_annotation_set: str, has_parcellation_terminology: str, specialization_of: str | None = None)

Bases: VersionedNamedThing

A parcellation atlas is a versioned release reference used to guide experiments or deal with the spatial relationship between objects or the location of objects within the context of some anatomical structure. An atlas is minimally defined by a notion of space (either implicit or explicit) and an annotation set. Reference atlases usually have additional parts that make them more useful in certain situations, such as a well defined coordinate system, delineations indicating the boundaries of various regions or cell populations, landmarks, and labels and names to make it easier to communicate about well known and useful locations (ref: ILX:0777109, RRID:SCR_023499).

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationAtlas', 'AnS:ParcellationAtlas']]

description: str

has_anatomical_annotation_set: str

has_anatomical_space: str

has_parcellation_terminology: str

id: str

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'https://w3id.org/my-org/anatomical-structure-schema', 'slot_usage': {'revision_of': {'any_of': [{'range': 'ParcellationAtlas'}, {'range': 'string'}], 'name': 'revision_of'}}})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'category': FieldInfo(annotation=List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationAtlas', 'AnS:ParcellationAtlas']], required=False, default=['AnS:ParcellationAtlas'], json_schema_extra={'linkml_meta': {'alias': 'category', 'designates_type': True, 'domain_of': ['NamedThing'], 'is_class_field': True}}), 'description': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'description', 'domain_of': ['NamedThing']}}), 'has_anatomical_annotation_set': FieldInfo(annotation=str, required=True, description='Reference to the anatomical annotation set component of the parcellation atlas', json_schema_extra={'linkml_meta': {'alias': 'has_anatomical_annotation_set', 'any_of': [{'range': 'AnatomicalAnnotationSet'}, {'range': 'string'}], 'domain_of': ['ParcellationAtlas']}}), 'has_anatomical_space': FieldInfo(annotation=str, required=True, description='Reference to the anatomical space component of the parcellation atlas', json_schema_extra={'linkml_meta': {'alias': 'has_anatomical_space', 'any_of': [{'range': 'AnatomicalSpace'}, {'range': 'string'}], 'domain_of': ['ParcellationAtlas']}}), 'has_parcellation_terminology': FieldInfo(annotation=str, required=True, description='Reference to the parcellation terminology component of the parcellation atlas', json_schema_extra={'linkml_meta': {'alias': 'has_parcellation_terminology', 'any_of': [{'range': 'ParcellationTerminology'}, {'range': 'string'}], 'domain_of': ['ParcellationAtlas']}}), 'id': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'id', 'domain_of': ['NamedThing']}}), 'name': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'name', 'domain_of': ['NamedThing']}}), 'revision_of': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, json_schema_extra={'linkml_meta': {'alias': 'revision_of', 'any_of': [{'range': 'ParcellationAtlas'}, {'range': 'string'}], 'domain_of': ['VersionedNamedThing']}}), 'specialization_of': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Reference to the general (non versioned) parcellation atlas for which the parcellation atlas is a specific  version release of.', json_schema_extra={'linkml_meta': {'alias': 'specialization_of', 'any_of': [{'range': 'ParcellationAtlas'}, {'range': 'string'}], 'domain_of': ['ParcellationAtlas']}}), 'version': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'version', 'domain_of': ['VersionedNamedThing']}})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

name: str

revision_of: str | None

specialization_of: str | None

version: str

class bkbit.models.anatomical_structure.ParcellationColorAssignment(*, part_of_parcellation_color_scheme: str, subject_parcellation_term: str, color: str | None = None)

Bases: ConfiguredBaseModel

The parcellation color assignment associates hex color value to a parcellation term within a versioned release of a color scheme. A parcellation term is uniquely denoted by a parcellation term identifier and the parcellation terminology it belongs to.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

color: str | None

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'https://w3id.org/my-org/anatomical-structure-schema'})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'color': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='A string representing to hex triplet code of a color', json_schema_extra={'linkml_meta': {'alias': 'color', 'domain_of': ['ParcellationColorAssignment'], 'structured_pattern': {'syntax': '{ColorHexTriplet}'}}}), 'part_of_parcellation_color_scheme': FieldInfo(annotation=str, required=True, description='Reference to the parcellation color scheme for which the color assignment is part of.', json_schema_extra={'linkml_meta': {'alias': 'part_of_parcellation_color_scheme', 'any_of': [{'range': 'ParcellationColorScheme'}, {'range': 'string'}], 'domain_of': ['ParcellationColorAssignment']}}), 'subject_parcellation_term': FieldInfo(annotation=str, required=True, description='Reference to the parcellation term identifier for which the color assignment is about.', json_schema_extra={'linkml_meta': {'alias': 'subject_parcellation_term', 'any_of': [{'range': 'ParcellationTerm'}, {'range': 'string'}], 'domain_of': ['ParcellationColorAssignment', 'ParcellationAnnotationTermMap']}})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

part_of_parcellation_color_scheme: str

subject_parcellation_term: str

class bkbit.models.anatomical_structure.ParcellationColorScheme(*, id: str, name: str, description: str, category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationColorScheme', 'AnS:ParcellationColorScheme']] = ['AnS:ParcellationColorScheme'], version: str, revision_of: str | None = None, subject_parcellation_terminology: str)

Bases: VersionedNamedThing

A parcellation color scheme is a versioned release color palette that can be used to visualize a parcellation terminology or its related parcellation annotation. A parcellation terminology may have zero or more parcellation color schemes and each color scheme is in context of a specific parcellation terminology, where each parcellation term is assigned a hex color value. A parcellation color scheme is defined as a part of one and only one parcellation terminology.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationColorScheme', 'AnS:ParcellationColorScheme']]

description: str

id: str

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'https://w3id.org/my-org/anatomical-structure-schema', 'slot_usage': {'revision_of': {'any_of': [{'range': 'ParcellationColorScheme'}, {'range': 'string'}], 'name': 'revision_of'}}})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'category': FieldInfo(annotation=List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationColorScheme', 'AnS:ParcellationColorScheme']], required=False, default=['AnS:ParcellationColorScheme'], json_schema_extra={'linkml_meta': {'alias': 'category', 'designates_type': True, 'domain_of': ['NamedThing'], 'is_class_field': True}}), 'description': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'description', 'domain_of': ['NamedThing']}}), 'id': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'id', 'domain_of': ['NamedThing']}}), 'name': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'name', 'domain_of': ['NamedThing']}}), 'revision_of': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, json_schema_extra={'linkml_meta': {'alias': 'revision_of', 'any_of': [{'range': 'ParcellationColorScheme'}, {'range': 'string'}], 'domain_of': ['VersionedNamedThing']}}), 'subject_parcellation_terminology': FieldInfo(annotation=str, required=True, description='Reference to the parcellation terminology for which the parcellation color scheme is in  context of.', json_schema_extra={'linkml_meta': {'alias': 'subject_parcellation_terminology', 'any_of': [{'range': 'ParcellationTerminology'}, {'range': 'string'}], 'domain_of': ['ParcellationColorScheme']}}), 'version': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'version', 'domain_of': ['VersionedNamedThing']}})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

name: str

revision_of: str | None

subject_parcellation_terminology: str

version: str

class bkbit.models.anatomical_structure.ParcellationTerm(*, id: str, name: str, description: str, category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationTerm', 'AnS:ParcellationTerm']] = ['AnS:ParcellationTerm'], symbol: str | None = None, part_of_parcellation_term_set: str, ordinal: Annotated[int | None, Ge(ge=0)] = None, has_parent_parcellation_term: str | None = None)

Bases: NamedThing

A parcellation term is an individual term within a specific parcellation terminology describing a single anatomical entity by a persistent identifier, name, symbol and description. A parcellation term is a unique and exclusive member of a versioned release parcellation terminology. Although term identifiers must be unique within the context of one versioned release of a parcellation terminology, they can be reused in different parcellation terminology versions enabling the representation of terminology updates and modifications over time.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationTerm', 'AnS:ParcellationTerm']]

description: str

has_parent_parcellation_term: str | None

id: str

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'https://w3id.org/my-org/anatomical-structure-schema'})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'category': FieldInfo(annotation=List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationTerm', 'AnS:ParcellationTerm']], required=False, default=['AnS:ParcellationTerm'], json_schema_extra={'linkml_meta': {'alias': 'category', 'designates_type': True, 'domain_of': ['NamedThing'], 'is_class_field': True}}), 'description': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'description', 'domain_of': ['NamedThing']}}), 'has_parent_parcellation_term': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Reference to the parent parcellation term for which the parcellation term is a child ( spatially part) of', json_schema_extra={'linkml_meta': {'alias': 'has_parent_parcellation_term', 'any_of': [{'range': 'ParcellationTerm'}, {'range': 'string'}], 'domain_of': ['ParcellationTerm']}}), 'id': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'id', 'domain_of': ['NamedThing']}}), 'name': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'name', 'domain_of': ['NamedThing']}}), 'ordinal': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Ordinal of the parcellation term among other terms within the context of the associated  parcellation terminology.', json_schema_extra={'linkml_meta': {'alias': 'ordinal', 'domain_of': ['ParcellationTermSet', 'ParcellationTerm']}}, metadata=[Ge(ge=0)]), 'part_of_parcellation_term_set': FieldInfo(annotation=str, required=True, description='Reference to the parcellation term set for which the parcellation term is part of.', json_schema_extra={'linkml_meta': {'alias': 'part_of_parcellation_term_set', 'any_of': [{'range': 'ParcellationTermSet'}, {'range': 'string'}], 'domain_of': ['ParcellationTerm']}}), 'symbol': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Symbol representing a parcellation term.', json_schema_extra={'linkml_meta': {'alias': 'symbol', 'domain_of': ['ParcellationTerm']}})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

name: str

ordinal: int | None

part_of_parcellation_term_set: str

symbol: str | None

class bkbit.models.anatomical_structure.ParcellationTermSet(*, id: str, name: str, description: str, category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationTermSet', 'AnS:ParcellationTermSet']] = ['AnS:ParcellationTermSet'], part_of_parcellation_terminology: str, ordinal: Annotated[int | None, Ge(ge=0)] = None, has_parent_parcellation_term_set: str | None = None)

Bases: NamedThing

A parcellation term set is the set of parcellation terms within a specific parcellation terminology. A parcellation term set belongs to one and only one parcellation terminology and each parcellation term in a parcellation terminology belongs to one and only one term set. If the parcellation terminology is a taxonomy, parcellation term sets can be used to represent taxonomic ranks. For consistency, if the terminology does not have the notion of taxonomic ranks, all terms are grouped into a single parcellation term set.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationTermSet', 'AnS:ParcellationTermSet']]

description: str

has_parent_parcellation_term_set: str | None

id: str

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'https://w3id.org/my-org/anatomical-structure-schema'})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'category': FieldInfo(annotation=List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationTermSet', 'AnS:ParcellationTermSet']], required=False, default=['AnS:ParcellationTermSet'], json_schema_extra={'linkml_meta': {'alias': 'category', 'designates_type': True, 'domain_of': ['NamedThing'], 'is_class_field': True}}), 'description': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'description', 'domain_of': ['NamedThing']}}), 'has_parent_parcellation_term_set': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Reference to the parent parcellation term set for which the parcellation term set is a child  (lower taxonomic rank) of.', json_schema_extra={'linkml_meta': {'alias': 'has_parent_parcellation_term_set', 'any_of': [{'range': 'ParcellationTermSet'}, {'range': 'string'}], 'domain_of': ['ParcellationTermSet']}}), 'id': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'id', 'domain_of': ['NamedThing']}}), 'name': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'name', 'domain_of': ['NamedThing']}}), 'ordinal': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Ordinal of the parcellation term set among other term sets within the context of the  associated parcellation terminology.', json_schema_extra={'linkml_meta': {'alias': 'ordinal', 'domain_of': ['ParcellationTermSet', 'ParcellationTerm']}}, metadata=[Ge(ge=0)]), 'part_of_parcellation_terminology': FieldInfo(annotation=str, required=True, description='Reference to the parcellation terminology for which the parcellation term set partitions.', json_schema_extra={'linkml_meta': {'alias': 'part_of_parcellation_terminology', 'any_of': [{'range': 'ParcellationTerminology'}, {'range': 'string'}], 'domain_of': ['ParcellationTermSet']}})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

name: str

ordinal: int | None

part_of_parcellation_terminology: str

class bkbit.models.anatomical_structure.ParcellationTerminology(*, id: str, name: str, description: str, category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationTerminology', 'AnS:ParcellationTerminology']] = ['AnS:ParcellationTerminology'], version: str, revision_of: str | None = None)

Bases: VersionedNamedThing

A parcellation terminology is a versioned release set of terms that can be used to label annotations in an atlas, providing human readability and context and allowing communication about brain locations and structural properties. Typically, a terminology is a set of descriptive anatomical terms following a specific naming convention and/or approach to organization scheme. The terminology may be a flat list of controlled vocabulary, a taxonomy and partonomy, or an ontology (ref: ILX:0777107, RRID:SCR_023499)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationTerminology', 'AnS:ParcellationTerminology']]

description: str

id: str

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'from_schema': 'https://w3id.org/my-org/anatomical-structure-schema', 'slot_usage': {'revision_of': {'any_of': [{'range': 'ParcellationTerminology'}, {'range': 'string'}], 'name': 'revision_of'}}})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'category': FieldInfo(annotation=List[Literal['https://w3id.org/my-org/anatomical-structure-schema/ParcellationTerminology', 'AnS:ParcellationTerminology']], required=False, default=['AnS:ParcellationTerminology'], json_schema_extra={'linkml_meta': {'alias': 'category', 'designates_type': True, 'domain_of': ['NamedThing'], 'is_class_field': True}}), 'description': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'description', 'domain_of': ['NamedThing']}}), 'id': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'id', 'domain_of': ['NamedThing']}}), 'name': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'name', 'domain_of': ['NamedThing']}}), 'revision_of': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, json_schema_extra={'linkml_meta': {'alias': 'revision_of', 'any_of': [{'range': 'ParcellationTerminology'}, {'range': 'string'}], 'domain_of': ['VersionedNamedThing']}}), 'version': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'version', 'domain_of': ['VersionedNamedThing']}})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

name: str

revision_of: str | None

version: str

class bkbit.models.anatomical_structure.VersionedNamedThing(*, id: str, name: str, description: str, category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/VersionedNamedThing', 'AnS:VersionedNamedThing']] = ['AnS:VersionedNamedThing'], version: str, revision_of: str | None = None)

Bases: NamedThing

Core base entity for Anatomical Structure schema representing an versioned named thing.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

category: List[Literal['https://w3id.org/my-org/anatomical-structure-schema/VersionedNamedThing', 'AnS:VersionedNamedThing']]

description: str

id: str

linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(root={'abstract': True, 'from_schema': 'https://w3id.org/my-org/anatomical-structure-core-schema'})

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'strict': False, 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'category': FieldInfo(annotation=List[Literal['https://w3id.org/my-org/anatomical-structure-schema/VersionedNamedThing', 'AnS:VersionedNamedThing']], required=False, default=['AnS:VersionedNamedThing'], json_schema_extra={'linkml_meta': {'alias': 'category', 'designates_type': True, 'domain_of': ['NamedThing'], 'is_class_field': True}}), 'description': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'description', 'domain_of': ['NamedThing']}}), 'id': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'id', 'domain_of': ['NamedThing']}}), 'name': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'name', 'domain_of': ['NamedThing']}}), 'revision_of': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, json_schema_extra={'linkml_meta': {'alias': 'revision_of', 'domain_of': ['VersionedNamedThing']}}), 'version': FieldInfo(annotation=str, required=True, json_schema_extra={'linkml_meta': {'alias': 'version', 'domain_of': ['VersionedNamedThing']}})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

name: str

revision_of: str | None

version: str